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Quantitative MR imaging in fracture dating—Initial results
Accepted Manuscript Title: Quantitative MR Imaging in Fracture Dating–Initial Results Author: Baron Katharina Neumayer Bernhard Widek Thomas Schick Fritz Scheicher Sylvia Hassler Eva Scheurer Eva PII: DOI: Reference:
S0379-0738(16)00039-6 http://dx.doi.org/doi:10.1016/j.forsciint.2016.01.020 FSI 8288
To appear in:
FSI
Received date: Revised date: Accepted date:
17-6-2015 13-10-2015 18-1-2016
Please cite this article as: B. Katharina, N. Bernhard, W. Thomas, S. Fritz, S. Sylvia, H. Eva, S. Eva, Quantitative MR Imaging in Fracture DatingndashInitial Results, Forensic Science International (2016), http://dx.doi.org/10.1016/j.forsciint.2016.01.020 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Quantitative MR Imaging in Fracture Dating – Initial Results
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Corresponding author: Katharina Baron Ludwig Boltzmann Institute for Clinical - Forensic Imaging Universitätsplatz 4/2; 8010 Graz, Austria
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0043 316 380 4353; [email protected]
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Quantitative MR Imaging in Fracture Dating – Initial Results
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Ludwig Boltzmann Institute for Clinical-Forensic Imaging (LBI-CFI), Graz, Austria
Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tübingen, Germany
Institute of Forensic Medicine, University of Basel - Health Department Basel, Switzerland
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Department of Radiology, Medical University of Graz, Austria
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Eva
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Baron Katharina , Neumayer Bernhard , Widek Thomas , Schick Fritz , Scheicher Sylvia , Hassler Eva , Scheurer
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Abstract For exact age determinations of bone fractures in a forensic context (e.g. in cases of child abuse)
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improved knowledge of the time course of the healing process and use of non-invasive modern imaging technology is of high importance. To date, fracture dating is based on radiographic
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methods by determining the callus status and thereby relying on an expert’s experience. As a novel approach, this study aims to investigate the applicability of magnetic resonance imaging (MRI) for
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bone fracture dating by systematically investigating time-resolved changes in quantitative MR characteristics after a fracture event. Prior to investigating fracture healing in children, adults were
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examined for this study in order to test the methodology for this application. Altogether, 31 MR examinations in 17 subjects (♀:11 ♂:6; median age 34±15 y, scanned 1 – 5 times over a period of
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up to 200 days after the fracture event), were performed on a clinical 3T MR scanner (TimTrio, Siemens AG, Germany). All subjects were treated conservatively for a fracture in either a long bone
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or in the collar bone. Both, qualitative and quantitative MR measurements were performed in all
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subjects. MR sequences for a quantitative measurement of relaxation times T1 and T2 in the fracture gap and musculature were applied. Maps of quantitative MR parameters T1, T2, and
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magnetisation transfer ratio (MTR) were calculated and evaluated by investigating changes over time in the fractured area by defined ROIs. Additionally, muscle areas were examined as reference regions to validate this approach. Quantitative evaluation of 23 MR data sets (12 test subjects, ♀: 7 ♂: 5) showed an initial peak in T1 values in the fractured area (T1=1895±607 ms), which decreased over time to a value of 1094±182 ms (200 days after the fracture event). T2 values also peaked for early-stage fractures (T2=115±80 ms) and decreased to 73±33 ms within 21 days after the fracture event. After that time point, no significant changes could be detected for T2. MTR remained constant at 35.5±8.0 % over time. The study shows that the quantitative assessment of T1 and T2 behaviour over time in the fractured region enable the generation of a novel model allowing for an objective age determination of a fracture.
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Page 3 of 3 Keywords: Forensic science; Fracture dating; Quantitative MRI; 3Tesla
1. Introduction In clinical forensic medicine different kinds of injuries have to be assessed whether and how they
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have been inflicted by a third party. In cases of inflicted fractures, the determination of the time of occurrence plays an important role as it can lead to an inclusion or exclusion of possible offenders
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as well as to the differentiation of multiple events. Therefore, the determination of a fracture’s age
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may concern cases regarding maltreatment of vulnerable persons, torture and abuses of adults and may be of importance in cases of insurance litigations. Additionally, the determination of the
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fracture’s age in alleged cases of child abuse is of crucial importance. According to Kogutt et al., fractures occur in up to 55 % of cases of child abuse [1], and 80 % of the investigated fractures of
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abused children occur in infants younger than 1.5 years [2]. Additionally, these children often present multiple fractures in different healing stages [3-5]. As children of this age cannot give information on the fracture event themselves, the determination of a fracture’s age is currently
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mainly based on the assessment of radiographs, according to a timetable of fracture healing phases
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[6, 7].
1.1.
Radiography in fracture healing
The bone healing process, which is consistently discussed in literature, starts with haemorrhage inflammation, followed by primary soft callus formation, callus mineralization, and finally bone remodelling. However, the time intervals of these phases are dependent on the age of an individual, as well as other physiological and external factors such as mobility or dietary habits [5, 8-10].
To date, radiographic imaging is routinely used for the examination of fractures in clinical medicine [11]. These radiographs provide a basis for the clinical diagnosis, therapeutic monitoring, and forensic assessment of fractures by displaying the fractured region, callus formation, and bone remodelling. However, the assessment of fractures in orthopaedic trauma literature lacks consensus about the definition of fracture healing regarding the specific time course. According to Prosser et al.
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Page 4 of 4 [7], estimations of the duration of the fracture healing process are rather based on experience than on actual evidence, and until now lack a scientific validation in clinical practice. A large amount of literature exists concerning the mechanical stimuli needed for a proper fracture healing ([12, 13] and references therein). However, only a few researchers describe fracture healing processes over the
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course of time, dating of inflicted fractures related to child abuse using radiographs and additional
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tissue and reliability of the evaluation of fracture healing [4, 22-25].
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validation by histology [14-21]. Still, radiographic imaging lacks information on surrounding soft
MRI in fracture healing
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Magnetic resonance imaging (MRI) allows the investigation of bone and surrounding soft tissue structures without any exposure to radiation by using magnetic fields and radiofrequency (RF)
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pulses which excite the protons in the tissues. As the excited protons relax back into equilibrium, a RF signal is emitted which is picked up by a receiver coil or antenna. The tissue contrast visible in
[26].
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MRI is defined by the sequence and characteristics of the RF pulses and the tissue characteristics
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Therefore, MRI techniques provide more information on the surrounding tissue, including the
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visibility of bone marrow, muscles, periosteum and fat as well as occult fractures [27, 28]. Nevertheless, due to the fact that cortical bone contains almost no free protons and has a very short T2 relaxation time, MR imaging has only sporadically been implemented in fracture dating and the diagnosis of child abuse [11]. Burger et al. [27] analysed signal intensity qualitatively in radius fractures over time and observed a decline of the signal in fracture areas in T1-weighted images, whereas signal intensity increased in T2-weighted images over time. In medical practice, quantitative MRI (measurements of the relaxation times T1 and T2, or the magnetization transfer ratio MTR), is already implemented in several diagnostic fields and can aid to evaluate specific diseases associated with tissue changes, e.g. neuromuscular diseases. Multiple studies examined lower limb muscles regarding their quantifiable changes in T1, T2, and MTR over time. In addition, follow up studies have been reported focusing on effects of exercise, body-weight or gender [29-31]. It was confirmed that MRI can represent a valuable method to detect metabolic, inflammatory, and
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Page 5 of 5 dystrophic changes in soft tissue (reviewed in [32])[33, 34]. Additionally, Lai et al. described changes in MRI signal intensities after analysing damages to the soft tissue and related degradation of haemoglobin to methaemoglobin [35]. Since the fracture healing phases are defined by tissue changes, a transition from one healing phase to another will most certainly involve a concomitant
Aims
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change of quantitative MR values.
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Quantitative MRI is expected to provide additional and more detailed information compared to the currently used method applied for fracture dating, i.e. radiography. In addition to being free of
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ionizing radiation, the assessment of quantitative features of tissue using MRI would enhance an objective evaluation of the age of fractures. This methodology may give the basis for a systematic
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approach of fracture dating, which can then be especially important in alleged cases of child abuse. Therefore, this study aims to apply quantitative MRI during fracture healing in adults as a first step to develop a model enabling the estimation of a fracture’s age by investigating time resolved
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changes in MR parameters. This includes as well the validation of the quantitative approach by
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literature.
