Accepted Manuscript Anti-Tumour Treatment A literature review of the association between Diffusion-Weighted MRI derived Apparent Diffusion Coefficient and tumour aggressiveness in pelvic cancer V.R. Bollineni, G. Kramer, Y. Liu, C. Melidis, N.M. de Souza PII: DOI: Reference:
S0305-7372(15)00055-9 http://dx.doi.org/10.1016/j.ctrv.2015.03.010 YCTRV 1390
To appear in:
Cancer Treatment Reviews Cancer Treatment Reviews
Received Date: Revised Date: Accepted Date:
13 February 2015 20 March 2015 23 March 2015
Please cite this article as: Bollineni, V.R., Kramer, G., Liu, Y., Melidis, C., de Souza, N.M., A literature review of the association between Diffusion-Weighted MRI derived Apparent Diffusion Coefficient and tumour aggressiveness in pelvic cancer, Cancer Treatment Reviews Cancer Treatment Reviews (2015), doi: http:// dx.doi.org/10.1016/j.ctrv.2015.03.010
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A literature review of the association between Diffusion-Weighted MRI derived Apparent Diffusion Coefficient and tumour aggressiveness in pelvic cancer VR Bollineni 1 G Kramer2 Y Liu 1 C Melidis 1 NM de Souza 3 From: 1European Organization for Research and Treatment of Cancer Headquarters, Brussels, Belgium. 2
Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands. 3
CRUK Cancer Imaging Centre, MRI Unit, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK.
Corresponding author Prof. Dr NM de Souza, MRI Unit, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5PT, UK.
Conflict of Interest Statement The authors state that the research presented in this manuscript is free of conflicts of interest.
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Abstract Diffusion-weighted Magnetic Resonance Imaging (DW-MRI) is used extensively to improve tumour detection and localization because it offers excellent soft tissue contrast between malignant and non-malignant tissues. It also provides a quantitative biomarker; the apparent diffusion coefficient (ADC) can be derived from DW-MRI sequences using multiple diffusion weightings. ADC reflects the tumour microenvironment, e.g. cell membrane integrity and cellularity and has potential for reporting on tumour aggressiveness. This review focuses on the use of the DW-MRI derived imaging biomarker ADC to reflect tumour aggressiveness and its potential impact in managing pelvic cancer patients. The clinical studies which evaluate the role of ADC in pelvic tumours (prostate, bladder, rectal, ovary, cervix and uterus) are summarized and the evidence linking ADC values with tumour aggressiveness is evaluated.
Keywords: Diffusion-weighted MRI, Apparent Diffusion Coefficient, Prostate cancer, Bladder cancer, Rectal cancer, Ovarian cancer, Cervical cancer, Endometrial cancer and Tumour aggressiveness
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Introduction Magnetic Resonance Imaging (MRI) is used to visualise anatomical structure or probe functional properties of tissues. In particular, diffusion-weighted (DW)-MRI is extensively applied in oncology for distinguishing malignant from non-malignant tissues. It interrogates the Brownian movement of water molecules at microscopic level [1] that is impeded by cell membranes, fibers or proteins within the extracellular matrix which is altered in processes such as inflammation or malignancy. Quantifying the diffusion properties of water molecules therefore provides information about tissue microstructure; in cancer tissues it reflects cell membrane integrity and cellularity, which in turn depends on tumour aggressiveness [2, 3]. Quantification is done by calculating the apparent diffusion coefficient (ADC) measured in mm2/sec, which is a function of the exponential decrease in signal intensity with increasing diffusion-weighting (b-value, Figure 1). The b-value is determined by the amplitude duration and spacing of the gradients applied within a diffusion-weighted sequence. A low ADC value equates to restrained diffusion and can be found in highly dense tissues such as tumours, lymph nodes or in areas of fibrosis. Conversely, a high ADC value means a lesser degree of restriction of extracellular water mobility and can be found in tissues with high glandular regions or significant necrotic component. Recently, Morgan et al. [4] demonstrated the value of ADC alteration over time to predict the natural history of untreated prostate cancer. The acquisition of DW-MRI is noninvasive, does not require exogenous contrast agents, and does not use ionizing radiation. Moreover, it can be obtained relatively rapidly, and can be easily incorporated into routine clinical practice [5]. MRI forms the mainstay for staging pelvic tumours but has not been exploited to image tumour behaviour. ADC derived from DW-MRI can potentially provide this information, thus adding to 3
tumour characterisation and aiding management decisions. This review therefore focuses on the current evidence for ADC to inform on tumour aggressiveness in pelvic tumours.
