Expert Radiation Oncologists Research Articles

A student trained convolutional neural network competing with a commercial AI software and experts in organ at risk segmentation

This retrospective, multi-centered study aimed to improve high-quality radiation treatment (RT) planning workflows by training and testing a Convolutional Neural Network (CNN) to perform auto segmentations of organs at risk (OAR) for prostate cancer (PCa) patients, specifically the bladder and rectum. The objective of this project was to develop a clinically applicable and robust artificial intelligence (AI) system to assist radiation oncologists in OAR segmentation. The CNN was trained using manual contours in CT-datasets from diagnostic 68Ga-PSMA-PET/CTs by a student, then validated (n = 30, PET/CTs) and tested (n = 16, planning CTs). Further segmentations were generated by a commercial artificial intelligence (cAI) software. The ground truth were manual contours from expert radiation oncologists. The performance was evaluated using the Dice-Sørensen Coefficient (DSC), visual analysis and a Turing test. The CNN yielded excellent results in both cohorts and OARs with a DSCmedian > 0.87, the cAI resulted in a DSC > 0.78. In the visual assessment, 67% (bladder) and 75% (rectum) of the segmentations were rated as acceptable for treatment planning. With a misclassification rate of 45.5% (bladder) and 51.1% (rectum), the CNN passed the Turing test. The metrics, visual assessment and the Turing test confirmed the clinical applicability and therefore the support in clinical routine.

Mitigating Interobserver Variability in Radiomics with ComBat: A Feasibility Study

This study investigates Intraobserver Features Variability (IFV) in radiomics studies and assesses the effectiveness of the ComBat harmonization method in mitigating these effects. Methods: This study utilizes data from the NSCLC-Radiomics-Interobserver1 dataset, comprising CT scans of 22 Non-Small Cell Lung Cancer (NSCLC) patients, with multiple Gross Tumor Volume (GTV) delineations performed by five radiation oncologists. Segmentation was completed manually (“vis”) or by autosegmentation with manual editing (“auto”). A total of 1229 radiomic features were extracted from each GTV, segmentation method, and oncologist. Features extracted included first order, shape, GLCM, GLRLM, GLSZM, and GLDM from original, wavelet-filtered, and LoG-filtered images. Results: Before implementing ComBat harmonization, 83% of features exhibited p-values below 0.05 in the “vis” approach; this percentage decreased to 34% post-harmonization. Similarly, for the “auto” approach, 75% of features demonstrated statistical significance prior to ComBat, but this figure declined to 33% after its application. Among a subset of three expert radiation oncologists, percentages changed from 77% to 25% for “vis” contouring and from 64% to 23% for “auto” contouring. This study demonstrates that ComBat harmonization could effectively reduce IFV, enhancing the feasibility of multicenter radiomics studies. It also highlights the significant impact of physician experience on radiomics analysis outcomes.

Optimización de la triple terapia en el tratamiento del cáncer de próstata hormonosensible metastásico

Triple therapy with docetaxel, androgen deprivation therapy (ADT) and androgen receptor pathway inhibitors (ARPIs) has demonstrated survival benefits in patients with metastatic hormone-sensitive prostate cancer (mHSPC), especially in those with high-risk disease. However, once the use of ADT and docetaxel is established, guidelines do not clearly specify which ARPI is most appropriate. In this work, a literature review to identify phase III clinical trials, systematic reviews, meta-analyses, and clinical practice guidelines on triple therapy in mHSPC was carried out. Evidence and recommendations were qualitatively reviewed to provide guidelines on the most suitable ARPI based on patient risk, disease volume, and nature of metastases (synchronous or metachronous). This review aims to update the previously published consensus on the optimal pharmacological treatment for mHSPC and to expose the opinions of hospital pharmacy, urology and medical and radiation oncology experts.

Efficient application of deep learning-based elective lymph node regions delineation for pelvic malignancies.

