Analysis of re-recurrent rectal cancer after curative treatment of locally recurrent rectal cancer.

PURPOSE: Substantiating data guiding clinical decision making in locally recurrent rectal cancer (LRRC) is lacking, specifically in target volume (TV) definition for chemoradiotherapy (CRT). A case-by-case review of local re-recurrences (re-LRRC) after multimodal treatment for LRRC was performed, to determine location of re-LRRC and assess whether treatment could have been improved. METHODS: All patients treated with curative intent for LRRC at the Catharina Hospital Eindhoven from October 2016 onwards, in whom complete imaging of (re-)LRRC and radiotherapy was available, were retrieved. Patients were discussed in plenary meetings with expert colorectal surgeons, radiation oncologists and radiologists. Each case was classified based on re-LRRC location, whether it was in accordance with the (current) radiotherapy protocol, and whether multimodal management would have been different in retrospect. RESULTS: Thirty-three cases were discussed. LRRC treatment was deemed suboptimal in 17/33 patients, due to different target volumes (13/17) and/or different surgery (9/17). 15/33 (46 %) of re-LRRC developed in-field of the prior radiotherapy TV, possibly showing RT-resistant disease. Other re-LRRCs developed out-field (n = 5, 15 %), marginally (n = 6, 18 %), or in a combined fashion (n = 7, 21 %). In retrospect, 48 % of cases were irradiated in line with current TV recommendations. TVs of 13/33 cases would have been altered if irradiated today. CONCLUSION: This study highlights room for improvement within current standard-ofcare treatment for LRRC. Different surgical management or TVs may have improved outcome in up to half of discussed cases. Further delineation guideline development, incorporating the results from this study, may improve oncological outcome, specifically local control, for LRRC patients.

Validation of different automated segmentation models for target volume contouring in postoperative radiotherapy for breast cancer and regional nodal irradiation.

Introduction: Target volume delineation is routinely performed in postoperative radiotherapy (RT) for breast cancer patients, but it is a time-consuming process. The aim of the present study was to validate the quality, clinical usability and institutional-specific implementation of different auto-segmentation tools into clinical routine. Methods: Three different commercially available, artificial intelligence-, ESTRO-guideline-based segmentation models (M1-3) were applied to fifty consecutive reference patients who received postoperative local RT including regional nodal irradiation for breast cancer for the delineation of clinical target volumes: the residual breast, implant or chestwall, axilla levels 1 and 2, the infra- and supraclavicular regions, the interpectoral and internal mammary nodes. Objective evaluation metrics of the created structures were conducted with the Dice similarity index (DICE) and the Hausdorff distance, and a manual evaluation of usability. Results: The resulting geometries of the segmentation models were compared to the reference volumes for each patient and required no or only minor corrections in 72 % (M1), 64 % (M2) and 78 % (M3) of the cases. The median DICE and Hausdorff values for the resulting planning target volumes were 0.87-0.88 and 2.96-3.55, respectively. Clinical usability was significantly correlated with the DICE index, with calculated cut-off values used to define no or minor adjustments of 0.82-0.86. Right or left sided target and breathing method (deep inspiration breath hold vs. free breathing) did not impact the quality of the resulting structures. Conclusion: Artificial intelligence-based auto-segmentation programs showed high-quality accuracy and provided standardization and efficient support for guideline-based target volume contouring as a precondition for fully automated workflows in radiotherapy treatment planning.

Enhanced head and neck radiotherapy target definition through multidisciplinary delineation and peer review: A prospective single-center study.

