Dose comparison of robustly optimized intensity modulated proton therapy (IMPT) vs IMRT and VMAT photon plans for testicular seminoma.

BACKGROUND: Patients with stage II seminoma have traditionally been treated with photons to the retroperitoneal and iliac space, which leads to a substantial dose bath to abdominal and pelvic organs at risk (OAR). As these patients are young and with excellent prognosis, reducing dose to OAR and thereby the risk of secondary cancer is of utmost importance. We compared IMPT to opposing IMRT fields and VMAT, assessing dose to OAR and both overall and organ-specific secondary cancer risk. MATERIAL AND METHODS: A comparative treatment planning study was conducted on planning CT-scans from ten patients with stage II seminoma, treated with photons to a 'dog-leg' field with doses ranging from 20 to 25 Gy and a 10 Gy sequential boost to the metastatic lymph node(s). Photon plans were either 3-4 field IMRT (Eclipse) or 1-2 arc VMAT (Pinnacle). Proton plans used robust (5 mm; 3.5%) IMPT (Eclipse), multi field optimization with 3 posterior fields supplemented by 2 anterior fields at the level of the iliac vessels. Thirty plans were generated. Mean doses to OARs were compared for IMRT vs IMPT and VMAT vs IMPT. The risk of secondary cancer was calculated according to the model described by Schneider, using excess absolute risk (EAR, per 10,000 persons per year) for body outline, stomach, duodenum, pancreas, bowel, bladder and spinal cord. RESULTS: Mean doses to all OARs were significantly lower with IMPT except similar kidney (IMRT) and spinal cord (VMAT) doses. The relative EAR for body outline was 0.59 for IMPT/IMRT (p < .05) and 0.33 for IMPT/VMAT (p < .05). Organ specific secondary cancer risk was also lower for IMPT except for pancreas and duodenum. CONCLUSION: Proton therapy reduced radiation dose to OAR compared to both IMRT and VMAT plans, and potentially reduce the risk of secondary cancer both overall and for most OAR.

Treatment plan comparison of proton vs photon radiotherapy for lower-grade gliomas.

BACKGROUND AND PURPOSE: Patients with lower-grade gliomas are long-term survivors after radiotherapy and may benefit from the reduced dose to normal tissue achievable with proton therapy. Here, we aimed to quantify differences in dose to the uninvolved brain and contralateral hippocampus and compare the risk of radiation-induced secondary cancer for photon and proton plans for lower-grade glioma patients. MATERIALS AND METHODS: Twenty-three patients were included in this in-silico planning comparative study and had photon and proton plans calculated (50.4 Gy(RBE = 1.1), 28 Fx) applying similar dose constraints to the target and organs at risk. Automatically calculated photon plans were generated with a 3 mm margin from clinical target volume (CTV) to planning target volume. Manual proton plans were generated using robust optimisation on the CTV. Dose metrics of organs at risk were compared using population mean dose-volume histograms and Wilcoxon signed-rank test. Secondary cancer risk per 10,000 persons per year (PPY) was estimated using dose-volume data and a risk model for secondary cancer induction. RESULTS: CTV coverage (V95%>98%) was similar for the two treatment modalities. Mean dose (Dmean) to the uninvolved brain was significantly reduced from 21.5 Gy (median, IQR 17.1-24.4 Gy) with photons compared to 10.3 Gy(RBE) (8.1-13.9 Gy(RBE)) with protons. Dmean to the contralateral hippocampus was significantly reduced from 6.5 Gy (5.4-11.7 Gy) with photons to 1.5 Gy(RBE) (0.4-6.8 Gy(RBE)) with protons. The estimated secondary cancer risk was reduced from 6.7 PPY (median, range 3.3-10.4 PPY) with photons to 3.0 PPY (1.3-7.5 PPY) with protons. CONCLUSION: A significant reduction in mean dose to uninvolved brain and contralateral hippocampus was found with proton planning. The estimated secondary cancer risk was reduced with proton therapy.

