Diffusion-weighted imaging for the follow-up of patients after matrix-associated autologous chondrocyte transplantation

European Journal of Radiology 73 (2010) 622–628

Contents lists available at ScienceDirect

European Journal of Radiology journal homepage: www.elsevier.com/locate/ejrad

Diffusion-weighted imaging for the follow-up of patients after matrix-associated autologous chondrocyte transplantation Klaus M. Friedrich a,1 , Tallal C. Mamisch b,∗ , Christina Plank a,1 , Georg Langs c,1 , Stefan Marlovits d,2 , Erich Salomonowitz e,3 , Siegfried Trattnig a,4 , Götz Welsch a,4 a

Medical University Vienna, Department of Radiology, MR Center of Excellence, Lazarettgasse 14, A-1090 Vienna, Austria Department of Orthopaedic Surgery, Inselspital, University Bern Freiburgstrasse, 3010 Bern, Switzerland Medical University Vienna, Center for Computational Image Analysis in Radiology, Währinger Gürtel 18-20, A-1090 Vienna, Austria d Medical University Vienna, Department of Trauma Surgery, Währinger Gürtel 18-20, A-1090 Vienna, Austria e Landesklinikum St. Pölten, Department of Radiology, Probst-Führer-Straße 4, A-3100 St. Pölten, Austria b c

a r t i c l e

i n f o

Article history: Received 20 July 2008 Received in revised form 16 November 2008 Accepted 22 December 2008 Keywords: Magnetic resonance imaging Articular cartilage Diffusion-weighted MRI Transplantation

a b s t r a c t Objective: To evaluate the use of diffusion-weighted imaging (DWI) for the assessment of cartilage maturation in patients after matrix-associated autologous chondrocyte transplantation (MACT). Materials and methods: Fifteen patients after MACT were examined by 3.0-T magnetic-resonancetomography; the examination was up to 13 month after surgery in group 1, and later than 13 month after surgery in group 2. Both groups had a follow-up one-year later. DWI was acquired using a steadystate gradient-echo sequence. Mean values of the diffusion quotients of regions of interest within cartilage repair tissue and of reference regions were assessed. Each region-of-interest was subdivided into a deep, and a superficial area. Results: Mean diffusion quotients of cartilage repair tissues were 1.44 (baseline), and 1.44 (follow-up). Mean diffusion quotients of reference tissues were 1.29 (baseline) and 1.28 (follow-up). At the follow-up diffusion quotients of cartilage repair tissue were significantly higher than those of reference cartilage. In group 1 the diffusion quotients were significantly lower at the follow-up (1.45 versus 1.65); in group 2 no statistically significant differences between follow-up (1.39) and baseline (1.41) were found. Reference cartilages and cartilage repair tissues of group 2 showed a decrease of diffusion quotients from the deep to the superficial area being stable at the follow-up. In group 1 initially a significant increase (1.49 versus 1.78) of the diffusion quotients from deep to superficial area of the cartilage repair tissue was found changing into a decrease (1.65 versus 1.52) at the follow-up. Conclusions: DWI detected changes of diffusion within cartilage repair tissue that may reflect cartilage maturation. Changes in diffusity occurred up to two years after surgery and were stable later. Zonal variations within cartilage could be measured. © 2009 Elsevier Ireland Ltd. All rights reserved.

1. Introduction

∗ Corresponding author. Tel.: +41 316322222; fax: +41 316323600. E-mail addresses: [email protected] (K.M. Friedrich), [email protected] (T.C. Mamisch), [email protected] (C. Plank), [email protected] (G. Langs), [email protected] (S. Marlovits), [email protected] (E. Salomonowitz), [email protected] (S. Trattnig), [email protected] (G. Welsch). 1 Tel.: +43 1 404004818; fax: +43 1 404004898. 2 Tel.: +43 1 404005619; fax: +43 1 404005939. 3 Tel.: +43 274230018006; fax: +43 274230018019. 4 Tel.: +43 1 404001771; fax: +43 1 404007631. 0720-048X/$ – see front matter © 2009 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ejrad.2008.12.017

Autologous chondrocyte implantation (ACI) is one of the most common therapies for treatment of cartilage defects in young patients. Matrix-associated ACI (MACI) [1] is a further modification of the ACI without any periosteal cover, which uses biomaterials as cell carriers [2–9]. Clinicians demand diagnostic techniques that can help to assess the long-term efficacy of the MACI procedure, and help to improve rehabilitation programs by providing proper recommendations for the resumption of daily activities. Clinical scores and arthroscopic biopsies have been used for follow-up evaluation of cartilage remodelling after surgery, although clinical scores suffer from subjectivity. Arthroscopic biopsies provide objective information by histological work-up, but are

