A study of prostate delineation referenced against a gold standard created from the visible human data

3D Unsupervised deep learning method for magnetic resonance imaging-to-computed tomography synthesis in prostate radiotherapy

Background and purpose

Magnetic resonance imaging (MRI)-to-computed tomography (CT) synthesis is essential in MRI-only radiotherapy workflows, particularly through deep learning techniques known for their accuracy. However, current supervised methods are limited to specific center's learnings and depend on registration precision. The aim of this study was to evaluate the accuracy of unsupervised and supervised approaches in the context of prostate MRI-to-CT generation for radiotherapy dose calculation.

Methods

CT/MRI image pairs from 99 prostate cancer patients across three different centers were used. A comparison between supervised and unsupervised conditional Generative Adversarial Networks (cGAN) was conducted. Unsupervised training incorporates a style transfer method with. Content and Style Representation for Enhanced Perceptual synthesis (CREPs) loss. For dose evaluation, the photon prescription dose was 60 Gy delivered in volumetric modulated arc therapy (VMAT). Imaging endpoint for sCT evaluation was Mean Absolute Error (MAE). Dosimetric endpoints included absolute dose differences and gamma analysis between CT and sCT dose calculations.

Results

The unsupervised paired network exhibited the highest accuracy for the body with a MAE at 33.6 HU, the highest MAE was 45.5 HU obtained with unsupervised unpaired learning. All architectures provided clinically acceptable results for dose calculation with gamma pass rates above 94 % (1 % 1 mm 10 %).

Conclusions

This study shows that multicenter data can produce accurate sCTs via unsupervised learning, eliminating CT-MRI registration. The sCTs not only matched HU values but also enabled precise dose calculations, suggesting their potential for wider use in MRI-only radiotherapy workflows.

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.

Prostate volume analysis in image registration for prostate cancer care: a verification study

Combined magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) may enhance diagnosis, aid surgical planning and intra-operative orientation for prostate biopsy and radical prostatectomy. Although PET-MRI may provide these benefits, PET-MRI machines are not widely available. Image fusion of Prostate specific membrane antigen PET/CT and MRI acquired separately may be a suitable clinical alternative. This study compares CT-MR registration algorithms for urological prostate cancer care. Paired whole-pelvis MR and CT scan data were used (n = 20). A manual prostate CTV contour was performed independently on each patients MR and CT image. A semi-automated rigid-, automated rigid- and automated non-rigid registration technique was applied to align the MR and CT data. Dice Similarity Index (DSI), 95% Hausdorff distance (95%HD) and average surface distance (ASD) measures were used to assess the closeness of the manual and registered contours. The automated non-rigid approach had a significantly improved performance compared to the automated rigid- and semi-automated rigid-registration, having better average scores and decreased spread for the DSI, 95%HD and ASD (all p < 0.001). Additionally, the automated rigid approach had similar significantly improved performance compared to the semi-automated rigid registration across all accuracy metrics observed (all p < 0.001). Overall, all registration techniques studied here demonstrated sufficient accuracy for exploring their clinical use. While the fully automated non-rigid registration algorithm in the present study provided the most accurate registration, the semi-automated rigid registration is a quick, feasible, and accessible method to perform image registration for prostate cancer care by urologists and radiation oncologists now.

Computed tomography synthesis from magnetic resonance imaging using cycle Generative Adversarial Networks with multicenter learning

Background and Purpose: Addressing the need for accurate dose calculation in MRI-only radiotherapy, the generation of synthetic Computed Tomography (sCT) from MRI has emerged. Deep learning (DL) techniques, have shown promising results in achieving high sCT accuracies. However, existing sCT synthesis methods are often center-specific, posing a challenge to their generalizability. To overcome this limitation, recent studies have proposed approaches, such as multicenter training . Material and methods: The purpose of this work was to propose a multicenter sCT synthesis by DL, using a 2D cycle-GAN on 128 prostate cancer patients, from four different centers. Four cases were compared: monocenter cases, monocenter training and test on another center, multicenter trainings and a test on a center not included in the training and multicenter trainings with an included center in the test. Trainings were performed using 20 patients. sCT accuracy evaluation was performed using Mean Absolute Error, Mean Error and Peak-Signal-to-Noise-Ratio. Dose accuracy was assessed with gamma index and Dose Volume Histogram comparison. Results: Qualitative, quantitative and dose results show that the accuracy of sCTs for monocenter trainings and multicenter trainings using a seen center in the test did not differ significantly. However, when the test involved an unseen center, the sCT quality was inferior. Conclusions: The aim of this work was to propose generalizable multicenter training for MR-to-CT synthesis. It was shown that only a few data from one center included in the training cohort allows sCT accuracy equivalent to a monocenter study.

Measurements of target volumes and organs at risk using DW‑MRI in patients with central lung cancer accompanied with atelectasis

Accurate imaging-based tumor delineation is crucial for guiding the radiotherapy treatments of various solid tumors. Currently, several imaging procedures, including diffusion-weighted magnetic resonance imaging (DW-MRI), intensified computed tomography and positron emission tomography are routinely used for targeted tumor delineation. However, the performance of these imaging procedures has not yet been comprehensively evaluated. In order to address this matter, the present study was conducted in an aim to assess the use of DW-MRI in guiding radiotherapy treatments, by comparing its performance to that of other imaging procedures. Specifically, the exposure dosages to organs at risk, including the lungs, heart and spinal mencord, were evaluated using various radiotherapy regimes. The findings of the present study demonstrated that DW-MRI is a non-invasive and cost-effective imaging procedure that can be used to reduce lung exposure doses, minimizing the risk of radiation pneumonitis. The data further demonstrate the immense potential of the DW-MRI procedure in the precision radiotherapy of lung cancers.

Evaluating the clinical acceptability of deep learning contours of prostate and organs-at-risk in an automated prostate treatment planning process

BACKGROUND

Radiation treatment is considered an effective and the most common treatment option for prostate cancer. The treatment planning process requires accurate and precise segmentation of the prostate and organs at risk (OARs), which is laborious and time-consuming when contoured manually. Artificial intelligence (AI)-based auto-segmentation has the potential to significantly accelerate the radiation therapy treatment planning process; however, the accuracy of auto-segmentation needs to be validated before its full clinical adoption.

PURPOSE

A commercial AI-based contouring model was trained to provide segmentation of the prostate and surrounding OARs. The segmented structures were input to a commercial auto-planning module for automated prostate treatment planning. This study comprehensively evaluates the performance of this contouring model in the automated prostate treatment planning process.