Phantom-based quality assurance for multicenter quantitative MRI in locally advanced cervical cancer.

BACKGROUND AND PURPOSE: A wide variation of MRI systems is a challenge in multicenter imaging biomarker studies as it adds variation in quantitative MRI values. The aim of this study was to design and test a quality assurance (QA) framework based on phantom measurements, for the quantitative MRI protocols of a multicenter imaging biomarker trial of locally advanced cervical cancer. MATERIALS AND METHODS: Fifteen institutes participated (five 1.5 T and ten 3 T scanners). Each institute optimized protocols for T2, diffusion-weighted imaging, T1, and dynamic contrast-enhanced (DCE-)MRI according to system possibilities, institutional preferences and study-specific constraints. Calibration phantoms with known values were used for validation. Benchmark protocols, similar on all systems, were used to investigate whether differences resulted from variations in institutional protocols or from system variations. Bias, repeatability (%RC), and reproducibility (%RDC) were determined. Ratios were used for T2 and T1 values. RESULTS: The institutional protocols showed a range in bias of 0.88-0.98 for T2 (median %RC = 1%; %RDC = 12%), -0.007 to 0.029 × 10-3 mm2/s for the apparent diffusion coefficient (median %RC = 3%; %RDC = 18%), and 0.39-1.29 for T1 (median %RC = 1%; %RDC = 33%). For DCE a nonlinear vendor-specific relation was observed between measured and true concentrations with magnitude data, whereas the relation was linear when phase data was used. CONCLUSION: We designed a QA framework for quantitative MRI protocols and demonstrated for a multicenter trial for cervical cancer that measurement of consistent T2 and apparent diffusion coefficient values is feasible despite protocol differences. For DCE-MRI and T1 mapping with the variable flip angle method, this was more challenging.

Tumour subregion analysis of colorectal liver metastases using semi-automated clustering based on DCE-MRI: Comparison with histological subregions and impact on pharmacokinetic parameter analysis.

PURPOSE: To use a novel segmentation methodology based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to define tumour subregions of liver metastases from colorectal cancer (CRC), to compare these with histology, and to use these to compare extracted pharmacokinetic (PK) parameters between tumour subregions. MATERIALS AND METHODS: This ethically-approved prospective study recruited patients with CRC and ≥1 hepatic metastases scheduled for hepatic resection. Patients underwent DCE-MRI pre-metastasectomy. Histological sections of resection specimens were spatially matched to DCE-MRI acquisitions and used to define histological subregions of viable and non-viable tumour. A semi-automated voxel-wise image segmentation algorithm based on the DCE-MRI contrast-uptake curves was used to define imaging subregions of viable and non-viable tumour. Overlap of histologically-defined and imaging subregions was compared using the Dice similarity coefficient (DSC). DCE-MRI PK parameters were compared for the whole tumour and histology-defined and imaging-derived subregions. RESULTS: Fourteen patients were included in the analysis. Direct histological comparison with imaging was possible in nine patients. Mean DSC for viable tumour subregions defined by imaging and histology was 0.738 (range 0.540-0.930). There were significant differences between Ktrans and kep for viable and non-viable subregions (p < 0.001) and between whole lesions and viable subregions (p < 0.001). CONCLUSION: We demonstrate good concordance of viable tumour segmentation based on pre-operative DCE-MRI with a post-operative histological gold-standard. This can be used to extract viable tumour-specific values from quantitative image analysis, and could improve treatment response assessment in clinical practice.

Modeling Dynamic Contrast-Enhanced MRI Data with a Constrained Local AIF.