While there are established international consensuses on the delineation of pelvic lymph node regions (LNRs), significant inter- and intra-observer variabilities persist. Contouring these clinical target volumes for irradiation in pelvic malignancies is both time-consuming and labor-intensive. The purpose of this study was to develop a deep learning model of pelvic LNRs delineation for patients with pelvic cancers. Planning computed tomography (CT) studies of 160 patients with pelvic primary malignancies (including rectal, prostate, and cervical cancer) were retrospectively collected and divided into training set (n=120) and testing set (n=40). Six pelvic LNRs, including abdominal presacral, pelvic presacral, internal iliac nodes, external iliac nodes, obturator nodes, and inguinal nodes were delineated by two radiation oncologists as ground truth (Gt) contours. The cascaded multi-heads U-net (CMU-net) was constructed based on the Gt contours from training cohort, which was subsequently verified in the testing cohort. The automatic delineation of six LNRs (Auto) was evaluated using dice similarity coefficient (DSC), average surface distance (ASD), 95th percentile Hausdorff distance (HD95), and a 7-point scale score. In the testing set, the DSC of six pelvic LNRs by CMU-net model varied from 0.851 to 0.942, ASD from 0.381 to 1.037mm, and HD95 from 2.025 to 3.697mm. No significant differences were founded in these three parameters between postoperative and preoperative cases. 95.9% and 96.2% of auto delineations by CMU-net model got a score of 1-3 by two expert radiation oncologists, respectively, meaning only minor edits needed. The CMU-net was successfully developed for automated delineation of pelvic LNRs for pelvic malignancies radiotherapy with improved contouring efficiency and highly consistent, which might justify its implementation in radiotherapy work flow.

On the trail of CBCT-guided adaptive rectal boost radiotherapy, does daily delineation require a radiation oncologist?

IntroductionDose-escalation radiotherapy for rectal tumours is increasingly considered as a non-operative approach, with online-adaptive radiotherapy (oART) supporting this approach by correcting inter-fraction tumour position errors. However, using cone-beam computed tomography (CBCT)-guided oART requires daily target volume delineation by different operators, leading to inter-operator delineation variability and potential dosimetric issues. This study aims to compare and quantify the inter-operator and inter-professional delineation variability of the rectal boost volume on CBCT, including volumes by an automatically delineated oART treatment planning system. Materials and methodsA rectal boost volume, defined as the primary tumour extended to the entire adjacent rectal wall, was delineated on 10 CBCTs from 5 patients by 15 operators: 4 expert radiation oncologists (ROs), 4 radiation therapists (RTTs) and 7 non-expert ROs. These contours were compared between the different professional groups. A comparison to the average volume of the group (ROs, RTTs, or non-expert ROs) with the lowest delineation variability was also performed for each individual volume including the volume automatically generated by an oART treatment planning system. ResultsDelineation variability was the highest in the superior (range: 2.3–6.0 mm), and inferior (2.3–12.4 mm) directions, compared to the left (0.2–4.4 mm), right (0.3–2.0 mm), anterior (0.1–2.9 mm), and posterior (0.5–4.0 mm) directions. Non-expert ROs, RTTs, and automatic oART volume showed similar ranges of delineation errors when compared to the expert ROs’ volume, which was chosen as reference volume since this professional group showed the lowest variability. DiscussionExpert ROs showed consistent results. Other professional groups exhibit similar variability, comparable to the automatic oART volume. Therefore, RTTs could safely perform the rectal boost delineation without non-expert ROs supervision in the absence of expert ROs during CBCT-based oART. Moreover, these findings provide quantitative data to compute accurate margins for the rectal boost planning target volume in a CBCT-guided oART workflow.

Optimizing triple therapy in patients with metastatic hormone-sensitive prostate cancer

Triple therapy with docetaxel, androgen deprivation therapy (ADT) and androgen receptor pathway inhibitors (ARPIs) has demonstrated survival benefits in patients with metastatic hormone-sensitive prostate cancer (mHSPC), especially in those with high-risk disease. However, once the use of ADT and docetaxel is established, guidelines do not clearly specify which ARPI is most appropriate. In this work, a literature review to identify phase III clinical trials, systematic reviews, meta-analyses, and clinical practice guidelines on triple therapy in mHSPC was carried out. Evidence and recommendations were qualitatively reviewed to provide guidelines on the most suitable ARPI based on patient risk, disease volume, and nature of metastases (synchronous or metachronous). This review aims to update the previously published consensus on the optimal pharmacological treatment for mHSPC and to expose the opinions of hospital pharmacy, urology and medical and radiation oncology experts.