K.M. Friedrich et al. / European Journal of Radiology 73 (2010) 622–628

invasive procedures [10,11]. Magnetic resonance imaging (MRI) is the method of choice for longitudinal follow-up, as it allows a non-invasive objective evaluation determining morphological and biochemical parameters [1,10–15]. There are several modern MRI techniques that can visualize ultra-structural components and reveal the biochemical composition of cartilage. T1 mapping with delayed Gadolinium Enhanced Magnetic Resonance Imaging of Cartilage (dGEMRIC), for example, reflects the glycosaminoglycans (GAG) content of cartilage, whereas T2 mapping provides indirect information about water content, orientation and concentration of collagen within cartilage [16–26]. Moreover, imaging of cartilage lesions has improved significantly due higher magnetic field strength scanners (3.0 T), superior gradient strengths, and sophisticated coils resulting in higher signal-to-noise ratio (SNR) and better time resolution [12,27,28]. In addition, imaging at 3T provides higher resolution and greater sensitivity [29]. Diffusion-weighted imaging (DWI) is an alternative to the above-mentioned MR techniques for grading cartilage [22,30–32]. It analyzes a biologic tissue at a microscopic level. The principle of DWI is to exploit the translational motion of water protons in biologic tissues, which is caused by the Brownian motion [33]. On diffusion-weighted MRI, translational motion causes phase dispersion of excited water protons, which subsequently leads to a signal loss on DWI. The translational motion of water protons is related to the amount of diffusion hindering obstacles present. The aim of this study was to evaluate the use of DWI for the assessment of cartilage maturation in patients after matrixassociated autologous chondrocyte transplantation (MACT). 2. Materials and methods 2.1. Study population Institutional Review Board approval and written, informed consent to collect data on the study population were obtained. Fifteen patients (2 females, 13 males; mean age, 37.8 years; age range, 21–54 years) who had undergone MACT of the knee joint were examined. The grafts were located on the medial femoral condyle in 12 patients, and on the lateral femoral condyle in 3 patients. All transplants were located within the weight bearing aspect of the femoral condyle. The mean size of the cartilage defect was 5.8 cm2 (range: 2.6–12.4 cm2 ). A hyaluronan-based scaffold was used (Hyalograft® C, Fidia Advanced Biomaterials, Abone Terme, Italy). A standardized postoperative rehabilitation protocol consisting of eight weeks of non-weight bearing was uniformly employed in all patients. All patients underwent the same postoperative imag-

623

ing protocol. The baseline MR examination was 3–13 month after surgery in 6 patients (group 1; mean age 37.0), and 19–42 month after surgery in 9 patients (group 2; mean age 38.3). Both groups had a follow-up MR examination one-year later. These time intervals were chosen in order to further evaluate the characteristics of cartilage maturation within the transplant [34]. 2.2. Image acquisition All MR examinations were performed on a 3.0 T MR scanner (Magnetom Trio, Siemens Medical Solutions Erlangen, Germany) using an eight-channel multi-element (phased array) knee coil (Invivo, Gainesville, FL, USA). For DWI, a three-dimensional, balanced, steady-state gradient-echo pulse sequence with diffusion weighting (3D-DW PSIF) (reversed FISP = Fast Imaging with SteadyState Precession) was used. Imaging parameters were as follows: TR = 16.3 ms; TE = 6.1 ms; flip angle = 30◦ ; FoV 170 mm × 170 mm; matrix size 256 × 256; and voxel size = 0.6 mm × 0.6 mm × 1.5 mm). In order to allow a semi-quantitative assessment of diffusional behavior in the cartilage, the diffusion sequence protocol consisted of two separate, but immediately consecutive, measurements using no (0), and 75 mT ms m−1 monopolar diffusion gradient moments for DWI and otherwise identical imaging parameters. Assuming tissue relaxation times do not significantly change in between two immediately consecutive measurements, the influence of tissue relaxation on such consecutive measurements is negligible. Additionally, a three-dimensional double echo steady-state (3DDESS) sequence (TR = 15.1 ms, TE = 5.11 ms, flip angle 40◦ , NEX = 2, FOV = 150 mm × 150 mm, voxel size 0.6 mm × 0.6 mm × 0.6 mm) was used for the morphological evaluation. After at least half an hour of rest to avoid any changes within diffusion values due to different weight bearing prior to MRI, the patients were carefully positioned and the knee was tightly fixed with fitting cushions to prevent any motion during the measurements. 2.3. Data analysis The morphological condition after MACT, using the DESS sequence, was analyzed by one musculoskeletal radiologist and one orthopedic surgeon in consensus, using the magnetic resonance observation of cartilage repair tissue (MOCART) scoring system [35]. This reliable point scoring system was designed to systematically record the constitution of the area of cartilage repair and surrounding tissues [36,37]. Fig. 1 shows examples of the DESS images used for the morphological evaluation of a cartilage transplant in a patient after MACT at the baseline, Fig. 2 the same patient at the one-year follow-up MR scan.