PURPOSE: This study aims to develop a constrained local arterial input function (cL-AIF) to improve quantitative analysis of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) data by accounting for the contrast-agent bolus amplitude error in the voxel-specific AIF. PROCEDURES: Bayesian probability theory-based parameter estimation and model selection were used to compare tracer kinetic modeling employing either the measured remote-AIF (R-AIF, i.e., the traditional approach) or an inferred cL-AIF against both in silico DCE-MRI data and clinical, cervical cancer DCE-MRI data. RESULTS: When the data model included the cL-AIF, tracer kinetic parameters were correctly estimated from in silico data under contrast-to-noise conditions typical of clinical DCE-MRI experiments. Considering the clinical cervical cancer data, Bayesian model selection was performed for all tumor voxels of the 16 patients (35,602 voxels in total). Among those voxels, a tracer kinetic model that employed the voxel-specific cL-AIF was preferred (i.e., had a higher posterior probability) in 80 % of the voxels compared to the direct use of a single R-AIF. Maps of spatial variation in voxel-specific AIF bolus amplitude and arrival time for heterogeneous tissues, such as cervical cancer, are accessible with the cL-AIF approach. CONCLUSIONS: The cL-AIF method, which estimates unique local-AIF amplitude and arrival time for each voxel within the tissue of interest, provides better modeling of DCE-MRI data than the use of a single, measured R-AIF. The Bayesian-based data analysis described herein affords estimates of uncertainties for each model parameter, via posterior probability density functions, and voxel-wise comparison across methods/models, via model selection in data modeling.

Diffusion tensor magnetic resonance imaging driven growth modeling for radiotherapy target definition in glioblastoma.

BACKGROUND: The clinical target volume (CTV) in radiotherapy is routinely based on gadolinium contrast enhanced T1 weighted (T1w + Gd) and T2 weighted fluid attenuated inversion recovery (T2w FLAIR) magnetic resonance imaging (MRI) sequences which have been shown to over- or underestimate the microscopic tumor cell spread. Gliomas favor spread along the white matter fiber tracts. Tumor growth models incorporating the MRI diffusion tensors (DTI) allow to account more consistently for the glioma growth. The aim of the study was to investigate the potential of a DTI driven growth model to improve target definition in glioblastoma (GBM). MATERIAL AND METHODS: Eleven GBM patients were scanned using T1w, T2w FLAIR, T1w + Gd and DTI. The brain was segmented into white matter, gray matter and cerebrospinal fluid. The Fisher-Kolmogorov growth model was used assuming uniform proliferation and a difference in white and gray matter diffusion of a ratio of 10. The tensor directionality was tested using an anisotropy weighting parameter set to zero (γ0) and twenty (γ20). The volumetric comparison was performed using Hausdorff distance, Dice similarity coefficient (DSC) and surface area. RESULTS: The median of the standard CTV (CTVstandard) was 180 cm3. The median surface area of CTVstandard was 211 cm2. The median surface area of respective CTVγ0 and CTVγ20 significantly increased to 338 and 376 cm2, respectively. The Hausdorff distance was greater than zero and significantly increased for both CTVγ0 and CTVγ20 with respective median of 18.7 and 25.2 mm. The DSC for both CTVγ0 and CTVγ20 were significantly below one with respective median of 0.74 and 0.72, which means that 74 and 72% of CTVstandard were included in CTVγ0 and CTVγ20, respectively. CONCLUSIONS: DTI driven growth models result in CTVs with a significantly increased surface area, a significantly increased Hausdorff distance and decreased overlap between the standard and model derived volume.

Are complex DCE-MRI models supported by clinical data?