Impact of the Novel MRI Contrast Agent Gadopiclenol on Radiotherapy Decision Making in Patients With Brain Metastases.

The aim of this study was to assess the effect of gadopiclenol versus gadobenate dimeglumine contrast-enhanced magnetic resonance imaging (MRI) on decision-making between whole-brain radiotherapy (WBRT) and stereotactic radiosurgery (SRS) for treatment of brain metastases (BMs). Patients with BMs underwent 2 separate MRI examinations in a double-blind crossover phase IIb comparative study between the MRI contrast agents gadopiclenol and gadobenate dimeglumine, both administered at 0.1 mmol/kg. The imaging data of a single site using identical MRI scanners and protocols were included in this post hoc analysis. Patients with 1 or more BMs in any of both MRIs were subjected to target volume delineation for treatment planning. Two radiation oncologists contoured all visible lesions and decided upon SRS or WBRT, according to the number of metastases. For each patient, SRS or WBRT treatment plans were calculated for both MRIs, considering the gross target volume (GTV) as the contrast-enhancing aspects of the tumor. Mean GTVs and volume of healthy brain exposed to 12 Gy (V12), as well as Dice similarity coefficient scores, were obtained. The Spearman rank (ρ) correlation was additionally calculated for assessing linear differences. Three different expert radiation oncologists blindly rated the contrast enhancement for contouring purposes. Thirteen adult patients were included. Gadopiclenol depicted additional BM as compared with gadobenate dimeglumine in 7 patients (54%). Of a total of 63 identified metastatic lesions in both MRI sets, 3 subgroups could be defined: A, 48 (24 pairs) detected equal GTVs visible in both modalities; B, 13 GTVs only visible in the gadopiclenol set (mean ± SD, 0.16 ± 0.37 cm3); and C, 2 GTVs only visible in the gadobenate dimeglumine set (mean ± SD, 0.01 ± 0.01). Treatment indication was changed for 2 (15%) patients, 1 from no treatment to SRS and for 1 from SRS to WBRT. The mean GTVs and brain V12 were comparable between both agents (P = 0.694, P = 0.974). The mean Dice similarity coefficient was 0.70 ± 0.14 (ρ = 0.82). According to the readers, target volume definition was improved in 63.9% of cases (23 of 36 evaluations) with gadopiclenol and 22.2% with gadobenate dimeglumine (8 of 36), whereas equivalence was obtained in 13.9% (5 of 36). Gadopiclenol-enhanced MRI improved BM detection and characterization, with a direct impact on radiotherapy treatment decision between WBRT and SRS. Additionally, a more exact target delineation and planning could be performed with gadopiclenol. A prospective evaluation in a larger cohort of patients is required to confirm these findings.

504 The ESTRO-EFOMP core curriculum: a joint effort from European medical physics experts in Radiation oncology

504 The ESTRO-EFOMP core curriculum: a joint effort from European medical physics experts in Radiation oncology

A Case-based Guide for World Health Organization (WHO) Grade 2 Meningioma Radiosurgery and Radiation Therapy from The Radiosurgery Society

Meningiomas represent the most common primary tumor of the central nervous system. Current treatment options include surgical resection with or without adjuvant radiation therapy (RT), definitive RT, and observation. However, the radiation dose, fractionation, and margins used to treat patients with WHO grade 2 meningiomas, which account for approximately 20% of all meningiomas, are not clearly defined, and deciding on the optimal treatment modality can be challenging owing to the lack of randomized data. In this manuscript, 3 cases of patients with WHO grade 2 meningiomas are presented with descriptions of treatment options after gross total resection, subtotal resection, and previous irradiation. Treatment recommendations were compiled from 9 central nervous system radiation oncology and neurosurgery experts from The Radiosurgery Society, and the consensus of treatment recommendations is reported. Both conventional and stereotactic RT are treatment options for WHO grade 2 meningiomas. The majority of prospective data in the setting of WHO grade 2 meningiomas involve larger margins. Stereotactic radiosurgery/hypofractionated stereotactic RT are less appropriate in this setting. Conventionally fractionated RT to at least 59.4 Gy is considered standard of care with utilization of preoperative and postoperative imaging to evaluate the extent of disease and possible osseous involvement. After careful discussion, stereotactic radiosurgery/hypofractionated stereotactic RT may play a role for the subset of patients who are unable to tolerate the standard lengthy conventionally fractionated treatment course, for those with prior RT, or for small residual tumors. However, more studies are needed to determine the optimal approach. This case-based evaluation of the current literature seeks to provide examples for the management of grade 2 meningiomas and give examples of both conventional and stereotactic RT.