This study evaluates the benefit of weekly delineation and peer review by a multidisciplinary team (MDT) of radiation oncologists (ROs), radiologists (RXs), and nuclear medicine (NM) physicians in defining primary and lymph node tumor volumes (GTVp and GTVn) for head and neck cancer (HNC) radiotherapy. This study includes 30 consecutive HNC patients referred for definitive curative (chemo)-radiotherapy. Imaging data including head and neck MRI, [18F]-FDG-PET and CT scan were evaluated by the MDT. The RO identified the 'undeniable' tumor as GTVp_core and determined GTVp_max, representing the maximum tumoral volume. The MDT delineation (MDT-D) by RX and NM physicians outlined their respective primary GTVs (GTVp_RX and GTVp_NM). During the MDT meeting (MDT-M), these contours were discussed to reach a consensus on the final primary GTV (GTVp_final). In the comparative analysis of various GTVp delineations, we performed descriptive statistics and assessed two MDT-M factors: 1) the added value of MDT-M, which includes the section of GTVp_final outside GTVp_core but within GTVp_RX or GTVp_NM, and 2) the part of GTVp_final that deviates from GTVp_max, representing the area missed by the RO. For GTVn, discussions evaluated lymph node extent and malignancy, documenting findings and the frequency of disagreements. The average GTVp core and max volumes were 19.5 cc (range: 0.4-90.1) and 22.1 cc (range: 0.8-106.2), respectively. Compared to GTVp_core, MDT-D to GTVp_final added an average of 3.3 cc (range: 0-25.6) and spared an average of 1.3 cc (0-15.6). Compared to GTVp_max, MDT-D and -M added an average of 2.7 cc (range: 0-20.3) and removed 2.3 cc (0-21.3). The most frequent GTVn discussions included morphologically suspicious nodes not fixing on [18F]-FDG-PET and small [18F]-FDG-PET negative retropharyngeal lymph nodes. Multidisciplinary review of target contours in HNC is essential for accurate treatment planning, ensuring precise tumor and lymph node delineation, potentially improving local control and reducing toxicity.

Comparison of different target volume delineation strategies based on recurrence patterns in adjuvant radiotherapy for glioblastoma.

Background: Radiation Therapy Oncology Group (RTOG) and the European Organization for Research and Treatment of Cancer (EORTC) recommendations are commonly used guidelines for adjuvant radiotherapy in glioblastoma. In our institutional protocol, we delineate T2-FLAIR alterations as gross target volume (GTV) with reduced clinical target volume (CTV) margins. We aimed to present our oncologic outcomes and compare the recurrence patterns and planning parameters with EORTC and RTOG delineation strategies. Methods: Eighty-one patients who received CRT between 2014 and 2021 were evaluated retrospectively. EORTC and RTOG delineations performed on the simulation computed tomography and recurrence patterns and planning parameters were compared between delineation strategies. Statistical Package for the Social Sciences (SPSS) version 23.0 (IBM, Armonk, NY, USA) was utilized for statistical analyses. Results: Median overall survival and progression-free survival were 21 months and 11 months, respectively. At a median 18 month follow-up, of the 48 patients for whom recurrence pattern analysis was performed, recurrence was encompassed by only our institutional protocol's CTV in 13 (27%) of them. For the remaining 35 (73%) patients, recurrence was encompassed by all separate CTVs. In addition to the 100% rate of in-field recurrence, the smallest CTV and lower OAR doses were obtained by our protocol. Conclusions: The current study provides promising results for including the T2-FLAIR alterations to the GTV with smaller CTV margins with impressive survival outcomes without any marginal recurrence. The fact that our protocol did not result in larger irradiated brain volume is further encouraging in terms of toxicity.

Clinical Evaluation of Deep Learning for Tumor Delineation on 18F-FDG PET/CT of Head and Neck Cancer.

Artificial intelligence (AI) may decrease 18F-FDG PET/CT-based gross tumor volume (GTV) delineation variability and automate tumor-volume-derived image biomarker extraction. Hence, we aimed to identify and evaluate promising state-of-the-art deep learning methods for head and neck cancer (HNC) PET GTV delineation. Methods: We trained and evaluated deep learning methods using retrospectively included scans of HNC patients referred for radiotherapy between January 2014 and December 2019 (ISRCTN16907234). We used 3 test datasets: an internal set to compare methods, another internal set to compare AI-to-expert variability and expert interobserver variability (IOV), and an external set to compare internal and external AI-to-expert variability. Expert PET GTVs were used as the reference standard. Our benchmark IOV was measured using the PET GTV of 6 experts. The primary outcome was the Dice similarity coefficient (DSC). ANOVA was used to compare methods, a paired t test was used to compare AI-to-expert variability and expert IOV, an unpaired t test was used to compare internal and external AI-to-expert variability, and post hoc Bland-Altman analysis was used to evaluate biomarker agreement. Results: In total, 1,220 18F-FDG PET/CT scans of 1,190 patients (mean age ± SD, 63 ± 10 y; 858 men) were included, and 5 deep learning methods were trained using 5-fold cross-validation (n = 805). The nnU-Net method achieved the highest similarity (DSC, 0.80 [95% CI, 0.77-0.86]; n = 196). We found no evidence of a difference between expert IOV and AI-to-expert variability (DSC, 0.78 for AI vs. 0.82 for experts; mean difference of 0.04 [95% CI, -0.01 to 0.09]; P = 0.12; n = 64). We found no evidence of a difference between the internal and external AI-to-expert variability (DSC, 0.80 internally vs. 0.81 externally; mean difference of 0.004 [95% CI, -0.05 to 0.04]; P = 0.87; n = 125). PET GTV-derived biomarkers of AI were in good agreement with experts. Conclusion: Deep learning can be used to automate 18F-FDG PET/CT tumor-volume-derived imaging biomarkers, and the deep-learning-based volumes have the potential to assist clinical tumor volume delineation in radiation oncology.