PURPOSE: To ascertain whether complex dynamic contrast enhanced (DCE) MRI tracer kinetic models are supported by data acquired in the clinic and to determine the consequences of limited contrast-to-noise. METHODS: Generically representative in silico and clinical (cervical cancer) DCE-MRI data were examined. Bayesian model selection evaluated support for four compartmental DCE-MRI models: the Tofts model (TM), Extended Tofts model, Compartmental Tissue Uptake model (CTUM), and Two-Compartment Exchange model. RESULTS: Complex DCE-MRI models were more sensitive to noise than simpler models with respect to both model selection and parameter estimation. Indeed, as contrast-to-noise decreased, complex DCE models became less probable and simpler models more probable. The less complex TM and CTUM were the optimal models for the DCE-MRI data acquired in the clinic. [In cervical tumors, Ktrans, Fp, and PS increased after radiotherapy (P = 0.004, 0.002, and 0.014, respectively)]. CONCLUSION: Caution is advised when considering application of complex DCE-MRI kinetic models to data acquired in the clinic. It follows that data-driven model selection is an important prerequisite to DCE-MRI analysis. Model selection is particularly important when high-order, multiparametric models are under consideration. (Parameters obtained from kinetic modeling of cervical cancer clinical DCE-MRI data showed significant changes at an early stage of radiotherapy.) Magn Reson Med 77:1329-1339, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Comparison of linear and nonlinear implementation of the compartmental tissue uptake model for dynamic contrast-enhanced MRI.

PURPOSE: Fitting tracer kinetic models using linear methods is much faster than using their nonlinear counterparts, although this comes often at the expense of reduced accuracy and precision. The aim of this study was to derive and compare the performance of the linear compartmental tissue uptake (CTU) model with its nonlinear version with respect to their percentage error and precision. THEORY AND METHODS: The linear and nonlinear CTU models were initially compared using simulations with varying noise and temporal sampling. Subsequently, the clinical applicability of the linear model was demonstrated on 14 patients with locally advanced cervical cancer examined with dynamic contrast-enhanced magnetic resonance imaging. RESULTS: Simulations revealed equal percentage error and precision when noise was within clinical achievable ranges (contrast-to-noise ratio >10). The linear method was significantly faster than the nonlinear method, with a minimum speedup of around 230 across all tested sampling rates. Clinical analysis revealed that parameters estimated using the linear and nonlinear CTU model were highly correlated (ρ ≥ 0.95). CONCLUSION: The linear CTU model is computationally more efficient and more stable against temporal downsampling, whereas the nonlinear method is more robust to variations in noise. The two methods may be used interchangeably within clinical achievable ranges of temporal sampling and noise. Magn Reson Med 77:2414-2423, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Uncertainties of deformable image registration for dose accumulation of high-dose regions in bladder and rectum in locally advanced cervical cancer.

PURPOSE: To compare the dose accumulation for bladder and rectum by deformable image registration (DIR) and direct addition (DA) of dose volume histogram parameters in magnetic resonance image-guided adaptive brachytherapy (IGABT). Two DIR algorithms, contour- and intensity-based, also have been analyzed. METHODS AND MATERIALS: Patients (n = 21) treated with IGABT for carcinoma cervix under the IntErnational study on MRI-guided BRachytherapy in locally Advanced CErvical cancer protocol were analyzed. Each patient underwent two HDR-BT applications, 1-week apart with two fractions of 7 Gy each delivered per application. For each application, magnetic resonance imaging, volume delineation, reconstruction, treatment planning (BT1 and BT2), and dose evaluation were carried out. BT1 and BT2 images were registered using an intensity-based DIR, followed by deformable dose accumulation (DDA), which was then compared with DA. To compare the intensity-based DIR to other DIR approaches, nine patients were further evaluated using an in-house contour-based DIR algorithm for bladder dose accumulation. RESULTS: Mean (±standard deviation; range) percentage variation between DA and DDA was found to be 2.4% (±3.3;-1.8, 11.5) and 5.2% (±5.1;-1.7, 16.5) for the rectum and bladder, respectively. The differences between the DA and DDA were found to be statistically significant for both rectum (p = 0.008) and bladder (p = 0.0003). Intensity-based DIR algorithm resulted in a larger mean deviation between DDA and DA as compared with contour-based DIR, although statistically insignificant (p = 0.32). The difference between DDA and DA was 2.4 ± 2.0% and 1.3 ± 1.2%, for intensity- and contour-based DIR, respectively. CONCLUSIONS: DA of dose volume histogram parameters provides a good estimate to the dose to the organs at risk; DIR based on image intensities may lead to systematic underestimation of dose due to implausible DIR.

