Variability in prostate and seminal vesicle delineations defined on magnetic resonance images, a multi-observer, -center and -sequence study

Improvement in male pelvis magnetic resonance image contouring following radiologist-delivered training

INTRODUCTION

The magnetic resonance linear accelerator (MRL) combines both magnetic resonance imaging and a linear accelerator, allowing for daily treatment adaptation. This study aimed to assess the impact of radiologist-delivered training in magnetic resonance (MR) contouring of relevant structures within the male pelvis.

METHODS

Two radiation oncologists, two radiation oncology registrars and seven radiation therapists completed contouring on 10 male pelvis MR datasets both pre- and post-training. A 2-hour MR anatomy training session was delivered by a radiologist, who also provided the 'gold standard' contours. The pre- and post-training contours were compared against the gold standard with Dice similarity coefficient (DSC) and Hausdorff distances calculated; and the pre- and post-confidence scores and timing were compared.

RESULTS

The improvement in DSC were significant in prostate, rectum and seminal vesicles, with a post-training median DSC of 0.87 ± 0.06, 0.92 ± 0.04 and 0.80 ± 0.14, respectively. The median Hausdorff improved with a median of 1.46 ± 0.78 mm, 0.52 ± 0.32 mm and 1.11 ± 0.86 mm for prostate, rectum and seminal vesicles, respectively. Bladder concordance was high both pre- and post-training. Urethra contours improved post-training, however, remained difficult to contour with a median post-DSC of 0.51 ± 0.24. Overall, confidence scoring improved (P < 0.001) and timing decreased by an average of 4.4 ± 16.4 min post-training.

CONCLUSION

Radiologist-delivered training improved concordance of male pelvis contouring on MR datasets. Further work is required in the identification of urethra on MRs. These findings are of importance in the MRL adaptive workflow.

Reference standard for the evaluation of automatic segmentation algorithms: Quantification of inter observer variability of manual delineation of prostate contour on MRI

PURPOSE

The purpose of this study was to investigate the relationship between inter-reader variability in manual prostate contour segmentation on magnetic resonance imaging (MRI) examinations and determine the optimal number of readers required to establish a reliable reference standard.

MATERIALS AND METHODS

Seven radiologists with various experiences independently performed manual segmentation of the prostate contour (whole-gland [WG] and transition zone [TZ]) on 40 prostate MRI examinations obtained in 40 patients. Inter-reader variability in prostate contour delineations was estimated using standard metrics (Dice similarity coefficient [DSC], Hausdorff distance and volume-based metrics). The impact of the number of readers (from two to seven) on segmentation variability was assessed using pairwise metrics (consistency) and metrics with respect to a reference segmentation (conformity), obtained either with majority voting or simultaneous truth and performance level estimation (STAPLE) algorithm.

RESULTS

The average segmentation DSC for two readers in pairwise comparison was 0.919 for WG and 0.876 for TZ. Variability decreased with the number of readers: the interquartile ranges of the DSC were 0.076 (WG) / 0.021 (TZ) for configurations with two readers, 0.005 (WG) / 0.012 (TZ) for configurations with three readers, and 0.002 (WG) / 0.0037 (TZ) for configurations with six readers. The interquartile range decreased slightly faster between two and three readers than between three and six readers. When using consensus methods, variability often reached its minimum with three readers (with STAPLE, DSC = 0.96 [range: 0.945-0.971] for WG and DSC = 0.94 [range: 0.912-0.957] for TZ, and interquartile range was minimal for configurations with three readers.

CONCLUSION

The number of readers affects the inter-reader variability, in terms of inter-reader consistency and conformity to a reference. Variability is minimal for three readers, or three readers represent a tipping point in the variability evolution, with both pairwise-based metrics or metrics with respect to a reference. Accordingly, three readers may represent an optimal number to determine references for artificial intelligence applications.

Accuracy of deformable image registration-based intra-fraction motion management in Magnetic Resonance-guided radiotherapy

Background and Purpose

Intra-fraction motion management is key in Stereotactic Ablative Radiotherapy (SABR) gated delivery. This study assessed the accuracy of automatic tumor segmentation in the delivery of MR-guided radiotherapy (MRgRT) by comparing it to manual delineations performed by experienced observers.

Materials and Methods

Twenty patients previously treated with MR-guided SABR for thoracic and abdominal tumors were included. Five observers with at least two years of experience in MRgRT manually delineated the gross tumor volume (GTV) for 20 patients on 240 frames of a cine MRI on a sagittal plane. Deformable Image Registration (DIR) based GTV contours were propagated using four different algorithms from a reference frame to subsequent frames.Geometrical analysis based on the Dice Similarity Coefficient (DSC), centroid distance and Hausdorff Distance (HDD) were performed to assess the inter-observer variability and the accuracy of automatic segmentation. A Confidence Value (CV) metric for the reliability of the tumor auto-contouring was also calculated.

Results

Inter-observer delineation variability resulted in mean DSC of 0.89, HDD of 5.8 mm and centroid distance of 1.7 mm. Tumor auto-contouring by the four DIR algorithms resulted in an excellent agreement with the manual delineations by the experienced observers. Mean DSC for each algorithm across all patients was greater than 0.90, whereas the HDD and centroid distances were below 4.0 mm and 1.5 mm, respectively. The CV showed a strong correlation with the DSC.

Conclusions

DIR-based auto-contouring in MRgRT exhibited a high level of agreement with the manual contouring performed by experts, allowing accurate gated delivery.

Parameters from site classification to harmonize MRI clinical studies: Application to a multi-site Parkinson's disease dataset

Multi‐site MRI datasets are crucial for big data research. However, neuroimaging studies must face the batch effect. Here, we propose an approach that uses the predictive probabilities provided by Gaussian processes (GPs) to harmonize clinical‐based studies. A multi‐site dataset of 216 Parkinson's disease (PD) patients and 87 healthy subjects (HS) was used. We performed a site GP classification using MRI data. The outcomes estimated from this classification, redefined like Weighted HARMonization PArameters (WHARMPA), were used as regressors in two different clinical studies: A PD versus HS machine learning classification using GP, and a VBM comparison (FWE‐p < .05, k = 100). Same studies were also conducted using conventional Boolean site covariates, and without information about site belonging. The results from site GP classification provided high scores, balanced accuracy (BAC) was 98.39% for grey matter images. PD versus HS classification performed better when the WHARMPA were used to harmonize (BAC = 78.60%; AUC = 0.90) than when using the Boolean site information (BAC = 56.31%; AUC = 0.71) and without it (BAC = 57.22%; AUC = 0.73). The VBM analysis harmonized using WHARMPA provided larger and more statistically robust clusters in regions previously reported in PD than when the Boolean site covariates or no corrections were added to the model. In conclusion, WHARMPA might encode global site‐effects quantitatively and allow the harmonization of data. This method is user‐friendly and provides a powerful solution, without complex implementations, to clean the analyses by removing variability associated with the differences between sites.