Reliable Delineation of Clinical Target Volumes for Cervical Cancer Radiotherapy on CT/MR Dual-Modality Images.

Accurate delineation of the clinical target volume (CTV) is a crucial prerequisite for safe and effective radiotherapy characterized. This study addresses the integration of magnetic resonance (MR) images to aid in target delineation on computed tomography (CT) images. However, obtaining MR images directly can be challenging. Therefore, we employ AI-based image generation techniques to "intelligentially generate" MR images from CT images to improve CTV delineation based on CT images. To generate high-quality MR images, we propose an attention-guided single-loop image generation model. The model can yield higher-quality images by introducing an attention mechanism in feature extraction and enhancing the loss function. Based on the generated MR images, we propose a CTV segmentation model fusing multi-scale features through image fusion and a hollow space pyramid module to enhance segmentation accuracy. The image generation model used in this study improves the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) from 14.87 and 0.58 to 16.72 and 0.67, respectively, and improves the feature distribution distance and learning-perception image similarity from 180.86 and 0.28 to 110.98 and 0.22, achieving higher quality image generation. The proposed segmentation method demonstrates high accuracy, compared with the FCN method, the intersection over union ratio and the Dice coefficient are improved from 0.8360 and 0.8998 to 0.9043 and 0.9473, respectively. Hausdorff distance and mean surface distance decreased from 5.5573 mm and 2.3269 mm to 4.7204 mm and 0.9397 mm, respectively, achieving clinically acceptable segmentation accuracy. Our method might reduce physicians' manual workload and accelerate the diagnosis and treatment process while decreasing inter-observer variability in identifying anatomical structures.

Segmentation of 71 Anatomical Structures Necessary for the Evaluation of Guideline-Conforming Clinical Target Volumes in Head and Neck Cancers.

The delineation of the clinical target volumes (CTVs) for radiation therapy is time-consuming, requires intensive training and shows high inter-observer variability. Supervised deep-learning methods depend heavily on consistent training data; thus, State-of-the-Art research focuses on making CTV labels more homogeneous and strictly bounding them to current standards. International consensus expert guidelines standardize CTV delineation by conditioning the extension of the clinical target volume on the surrounding anatomical structures. Training strategies that directly follow the construction rules given in the expert guidelines or the possibility of quantifying the conformance of manually drawn contours to the guidelines are still missing. Seventy-one anatomical structures that are relevant to CTV delineation in head- and neck-cancer patients, according to the expert guidelines, were segmented on 104 computed tomography scans, to assess the possibility of automating their segmentation by State-of-the-Art deep learning methods. All 71 anatomical structures were subdivided into three subsets of non-overlapping structures, and a 3D nnU-Net model with five-fold cross-validation was trained for each subset, to automatically segment the structures on planning computed tomography scans. We report the DICE, Hausdorff distance and surface DICE for 71 + 5 anatomical structures, for most of which no previous segmentation accuracies have been reported. For those structures for which prediction values have been reported, our segmentation accuracy matched or exceeded the reported values. The predictions from our models were always better than those predicted by the TotalSegmentator. The sDICE with 2 mm margin was larger than 80% for almost all the structures. Individual structures with decreased segmentation accuracy are analyzed and discussed with respect to their impact on the CTV delineation following the expert guidelines. No deviation is expected to affect the rule-based automation of the CTV delineation.

Radiological Biomarkers in MRI directed Rectal Cancer Radiotherapy Volume Delineation.