Materials and methods section: Search strategy The PubMed database was searched for articles published up to 1st September 2014, including electronic early-release publications. The search terms used were in conjunction with tumour aggressiveness: “Prostate cancer- tumour aggressiveness”, “Bladder cancer”, “Rectal cancer,” “Ovarian cancer,” “Endometrial cancer,” “Cervical cancer,” “Apparent diffusion coefficient”, “Diffusion weighted imaging” and “DW-MRI”. In addition, papers’ references lists were screened in order to retrieve additional relevant papers. The literature search generated a total of 147 references. Both prospective and retrospective studies were included. Studies only available in abstract form and articles in languages other than English were considered ineligible (n=39). Other non-ADC papers addressing studies of pelvic tumors and infectious diseases were also considered ineligible (n=55). Major conclusions were drawn from prospective and retrospective in vivo studies that used ADC derived from DW-MRI to characterise tumour aggressiveness. After removing duplicates and ineligible studies, 31 studies were finally included in this review. The selection process of the search strategy is summarized in Figure 2, and the results are tabulated in Table 1.
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Results Prostate cancer DW-MRI has been implemented in the clinic to detect and stage the primary tumour [6] and ADC has been shown in an early study to be a marker of tumour aggressiveness [3]. Its ability to differentiate between high and low risk tumours (Figure 3) has been subsequently corroborated by different groups [7], who have indicated the ability of ADC to differentiate Gleason score 8 and 9 from Gleason score 6 and 7 tumours (P < 0.001) [8]. Thormer et al. [9] showed that a tumour ADC value ≤ 0.46 mm2/s was associated with high grade and aggressive prostate cancer tumours. However, caution with interpretation of absolute values is necessary as they are critically dependent on acquisition (selection of b-values) and on the method of modeling used (mono-, bi- or multiexponential fit of the data). Donati et al. [10] in a univariate analysis showed that while both tumour volume (as defined by ADC abnormality) and mean ADC showed significant correlation with Gleason score, on multivariate analysis only mean ADC significantly predicted tumour aggressiveness (P = 0.015). Using histogram analysis of ADCs from individual voxels within whole tumour regions, the 10th percentile ADC also has been shown to correlate with Gleason score and differentiates tumours with a Gleason score of 6 from those with a Gleason score of 7 and higher [11] . The negative correlation of ADC value with Ki67 as a measure of cell proliferation has also been confirmed [7]. A limitation of the use of this biomarker is that much of the data quoted applies specifically to tumours in the peripheral zone of the prostate. In the central gland, the presence of benign prostatic hypertrophy confounds the measurement; Verma et al. [12], showed that while a correlation between ADC, lesion size and Gleason score exists for the peripheral zone, the relationship did not hold true for the central gland of prostate tumours. 5
Bladder cancer In bladder cancer, the comparison of high with low grade tumours verified histologically in a series of 43 cases indicated a lower ADC in the former group (P<0.0001) [13]. Furthermore, patients with muscle invasive tumours had lower ADC values (n = 10; ADC= 0.76 mm2/s) compared with non-invasive muscle tumours (n = 33; ADC= 1.12 mm2/s; P = 0.0004). This finding agreed with that from a study by Kobayashi et al. [14], who also showed that ADC values were significantly lower in tumours of a higher T-stage [15]. They indicated that an ADC cut-off of 0.92 mm2/s on the Receiver Operating Characteristic (ROC) curve best differentiated aggressive disease from less aggressive disease clinically, with an accuracy of 87%, specificity and sensitivity of 85% and 87% respectively, although as previously indicated, absolute values of ADC need to be interpreted in context of their acquisition and analysis methodology. Rosenkrantz et al. [16], also confirmed a lower ADC when tumours were higher stage (≥T2) (P = 0.005) and high grade (P = 0.023). These findings have been extended to cystectomy studies, which analyses the whole lesion and avoids the error of grading randomly sampled biopsies. The corresponding MRI examinations have looked at the whole lesion (rather than single slice) to include tumour heterogeneity [17]. In these cases mean ADC values were significantly lower in stage ≥ T3 tumours (P = 0.04) but showed no association with nodal disease or later development of metastasis, possibly due to small sample size. In bladder cancer, there is evidence correlating ADC values with proliferative activity reflected by Ki-67, as well as with tumour size and Tstage of disease [15].
