TPS8124 Background: Immune checkpoint inhibitor (ICI)–based regimens are standard first-line therapy for metastatic non–small-cell lung cancer (NSCLC) without actionable driver mutations; however, most patients experience disease progression within 12 months. A subset develop oligoprogression, defined by progression at a limited number of metastatic sites with otherwise controlled disease. Oligoprogression represents a therapeutic window in which local ablative therapy could be used to prolong disease control. In the prior phase II CURB trial, SBRT was shown to significantly prolong progression-free survival (PFS) in patients with oligoprogressive NSCLC. Methods: CCTG-BR38 is an international, multicenter, open-label, randomized phase III trial conducted through the NCI National Clinical Trials Network. Adults with stage IV NSCLC receiving first-line ICI ± chemotherapy who develop ≤5 extracranial oligoprogressive lesions are randomized 1:1 to: (1) switch to second-line standard systemic therapy or (2) SBRT (30 Gy in 3 fractions) to all oligoprogressive sites followed by continuation of the same first-line systemic therapy. Randomization is stratified by type of first-line systemic therapy (ICI alone vs ICI + chemotherapy), number of oligoprogressive lesions (1–2 vs 3–5), and ECOG performance status (0-1 vs 2). Patients with treated, stable brain metastases are eligible. Primary Endpoints: Dual primary endpoints are PFS and overall survival (OS). Secondary endpoints include safety (CTCAE v5.0), patient-reported adverse events (PRO-CTCAE), quality of life (EORTC QLQ-C30/LC13), and cost-effectiveness (EQ-5D-5L; Canadian sites). Optional blood and tissue collection for exploratory biomarker analyses are planned. Statistical Considerations: A total of 320 patients (160 per arm) will be enrolled. The sample size is based on detecting a HR of 0.7 for OS (an improvement in median OS from 10 to 14.3 months) with 80% power using a 1-sided 2% level test (the overall 1-sided 2.5% type I error will be assigned 2% to OS and 0.5% to PFS). Interim analyses for futility and efficacy are planned. Current Status: The trial was centrally activated on April 3, 2025. Accrual is ongoing across Canadian and US NCTN sites. Clinical trial information: NCT06686771 .

Background and purpose:Artificial intelligence (AI) auto-segmentation is increasingly used in radiotherapy to reduce contouring time, with physician review required before clinical use. These tools reliably achieve high geometric and dose agreement with manual organ of interest (OOI) contours, but whether such agreement predicts clinical acceptability on structured physician review is not well characterized. Materials and methods:We analyzed twenty-three lung cancer cases using manual contours and AI-generated contours [Ethos-2 and RayStation (RS) 2023B] for the lungs, heart, esophagus, and spinal canal. We assessed quantitative agreement using Dice similarity coefficient (DSC), distance-to-agreement, and volumetric differences, as well as dose differences by comparing mean and maximum dose. For qualitative assessment, ten thoracic radiation oncologists each blindly reviewed ten cases, noting preferred and unacceptable contours, and differences were evaluated using Cochran's Q and pairwise McNemar tests. Results:Both AI platforms showed high geometric agreement with manual contours (DSC > 0.9 in over 70% of cases) and negligible dose differences across OOIs. However, reviewers more often found AI contours unacceptable for the esophagus (RS2023B) and the heart (Ethos-2). The most common reason for a contour being deemed unacceptable was insufficient anatomic accuracy rather than safety concerns. Conclusions:While AI-based auto-segmentation performed well on geometric and dose metrics, differences in physician acceptability persisted for some OOIs. These findings indicate that quantitative agreement is not a reliable predictor of clinical acceptability.