METHODS AND MATERIALS

A 3D U-Net-based model (INTContour, Carina AI) was trained and validated on 84 computed tomography (CT) scans and tested on an additional 23 CT scans from patients treated in our local institution. Prostate and OARs contours generated by the AI model (AI contour) were geometrically evaluated against Reference contours. The prostate contours were further evaluated against AI, Reference, and two additional observer contours for comparison using inter-observer variation (IOV) and 3D boundaries discrepancy analyses. A blinded evaluation was introduced to assess subjectively the clinical acceptability of the AI contours. Finally, treatment plans were created from an automated prostate planning workflow using the AI contours and were evaluated for their clinical acceptability following the RTOG-0815 protocol.

RESULTS

The AI contours demonstrated good geometric accuracy on OARs and prostate contours, with average Dice similarity coefficients (DSC) for bladder, rectum, femoral heads, seminal vesicles, and penile bulb of 0.93, 0.85, 0.96, 0.72, and 0.53, respectively. The DSC, 95% directed Hausdorff Distance (HD95), and Mean Surface Distance (MSD) for the prostate were 0.83±0.05, 6.07±1.87 mm, and 2.07±0.73 mm, respectively. No significant differences were found when comparing with IOV. In the double-blinded evaluation, 95.7% of the AI contours were scored as either "Perfect" (34.8%) or "Acceptable" (60.9%), while only one case (4.3%) was scored as "Unacceptable with minor changes required". In total, 69.6% of the AI contours were considered equal to or better than the Reference contours by an independent radiation oncologist. Automated treatment plans created from the AI contours produced similar and clinically-acceptable dosimetric distributions as those from plans created from Reference contours.

CONCLUSIONS

The investigated AI-based commercial model for prostate segmentation demonstrated good performance in clinical practice. Using this model, the implementation of an automated prostate treatment planning process is clinically feasible. This article is protected by copyright. All rights reserved.

Segmentation of male pelvic organs on computed tomography with a deep neural network fine-tuned by a level-set method

Computed Tomography (CT) imaging is used in Radiation Therapy planning, where the treatment is carefully tailored to each patient in order to maximize radiation dose to the target while decreasing adverse effects to nearby healthy tissues. A crucial step in this process is manual organ contouring, which if performed automatically could considerably decrease the time to starting treatment and improve outcomes. Computerized segmentation of male pelvic organs has been studied for decades and deep learning models have brought considerable advances to the field, but improvements are still demanded. A two-step framework for automatic segmentation of the prostate, bladder and rectum is presented: a convolutional neural network enhanced with attention gates performs an initial segmentation, followed by a region-based active contour model to fine-tune the segmentations to each patient's specific anatomy. The framework was evaluated on a large collection of planning CTs of patients who had Radiation Therapy for prostate cancer. The Surface Dice Coefficient improved from 79.41 to 81.00% on segmentation of the prostate, 94.03-95.36% on the bladder and 82.17-83.68% on the rectum, comparing the proposed framework with the baseline convolutional neural network. This study shows that traditional image segmentation algorithms can help improve the immense gains that deep learning models have brought to the medical imaging segmentation field.

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.

An Inter-observer Study to Determine Radiotherapy Planning Target Volumes for Recurrent Gynaecological Cancer Comparing Magnetic Resonance Imaging Only With Computed Tomography-Magnetic Resonance Imaging

AIMS

Target delineation uncertainty is arguably the largest source of geometric uncertainty in radiotherapy. Several factors can affect it, including the imaging modality used for delineation. It is accounted for by applying safety margins to the target to produce a planning target volume (PTV), to which treatments are designed. To determine the margin, the delineation uncertainty is measured as the delineation error, and then a margin recipe used. However, there is no published evidence of such analysis for recurrent gynaecological cancers (RGC). The aims of this study were first to quantify the delineation uncertainty for RGC gross tumour volumes (GTVs) and to calculate the associated PTV margins and then to quantify the difference in GTV, delineation uncertainty and PTV margin, between a computed tomography-magnetic resonance imaging (CT-MRI) and MRI workflow.

MATERIALS AND METHODS

Seven clinicians delineated the GTV for 20 RGC tumours on co-registered CT and MRI datasets (CT-MRI) and on MRI alone. The delineation error, the standard deviation of distances from each clinician's outline to a reference, was measured and the required PTV margin determined. Differences between using CT-MRI and MRI alone were assessed.

RESULTS

The overall delineation error and the resulting margin were 3.1 mm and 8.5 mm, respectively, for CT-MRI, reducing to 2.5 mm and 7.1 mm, respectively, for MRI alone. Delineation errors and therefore the theoretical margins, varied widely between patients. MRI tumour volumes were on average 15% smaller than CT-MRI tumour volumes.

DISCUSSION

This study is the first to quantify delineation error for RGC tumours and to calculate the corresponding PTV margin. The determined margins were larger than those reported in the literature for similar patients, bringing into question both current margins and margin calculation methods. The wide variation in delineation error between these patients suggests that applying a single population-based margin may result in PTVs that are suboptimal for many. Finally, the reduced tumour volumes and safety margins suggest that patients with RGC may benefit from an MRI-only treatment workflow.

Anthropometry-based generation of personalized and population-specific human airway models

Understanding aerosol deposition in the human lung is of great significance in pulmonary toxicology and inhalation pharmacology. Adverse effects of inhaled environmental aerosols and pharmacological efficacy of inhaled therapeutics are dependent on aerosol properties as well as person-specific respiratory tract anatomy and physiology. Anatomical geometry and physiological function of human airways depend on age, gender, weight, fitness, health, and disease status. Tools for the generation of the population- and subject-specific virtual airway anatomical geometry based on anthropometric data and physiological vitals are invaluable in respiratory diagnostics, personalized pulmonary pharmacology, and model-based management of chronic respiratory diseases. Here we present a novel protocol and software framework for the generation of subject-specific airways based on anthropometric measurements of the subject's body, using the anatomical input, and the conventional spirometry, providing the functional (physiological) data. This model can be used for subject-specific simulations of respiration physiology, gas exchange, and aerosol inhalation and deposition.

MRI-based IMPT planning for prostate cancer

PURPOSE

Treatment planning for proton therapy requires the relative proton stopping power ratio (RSP) information of the patient for accurate dose calculations. RSP are conventionally obtained after mapping of the Hounsfield units (HU) from a calibrated patient computed tomography (CT). One or multiple CT are needed for a given treatment which represents additional, undesired dose to the patient. For prostate cancer, magnetic resonance imaging (MRI) scans are the gold standard for segmentation while offering dose-less imaging. We here quantify the clinical applicability of converted MR images as a substitute for intensity modulated proton therapy (IMPT) treatment of the prostate.

