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Year : 2012  |  Volume : 8  |  Issue : 1  |  Page : 68-73

Evaluation of diffusion-weighted imaging as a predictive marker for tumor response in patients undergoing chemoradiation for postoperative recurrences of cervical cancer

1 Department of Radiation Oncology, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai, India
2 Department of Radiodiagnosis, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai, India
3 Department of Radiation Oncology and Medical Physics, Tata Memorial Hospital, Tata Memorial Centre, Mumbai, Maharashtra, India
4 Department of Medical Oncology, Tata Memorial Hospital, Tata Memorial Centre, Mumbai, Maharashtra, India

Date of Web Publication19-Apr-2012

Correspondence Address:
Supriya Chopra
Department of Radiation Oncology, PS-246 Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Kharghar, Navi Mumbai - 410 210, Maharshtra
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0973-1482.95177

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 > Abstract 

Purpose: To investigate diffusion-weighted imaging (DWI) as a response biomarker in patients undergoing chemoradiation for postoperative recurrences of cervical cancer.
Materials and Methods: From October 2008 to March 2011, 20 patients were included. All underwent T2-weighted (T2W) and DWI before and after chemoradiation. Gross tumor volume (GTV), lateral extent, apparent diffusion coefficient (ADC), and presence of regions of focally restricted diffusion were determined at baseline. Response to chemoradiation was categorized as either partial or complete. Receiver operator characteristics (ROC) curve identified thresholds of GTV and ADC that best predict for partial response. Univariate and multivariate analysis were performed on SPSS version 15.
Results: The median GTV was 24.5 cc (4.1-110 cc). Central and lateral disease was present in 8 and 12 patients, respectively. The median ADC was 1 × 10 -3 mm 2 /s (0.8-1.3 × 10 -3 mm 2 /s) and 12/20 (60%) patients had focal restricted diffusion. Overall 10/20 patients had partial response. ROC analysis identified volume of 25 cc or higher [sensitivity = 80%, specificity = 80%, area under curve (AUC) = 0.76, P = 0.04] and ADC more than 1 × 10 -3 mm 2 /s (sensitivity = 70%, specificity = 50%, AUC = 0.62; P = 0.34) to best predict for partial response. On univariate analysis bulky disease (77.7% vs. 27%; P = 0.03), lateral disease (66.6% vs. 25%; P = 0.08), and focal regions of restricted diffusion (66.6% vs. 25%; P = 0.06) predicted for partial response to chemoradiation. All factors continued to be significant on multivariate analysis. On restricting analysis to bulky tumors ADC greater than 0.95 × 10 -3 mm 2 /s predicted partial response with high sensitivity (85.7%) and specificity (100%) (AUC 0.96; P = 0.05). On univariate analysis lateral disease (P = 0.04), high baseline ADC (P = 0.07) predicted for partial response.
Conclusions: Baseline ADC and focal regions of ADC restriction predict for partial response with moderate sensitivity and specificity in patients with postoperative recurrences of cervical cancer and need to be validated in larger cohort.

Keywords: Cervical cancer, diffusion-weighted imaging, MRI, postoperative, recurrent

How to cite this article:
Chopra S, Verma A, Kundu S, Engineer R, Medhi S, Mahantshetty U, Gupta S, Shrivastava SK. Evaluation of diffusion-weighted imaging as a predictive marker for tumor response in patients undergoing chemoradiation for postoperative recurrences of cervical cancer. J Can Res Ther 2012;8:68-73

How to cite this URL:
Chopra S, Verma A, Kundu S, Engineer R, Medhi S, Mahantshetty U, Gupta S, Shrivastava SK. Evaluation of diffusion-weighted imaging as a predictive marker for tumor response in patients undergoing chemoradiation for postoperative recurrences of cervical cancer. J Can Res Ther [serial online] 2012 [cited 2019 Sep 20];8:68-73. Available from: http://www.cancerjournal.net/text.asp?2012/8/1/68/95177

 > Introduction Top

Patients with postsurgical recurrences of cervical cancer have unfavorable prognosis. Radical chemoradiation followed by interstitial brachytherapy results in a 5-year overall survival of 35-46%. [1],[2] Though treatment intensification is desirable, there is dearth of validated prognostic factors that could select patients at higher risk of treatment failure. Selected studies have identified pretreatment tumor size and total radiation dose to be predictive of local control; however, both lack specificity. [3] Serum SCC-antigen levels, a relatively reliable prognostic marker, in early stage cervical cancer has not been investigated in patients harboring postoperative recurrences. [4]