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using MR relaxometry of muscles as reference values and comparison with values known from
2. Materials and Methods
The performed experiments were approved by the responsible ethical commission of the local university.
2.1.
Subjects and MRI examination schedule
A total of 17 test subjects (Table 1) with at least one conservatively treated fracture of a long bone or collar bone participated in this study (6 males and 11 females, median age 34±15 y; body mass index: 23±2.80). All subjects were older than 18 years, could provide exact information on the time the fracture occurred, and signed an informed written consent prior to being included in the study.
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Page 6 of 6 Each participant was scanned at least once, the maximum number of examinations being five within a time period of 190 days after the fracture event, resulting in a total of 31 MRI scans.
1
2
3
4
5
6
7
8
9
10
11
12
Sex
m
f
m
f
f
m
f
m
f
f
F
f
Fractured
MC
MT 5
W
MT
5
CB
MT
bone
5
1
W
CB
CR
CB
CB
R
1 Scan (daf)
5
29
22
3
15
7
7
6
7
9
14
nd
2
Scan daf)
55
35
84
78
91
112
th
108
th
190
4 Scan (daf) 5 Scan (daf) Total scans
2
1
5
1
1
3
1
1
15
16
17
m
f
m
f
F
W
18
15
36
MT 5
14 42
84
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36
rd
3 Scan (daf)
14
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13
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Patient
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Table 1: Description of the test subjects, fractured bone and the timeframes of scans after the primary fracture event
3
1
3
1
W
24
MT
PH
5 85
13
1
1
60 104
1
2
3
m: male / f: female / daf: days after fracture event / MT: Metatarsal bone / CB: Collar bone / W: Weber fracture / CR: Caput Radii / R: Radius / PH: Phalanx / yellow: images used for optimisation of MR protocol / red: excluded due to non-evaluable
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image properties
MRI protocol
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All measurements were performed on a clinical 3T MR whole-body scanner (TimTrio, Siemens AG,
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Erlangen, Germany). All morphological scans as well as the sequences for quantitative analyses
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were based on product sequences of the manufacturer, readily implementable on standard MRI systems with unmodified software.
Table 2: MRI protocol performed for all subjects at every examination #
Name
TA
TR
TE
IPR
SLT
BW
FoV
FA
1
T1w VIBE WE
2:37
9.47
4.9
0.5*0.5
1.5
300
150
10
2
PDw SFS SPACE
7:53
1,200
32
0.5*0.5
0.6
539
160
-
3
T2w TSE FS
4:26
4,000
76
0.6*0.4
2
182
140
150
4
T1w TSE
4:43
655
10
0.5*0.5
2
260
150
140
5
T1w FLASH3D
1:39
11
4.45
0.5*0.5
1.5
390
150
4
6
T1w FLASH3D
1:39
11
4.45
0.5*0.5
1.5
390
150
19
7
MSE (≥12 Echoes)
6:10
3,800
T10.6
1.0*1.0
1.5
250
128
180
8
T1w FLASH3D with MT pulse
1:57
26
4.27
0.5*0.5
1.5
390
150
8
9
T1w FLASH3D without MT pulse
1:57
26
4.27
0.5*0.5
1.5
390
150
8
2
TA: Acquisition time (m+s) TR: repetition time (ms); TE: echo time (ms), IPR: resolution (mm ); SLT: slice thickness (mm); BW: bandwidth (Hz/px); FoV: Field of View (mm); FA: flip/refocusing angle(°)
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Overall, a total of 9 MR sequences were applied after recording scout images for proper slice positioning, for the determination of both, qualitative (sequence 1 – 4 in Table 2) and quantitative
2.3.
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(sequences 5 – 9 in Table 2) parameters.
Data processing and analysis
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In total, 31 MR scans were anonymised and morphologically evaluated by a board certified
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radiologist with 4 years of experience in clinical radiology including MRI and 3 years of experience in forensic imaging without knowledge of the time point when datasets were recorded in the course
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of fracture healing. The morphological analysis included the determination of the fracture type as well as the description of the bone alignment in the fracture area in order to enable accurate
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evaluation of the fractured region. Five out of these 31 scans were used to optimize the MR protocol (Table 1, yellow). After the exclusion of 3 data sets due to non-evaluable image properties (Table 1, red), 23 data sets were evaluated quantitatively.
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Firstly, quantitative maps for visualization of the spatial distribution of relaxation times T1 and T2
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and the MTR were calculated using Matlab (R2014a, The Mathworks, Natick, MA, USA). Prior to the
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construction of quantitative maps, all data were noise reduced according to the method proposed by Gudbjartsson and Patz [36] regarding the reduction of bias in magnitude data. The longitudinal relaxation time T1 was determined using the DESPOT1 (driven equilibrium single pulse observation of T1) method proposed by Deoni et al. [37] and the data based on sequences 5 and 6 (Table 2). The transverse relaxation time T2 was derived from multi echo spin-echo data (MSE, sequence 7 in Table 2) by discarding the first echo and applying mono-exponential fitting to the remaining data. Maps for MTR were derived by calculating (1-[M1/M0])*100%, with M1 as the image data acquired after a preceding MT pulse (standard implementation of the pre-saturation scheme provided by the scanner) and M0 as the image without saturation (sequences 8 and 9 in Table 2).
Three regions of interest (ROIs) were defined in each of the 23 data sets, outlining cross-sectional areas of the fracture, specific muscles surrounding the fractured area, and the affected bones
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Page 8 of 8 (including bone marrow). Due to the differing locations of the fractures, muscles surrounding these fractures were measured as references: the brachioradialis (radius head fracture), pronator quadrates (distal radius fracture) and deltoideus (clavicular fracture) muscles in the upper extremities, and the flexor halluces brevis (metatarsal bone [MT] I fracture), flexor digiti minimi
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brevis (MT V fracture) and peronaeus brevis (fibula fracture) muscles in the lower extremities. These muscle values formed the basis for the validation of our approach (section 4.1); therefore,
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special attention was drawn to the measurement of healthy muscles, without any signs of damage.
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Bone regions in spatial proximity to the fracture were measured to provide values for intact bone. In each case the contamination of the ROIs (fracture gap, muscle, bone) by fascia or subcutaneous
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and intermuscular fat, bone haematoma, or bone fat was avoided. For data of subsequent acquisitions the ROIs were positioned on the slice that resembled most the one used for the
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previous acquisition. For muscle and bone, ROIs of similar size (in pixels) were defined. Since the fractured areas changed their size over time due to healing processes, the size of the
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corresponding ROIs varied as well; however, it was maximized for each analysis.
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Finally, the MR parameters of each region were defined by calculating the median values of T1, T2,
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and MTR within the ROIs of the quantitative maps. Figure 1 represents an example of a Weber B fracture of a 64 year old Caucasian male (height: 183 cm, weight: 85 kg) in two healing stages. The MR images (T1w FLASH3D sequence without preceding MT pulse, left side) show the ROI of the fracture (dashed line) and the numbers indicate the fibula, the peroneus longus muscle and the peroneus longus tendon. The quantitative maps (right side) formed the basis for the calculation of the relaxation time T1, indicated in red in the colour scale.
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Right side: corresponding quantitative T1 maps and the transferred ROIs (black dashed line). The colour scale illustrates increasing relaxation time T1 (from blue to red). Additionally, the median T1 values of the ROIs are highlighted in red with a black box.
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Figure 1: Left side: MR images of a Weber B fracture in a T1w FLASH3D sequence without preceding MT pulse 20 days (top) and 3.5 months (bottom) after the fracture event. The dashed lines (red) indicate the ROIs of the fracture. 1 – 3 specify the fibula, peroneus longus muscle, and peroneus longus tendon, respectively.
2.4.
Phase determination
The phases in the healing process of secondary fractures are referred to as the “fracture event”, “haemorrhage inflammation”, “primary soft callus formation”, “callus mineralization” and “callus remodelling” [5, 8-10, 38, 39]. In addition to the phases described in literature, interphases were introduced based on observed data to enable more detailed description of the time intervals of the healing process (Table 3). All fractures were grouped according to these phases.