METHODS

MRCAT (Magnetic Resonance for Calculating ATtenuation) is a Philips-developed technology which produces a synthetic CT image consisting of five HU from a specific set of MRI acquisitions. MRCAT and original planning CT data sets were obtained for ten patients. An IMPT plan was generated on the MRCAT for each patient. Plans were produced such that they fulfill the prostate protocol in use at Massachusetts General Hospital (MGH). The plans were then recomputed onto the nominal planning CT for each patient. Robustness analyses (±5 mm setup shifts and ±3.5 % range uncertainties) were also performed.

RESULTS

Comparison of MRCAT plans and their recomputation onto the planning CT plan showed excellent agreement. Likewise, dose perturbations due to setup shifts and range uncertainties were well within clinical acceptance demonstrating the clinical viability of the approach.

CONCLUSIONS

This work demonstrate the clinical acceptability of substituting MR converted RSP images instead of CT for IMPT planning of prostate cancer. This further translates into higher contouring accuracy along with lesser imaging dose.

Evaluation of a deep learning-based pelvic synthetic CT generation technique for MRI-based prostate proton treatment planning

The purpose of this work is to validate the application of a deep learning-based method for pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy treatment planning. We propose to integrate dense block minimization into 3D cycle-consistent generative adversarial networks (cycleGAN) framework to effectively learn the nonlinear mapping between MRI and CT pairs. A cohort of 17 patients with co-registered CT and MR pairs were used to test the deep learning-based sCT generation method by leave-one-out cross-validation. Image quality between the sCT and CT images, gamma analysis passing rate, dose-volume metrics, distal range displacement, and the individual pencil beam Bragg peak shift between sCT- and CT-based proton plans were evaluated. The average mean absolute error (MAE) was 51.32  ±  16.91 HU. The relative differences of the statistics of the PTV dose-volume histogram (DVH) metrics in between sCT and CT were generally less than 1%. Mean values of dose difference, absolute dose difference (in percent of the prescribed dose) were  -0.07%  ±  0.07% and 0.23%  ±  0.08%. Mean gamma analysis pass rate of 1 mm/1%, 2 mm/2%, 3 mm/3% criteria with 10% dose threshold were 92.39%  ±  5.97%, 97.95%  ±  2.95% and 98.97%  ±  1.62% respectively. The median, mean and standard deviation of absolute maximum range differences were 0.09 cm and 0.23  ±  0.25 cm. The median and mean Bragg peak shifts among the 17 patients were 0.09 cm and 0.18  ±  0.07 cm. The image similarity, dosimetric and distal range agreement between sCT and original CT suggests the feasibility of further development of an MRI-only workflow for prostate proton radiotherapy.

Clinical and radiobiological evaluation of a method for planning target volume generation dependent on organ-at-risk exclusions in magnetic resonance imaging-based prostate radiotherapy

Background and purpose

Due to a smaller target volume when delineating prostate on magnetic resonance imaging (MRI), margins may be too tight as compared to computed tomography (CT) delineation, potentially reducing tumor control probability (TCP) in prostate radiotherapy. This study evaluated a clinically implemented MRI-based target expansion method to provide adequate margins yet limit organ-at-risk (OAR) dose as compared to CT-based delineation.

Methods and materials

Patients in this study were treated to 79.2 Gy in 44 fractions via intensity modulated radiotherapy using an MRI-based expansion method, which excluded OARs when performing a 5 mm isotropic (except 4 mm posterior) expansion from gross tumor volume to clinical target volume (CTV), followed by an isotropic 5 mm expansion to generate the planning target volume (PTV). Ten cases were re-planned using CT-delineated prostate with CTV-to-PTV expansion of isotropic 8 mm, except for a 5 mm posterior expansion, with comparison of PTV volumes, TCP and normal tissue complication probability (NTCP) to the MRI-based method. Under IRB approved protocol, we retrospectively evaluated 51 patients treated with the MRI-based method for acute bladder and rectal toxicity with CTC-AE version 4.0 used for scoring.

Results

MRI-based PTV volume differed by 4% compared to CT-based PTV volume. Radiobiological calculated TCP of the MRI-based method was found comparable to CT-based methods with an average equivalent uniform dose of 80.5 Gy and 80.1 Gy respectively. Statistically significant decrease in bladder NTCP (toxicity Grade 2 and above for 5% complications within 5 years post radiotherapy) was observed in the MRI-based method. Outcomes data collected showed 65% and 100% of patients studied experienced Grade 0/1 bladder and rectal acute toxicity respectively. Grade 2 bladder toxicity was indicated in the remaining 35% of patients studied with no Grade 3 toxicity reported.

Conclusions

Results showed comparable PTV volume with MRI-based method, and NTCP was reduced while maintaining TCP. Clinically, bladder and rectal toxicities were observed to be minimal.

ESTRO ACROP consensus guideline on CT- and MRI-based target volume delineation for primary radiation therapy of localized prostate cancer

BACKGROUND AND PURPOSE

Delineation of clinical target volumes (CTVs) remains a weak link in radiation therapy (RT), and large inter-observer variation is seen. Guidelines for target and organs at risk delineation for prostate cancer in the primary setting are scarce. The aim was to develop a delineation guideline obtained by consensus between a broad European group of radiation oncologists.

MATERIAL AND METHODS

An ESTRO contouring consensus panel consisting of leading radiation oncologists and one radiologist with known subspecialty expertise in prostate cancer was asked to delineate the prostate, seminal vesicles and rectum on co-registered CT and MRI scans. After evaluation of the different contours, literature review and multiple informal discussions by electronic mail a CTV definition was defined and a guide for contouring the CTV of the prostate and the rectum was developed.

RESULTS

The panel achieved consensus CTV contouring definitions to be used as guideline for primary RT of localized prostate cancer.

CONCLUSION

The ESTRO consensus on CT/MRI based CTV delineation for primary RT of localized prostate cancer, endorsed by a broad base of the radiation oncology community, is presented to improve consistency and reliability.

A novel CBCT-based method for derivation of CTV-PTV margins for prostate and pelvic lymph nodes treated with stereotactic ablative radiotherapy

BACKGROUND

Traditional CTV-PTV margin recipes are not generally applicable in the situation of stereotactic ablative radiotherapy (SABR) treatments of multiple target volumes with a single isocentre. In this work, we present a novel geometric method of margin derivation based on CBCT-derived anatomical data.

METHODS

Twenty patients with high-risk localized prostate cancer were selected for retrospective review. Individual volumes of interest (prostate, prostate and seminal vesicles and pelvic lymph nodes) were delineated on five representative CBCTs and registered to the planning CT using two registration protocols: bone match or prostate-based soft tissue match. Margins were incrementally expanded around composite CTV structures until 95% overlap was achieved.