Inclusion of functional information from perfusion SPECT improves predictive value of dose-volume parameters in lung toxicity outcome after radiotherapy for non-small cell lung cancer: A prospective study.

BACKGROUND AND PURPOSE: To compare functional and standard dose-volume parameters as predictors of postradiation pulmonary toxicity in lung cancer patients undergoing curative chemo-radiotherapy (RT) studied prospectively. MATERIAL AND METHODS: A total of 58 patients treated with Intensity Modulated RT (60-66Gy) were analysed. Standard dose-volume parameters were extracted from treatment planning computed tomography (CT) scans. Corresponding functional dose-volume parameters were calculated from perfusion single-photon emission computed tomography (SPECT). Primary end-point was radiation pneumonitis (RP) grade 2-5. RESULTS: Functional mean lung dose (MLD) and lung volumes receiving 5, 10, 20 and 30Gy (V5-V30, respectively) revealed high correlation with corresponding standard parameters (r>0.8). Standard MLD, V20 and V30 were significantly higher in patients with RP (p=0.01). All functional parameters were significantly higher in the RP patients (p<0.03). In multivariate analysis functional parameters produced superior risk estimates, while all standard parameters, except V30, were not related to the risk of RP. Area under the curve (AUC) for functional metrics generally exceeded the AUC for corresponding standard parameters, but they were not significantly different from each other. CONCLUSION: SPECT-based functional parameters were better to predict the risk of RP compared to standard CT-based dose-volume parameters. Functional parameters may be useful to guide radiotherapy planning in order to reduce the risk of radiation-induced toxicity.

A method for selection of beam angles robust to intra-fractional motion in proton therapy of lung cancer.

BACKGROUND: Proton therapy offers the potential for sparing the normal tissue surrounding the target. However, due to well-defined proton ranges around the Bragg peak, dose deposition is more sensitive to changes in the water equivalent path length (WEPL) than with photons. In this study, we assess WEPL variations caused by breathing-induced motion for all possible beam angles in a series of lung cancer patients. By studying the association between measures for WEPL variation and breathing-induced target dose degradation we aimed to develop and explore a tool to identify beam angles that are robust to patient-specific patterns of intra-fractional motion. MATERIAL AND METHODS: Using four-dimensional computed tomography (4DCT) images of three lung cancer patients we evaluated the impact of the WEPL changes on target dose coverage for a series of coplanar single-beam plans. The plans were optimised for the internal target volume (ITV) at the maximum intensity projection (MIP) CT for every 3° gantry interval. The plans were transferred to the ten 4DCT phases and the average reduction in ITV V95 over the ten phases, relative to the original MIP CT calculation, was quantified. The target dose reduction was associated with the mean difference between the WEPL and the phase-averaged WEPL computed for all beam rays across all possible gantry-couch angle combinations. RESULTS: The gantry-couch angle maps showed areas of both high and low WEPL variation, with overall quite similar patterns yet with individual differences reflecting differences in tumour position and breathing-induced motion. The coplanar plans showed a strong association between WEPL changes and ITV V95 reduction, with a correlation coefficient ranging between 0.92 and 0.98 for the three patients (p < 0.01). CONCLUSION: We have presented a 4DCT-based method to quantify WEPL changes during the breathing cycle. The method identified proton field gantry-couch angle combinations that were either sensitive or robust to WEPL changes. WEPL variations along the beam path were associated with target under-dosage.

Correction of diffusion-weighted magnetic resonance imaging for brachytherapy of locally advanced cervical cancer.