Impact of gadopiclenol on decision making in patients with brain metastases: A post-hoc study.

e14003 Background: Gadopiclenol (Elucirem, Guerbet, France) is a new high relaxivity macrocyclic gadolinium-based contrast agent (GBCA), recently approved by the FDA and EMA at the dose of 0.05 mmol/kg. The aim of this post-hoc analysis was to evaluate the impact of contrast-enhanced MRI with gadopiclenol at 0.1 mmol/kg on decision making and radiotherapy (RT) treatment planning of brain metastases (BM). Methods: This is a post-hoc analysis of data from a phase IIb study where patients underwent two separate MRI examinations, one with gadopiclenol at 0.025, 0.05, 0.1 or 0.2 mmol/kg and one with gadobenate dimeglumine at 0.1 mmol/kg. MR images of patients who received both GBCAs at 0.1 mmol/kg, with ≥1 BM detected in either of the scans, were subjected to a blinded reader analysis and contouring by two radiation oncology experts. For each patient, treatment plans (stereotactic radiosurgery [SRS] or whole-brain radiotherapy [WBRT]) were determined for both MRIs, with the gross target volume (GTV) indicating the contrast-enhancing aspects of the tumor. Mean GTVs and normal tissue volumes receiving 12 Gy (V12), as well as the Dice similarity coefficient (DSC) were obtained for the paired contours. The Spearman´s rank (ρ) correlation was additionally calculated. Furthermore, three experts blindly evaluated the contrast enhancement of each lesion for contouring purposes and subjectively qualified them as “better”, in detriment of the counterpart, or “equal”. Results: In total, images from 13 adult patients were analyzed. MRI with gadopiclenol depicted additional BM as compared with gadobenate dimeglumine in 7 patients (54%). The treatment plan was changed in 2 patients (15%), from no treatment to SRS and from SRS to WBRT. Gadopiclenol depicted additional BM in these 2 patients (from 0 and 10 BM with gadobenate dimeglumine to 1 and 15 BM with gadopiclenol). The mean GTVs and V12 were comparable between gadopiclenol and gadobenate dimeglumine (p=0.694, p=1.974). The mean DSC was 0.70 (SD: 0.14, ρ0.82). From a total of 36 answers, contrast enhancement was qualified as better with gadopiclenol in 21 (58.3%) evaluations, better with gadobenate dimeglumine in 8 (22.2%) evaluations, while no difference was observed in 7 (19.4%) evaluations. Conclusions: Gadopiclenol at 0.1 mmol/kg improved BM detection and contrast enhancement with potential impact on RT treatment decisions.

Enhancing thoracic oncology in Armenia: Impact of the implementation of an expert-guided virtual multidisciplinary tumor board.