Fig. 1. Morphologic 3D isotropic double echo steady-state (DESS) sequence with sagittal (a), coronal (b), and axial (c) reconstruction in a 24-year-old patient six months after MACT surgery due to osteochondritis dissecans. Arrows mark the cartilage repair area.

624

K.M. Friedrich et al. / European Journal of Radiology 73 (2010) 622–628

Fig. 2. Morphologic 3D isotropic double echo steady-state (DESS) sequence with sagittal (a), coronal (b), and axial (c) reconstruction in the same patient as in Fig. 1, at the one-year follow-up 18 months after MACT surgery. Arrows mark the cartilage repair area.

The DESS sequence was also used to localize the areas of cartilage repair on three consecutive slices. These slices were selected for further analysis on the PSIF images. The surgical reports and drawings were also consulted to confirm the position of the implants. Regions of interest were drawn semi-automatically by software that was implemented in Matlab (Version 7.4.0.287, R2007a, The MathWorks Inc., Natick, MA, USA), which runs on standard personal computers. Two radiologists in consensus interactively delineated the area of cartilage repair and an area of healthy reference cartilage in each of the three selected consecutive slices. The software then automatically subdivided the areas of cartilage repair into three parts of equal length, which resulted in a total of nine regions of interest (ROI) for cartilage repair tissue. In addition, each of the nine ROIs was automatically subdivided into a superficial and a deep zone by the software. The selected healthy reference cartilage area was also subdivided into a superficial and a deep zone. Thus, the software generated 18 ROIs for cartilage repair tissue and 6 ROIs for reference tissue on the PSIF images without a diffusion gradient, and then transferred those ROIs onto the PSIF with a diffusion gradient of 75 mT ms m−1 . The mean signal intensity within each ROI was calculated by the software. Diffusion quotients were calculated by dividing the mean signal intensities within the ROIs on the PSIF images with and without a diffusion gradient. Mean values of the diffusion quotients of the ROIs for cartilage repair tissue and healthy reference cartilage were assessed. Fig. 3 shows one exemplary image from one MACT patient for the semi-automatic ROI evaluation using the abovementioned software. Figs. 4 and 5 demonstrate one PSIF image without a diffusion gradient and one PSIF image with a diffusion gradient of 75 mT ms m−1 . Fig. 6 displays fused diffusion maps of the baseline and the one-year follow-up scan of a patient after MACT.

The diffusion quotients were used to compare the microstructure of the cartilage repair areas of the patients in group 1 with the microstructure of the cartilage repair areas of the patients in group 2. In addition, both groups were compared with the healthy reference cartilage. Statistical tests were used to perform the data analyses. Quantitative evaluation was done by analyses of variance using a three-way ANOVA with random factors, considering the fact of different measurements within each patient. For the trend, seen as possible difference, between the cartilage layers, a three-way analysis of variance with random effects with two repeated measures factors was performed. SPSS version 15.0 (SPSS Institute, Chicago, IL, USA) for Windows (Microsoft, Redmond, WA, USA) was used. Differences between cartilage repair regions and normal hyaline cartilage sites with a p-value less than 0.05 were considered statistically significant.

3. Results In general for all patients, the diffusion quotients (mean ± standard deviation (SD)) of the transplants (1.45 ± 0.24) were significantly higher (p < 0.001) than those of the healthy reference cartilage (1.23 ± 0.17). The mean diffusion quotients for the transplants and the healthy reference cartilages at the basic and follow-up examination in groups 1 and 2 are provided in Table 1. In group 1, a significant drop (p = 0.030) in the diffusion quotients of the transplants was found comparing the baseline (1.50 ± 0.27), with the follow-up examination (1.39 ± 0.26), whereas these values were stable in group 2 (1.46 ± 0.21 versus 1.44 ± 0.26) (p = 0.788). No difference was found between the baseline and the one-year follow-up scan in healthy reference cartilage. For group 1 (baseline:

Table 1 Mean diffusion quotients of cartilage within the selected ROIs (mean ± SD).