BACKGROUND: Geometrical distortion is a major obstacle for the use of echo planar diffusion-weighted magnetic resonance imaging (DW-MRI) in planning of radiotherapy. This study compares geometrical distortion correction methods of DW-MRI at time of brachytherapy (BT) in locally advanced cervical cancer patients. MATERIAL AND METHODS: In total 21 examinations comprising DW-MRI, dual gradient echo (GRE) for B0 field map calculation and T2-weighted (T2W) fat-saturated MRI of eight patients with locally advanced cervical cancer were acquired during BT with a plastic tandem and ring applicator in situ. The ability of B0 field map correction (B0M) and deformable image registration (DIR) to correct DW-MRI geometric image distortion was compared to the non-corrected DW-MRI including evaluation of apparent diffusion coefficient (ADC) for the gross tumor volume (GTV). RESULTS: Geometrical distortion correction decreased tandem displacement from 3.3 ± 0.9 mm (non-corrected) to 2.9 ± 1.0 mm (B0M) and 1.9 ± 0.6 mm (DIR), increased mean normalized cross-correlation from 0.69 ± 0.1 (non- corrected) to 0.70 ± 0.10 (B0M) and 0.77 ± 0.1 (DIR), and increased the Jaccard similarity coefficient from 0.72 ± 0.1 (non-corrected) to 0.73 ± 0.06 (B0M) and 0.77 ± 0.1 (DIR). For all parameters only DIR corrections were significant (p < 0.05). ADC of the GTV did not change significantly with either correction method. CONCLUSION: DIR significantly improved geometrical accuracy of DW-MRI, with remaining residual uncertainties of less than 2 mm, while no significant improvement was seen using B0 field map correction.

Proof of principle: Applicator-guided stereotactic IMRT boost in combination with 3D MRI-based brachytherapy in locally advanced cervical cancer.

PURPOSE: To describe a new technique involving high-precision stereotactic intensity-modulated radiation therapy (IMRT) boost in combination with intracavitary-interstitial (IC-IS) brachytherapy (BT) in cervical tumors that cannot be sufficiently covered by IC-IS-BT due to extensive residual disease and/or difficult topography at the time of BT. METHODS AND MATERIALS: Three patients with stage IIIB-IVA cervical cancer had significant residual disease at the time of BT. MRI-guided IC-IS-BT (pulsed-dose rate) was combined with a stereotactic IMRT boost guided according to the BT applicator in situ, using cone beam CT. The planning aim dose (total external beam radiotherapy and BT) for the high-risk clinical target volume (HR-CTV) was D90 >70-85 Gy, whereas constraints for organs at risk were D2cm3 <70 Gy for rectum, sigmoid, and bowel and <90 Gy for bladder in terms of equivalent total dose in 2 Gy fractions. An IMRT boost adapted to the BT dose distribution was optimized to target the regions poorly covered by BT. RESULTS: HR-CTV doses of D90 >81 Gy were obtained in the central HR-CTV and D90 >69 Gy in the distal regions of HR-CTV. Image-guided set up of the IMRT boost with the applicator in situ was feasible. The dose plans were robust to intra-fraction uncertainties of 3 mm. Local control with acceptable morbidity was obtained at a followup of 3, 2.5, and 1 year, respectively. CONCLUSIONS: The combination of MRI-guided BT with an applicator-guided stereotactic IMRT boost is feasible. This technique seems to be useful in the few cases where HR-CTV coverage cannot be obtained even with IS-IC-BT.

Clinical validation of a 4D-CT based method for lung ventilation measurement in phantoms and patients.