e13808 Background: The importance of expert-guided multidisciplinary tumor boards (MDTs) in the management of patients with complex malignancies is well established. Modern global telecommunication platforms allow for holding specialized virtual MDT discussions led by international experts even in limited-resource settings. The creation of such a group is of high importance for Armenia given the high incidence and increasing complexity of thoracic malignancies. We describe the initial impact of the implementation of the Thoracic Tumors Working Group (TTWG) of Armenia from August 2022 through January 2024. Methods: The TTWG of Armenia is an MDT comprised of medical oncologists, radiation oncologists, thoracic surgeons, pathologists, and radiologists. The group was formed under the Immune-Oncology Research Institute in August 2022 to discuss the management of patients with complicated thoracic malignancies. For each case, the clinical history, imaging, pathologic findings, and patient management plans are discussed. Updates on treatment paradigms and ongoing clinical trials are also reviewed. The MDTs are held biweekly via the Zoom platform under the supervision of international experts in thoracic oncology. Recordings of MDTs were reviewed to retrospectively identify case characteristics and the impact on patient management. Results: From August 2022 through January 2024, 89 cases were discussed during 33 TTWG MDTs. On average, each MDT was attended by 14 physicians and trainees in Armenia, and by two international experts in thoracic medical and radiation oncology. Median meeting length was 55 minutes with a median of 3 cases presented. Diagnoses included lung adenocarcinoma (n=31, 37.3%), squamous cell lung carcinoma (n=15, 18.0%), neuroendocrine tumors (n=16, 19.3%), small cell lung cancer (n=16, 19.3%), and thymic epithelial tumors (n=6, 7.3%). All disease stages were represented: I 3.7%, II 4.9%, III 31.7%, and IV 47.9%. The male-to-female ratio was 3.6:1 and the median age was 63 years (range: 29-76). Based on MDT discussion, the pre-MDT diagnosis was confirmed in 95.5% (n=85) of patients with down-staging in 3.4% (n=3). The proposed pre-MDT treatment plan was significantly altered in 42.7% (n=38) of patients. Additional studies, mainly PET/CT, bronchoscopy, and broader molecular profiling were recommended for 29.2% (n=26) of patients. Follow-up discussions were held for 7.9% (n=7) of patients based on information arising from prior MDT discussions. The TTWG of Armenia continues to be active. Conclusions: Our initial data suggest that the TTWG of Armenia has had a meaningful influence on patient management by providing access to specialty-expert care and physician education. The impact on patient outcomes will continue to be assessed. The TTWG of Armenia can serve as a model to improve outcomes in other resource-limited settings.

Clinical evaluation of a deep learning CBCT auto-segmentation software for prostate adaptive radiation therapy

PurposeAim of the present study is to characterize a deep learning-based auto-segmentation software (DL) for prostate cone beam computed tomography (CBCT) images and to evaluate its applicability in clinical adaptive radiation therapy routine. Materials and methodsTen patients, who received exclusive radiation therapy with definitive intent on the prostate gland and seminal vesicles, were selected. Femoral heads, bladder, rectum, prostate, and seminal vesicles were retrospectively contoured by four different expert radiation oncologists on patients CBCT, acquired during treatment. Consensus contours (CC) were generated starting from these data and compared with those created by DL with different algorithms, trained on CBCT (DL-CBCT) or computed tomography (DL-CT). Dice similarity coefficient (DSC), centre of mass (COM) shift and volume relative variation (VRV) were chosen as comparison metrics. Since no tolerance limit can be defined, results were also compared with the inter-operator variability (IOV), using the same metrics. ResultsThe best agreement between DL and CC was observed for femoral heads (DSC of 0.96 for both DL-CBCT and DL-CT). Performance worsened for low-contrast soft tissue organs: the worst results were found for seminal vesicles (DSC of 0.70 and 0.59 for DL-CBCT and DL-CT, respectively). The analysis shows that it is appropriate to use algorithms trained on the specific imaging modality. Furthermore, the statistical analysis showed that, for almost all considered structures, there is no significant difference between DL-CBCT and human operator in terms of IOV. ConclusionsThe accuracy of DL-CBCT is in accordance with CC; its use in clinical practice is justified by the comparison with the inter-operator variability.

Recommendations on the treatment of metastatic hormone-sensitive prostate cancer: Patient selection

The standard treatment for metastatic hormone-sensitive prostate cancer (mHSPC) is now a combination of androgen deprivation therapy plus an androgen receptor-targeted therapy (abiraterone, apalutamide, enzalutamide or darolutamide), with or without chemotherapy (docetaxel). The selection of suitable patients for each therapeutic approach has become a determining factor to ensure efficacy and minimize side effects. This article combines recent clinical evidence with the accumulated experience of experts in medical oncology, radiation oncology and urology, to provide a comprehensive view and therapeutic recommendations for mHSPC.

Recomendaciones de tratamiento en el cáncer de próstata hormonosensible metastásico: selección de pacientes

The standard treatment for metastatic hormone-sensitive prostate cancer (mHSPC) is now a combination of androgen deprivation therapy plus an androgen receptor-targeted therapy (abiraterone, apalutamide, enzalutamide or darolutamide), with or without chemotherapy (docetaxel). The selection of suitable patients for each therapeutic approach has become a determining factor to ensure efficacy and minimize side effects. This article combines recent clinical evidence with the accumulated experience of experts in medical oncology, radiation oncology and urology, to provide a comprehensive view and therapeutic recommendations for mHSPC.