Our study evaluated whether an MRI reporting system highlighting areas of contiguous and discontinuous extramural venous invasion (EMVI) can improve the accuracy of gross tumour volume (GTV) delineation. Initially, 27 consecutive patients with locally advanced rectal cancer treated between 2012 and 2014 were evaluated. We used an MRI reporting proforma that documented the position of the primary tumour, lymph nodes and EMVI. The new GTVs delineated were compared with historical radiotherapy treatment volumes to identify the frequency of GTV geographical miss. We observed that the delineation of involved nodes and areas of EMVI was more likely to represent sources of uncertainty wherein nodal GTV geographical miss was evident in 5 out of 27 patients (19%). Complete EMVI GTV geographical miss occurred in two patients (7%). We re-evaluated our radiotherapy practice in a further 27 patients after the implementation of a modified MRI reporting system. An improvement was seen; nodal miss was observed in two patients (7%) and partial EMVI miss in one patient (4%), although these areas were encompassed in the planning target volume (PTV). Our study shows that extramural venous invasion and involved nodes need to be highlighted on MRI to improve the accuracy of rectal cancer GTV delineation.

Optimization of supraclavicular lymph node clinical target volume delineation in high-risk breast cancer: a single center experience and recommendation.

BACKGROUND: Prophylactic irradiation of supraclavicular lymph node drainage areas can improve the regional control rate of lymph node-positive or lymph node-negative disease but a locally-advanced stage breast cancer, and it can reduce breast cancer-related mortality. However, many controversies exist in the clinical target volume delineation of supraclavicular lymph node drainage in patients with breast cancer. METHODS: We retrospectively analyzed 42 patients with breast cancer and supraclavicular lymph node metastasis at our hospital between January 2017 and December 2021. Among these cases, 32 were locally advanced and 10 were stage IV at initial treatment. A patient with breast cancer who did not undergo dissection of the supraclavicular and infraclavicular lymph nodes at our hospital was selected as a standard patient. A contrast-enhanced computed tomography (CT) scan for positioning was used as a template image, and blood vessels, muscles, and bony landmarks were used as references for positioning. The metastatic supraclavicular lymph nodes were identified in all enrolled patients and projected into the template CT images. RESULTS: The metastastic pattern of supraclavicular lymph node in breast cancer was proposed: distribution along the posterolateral border of the internal jugular vein (medial supraclavicular group) and along the transverse jugular vein (lateral supraclavicular group). We theorized that the lateral and posterior borders of the clinical target volume in the supraclavicular region should include the lymph nodes in the posterior triangle of the neck (level V) in high-risk individuals. If the metastatic axillary lymph node is extensive, then the superior border of the supraclavicular region should be moved upward appropriately. CONCLUSIONS: This study analyzed patients with breast cancer and supraclavicular lymph node metastasis at initial treatment, explored the metastastic pattern of supraclavicular lymph node, and applied anatomical knowledge to further optimize the target volume delineation of supraclavicular lymph node drainage area in high-risk breast cancer.

ESTRO ACROP consensus recommendation on the target volume definition for radiation therapy of macroscopic prostate cancer recurrences after radical prostatectomy.

Background: The European Society for Radiotherapy & Oncology (ESTRO) Advisory Committee for Radiation Oncology Practice (ACROP) panel on prostate bed delineation reflected on macroscopic local recurrences in patients referred for postoperative radiotherapy (PORT), a challenging situation without standardized approach, and decided to propose a consensus recommendation on target volume selection and definition. Methods: An ESTRO ACROP contouring consensus panel consisting of 12 radiation oncologists and one radiologist, all with subspecialty expertise in prostate cancer, was established. Participants were asked to delineate the prostate bed clinical target volumes (CTVs) in two separate clinically relevant scenarios: a local recurrence at the seminal vesicle bed and one apically at the level of the anastomosis. Both recurrences were prostate-specific membrane antigen (PSMA)-avid and had an anatomical correlate on magnetic resonance imaging (MRI). Participants also answered case-specific questionnaires addressing detailed recommendations on target delineation. Discussions via electronic mails and videoconferences for final editing and consensus were performed. Results: Contouring of the two cases confirmed considerable variation among the panelists. Finally, however, a consensus recommendation could be agreed upon. Firstly, it was proposed to always delineate the entire prostate bed as clinical target volume and not the local recurrence alone. The panel judged the risk of further microscopic disease outside of the visible recurrence too high to safely exclude the rest of the prostate bed from the CTV. A focused, "stereotactic" approach should be reserved for re-irradiation after previous PORT. Secondly, the option of a focal boost on the recurrence was discussed. Conclusion: Radiation oncologists are increasingly confronted with macroscopic local recurrences visible on imaging in patients referred for postoperative radiotherapy. It was recommended to always delineate and irradiate the entire prostate bed, and not the local recurrence alone, whatever the exact location of that recurrence. Secondly, specific dose-escalation on the macroscopic recurrence should only be considered if an anatomic correlate is visible. Such a focal boost is probably feasible, provided that OAR constraints are prioritized. Possible dose is also dependent on the location of the recurrence. Its potential benefit should urgently be investigated in prospective clinical trials.