In recent years, diffusion-weighted magnetic resonance imaging (DW-MRI) has been investigated as a potential imaging biomarker for cervical cancer. [5],[6],[7] DW-MRI images the microscopic motion of water protons along and across the cytoskeleton in tissues and enables a noninvasive depiction of intratumoral motion of water protons. Apparent diffusion coefficient (ADC), a quantitative measure of diffusion, can be readily calculated on commercial MRI platforms. Preliminary studies have also evaluated its utility in predicting histological type and tumor grade. [7],[8] However, DW-MRI has not been investigated as a response biomarker in patients with postoperative recurrences of cervical cancer. The present study was designed to investigate baseline intratumoral heterogeneity in ADC as a potential "imaging biomarker" for early response to chemoradiotherapy.

 > Materials and Methods Top

From October 2008 to March 2011, patients with postoperative vault recurrences, scheduled to undergo tomotherapy-based chemoradiation and interstitial brachytherapy, were included in this study. Those with gross residual disease after hysterectomy were excluded such that the study cohort represents "true recurrences" rather than "residual disease."

All MR imaging was performed on a 3T MR scanner (Signa HDxT, General Electric Medical Systems, Milwaukee, WIS, USA) equipped with an actively shielded whole body magnetic field gradient set, using an 8-channel transmit-receive radiofrequency coil (torso phase array coil). Patients were instructed to report for imaging after emptying bowel contents and were instructed to consume 500 ml of water over 15 min. Patients were positioned supine with arms above the head and the coil was centered at the pubic symphysis. Scanning was performed 30 min after consuming water to achieve even distribution of fluid in the small bowel lumen with low level of peristaltic activity and to facilitate fusion with CT images obtained for radiation planning. T2-weighted (T2W) fast spin echo MRI of the pelvis was performed using the following parameters [TE = 120 ms, TR = 4040 ms, field of view (FOV) = 40 × 40 cm, matrix = 288 × 224, ex = 2, slice thickness = 3 mm with 1 mm spacing]. This was followed by DW-MRI (TE = 74 ms, TR = 6000 ms, FOV = 40 × 40 cm, bandwidth = 250 KHz, b value = 0 and 500, matrix 128 × 128, Nex = 4, slice thickness = 3 mm, interslice gap of 1 mm).

All patients received tomotherapy-based image guided intensity modulated radiotherapy (IG-IMRT). IG-IMRT schedule consisted of 50 Gy/25 fractions delivered over 5 weeks along with concurrent weekly cisplatin (40 mg/m 2 ). Response assessment and brachytherapy preplanning MRI were performed within a week of completing IG-IMRT. In addition to T2W-MRI, diffusion-weighted imaging (DWI) was obtained for the purpose of present study. Subsequently, all patients underwent template guided high dose rate pelvic interstitial brachytherapy (20 Gy/5 #/ 3 days).

Baseline MR images were transferred to FocalSim Workstation (version 4.3.3) and gross tumor volume (GTV) was delineated on T2W images by radiation oncologists (SC, RE) in consultation with radiologists (SM, AV). For all patients, GTV was estimated and median GTV was obtained for the study population. Patients were categorized on the basis of lateral extent to have either "medial /central disease" or "lateral disease." GTV was also reviewed for presence of any regions of necrosis. Percentage volume of necrosis was quantified in patients with visible regions of tumor necrosis.