Background:Reirradiation is an increasingly common challenge with limited prospective evidence to guide practice, which varies internationally. This paper presents the patterns of practice in thoracic reirradiation within a high-volume academic center. Methods:Thoracic reirradiation cases, discussed at the thoracic radiotherapy quality assurance (QA) meeting, were prospectively collected over 12 months between April 2024 and March 2025. Data collected included patient demographics, primary tumor site, details of previous and current planned radiotherapy, the extent and type of overlap and any treatment plan modifications. The data was analyzed using descriptive statistics. Results:85 (18.2 % of 466 cases) reirradiation cases were identified at 26 QA meetings. Most reirradiation plans (68.2 %) were of radical intent, with dose overlap (89.4 %, n = 76). Challenges included unreliable registration of prior radiotherapy datasets (16.5 %) and deciding appropriate plan modifications to improve safety: 24.7 % optimized dose distribution to an OAR, 23.5 % involved dose reductions from standard prescriptions and 15.3 % compromised target volume coverage. The most frequently identified dose-limiting OARs were the proximal bronchial tree, esophagus, and spinal cord. Concerns about a lack of normal tissue recovery arose in 7.1 % of cases. In 10.6 % of cases there was explicit discussion of a dose discount for OARs for presumed partial tissue recovery. Peer-review prompted revision of the treatment plan in 11.8 % of cases. Conclusion:These findings underscore the complexity of thoracic reirradiation and highlight the need for further guidance in the area and the role of QA rounds in optimizing safety and treatment decisions while best practice remains uncertain.

Purpose The Stereotactic Radiation Therapy for Ultra-Central Non-Small Cell Lung Cancer: Safety and Efficacy Trial (SUNSET) trial investigated the maximum tolerated dose for ultracentral lung tumors treated with stereotactic body radiation therapy. Here, we report a spatial and dosimetric secondary analysis of the treatment plans and assess relationships between doses to targets, organs at risk (OARs), and clinical outcomes. Methods and Materials Five institutions enrolled patients with ultracentral lung cancer, cT1-3N0M0, and all received 60 Gy in 8 fractions. Maximum dose was limited to 120% of prescription. Planning data sets and treatment plans were imported into a central repository. Univariable logistic and Cox proportional hazards regression modeling were performed to identify significant dosimetric predictors for related grade ≥2 adverse events, overall survival, and local control (LC). Results Thirty patients were included in this analysis. At median follow-up of 36.5 months, 11 patients experienced grade ≥2 toxicity. The planning target volume (PTV) overlapped with 58 central OARs of which airway was most common (n = 26). The mean maximum dose was 69.3 Gy (range, 63.8-72.0 Gy); all were within the internal target volume. Mean ± SD PTV D98 was 56.1 ± 7.8 Gy, whereas D0.1 cm3 of proximal bronchial tree, esophagus, and pulmonary artery were 53.1 ± 12.6 Gy, 26.5 ± 10.5 Gy, and 57.0 ± 8.6 Gy, respectively. On regression analysis, the combined overlap volume (cm3) of the 2 primary overlapping OARs with PTV was associated with inferior LC (hazard ratio [HR], 2.86; P = .012); however, it was not associated with increase in grade ≥2 adverse events (odds ratio, 1.17; P = .49). There was no association between OAR doses (D1 cm3 and D0.1 cm3) with toxicity. PTV undercoverage (D98) was not associated with worse LC (HR per 5 Gy, 1.54; P = .68); however, lower PTV coverage was significantly associated with reduced overall survival for D98 (HR, 0.65; P = .014) and D95 (HR per 5 Gy, 0.66; P = .035). Conclusions Within the dose constraints used in the trial, there was no relationship identified between OAR doses and toxicity. LC decreased with increasing overlap of PTV with OARs; however, this was not associated with dosimetric undercoverage of the target.