Federated learning for multi-center imaging diagnostics: a simulation study in cardiovascular disease

Deep learning models can enable accurate and efficient disease diagnosis, but have thus far been hampered by the data scarcity present in the medical world. Automated diagnosis studies have been constrained by underpowered single-center datasets, and although some results have shown promise, their generalizability to other institutions remains questionable as the data heterogeneity between institutions is not taken into account. By allowing models to be trained in a distributed manner that preserves patients’ privacy, federated learning promises to alleviate these issues, by enabling diligent multi-center studies. We present the first simulated federated learning study on the modality of cardiovascular magnetic resonance and use four centers derived from subsets of the M&M and ACDC datasets, focusing on the diagnosis of hypertrophic cardiomyopathy. We adapt a 3D-CNN network pretrained on action recognition and explore two different ways of incorporating shape prior information to the model, and four different data augmentation set-ups, systematically analyzing their impact on the different collaborative learning choices. We show that despite the small size of data (180 subjects derived from four centers), the privacy preserving federated learning achieves promising results that are competitive with traditional centralized learning. We further find that federatively trained models exhibit increased robustness and are more sensitive to domain shift effects.

Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer

Background

The evaluation of automatic segmentation algorithms is commonly performed using geometric metrics. An analysis based on dosimetric parameters might be more relevant in clinical practice but is often lacking in the literature. The aim of this study was to investigate the impact of state-of-the-art 3D U-Net-generated organ delineations on dose optimization in radiation therapy (RT) for prostate cancer patients.

Methods

A database of 69 computed tomography images with prostate, bladder, and rectum delineations was used for single-label 3D U-Net training with dice similarity coefficient (DSC)-based loss. Volumetric modulated arc therapy (VMAT) plans have been generated for both manual and automatic segmentations with the same optimization settings. These were chosen to give consistent plans when applying perturbations to the manual segmentations. Contours were evaluated in terms of DSC, average and 95% Hausdorff distance (HD). Dose distributions were evaluated with the manual segmentation as reference using dose volume histogram (DVH) parameters and a 3%/3 mm gamma-criterion with 10% dose cut-off. A Pearson correlation coefficient between DSC and dosimetric metrics, i.e. gamma index and DVH parameters, has been calculated.

Results

3D U-Net-based segmentation achieved a DSC of 0.87 (0.03) for prostate, 0.97 (0.01) for bladder and 0.89 (0.04) for rectum. The mean and 95% HD were below 1.6 (0.4) and below 5 (4) mm, respectively. The DVH parameters, V\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{60/65/70\,{\mathrm{Gy}}}$$\end{document}60/65/70Gy for the bladder and V\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{50/65/70\,{\mathrm{Gy}}}$$\end{document}50/65/70Gy for the rectum, showed agreement between dose distributions within \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pm \, 5\%$$\end{document}±5% and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pm \,2\%$$\end{document}±2%, respectively. The D\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{98/2\%}$$\end{document}98/2% and V\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{95\%}$$\end{document}95%, for prostate and its 3 mm expansion (surrogate clinical target volume) showed agreement with the reference dose distribution within 2% and 3 Gy with the exception of one case. The average gamma pass-rate was 85%. The comparison between geometric and dosimetric metrics showed no strong statistically significant correlation.

Conclusions

The 3D U-Net developed for this work achieved state-of-the-art geometrical performance. Analysis based on clinically relevant DVH parameters of VMAT plans demonstrated neither excessive dose increase to OARs nor substantial under/over-dosage of the target in all but one case. Yet the gamma analysis indicated several cases with low pass rates. The study highlighted the importance of adding dosimetric analysis to the standard geometric evaluation.

A rapid review of influential factors and appraised solutions on organ delineation uncertainties reduction in radiotherapy

Background and purpose.Accurate volume delineation plays an essential role in radiotherapy. Contouring is a potential source of uncertainties in radiotherapy treatment planning that could affect treatment outcomes. Therefore, reducing the degree of contouring uncertainties is crucial. The role of utilized imaging modality in the organ delineation uncertainties has been investigated. This systematic review explores the influential factors on inter-and intra-observer uncertainties of target volume and organs at risk (OARs) delineation focusing on the used imaging modality for these uncertainties reduction and the reported subsequent histopathology and follow-up assessment.Methods and materials.An inclusive search strategy has been conducted to query the available online databases (Scopus, Google Scholar, PubMed, and Medline). 'Organ at risk', 'target', 'delineation', 'uncertainties', 'radiotherapy' and their relevant terms were utilized using every database searching syntax. Final article extraction was performed following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Included studies were limited to the ones published in English between 1995 and 2020 and that just deal with computed tomography (CT) and magnetic resonance imaging (MRI) modalities.Results.A total of 923 studies were screened and 78 were included of which 31 related to the prostate 20 to the breast, 18 to the head and neck, and 9 to the brain tumor site. 98% of the extracted studies performed volumetric analysis. Only 24% of the publications reported the dose deviations resulted from variation in volume delineation Also, heterogeneity in studied populations and reported geometric and volumetric parameters were identified such that quantitative synthesis was not appropriate.Conclusion.This review highlightes the inter- and intra-observer variations that could lead to contouring uncertainties and impede tumor control in radiotherapy. For improving volume delineation and reducing inter-observer variability, the implementation of well structured training programs, homogeneity in following consensus and guidelines, reliable ground truth selection, and proper imaging modality utilization could be clinically beneficial.

The impact of image acquisition time on registration, delineation and image quality for magnetic resonance guided radiotherapy of prostate cancer patients

Background and Purpose

Magnetic resonance (MR) guided radiotherapy utilizes MR images for (online) plan adaptation and image guidance. The aim of this study was to investigate the impact of variation in MR acquisition time and scan resolution on image quality, interobserver variation in contouring and interobserver variation in registration.

Materials and Methods

Nine patients with prostate cancer were included. Four T2-weighted 3D turbo spin echo (T2w 3D TSE) sequences were acquired with different acquisition times and resolutions. Two radiologists assessed image quality, conspicuity of the capsule, peripheral zone and central gland architecture and motion artefacts on a 5 point scale. Images were delineated by two radiation oncologists and interobserver variation was assessed by the 95% Hausdorff distance. Seven observers registered the MR images on the planning CT. Registrations were compared on systematic offset and interobserver variation.