Inter-observer variation of target volume delineation for CT-guided cervical cancer brachytherapy.

Purpose: Delineation is a critical and challenging step in radiotherapy planning. Differences in delineation among observers are common, despite the presence of contouring guidelines. This study aimed to identify the inter-observer variability in the target volume delineation of computed tomography (CT)-guided brachytherapy for cervical cancer. Material and methods: Four radiation oncologists (ROs) with different expertise levels delineated high-risk (HR) and intermediate-risk (IR) clinical target volume (CTV) according to GYN GEC-ESTRO recommendations, in a blinded manner on every CT set of ten locally advanced cervical cancer cases. The most experienced RO's contours were determined as the index and used for comparison. Dice similarity coefficient (DSC) and pairwise Hausdorff distance (HD) metrics were applied to compare the overlap and gross deviations of all contours. Results: Median DSC for HR-CTV and IR-CTV were 0.73 and 0.76, respectively, and a good concordance was achieved for both in majority of contours. While there was no difference in DSC measurements for HR-CTV among the three ROs, RO-3 provided improved DSC values for IR-CTV (p = 0.01). Median HD95 was 5.02 mm and 6.83 mm, and median HDave was 1.69 mm and 2.21 mm for HR-CTV and IR-CTV, respectively. There was no significant difference among ROs in HR-CTV for HD95 or HDave; however, IR-CTV value was significantly improved according to RO-3 (p = 0.01). Case-by-case HD analysis showed no significant inter-observer variations, except for two cases. Conclusions: The inter-observer agreement is generally high for target volumes in CT-guided brachytherapy for cervical cancer. The agreement is lower for IR-CTV than HR-CTV. The individual characteristics of each case and different expertise levels of the ROs may have caused the differences. Despite the good concordance for delineation, dosimetric consequences can still be clinically significant.

Impact of MRI on target volume definition in head and neck cancer patients.

BACKGROUND: Target volume definition for curative radiochemotherapy in head and neck cancer is crucial since the predominant recurrence pattern is local. Additional diagnostic imaging like MRI is increasingly used, yet it is usually hampered by different patient positioning compared to radiotherapy. In this study, we investigated the impact of diagnostic MRI in treatment position for target volume delineation. METHODS: We prospectively analyzed patients who were suitable and agreed to undergo an MRI in treatment position with immobilization devices prior to radiotherapy planning from 2017 to 2019. Target volume delineation for the primary tumor was first performed using all available information except for the MRI and subsequently with additional consideration of the co-registered MRI. The derived volumes were compared by subjective visual judgment and by quantitative mathematical methods. RESULTS: Sixteen patients were included and underwent the planning CT, MRI and subsequent definitive radiochemotherapy. In 69% of the patients, there were visually relevant changes to the gross tumor volume (GTV) by use of the MRI. In 44%, the GTV_MRI would not have been covered completely by the planning target volume (PTV) of the CT-only contour. Yet, median Hausdorff und DSI values did not reflect these differences. The 3-year local control rate was 94%. CONCLUSIONS: Adding a diagnostic MRI in RT treatment position is feasible and results in relevant changes in target volumes in the majority of patients.

The role and potential of using quantitative MRI biomarkers for imaging guidance in brain cancer radiotherapy treatment planning: A systematic review.