Purpose/Objective(s) Stereotactic ablative body radiotherapy (SABR) is an emerging treatment option for lung cancer patients with interstitial lung disease (ILD). Identifying patients who are at greater risk of toxicity after SABR would help personalize their treatment. The aim of this study was to develop and validate methods to predict pulmonary toxicity in patients with ILD receiving SABR using radiomic and dosimetric-based machine learning methods. Materials/Methods This retrospective study used data from the ASPIRE-ILD clinical trial, currently the largest multi-centre trial investigating the use of SABR for the treatment of lung cancer patients with ILD. Dose-volume histogram features were calculated from the treatment plans and included the Vx, as both a percentage and volume, in steps of 5 Gy from 5 to 60 Gy, the mean and max lung dose, the D2cm, and the R50. Radiomic features were calculated from the lung volume of each patient's diagnostic pre-treatment CT scan using open source software. Additionally, deep learning-based features were extracted from each CT scan using a UNet convolutional neural network (CNN). The AdaBoost algorithm for boosted decision trees was used to train a prediction model for the binary prediction of grade ≥ 2 pulmonary toxicity, splitting the patient cohort into low and high-risk groups. Different combinations of feature sources were tested to determine the source of any predictive power and a leave-one-out cross-validation approach was applied to test over the full dataset. Results Baseline planning scans and diagnostic imaging was available from all 39 patients, of whom 11 developed grade ≥ 2 CTCAE v5 pulmonary toxicity with dyspnea (n=7) and pneumonitis (n=3) being the predominant toxicities. The best-performing model included dose, CT radiomic and CT deep learning features to achieve an AUC of 0.841 with a sensitivity of 81.8% and a specificity of 78.6%. This model correctly classified 9/15 patients as high-risk and 22/24 patients as low-risk giving a precision and negative predictive value of 60% and 92% respectively. Table 1 displays all model results. Conclusion A radiomic- and dosimetric-based machine learning method to predict the occurrence of pulmonary toxicity in lung cancer patients with ILD receiving SABR has been developed and validated. To our knowledge, this is the first study showing the benefit of radiomic and deep learning CT features, or to use of machine learning for stratifying these patients into low- and high-risk groups. Validation in a larger and more diverse dataset is needed.

Purpose/Objective(s) Stereotactic ablative radiotherapy (SABR) for ultra-central (UC) lung tumors can be associated with morbidity and mortality. We report local control (LC) and toxicity following SABR (≤8 daily fractions) with planning target volumes (PTV) overlapping trachea, proximal bronchial tree (PBT), esophagus, and/or pulmonary artery and vein (PA/PV). Materials/Methods One hundred thirty-four of 1771 (7.6%) patients receiving lung SABR (January 2006-May 2023) were included from a prospective institutional database. In total, 141 UC lung tumors (75% primary NSCLC, 25% metastases, no nodes) were analyzed. Primary outcomes were LC and incidence of grade (G) 3-5 CTCAE V5.0 toxicity. Secondary outcomes were overall survival (OS), progression-free survival (PFS), regional (RC) and distant control (DC), and incidence of G2+ pneumonitis (RP). Results Median follow-up was 23.0 months (2.0-165.0). Median tumor size was 2.1 cm (0.8-6.0). Sixty-five (62.5%) patients with primary NSCLC were medically inoperable. PTV overlapped trachea in 7.1%, PBT 67.4%, esophagus 2.1%, PA 47.5%, and PV 12.8%. Tumor abutted PBT in 36.2% and PA/PV in 29.8%. No endobronchial invasion was noted. The most common prescription (89.4%) was 60 Gy in 8 fractions (BED10 59.5-123.6 Gy). Prescription isodose line (median: 87% [68.0-99.0]) was ≤90% for 96 tumors (68.1%). Median PTV D99 and D95 were 96.2% (38.1-99.2) and 100.0% (70.9-108.4). PTV D99≥90% was achieved for 87.9% of tumors. PTV D95≥100% was achieved for 66.7% of tumors. Median PTV average dose was 109.2% (100.2-125.0). PTV Dmax (median: 119.8% [104.8-149.2]) was ≤120% for 72 tumors (51.1%). Median Dmax,EQD2(a/b = 3) (Gy) for trachea was 9.6 (0.1-138.5), PBT 124.6 (0.8-178.9), esophagus 22.2 (3.0-92.2), and PA/PV 135.6 (72.7-143.7). Median lung V20 was 8.8% (1.0-21.0). Five-year LC was 91.9% (95% CI:86.3-97.8). Tumor size (subdistribution hazard ratio (sHR) = 1.50; 95% CI:1.01-2.23; p = .044), PTV volume (sHR = 1.01; 95% CI:1.01-1.02; p<.001), and PET SUVmax (sHR = 1.07; 95% CI:1.01-1.14; p = .021) predicted local failure. Two patients (1.5%) experienced G3-5 toxicities: 1) one with G3 pneumothorax/pneumopericardium, G3 RP, and G5 aspiration post 60 Gy in 8 fractions, 2) another with G5 heart failure exacerbation post 24 Gy in 1 fraction. Median OS was 46.0 months (95% CI:35.0-67.0). For patients with primary NSCLC, median PFS was 75.0 months (95% CI:35.0-NR) and 5-year RC and DC were 70.7% (95% CI:60.2-83.0) and 80.9% (95% CI:72.5-90.3). Incidence of G2+ RP was 12.9%. Multiple tumors (sHR = 6.13; 95% CI:2.37-15.8; p<.001), lung V20 (sHR = 1.12; 95% CI:1.01-1.23; p = .025), and systemic therapy use (sHR = 5.70; 95% CI:1.88-17.3; p = .002) predicted G2+ RP. Conclusion SABR, planned over 8 fractions with limited organ-at-risk hotspots and moderate PTV Dmax, has high LC and low toxicity for well-selected patients with UC lung tumors.