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Page 10 of 10 Table 3: Phases of fracture healing Time
Processes
P0
day 0
Fracture event
P1
0 – 2 days after fracture event
Haemorrhage inflammation
P2
3 – 7 days after fracture event
Start of soft callus formation
P 2.5
8 – 21 days after fracture event
Soft callus formation
P3
22 – 42 days after fracture event
Soft callus formation finished
P 3.5
43 – 84 days after fracture event
Hard callus formation
P4
85 – 112 days after fracture event
Hard callus formation finished
P 4.5
113-139 days after fracture event
Start of remodelling process
P5
≥ 140 days after fracture event
Remodelling process
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Phase (P)
Statistical analysis
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Statistical analysis was performed using SPSS 22 (SPSS Chicago, IL, USA). The complete quantitative data analysis was done twice by a forensic anthropologist to assess intra-observer
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reliability, which was expressed by the intra-observer correlation coefficient between two repeated measurements of the fractures, muscles, and bones. T1, T2, and MTR values of six muscles, each
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surrounding one specific fractured region, were compared using ANOVA. Additionally, the calculated mean difference between muscle values of the upper and the lower extremities was
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tested using a Student’s t-test for 2 independent samples. Box plots of the different muscle
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compartments against the final T1, T2 and MTR values were used to visualize the results. Scatter plots of the bone measurements were used to show the results for one evaluation (measurement 1) plus one repetition 5 days later (measurement 2) and intra-observer reliability was analysed. Spearman’s rank correlation coefficient was calculated to measure the correlation between T1, T2 and MTR, and the age of the fracture over time. Additionally, in cases showing non-significant results as indicated by the correlation coefficient, a variance analysis over the different healing phases was implemented instead. Box plots of healing phases against T1 and T2 values, respectively, were used to visualize the results.
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Page 11 of 11 3. Results The morphological examination of the data demonstrated highly satisfying image quality, which is decisive for subsequent quantitative analysis. The image quality for all morphological as well as quantitative sequences was not disturbed by casts or bandages, resulting in MR images of
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evaluable quality and good anatomical coverage. Furthermore, all fractures included in the
Quantitative analysis of muscles
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3.1.
Figure 2: T1, T2 and MTR (magnetic transfer ratio, p. u. percentage units) measurements categorised for 6 different th th muscles. Horizontal bars indicate the median, the 25 and 75 percentiles. The most probable outlier is displayed with a star.
Individual group mean values of 6 different for
all
quantitative
MRI
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muscles
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quantitative analysis showed a regular healing process over the course of the study.
measurements are shown in Figure 2 and
differed significantly (ANOVA, p<0.05), while T2 and MTR did not. The differences muscles
of
the
upper
(T1:
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between
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Table 4. Between muscles, T1 values
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1,572±210 ms; T2: 52±5 ms; MTR: 47±3 %)
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and lower extremities (T1: 1,280±216 ms;
T2: 55±6 ms; MTR: 47±8 %) were significant (t-test: p<0.05) for T1, but not for T2 and MTR (p=0.4 and 0.95, respectively).
Table 4 presents the individual mean muscle values for T1, T2 and MTR including the related fracture region, as well as the number of individual measurements. The overall muscle values were 1,447±157 ms, 54±6 ms and 46±6 % for T1, T2 and MTR, respectively.
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Page 12 of 12 Table 4: T1, T2 and MTR mean values ± standard deviation for all measured muscles T2 (ms)
MTR (p.u.)
Fracture Region
N
M. brachioradialis
1,389 ± 338
53±10
52 ± 2
Radius head
3
M. pronator quadratus
1,609 ± 0
64 ± 0
45 ± 0
Distal radius
1
M. deltoideus
1,637 ± 81
51 ± 2
46 ± 2
Claviculae
9
M. flexor hallucis brevis
1,369 ± 45
52 ± 6
48 ± 1
MT I
3
M. flexor digiti minimi brevis
1,400 ± 262
60 ± 4
49 ± 9
MT V
M. peronaeus brevis
1,070 ± 56
52 ± 2
44 ± 10
Weber A, B, C
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Quantitative analysis of bones surrounding the fractured areas
The determination of the relaxation times
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Figure 3: Scatter plot describing intra-observer variation between two measurements of T1, T2, and MTR p.u. (percentage units)
in bone areas surrounding the fracture of
values of the bone.
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two independent evaluations did not lead
Further data evaluation dependent on the region
did
not
lead
to
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to reproducible results, shown in Figure 3.
anatomical
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T1 (ms)
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reproducible results either. The reason for
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this finding is mainly seen in spatially variable composition of bone marrow, with of
hematopoietic
cells
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fractions
and
adipocytes, dependent on the location and age of the subjects.
3.3.
Morphological and quantitative analysis of the fractured areas
The data of the fractured areas were grouped into eight clusters, in accordance with the age of the fractures at the time of the MR scan (Table 5). The clusters were defined in conformity with literature values regarding the different healing phases, and combined with our own phase determination, as described in Table 3 [5, 8-10, 38, 39]. No data sets for healing phases 1 and 4.5 were available.
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Page 13 of 13 The morphological evaluation by the board certified radiologist showed multiple combinations of fracture types and bone alignment, as summarized in Table 6. Figure 4 shows fracture values for T1 and T2 over time. These values are grouped according to the phases of fracture healing, as described in Table 3. Additionally, Table 7 shows the mean ± standard deviation of T1, T2, and
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MTR values in different healing phases. There was a significant negative correlation between T1 values and the healing phases (ρ=-0.46, p=0.003). Despite the variation of T2 in the early phases,
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after phase 3 (day 22) no significant changes were detectable (p=0.8). MTR values of the healing
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phases showed no significant differences (p=0.7), resulting in an overall mean of 35.5±8.0%.
Table 5: Data grouped by days after fracture occurrence 1
2
2.5
3
4
4.5
5
Days after fracture
0–2
3–7
8 – 21
22 – 42
3.5
43 – 84
85 – 112
113 – 139
≥140
Number of data sets
0
4
5
5
4
4
0
1
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an
Healing phase
Table 6: Quantity of fracture types and types of fracture dislocation (D.) in all evaluated data sets Number
Transversal fracture
4
Oblique fracture
13
Bending fracture
4
Comminuted fracture
5
Compressed fracture
2
Meissel fracture
3
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Fracture Type
Type of fracture dislocation
Number
D. ad latus (displaced)
14
D. ad longitudem (shortened)
20
D. cum distractione (emerged)
1
D. cum compressione (compressed)
3
D. ad axim (angled)
2
No dislocation/regular alignment
8
Table 7: Mean ± standard deviation of T1, T2 and MTR for the fractured regions of different healing phases mean ± standard deviation
Phase:
2 (days 3 – 7)
2.5 (days 8 – 21)
3 (days 22 – 42)
3.5 (days 43 – 84)
4 (days 85 – 112)
4.5 (days 113-139)
5 (≥140 days)
T1 (ms):
1,895 ± 607
1,694 ± 433
1,515 ± 409
1,516 ± 315
1,246 ± 79
-
1,094 ± 182
T2 (ms):
115 ± 80
73 ± 33
66 ± 9
59 ± 7
69 ± 12
-
79 ± 13
MTR (p.u.):
32 ± 5
32 ± 10
38 ± 4
39 ± 13
34 ± 7
-
31 ± 18
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Page 14 of 14 Figure 4: (a) and (b) Box plots of T1 and T2 measurements of fractures, clustered according to the different healing th
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phases as described in Table 3 and in literature. Horizontal bars indicate the median, the 25 and 75 percentiles. The minor outlier is displayed with an open dot. (c) Scatter plot of T1 values of different healing phases from female (black
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dots) and male (grey squares) subjects, including regression lines for data of female (black) and male (grey) subjects.
3.4.
Intra-observer reliability
Intra-observer reliability on the basis of double measurements of the ROIs in muscle, bone and fracture areas showed no statistically relevant differences (p<0.05) for T1, T2 and MRT in fracture and muscle regions, except for the bone measurements. Reproducible results were obtained for muscle and fracture regions.
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Page 15 of 15 4. Discussion In forensic examinations, especially in alleged cases of child abuse, an accurate, objective, and radiation-free method for accurate dating of injuries, particularly of fractures, is not available so far. Therefore, this study aimed to evaluate quantitative MRI as a potential tool for objective fracture
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dating. The MR protocols used in this study fulfilled three main requirements: Firstly, the protocols allowed for the acquisition of MR images with a satisfying image quality for morphological analysis.
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Secondly, the obtained image quality enabled quantitative analysis of the regions of interest based
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on the morphological assessment, which was validated by the comparison of acquired muscle values with literature. Finally, quantitative MRI data were successfully determined for fractured
Validation of the quantitative approach
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4.1.
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areas.