Results

Acquisition times ranged between 1.3 and 6.3 min. Overall image quality and capsule definition were significantly worse for the MR sequence with an acquisition time of 1.3 min compared to the other sequences. Median 95% Hausdorff distance showed no significant differences in interobserver variation of contouring. Systematic offset and interobserver variation in registration were small (<1 mm) and of no clinical significance.

Conclusions

Our results can be used to effectively shorten overall fraction time for online adaptive MR guided radiotherapy by optimising the imaging sequence used for registration. From the sequences studied, a sequence of 3.1 min with anisotropic voxels of 1.2 × 1.2 × 2.4 mm³ provided the shortest acquisition time without compromising image quality.

Clinical experience and cost evaluation of magnetic resonance imaging -only workflow in radiation therapy planning of prostate cancer

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Using MRI-only for prostate cancer radiation therapy planning (RTP) can reduce costs.

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An MRI-only workflow is particularly suitable for medium-sized and large departments.

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Omitting CT in the RTP workflow saves scanner, staff, and patient time.

Background and purpose

In radiation therapy (RT), significant improvements have been made recently particularly in the practices of planning imaging. This study aimed to conduct a cost evaluation between magnetic resonance imaging (MRI) -only and combined computed tomography (CT) and MRI workflows.

Materials and methods

The time-driven activity-based costing (TDABC) model was used to conduct a cost evaluation between the two workflows in those steps, where cost differences were expected. Costs were divided into capital costs and operational costs. The former consisted of fixed, one-time expenses, e.g. the purchase of a scanner, whereas the latter were partially based on the amount of activity consumed i.e. time required for image acquisition, image registration and structure contouring.

Results

In a review over a period of 10 years for 300 annual prostate cancer patients, the total cost of the workflow steps included in the study for an individual patient applying the MRI-only workflow was 903 € (100%), comprised of 537 € (59%) capital costs and 366 € (41%) operational costs. The corresponding total cost for an individual patient applying the CT + MRI workflow was 922 € (100%), comprised of 197 € (21%) capital costs and 726 € (79%) operational costs. In 10 years for 3000 patients, a total saving of 58,544 € (2%) was achieved with the MRI-only workflow compared with the dual imaging workflow.

Conclusions

MRI-only workflow is a feasible and economic way to perform clinical RT for localized prostate cancer, in particular for medium- and large-sized departments treating a sufficient number of patients.

Novel methodology to assess the effect of contouring variation on treatment outcome

PURPOSE

Contouring variation is one of the largest systematic uncertainties in radiotherapy, yet its effect on clinical outcome has never been analyzed quantitatively. We propose a novel, robust methodology to locally quantify target contour variation in a large patient cohort and find where this variation correlates with treatment outcome. We demonstrate its use on biochemical recurrence for prostate cancer patients.

METHOD

We propose to compare each patient's target contours to a consistent and unbiased reference. This reference was created by auto-contouring each patient's target using an externally trained deep learning algorithm. Local contour deviation measured from the reference to the manual contour was projected to a common frame of reference, creating contour deviation maps for each patient. By stacking the contour deviation maps, time to event was modeled pixel-wise using a multivariate Cox proportional hazards model (CPHM). Hazard ratio (HR) maps for each covariate were created, and regions of significance found using cluster-based permutation testing on the z-statistics. This methodology was applied to clinical target volume (CTV) contours, containing only the prostate gland, from 232 intermediate- and high-risk prostate cancer patients. The reference contours were created using ADMIRE® v3.4 (Elekta AB, Sweden). Local contour deviations were computed in a spherical coordinate frame, where differences between reference and clinical contours were projected in a 2D map corresponding to sampling across the coronal and transverse angles every 3°. Time to biochemical recurrence was modeled using the pixel-wise CPHM analysis accounting for contour deviation, patient age, Gleason score, and treated CTV volume.

RESULTS

We successfully applied the proposed methodology to a large patient cohort containing data from 232 patients. In this patient cohort, our analysis highlighted regions where the contour variation was related to biochemical recurrence, producing expected and unexpected results: (a) the interface between prostate-bladder and prostate-seminal vesicle interfaces where increase in the manual contour relative to the reference was related to a reduction of risk of biochemical recurrence by 4-8% per mm and (b) the prostate's right, anterior and posterior regions where an increase in the manual contour relative to the reference contours was related to an increase in risk of biochemical recurrence by 8-24% per mm.

CONCLUSION

We proposed and successfully applied a novel methodology to explore the correlation between contour variation and treatment outcome. We analyzed the effect of contour deviation of the prostate CTV on biochemical recurrence for a cohort of more than 200 prostate cancer patients while taking basic clinical variables into account. Applying this methodology to a larger dataset including additional clinically important covariates and externally validating it can more robustly identify regions where contour variation directly relates to treatment outcome. For example, in the prostate case we use to demonstrate our novel methodology, external validation will help confirm or reject the counter-intuitive results (larger contours resulting in higher risk). Ultimately, the results of this methodology could inform contouring protocols based on actual patient outcomes.

Reduction of inter-observer contouring variability in daily clinical practice through a retrospective, evidence-based intervention

BACKGROUND

Inter-observer variations (IOVs) arising during contouring can potentially impact plan quality and patient outcomes. Regular assessment of contouring IOV is not commonly performed in clinical practice due to the large time commitment required of clinicians from conventional methods. This work uses retrospective information from past treatment plans to facilitate a time-efficient, evidence-based intervention to reduce contouring IOV.

METHODS

The contours of 492 prostate cancer treatment plans created by four radiation oncologists were analyzed in this study. Structure volumes, lengths, and DVHs were extracted from the treatment planning system and stratified based on primary oncologist and inclusion of a pelvic lymph node (PLN) target. Inter-observer variations and their dosimetric consequences were assessed using Student's t-tests. Results of this analysis were presented at an intervention meeting, where new consensus contour definitions were agreed upon. The impact of the intervention was assessed one-year later by repeating the analysis on 152 new plans.

RESULTS

Significant IOV in prostate and PLN target delineation existed pre-intervention between oncologists, impacting dose to nearby OARs. IOV was also present for rectum and penile-bulb structures. Post-intervention, IOV decreased for all previously discordant structures. Dosimetric variations were also reduced. Although target contouring concordance increased significantly, some variations still persisted for PLN structures, highlighting remaining areas for improvement.