Baseline examination

ROI

Level

Group 1

Transplant

Superficial Deep Total Superficial Deep Total

1.50 1.52 1.51 1.23 1.21 1.22

± ± ± ± ± ±

0.33 0.26 0.26 0.24 0.14 0.12

1.47 1.44 1.46 1.25 1.23 1.23

± ± ± ± ± ±

0.29 0.18 0.21 0.20 0.17 0.13

Superficial Deep Total Superficial Deep Total

1.37 1.40 1.39 1.28 1.25 1.26

± ± ± ± ± ±

0.28 0.27 0.26 0.30 0.40 0.25

1.41 1.46 1.44 1.23 1.21 1.21

± ± ± ± ± ±

0.29 0.24 0.26 0.18 0.18 0.15

Reference

Transplant Follow-up examination

Reference

Group 2

K.M. Friedrich et al. / European Journal of Radiology 73 (2010) 622–628

625

Fig. 3. Typical evaluation of a patient after MACT using the custom-built semi-automatic region-of-interest (ROI) evaluation tool. (1) Only a few mouse clicks at the margins of the transplant are necessary for the annotation (red line). (2) The software then automatically calculates six regions of interest within the selected transplant (white lines). (3) After that, an area of reference cartilage must be selected by a few mouse clicks around the margins of the reference cartilage (green line). (4) The software automatically calculates two regions of interest within the selected area of reference cartilage (white lines).

1.22 ± 0.12; one-year follow-up: 1.26 ± 0.25) (p = 0.566) and group 2 (baseline: 1.23 ± 0.13; one-year follow-up: 1.21 ± 0.15) (p = 0.657) values where stable. The mean diffusion quotients for the deep and superficial zones of the transplant and the healthy reference cartilage in groups 1 and 2 at the baseline and the follow-up examination are provided in Table 1. A zonal variation in the diffusivity of cartilage was found. In total, the mean diffusion quotients for the healthy reference cartilage were higher in the superficial zone compared to the deep zone, and the mean diffusion quotients of the transplants were lower in the superficial zone compared to the deep zone; however, no significant differences were found (pRef = 0.609, pTX = 0.572).

The morphological assessment showed no significant difference (p = 0.217) between patients in group 1 (MOCART score: 70.7 points) and 2 (MOCART score: 75.7 points). 4. Discussion Several studies have proved that the dGEMRIC technique is a reliable tool for the assessment of the microstructure of cartilage. It has been shown that T1 maps obtained by the dGEMRIC technique reflect the proteoglycan content of cartilage. Other authors have used T2 mapping for the visualization of the microstructure of cartilage. Their results indicate that T2 mapping

Fig. 4. DWI raw images acquired using a steady-state gradient-echo pulse sequence (3D-DW PSIF) without a diffusion gradient (a) and with a diffusion gradient of 75 mT ms m−1 (b) of the same patient as in Fig. 1, six months after MACT. Arrows mark the cartilage repair area.

626

K.M. Friedrich et al. / European Journal of Radiology 73 (2010) 622–628

Fig. 5. DWI raw images acquired using a steady-state gradient-echo pulse sequence (3D-DW PSIF) without a diffusion gradient (a) and with a diffusion gradient of 75 mT ms m−1 (b) of the same patient as in Fig. 1 at the one-year follow-up 18 months after MACT. Arrows mark the cartilage repair area.