RESULTS

CTV-PTV margins of 5.2, 6.5 and 7.6 mm were required for prostate, prostate and seminal vesicles and pelvic lymph nodes respectively using a prostate matching protocol. For the prostate and seminal vesicle structures, margins calculated using our method displayed good agreement with a conventional margin recipe (within ±1.0 mm).

CONCLUSIONS

We have presented an alternative method of CTV-PTV margin derivation that is applicable to SABR treatments with more than one isocentric target. These results have informed an institutional trial of prostate and pelvic nodal SABR in men with high-risk localized prostate cancer.

Variability in axillary lymph node delineation for breast cancer radiotherapy in presence of guidelines on a multi-institutional platform

AIM

To quantify the variability between radiation oncologists (ROs) when outlining axillary nodes in breast cancer.

MATERIAL AND METHODS

For each participating center, three ROs with different levels of expertise, i.e., junior (J), senior (S) and expert (E), contoured axillary nodal levels (L1, L2, L3 and L4) on the CT images of three different patients (P) of an increasing degree of anatomical complexity (from P1 to P2 to P3), according to contouring guidelines. Consensus contours were generated using the simultaneous truth and performance level estimation (STAPLE) method.

RESULTS

Fifteen centers and 42 ROs participated. Overall, the median Dice similarity coefficient was 0.66. Statistically significant differences were observed according to the level of expertise (better agreement for J and E, worse for S); the axillary level (better agreement for L1 and L4, worse for L3); the patient (better agreement for P1, worse for P3). Statistically significant differences in contouring were found in 18% of the inter-center comparison. Less than a half of the centers could claim to have a good agreement between the internal ROs.

CONCLUSIONS

The overall intra-institute and inter-institute agreement was moderate. Central lymph-node levels were the most critical and variability increased as the complexity of the patient's anatomy increased. These findings might have an effect on the interpretation of results from multicenter and even mono-institute studies.

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.

Implementation of diffusion-weighted magnetic resonance imaging in target delineation of central lung cancer accompanied with atelectasis in precision radiotherapy

Radiotherapy, particularly the target delineation of cancer based on scanned images, plays a key role in the planning of cancer treatment. Recently, diffusion-weighted magnetic resonance imaging (DW-MRI) has emerged as a prospective superior procedure compared with intensified computed tomography (CT) and positron emission tomography (PET) in the target delineation of cancer. However, the implication of DW-MRI in lung cancer, the leading cause of cancer-associated mortality worldwide, has not been extensively evaluated. In the present study, the gross target volumes of lung cancer masses delineated using the DW-MRI, CT and PET procedures were compared in a pairwise manner in a group of 27 lung cancer patients accompanied with atelectasis of various levels. The data showed that compared with CT and PET procedures, DW-MRI has a more precise delineation of lung cancer while exhibiting higher reproducibility. Together with the fact that it is non-invasive and cost-effective, these data demonstrate the great application potential of the DW-MRI procedure in cancer precision radiotherapy.

Advances in Prostate Cancer Magnetic Resonance Imaging and Positron Emission Tomography-Computed Tomography for Staging and Radiotherapy Treatment Planning

Conventional prostate cancer staging strategies have limited accuracy to define the location, grade, and burden of disease. Evaluations have historically relied upon prostate-specific antigen levels, digital rectal examinations, random systematic biopsies, computed tomography, pelvic lymphadenectomy, or ^99mtechnetium methylene diphosphonate bone scans. Today, risk-stratification tools incorporate these data in a weighted format to guide management. However, the limitations and potential consequences of their uncertainties are well known. Inaccurate information may contribute to understaging and undertreatment, or overstaging and overtreatment. Meanwhile, advances in multiparametric magnetic resonance imaging (MRI), whole-body MRI, lymphotropic nanoparticle-enhanced MRI, and positron emission tomography are now available to improve the accuracy of risk stratification to facilitate more informed medical decisions. They also guide radiation oncologists to develop more accurate treatment plans. This review provides a primer to incorporate these advances into routine clinical workflow.

Coverage-based treatment planning to accommodate delineation uncertainties in prostate cancer treatment

PURPOSE

To compare two coverage-based planning (CP) techniques with fixed margin-based (FM) planning for high-risk prostate cancer treatments, with the exclusive consideration of the dosimetric impact of delineation uncertainties of target structures and normal tissues.

METHODS

In this work, 19-patient data sets were involved. To estimate structure dose for each delineated contour under the influence of interobserver contour variability and CT image quality limitations, 1000 alternative structures were simulated by an average-surface-of-standard-deviation model, which utilized the patient-specific information of delineated structure and CT image contrast. An IMRT plan with zero planning-target-volume (PTV) margin on the delineated prostate and seminal vesicles [clinical-target-volume (CTV prostate) and CTVSV] was created and dose degradation due to contour variability was quantified by the dosimetric consequences of 1000 alternative structures. When D98 failed to achieve a 95% coverage probability objective D98,95 ≥ 78 Gy (CTV prostate) or D98,95 ≥ 66 Gy (CTVSV), replanning was performed using three planning techniques: (1) FM (PTV prostate margin = 4,5,6 mm and PTVSV margin = 4,5,7 mm for RL, PA, and SI directions, respectively), (2) CPOM which optimized uniform PTV margins for CTV prostate and CTVSV to meet the D98,95 objectives, and (3) CPCOP which directly optimized coverage-based objectives for all the structures. These plans were intercompared by computing percentile dose-volume histograms and tumor-control probability/normal tissue complication probability (TCP/NTCP) distributions.

RESULTS

Inherent contour variability resulted in unacceptable CTV coverage for the zero-PTV-margin plans for all patients. For plans designed to accommodate contour variability, 18/19 CP plans were most favored by achieving desirable D98,95 and TCP/NTCP values. The average improvement of probability of complication free control was 9.3% for CPCOP plans and 3.4% for CPOM plans.

CONCLUSIONS

When the delineation uncertainties need to be considered for prostate patients, CP techniques can produce more desirable plans than FM plans for most patients. The relative advantages between CPCOP and CPOM techniques are patient specific.