Expert Perspectives on Controversies in Castration-Sensitive Prostate Cancer Management: Narrative Review and Report of the First US Prostate Cancer Conference Part 1.

Castration-sensitive prostate cancer (CSPC) is a complex and heterogeneous condition encompassing a range of clinical presentations. As new approaches have expanded management options, clinicians are left with myriad questions and controversies regarding the optimal individualized management of CSPC. The US Prostate Cancer Conference (USPCC) multidisciplinary panel was assembled to address the challenges of prostate cancer management. The first annual USPCC meeting included experts in urology, medical oncology, radiation oncology, and nuclear medicine. USPCC co-chairs and session moderators identified key areas of controversy and uncertainty in prostate cancer management and organized the sessions with multidisciplinary presentations and discussion. Throughout the meeting, experts responded to questions prepared by chairs and moderators to identify areas of agreement and controversy. The USPCC panel discussion and question responses for CSPC-related topics are presented. Key advances in CSPC management endorsed by USPCC experts included the development and clinical utilization of gene expression classifiers and artificial intelligence (AI) models for risk stratification and treatment selection in specific patient populations, the use of advanced imaging modalities in patients with clinically localized unfavorable intermediate or high-risk disease and those with biochemical recurrence, recommendations of doublet or triplet therapy for metastatic CSPC (mCSPC), and consideration of prostate and/or metastasis-directed radiation therapy in select patients with mCSPC. CSPC is a diverse disease with many therapeutic options and the potential for adverse outcomes associated with either undertreatment or overtreatment. Future studies are needed to validate and clinically integrate novel technologies, including genomics, AI, and advanced imaging, to optimize outcomes among patients with CSPC.

Multidisciplinary Team Approach in Prostate-Specific Membrane Antigen Theranostics for Prostate Cancer: A Narrative Review

In managing prostate cancer, the integration of multidisciplinary team (MDT) with prostate-specific membrane antigen (PSMA) theranostics marks a significant advancement, addressing the disease's spectrum from indolent forms to aggressive metastatic stages. MDTs, comprising urology, oncology, radiation oncology, pathology, radiology, and nuclear medicine experts, are pivotal in delivering tailored, evidence-based care, essential for the varied clinical presentations of prostate cancer. The introduction of PSMA-targeted theranostics and PSMA positron emission tomography imaging has impacted the approach to diagnosis and treatment, offering enhanced precision in disease localization and enabling more nuanced management strategies for conditions such as oligometastatic prostate cancer, metastatic hormone-sensitive prostate cancer, and metastatic castration-resistant prostate cancer. The collaborative approach of MDTs in utilizing PSMA-targeted radioligand therapy emphasizes meticulous patient selection, predictive assessment of therapy response, and careful management of therapy-related toxicities. Additionally, recent strategies, including combination therapies from ENZA-P and Lu-PARP trials, show potential for improving treatment efficacy. This unified approach showcases the critical role of MDTs in optimizing treatment outcomes, underscoring the importance of collaboration in advancing the treatment of prostate cancer with PSMAtargeted therapies, thereby setting a new paradigm in personalized prostate cancer management.

A data-driven model for personalised risk prediction of radiation-induced oral mucositis in oral cavity cancer patients