Rectal cancer
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The concept of using ADC value as a potential non-invasive biomarker of rectal cancer tumour aggressiveness was pursued by Curvo-Semedo et al. [18] who showed that mean ADC values were significantly different between mesorectal fascia (MRF)-free versus MRF invaded (P = 0.013) tumours. They also observed that mean ADC values were lower for less differentiated grades and for nodal positive disease and concluded that the ADC value could potentially be used as a non-invasive biomarker for predicting MRF status, histological grade and the nodal status in rectal cancers. Akashi et al. [19], also showed that mean ADC values significantly differed between poorly differentiated and well differentiated tumours (P = 0.02). A significant negative correlation has also been shown between ADC and extramural depth in rectal cancer (r = 0.58; P = 0.001) [20] and mirrored the results for serum biomarkers between CEA < 5ng/mL vs ≥ 5ng/mL (P = 0.013) and CA19-9 < 27 U/mL vs ≥27 U/mL (P = 0.012). Therefore, like serum biomarkers and extramural depth, the imaging parameter ADC is associated with a more aggressive tumour profile and has potential to provide an imaging assessment of tumour aggressiveness and predict treatment response [21].
Ovarian cancer Several recent studies in ovarian cancer have demonstrated that the excellent soft-tissue contrast between tumour and normal tissues at b-values >900 s/mm2 allows visual tumour differentiation of nodular and plaque-like serosal and peritoneal disease. In ovarian masses, the lowest ADC values are observed in malignant lesions (1.39 ± 0.62 mm2/s) [22]. This quantifiable difference in ADC between benign and malignant ovarian tumours has been confirmed in a number of other studies [23]. More detailed ADC histogram analysis of the entire tumour volume provides
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information on the heterogeneity of diffusivity within the tumour and thus on the range of tumour microenvironments present, which is of particular interest in ovarian cancer where tumour is often present at the outset within a variety of tissue types (ovary, peritoneum, omentum, lymph nodes). This concept can be extended to studying heterogeneity of response, where more cellular, proliferative elements can be tracked in their response to neoadjuvant chemotherapy prior to interval debulking surgery. In a study by Kyriazi et al. [24]., the 25th ADC percentile on histogram analysis performed best (AUC 0.82) in identifying treatment response over conventional biochemical and morphological criteria (89% vs 64%). Another potential clinical benefit in ovarian cancer, where disease presents late and distributed throughout the abdomen and pelvis is in differentiating response characteristics at different anatomic sites, likely to be related to their proliferative potential at these sites. In a prospective study, Sala et al. [25] showed a larger increase in the ADC value of the primary tumour in responders to platinum-based neoadjuvant chemotherapy than in the non-responders (P = 0.002). However, no significant change was observed at metastatic sites. Thus, ADC has potential not just to report on tumour aggressiveness at the outset, but also to monitor differential response to chemotherapy in multi-site, metastatic disease. Endometrial cancer In uterine endometrial cancer conventional T2-W MRI often in conjunction with dynamic contrast-enhanced T1-W sequences is used to stage the disease [26]. Besides depth of the myometrial invasion, histological grade is an important prognostic factor, correlating strongly with risk of lymph node metastasis and survival [27] and strongly determining management strategies. The use of DW-MRI for distinguishing tumour grade was investigated by Tamai et al.
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[28], who reported that grade 3 tumors showed significantly lower mean ADC values (0.73 ± 0.09 mm2/s; p<0.01) compared to grade 1 tumours, but with considerable overlap. Another study showed that although in comparison to benign endometrial pathology (e.g. benign polyps and hyperplasia) ADC values of endometrial cancer were significantly lower [29], no significant differences were detectable between different histological grades. These conflicting results might be explained due to the small sample sizes and necessitate the use of larger, prospectively powered studies.