BACKGROUND: Lung cancer patients referred to radiotherapy (RT) often present with regional lung function deficits, and it is therefore of interest to image their lung function prior to treatment. In this study a method was developed that uses a deformable image registration (DIR) between the peak-inhale and peak-exhale phases of a thoracic four-dimensional computed tomography (4D-CT) scan to extract ventilation information. The method calculates the displacement vector fields (DVFs) resulting from the DIR using the Jacobian map approach in order to extract information regarding regional lung volume change. MATERIAL AND METHODS: The DVFs resulting from DIRs were analysed to compute the Jacobian determinant of vectors in the field, thus obtaining a map of the vector gradients of the entire registered CT image, i.e. voxel-wise local volume change. Geometric and quantitative validation was achieved using images of both phantoms and patients. In the phantom studies, translations and deformations of known size and direction were introduced to validate both the DIR algorithm and the method as a whole. Furthermore, five patients underwent 4D-CT for planning of stereotactic body RT (SBRT). The patients were immobilised in a stereotactic body frame (SBF) and for each patient, two thoracic 4D-CT scans were acquired, one scan with respiration restricted by an abdominal compression plate and the other under free breathing. RESULTS: In the phantom studies deformation errors were found to be of the order of the expected precision of 3 mm, corresponding to the image slice distance, in lateral and vertical directions. For the longitudinal direction a more pronounced discrepancy was observed, with the algorithm predicting displacement lengths of less than half of the physically introduced deformation. Qualitatively the method performed as expected. In the patient study an inverse consistency test showed deviations of up to 5.8 mm, i.e. almost twice the image slice separation. Jacobian maps of the patient images indicated well-ventilated areas as anatomically expected. CONCLUSION: The established method provides a means of using a (commercially available) DIR algorithm to obtain a quantitative measure of local lung volume change. With further phantom and patient validation studies, quantitative maps of specific ventilation should be possible to produce and use in a clinical setting.

Apparent diffusion coefficients in GEC ESTRO target volumes for image guided adaptive brachytherapy of locally advanced cervical cancer.

BACKGROUND AND PURPOSE: T2 weighted MRI is recommended for image guided adaptive brachytherapy (IGABT) in cervical cancer. Diffusion weighted imaging (DWI) and the derived apparent diffusion coefficient (ADC) may add additional biological information on tumour cell density. The purpose of this study was to evaluate the distribution of the ADC within target volumes as recommended by GEC-ESTRO: Gross Tumour Volume at BT (GTV(BT)), High-Risk Clinical Tumour Volume (HR-CTV) and Intermediate-Risk Clinical Target Volume (IR-CTV) and to evaluate the change of diffusion between fractions of IGABT. MATERIAL AND METHODS: Fifteen patients with locally advanced cervical cancer were examined by MRI before their first (BT1) and second (BT2) fraction of IGABT, resulting in a total of 30 MR examinations including both T2 weighted and DWI sequences. The Apparent Diffusion Coefficient (ADC) was calculated by use of three levels of b-values (0, 600, 1000 s/mm(2)). ADC maps were constructed and fused with the GEC ESTRO target contours. The mean ADC value within each target volume was calculated. Furthermore, volumes of low diffusion (ADC(low)) were defined based on an ADC threshold of 1.2 × 10(-3) mm(2)/s, and overlap with target volumes was evaluated. Change of ADC level in target volumes and change of ADC(low) volume from BT1 to BT2 was also evaluated. RESULTS: The mean ADC was significantly lower in GTV(BT) than in HR-CTV (p<0.001) which again was significantly lower than in IR-CTV (p<0.001). There was no significant change of the ADC(low) volume or ADC level within each target structure between BT1 and BT2 (p=0.242). All three GEC-ESTRO volumes contained volumes with low diffusion. The GTV(BT) contained 37.2% volume of low diffusion, HR-CTV 20.3% and IR-CTV 10.8%. CONCLUSION: With DWI we were able to find a significant difference in ADC-values for the three different GEC ESTRO targets. This supports the assumption that the target volumes used for dose prescription in IGABT contain tissues with different characteristics, with the tumour (GTV(BT)) being the volume with the lowest diffusion. No significant changes were found from BT1 to BT2 indicating that changes of ADC level and volumes are stable at the time of BT. Further studies are needed to evaluate the role of DWI in target contouring and dose prescription for IGABT.