Quantitative MRI analysis of the muscles surrounding the fractured area was implemented to provide a reference and to validate the quantitative approach of this study. Hence, T1, T2, and MTR
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of the muscle were determined and compared to the values known from literature.
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Saab et al. [30] and Varghese et al. [31] could quantify exercise-induced changes in muscles via
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MR relaxometry. Therefore, it was assumed that the results regarding muscles of the upper and the lower extremities might slightly vary due to different muscle activity prior to the MR examinations. This assumption could be confirmed for T1, since significant differences of T1 in muscles between the upper and lower extremities were observed. Using the current approach, observed changes in MR characteristics due to varying muscle activity in different muscle compartments were found to be consistent with the literature. Following this confirmation, the MR protocols were used to characterise the lower limb muscles and ascertain their agreement with literature values (Table 8). Additional comparison of T1 from one specific muscle (peroneus) also revealed similar results to literature – Morrow et al. [29] reported T1 values of approximately 1,050 to 1,400 ms.
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Page 16 of 16 Table 8: Comparison of T1 and T2 values of muscles Comparison of quantitative muscle parameters Jordan et al. [40]
Kan et al. [41]
T1 (ms):
1,000 - 1,500
1,198.0 - 1,314.8
–
T2 (ms):
35 - 60
28.2 – 30.4
38 - 42
Anatomical region
lower limbs
lower limb
lower limbs
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Morrow et al. [29]
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Similar results could also be established for MTR. However, in contrast to relaxation times, MTR data are not considered as absolute values, since they depend on the chosen approach used for
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suppression of off-resonant spins and data recording. A deviation from the standard saturation scheme by varying pulse duration, pulse shape or off-resonance frequency may improve the
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observed tissue saturation. However, the application of the standard saturation allows for easy adaption of the method as well as reproducibility and comparison of MTR values.
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In conclusion, we demonstrate literature-consistent results for muscle compartments using the chosen MR sequences and post-processing strategies [29, 40, 41], and therefore successfully
4.2.
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validated the established MR protocols.
Bone marrow and bone variation
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The analysis of the bone surrounding the affected regions (including bone marrow) was conducted to obtain reference values, based on the assumption that fracture values will return to values of healthy bone over time. Reproduction of quantitative values for bones was not possible, most probably due to unclear and indefinable haematoma regions within the bone, as well as oedema within the medullary cavity. Additionally, according to our knowledge, no literature describes bone values for T1 and T2 quantitatively within a 3T MRI system in vivo. Therefore, the obtained bone values in this study lack an appropriate comparison.
4.3.
Timeline of fracture repair
Quantitative measurements of the fractured area shall provide objective information about the healing process of the bone and the surrounding tissue. Morphological assessments of the fractured
Page 17 of 28
Page 17 of 17 areas showed a high variation in fracture types included in this study. Nonetheless, a good reproducibility of T1, T2 and MTR fracture values over time could be demonstrated. The beginning of the healing phases was defined by a strong variation in T1 and T2 values, which might be explained by the different extent of haematoma formation, soft tissue injuries, and
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inflammatory responses between test subjects and fracture types. However, a negative correlation of T1 and T2 with time was observed. Furthermore, differences in T1 changes related to gender
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over time were discovered. The T1 values of fractured regions displayed a slower decay over time
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in females than in male (Figure 4c), potentially indicating the presence of gender-dependent influences in the healing process. However, these initial results are not significant at this point due
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to the reduced sample size. Furthermore, we hypothesize that differences in the decay of T1 are partly dependent on the fractured region, which will be evaluated with an increased sample size.
to alter within different fracture regions.
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Anyhow, the main trend of a steady decrease in T1 of the fractured region over time is not expected
A hyper-intense signal in T1-weighted images can potentially indicate an increased amount of
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proteins, laminar necrosis, and presence of paramagnetic substances like methaemoglobin [35].
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Methaemoglobin, appearing in sub-acute haematoma, stays visible on T1-weighted MR images for
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several months after haemorrhage [35]. Numerous physiological processes take place during fracture repair, including haemorrhage inflammation and therefore haemolysis, which cause methaemoglobin to be released into the haematoma cavity [42]. It is assumed that the release of methaemoglobin is responsible for the fast increase in T1 values during the first phase of fracture healing. Furthermore, it is supposed that remodelling and degradation of this paramagnetic substance induces the decline in T1 over time. If these results can be confirmed in studies with a higher number of subjects, changes in signal intensity of quantitative T1 sequences represent a valuable indicator for establishing a model for fracture healing. In addition to T1 fracture values, also T2 weighted sequences of fractures could be suitable for fracture dating, especially during the first phases of bone healing. Maillard et al. [43] described that inflammatory processes in juvenile dermatomyositis induce long T2 relaxation times (and therefore hyper-intensity in T2-weighted images). The same could be true for T2 values in fractures until
Page 18 of 28
Page 18 of 18 phase 2, where acute inflammation occurs and higher T2 values than in following phases were observed. During haemorrhage inflammation vasodilatation and a strengthened permeability of the vascular system occur, causing an increased movement of plasma fluids into the injured region [44]. It is assumed that in the early phases of fracture healing unbound water molecules of plasma fluid
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are predominant in the fractured area, which leads to an increase of T2. Subsequently, proteins and larger molecules are introduced into the injured area causing a steady decrease in T2. The
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inflammatory process in fractures declines after three weeks, when the oedema is reduced and the
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soft callus formation proceeds. At this time point, the values of T2 in the fractured area decreased to a constant level. In combination with T1 values, this may allow for a reliable model for more precise
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dating of fractures.
The magnetisation transfer ratio (MTR) appears stable over time and no significant differences
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between the phases were observed. Changes in MTR depend on the changes of the macromolecular content and amount of proteins within one region [45]. Since a change of the macromolecular content and proteins in the fractured region during the fracture healing phases is
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supported by the results so far.
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expected, a change in the MTR values would be assumed. However, this assumption is not
4.4.
Study limitations
The chosen MR protocols can be readily implemented in standard clinical examinations on a 3T MRI scanner. However, the examination time should be further shortened after adequate evaluation of the sequences with a higher number of subjects, especially with respect to the examination of children, who – with prolonged MR scanning times – might generate more moving artefacts when compared to adults. A higher number of subjects will be necessary also to validate the results and to allow for grouping the data according to sex, age, and fracture type.
5. Conclusion The determination of the time course of a fracture healing process is important for forensic medicine in view of being capable of dating fractures in living victims. The aim of this pilot study was to
Page 19 of 28
Page 19 of 19 investigate the applicability of quantitative MRI for bone fracture dating in adults by systematically investigating time-resolved changes in quantitative MR parameters after a fracture event. 31 data sets of 17 test subjects all treated conservatively for a fracture in either a long bone or clavicle were evaluated, resulting in 23 quantitative analyses of fractures.
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On the basis of these results, a methodological approach for the quantitative and observerindependent analysis of fractures over time is presented. Significant changes of T1 values
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depending on the healing state of the fracture were demonstrated. Additional assessment of T2
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appears to be especially valuable for monitoring the transition of haematoma degradation to soft callus formation. Despite the high variance of subjects in this study regarding age, gender, or type
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of fracture, the quantitative MR approach provides promising results as a first step towards objective
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estimation of the date of a fracture.
Conflict of Interest
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The authors of this manuscript declare that they have no conflict of interest.
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Page 20 of 20
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Kruger, K., et al., [The MR tomographic imaging of uncomplicated secondary fracture healing exemplified by the distal radius fracture]. Rofo, 1999. 170(3): p. 262-8.
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Neumayer, B., et al., Age determination of soft tissue hematomas. NMR Biomed, 2014. 27(11): p. 1397-402.
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Deoni, S.C., B.K. Rutt, and T.M. Peters, Rapid combined T1 and T2 mapping using gradient recalled acquisition in the steady state. Magn Reson Med, 2003. 49(3): p. 515-26.
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Einhorn, T.a., The science of fracture healing. J. Orthop. Trauma, 2005. 19(10 Suppl): p. S4--6.
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Gerstenfeld, L.C., et al., Fracture healing as a post-natal developmental process: molecular, spatial, and temporal aspects of its regulation. J. Cell. Biochem., 2003. 88(5): p. 873-84.
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Bradley, W.G., Jr., MR appearance of hemorrhage in the brain. Radiology, 1993. 189(1): p. 15-26.
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Maillard, S.M., et al., Quantitative assessment of MRI T2 relaxation time of thigh muscles in juvenile dermatomyositis. Rheumatology (Oxford), 2004. 43(5): p. 603-8.