Purpose/Objective(s) The SUNSET phase I trial investigated the maximum tolerated dose for ultracentral (UC) lung tumors treated with stereotactic body radiotherapy (SBRT). Here we report a detailed spatial and dosimetric secondary analysis of the treatment plan and assess relationships between doses to targets, organs-at-risk (OARs) and clinical outcomes. Materials/Methods Five Canadian institutions enrolled patients with UC primary lung cancer, cT1-3N0M0, and all received SBRT to a dose of 60 Gy in 8 daily fractions. Maximum dose (Dmax) was limited to 120% of prescription. Targets were delineated as internal target volume (ITV) (combining gross tumor volume (GTV) across respiratory phases) expanded by 5 mm to form planning target volume (PTV). All OARs including great vessels and bilateral proximal bronchial tree up to segmental bronchus were contoured at baseline. To evaluate OAR and target doses, planning datasets and treatment plans were imported into a central repository. Descriptive statistics were generated for baseline characteristics and dosimetry. Univariable logistic and Cox proportional hazards regression modelling were performed to identify significant dosimetric predictors for related grade ≥ 2 adverse events (CTCAE v4.0), overall survival (OS) and local control (LC). Results All 30 enrolled patients (13 males, 17 females) were included in this sub-study. At median follow-up of 36.5 months, 9 patients (30.0%) experienced grade 2 adverse events and 1 patient (3.3%) each with grade 3(dyspnea) and 5(infection) attributed to treatment. Median ITV and PTV sizes were 11.3 cc (IQR: 6.2-26.8) and 34.4 cc (IQR: 21.9-62.2), respectively. PTV overlapped with at least one OAR for all patients, most commonly the proximal bronchial tree (PBT) or trachea (27/30). Additionally, a second overlapping structure was identified in 26/30 patients, most commonly the pulmonary artery (14/26) and esophagus (9/26). The mean overlap of first and second OAR with PTV were 0.95 cc (range = 0-4.2) and 0.7 cc (range = 0-4.7), respectively. The mean Dmax was 69.4 Gy (range = 64-72.5 Gy); all were within the PTV. Mean (± SD) PTV D98 was 56.1 ± 7.8 Gy, while D0.1 cc of PBT, esophagus and pulmonary artery were 53.1 ± 12.6 Gy, 26.5 ± 10.5 Gy and 57 ± 8.6 Gy, respectively. On analysis, combined overlap volume (cc) of the two primary overlapping OARs with PTV was associated with statistically significant inferior LC (hazard ratio [HR] per 1 cc increase: 2.86, P = 0.012); however, overlap volume was not associated with an increase in grade ≥ 2 adverse events (odds ratio [OR] per 1 cc increase: 1.17, P = 0.49). There was no association between OAR doses (D1 cc/D0.1 cc) with toxicity. PTV under-coverage (D98) was not associated with worse LC (HR per 5 Gy increase: 1.54, P = 0.68). Conclusion Within the dose constraints used in the trial, there was no relationship identified between OAR doses and toxicity. Local control decreased with increasing overlap of PTV with OARs, however, this was not associated with dosimetric under-coverage of the target.