Background and purpose: Improving the accuracy of brain tumour radiotherapy (RT) treatment planning is important to optimise patient outcomes. This systematic review investigates primary studies providing clinical evidence for the integration of quantitative magnetic resonance imaging (qMRI) biomarkers and MRI radiomics to optimise brain tumour RT planning. Materials and methods: PubMed, Scopus, Embase and Web of Science databases were searched for all years until June 21, 2022. The search identified original articles demonstrating clinical evidence for the use of qMRI biomarkers and MRI radiomics for the optimization of brain cancer RT planning. Relevant information was extracted and tabulated, including qMRI metrics and techniques, impact on RT plan optimization and changes in target and normal tissue contouring and dose distribution. Results: Nineteen articles met the inclusion criteria. Studies were grouped according to the qMRI biomarkers into: 1) diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI; five studies); 2) diffusion tensor imaging (DTI; seven studies); and 3) MR spectroscopic imaging (MRSI; seven studies). No relevant MRI-based radiomics studies were identified. Integration of DTI maps offers the potential for improved organs at risk (OAR) sparing. MRSI metabolic maps are a promising technique for improving delineation accuracy in terms of heterogeneity and infiltration, with OAR sparing. No firm conclusions could be drawn regarding the integration of DWI metrics and PWI maps. Conclusions: Integration of qMRI metrics into RT planning offers the potential to improve delineation and OAR sparing. Clinical trials and consensus guidelines are required to demonstrate the clinical benefits of such approaches.

Impact of Postoperative Changes in Brain Anatomy on Target Volume Delineation for High-Grade Glioma.

High-grade glioma has a poor prognosis, and radiation therapy plays a crucial role in its management. Every step of treatment planning should thus be optimised to maximise survival chances and minimise radiation-induced toxicity. Here, we compare structures needed for target volume delineation between an immediate postoperative magnetic resonance imaging (MRI) and a radiation treatment planning MRI to establish the need for the latter. Twenty-eight patients were included, with a median interval between MRIs (range) of 19.5 (8-50) days. There was a mean change in resection cavity position (range) of 3.04 ± 3.90 (0-22.1) mm, with greater positional changes in skull-distant (>25 mm) resection cavity borders when compared to skull-near (≤25 mm) counterparts (p < 0.001). The mean differences in resection cavity and surrounding oedema and FLAIR hyperintensity volumes were -32.0 ± 29.6% and -38.0 ± 25.0%, respectively, whereas the mean difference in midline shift (range) was -2.64 ± 2.73 (0-11) mm. These data indicate marked short-term volumetric changes and support the role of an MRI to aid in target volume delineation as close to radiation treatment start as possible. Planning adapted to the actual anatomy at the time of radiation limits the risk of geographic miss and might thus improve outcomes in patients undergoing adjuvant radiation for high-grade glioma.

ESTRO ACROP guideline on prostate bed delineation for postoperative radiotherapy in prostate cancer.

Purpose/Objective: Radiotherapy to the prostate bed is a potentially curative salvage option after radical prostatectomy. Although prostate bed contouring guidelines are available in the literature, important variabilities exist. The objective of this work is to provide a contemporary consensus guideline for prostate bed delineation for postoperative radiotherapy. Methods: An ESTRO-ACROP contouring consensus panel consisting of 11 radiation oncologists and one radiologist, all with known subspecialty expertise in prostate cancer, was established. Participants were asked to delineate the prostate bed clinical target volumes (CTVs) in 3 separate clinically relevant scenarios: adjuvant radiation, salvage radiation with PSA progression, and salvage radiation with persistently elevated PSA. These cases focused on the presence of positive surgical margin, extracapsular extension, and seminal vesicles involvement. None of the cases had radiographic evidence of local recurrence on imaging. A single computed tomography (CT) dataset was shared via FALCON platform and contours were performed using EduCaseTM software. Contours were analyzed qualitatively using heatmaps which provided a visual assessment of controversial regions and quantitatively analyzed using Sorensen-Dice similarity coefficients. Participants also answered case-specific questionnaires addressing detailed recommendations on target delineation. Discussions via electronic mails and videoconferences for final editing and consensus were performed. Results: The mean CTV for the adjuvant case was 76 cc (SD = 26.6), salvage radiation with PSA progression was 51.80 cc (SD = 22.7), and salvage radiation with persistently elevated PSA 57.63 cc (SD = 25.2). Compared to the median, the mean Sorensen-Dice similarity coefficient for the adjuvant case was 0.60 (SD 0.10), salvage radiation with PSA progression was 0.58 (SD = 0.12), and salvage radiation with persistently elevated PSA 0.60 (SD = 0.11). A heatmap for each clinical scenario was generated. The group agreed to proceed with a uniform recommendation for all cases, independent of the radiotherapy timing. Several controversial areas of the prostate bed CTV were identified based on both heatmaps and questionnaires. This formed the basis for discussions via videoconferences where the panel achieved consensus on the prostate bed CTV to be used as a novel guideline for postoperative prostate cancer radiotherapy. Conclusion: Variability was observed in a group formed by experienced genitourinary radiation oncologists and a radiologist. A single contemporary ESTRO-ACROP consensus guideline was developed to address areas of dissonance and improve consistency in prostate bed delineation, independent of the indication.There is important variability in existing contouring guidelines for postoperative prostate bed (PB) radiotherapy (RT) after radical prostatectomy. This work aimed at providing a contemporary consensus guideline for PB delineation. An ESTRO ACROP consensus panel including radiation oncologists and a radiologist, all with known subspecialty expertise in prostate cancer, delineated the PB CTV in 3 scenarios: adjuvant RT, salvage RT with PSA progression, and salvage RT with persistently elevated PSA. None of the cases had evidence of local recurrence. Contours were analysed qualitatively using heatmaps for visual assessment of controversial regions and quantitatively using Sorensen-Dice coefficient. Case-specific questionnaires were also discussed via e-mails and videoconferences for consensus. Several controversial areas of the PB CTV were identified based on both heatmaps and questionnaires. This formed the basis for discussions via videoconferences. Finally, a contemporary ESTRO-ACROP consensus guideline was developed to address areas of dissonance and improve consistency in PB delineation, independent of the indication.