Comparison of manual and automatic MR-CT registration for radiotherapy of prostate cancer

In image‐guided radiotherapy (IGRT) of prostate cancer, delineation of the clinical target volume (CTV) often relies on magnetic resonance (MR) because of its good soft‐tissue visualization. Registration of MR and computed tomography (CT) is required in order to add this accurate delineation to the dose planning CT. An automatic approach for local MR‐CT registration of the prostate has previously been developed using a voxel property‐based registration as an alternative to a manual landmark‐based registration. The aim of this study is to compare the two registration approaches and to investigate the clinical potential for replacing the manual registration with the automatic registration. Registrations and analysis were performed for 30 prostate cancer patients treated with IGRT using a Ni‐Ti prostate stent as a fiducial marker. The comparison included computing translational and rotational differences between the approaches, visual inspection, and computing the overlap of the CTV. The computed mean translational difference was 1.65, 1.60, and 1.80 mm and the computed mean rotational difference was 1.51°, 3.93°, and 2.09° in the superior/inferior, anterior/posterior, and medial/lateral direction, respectively. The sensitivity of overlap was 87%. The results demonstrate that the automatic registration approach performs registrations comparable to the manual registration.

PACS number(s): 87.57.nj, 87.61.‐c, 87.57.Q‐, 87.56.J‐

MRI-guided prostate adaptive radiotherapy - A systematic review

Dose escalated radiotherapy improves outcomes for men with prostate cancer. A plateau for benefit from dose escalation using EBRT may not have been reached for some patients with higher risk disease. The use of increasingly conformal techniques, such as step and shoot IMRT or more recently VMAT, has allowed treatment intensification to be achieved whilst minimising associated increases in toxicity to surrounding normal structures. To support further safe dose escalation, the uncertainties in the treatment target position will need be minimised using optimal planning and image-guided radiotherapy (IGRT). In particular the increasing usage of profoundly hypo-fractionated stereotactic therapy is predicated on the ability to confidently direct treatment precisely to the intended target for the duration of each treatment. This article reviews published studies on the influences of varies types of motion on daily prostate position and how these may be mitigated to improve IGRT in future. In particular the role that MRI has played in the generation of data is discussed and the potential role of the MR-Linac in next-generation IGRT is discussed.

Maintaining prostate contouring consistency following an educational intervention

Introduction

The aim of this study was to assess variation in prostate contouring 12 months following a structured interactive educational intervention (EI) and to test the hypothesis that EIs positively impact on prostate contouring accuracy and consistency long term.

Methods

A common set of computed tomography (CT) and magnetic resonance imaging (MRI) data sets were used to assess prostate contouring consistency before, immediately after and 12 months following an EI. No further EIs were provided after the initial EI. Contour variation was assessed using the volume ratio (VR), defined as the ratio of the encompassing volume to common volume.

Results

Of the original five radiation oncologists (ROs) at baseline, four completed all assessments, and one was unavailable at 12 months follow‐up. At 12 months, mean VR deteriorated by 3.2% on CT and 1.9% on MRI compared to immediately post EI. Overall, compared to the pre‐EI baseline VR, an improvement of 11.4% and 10.8% was demonstrated on CT and MRI, respectively.

Conclusion

Good retention of applied knowledge 12 months following an EI on prostate contouring was demonstrated. This study advocates for EIs to be included as part of continuing medical education to reduce contour variation among ROs and improve knowledge retention long term.

Contouring variability of human- and deformable-generated contours in radiotherapy for prostate cancer

This study was designed to evaluate contouring variability of human-and deformable-generated contours on planning CT (PCT) and CBCT for ten patients with low-or intermediate-risk prostate cancer. For each patient in this study, five radiation oncologists contoured the prostate, bladder, and rectum, on one PCT dataset and five CBCT datasets. Consensus contours were generated using the STAPLE method in the CERR software package. Observer contours were compared to consensus contour, and contour metrics (Dice coefficient, Hausdorff distance, Contour Distance, Center-of-Mass [COM] Deviation) were calculated. In addition, the first day CBCT was registered to subsequent CBCT fractions (CBCTn: CBCT2-CBCT5) via B-spline Deformable Image Registration (DIR). Contours were transferred from CBCT1 to CBCTn via the deformation field, and contour metrics were calculated through comparison with consensus contours generated from human contour set. The average contour metrics for prostate contours on PCT and CBCT were as follows: Dice coefficient-0.892 (PCT), 0.872 (CBCT-Human), 0.824 (CBCT-Deformed); Hausdorff distance-4.75 mm (PCT), 5.22 mm (CBCT-Human), 5.94 mm (CBCT-Deformed); Contour Distance (overall contour)-1.41 mm (PCT), 1.66 mm (CBCT-Human), 2.30 mm (CBCT-Deformed); COM Deviation-2.01 mm (PCT), 2.78 mm (CBCT-Human), 3.45 mm (CBCT-Deformed). For human contours on PCT and CBCT, the difference in average Dice coefficient between PCT and CBCT (approx. 2%) and Hausdorff distance (approx. 0.5 mm) was small compared to the variation between observers for each patient (standard deviation in Dice coefficient of 5% and Hausdorff distance of 2.0 mm). However, additional contouring variation was found for the deformable-generated contours (approximately 5.0% decrease in Dice coefficient and 0.7 mm increase in Hausdorff distance relative to human-generated contours on CBCT). Though deformable contours provide a reasonable starting point for contouring on CBCT, we conclude that contours generated with B-Spline DIR require physician review and editing if they are to be used in the clinic.

MRI target delineation may reduce long-term toxicity after prostate radiotherapy

BACKGROUND AND PURPOSE

Aiming for minimal toxicity after radical prostate cancer (PC) radiotherapy (RT), magnetic resonance imaging (MRI) target delineation could be a possible benefit knowing that clinical target volumes (CTV) are up to 30% smaller, when CTV delineation on MRI is compared to standard computed tomography (CT). This study compares long-term toxicity using CT or MRI delineation before PC RT.

MATERIAL AND METHODS

Urinary and rectal toxicity assessments 36 months after image-guided RT (78 Gy) using CTC-AE scores in two groups of PC patients. Peak symptom score values were registered. One group of patients (n=72) had standard CT target delineation and gold markers as fiducials. Another group of patients (n=73) had MRI target delineation and a nickel-titanium stent as fiducial.

RESULTS

At 36 months no difference in overall survival (92% in both groups, p=0.29) or in PSA-relapse free survival was found between the groups (MRI=89% and CT=94%, p=0.67). A significantly smaller CTV was found in the MRI group (p=0.02). Urinary retention and frequency were significantly reduced in the MRI group (p=0.03 in the matter of both). The overall urinary and rectal toxicity did not differ between the two groups.

CONCLUSION

MRI delineation leads to a significantly reduced CTV. Significantly lower urinary frequency and urinary retention toxicity scores were observed following MRI delineation. The study did not find significant differences in overall urinary or rectal toxicity between the two groups. PSA-relapse survival did not differ between the two groups at 36 months.