Baseline DW images were postprocessed on offline workstation (GE Advantage Version AW4.4-06.02-EXT-CTT-5.x) to generate ADC maps. T2W images and ADC maps were reviewed side by side by radiologists (AV, SM) and radiation oncologist (SC). A region of interest (ROI) was delineated on ADC maps at tumor midslice and ADC value was obtained. In addition, ADC values were obtained for slice above and below the ROI. All care was taken to exclude visible regions of necrosis. ADC values thus obtained were averaged to obtain "tumor ADC value." In addition, radiologists (AV, SM) also reviewed the entire tumor for regions of restricted diffusion within the GTV. These regions were delineated as a separate ROI and ADC value was determined. Patients were considered to have "focally restricted diffusion" within the GTV if the ADC values were decreased by >0.2 × 10−3 mm/s. This cut-off was chosen to exclude differences in ADC due to tumor differentiation. [8]

All post-EBRT MRIs were reviewed by radiologists (AV, SM). Absence of any disease on diagnostic MRI was categorized as "complete response" and presence of any residual disease was categorized as "partial response." While no attempt was made to calculate ADC values in complete responders, ADC value was determined for partial responders by delineating ROI in the region of residual disease. As tumor regions with baseline restriction of diffusion could potentially be at risk for harboring residual disease, spatial correspondence between residual disease and baseline regions of restricted diffusion was also evaluated.

All statistical analysis was done on SPSS version 15. A threshold T2 volume and ADC value were determined for predicting partial response to EBRT using receiver operator characteristics (ROC) analysis. ROC analysis was also undertaken to validate the cut-off values for "regions of focally restricted diffusion."

Subsequently following pretreatment factors were analyzed as a predictive factor for partial response to EBRT: tumor volume, baseline ADC value, presence of lateral disease, presence of regions of focally restricted diffusion, and presence of visible regions of necrosis. Factors found to be statistically significant or borderline significant on univariate analysis were included in multivariate analysis.

 > Results Top

Twenty women scheduled to undergo chemoradiotherapy for postoperative vault recurrences were included in the present study. The mean age of the study cohort was 45 years (35-65 years). None of the patients had received radiation at an earlier date.

The median GTV at presentation was 24.5 cc (4.1-110 cc). The median midtumor ADC value was 1.1 × 10−3 mm 2 /s (0.8 × 10−3 mm 2 /s to 1.3 × 10−3 mm 2 /s). A total of eight patients (40%) had central or medial parametrial disease and 12 (60%) had disease extending laterally. Overall, 12/20 patients (60%) had focal regions of restricted diffusion [Table 1].
Table 1: Table depicting apparent diffusion coeffi cients at midtumor level and in regions of maximum restriction. Tumors were considered to have focal regions of restricted diffusion only if ADC values were reduced by more than 0.2 × 10-3/mm2/s

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All response assessment was done one week after concurrent chemoradiotherapy and prior to interstitial brachytherapy. Overall, 50% of patients (10/20) had complete response. Pre- and post-chemoradiotherapy ADC values for those with partial response are depicted in [Table 2]. Amongst partial responders the average percentage change in ADC (∆ ADC) was 29% (0-66.6%). While all patients had residual disease in the region of primary tumor and regions of focally restricted ADC, 3/9 patients with residual disease had spatial correspondence exclusively to the regions of baseline-restricted diffusion [Table 2] and [Figure 1]A and B.
Figure 1: (A) Baseline ADC map demonstrating regions of restricted diffusion within the tumor. In this patient while average midtumor ADC was 1 × 10-3 mm2/s, the regions of restricted diffusion (as shown in the figure) had ADC value of 0.7 × 10-3 mm2/s. (B) Post-chemoradiotherapy apparent diffusion coefficient map depicting residual disease spatially corresponding to baseline regions of restricted diffusion

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Table 2: Table depicting pre and post-chemoradiotherapy apparent diffusion coefficients in patients with partial response

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ROC analysis identified absolute volume of 25 cc or higher [sensitivity = 70%, specificity = 80%, area under curve (AUC) = 0.76, P = 0.04] and average ADC value of more than 1 (sensitivity = 70%, specificity = 50%, AUC = 0.62, P = 0.34) [Figure 2]A and B to best predict for partial response to chemoradiotherapy. The data were therefore categorized across these absolute values for univariate and multivariate analysis. Tumor volume was categorized above and below 25 cc as "bulky" and "nonbulky" disease, respectively, and ADC was categorized above and below 1 × 10−3 mm 2 /s to "high ADC" or "low ADC."
Figure 2: ROC curve depicting sensitivity and specifi city of ADC values in predicting partial response chemoradiotherapy. (A) ADC value of 1 × 10-3 mm2/s predicted for partial response with sensitivity and specifi city of 70% and 50%, respectively, in the entire patient cohort (AUC = 0.62; P = 0.34). (B) ROC analysis restricted to patients with bulky tumors. ADC value of 1 × 10-3 mm2/s predicted for partial response with sensitivity and specifi city of 87% and 100%, respectively, (AUC = 0.96; P = 0.05)

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ROC analysis also evaluated the validity of using ADC difference > 0.2 × 10−3 mm 2 /s to predict for partial response. This value was associated with sensitivity and specificity of 80% and 60%, respectively, (AUC = 0.70, P = 0.12).