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Lippert, H., Wundatlas: Kompendium der komplexen Wundbehandlung Vol. 3. 2014: Thieme.
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Sinclair, C.D.J., et al., Quantitative Magnetization Transfer in In Vivo Healthy Human Skeletal Muscle at 3 T. Magnetic Resonance in Medicine, 2010. 64(6): p. 1739-1748.
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36.
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S0379-0738(16)00039-6 http://dx.doi.org/doi:10.1016/j.forsciint.2016.01.020 FSI 8288
To appear in:
FSI
Received date: Revised date: Accepted date:
17-6-2015 13-10-2015 18-1-2016
Please cite this article as: B. Katharina, N. Bernhard, W. Thomas, S. Fritz, S. Sylvia, H. Eva, S. Eva, Quantitative MR Imaging in Fracture DatingndashInitial Results, Forensic Science International (2016), http://dx.doi.org/10.1016/j.forsciint.2016.01.020 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Page 1 of 1
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Quantitative MR Imaging in Fracture Dating – Initial Results
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Corresponding author: Katharina Baron Ludwig Boltzmann Institute for Clinical - Forensic Imaging Universitätsplatz 4/2; 8010 Graz, Austria
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0043 316 380 4353; [email protected]
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1
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Quantitative MR Imaging in Fracture Dating – Initial Results
1
3
1
Ludwig Boltzmann Institute for Clinical-Forensic Imaging (LBI-CFI), Graz, Austria
Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tübingen, Germany
Institute of Forensic Medicine, University of Basel - Health Department Basel, Switzerland
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4
Department of Radiology, Medical University of Graz, Austria
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Eva
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Baron Katharina , Neumayer Bernhard , Widek Thomas , Schick Fritz , Scheicher Sylvia , Hassler Eva , Scheurer
Page 2 of 28
Page 2 of 2
Abstract For exact age determinations of bone fractures in a forensic context (e.g. in cases of child abuse)
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improved knowledge of the time course of the healing process and use of non-invasive modern imaging technology is of high importance. To date, fracture dating is based on radiographic
cr
methods by determining the callus status and thereby relying on an expert’s experience. As a novel approach, this study aims to investigate the applicability of magnetic resonance imaging (MRI) for
us
bone fracture dating by systematically investigating time-resolved changes in quantitative MR characteristics after a fracture event. Prior to investigating fracture healing in children, adults were
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examined for this study in order to test the methodology for this application. Altogether, 31 MR examinations in 17 subjects (♀:11 ♂:6; median age 34±15 y, scanned 1 – 5 times over a period of
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up to 200 days after the fracture event), were performed on a clinical 3T MR scanner (TimTrio, Siemens AG, Germany). All subjects were treated conservatively for a fracture in either a long bone
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or in the collar bone. Both, qualitative and quantitative MR measurements were performed in all
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subjects. MR sequences for a quantitative measurement of relaxation times T1 and T2 in the fracture gap and musculature were applied. Maps of quantitative MR parameters T1, T2, and
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magnetisation transfer ratio (MTR) were calculated and evaluated by investigating changes over time in the fractured area by defined ROIs. Additionally, muscle areas were examined as reference regions to validate this approach. Quantitative evaluation of 23 MR data sets (12 test subjects, ♀: 7 ♂: 5) showed an initial peak in T1 values in the fractured area (T1=1895±607 ms), which decreased over time to a value of 1094±182 ms (200 days after the fracture event). T2 values also peaked for early-stage fractures (T2=115±80 ms) and decreased to 73±33 ms within 21 days after the fracture event. After that time point, no significant changes could be detected for T2. MTR remained constant at 35.5±8.0 % over time. The study shows that the quantitative assessment of T1 and T2 behaviour over time in the fractured region enable the generation of a novel model allowing for an objective age determination of a fracture.
Page 3 of 28
Page 3 of 3 Keywords: Forensic science; Fracture dating; Quantitative MRI; 3Tesla
1. Introduction In clinical forensic medicine different kinds of injuries have to be assessed whether and how they
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have been inflicted by a third party. In cases of inflicted fractures, the determination of the time of occurrence plays an important role as it can lead to an inclusion or exclusion of possible offenders
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as well as to the differentiation of multiple events. Therefore, the determination of a fracture’s age
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may concern cases regarding maltreatment of vulnerable persons, torture and abuses of adults and may be of importance in cases of insurance litigations. Additionally, the determination of the
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fracture’s age in alleged cases of child abuse is of crucial importance. According to Kogutt et al., fractures occur in up to 55 % of cases of child abuse [1], and 80 % of the investigated fractures of
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abused children occur in infants younger than 1.5 years [2]. Additionally, these children often present multiple fractures in different healing stages [3-5]. As children of this age cannot give information on the fracture event themselves, the determination of a fracture’s age is currently
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mainly based on the assessment of radiographs, according to a timetable of fracture healing phases
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[6, 7].
1.1.
Radiography in fracture healing
The bone healing process, which is consistently discussed in literature, starts with haemorrhage inflammation, followed by primary soft callus formation, callus mineralization, and finally bone remodelling. However, the time intervals of these phases are dependent on the age of an individual, as well as other physiological and external factors such as mobility or dietary habits [5, 8-10].
To date, radiographic imaging is routinely used for the examination of fractures in clinical medicine [11]. These radiographs provide a basis for the clinical diagnosis, therapeutic monitoring, and forensic assessment of fractures by displaying the fractured region, callus formation, and bone remodelling. However, the assessment of fractures in orthopaedic trauma literature lacks consensus about the definition of fracture healing regarding the specific time course. According to Prosser et al.
Page 4 of 28
Page 4 of 4 [7], estimations of the duration of the fracture healing process are rather based on experience than on actual evidence, and until now lack a scientific validation in clinical practice. A large amount of literature exists concerning the mechanical stimuli needed for a proper fracture healing ([12, 13] and references therein). However, only a few researchers describe fracture healing processes over the
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course of time, dating of inflicted fractures related to child abuse using radiographs and additional
1.2.
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tissue and reliability of the evaluation of fracture healing [4, 22-25].
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validation by histology [14-21]. Still, radiographic imaging lacks information on surrounding soft
MRI in fracture healing
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Magnetic resonance imaging (MRI) allows the investigation of bone and surrounding soft tissue structures without any exposure to radiation by using magnetic fields and radiofrequency (RF)
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pulses which excite the protons in the tissues. As the excited protons relax back into equilibrium, a RF signal is emitted which is picked up by a receiver coil or antenna. The tissue contrast visible in
[26].
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MRI is defined by the sequence and characteristics of the RF pulses and the tissue characteristics
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Therefore, MRI techniques provide more information on the surrounding tissue, including the
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visibility of bone marrow, muscles, periosteum and fat as well as occult fractures [27, 28]. Nevertheless, due to the fact that cortical bone contains almost no free protons and has a very short T2 relaxation time, MR imaging has only sporadically been implemented in fracture dating and the diagnosis of child abuse [11]. Burger et al. [27] analysed signal intensity qualitatively in radius fractures over time and observed a decline of the signal in fracture areas in T1-weighted images, whereas signal intensity increased in T2-weighted images over time. In medical practice, quantitative MRI (measurements of the relaxation times T1 and T2, or the magnetization transfer ratio MTR), is already implemented in several diagnostic fields and can aid to evaluate specific diseases associated with tissue changes, e.g. neuromuscular diseases. Multiple studies examined lower limb muscles regarding their quantifiable changes in T1, T2, and MTR over time. In addition, follow up studies have been reported focusing on effects of exercise, body-weight or gender [29-31]. It was confirmed that MRI can represent a valuable method to detect metabolic, inflammatory, and
Page 5 of 28
Page 5 of 5 dystrophic changes in soft tissue (reviewed in [32])[33, 34]. Additionally, Lai et al. described changes in MRI signal intensities after analysing damages to the soft tissue and related degradation of haemoglobin to methaemoglobin [35]. Since the fracture healing phases are defined by tissue changes, a transition from one healing phase to another will most certainly involve a concomitant
Aims
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1.2.
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change of quantitative MR values.
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Quantitative MRI is expected to provide additional and more detailed information compared to the currently used method applied for fracture dating, i.e. radiography. In addition to being free of
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ionizing radiation, the assessment of quantitative features of tissue using MRI would enhance an objective evaluation of the age of fractures. This methodology may give the basis for a systematic
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approach of fracture dating, which can then be especially important in alleged cases of child abuse. Therefore, this study aims to apply quantitative MRI during fracture healing in adults as a first step to develop a model enabling the estimation of a fracture’s age by investigating time resolved
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changes in MR parameters. This includes as well the validation of the quantitative approach by
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literature.