CONCLUSION

We detected significant contouring IOV in routine practice using easily accessible retrospective data and successfully decreased IOV in our clinic through a reflective intervention. Continued application of this approach may aid improvements in practice standardization and enhance quality of care.

Data Augmentation and Transfer Learning to Improve Generalizability of an Automated Prostate Segmentation Model

OBJECTIVE. Deep learning applications in radiology often suffer from overfitting, limiting generalization to external centers. The objective of this study was to develop a high-quality prostate segmentation model capable of maintaining a high degree of performance across multiple independent datasets using transfer learning and data augmentation. MATERIALS AND METHODS. A retrospective cohort of 648 patients who underwent prostate MRI between February 2015 and November 2018 at a single center was used for training and validation. A deep learning approach combining 2D and 3D architecture was used for training, which incorporated transfer learning. A data augmentation strategy was used that was specific to the deformations, intensity, and alterations in image quality seen on radiology images. Five independent datasets, four of which were from outside centers, were used for testing, which was conducted with and without fine-tuning of the original model. The Dice similarity coefficient was used to evaluate model performance. RESULTS. When prostate segmentation models utilizing transfer learning were applied to the internal validation cohort, the mean Dice similarity coefficient was 93.1 for whole prostate and 89.0 for transition zone segmentations. When the models were applied to multiple test set cohorts, the improvement in performance achieved using data augmentation alone was 2.2% for the whole prostate models and 3.0% for the transition zone segmentation models. However, the best test-set results were obtained with models fine-tuned on test center data with mean Dice similarity coefficients of 91.5 for whole prostate segmentation and 89.7 for transition zone segmentation. CONCLUSION. Transfer learning allowed for the development of a high-performing prostate segmentation model, and data augmentation and fine-tuning approaches improved performance of a prostate segmentation model when applied to datasets from external centers.

Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy

PURPOSE

Image-guided radiation therapy could benefit from implementing adaptive radiation therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone-beam computed tomography (CBCT)-to-synthetic CT (sCT) conversion algorithm was evaluated regarding image quality, image segmentation and dosimetric accuracy for head and neck (H&N), thoracic and pelvic body regions.

METHODS

Using a cycle-GAN, three body site-specific models were priorly trained with independent paired CT and CBCT datasets of a kV imaging system (XVI, Elekta). sCT were generated based on first-fraction CBCT for 15 patients of each body region. Mean errors (ME) and mean absolute errors (MAE) were analyzed for the sCT. On the sCT, manually delineated structures were compared to deformed structures from the planning CT (pCT) and evaluated with standard segmentation metrics. Treatment plans were recalculated on sCT. A comparison of clinically relevant dose-volume parameters (D₉₈, D₅₀ and D₂ of the target volume) and 3D-gamma (3%/3mm) analysis were performed.

RESULTS

The mean ME and MAE were 1.4, 29.6, 5.4 Hounsfield units (HU) and 77.2, 94.2, 41.8 HU for H&N, thoracic and pelvic region, respectively. Dice similarity coefficients varied between 66.7 ± 8.3% (seminal vesicles) and 94.9 ± 2.0% (lungs). Maximum mean surface distances were 6.3 mm (heart), followed by 3.5 mm (brainstem). The mean dosimetric differences of the target volumes did not exceed 1.7%. Mean 3D gamma pass rates greater than 97.8% were achieved in all cases.

CONCLUSIONS

The presented method generates sCT images with a quality close to pCT and yielded clinically acceptable dosimetric deviations. Thus, an important prerequisite towards clinical implementation of CBCT-based ART is fulfilled.

Harmonization of Brain Diffusion MRI: Concepts and Methods

MRI diffusion data suffers from significant inter- and intra-site variability, which hinders multi-site and/or longitudinal diffusion studies. This variability may arise from a range of factors, such as hardware, reconstruction algorithms and acquisition settings. To allow a reliable comparison and joint analysis of diffusion data across sites and over time, there is a clear need for robust data harmonization methods. This review article provides a comprehensive overview of diffusion data harmonization concepts and methods, and their limitations. Overall, the methods for the harmonization of multi-site diffusion images can be categorized in two main groups: diffusion parametric map harmonization (DPMH) and diffusion weighted image harmonization (DWIH). Whereas DPMH harmonizes the diffusion parametric maps (e.g., FA, MD, and MK), DWIH harmonizes the diffusion-weighted images. Defining a gold standard harmonization technique for dMRI data is still an ongoing challenge. Nevertheless, in this paper we provide two classification tools, namely a feature table and a flowchart, which aim to guide the readers in selecting an appropriate harmonization method for their study.

Validation of automated magnetic resonance image segmentation for radiation therapy planning in prostate cancer

Background and purpose

Magnetic resonance imaging (MRI) is increasingly used in radiation therapy planning of prostate cancer (PC) to reduce target volume delineation uncertainty. This study aimed to assess and validate the performance of a fully automated segmentation tool (AST) in MRI based radiation therapy planning of PC.

Material and methods

Pelvic structures of 65 PC patients delineated in an MRI-only workflow according to established guidelines were included in the analysis. Automatic vs manual segmentation by an experienced oncologist was compared with geometrical parameters, such as the dice similarity coefficient (DSC). Fifteen patients had a second MRI within 15 days to assess repeatability of the AST for prostate and seminal vesicles. Furthermore, we investigated whether hormonal therapy or body mass index (BMI) affected the AST results.

Results

The AST showed high agreement with manual segmentation expressed as DSC (mean, SD) for delineating prostate (0.84, 0.04), bladder (0.92, 0.04) and rectum (0.86, 0.04). For seminal vesicles (0.56, 0.17) and penile bulb (0.69, 0.12) the respective agreement was moderate. Performance of AST was not influenced by neoadjuvant hormonal therapy, although those on treatment had significantly smaller prostates than the hormone-naïve patients (p < 0.0001). In repeat assessment, consistency of prostate delineation resulted in mean DSC of 0.89, (SD 0.03) between the paired MRI scans for AST, while mean DSC of manual delineation was 0.82, (SD 0.05).

Conclusion

Fully automated MRI segmentation tool showed good agreement and repeatability compared with manual segmentation and was found clinically robust in patients with PC. However, manual review and adjustment of some structures in individual cases remain important in clinical use.

Comparison of prostate delineation on multimodality imaging for MR-guided radiotherapy

OBJECTIVE:

With increasing incorporation of MRI in radiotherapy, we investigate two MRI sequences for prostate delineation in radiographer-led image guidance.