Automated deep learning auto-segmentation of air volumes for MRI-guided online adaptive radiation therapy of abdominal tumors.

Objective. In the current MR-Linac online adaptive workflow, air regions on the MR images need to be manually delineated for abdominal targets, and then overridden by air density for dose calculation. Auto-delineation of these regions is desirable for speed purposes, but poses a challenge, since unlike computed tomography, they do not occupy all dark regions on the image. The purpose of this study is to develop an automated method to segment the air regions on MRI-guided adaptive radiation therapy (MRgART) of abdominal tumors.Approach. A modified ResUNet3D deep learning (DL)-based auto air delineation model was trained using 102 patients' MR images. The MR images were acquired by a dedicated in-house sequence named 'Air-Scan', which is designed to generate air regions that are especially dark and accentuated. The air volumes generated by the newly developed DL model were compared with the manual air contours using geometric similarity (Dice Similarity Coefficient (DSC)), and dosimetric equivalence using Gamma index and dose-volume parameters.Main results. The average DSC agreement between the DL generated and manual air contours is 99% ± 1%. The gamma index between the dose calculations with overriding the DL versus manual air volumes with density of 0.01 is 97% ± 2% for a local gamma calculation with a tolerance of 2% and 2 mm. The dosimetric parameters from planning target volume-PTV and organs at risk-OARs were all within 1% between when DL versus manual contours were overridden by air density. The model runs in less than five seconds on a PC with 28 Core processor and NVIDIA Quadro®P2000 GPU.Significance: a DL based automated segmentation method was developed to generate air volumes on specialized abdominal MR images and generate results that are practically equivalent to the manual contouring of air volumes.

Nasopharyngeal cancer: the impact of guidelines and teaching on radiation target volume delineation.

Target volume delineation in the radiation treatment of nasopharyngeal cancer is challenging due to several reasons such as the complex anatomy of the site, the need for the elective coverage of definite anatomical regions, the curative intent of treatment and the rarity of the disease, especially in non-endemic areas. We aimed to analyze the impact of educational interactive teaching courses on target volume delineation accuracy between Italian radiation oncology centers. Only one contour dataset per center was admitted. The educational course consisted in three parts: (1) The completely anonymized image dataset of a T4N1 nasopharyngeal cancer patient was shared between centers before the course with the request of target volume and organs at risk delineation; (2) the course was held online with dedicated multidisciplinary sessions on nasopharyngeal anatomy, nasopharyngeal cancer pattern of diffusion and on the description and explanation of international contouring guidelines. At the end of the course, the participating centers were asked to resubmit the contours with appropriate corrections; (3) the pre- and post-course contours were analyzed and quantitatively and qualitatively compared with the benchmark contours delineated by the panel of experts. The analysis of the 19 pre- and post-contours submitted by the participating centers revealed a significant improvement in the Dice similarity index in all the clinical target volumes (CTV1, CTV2 and CTV3) passing from 0.67, 0.51 and 0.48 to 0.69, 0.65 and 0.52, respectively. The organs at risk delineation was also improved. The qualitative analysis consisted in the evaluation of the inclusion of the proper anatomical regions in the target volumes; it was conducted following internationally validated guidelines of contouring for nasopharyngeal radiation treatment. All the sites were properly included in target volume delineation by >50% of the centers after correction. A significant improvement was registered for the skull base, the sphenoid sinus and the nodal levels. These results demonstrated the important role that educational courses with interactive sessions could have in such a challenging task as target volume delineation in modern radiation oncology.