Cervical cancer In cervical cancer, data on the potential of ADC as a biomarker of aggressiveness are conflicting. A significant correlation between ADC and tumour type and differentiation have been reported [30, 31], but correlations with FIGO stage or lymph node status have been variously noted as absent [31], or present [32]. The correlation with FIGO stage and lymph node status was also seen by Nakamura et al. [33], who additionally showed a significant correlation with lymphovascular space involvement, stromal and parametrial invasion. Other ADC measures showed less or no correlation with any prognostic factors [34][33][35]. Despite these variable data on correlations of ADC with clinico-pathological features, the correlations of mean and minimum ADC values with clinical outcome are positive. The mean ADC was significant lower in patients with local tumour recurrence or metastasis in the study by Kuang et al [31] and was significantly associated with disease-free survival (DFS) and overall survival (OS) in the study by Micco et al. [32]. Multivariate analysis performed by Nakamura et al. [33] showed that mean ADC was an independent prognostic factor for DFS after radical hysterectomy. In addition a
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retrospective study also showed that pre-treatment mean ADC was a prognostic factor for DFS after chemoradiotherapy in univariate analysis, with a trend towards being an independent prognostic factor for recurrence in multivariate analysis (P = 0.066) [36]. Therefore, pretreatment mean ADC could be an important indicator for identifying patients with more aggressive disease who are at risk for disease recurrence. Several studies have focused on the use of serial DW-MRI for predicting outcome in patients receiving neoadjuvant chemotherapy or chemoradiotherapy. In patients achieving complete response, the increase in ADC was significantly larger as early as 2 weeks after start of treatment than in patients who subsequently did not [37–39], so that change in ADC at an early time point holds potential as a biomarker of likely aggressive, poorly responding disease.
Limitations Several of the clinical studies discussed in this review have limitations. First and foremost, there is inevitable reporting bias towards patients with relatively aggressive disease [6, 10, 11, 14, 15]. Secondly, ADC value depends on the MRI imaging protocol and thus it should be stressed that the cut-off ADC values defined in one study cannot be easily translated to other centers due to differences in ADC quantification and different DW-MRI imaging protocols. Thirdly, most studies describe the measurement of ADC values by defining one or two regions-of-interest (ROIs) placed within the tumour or even in a single slice, which does not represent the overall tumour profile. Hence, advanced techniques like the whole tumour ADC with voxel-by-voxel histogram analysis is preferred to reduce operator dependence and provide a more objective and comprehensive tumour assessment that reflects the global tumour microenvironment and tumour 10
heterogeneity. Other limitations include the fact that many studies quoted are retrospective and had a small sample size and that there is paucity of data relating ADC values with clinical outcomes such as local recurrence, patient survival and development of metastasis.
Standardization Implementing DW-MRI imaging to charaterise tumours and assess their response to treatment requires that an observed alteration of the imaging biomarker (ADC) due to treatment must be greater than the intrinsic and extrinsic variability of the biomarker in the absence of treatment. Reproducibility of functional and molecular imaging techniques depend on quality data and standardized procedures [40]. Although, advanced MR techiques, such as DW-MRI, are relatively simple, nevertheless they require definite protocols, meticulous acquisition and image analysis for quantification. The European Organisation for Research and Treatment of Cancer (EORTC) published recommendations for the measurement of tumour fluorodeoxy-glucose (FDG) uptake in monitoring treatment response in 1999 [41]. We are concerned, however that such recommendations are lacking for DW-MRI, making it diffuclt to include DW-MRI in large multicenter trials. However, studies are increasingly reported that show that the variability between different vendors and field-strengths do not exceed intrinsic test-re-test variability: this suggests that comparability and consistency can be achieved to a certain level between different institutions. In lung cancer, intra-observer coefficients of variation of around 11% per lesion and 5% per patient have been demonstrated at a single institution [42], while in a multicentre study in livers of healthy volunteers using optimised protocols in 4 institutions yielded a coefficient of variation of ~5% [43]. Guidelines are needed to define basic standards for DW-MRI
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measurement and to achieve quality control. Standardisation and optimisation of protocols would be the crucial step that enables reliable, consistent and fit-for purpose quantitative measurements when DW-MRI is implemented in large multi-central trials.
Conclusion In conclusion, DW-MRI offers a means of non-invasively imaging the tumour microenvironment in vivo and deriving valuable information regarding tumour aggressiveness (Table 2). The ADC calculated from DW-MRI enables identification of patients at high risk of recurrence or those with a poorer prognosis, so more intensive treatment regimens can be planned at the outset. Through evaluation of tumour aggressiveness, DW-MRI offers potential for efficient patient selection, stratification and management in clinical trials.