METHODS:

Five therapeutic radiographers contoured the prostate individually on CT, T2 weighted (T2W) and T2* weighted (T2*W) imaging for 10 patients. Contours were analysed with Monaco ADMIRE (research v. 2.0) to assess interobserver variability and accuracy by comparison with a gold standard clinician contour. Observers recorded time taken for contouring and scored image quality and confidence in contouring.

RESULTS:

There is good agreement when comparing radiographer contours to the gold-standard for all three imaging types with Dice similarity co-efficient 0.91-0.94, Cohen's κ 0.85-0.91, Hausdorff distance 4.6-7.6 mm and mean distance between contours 0.9-1.2 mm. In addition, there is good concordance between radiographers across all imaging modalities. Both T2W and T2*W MRI show reduced interobserver variability and improved accuracy compared to CT, this was statistically significant for T2*W imaging compared to CT across all four comparison metrics. Comparing MRI sequences reveals significantly reduced interobserver variability and significantly improved accuracy on T2*W compared to T2W MRI for DSC and Cohen's κ. Both MRI sequences scored significantly higher compared to CT for image quality and confidence in contouring, particularly T2*W. This was also reflected in the shorter time for contouring, measuring 15.4, 9.6 and 9.8 min for CT, T2W and T2*W MRI respectively. Conclusion: Therapeutic radiographer prostate contours are more accurate, show less interobserver variability and are more confidently and quickly outlined on MRI compared to CT, particularly using T2*W MRI. Advances in knowledge: Our work is relevant for MRI sequence choice and development of the roles of the interprofessional team in the advancement of MRI-guided radiotherapy.

Basic concepts and applications of functional magnetic resonance imaging for radiotherapy of prostate cancer

Recently, the interest to integrate magnetic resonance imaging (MRI) in radiotherapy for prostate cancer has increased considerably. MRI can contribute in all steps of the radiotherapy workflow from diagnosis, staging, and target definition to treatment follow-up. Of particular interest is the ability of MRI to provide a wide range of functional measures. The complexity of MRI as an imaging modality combined with the growing interest of the application to prostate cancer radiotherapy, emphasize the need for dedicated education within the radiation oncology community. In this context, an overview of the most common as well as a few upcoming functional MR imaging techniques is presented: the basic methodology and measurement is described, the link between the functional measures and the underlying biology is established, and finally relevant applications of functional MRI useful for prostate cancer radiotherapy are given.

Improving fiducial and prostate capsule visualization for radiotherapy planning using MRI

BACKGROUND AND PURPOSE

Intraprostatic fiducial markers (FM) improve the accuracy of radiotherapy (RT) delivery. Here we assess geometric integrity and contouring consistency using a T2*-weighted (T2*W) sequence alone, which allows visualization of the FM.

MATERIAL AND METHODS

Ten patients scanned within the Prostate Advances in Comparative Evidence (PACE) trial (NCT01584258) had prostate images acquired with computed tomography (CT) and Magnetic Resonance (MR) Imaging: T2-weighted (T2W) and T2*W sequences. The prostate was contoured independently on each imaging dataset by three clinicians. Interobserver variability was assessed using comparison indices with Monaco ADMIRE (research version 2.0, Elekta AB) and examined for statistical differences between imaging sets. CT and MR images of two test objects were acquired to assess geometric distortion and accuracy of marker positioning. The first was a linear test object comprising straight tubes in three orthogonal directions, the second was a smaller test object with markers suspended in gel.

RESULTS

Interobserver variability for prostate contouring was lower for both T2W and T2*W compared to CT, this was statistically significant when comparing CT and T2*W images. All markers are visible in T2*W images with 29/30 correctly identified, only 3/30 are visible in T2W images. Assessment of geometric distortion revealed in-plane displacements were under 0.375 mm in MRI, and through plane displacements could not be detected. The signal loss in the MR images is symmetric in relation to the true marker position shown in CT images.

CONCLUSION

Prostate T2*W images are geometrically accurate, and yield consistent prostate contours. This single sequence can be used to identify FM and for prostate delineation in a mixed MR-CT workflow.

Biochemical recurrence prediction after radiotherapy for prostate cancer with T2w magnetic resonance imaging radiomic features

Background and purpose

High-risk prostate cancer patients are frequently treated with external-beam radiotherapy (EBRT). Of all patients receiving EBRT, 15–35% will experience biochemical recurrence (BCR) within five years. Magnetic resonance imaging (MRI) is commonly acquired as part of the diagnostic procedure and imaging-derived features have shown promise in tumour characterisation and biochemical recurrence prediction. We investigated the value of imaging features extracted from pre-treatment T2w anatomical MRI to predict five year biochemical recurrence in high-risk patients treated with EBRT.

Materials and methods

In a cohort of 120 high-risk patients, imaging features were extracted from the whole-prostate and a margin surrounding it. Intensity, shape and textural features were extracted from the original and filtered T2w-MRI scans. The minimum-redundancy maximum-relevance algorithm was used for feature selection. Random forest and logistic regression classifiers were used in our experiments. The performance of a logistic regression model using the patient’s clinical features was also investigated. To assess the prediction accuracy we used stratified 10-fold cross validation and receiver operating characteristic analysis, quantified by the area under the curve (AUC).

Results

A logistic regression model built using whole-prostate imaging features obtained an AUC of 0.63 in the prediction of BCR, outperforming a model solely based on clinical variables (AUC = 0.51). Combining imaging and clinical features did not outperform the accuracy of imaging alone.

Conclusions

These results illustrate the potential of imaging features alone to distinguish patients with an increased risk of recurrence, even in a clinically homogeneous cohort.

Role of Prostate MR Imaging in Radiation Oncology

The use of prostate MR imaging in radiotherapy continues to evolve. This article describes its current application in the selection of treatment regimens, integration in treatment planning or simulation, and assessment of response. An expert consensus statement from the annual MR in RT symposium is presented, as a list of 21 key quality indicators for the practice of MR imaging simulation in prostate cancer. Although imaging requirements generally follow PIRADSv2 guidelines, additional requirements specific to radiotherapy planning are described. MR imaging-only workflows and MR imaging-guided treatment systems are expected to replace conventional computed tomography-based practice, further adding specific requirements for MR imaging in radiotherapy.

Clinical workflow for MR-only simulation and planning in prostate

Purpose

To describe the details and experience of implementing a MR-only workflow in the clinic for simulation and planning of prostate cancer patients.