Abstract Aim: Radiation-induced oral mucositis (OM) is the most common complication presenting with chemo radiation therapy of oral cavity cancer. Tobacco use, oral hygiene and nutritional status are important entities that impact the incidence of OM. These entities must also be studied along with treatment planning strategies, to alleviate its incidence. Our study aims to present a novel method to model the OM incidence using a mucosal surface contour (MSC). Methods: Computed tomography (CT) images of 60 oral cavity patients who have started their intensity-modulated radiation therapy (IMRT)/volumetric-modulated arc therapy (VMAT) with concomitant chemotherapy (Cisplatin) were delineated with MSC as one of the organs at risk by three expert radiation oncologists. V30, V50 and Dmean doses of MSC and the PTV 60 (planning target volume for 60 Gy), along with Dmax of PTV60, were extracted from the dose volume histograms. OM toxicity was assessed once weekly, and the outcome was scored using CTCAE v5·0 grading. Tobacco use (Tb), oral hygiene (OHy) and nutritional status (Ns) were also numerically scored. A multiple linear regression analysis was done using the patient parameters and the outcome scores as predictor variables and response variables, respectively. Optimal dose volume constraints (Dmean, V30, V50) for a 20% reduction of OM were derived from the mathematical equations. Another 20 patients were planned prospectively using IMRT/VMAT with the above resulted in dose constraints. Clinical outcome was scored for these patients using CTCAE v5·0. Outcome results of the two phases (60 patients and 20 patients) were statistically compared with two-sample t-test. Results: For MSC, three mathematical equations were formulated using multiple linear regression analysis. Derived values of V30, V50 and Dmean constraints were used for dose optimisation in the second phase of treatment planning. It has showed a statistically significant deviation from the first phase of the study, with a confidence interval of 95% (p value: 0·0348) by introducing calculated dose constraints for MSC in dose optimisation. Conclusion: In this study, the feasibility of using multiple linear regression analysis to model OM incidence in radiation therapy clinics was explored. Derived dose–volume constraints for MSC could be used in IMRT/VMAT optimization to reduce its incidence. Patient treatment could be individualised by incorporating dose–volume parameters, nutritional status, tobacco use and oral hygiene status in the treatment planning procedure.

Clinical Use of a Commercial Artificial Intelligence-Based Software for Autocontouring in Radiation Therapy: Geometric Performance and Dosimetric Impact.

When autocontouring based on artificial intelligence (AI) is used in the radiotherapy (RT) workflow, the contours are reviewed and eventually adjusted by a radiation oncologist before an RT treatment plan is generated, with the purpose of improving dosimetry and reducing both interobserver variability and time for contouring. The purpose of this study was to evaluate the results of application of a commercial AI-based autocontouring for RT, assessing both geometric accuracies and the influence on optimized dose from automatically generated contours after review by human operator. A commercial autocontouring system was applied to a retrospective database of 40 patients, of which 20 were treated with radiotherapy for prostate cancer (PCa) and 20 for head and neck cancer (HNC). Contours resulting from AI were compared against AI contours reviewed by human operator and human-only contours using Dice similarity coefficient (DSC), Hausdorff distance (HD), and relative volume difference (RVD). Dosimetric indices such as Dmean, D0.03cc, and normalized plan quality metrics were used to compare dose distributions from RT plans generated from structure sets contoured by humans assisted by AI against plans from manual contours. The reduction in contouring time obtained by using automated tools was also assessed. A Wilcoxon rank sum test was computed to assess the significance of differences. Interobserver variability of the comparison of manual vs. AI-assisted contours was also assessed among two radiation oncologists for PCa. For PCa, AI-assisted segmentation showed good agreement with expert radiation oncologist structures with average DSC among patients ≥ 0.7 for all structures, and minimal radiation oncology adjustment of structures (DSC of adjusted versus AI structures ≥ 0.91). For HNC, results of comparison between manual and AI contouring varied considerably e.g., 0.77 for oral cavity and 0.11-0.13 for brachial plexus, but again, adjustment was generally minimal (DSC of adjusted against AI contours 0.97 for oral cavity, 0.92-0.93 for brachial plexus). The difference in dose for the target and organs at risk were not statistically significant between human and AI-assisted, with the only exceptions of D0.03cc to the anal canal and Dmean to the brachial plexus. The observed average differences in plan quality for PCa and HNC cases were 8% and 6.7%, respectively. The dose parameter changes due to interobserver variability in PCa were small, with the exception of the anal canal, where large dose variations were observed. The reduction in time required for contouring was 72% for PCa and 84% for HNC. When an autocontouring system is used in combination with human review, the time of the RT workflow is significantly reduced without affecting dose distribution and plan quality.