Acknowledgements The authors like to thank the support of Fonds Cancer (FOCA) from Belgium for the support of the fellowship of Vikram rao Bollineni. Disclosure: The authors declare no conflict of interest. The publication content is solely the responsibility of the authors and does not necessarily reflect the view of FOCA.
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diffusion coefficients (ADCs) in healthy liver. Br J Radiol. 2015 Mar 19:20140717. [Epub ahead of print] Figure Legends Figure 1: Decline of signal intensity with increasing diffusion-weighting (b-value) is exponential. The apparent diffusion coefficient (ADC) is a fynction of this exponential decay.
Figure 2: Study selection process
Figure 3: Diffusion-weighted (DW)- MRI of high and low risk prostate tumours: Transverse T2W (A) and Apparent Diffusion coefficient (ADC) map (B) derived using b-values of 0, 100, 300. 500 and 800 s/mm2 in a patient with prostate cancer of Gleason grade 4+3. The low-signalintensity tumour on T2-W in A (arrows), shows marked diffusion restriction in B (arrow). In comparison, equivalent T2-W (C) and ADC map (D) in a patient with a Gleason grade 3+3 prostate cancer managed by active surveillance shows a tumour that is more difficult to define on T2-W and with less restricted diffusion (C) than in B (arrows).
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Legends to Tables Table 1: Summary of clinical studies in pelvic tumours reporting DW-MRI derived ADC as a biomarker of tumour aggressiveness. Table 2: Added value of DW-MRI for characterizing pelvic tumours.
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19
20
21
22
23
24
No. of Patients
Tumour type
22
Prostate
131
85
39
29
28
110
43
121
132
Prostate
Prostate
Prostate
Prostate
Prostate
Prostate
Bladder
Bladder
Bladder
Clinical study Assessment of aggressiveness
Prediction of aggressiveness
Assessment of aggressiveness before prostatectomy
Assessment of aggressiveness Clinical benefit of assessing ADC values
Assessment of aggressiveness
Assessing prostate cancer with ADC
Staging and grading
Prediction of aggressiveness ADC for reflecting invasion and proliferation
Purpose To evaluate prostate cancer aggressiveness using ADC
Results High risk tumours (Gleason score 8 and 9) had significantly lower ADC than low risk tumours (Gleason score 6 and 7)
Conclusion(s) ADC differentiates high grade from low grade lesions
To investigate whether tumour volume derived from ADC or mean ADC are independent predictors of prostate tumour Gleason score To investigate the association between prostate cancer aggressiveness and ADC derived from whole lesion analysis
In univariate analysis both tumour volume and mean ADC showed significant correlation with Gleason score. On multivariate analysis only mean ADC significantly correlated with Gleason score
Mean ADC is an independent predictor of tumour aggressiveness
10th percentile ADC correlated with Gleason score and differentiated Gleason 6 from Gleason score >7
10th percentile ADC could be used as a risk stratification factor at the time of diagnosis
To assess the value of DWIMRI for the prediction of prostate cancer aggressiveness To evaluate an association between the ADC value and Ki-67 and /or Gleason score
Tumour ADC value ≤ 0.46 mm2/s was associated with high grade and aggressive prostate cancer tumours
DW-MRI is a prognostic tool in patients monitored on active surveillance
[9]
Large actively proliferating tumours had significantly lower ADC values. ADC values are significantly associated with Gleason score in multivariate analysis. Tumour aggressiveness has strong inverse relationship with ADC value
ADC value identifies aggressive cancer foci at the time of diagnosis
[7]
To evaluate ADC values as predictor of aggressiveness in peripheral zone prostate cancer and comparing with Gleason score To determine the correlation between ADC, lesion size and Gleason score in prostate cancer patients To evaluate DW-MRI as a biomarker for prediction of bladder cancer aggressiveness using histopathology as the gold standard To investigate association between ADC and pathological grade To evaluate the role of ADC as a biomarker for bladder cancer