Methods

Forty-eight prostate cancer patients from June 2016 - Dec 2016 receiving external beam radiotherapy were scheduled to undergo MR-only simulation. MR images were acquired for contouring (T2w axial, coronal, sagittal), synthetic-CT generation (3D FFE-based) and fiducial identification (3D bFFE-based). The total acquisition time was 25 min. Syn-CT was generated at the console using commercial software called MRCAT. As part of acceptance testing of the MRCAT package, external laser positioning system QA (< 2 mm) and geometric fidelity QA (< 2 mm within 50 cm LR and 30 cm AP) were performed and baseline values were set. Our current combined CT + MR simulation process was modified to accommodate a MRCAT-based MR-only simulation workflow. An automated step-by-step process using a MIM™ workflow was created for contouring on the MR images. Patient setup for treatment was achieved by matching the MRCAT DRRs with the orthogonal KV radiographs based on either fiducial ROIs or bones. 3-D CBCTs were acquired and compared with the MR/syn-CT to assess the rectum and bladder filling compared to simulation conditions.

Results

Forty-two patients successfully underwent MR-only simulation and met all of our institutional dosimetric objectives that were developed based on a CT + MR-based workflow. The remaining six patients either had a hip prosthesis or their large body size fell outside of the geometric fidelity QA criteria and thus they were not candidates for MR-only simulation. A total time saving of ~15 min was achieved with MR-based simulation as compared to CT + MR-based simulation. An automated and organized MIM workflow made contouring on MR much easier, quicker and more accurate compared with combined CT + MR images because the temporal variations in normal structure was minimal. 2D and 3D treatment setup localization based on bones/fiducials using a MRCAT reference image was successfully achieved for all cases.

Conclusions

MR-only simulation and planning with equivalent or superior target delineation, planning and treatment setup localization accuracy is feasible in a clinical setting. Future work will focus on implementing a robust 3D isotropic acquisition for contouring.

Electronic supplementary material

The online version of this article (doi:10.1186/s13014-017-0854-4) contains supplementary material, which is available to authorized users.

Volumetry of the dominant intraprostatic tumour lesion: intersequence and interobserver differences on multiparametric MRI

OBJECTIVE

To establish the interobserver reproducibility of tumour volumetry on individual multiparametric (mp) prostate MRI sequences, validate measurements with histology and determine whether functional to morphological volume ratios reflect Gleason score.

METHODS

41 males with prostate cancer treated with prostatectomy (Cohort 1) or radical radiotherapy (Cohort 2), who had pre-treatment mpMRI [T2 weighted (T2W) MRI, diffusion-weighted (DW)-MRI and dynamic contrast-enhanced (DCE)-MRI], were studied retrospectively. Dominant intraprostatic lesions (DIPLs) were manually delineated on each sequence and volumes were compared between observers (n = 40 analyzable) and with radical prostatectomy (n = 20). Volume ratios of DW-MRI and DCE-MRI to T2W MRI were documented and compared between Gleason grade 3 + 3, 3 + 4 and 4 + 3 or greater categories.

RESULTS

Limits of agreement of DIPL volumes between observers were: T2W MRI 0.9, -1.1 cm3, DW-MRI 1.3, -1.7 cm3 and DCE-MRI 0.74, -0.89 cm3. In Cohort 1, T2W volumes overestimated fixed specimen histological volumes (+33% Observer 1, +16% Observer 2); DW- and DCE-MRI underestimated histological volume, the latter markedly so (-32% Observer 1, -79% Observer 2). Differences between T2W, DW- and DCE-MRI volumes were significant (p < 10-8). The ratio of DW-MRI volume (73.9 ± 18.1% Observer 1, 72.5 ± 21.9% Observer 2) and DCE-MRI volume (42.6 ± 24.6% Observer 1, 34.3 ± 24.9% Observer 2) to T2W volume was significantly different (p < 10-8), but these volume ratios did not differ between the Gleason grades.

CONCLUSION

The low variability of the DIPL volume on T2W MRI between Observers and agreement with histology indicates its suitability for delineation of gross tumour volume for radiotherapy planning. The volume of cellular tumour represented by DW-MRI is greater than the vascular (DCE) abnormality; ratios of both to T2W volume are independent of Gleason score. Advances in knowledge: (1) Manual volume measurement of tumour is reproducible within 1 cm3 between observers on all sequences, confirming suitability across observers for radiotherapy planning. (2) Volumes derived on T2W MRI most accurately represent in vivo lesion volumes. (3) The proportion of cellular (DW-MRI) or vascular (DCE-MRI) volume to morphological (T2W MRI) volume is not affected by Gleason score.

Dosimetric and workflow evaluation of first commercial synthetic CT software for clinical use in pelvis

To evaluate a commercial synthetic CT (syn-CT) software for use in prostate radiotherapy. Twenty-five prostate patients underwent CT and MR simulation scans in treatment position on a 3T MR scanner. A commercially available MR protocol was used that included a T2w turbo spin-echo sequence for soft-tissue contrast and a dual echo 3D mDIXON fast field echo (FFE) sequence for generating syn-CT. A dual-echo 3D FFE B ₀ map was used for patient-induced susceptibility distortion analysis and a new 3D balanced-FFE sequence was evaluated for identification of implanted gold fiducial markers and subsequent image-guidance during radiotherapy delivery. Tissues were classified as air, adipose, water, trabecular/spongy bone and compact/cortical bone and assigned bulk HU values. The accuracy of syn-CT for treatment planning was analyzed by transferring the structures and plan from planning CT to syn-CT and recalculating the dose. Accuracy of localization at the treatment machine was evaluated by comparing registration of kV radiographs to either digitally reconstructed radiographs (DRRs) generated from syn-CT or traditional DRRs generated from the planning CT. Similarly, accuracy of setup using CBCT and syn-CT was compared to that using the planning CT. Finally, a MR-only simulation workflow was established and end-to-end testing was completed on five patients undergoing MR-only simulation. Dosimetric comparison between the original CT and syn-CT plans was within 0.5% on average for all structures. The de-novo optimized plans on the syn-CT met institutional clinical objectives for target and normal structures. Patient-induced susceptibility distortion based on B ₀ maps was within 1 mm and 0.5 mm in the body and prostate respectively. DRR and CBCT localization based on MR-localized fiducials showed a standard deviation of  <1 mm. End-to-end testing and MR simulation workflow was successfully validated. MRI derived synthetic CT can be successfully used for a MR-only planning and treatment for prostate radiotherapy.

Uncertainties in volume delineation in radiation oncology: A systematic review and recommendations for future studies

BACKGROUND AND PURPOSE

Volume delineation is a well-recognised potential source of error in radiotherapy. Whilst it is important to quantify the degree of interobserver variability (IOV) in volume delineation, the resulting impact on dosimetry and clinical outcomes is a more relevant endpoint. We performed a literature review of studies evaluating IOV in target volume and organ-at-risk (OAR) delineation in order to analyse these with respect to the metrics used, reporting of dosimetric consequences, and use of statistical tests.