provides information about collagen matrix concentration and organization within cartilage. DWI has also been shown to provide valid information about cartilage microstructure. A prior study demonstrated an increase in diffusivity in cartilage after treatment with trypsin, which essentially removed the proteoglycans and noncollagenous proteins [38]. This indicated that cartilage composition is a major determinant of diffusivity in cartilage. Mlynarik et al. investigated the apparent diffusion coefficient (ADC) as a possible marker for early cartilage degeneration, and concluded that an increase in the ADC may indicate microstructural alterations within macroscopically intact cartilage [32]. From these and other studies [30–32,39,40], it can be deduced that measurements of diffusivity in cartilage may provide results that are more similar to dGEMRIC than to T2 mapping, and may thus be more sensitive to the proteoglycan content of the cartilage, which more closely reflects the collagen content and organization. In this study, a 3D steady-state diffusion technique (3D-PSIF) with strong diffusion sensitivity of the sampled magnetization (M− ) transverse component [41,42] was used. Sequence parameters were tuned with respect to optimal signal sensitivity for diffusion (16.82 TR on the order of 0.5 × T2 (for cartilage at 3T), flip angle alpha = 30◦ ). Using a 3D steady-state sequence for DWI is a relatively new technique that has already been applied to the visualization of chronic osteomyelitis [43], and for the differentiation of osteoporotic and metastatic vertebral fractures [44–46]. The advantages of 3D-DW-PSIF are the high signal-to-noise ratio, and the acquisition of a 3D data set. A recent study has proven that 3D-DW-PSIF can be used for in vivo DWI of cartilage [47].

The theoretical model of diffusion contributing to a steady-state signal was described several years ago [41,42,48–50]. However, the signal of 3D-PSIF turned out to have a complex dependence on the flip angle alpha, T1 , T2 , TR, and the single diffusion-sensitizing gradient [41], and is thus difficult to quantify. Contrasts that originate from T1 and T2 relaxation are superimposed on the contrast that originates from diffusion. Therefore, a quantification of diffusion, as achieved by calculating b-values and ADC maps, is challenging [41,50,51], and was a limitation of this study. Buxton et al. solved the problem of quantification by simplifying the analytical signal equation [41]. We decided to choose a semi-quantitative approach by calculating the diffusion quotients in this study; however, in future studies, the quantification of the applied diffusion values needs to be targeted. Although a quantification of diffusion cannot be achieved with this approach, it proved to be a stable method for in vivo evaluating relative changes in cartilage transplants compared to healthy reference cartilage, and comparing the transplants over time. In this context, DWI using the semi-quantitative approach can complement the information obtained from dGEMRIC or T2 -mapping. Compared to dGEMRIC [52], it has the advantage that no contrast medium is needed. In addition, the examination time with 3D-DWPSIF is shorter compared to dGEMRIC, where pre- and post-contrast measurements are necessary. Compared to T2 relaxation DWI may have the potential to visualize the cartilage ultrastructure on a more dynamic approach. Although it is a limitation within this study, that no direct comparison to dGEMRIC or T2 was applied, the presented DWI approach was able to depict the constitution of control

Fig. 6. Fused diffusion color maps of the same patient as in Fig. 1, six months (a) and 18 months (b) after MACT. Color-coded diffusion map demonstrates a slight decrease in diffusivity over time within the area of cartilage repair marked by the arrows.

K.M. Friedrich et al. / European Journal of Radiology 73 (2010) 622–628