Dosimetric effects of bladder and rectal contrast agents in prostate radiotherapy

Background and purpose

Accurate delineation of the target volume and organs at risk (OARs) are vital to ensure systematic errors are small. The use of contrast agents (CAs) in the bladder and rectum may aid contouring and reduce inter and intra-observer variability. The aim of this study was to evaluate the dosimetric effect of the presence of such contrast on the monitor units (MUs), planning target volume (PTV), rectum and bladder.

Materials and methods

The prostate, seminal vesicles, rectum and bladder were contoured by a single observer on ten patients with bladder and rectal contrast. To evaluate the dosimetric effect of the presence of contrast, the density of the ten patients with contrast in the bladder and rectum was virtually changed to 1 g/cm3. A four-field 15 MV conformal radiation therapy technique was applied in which dose volume histograms and MUs were compared using computed tomographic (CT) density and the 1 g/cm3density.

Results

The presence of contrast resulted in a 0·09% (<1 MU) increase in anterior MUs and decrease of 1% (<1 MU) in the posterior beam MUs. Lateral beams were not affected. The PTV and bladder dose increased slightly without contrast. The rectum showed a maximum change of 0·62% dose among the measured dose values. A maximum dose of 0·3 Gy at the 30% volume was also seen.

Conclusions

The dosimetric effect of bladder and rectal CAs on MUs, dose to the PTV and OARs in using this technique was very small. This would not be clinically significant, but only if the extreme limits of dose volume constraints were being reached.

Automatic prostate segmentation in cone-beam computed tomography images using rigid registration

We propose to evaluate automatic three-dimensional gray-value rigid registration (RR) methods for prostate localization on cone-beam computed tomography (CBCT) scans. In total, 103 CBCT scans of 9 prostate patients have been analyzed. Each one was registered to the planning CT scan using different methods: (a) global RR, (b) pelvis bone structure RR, (c) bone RR refined by local soft-tissue RR using the CT clinical target volume (CTV) expanded with a 1, 3, 5, 8, 10, 12, 15 or 20-mm margin. To evaluate results, a radiation oncologist was asked to manually delineate the CTV on the CBCT scans. The Dice coefficients between each automatic CBCT segmentation - derived from the transformation of the manual CT segmentation - and the manual CBCT segmentation were calculated. Global or bone CT/CBCT RR has been shown to yield insufficient results in average. Local RR with an 8-mm margin around the CTV after bone RR was found to be the best candidate for systematically significantly improving prostate localization.

Prospective multi-center dosimetry study of low-dose Iodine-125 prostate brachytherapy performed after transurethral resection

Purpose

To evaluate in a multicenter setting the ability of centers to perform pre-implant permanent prostate brachytherapy planning, fulfilling dosimetric goals and constraints based on the Groupe de Curiethérapie-European Society for Radiotherapy and Oncology guidelines in the setting of implantation after prior prostate transurethral resection (TURP).

Material and methods

A reference transrectal ultrasound image set of the prostate gland from a patient who had undergone TURP was used. Contouring of the prostate, clinical target volume and organs at risk was performed by the coordinating center. Goals and constraints regarding the dosimetry were defined.

Results

Seventeen of twenty-five centers invited to participate were able to import the Digital Imaging and Communications in Medicine-images into their planning computer and plan the implant using the defined guidelines. All centers were able to plan treatment, and achieve the recommended objectives and constraints. However, sector analysis has shown a risk of under-dosage in the anterior part of the prostate.

Conclusions

Correct pre-implantation planning with adherence to protocol guidelines and in compliance with defined dosimetric constraints seems feasible in a post-TURP setting, at least on a theoretical basis. A prospective study evaluating the outcome of prostate brachytherapy performed after TURP can therefore be undertaken with an expectation of a correct dosimetry in the multicenter setting.

Improved tumour control probability with MRI-based prostate brachytherapy treatment planning

BACKGROUND

Due to improved visibility on MRI, contouring of the prostate is improved compared to CT. The aim of this study was to quantify the benefits of using MRI for treatment planning as compared to CT-based planning for temporary implant prostate brachytherapy.

MATERIAL AND METHODS

CT and MRI image data of 13 patients were used to delineate the prostate and organs at risk (OARs) and to reconstruct the implanted catheters (typically 12). An experienced treatment planner created plans on the CT-based structure sets (CT-plan) and on the MRI-based structure sets (MRI-plan). Then, active dwell-positions and weights of the CT-plans were transferred to the MRI-based structure sets (CT-plan(MRI-contours)) and resulting dosimetric parameters and tumour control probabilities (TCPs) were studied.

RESULTS

For the CT-plan(MRI-contours) a statistically significant lower target coverage was detected: mean V100 was 95.1% as opposed to 98.3% for the original plans (p < 0.01). Planning on CT caused cold-spots that influence the TCP. MRI-based planning improved the TCPs by 6-10%, depending on the parameters of the radiobiological model used for TCP calculation. Basing the treatment plan on either CT- or MRI-delineations does not influence plan quality.

CONCLUSION

Evaluation of CT-based treatment planning by transferring the plan to MRI reveals underdosage of the prostate, especially at the base side. Planning on MRI can prevent cold-spots in the tumour and improves the TCP.

Accident prevention in day-to-day clinical radiation therapy practice

Nearly 50-60% of cancer patients will undergo radiotherapy at some point in their treatment. Around 85% of the world's population live in developing countries served by approximately 30% of the world's radiotherapy facilities. It has been suggested that 1 megavoltage unit is required for every 500 new treatment courses per year, while others estimate that 1 megavoltage unit is needed for every 300 new treatments. However, these numbers do not necessarily take into account the development of new technologies and treatment modalities, which are more time- and resource-intensive. The International Commission on Radiological Protection has emphasised that 'purchasing new equipment without a concomitant effort on education and training and on a programme of quality assurance is dangerous', and 'the decision to implement a new technology for radiation therapy should be based on a thorough evaluation of the expected benefits, rather than being driven by the technology itself'. It is estimated that the rate of serious mistakes could be as high as 0.2%, which is several orders of magnitude higher than the rate reported for commercial aviation. So, how safe is safe? It can be stated that the development of a culture of safety is critical and requires efforts in education and training, which could prove difficult in overloaded departments.