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using MR relaxometry of muscles as reference values and comparison with values known from
2. Materials and Methods
The performed experiments were approved by the responsible ethical commission of the local university.
2.1.
Subjects and MRI examination schedule
A total of 17 test subjects (Table 1) with at least one conservatively treated fracture of a long bone or collar bone participated in this study (6 males and 11 females, median age 34±15 y; body mass index: 23±2.80). All subjects were older than 18 years, could provide exact information on the time the fracture occurred, and signed an informed written consent prior to being included in the study.
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Page 6 of 6 Each participant was scanned at least once, the maximum number of examinations being five within a time period of 190 days after the fracture event, resulting in a total of 31 MRI scans.
1
2
3
4
5
6
7
8
9
10
11
12
Sex
m
f
m
f
f
m
f
m
f
f
F
f
Fractured
MC
MT 5
W
MT
5
CB
MT
bone
5
1
W
CB
CR
CB
CB
R
1 Scan (daf)
5
29
22
3
15
7
7
6
7
9
14
nd
2
Scan daf)
55
35
84
78
91
112
th
108
th
190
4 Scan (daf) 5 Scan (daf) Total scans
2
1
5
1
1
3
1
1
15
16
17
m
f
m
f
F
W
18
15
36
MT 5
14 42
84
an
36
rd
3 Scan (daf)
14
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st
13
cr
Patient
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Table 1: Description of the test subjects, fractured bone and the timeframes of scans after the primary fracture event
3
1
3
1
W
24
MT
PH
5 85
13
1
1
60 104
1
2
3
m: male / f: female / daf: days after fracture event / MT: Metatarsal bone / CB: Collar bone / W: Weber fracture / CR: Caput Radii / R: Radius / PH: Phalanx / yellow: images used for optimisation of MR protocol / red: excluded due to non-evaluable
2.2.
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image properties
MRI protocol
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All measurements were performed on a clinical 3T MR whole-body scanner (TimTrio, Siemens AG,
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Erlangen, Germany). All morphological scans as well as the sequences for quantitative analyses
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were based on product sequences of the manufacturer, readily implementable on standard MRI systems with unmodified software.
Table 2: MRI protocol performed for all subjects at every examination #
Name
TA
TR
TE
IPR
SLT
BW
FoV
FA
1
T1w VIBE WE
2:37
9.47
4.9
0.5*0.5
1.5
300
150
10
2
PDw SFS SPACE
7:53
1,200
32
0.5*0.5
0.6
539
160
-
3
T2w TSE FS
4:26
4,000
76
0.6*0.4
2
182
140
150
4
T1w TSE
4:43
655
10
0.5*0.5
2
260
150
140
5
T1w FLASH3D
1:39
11
4.45
0.5*0.5
1.5
390
150
4
6
T1w FLASH3D
1:39
11
4.45
0.5*0.5
1.5
390
150
19
7
MSE (≥12 Echoes)
6:10
3,800
T10.6
1.0*1.0
1.5
250
128
180
8
T1w FLASH3D with MT pulse
1:57
26
4.27
0.5*0.5
1.5
390
150
8
9
T1w FLASH3D without MT pulse
1:57
26
4.27
0.5*0.5
1.5
390
150
8
2
TA: Acquisition time (m+s) TR: repetition time (ms); TE: echo time (ms), IPR: resolution (mm ); SLT: slice thickness (mm); BW: bandwidth (Hz/px); FoV: Field of View (mm); FA: flip/refocusing angle(°)
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Overall, a total of 9 MR sequences were applied after recording scout images for proper slice positioning, for the determination of both, qualitative (sequence 1 – 4 in Table 2) and quantitative
2.3.
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(sequences 5 – 9 in Table 2) parameters.
Data processing and analysis
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In total, 31 MR scans were anonymised and morphologically evaluated by a board certified
us
radiologist with 4 years of experience in clinical radiology including MRI and 3 years of experience in forensic imaging without knowledge of the time point when datasets were recorded in the course
an
of fracture healing. The morphological analysis included the determination of the fracture type as well as the description of the bone alignment in the fracture area in order to enable accurate
M
evaluation of the fractured region. Five out of these 31 scans were used to optimize the MR protocol (Table 1, yellow). After the exclusion of 3 data sets due to non-evaluable image properties (Table 1, red), 23 data sets were evaluated quantitatively.
d
Firstly, quantitative maps for visualization of the spatial distribution of relaxation times T1 and T2
te
and the MTR were calculated using Matlab (R2014a, The Mathworks, Natick, MA, USA). Prior to the
Ac ce p
construction of quantitative maps, all data were noise reduced according to the method proposed by Gudbjartsson and Patz [36] regarding the reduction of bias in magnitude data. The longitudinal relaxation time T1 was determined using the DESPOT1 (driven equilibrium single pulse observation of T1) method proposed by Deoni et al. [37] and the data based on sequences 5 and 6 (Table 2). The transverse relaxation time T2 was derived from multi echo spin-echo data (MSE, sequence 7 in Table 2) by discarding the first echo and applying mono-exponential fitting to the remaining data. Maps for MTR were derived by calculating (1-[M1/M0])*100%, with M1 as the image data acquired after a preceding MT pulse (standard implementation of the pre-saturation scheme provided by the scanner) and M0 as the image without saturation (sequences 8 and 9 in Table 2).
Three regions of interest (ROIs) were defined in each of the 23 data sets, outlining cross-sectional areas of the fracture, specific muscles surrounding the fractured area, and the affected bones
Page 8 of 28
Page 8 of 8 (including bone marrow). Due to the differing locations of the fractures, muscles surrounding these fractures were measured as references: the brachioradialis (radius head fracture), pronator quadrates (distal radius fracture) and deltoideus (clavicular fracture) muscles in the upper extremities, and the flexor halluces brevis (metatarsal bone [MT] I fracture), flexor digiti minimi
ip t
brevis (MT V fracture) and peronaeus brevis (fibula fracture) muscles in the lower extremities. These muscle values formed the basis for the validation of our approach (section 4.1); therefore,
cr
special attention was drawn to the measurement of healthy muscles, without any signs of damage.
us
Bone regions in spatial proximity to the fracture were measured to provide values for intact bone. In each case the contamination of the ROIs (fracture gap, muscle, bone) by fascia or subcutaneous
an
and intermuscular fat, bone haematoma, or bone fat was avoided. For data of subsequent acquisitions the ROIs were positioned on the slice that resembled most the one used for the
M
previous acquisition. For muscle and bone, ROIs of similar size (in pixels) were defined. Since the fractured areas changed their size over time due to healing processes, the size of the
d
corresponding ROIs varied as well; however, it was maximized for each analysis.
te
Finally, the MR parameters of each region were defined by calculating the median values of T1, T2,
Ac ce p
and MTR within the ROIs of the quantitative maps. Figure 1 represents an example of a Weber B fracture of a 64 year old Caucasian male (height: 183 cm, weight: 85 kg) in two healing stages. The MR images (T1w FLASH3D sequence without preceding MT pulse, left side) show the ROI of the fracture (dashed line) and the numbers indicate the fibula, the peroneus longus muscle and the peroneus longus tendon. The quantitative maps (right side) formed the basis for the calculation of the relaxation time T1, indicated in red in the colour scale.
Page 9 of 28
Page 9 of 9
Right side: corresponding quantitative T1 maps and the transferred ROIs (black dashed line). The colour scale illustrates increasing relaxation time T1 (from blue to red). Additionally, the median T1 values of the ROIs are highlighted in red with a black box.
Ac ce p
te
d
M
an
us
cr
ip t
Figure 1: Left side: MR images of a Weber B fracture in a T1w FLASH3D sequence without preceding MT pulse 20 days (top) and 3.5 months (bottom) after the fracture event. The dashed lines (red) indicate the ROIs of the fracture. 1 – 3 specify the fibula, peroneus longus muscle, and peroneus longus tendon, respectively.
2.4.
Phase determination
The phases in the healing process of secondary fractures are referred to as the “fracture event”, “haemorrhage inflammation”, “primary soft callus formation”, “callus mineralization” and “callus remodelling” [5, 8-10, 38, 39]. In addition to the phases described in literature, interphases were introduced based on observed data to enable more detailed description of the time intervals of the healing process (Table 3). All fractures were grouped according to these phases.