Post-induction lymph node delineation in nasopharyngeal cancer: A single-center experience.

BACKGROUND: We routinely delineate the gross tumor volume (GTV) for the lymph nodes (LN) based on post-induction chemotherapy (IC) MRI in nasopharyngeal carcinoma (NPC). Herein, we investigated the sufficiency of this method, particularly in high-risk LNs. METHODS: Eighty-one LNs with a high-risk of clinical extranodal extension and/or ≥3-cm diameter in 58 patients were evaluated. A new GTV covering the pre-IC LN volume was delineated for each LN. RESULTS: The median volume reduction was 72.5% for the GTV and 53.1% for the planning target volume. After a median 43 months, the overall LN local control rate was 97.5%. The 2- and 5-year LN recurrence-free survival, overall survival, and disease-free survival rate was 88.3% and 84.4%, 92.5% and 85.1%, and 86.8% and 79.2%, respectively. CONCLUSION: IC yields a significant reduction in nodal target volumes, and post-IC nodal volume-based radiotherapy provides excellent LC in NPC, even in high-risk LNs.

The application of multiple metrics in deformable image registration for target volume delineation of breast tumor bed.

BACKGROUND AND PURPOSE: For postoperative breast cancer patients, deformable image registration (DIR) is challenged due to the large deformations and non-correspondence caused by tumor resection and clip insertion. To deal with it, three metrics (fiducial-, region-, and intensity-based) were jointly used in DIR algorithm for improved accuracy. MATERIALS AND METHODS: Three types of metrics were combined to form a single-objective function in DIR algorithm. Fiducial-based metric was used to minimize the distance between the corresponding point sets of two images. Region-based metric was used to improve the overlap between the corresponding areas of two images. Intensity-based metric was used to maximize the correlation between the corresponding voxel intensities of two images. The two CT images, one before surgery and the other after surgery, were acquired from the same patient in the same radiotherapy treatment position. Twenty patients who underwent breast-conserving surgery and postoperative radiotherapy were enrolled in this study. RESULTS: For target registration error, the difference between the proposed and the conventional registration methods was statistically significant for soft tissue (2.06 vs. 7.82, p = 0.00024 < 0.05) and body boundary (3.70 vs. 6.93, p = 0.021 < 0.05). For visual assessment, the proposed method achieved better matching result for soft tissue and body boundary. CONCLUSIONS: Comparing to the conventional method, the registration accuracy of the proposed method was significantly improved. This method provided a feasible way for target volume delineation of tumor bed in postoperative radiotherapy of breast cancer patients.

The Key Clinical Questions of Neoadjuvant Chemoradiotherapy for Resectable Esophageal Cancer-A Review.

Over 50% of individuals with esophageal cancer (EC) present with advanced stages of the disease; therefore, their outcome following surgery alone is poor, with only 25%-36% being alive 5 years post-surgery. Based on the evidence that the CROSS and NEOCRTEC5010 trials provided, neoadjuvant chemoradiotherapy (nCRT) is now the standard therapy for patients with locally advanced EC. However, there are still many concerning clinical questions that remain controversial such as radiation dose, appropriate patient selection, the design of the radiation field, the time interval between chemoradiotherapy (CRT) and surgery, and esophageal retention. With immune checkpoint inhibitors (ICIs) rapidly becoming a mainstay of cancer therapy, along with radiation, chemotherapy, and surgery, the combination mode of immunotherapy is also becoming a hot topic of discussion. Here, we try to provide constructive suggestions to answer the perplexing problems and clinical concerns for the progress of nCRT for EC in the future.