cartilage sites and cartilage repair tissue in a longitudinal followup. In this study, we examined MACT patients and were able to assess the diffusivity of healthy and altered cartilage simultaneously. Our results showed a significant difference between the diffusivity of healthy control cartilage and altered cartilage repair tissue, as expected from the theoretical models and prior studies [47]. By comparing two groups of MACT patients at different time points after transplantation, and also comparing the acquired data from this baseline examination with the data acquired at a one-year follow-up of both groups, this study in vivo evaluated the change in diffusivity in cartilage transplants within the postoperative period. Whereas an existing cross-sectional study is reporting a decrease in diffusivity of the cartilage repair tissue over time as a sign of repair tissue maturation [47], within the present study a longitudinal one-year follow-up MRI could be performed within the same patient group. Comparing the shorter (group 1) and the longer (group 2) follow-up interval, during this one-year followup, a decrease of diffusivity was found within group 1, whereas diffusivity in group 2 was stable. This fact strengthens the theory, that the decrease in diffusivity over time may in fact visualize the maturation process of the cartilage repair tissue. Furthermore our results are showing that the reported diffusivity of the cartilage transplants approximate the diffusivity of the healthy reference cartilage over time. Nevertheless also within the longest followup periods the diffusivity of repair tissue never reaches values of healthy control cartilage. This observation fits to the results of prior histological studies [53], which demonstrated that cartilage repair tissue is always a mix of hyaline-like, fibro-hyaline, and fibrous tissue and never reaches the quality of purely hyaline cartilage as seen in the healthy reference cartilage. Zonal variations of the cartilage from the deep to the superficial layer had been impressively demonstrated by T2 mapping [23,54]. In vitro studies using DWI had reported an increase in the ADC of cartilage from close to the tidemark to close to the cartilage surface in excised plugs of calf, canine humeral head, and human patellar and femoral condyle cartilage [32,38,40]. This increase in diffusivity correlates with our finding of an increase in the mean diffusion quotients from the deep to the superficial zone of healthy cartilage, but those differences were not strong enough to reach significance. Thus, these data might indicate that our examination technique was not sensitive enough for a reliable in vivo evaluation of zonal variations within the femoral cartilage. In the future, protocols with even higher spatial resolution might overcome these initial problems. Another reason for the lack of significance might be the fact that the transplants are thicker than the reference cartilage. One limitation of the current study is that histologic specimens were not available for direct comparison; however, since all patients showed satisfactory to excellent clinical outcomes, there was no indication to perform a repair tissue biopsy. To overcome this limitation, an intra-individual comparison of the diffusion quotient values with healthy reference cartilage was performed in the same knee joint. Since no follow-up arthroscopy was performed in these patients, the intactness of this reference site was defined based on standard cartilage MR imaging, as well as surgical reports of the initial cartilage transplantation. As mentioned above, a clear limitation of this study is the lack of direct quantification using ADC values. This certainly remains challenging for future studies, however the present approach is, to our knowledge, one of the first in vivo examinations using DWI in the biochemical post-operative evaluation of cartilage repair tissue. Hence the obtained semi-quantitative 3D-DW-PSIF approach shows the potential of DWI in the evaluation of articular cartilage and cartilage repair tissue and may demand further research on this topic.