On univariate analysis, the presence of bulky disease was identified as the most important predictor for partial response (77.7% vs. 27%; P = 0.03), whereas presence of lateral disease (66.6% vs. 25%; P = 0.08) and focal regions of restricted diffusion (66.6% vs. 25%; P = 0.06) were identified as borderline significant. Presence of visible necrosis on imaging did not impact tumor response [Table 3]. Absolute ADC value was not identified to be predictive of tumor response. This trend was maintained on multivariate analysis as well [bulky disease (P = 0.02), lateral extent (P = 0.07), and focal regions of restricted diffusion (P = 0.07)].
Table 3: Univariate analysis of baseline tumor factors and response to chemoradiotherapy

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The mean baseline ADC of complete responders was identified to be lower than partial responders (0.85 × 1 × 10−3 mm 2 /s vs. 1.1 × 10−3 mm 2 /s; P = 0.03). On ROC analysis, ADC cut-off of 0.95 × 10−3 mm 2 /s predicted for partial response with sensitivity of 85.7%, specificity of 100% (AUC = 0.96; P = 0.05) [Figure 2]B. On univariate analysis lateral tumor extent (P = 0.04), baseline ADC value more than 1 × 10−3 mm 2 /s (P = 0.07) were identified to predict for partial response to chemoradiotherapy. As all but one patient had focal regions of restricted diffusion, the impact of this factor could not be assessed. Absolute volume however had no bearing on response to chemoradiotherapy (P = 0.39). All factors identified to be significant or borderline significant on univariate analysis continued to be significant or borderline significant on multivariate analysis.

 > Discussion Top

The present study investigates ADC as an imaging response biomarker in patients with postoperative recurrences of cervical cancer. After initiation of chemoradiation, early apoptotic cell death, loss of membrane integrity, and increased extracellular space lead to alterations in intratumoral water diffusion and hence tumor ADC. [9] These alterations in cellular characteristics precede reduction in tumor size and can be used as an early imaging biomarker of therapeutic response. Clinical studies in breast, [10] rectal, [11] hepatocellular, [12] head and neck, [13] and cervical cancer [5],[6],[7] have demonstrated that midtreatment increase in ADC after chemotherapy or chemoradiation could be used as an imaging response biomarker. Though mid-treatment alterations in ADC may predict for sensitivity (or lack of it) to chemotherapy or chemoradiation, modulation of the planned treatment may not be practically feasible. Therefore, investigation of baseline heterogeneity of ADC and it's correlation with tumor response may be worthwhile.

Various studies investigating the predictive ability of baseline ADC have reported heterogeneous results. While few studies have predicted higher odds of complete response with lower baseline ADC values, [5],[11] other studies have not confirmed the existence of this correlation. [6],[14] Though most of the studies use common methodology of placing ROI over the tumor while excluding regions of necrosis, the heterogeneity of results could possibly be attributed to data averaging across the tumor or defined ROI such that the impact of focal regions of restricted diffusion is often missed. In this prospective study, we sought to evaluate baseline ADC and impact of focal regions of restricted diffusion/ADC on early therapeutic response in patients undergoing chemoradiotherapy for postoperative recurrences in cervical cancer. While tumor ADC was determined with methodology similar to previously published studies, there were no established guidelines for defining regions of focally restricted diffusion. Tumor differentiation is known to alter ADC values by 0.1-0.2 × 10−3 mm 2 /s; [8] hence, a difference of more than 0.2 × 10−3 mm 2 /s was chosen to define focal regions of ADC restriction. These ADC differences represent a 2-fold difference in cellular density [15] and could potentially be of therapeutic importance.