METHODS AND MATERIALS

Medline and Pubmed databases were queried for relevant articles using keywords. We included studies published in English between 2000 and 2014 with more than two observers.

RESULTS

119 studies were identified covering all major tumour sites. CTV (n=47) and GTV (n=38) were most commonly contoured. Median number of participants and data sets were 7 (3-50) and 9 (1-132) respectively. There was considerable heterogeneity in the use of metrics and methods of analysis. Statistical analysis of results was reported in 68% (n=81) and dosimetric consequences in 21% (n=25) of studies.

CONCLUSION

There is a lack of consistency in conducting and reporting analyses from IOV studies. We suggest a framework to use for future studies evaluating IOV.

Inter-site and inter-scanner diffusion MRI data harmonization

We propose a novel method to harmonize diffusion MRI data acquired from multiple sites and scanners, which is imperative for joint analysis of the data to significantly increase sample size and statistical power of neuroimaging studies. Our method incorporates the following main novelties: i) we take into account the scanner-dependent spatial variability of the diffusion signal in different parts of the brain; ii) our method is independent of compartmental modeling of diffusion (e.g., tensor, and intra/extra cellular compartments) and the acquired signal itself is corrected for scanner related differences; and iii) inter-subject variability as measured by the coefficient of variation is maintained at each site. We represent the signal in a basis of spherical harmonics and compute several rotation invariant spherical harmonic features to estimate a region and tissue specific linear mapping between the signal from different sites (and scanners). We validate our method on diffusion data acquired from seven different sites (including two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. Since the extracted rotation invariant spherical harmonic features depend on the accuracy of the brain parcellation provided by Freesurfer, we propose a feature based refinement of the original parcellation such that it better characterizes the anatomy and provides robust linear mappings to harmonize the dMRI data. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across multiple sites before and after data harmonization. We also show results using tract-based spatial statistics before and after harmonization for independent validation of the proposed methodology. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences can be accurately removed using the proposed method.

Harmonization of the Volume of Interest Delineation among All Eleven Radiotherapy Centers in the North of France

Background

Inter-observer delineation variation has been detailed for many years in almost every tumor location. Inadequate delineation can impair the chance of cure and/or increase toxicity. The aim of our original work was to prospectively improve the homogeneity of delineation among all of the senior radiation oncologists in the Nord-Pas de Calais region, irrespective of the conditions of practice.

Methods

All 11 centers were involved. The first studied cancer was prostate cancer. Three clinical cases were studied: a low-risk prostate cancer case (case 1), a high-risk prostate cancer case (pelvic nodes, case 2) and a case of post-operative biochemical elevated PSA (case 3). All of the involved physicians delineated characteristically the clinical target volume (CTV) and organs at risk. The volumes were compared using validated indexes: the volume ratio (VR), common and additional volumes (CV and AV), volume overlap (VO) and Dice similarity coefficient (DSC). A second delineation of the same three cases was performed after discussion of the slice results and the choice of shared guidelines to evaluate homogenization. A comparative analysis of the indexes before and after discussion was conducted using the Wilcoxon test for paired samples. A p-value less than 0.05 was considered to indicate statistical significance.

Results

The indexes were not improved in case 1, for which the inter-observer agreement was considered good after the first comparison (DSC = 0.83±0.06). In case 2, the second comparison showed homogenization of the CTV delineation with a significant improvement in CV (81.4±11.7 vs. 88.6±10.26, respectively, p = 0.048), VO (0.41±0.09 vs. 0.47±0.07, respectively; p = 0.009) and DSC (0.58±0.09 vs. 0.63±0.07, respectively; p = 0.0098). In case 3, VR and AV were significantly improved: VR: 1.71(±0.6) vs. 1.34(±0.46), respectively, p = 0.0034; AV: 46.58(±14.50) vs. 38.08(±15.10), respectively, p = 0.0024. DSC was not improved, but it was already superior to 0.6 in the first comparison.

Conclusion

Our prospective work showed that a collaborative discussion about clinical cases and the choice of shared guidelines within an established framework improved the homogeneity of CTV delineation among the senior radiation oncologists in our region.

The use of atlas registration and graph cuts for prostate segmentation in magnetic resonance images

PURPOSE

An automatic method for 3D prostate segmentation in magnetic resonance (MR) images is presented for planning image-guided radiotherapy treatment of prostate cancer.

METHODS

A spatial prior based on intersubject atlas registration is combined with organ-specific intensity information in a graph cut segmentation framework. The segmentation is tested on 67 axial T2-weighted MR images in a leave-one-out cross validation experiment and compared with both manual reference segmentations and with multiatlas-based segmentations using majority voting atlas fusion. The impact of atlas selection is investigated in both the traditional atlas-based segmentation and the new graph cut method that combines atlas and intensity information in order to improve the segmentation accuracy. Best results were achieved using the method that combines intensity information, shape information, and atlas selection in the graph cut framework.

RESULTS

A mean Dice similarity coefficient (DSC) of 0.88 and a mean surface distance (MSD) of 1.45 mm with respect to the manual delineation were achieved.

CONCLUSIONS

This approaches the interobserver DSC of 0.90 and interobserver MSD 0f 1.15 mm and is comparable to other studies performing prostate segmentation in MR.

A comparative assessment of prostate positioning guided by three-dimensional ultrasound and cone beam CT

Background

The accuracy of the Elekta Clarity™ three-dimensional ultrasound system (3DUS) was assessed for prostate positioning and compared to seed- and bone-based positioning in kilo-voltage cone-beam computed tomography (CBCT) during a definitive radiotherapy.

Methods

The prostate positioning of 6 patients, with fiducial markers implanted into the prostate, was controlled by 3DUS and CBCT. In total, 78 ultrasound scans were performed trans-abdominally and compared to bone-matches and seed-matches in CBCT scans. Setup errors detected by the different modalities were compared. Systematic and random errors were analysed, and optimal setup margins were calculated.

Results

The discrepancy between 3DUS and seed-match in CBCT was −0.2 ± 2.7 mm laterally, −1.9 ± 2.3 mm longitudinally and 0.0 ± 3.0 mm vertically and significant only in longitudinal direction. Using seed-match as reference, systematic errors of 3DUS were 1.3 mm laterally, 0.8 mm longitudinally and 1.4 mm vertically, and random errors were 2.5 mm laterally, 2.3 mm longitudinally, and 2.7 mm vertically. No significant difference could be detected for 3DUS in comparison to bone-match in CBCT.