The higher the ADC value the lower the Gleason score in peripheral zone prostate cancers. Tumour volume and ADC both predicted aggressiveness in peripheral zone tumours High grade tumours had lower ADC than lowgrade tumours. Muscle invasive tumours had lower ADC values than non-invasive muscle tumours ADC values were significantly lower in high grade tumours than in low grade tumours. Additionally, tumours with higher T stage also showed significantly lower ADC values A significant inverse correlation was observed between ADC value and Ki-67, larger tumours and higher T-stage disease
Ref
[8]
[10]
ADC is a promising biomarker to distinguish between high (GS of 8 and 9), low (GS of 6) and intermediate risk (GS of 7) prostate cancers. DW-MRI offers the potential to predict prostate cancer aggressiveness
[11]
[6]
[12] Quantitative ADC measurements predict bladder cancer stage and grade
ADC values can serve as a potential biomarker to predict aggressiveness of bladder cancer ADC represents the invasiveness of tumour and proliferation activity of bladder cancer
[13]
[14] [15]
37
50
Bladder
Rectum
DW-MRI in carcinoma of the bladder
Assessment of aggressiveness
40
Rectum
Assessment of aggressiveness
90
Rectum
ADC and Extramural depth of invasion
Rectum
Prediction of response to therapy
31
Ovary
Assessment of therapy response
Ovary
Assessment of therapy response
Ovary
DW-MR in ovarian cancer
Ovary
Conventional vs DWMRI for detecting malignant lesions
Endometrium
DW-MRI in endometrial cancer
23
Endometrium
Assessment of tumour grade
42
Cervix
ADC values in cervical cancer
42
22
102
85
30
To evaluate association between MRI parameters and pathological indicators of bladder cancer aggressiveness
Higher stage (≥T2) tumours showed lower ADC values than low stage (≤ T1) tumours; high grade tumours showed significantly lower ADC values.
Lesion size and ADC values can potentially be used as markers of tumour stage and grade of bladder cancer.
To determine the usefulness of ADC value as a potential non-invasive biomarker of rectal cancer tumour aggressiveness To evaluate the potential value of ADC as a biomarker of tumour aggressiveness To evaluate the association between extramural depth and ADC values To evaluate ADC for assessing therapeutic response in locally advanced disease To investigate value of ADC in assessing chemotherapy response in metastatic ovarian cancer patients To evaluate the role of DWMRI in assessing response to chemotherapy
Mean ADC values were significantly different between tumours with MRF-free versus MRF invaded status. Mean ADC values were low for nodal positive disease
ADC value is a potential noninvasive biomarker for predicting MRF status, nodal status and the histological differentiation grade in rectal cancers. ADC provides prognostic information about advanced rectal cancer ADC and EMD of invasion are associated with a more aggressive tumour profile. ADC value is promising for evaluating response to therapy
To investigate DW-MR in differentiating borderline from malignant epithelial tumours To investigate the value of DW-MRI in discriminating benign from malignant lesions To evaluate whether the ADC values of endometrial cancer differ from those of normal uterine endometrium To evaluate whether DWMRI can be used in the assessment of tumour grade
ADC lower in malignant than in borderline epithelial tumours.
To compare ADC values of cervical cancer with those of normal cervical epithelium
Mean ADC values differed significantly between poorly and well differentiated tumours A significant negative correlation was found between ADC and extramural depth of invasion ADC distribution for the therapy-responder group showed a significant shift to higher ADC values after treatment. Increase in ADC values after the 1st and 3rd cycles of chemotherapy in responders
Early increases in ADC values characterize chemotherapy response.
An increase in ADC values of the primary tumours was found in responders than in nonresponders after 3 cycles of chemotherapy.