In the present study apart from known prognostic factors (tumor bulk, parametrium), we observed that focal regions of restricted diffusion defined using the aforesaid cut-off predicted for partial response with sensitivity and specificity of 80% and 60%, respectively. When data analysis was restricted to patients with bulky tumor than in addition to lateral disease extent, baseline ADC > 1 × 10−3 mm 2 /s predicted for partial response with a sensitivity and specificity of 85.7% and 100% respectively. The aforesaid distinct DWI features (focal ADC restriction and high ADC) are representative of two adverse biological features, namely intratumoral necrosis (secondary to hypoxia) and focally increased cellularity which contribute toward poor response to chemoradiotherapy. [15],[16] Poor response with higher baseline ADC values has been reported in other solid tumors; [5] however, the impact of focal regions of restricted diffusion remains uninvestigated.

We also investigated tumor response in spatial reference to focal regions of restricted diffusion. Of a total of 10 partial responders, 9 had focally restricted diffusion at baseline. In 6/9 patients with restricted diffusion, the residual disease had spatial correspondence to baseline regions of tumor bulk including regions of restricted diffusion. However, in 3/9 patients the residual disease was restricted only to regions of focally restricted diffusion at baseline imaging. Though our data are not mature on the basis of these preliminary observations, we hypothesize that "focal regions of restricted intratumoral diffusion are potentially high risk subregions for harboring residual and recurrent disease after chemoradiotherapy" and merit further investigation. To this end, we have recently initiated a two-stage prospective study at our institution that evaluates local response in spatial reference to baseline multiparametric functional positron emission tomography and MR imaging in patients undergoing chemoradiation for postoperative recurrences of cervical cancer (clinical trials.gov NCT01391065). [17] While the first stage is designed to investigate the validity of our hypothesis by evaluating local response in spatial reference to biological high risk volume (as identified by multparametric imaging), the second stage would focus on delivering dose modulated brachytherapy with an aim to improve local control.

Various studies have proposed percentage change in ADC to be predictive of tumor response [5],[6],[11] and 2-year local control after chemoradiotherapy. [13] Our patients did not undergo midtreatment imaging; however, we had access to MRI obtained prior to interstitial brachytherapy (1 week after completing chemoradiotherapy). We calculated ∆ ADC for only partial responders. In our study ∆ADC ranged from 0 to 66.6%. Low values of ∆ADC are known to predict for higher odds of residual disease and local recurrence. [11] However, in absence of long-term follow-up data we could not assess this relationship.

Though the study evaluated and identified baseline ADC and focal regions of restricted diffusion as a potential predictive factor of partial response, the study methodology has certain drawbacks. The study results are based on a pilot study of only 20 patients and small patient number could potentially affect statistical conclusions. The study methodology used a difference of >0.2 × 10−3 mm 2 /s from average tumor ADC to define presence of "focal regions of restricted diffusion." We used this cut-off to exclude ADC differences attributable to tumor differentiation. [8] However, validity of this definition needs to be investigated in a larger cohort with long-term follow-up. Secondly, in our study evaluation of spatial correspondence of residual disease was performed by viewing images simultaneously on the digital viewer. An ideal evaluation of spatial correspondence should involve image fusion while maintaining uniform bladder and bowel filling. In an ongoing prospective study, we intend to validate the concept of focal restricted diffusion and adopt stringent image fusion methodology to investigate differences in spatial response to chemoradiation. [17]

 > Conclusions Top

Spatial heterogeneity in tumor diffusion predicts for partial response to chemoradiotherapy in patients with postoperative recurrences of cervical cancer. In addition, baseline ADC may reliably predict for partial response following chemoradiation in patients with bulky recurrences of cervical cancer. Evaluation of response in spatial reference to focal regions of ADC restriction will provide better understanding of radiation sensitivity of heterogeneous tumor subvolumes and provide avenues for further improvement of therapeutics.