Page 10 of 28
Page 10 of 10 Table 3: Phases of fracture healing Time
Processes
P0
day 0
Fracture event
P1
0 – 2 days after fracture event
Haemorrhage inflammation
P2
3 – 7 days after fracture event
Start of soft callus formation
P 2.5
8 – 21 days after fracture event
Soft callus formation
P3
22 – 42 days after fracture event
Soft callus formation finished
P 3.5
43 – 84 days after fracture event
Hard callus formation
P4
85 – 112 days after fracture event
Hard callus formation finished
P 4.5
113-139 days after fracture event
Start of remodelling process
P5
≥ 140 days after fracture event
Remodelling process
cr
us
2.5.
ip t
Phase (P)
Statistical analysis
an
Statistical analysis was performed using SPSS 22 (SPSS Chicago, IL, USA). The complete quantitative data analysis was done twice by a forensic anthropologist to assess intra-observer
M
reliability, which was expressed by the intra-observer correlation coefficient between two repeated measurements of the fractures, muscles, and bones. T1, T2, and MTR values of six muscles, each
d
surrounding one specific fractured region, were compared using ANOVA. Additionally, the calculated mean difference between muscle values of the upper and the lower extremities was
te
tested using a Student’s t-test for 2 independent samples. Box plots of the different muscle
Ac ce p
compartments against the final T1, T2 and MTR values were used to visualize the results. Scatter plots of the bone measurements were used to show the results for one evaluation (measurement 1) plus one repetition 5 days later (measurement 2) and intra-observer reliability was analysed. Spearman’s rank correlation coefficient was calculated to measure the correlation between T1, T2 and MTR, and the age of the fracture over time. Additionally, in cases showing non-significant results as indicated by the correlation coefficient, a variance analysis over the different healing phases was implemented instead. Box plots of healing phases against T1 and T2 values, respectively, were used to visualize the results.
Page 11 of 28
Page 11 of 11 3. Results The morphological examination of the data demonstrated highly satisfying image quality, which is decisive for subsequent quantitative analysis. The image quality for all morphological as well as quantitative sequences was not disturbed by casts or bandages, resulting in MR images of
ip t
evaluable quality and good anatomical coverage. Furthermore, all fractures included in the
Quantitative analysis of muscles
us
3.1.
Figure 2: T1, T2 and MTR (magnetic transfer ratio, p. u. percentage units) measurements categorised for 6 different th th muscles. Horizontal bars indicate the median, the 25 and 75 percentiles. The most probable outlier is displayed with a star.
Individual group mean values of 6 different for
all
quantitative
MRI
an
muscles
cr
quantitative analysis showed a regular healing process over the course of the study.
measurements are shown in Figure 2 and
differed significantly (ANOVA, p<0.05), while T2 and MTR did not. The differences muscles
of
the
upper
(T1:
d
between
M
Table 4. Between muscles, T1 values
te
1,572±210 ms; T2: 52±5 ms; MTR: 47±3 %)
Ac ce p
and lower extremities (T1: 1,280±216 ms;
T2: 55±6 ms; MTR: 47±8 %) were significant (t-test: p<0.05) for T1, but not for T2 and MTR (p=0.4 and 0.95, respectively).
Table 4 presents the individual mean muscle values for T1, T2 and MTR including the related fracture region, as well as the number of individual measurements. The overall muscle values were 1,447±157 ms, 54±6 ms and 46±6 % for T1, T2 and MTR, respectively.
Page 12 of 28
Page 12 of 12 Table 4: T1, T2 and MTR mean values ± standard deviation for all measured muscles T2 (ms)
MTR (p.u.)
Fracture Region
N
M. brachioradialis
1,389 ± 338
53±10
52 ± 2
Radius head
3
M. pronator quadratus
1,609 ± 0
64 ± 0
45 ± 0
Distal radius
1
M. deltoideus
1,637 ± 81
51 ± 2
46 ± 2
Claviculae
9
M. flexor hallucis brevis
1,369 ± 45
52 ± 6
48 ± 1
MT I
3
M. flexor digiti minimi brevis
1,400 ± 262
60 ± 4
49 ± 9
MT V
M. peronaeus brevis
1,070 ± 56
52 ± 2
44 ± 10
Weber A, B, C
4
Quantitative analysis of bones surrounding the fractured areas
The determination of the relaxation times
us
Figure 3: Scatter plot describing intra-observer variation between two measurements of T1, T2, and MTR p.u. (percentage units)
in bone areas surrounding the fracture of
values of the bone.
an
two independent evaluations did not lead
Further data evaluation dependent on the region
did
not
lead
to
M
to reproducible results, shown in Figure 3.
anatomical
3
cr
3.2.
ip t
T1 (ms)
d
reproducible results either. The reason for
te
this finding is mainly seen in spatially variable composition of bone marrow, with of
hematopoietic
cells
Ac ce p
fractions
and
adipocytes, dependent on the location and age of the subjects.
3.3.
Morphological and quantitative analysis of the fractured areas
The data of the fractured areas were grouped into eight clusters, in accordance with the age of the fractures at the time of the MR scan (Table 5). The clusters were defined in conformity with literature values regarding the different healing phases, and combined with our own phase determination, as described in Table 3 [5, 8-10, 38, 39]. No data sets for healing phases 1 and 4.5 were available.
Page 13 of 28
Page 13 of 13 The morphological evaluation by the board certified radiologist showed multiple combinations of fracture types and bone alignment, as summarized in Table 6. Figure 4 shows fracture values for T1 and T2 over time. These values are grouped according to the phases of fracture healing, as described in Table 3. Additionally, Table 7 shows the mean ± standard deviation of T1, T2, and
ip t
MTR values in different healing phases. There was a significant negative correlation between T1 values and the healing phases (ρ=-0.46, p=0.003). Despite the variation of T2 in the early phases,
cr
after phase 3 (day 22) no significant changes were detectable (p=0.8). MTR values of the healing
us
phases showed no significant differences (p=0.7), resulting in an overall mean of 35.5±8.0%.
Table 5: Data grouped by days after fracture occurrence 1
2
2.5
3
4
4.5
5
Days after fracture
0–2
3–7
8 – 21
22 – 42
3.5
43 – 84
85 – 112
113 – 139
≥140
Number of data sets
0
4
5
5
4
4
0
1
M
an
Healing phase
Table 6: Quantity of fracture types and types of fracture dislocation (D.) in all evaluated data sets Number
Transversal fracture
4
Oblique fracture
13
Bending fracture
4
Comminuted fracture
5
Compressed fracture
2
Meissel fracture
3
Ac ce p
te
d
Fracture Type
Type of fracture dislocation
Number
D. ad latus (displaced)
14
D. ad longitudem (shortened)
20
D. cum distractione (emerged)
1
D. cum compressione (compressed)
3
D. ad axim (angled)
2
No dislocation/regular alignment
8
Table 7: Mean ± standard deviation of T1, T2 and MTR for the fractured regions of different healing phases mean ± standard deviation
Phase:
2 (days 3 – 7)
2.5 (days 8 – 21)
3 (days 22 – 42)
3.5 (days 43 – 84)
4 (days 85 – 112)
4.5 (days 113-139)
5 (≥140 days)
T1 (ms):
1,895 ± 607
1,694 ± 433
1,515 ± 409
1,516 ± 315
1,246 ± 79
-
1,094 ± 182
T2 (ms):
115 ± 80
73 ± 33
66 ± 9
59 ± 7
69 ± 12
-
79 ± 13
MTR (p.u.):
32 ± 5
32 ± 10
38 ± 4
39 ± 13
34 ± 7
-
31 ± 18
Page 14 of 28
Page 14 of 14 Figure 4: (a) and (b) Box plots of T1 and T2 measurements of fractures, clustered according to the different healing th
th
phases as described in Table 3 and in literature. Horizontal bars indicate the median, the 25 and 75 percentiles. The minor outlier is displayed with an open dot. (c) Scatter plot of T1 values of different healing phases from female (black
Ac ce p
te
d
M
an
us
cr
ip t
dots) and male (grey squares) subjects, including regression lines for data of female (black) and male (grey) subjects.
3.4.
Intra-observer reliability
Intra-observer reliability on the basis of double measurements of the ROIs in muscle, bone and fracture areas showed no statistically relevant differences (p<0.05) for T1, T2 and MRT in fracture and muscle regions, except for the bone measurements. Reproducible results were obtained for muscle and fracture regions.