627

5. Conclusions DWI detected changes in diffusion within cartilage repair tissue after MACT, which seem to reflect cartilage maturation. This followup study indicates that these changes occur up to two years after surgery, and are stable subsequently. Zonal variations in diffusitivity within the cartilage could be measured, but showed – probably due to the different thickness of the transplant and the reference cartilage – no significant results and remain a challenge for future studies, as is the quantification of diffusion values.

References [1] Marlovits S, Zeller P, Singer P, Resinger C, Vecsei V. Cartilage repair: generations of autologous chondrocyte transplantation. Eur J Radiol 2006;57(1):24–31. [2] Brittberg M. Autologous chondrocyte transplantation. Clin Orthop Relat Res 1999;(Suppl. 367):S147–55. [3] Erggelet C, Browne JE, Fu F, Mandelbaum BR, Micheli LJ, Mosely JB. Autologous chondrocyte transplantation for treatment of cartilage defects of the knee joint Clinical results. Zentralbl Chir 2000;125(6):516–22. [4] Hangody L, Fules P. Autologous osteochondral mosaicplasty for the treatment of full-thickness defects of weight-bearing joints: ten years of experimental and clinical experience. J Bone Joint Surg Am 2003;85-A(Suppl. 2):25–32. [5] Micheli LJ, Browne JE, Erggelet C, et al. Autologous chondrocyte implantation of the knee: multicenter experience and minimum 3-year follow-up. Clin J Sport Med 2001;11(4):223–8. [6] Minas T, Peterson L. Advanced techniques in autologous chondrocyte transplantation. Clin Sports Med 1999;18(1), 13–44, v–vi. [7] Peterson L, Brittberg M, Kiviranta I, Akerlund EL, Lindahl A. Autologous chondrocyte transplantation. Biomechanics and long-term durability. Am J Sports Med 2002;30(1):2–12. [8] Tins BJ, McCall IW, Takahashi T, et al. Autologous chondrocyte implantation in knee joint: MR imaging and histologic features at 1-year follow-up. Radiology 2005;234(2):501–8. [9] Nehrer S, Minas T. Treatment of articular cartilage defects. Invest Radiol 2000;35(10):639–46. [10] Minas T, Chiu R. Autologous chondrocyte implantation. Am J Knee Surg 2000;13(1):41–50. [11] Peterson L, Minas T, Brittberg M, Nilsson A, Sjogren-Jansson E, Lindahl A. Twoto 9-year outcome after autologous chondrocyte transplantation of the knee. Clin Orthop Relat Res 2000;374:212–34. [12] Chung CB, Frank LR, Resnick D. Cartilage imaging techniques: current clinical applications and state of the art imaging. Clin Orthop Relat Res 2001;(Suppl. 391):S370–8. [13] Marcacci M, Berruto M, Brocchetta D, et al. Articular cartilage engineering with Hyalograft C: 3-year clinical results. Clin Orthop Relat Res 2005;435:96–105. [14] Burstein D, Bashir A, Gray ML. MRI techniques in early stages of cartilage disease. Invest Radiol 2000;35(10):622–38. [15] Huber M, Trattnig S, Lintner F. Anatomy, biochemistry, and physiology of articular cartilage. Invest Radiol 2000;35(10):573–80. [16] Bashir A, Gray ML, Hartke J, Burstein D. Nondestructive imaging of human cartilage glycosaminoglycan concentration by MRI. Magn Reson Med 1999;41(5):857–65. [17] Burstein D, Velyvis J, Scott KT, et al. Protocol issues for delayed Gd(DTPA)(2−)enhanced MRI (dGEMRIC) for clinical evaluation of articular cartilage. Magn Reson Med 2001;45(1):36–41. [18] Mosher TJ, Dardzinski BJ, Smith MB. Human articular cartilage: influence of aging and early symptomatic degeneration on the spatial variation of T2—preliminary findings at 3 T. Radiology 2000;214(1):259–66. [19] Nieminen MT, Rieppo J, Silvennoinen J, et al. Spatial assessment of articular cartilage proteoglycans with Gd-DTPA-enhanced T1 imaging. Magn Reson Med 2002;48(4):640–8. [20] Nieminen MT, Rieppo J, Toyras J, et al. T2 relaxation reveals spatial collagen architecture in articular cartilage: a comparative quantitative MRI and polarized light microscopic study. Magn Reson Med 2001;46(3):487–93. [21] Recht M, Bobic V, Burstein D, et al. Magnetic resonance imaging of articular cartilage. Clin Orthop Relat Res 2001;(Suppl. 391):S379–96. [22] Recht MP, Goodwin DW, Winalski CS, White LM. MRI of articular cartilage: revisiting current status and future directions. AJR Am J Roentgenol 2005;185(4):899–914. [23] Smith HE, Mosher TJ, Dardzinski BJ, et al. Spatial variation in cartilage T2 of the knee. J Magn Reson Imaging 2001;14(1):50–5. [24] Tiderius CJ, Olsson LE, Leander P, Ekberg O, Dahlberg L. Delayed gadoliniumenhanced MRI of cartilage (dGEMRIC) in early knee osteoarthritis. Magn Reson Med 2003;49(3):488–92. [25] Trattnig S, Mlynarik V, Breitenseher M, et al. MRI visualization of proteoglycan depletion in articular cartilage via intravenous administration of Gd-DTPA. Magn Reson Imaging 1999;17(4):577–83. [26] Kimelman T, Vu A, Storey P, McKenzie C, Burstein D, Prasad P. Three-dimensional T1 mapping for dGEMRIC at 3.0 T using the look locker method. Invest Radiol 2006;41(2):198–203.