DW-MRI may be the appropriate imaging modality to monitor chemotherapy response in advanced ovarian cancer patients ADC differentiates malignant from borderline epithelial tumours
ADC values highest in benign and lowest in malignant tumours
ADC can distinguish benign from malignant tumours
ADC of normal endometrium significantly higher than that of endometrial cancer; ADC of grade 3 was significantly lower than in grade 1 tumours ADC values were statistically different between malignant and benign endometrial pathology; however no significant difference between histological tumour grades. Mean ADC was significantly higher in patients with cervical cancer compared to non malignant cervical epithelium
ADC can differentiate high from low-grade tumours
ADC values can differentiate between benign and malignant pathology but not between tumour grades. Mean ADC may be used for detecting cervical cancer
[16]
[18]
[19]
[20]
[21]
[24]
[25]
[23]
[22]
[28]
[29]
[30]
179
Cervix
Value of ADC in cervical cancer
Cervix
Correlation of DWMRI and clinical outcome
80
Cervix
Correlation of ADC values with prognostic values
66
Cervix
Correlating ADC with clinical outcome
Cervix
Value of ADC in cervical cancer
Cervix
ADC histogram analysis for tumour recurrence
Cervix
Predicting response using DW-MRI
49
47
42
25
75
30
Cervix
Cervix
Response assessment using DW-MRI
Response assessment using DW-MRI
To assess the value of ADC measurement in patients with cervical cancer To correlate DW-MRI with prognostic factors, disease free and overall survival To correlate the ADCmax/mean/min with prognostic factors To evaluate the correlation between minimum ADC and clinical outcome To assess the value of ADC measurement in patients with cervical cancer To investigate the value of pre-treatment ADC histogram analysis in predicting tumour recurrence after chemoradiotherapy To evaluate the efficacy of DW-MRI in prediction response to CRT To assess the value of ADC in predicting and monitoring treatment response in patients receiving chemoradiotherapy To evaluate if DW-MRI could be used for response assessment to neoadjuvant chemotherapy in patients with locally advanced disease
ADC significantly lower in cervical cancer compared to normal cervix; ADC distinguished tumour type, differentiation, recurrence and metastasis after hysterectomy. Mean ADC differed significantly between different FIGO stages and correlated with the presence of lymph node metastasis, DFS and OS Mean ADCwas significantly associated with FIGO stage, tumour size, stromal invasion, parametrial invasion, lymph node metastasis and was also predictive for disease recurrence Low minimum ADC correlated with shorter OS. However no correlation was found with FIGO stage or DFS The average median ADC was significantly lower in patients with cervical cancer. FIGO stage T1b/T2a showed a significantly lower average ADC compared to higher stages Pre-treatment mean ADC and the 75th percentile were significantly higher ADC in patients who recurred; the 75th percentile was a significant predictor of recurrence (HR: 1.319).
ADC can be used for diagnosing cervical cancer and for grading histological type and prognosis
Change in ADC 28 days after start of chemoradiotherapy was significantly larger in patients with complete response compared to patients with residual tumour 2 and 4 weeks after start of therapy patients with complete response showed a higher percentage ADC increase. Absolute ADC values were significantly higher for complete compared to partial response and stable disease ADC significantly increased compared to baseline after chemotherapy in the responders.
DW-MRI could be useful for early response assessment.
Mean ADC may serve as prognostic biomarker of survival
Mean ADC could be used to identify patients at risk for recurrence Minimum ADC might be used for predicting OS Median ADC values could distinguish aggressive cervical cancer ADC histogram analysis could be used to identify patients at risk of recurrence after chemoradiotherapy
DW-MRI could be useful for predicting and monitoring treatment response
[31]
[32]
[33]
[34]
[35]
[36]
[37]
[38]
DW-MRI is able to differentiate responders and non responders
Abbreviations: DW-MRI = Diffusion weighted MRI; ADC = Apparent diffusion coefficient; DFS = Disease free survival; OS = Overall survival;
[39]
Table 2: Added value of Diffusion-weighted-MRI for Pelvic Cancers Disease Prostate cancer
Bladder cancer
-
Rectal cancer
-
Ovarian cancer
Endometrial cancer Cervical cancer
-
Added value of DW-MRI Assessment of tumour aggressiveness / biology Differentiate high grade vs low grade lesions Potential surrogate marker for Gleason score Differentiate between aggressive disease from less aggressive disease clinically Differentiate between muscle invasive tumours from nonmuscle invasive tumours Differentiate between high grade and low grade tumours Characterization of poorly differentiated from well differentiated tumours Assessment of extra mural depth of invasion Potential to predict mesorectal fascia-free versus mesorectal fascia-invaded and nodal status Reflects tumour aggressiveness Differentiate benign from malignant masses Ovarian cancer staging Detection of small peritoneal deposits in pelvis Differentiate between local and diffuse pelvic recurrence Decline in disease activity can be inferred from rising ADCs after treatment Differentiate malignant from benign lesions Differentiate high from low grade lesions Differentiation between normal tissue and malignant lesions Correlation with clinico-histopathological prognostic factors. Identify patients at risk of recurrence after therapy Early assessment of response to therapy
Highlights 1. Low ADC values are associated with more aggressive tumours 2. ADC values have a potential to differentiate pelvic cancers at high risk of poor response and recurrence 3. ADC values allow evaluation of biological behaviour of pelvic cancers
25