Page 15 of 28
Page 15 of 15 4. Discussion In forensic examinations, especially in alleged cases of child abuse, an accurate, objective, and radiation-free method for accurate dating of injuries, particularly of fractures, is not available so far. Therefore, this study aimed to evaluate quantitative MRI as a potential tool for objective fracture
ip t
dating. The MR protocols used in this study fulfilled three main requirements: Firstly, the protocols allowed for the acquisition of MR images with a satisfying image quality for morphological analysis.
cr
Secondly, the obtained image quality enabled quantitative analysis of the regions of interest based
us
on the morphological assessment, which was validated by the comparison of acquired muscle values with literature. Finally, quantitative MRI data were successfully determined for fractured
Validation of the quantitative approach
M
4.1.
an
areas.
Quantitative MRI analysis of the muscles surrounding the fractured area was implemented to provide a reference and to validate the quantitative approach of this study. Hence, T1, T2, and MTR
d
of the muscle were determined and compared to the values known from literature.
te
Saab et al. [30] and Varghese et al. [31] could quantify exercise-induced changes in muscles via
Ac ce p
MR relaxometry. Therefore, it was assumed that the results regarding muscles of the upper and the lower extremities might slightly vary due to different muscle activity prior to the MR examinations. This assumption could be confirmed for T1, since significant differences of T1 in muscles between the upper and lower extremities were observed. Using the current approach, observed changes in MR characteristics due to varying muscle activity in different muscle compartments were found to be consistent with the literature. Following this confirmation, the MR protocols were used to characterise the lower limb muscles and ascertain their agreement with literature values (Table 8). Additional comparison of T1 from one specific muscle (peroneus) also revealed similar results to literature – Morrow et al. [29] reported T1 values of approximately 1,050 to 1,400 ms.
Page 16 of 28
Page 16 of 16 Table 8: Comparison of T1 and T2 values of muscles Comparison of quantitative muscle parameters Jordan et al. [40]
Kan et al. [41]
T1 (ms):
1,000 - 1,500
1,198.0 - 1,314.8
–
T2 (ms):
35 - 60
28.2 – 30.4
38 - 42
Anatomical region
lower limbs
lower limb
lower limbs
ip t
Morrow et al. [29]
cr
Similar results could also be established for MTR. However, in contrast to relaxation times, MTR data are not considered as absolute values, since they depend on the chosen approach used for
us
suppression of off-resonant spins and data recording. A deviation from the standard saturation scheme by varying pulse duration, pulse shape or off-resonance frequency may improve the
an
observed tissue saturation. However, the application of the standard saturation allows for easy adaption of the method as well as reproducibility and comparison of MTR values.
M
In conclusion, we demonstrate literature-consistent results for muscle compartments using the chosen MR sequences and post-processing strategies [29, 40, 41], and therefore successfully
4.2.
te
d
validated the established MR protocols.
Bone marrow and bone variation
Ac ce p
The analysis of the bone surrounding the affected regions (including bone marrow) was conducted to obtain reference values, based on the assumption that fracture values will return to values of healthy bone over time. Reproduction of quantitative values for bones was not possible, most probably due to unclear and indefinable haematoma regions within the bone, as well as oedema within the medullary cavity. Additionally, according to our knowledge, no literature describes bone values for T1 and T2 quantitatively within a 3T MRI system in vivo. Therefore, the obtained bone values in this study lack an appropriate comparison.
4.3.
Timeline of fracture repair
Quantitative measurements of the fractured area shall provide objective information about the healing process of the bone and the surrounding tissue. Morphological assessments of the fractured
Page 17 of 28
Page 17 of 17 areas showed a high variation in fracture types included in this study. Nonetheless, a good reproducibility of T1, T2 and MTR fracture values over time could be demonstrated. The beginning of the healing phases was defined by a strong variation in T1 and T2 values, which might be explained by the different extent of haematoma formation, soft tissue injuries, and
ip t
inflammatory responses between test subjects and fracture types. However, a negative correlation of T1 and T2 with time was observed. Furthermore, differences in T1 changes related to gender
cr
over time were discovered. The T1 values of fractured regions displayed a slower decay over time
us
in females than in male (Figure 4c), potentially indicating the presence of gender-dependent influences in the healing process. However, these initial results are not significant at this point due
an
to the reduced sample size. Furthermore, we hypothesize that differences in the decay of T1 are partly dependent on the fractured region, which will be evaluated with an increased sample size.
to alter within different fracture regions.
M
Anyhow, the main trend of a steady decrease in T1 of the fractured region over time is not expected
A hyper-intense signal in T1-weighted images can potentially indicate an increased amount of
d
proteins, laminar necrosis, and presence of paramagnetic substances like methaemoglobin [35].
te
Methaemoglobin, appearing in sub-acute haematoma, stays visible on T1-weighted MR images for
Ac ce p
several months after haemorrhage [35]. Numerous physiological processes take place during fracture repair, including haemorrhage inflammation and therefore haemolysis, which cause methaemoglobin to be released into the haematoma cavity [42]. It is assumed that the release of methaemoglobin is responsible for the fast increase in T1 values during the first phase of fracture healing. Furthermore, it is supposed that remodelling and degradation of this paramagnetic substance induces the decline in T1 over time. If these results can be confirmed in studies with a higher number of subjects, changes in signal intensity of quantitative T1 sequences represent a valuable indicator for establishing a model for fracture healing. In addition to T1 fracture values, also T2 weighted sequences of fractures could be suitable for fracture dating, especially during the first phases of bone healing. Maillard et al. [43] described that inflammatory processes in juvenile dermatomyositis induce long T2 relaxation times (and therefore hyper-intensity in T2-weighted images). The same could be true for T2 values in fractures until
Page 18 of 28
Page 18 of 18 phase 2, where acute inflammation occurs and higher T2 values than in following phases were observed. During haemorrhage inflammation vasodilatation and a strengthened permeability of the vascular system occur, causing an increased movement of plasma fluids into the injured region [44]. It is assumed that in the early phases of fracture healing unbound water molecules of plasma fluid
ip t
are predominant in the fractured area, which leads to an increase of T2. Subsequently, proteins and larger molecules are introduced into the injured area causing a steady decrease in T2. The
cr
inflammatory process in fractures declines after three weeks, when the oedema is reduced and the
us
soft callus formation proceeds. At this time point, the values of T2 in the fractured area decreased to a constant level. In combination with T1 values, this may allow for a reliable model for more precise
an
dating of fractures.
The magnetisation transfer ratio (MTR) appears stable over time and no significant differences
M
between the phases were observed. Changes in MTR depend on the changes of the macromolecular content and amount of proteins within one region [45]. Since a change of the macromolecular content and proteins in the fractured region during the fracture healing phases is
Ac ce p
te
supported by the results so far.
d
expected, a change in the MTR values would be assumed. However, this assumption is not
4.4.
Study limitations
The chosen MR protocols can be readily implemented in standard clinical examinations on a 3T MRI scanner. However, the examination time should be further shortened after adequate evaluation of the sequences with a higher number of subjects, especially with respect to the examination of children, who – with prolonged MR scanning times – might generate more moving artefacts when compared to adults. A higher number of subjects will be necessary also to validate the results and to allow for grouping the data according to sex, age, and fracture type.
5. Conclusion The determination of the time course of a fracture healing process is important for forensic medicine in view of being capable of dating fractures in living victims. The aim of this pilot study was to
Page 19 of 28
Page 19 of 19 investigate the applicability of quantitative MRI for bone fracture dating in adults by systematically investigating time-resolved changes in quantitative MR parameters after a fracture event. 31 data sets of 17 test subjects all treated conservatively for a fracture in either a long bone or clavicle were evaluated, resulting in 23 quantitative analyses of fractures.
ip t
On the basis of these results, a methodological approach for the quantitative and observerindependent analysis of fractures over time is presented. Significant changes of T1 values
cr
depending on the healing state of the fracture were demonstrated. Additional assessment of T2
us
appears to be especially valuable for monitoring the transition of haematoma degradation to soft callus formation. Despite the high variance of subjects in this study regarding age, gender, or type
an
of fracture, the quantitative MR approach provides promising results as a first step towards objective
M
estimation of the date of a fracture.
Conflict of Interest
Ac ce p
te
d
The authors of this manuscript declare that they have no conflict of interest.
Page 20 of 28
Page 20 of 20
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