Conclusions

3DUS is feasible for image guidance for patients with prostate cancer and appears comparable to CBCT based image guidance in the retrospective study. While 3DUS offers some distinct advantages such as no need of invasive fiducial implantation and avoidance of extra radiation, its disadvantages include the operator dependence of the technique and dependence on sufficient bladder filling. Further study of 3DUS for image guidance in a large patient cohort is warranted.

Magnetic resonance imaging acquisition techniques for radiotherapy planning

Magnetic resonance imaging (MRI) has a number of benefits for the planning of radiotherapy (RT), but its uptake into clinical practice has often been restricted to specialist research sites. There is often a lack of detailed MRI knowledge within the RT community and an apprehension of geometric distortions, both of which prevent its best utilization and merit the introduction of a standardized approach and common guidelines. This review sets out to address some of the issues involved in acquiring MRI scans for RT planning in the context of a number of clinical sites of interest and concludes with recommendations for its best practice in terms of imaging protocol and quality assurance. The article is of particular interest to the growing number of cancer therapy centers that are embarking on MRI simulation on either existing systems or their own dedicated scanners.

Change in prostate volume during extreme hypo-fractionation analysed with MRI

BACKGROUND

Hypo-fractionated external beam radiotherapy with narrow CTV-PTV margins is increasingly applied for prostate cancer. This demands a precise target definition and knowledge on target location and extension during treatment. It is unclear how increase in fraction size affects changes in prostate volume during treatment. Our aim was to study prostate volume changes during extreme hypo-fractionation (7 × 6.1 Gy) by using sequential MRIs.

METHODS

Twenty patients treated with extreme hypo-fractionation were recruited from an on-going prospective randomized phase III trial. An MRI scan was done before start of treatment, at mid treatment and at the end of radiotherapy. The prostate was delineated at each MRI and the volume and maximum extension in left-right, anterior-posterior and cranial-caudal directions were measured.

RESULTS

There was a significant increase in mean prostate volume (14%) at mid treatment as compared to baseline. The prostate volume remained enlarged (9%) at the end of radiotherapy. Prostate swelling was most pronounced in the anterior-posterior and cranial-caudal directions.

CONCLUSIONS

Extreme hypo-fractionation induced a significant prostate swelling during treatment that was still present at the time of last treatment fraction. Our results indicate that prostate swelling is an important factor to take into account when applying treatment margins during short extreme hypo-fractionation, and that tight margins should be applied with caution.

Cold spot mapping inferred from MRI at time of failure predicts biopsy-proven local failure after permanent seed brachytherapy in prostate cancer patients: implications for focal salvage brachytherapy

BACKGROUND AND PURPOSE

(1) To establish a method to evaluate dosimetry at the time of primary prostate permanent implant (pPPI) using MRI of the shrunken prostate at the time of failure (tf). (2) To compare cold spot mapping with sextant-biopsy mapping at tf.

MATERIAL AND METHODS

Twenty-four patients were referred for biopsy-proven local failure (LF) after pPPI. Multiparametric MRI and combined-sextant biopsy with a central review of the pathology at tf were systematically performed. A model of the shrinking pattern was defined as a Volumetric Change Factor (VCF) as a function of time from time of pPPI (t0). An isotropic expansion to both prostate volume (PV) and seed position (SP) coordinates determined at tf was performed using a validated algorithm using the VCF.

RESULTS

pPPI CT-based evaluation (at 4weeks) vs. MR-based evaluation: Mean D90% was 145.23±19.16Gy [100.0-167.5] vs. 85.28±27.36Gy [39-139] (p=0.001), respectively. Mean V100% was 91.6±7.9% [70-100%] vs. 73.1±13.8% [55-98%] (p=0.0006), respectively. Seventy-seven per cent of the pathologically positive sextants were classified as cold.

CONCLUSIONS

Patients with biopsy-proven LF had poorer implantation quality when evaluated by MRI several years after implantation. There is a strong relationship between microscopic involvement at tf and cold spots.

3 Tesla multiparametric MRI for GTV-definition of Dominant Intraprostatic Lesions in patients with Prostate Cancer--an interobserver variability study

PURPOSE

To evaluate the interobserver variability of gross tumor volume (GTV) - delineation of Dominant Intraprostatic Lesions (DIPL) in patients with prostate cancer using published MRI criteria for multiparametric MRI at 3 Tesla by 6 different observers.

MATERIAL AND METHODS

90 GTV-datasets based on 15 multiparametric MRI sequences (T2w, diffusion weighted (DWI) and dynamic contrast enhanced (DCE)) of 5 patients with prostate cancer were generated for GTV-delineation of DIPL by 6 observers. The reference GTV-dataset was contoured by a radiologist with expertise in diagnostic imaging of prostate cancer using MRI. Subsequent GTV-delineation was performed by 5 radiation oncologists who received teaching of MRI-features of primary prostate cancer before starting contouring session. GTV-datasets were contoured using Oncentra Masterplan® and iplan® Net. For purposes of comparison GTV-datasets were imported to the Artiview® platform (Aquilab®), GTV-values and the similarity indices or Kappa indices (KI) were calculated with the postulation that a KI > 0.7 indicates excellent, a KI > 0.6 to < 0.7 substantial and KI > 0.5 to < 0.6 moderate agreement. Additionally all observers rated difficulties of contouring for each MRI-sequence using a 3 point rating scale (1 = easy to delineate, 2 = minor difficulties, 3 = major difficulties).

RESULTS

GTV contouring using T2w (KI-T2w = 0.61) and DCE images (KI-DCE = 0.63) resulted in substantial agreement. GTV contouring using DWI images resulted in moderate agreement (KI-DWI = 0.51). KI-T2w and KI-DCE was significantly higher than KI-DWI (p = 0.01 and p = 0.003). Degree of difficulty in contouring GTV was significantly lower using T2w and DCE compared to DWI-sequences (both p < 0.0001). Analysis of delineation differences revealed inadequate comparison of functional (DWI, DCE) to anatomical sequences (T2w) and lack of awareness of non-specific imaging findings as a source of erroneous delineation.

CONCLUSIONS

Using T2w and DCE sequences at 3 Tesla for GTV-definition of DIPL in prostate cancer patients by radiation oncologists with knowledge of MRI features results in substantial agreement compared to an experienced MRI-radiologist, but for radiotherapy purposes higher KI are desirable, strengthen the need for expert surveillance. DWI sequence for GTV delineation was considered as difficult in application.