628

K.M. Friedrich et al. / European Journal of Radiology 73 (2010) 622–628

[27] Craig JG, Go L, Blechinger J, et al. Three-tesla imaging of the knee: initial experience. Skeletal Radiol 2005;34(8):453–61. [28] Weckbach S, Mendlik T, Horger W, Wagner S, Reiser MF, Glaser C. Quantitative assessment of patellar cartilage volume and thickness at 3.0 Tesla comparing a 3D-fast low angle shot versus a 3D-true fast imaging with steady-state precession sequence for reproducibility. Invest Radiol 2006;41(2):189–97. [29] Mosher TJ. Musculoskeletal imaging at 3 T: current techniques and future applications. Magn Reson Imaging Clin N Am 2006;14(1):63–76. [30] Miller KL, Hargreaves BA, Gold GE, Pauly JM. Steady-state diffusion-weighted imaging of in vivo knee cartilage. Magn Reson Med 2004;51(2):394–8. [31] Miller KL, Pauly JM. Nonlinear phase correction for navigated diffusion imaging. Magn Reson Med 2003;50(2):343–53. [32] Mlynarik V, Sulzbacher I, Bittsansky M, Fuiko R, Trattnig S. Investigation of apparent diffusion constant as an indicator of early degenerative disease in articular cartilage. J Magn Reson Imaging 2003;17(4):440–4. [33] Szafer A, Zhong J, Anderson AW, Gore JC. Diffusion-weighted imaging in tissues: theoretical models. NMR Biomed 1995;8(7–8):289–96. [34] Trattnig S, Pinker K, Krestan C, Plank C, Millington S, Marlovits S. Matrix-based autologous chondrocyte implantation for cartilage repair with HyalograftC: two-year follow-up by magnetic resonance imaging. Eur J Radiol 2006;57(1):9–15. [35] Marlovits S, Striessnig G, Resinger CT, et al. Definition of pertinent parameters for the evaluation of articular cartilage repair tissue with high-resolution magnetic resonance imaging. Eur J Radiol 2004;52(3):310–9. [36] Marlovits S, Singer P, Zeller P, Mandl I, Haller J, Trattnig S. Magnetic resonance observation of cartilage repair tissue (MOCART) for the evaluation of autologous chondrocyte transplantation: determination of interobserver variability and correlation to clinical outcome after 2 years. Eur J Radiol 2006;57(1):16–23. [37] Trattnig S, Millington SA, Szomolanyi P, Marlovits S. MR imaging of osteochondral grafts and autologous chondrocyte implantation. Eur Radiol 2007;17(1):103–18. [38] Burstein D, Gray ML, Hartman AL, Gipe R, Foy BD. Diffusion of small solutes in cartilage as measured by nuclear magnetic resonance (NMR) spectroscopy and imaging. J Orthop Res 1993;11(4):465–78. [39] Filidoro L, Dietrich O, Weber J, et al. High-resolution diffusion tensor imaging of human patellar cartilage: feasibility and preliminary findings. Magn Reson Med 2005;53(5):993–8. [40] Xia Y, Farquhar T, Burton-Wurster N, Ray E, Jelinski LW. Diffusion and relaxation mapping of cartilage-bone plugs and excised disks using microscopic magnetic resonance imaging. Magn Reson Med 1994;31(3):273–82.

[41] Buxton RB. The diffusion sensitivity of fast steady-state free precession imaging. Magn Reson Med 1993;29(2):235–43. [42] Wu EX, Buxton RB. Effect on diffusion on steady-state magnetization with pulsed field gradients. J Magn Reson 1990;90:243–53. [43] Bitzer M, Schick F, Hartmann J, et al. MRI of intraosseos fistulous systems and sequesters in cronic osteomyelitis with standard spin echo sequences, highly selective chemical-shift imaging, diffusion weighted imaging, and magnetisation-transfer. Rofo 2002;174(11):1422–9. [44] Baur A, Dietrich O, Reiser MF. Diffusion-weighted imaging of bone marrow: current status. Eur Radiol 2003;13(7):1699–708. [45] Baur A, Huber A, Arbogast S, et al. Diffusion-weighted imaging of tumor recurrencies and posttherapeutical soft-tissue changes in humans. Eur Radiol 2001;11(5):828–33. [46] Baur A, Stabler A, Bruning R, et al. Diffusion-weighted MR imaging of bone marrow: differentiation of bnigne versus pathologic compression fractures. Radiology 1998;207(2):349–56. [47] Mamisch T, Menzel M, Welsch G, et al. Steady-state diffusion imaging for MR in-vivo evaluation of reparative cartilage after matrix-associated autologous chondrocyte transplantation at 3 Tesla—preliminary results. Eur J Rad 2008;65(1):72–9. [48] Deoni SC, Peters TM, Rutt BK. Quantitative diffusion imaging with steady-state free precession. Magn Reson Med 2004;51(2):428–33. [49] Kaiser R, Bartholdi E, Ernst RR. Diffusion and field-gradient effects in NMR Fourier Spectroscopy. J Chem Phys 1974;80(8):2966–79. [50] Le Bihan D. Intravoxel incoherent motion imaging using steady-state free precession. Magn Reson Med 1988;7(3):346–51. [51] Le Bihan D, Mangin JF, Poupon C, et al. Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging 2001;13(4):534–46. [52] Watanabe A, Wada Y, Obata T, et al. Delayed gadolinium-enhanced MR to determine glycosaminoglycan concentration in reperative cartilage after autologous chondrocyte implantation: preliminary results. Radiology 2006;239(1): 201–8. [53] Briggs TW, Mahroof S, David LA, Flannelly J, Pringle J, Bayliss M. Histological evaluation of chondral defects after autologous chondrocyte implantation of the knee. J Bone Joint Surg Br 2003;85(7):1077–83. [54] White L, Sussman M, Hurtig M, Probyn L, Tomlinson G, Kandel R. Cartilage T2 assessment: differentiation of normal hyaline cartilage and reparative tissue after arthroscopic cartilage repair in equine subjects. Radiology 2006;241:407–14.