Concurrent segmentation of the prostate on MRI and CT via linked statistical shape models for radiotherapy planning

PURPOSE

Prostate gland segmentation is a critical step in prostate radiotherapy planning, where dose plans are typically formulated on CT. Pretreatment MRI is now beginning to be acquired at several medical centers. Delineation of the prostate on MRI is acknowledged as being significantly simpler to perform, compared to delineation on CT. In this work, the authors present a novel framework for building a linked statistical shape model (LSSM), a statistical shape model (SSM) that links the shape variation of a structure of interest (SOI) across multiple imaging modalities. This framework is particularly relevant in scenarios where accurate boundary delineations of the SOI on one of the modalities may not be readily available, or difficult to obtain, for training a SSM. In this work the authors apply the LSSM in the context of multimodal prostate segmentation for radiotherapy planning, where the prostate is concurrently segmented on MRI and CT.

METHODS

The framework comprises a number of logically connected steps. The first step utilizes multimodal registration of MRI and CT to map 2D boundary delineations of the prostate from MRI onto corresponding CT images, for a set of training studies. Hence, the scheme obviates the need for expert delineations of the gland on CT for explicitly constructing a SSM for prostate segmentation on CT. The delineations of the prostate gland on MRI and CT allows for 3D reconstruction of the prostate shape which facilitates the building of the LSSM. In order to perform concurrent prostate MRI and CT segmentation using the LSSM, the authors employ a region-based level set approach where the authors deform the evolving prostate boundary to simultaneously fit to MRI and CT images in which voxels are classified to be either part of the prostate or outside the prostate. The classification is facilitated by using a combination of MRI-CT probabilistic spatial atlases and a random forest classifier, driven by gradient and Haar features.

RESULTS

The authors acquire a total of 20 MRI-CT patient studies and use the leave-one-out strategy to train and evaluate four different LSSMs. First, a fusion-based LSSM (fLSSM) is built using expert ground truth delineations of the prostate on MRI alone, where the ground truth for the gland on CT is obtained via coregistration of the corresponding MRI and CT slices. The authors compare the fLSSM against another LSSM (xLSSM), where expert delineations of the gland on both MRI and CT are employed in the model building; xLSSM representing the idealized LSSM. The authors also compare the fLSSM against an exclusive CT-based SSM (ctSSM), built from expert delineations of the gland on CT alone. In addition, two LSSMs trained using trainee delineations (tLSSM) on CT are compared with the fLSSM. The results indicate that the xLSSM, tLSSMs, and the fLSSM perform equivalently, all of them out-performing the ctSSM.

CONCLUSIONS

The fLSSM provides an accurate alternative to SSMs that require careful expert delineations of the SOI that may be difficult or laborious to obtain. Additionally, the fLSSM has the added benefit of providing concurrent segmentations of the SOI on multiple imaging modalities.

Comparison of prostate volume, shape, and contouring variability determined from preimplant magnetic resonance and transrectal ultrasound images

PURPOSE

To compare preimplant prostate contours and contouring variability between magnetic resonance (MR) and transrectal ultrasound images.

METHODS AND MATERIALS

Twenty-three patients were imaged using ultrasound (US) and MR before permanent brachytherapy treatment. Images were anonymized, randomized, and duplicated, and the prostate was independently delineated by five radiation oncologists. Contours were compared in terms of volume, dimensions, posterior rectal indentation, and observer variability. The Jaccard index quantified spatial overlap between contours from duplicated images.

RESULTS

The mean US/MR volume ratio was 0.99±0.08 (p=0.5). The width, height, and length ratios for the prostate were 0.98±0.06 (p=0.09), 0.99±0.08 (p=0.4), and 1.05±0.14 (p=0.1). Rectal indentation was larger on US by 0.18mL (p=0.01) and correlated with prostate volume (p<0.01). MR and US interobserver variability in volume were similar at 3.5±1.7 and 3.3±1.9mL (p=0.6). Intraobserver variability was smaller on US at 1.4±1.1mL compared with MR at 2.4±2.2mL (p=0.01). Local intraobserver variability was lower on US at the midgland slice (p<0.01) but lower on MR at the base (p<0.01) and apex (p<0.01) slices.

CONCLUSIONS

US is comparable to MR for preimplant prostate delineation, with no significant difference in volume and dimensions. Rectal indentation because of the transrectal ultrasound probe was measurable, although the effects were small. Intraobserver variability was lower on US for the prostate volume but was lower on MR locally at the base and apex. However, the difference was not observed for the interobserver variability, which was similar between MR and US.

Multidisciplinary collaborative gross tumour volume definition for lung cancer radiotherapy: a prospective study

Variability in gross tumour volume (GTV) definition is a major source of systematic error in conformal radiotherapy. This prospective study assesses the role of multidisciplinary collaboration between oncologists and radiologists in defining lung cancer volumes. Twenty patients with non-small cell lung cancer due to receive three-dimensional conformal radiotherapy formed the study population. GTVs were defined by a radiologist (GTVrad) and an oncologist (GTVonc) using available clinical information and imaging. A collaborative meeting was then held to agree on a final, common GTV (GTVfin) to be used for treatment planning, and differences analysed. The collaboration changed the GTV in 19/20 patients with a total of 50 regions being edited. Changes made were categorized as (a) differentiation of tumour from atelectasis or ground glass shadowing, (b) separation of tumour from vasculature, and (c) defining mediastinal extent of tumour. Oncologists were more confident in the GTVfin than the GTVonc. The radiologist took longer to define the GTV than the oncologist. Real-time collaborative GTV definition by a radiologist and oncologist is practical and feasible. This approach allows specific areas of uncertainty to be categorized and focussed on, reducing systematic error in GTV definition. The physician's approach to risk and decision making for each patient may also play a role.

Expansion/de-expansion tool to quantify the accuracy of prostate contours

PURPOSE

Accurate delineation of the prostate gland on computed tomography (CT) remains a persistent challenge and continues to introduce geometric uncertainty into the planning and delivery of external beam radiotherapy. We, therefore, developed an expansion/de-expansion tool to quantify the contour errors and determine the location of the deviations.

METHODS AND MATERIALS

A planning CT scan and magnetic resonance imaging scan were prospectively acquired for 10 patients with prostate cancer. The prostate glands were contoured by 3 independent observers using the CT data sets with instructions to contour the prostate without underestimation but to minimize overestimation. The standard prostate for each patient was defined using magnetic resonance imaging and CT on multiple planes. After registration of the CT and magnetic resonance imaging data sets, the CT-defined prostates were scored for accuracy. The contours were defined as ideal if they were within a 2.5-mm expansion of the standard without underestimation, acceptable if they were within a 5.0-mm expansion and a 2.5-mm de-expansion, and unacceptable if they extended >5.0 mm or underestimated the prostate by >2.5 mm.

RESULTS

A total of 636 CT slices were individually analyzed, with the vast majority scored as ideal or acceptable. However, none of the 30 prostate contour sets had all the contours scored as ideal or acceptable. For all 3 observers, the unacceptable contours were more likely from underestimation than overestimation of the prostate. The errors were more common at the base and apex than the mid-gland.