 > References Top

1.Piura B, Rabinovich A, Friger M. Recurrent cervical carcinoma after radical hysterectomy and pelvic lymph node dissection: A study of 32 cases. Eur J Gynaecol Oncol 2008;29:31-6.  Back to cited text no. 1
2.Mahantshelly U, Banerjee S, Chopra S, Engineer R, Shrivastava SK. Clinical outcome of patients treated with template based high dose rate (HDR) interstitial brachytherapy boost in gynecological malignancies. Radiother Oncol 2011;99:S117.  Back to cited text no. 2
3.Monk BJ, Walker JL, Tewari K, Ramsinghani NS, Syed AM, DiSaia PJ. Open Interstitial Brachytherapy for the Treatment of Local-Regional Recurrences of Uterine Corpus and Cervix Cancer after Primary Surgery. J Gynecol Oncol 1994;52:222-8.  Back to cited text no. 3
4.Reesink-Peters N, van der Velden J, ten Hoor KA, Boezen HM, de Vries EG, Schilthuis MS, et al. Preoperative serum squamous cell carcinoma antigen levels in clinical decision making for patients with early-stage cervical cancer. J Clin Oncol 2005;23:1455-62.  Back to cited text no. 4
5.Liu Y, Bai R, Sun H, Liu H, Zhao X, Li Y. Diffusion-weighted imaging in predicting and monitoring the response of uterine cervical cancer to combined chemoradiation. Clin Radiol 2009;64:1067-74.  Back to cited text no. 5
6.Harry VN, Semple SI, Gilbert FJ, Parkin DE. Diffusion-weighted magnetic resonance imaging in the early detection of response to chemoradiation in cervical cancer. Gynecol Oncol 2008;111:213-20.  Back to cited text no. 6
7.McVeigh P, Syed A, Milosevic M, Fyles A, Haider M. Diffusion-weighted MRI in cervical cancer. Eur Radiol 2008;18:1058-64.  Back to cited text no. 7
8.Payne GS, Schmidt M, Morgan VA, Giles S, Bridges J, Ind T, et al. Evaluation of magnetic resonance diffusion and spectroscopy measurements as predictive biomarkers in stage 1 cervical cancer. Gynecol Oncol 2010;116:246-52.  Back to cited text no. 8
9.Koh DM, Collins DJ. Diffusion-Weighted MRI in the Body: Applications and Challenges in Oncology. AJR Am J Roentgenol 2007;188:1622-35.  Back to cited text no. 9
10.Pickles MD, Gibbs P, Lowry M, Turnbull LW. Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer. Magn Reson Imaging 2006;24:843-7.  Back to cited text no. 10
11.Lambrecht M, Vandecaveye V, De Keyzer F, Roels S, Penninckx F, Van Cutsem E, et al. Value of diffusion-weighted magnetic resonance imaging for prediction and early assessment of response to neoadjuvant radiochemotherapy in rectal cancer: Preliminary results. Int J Radiat Oncol Biol Phys 2012;82:863-70.  Back to cited text no. 11
12.Dong S, Ye XD, Yuan Z, Xu LC, Xiao XS. Relationship of apparent diffusion coefficient to survival for patients with unresectable primary hepatocellular carcinoma after chemoembolization. Eur J Radiol 2012;81:472-7.  Back to cited text no. 12
13.Vandecaveye V, Dirix P, De Keyzer F, Op de Beeck K, Poorten VV, Hauben E, et al. Diffusion-weighted magnetic resonance imaging early after chemoradiotherapy to monitor treatment response in head and neck squamous cell carcinoma. Int J Radiat Oncol Biol Phys 2012;82:1098-107.  Back to cited text no. 13
14.Nilsen L, Fangberget A, Geier O, Olsen DR, Seierstad T. Diffusion-weighted magnetic resonance imaging for pretreatment prediction and monitoring of treatment response of patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy. Acta Oncol 2010;49:354-60.  Back to cited text no. 14
15.Lyng H, Haraldseth O, Rofstad EK. Measurement of cell density and necrotic fraction in human melanoma xenografts by diffusion weighted magnetic resonance imaging. Magn Reson Med 2000;43:828-36.  Back to cited text no. 15
16.Vandecaveye V, De Keyzer F, Nuyts S, Deraedt K, Dirix P, Hamaekers P, et al. Detection of head and neck squamous cell carcinoma with diffusion weighted MRI after (chemo)radiotherapy: Correlation between radiologic and histopathologic findings. Int J Radiat Oncol Biol Phys 2007;67:960-71.  Back to cited text no. 16
17.MR-PET Guided Biologically Optimised Interstitial Brachytherapy. Available from: http://clinicaltrials.gov. [Last Accessed on 2011 Jul 10].  Back to cited text no. 17


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  [Table 1], [Table 2], [Table 3]

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