AHOD2131: A Randomized Phase 3 Response-Adapted Trial Comparing Standard Therapy with Immuno-Oncology Therapy for Children and Adults with Newly Diagnosed Stage I and II Classic Hodgkin Lymphoma

Background: Chemotherapy in combination with radiotherapy (RT) is the standard for early-stage (ES) Hodgkin lymphoma (cHL). Despite high cure rates (12-year overall survival (OS) >93%), there is room to improve short and long-term outcomes for children and adults with ES cHL. Incorporation of immunotherapy (IO) into front line treatment of ES cHL is an opportunity to both improve progression-free survival (PFS) and maintain OS, while minimizing long-term morbidity and mortality by reducing exposure to RT and high-dose chemotherapy. Study Design and Methods: HL leaders of the NCTN groups, expert HL researchers and physicians, and representatives from the Cancer Therapy Evaluation Program (CTEP) formed a working group in April 2020 with the goals of harmonizing treatment approaches for ES cHL across pediatric and adult patients and reaching consensus regarding the optimal study design for incorporating IO therapy into frontline treatment. Study champions identified from each of the North American cooperative groups [Children's Oncology Group (COG), SWOG, ECOG-ACRIN, Alliance, NRG] and experts in imaging, radiation oncology, lymphoma biology and patient-reported outcomes (PROs) were included. The resulting COG-led clinical trial, AHOD2131, represents the largest ES cHL trial in the history of North American cooperative groups and the first to enroll patients across the age continuum. AHOD2131 (NCT05675410; Figure) is a randomized, phase 3 trial enrolling patients ages 5 to 60 years with newly diagnosed, previously untreated stage I and II cHL and will investigate the addition of the CD30-antibody drug conjugate brentuximab vedotin (Bv) with PD-1 blockade (nivolumab) compared to standard chemotherapy +/- RT. Since the April 2023 activation, 97 North American sites have activated the trial, and 21 participants have enrolled. Target enrollment is 1875 patients over 5 years of accrual, for an estimated 1782 eligible and evaluable patients. The primary objective is to compare the 3-year PFS of patients with ES cHL treated through a response-adapted, superiority design with either standard therapy or with an IO approach (BV + nivolumab). All patients will be stratified as favorable or unfavorable based on disease risk features at enrollment. Based on initial response assessment by PET/CT (via central review) after 2 cycles of ABVD, patients were classified to PET2 positive (SER, defined as 5 Point Score 4 or 5, ~15% of patients) and PET negative (RER). Those who are PET positive will receive involved site RT (ISRT). The SER and RER patients will be randomized to standard chemotherapy vs. IO therapy respectively. In addition to the primary outcome of PFS, there are 11 secondary and 10 exploratory aims. The secondary aims focus on OS, PFS of subgroups, and event-free survival at 12 years, physician-reported treatment-related adverse event (AE) rates, patient-reported AE using pediatric and adult versions of Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE), and the capture of representation by self-report and the use of electronic PRO data collections. The exploratory aims include the assessment of imaging central review as compared to local institutional review and the use of convolutional neural networks through artificial-intelligence machine learning. The study will examine the effect of therapy on acute and long-term adverse effects including health-related quality of life (HRQoL) and OS for up to 12 years. The study will compare patient self-report and provider AE reports and evaluate the associations of self-reported race/ethnicity and social determinants of health (SDOH)and post-progression/post-relapse OS. AHOD2131 strengthens the effort between the North American cooperative groups to conduct collaborative clinical trials and aims to harmonize an improved standard of care for ES cHL across the age continuum.

Systemic Therapy for Small-Cell Lung Cancer: ASCO-Ontario Health (Cancer Care Ontario) Guideline.

To provide evidence-based recommendations to practicing clinicians on the management of patients with small-cell lung cancer. An Expert Panel of medical oncology, thoracic surgery, radiation oncology, pulmonary, community oncology, research methodology, and advocacy experts were convened to conduct a literature search, which included systematic reviews, meta-analyses, and randomized controlled trials published from 1990 through 2022. Outcomes of interest included response rates, overall survival, disease-free survival or recurrence-free survival, and quality of life. Expert Panel members used available evidence and informal consensus to develop evidence-based guideline recommendations. The literature search identified 95 relevant studies to inform the evidence base for this guideline. Evidence-based recommendations were developed to address systemic therapy options, timing of therapy, treatment in patients who are older or with poor performance status, role of biomarkers, and use of myeloid-supporting agents in patients with small-cell lung cancer.Additional information is available at www.asco.org/thoracic-cancer-guidelines.