CONCLUSIONS

The expansion/de-expansion tool allows for directed feedback on the location of contour deviations, as well as the determination of over- or underestimation of the prostate. This metric might help improve the accuracy of prostate contours.

Real time 4D IMRT treatment planning based on a dynamic virtual patient model: proof of concept

PURPOSE

To develop a novel four-dimensional (4D) intensity modulated radiation therapy (IMRT) treatment planning methodology based on dynamic virtual patient models.

METHODS

The 4D model-based planning (4DMP) is a predictive tracking method which consists of two main steps: (1) predicting the 3D deformable motion of the target and critical structures as a function of time during treatment delivery; (2) adjusting the delivery beam apertures formed by the dynamic multi-leaf collimators (DMLC) to account for the motion. The key feature of 4DMP is the application of a dynamic virtual patient model in motion prediction, treatment beam adjustment, and dose calculation. A lung case was chosen to demonstrate the feasibility of the 4DMP. For the lung case, a dynamic virtual patient model (4D model) was first developed based on the patient's 4DCT images. The 4D model was capable of simulating respiratory motion of different patterns. A model-based registration method was then applied to convert the 4D model into a set of deformation maps and 4DCT images for dosimetric purposes. Based on the 4D model, 4DMP treatment plans with different respiratory motion scenarios were developed. The quality of 4DMP plans was then compared with two other commonly used 4D planning methods: maximum intensity projection (MIP) and planning on individual phases (IP).

RESULTS

Under regular periodic motion, 4DMP offered similar target coverage as MIP with much better normal tissue sparing. At breathing amplitude of 2 cm, the lung V20 was 23.9% for a MIP plan and 16.7% for a 4DMP plan. The plan quality was comparable between 4DMP and IP: PTV V97 was 93.8% for the IP plan and 93.6% for the 4DMP plan. Lung V20 of the 4DMP plan was 2.1% lower than that of the IP plan and Dmax to cord was 2.2 Gy higher. Under a real time irregular breathing pattern, 4DMP had the best plan quality. PTV V97 was 90.4% for a MIP plan, 88.6% for an IP plan and 94.1% for a 4DMP plan. Lung V20 was 20.1% for the MIP plan, 17.8% for the IP plan and 17.5% for the 4DMP plan. The deliverability of the real time 4DMP plan was proved by calculating the maximum leaf speed of the DMLC.

CONCLUSIONS

The 4D model-based planning, which applies dynamic virtual patient models in IMRT treatment planning, can account for the real time deformable motion of the tumor under different breathing conditions. Under regular motion, the quality of 4DMP plans was comparable with IP and superior to MIP. Under realistic motion in which breathing amplitude and period change, 4DMP gave the best plan quality of the three 4D treatment planning techniques.

Evaluation of tomotherapy MVCT image enhancement program for tumor volume delineation

The aims of this study were to investigate the variability between physicians in delineation of head and neck tumors on original tomotherapy megavoltage CT (MVCT) studies and corresponding software enhanced MVCT images, and to establish an optimal approach for evaluation of image improvement. Five physicians contoured the gross tumor volume (GTV) for three head and neck cancer patients on 34 original and enhanced MVCT studies. Variation between original and enhanced MVCT studies was quantified by DICE coefficient and the coefficient of variance. Based on volume of agreement between physicians, higher correlation in terms of average DICE coefficients was observed in GTV delineation for enhanced MVCT for patients 1, 2, and 3 by 15%, 3%, and 7%, respectively, while delineation variance among physicians was reduced using enhanced MVCT for 12 of 17 weekly image studies. Enhanced MVCT provides advantages in reduction of variance among physicians in delineation of the GTV. Agreement on contouring by the same physician on both original and enhanced MVCT was equally high.

PACS numbers: 87.57.N‐, 87.57.np, 87.57.nt

A review of methods of analysis in contouring studies for radiation oncology

Inter-observer variability in anatomical contouring is the biggest contributor to uncertainty in radiation treatment planning. Contouring studies are frequently performed to investigate the differences between multiple contours on common datasets. There is, however, no widely accepted method for contour comparisons. The purpose of this study is to review the literature on contouring studies in the context of radiation oncology, with particular consideration of the contouring comparison methods they employ. A literature search, not limited by date, was conducted using Medline and Google Scholar with key words: contour, variation, delineation, inter/intra observer, uncertainty and trial dummy-run. This review includes a description of the contouring processes and contour comparison metrics used. The use of different processes and metrics according to tumour site and other factors were also investigated with limitations described. A total of 69 relevant studies were identified. The most common tumour sites were prostate (26), lung (10), head and neck cancers (8) and breast (7).The most common metric of comparison was volume used 59 times, followed by dimension and shape used 36 times, and centre of volume used 19 times. Of all 69 publications, 67 used a combination of metrics and two used only one metric for comparison. No clear relationships between tumour site or any other factors that may influence the contouring process and the metrics used to compare contours were observed from the literature. Further studies are needed to assess the advantages and disadvantages of each metric in various situations.

Can images obtained with high field strength magnetic resonance imaging reduce contouring variability of the prostate?

PURPOSE

The objective of this study is to determine whether there is less contouring variability of the prostate using higher-strength magnetic resonance images (MRI) compared with standard MRI and computed tomography (CT).

METHODS AND MATERIALS

Forty patients treated with prostate brachytherapy were accrued to a prospective study that included the acquisition of 1.5-T MR and CT images at specified time points. A subset of 10 patients had additional 3.0-T MR images acquired at the same time as their 1.5-T MR scans. Images from each of these patients were contoured by 5 radiation oncologists, with a random subset of patients repeated to quantify intraobserver contouring variability. To minimize bias in contouring the prostate, the image sets were placed in folders in a random order with all identifiers removed from the images.

RESULTS

Although there was less interobserver contouring variability in the overall prostate volumes in 1.5-T MRI compared with 3.0-T MRI (p < 0.01), there was no significant differences in contouring variability in the different regions of the prostate between 1.5-T MRI and 3.0-T MRI. MRI demonstrated significantly less interobserver contouring variability in both 1.5-T and 3.0-T compared with CT in overall prostate volumes (p < 0.01, p = 0.01), with the greatest benefits being appreciated in the base of the prostate. Overall, there was less intraobserver contouring variability than interobserver contouring variability for all of the measurements analyzed.

CONCLUSIONS

Use of 3.0-T MRI does not demonstrate a significant improvement in contouring variability compared with 1.5-T MRI, although both magnetic strengths demonstrated less contouring variability compared with CT.