Purpose/Objective(s) Potentially curative chemoradiotherapy (CRT) is the treatment of choice in locally-advanced inoperable non-small cell lung cancer (NSCLC). Locoregional relapse is common but potentially salvageable in the absence of distant disease. 4DPET/4DCT image features during a course of CRT have been shown to predict clinical outcomes, two years post-CRT completion, including overall survival. The impact on five-year outcomes and the predictive power of these image features 3-month post-CRT are not clear. Materials/Methods In this prospective, REB-approved study, patients with LA-NSCLC receiving curative intent CRT had 4DPET/4DCT scans at 0, 2, 4, 7 weeks during CRT, and 3-month post-CRT. These patients were treated pre-Durvalumab approval (2010-12). Image features including V3SUV (volume represented by voxels with SUV>3), SUV50 (SUV>50% of SUVmax), Gross tumor volume on CT (GTV_CT) and their rates of change between timepoints were analyzed and correlated with clinical outcomes (locoregional relapse-free survival (LRRFS), overall survival (OS)) at 2 years and 5 years using mixed-effect models for longitudinal data. The predictive power of the features identified associated with the outcomes were further assessed by area under ROC curve using logistic regression. Results Of 29 patients recruited, 25 completed all scans and were included for analysis. Median follow-up was 32 months. Median OS was 32 months and median LRRFS was 23.9 months. At 2 years, 15 were alive, 11 disease-free. At 5 years, 8 were alive and 6 disease-free. Five out of 6 that were relapse-free at 5 years remained disease-free at their last follow-up (median follow-up = 120 months). Multiple image features at weeks 0 and 2 reached statistical significance for OS and LRRFS at 2 years, including V3SUV_tumor and nodal disease volume(V3SUV_t+n), V3SUV_nodal disease volume(V3SUV_n) and GTV_CT_n (LRRFS only). V3SUV_t+n and V3SUV_n at week 2 of CRT most strongly predicted LRRFS (p = 0.003, AUC 0.80) and OS (p = 0.018, AUC 0.76) at 2 years. No features at 3-month post-CRT were predictive of outcomes. No features were predictive of 5-year LRRFS and OS. Conclusion In this study of CRT without adjuvant immunotherapy, 5-year OS of 32% and LRRFS of 24% were observed, and the 3-month follow-up 4DPET/4DCT was not predictive of outcomes. 4DPET/4DCT at week 2 CRT has a potential to guide earlier salvage treatment in CRT non-responders.

Background and Purpose: Unexpected liver volume reductions occurred during trials of liver SBRT and concurrent sorafenib. The aims were to accumulate liver SBRT doses to assess the impact of these anatomic variations on normal tissue dose parameters and toxicity. Materials and Methods: Thirty-two patients with hepatocellular carcinoma (HCC) or metastases treated on trials of liver SBRT (30-57 Gy, 6 fractions) and concurrent sorafenib were analyzed. SBRT doses were accumulated using biomechanical deformable registration of daily cone-beam CT. Dose deviations (accumulated-planned) for normal tissues were compared for patients with liver volume reductions > 100 cc versus stable volumes, and accumulated doses were reported for three patients with grade 3-5 luminal gastrointestinal toxicities. Results: Patients with reduced (N = 12) liver volumes had larger mean deviations of 0.4-1.3 Gy in normal tissues, versus -0.2-0.4 Gy for stable cases (N = 20), P > 0.05. Deviations > 5% of the prescribed dose occurred in both groups. Two HCC patients with toxicities to small and large bowel had liver volume reductions and deviations to the maximum dose of 4% (accumulated 36.9 Gy) and 3% (accumulated 33.4 Gy) to these organs respectively. Another HCC patient with a toxicity of unknown location plus tumor rupture, had stable liver volumes and deviations to luminal organs of -6% to 4.5% (accumulated < 30.5 Gy). Conclusion: Liver volume reductions during SBRT and concurrent sorafenib were associated with larger increases in accumulated dose to normal tissues versus stable liver volumes. These dosimetric changes may have further contributed to toxicities in HCC patients who have higher baseline risks. (c) 2023 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 182 (2023) 1-7

In 2021, Ontario Health (Cancer Care Ontario) introduced a quality-based procedure model for the funding of radiation treatment (RT) in Ontario. This model ties reimbursement to patient care activities, ensuring equity and transparency in funding. Over 200 RT interprofessionals (oncologists, therapists and physicists) participated on 22 expert panels to establish or identify 288 evidence-based RT protocols and 672 quality expectations (QEs) to optimally deliver RT, which eventually led to the micro-costing of all protocols. Iterative review is required to ensure updated techniques and identify evolving standards of care, thereby providing the highest quality of RT care to Ontarians.