Predicting the effect of consolidation immunotherapy after chemoradiotherapy (CRT) for unresectable locally advanced non‐small‐cell lung cancer (LA‐NSCLC) patients remains a challenge, given the restricted sensitivity of single circulating tumor DNA (ctDNA) molecular residual disease (MRD) detection. In this study, 384 longitudinal blood samples from 160 patients with LA‐NSCLC undergoing CRT ± consolidation immunotherapy, tumor tissue whole‐genome or whole‐exome sequencing (WGS/WES) from 421 LA‐NSCLC patients treated with radiotherapy, and RNA‐sequencing data from 1149 subjects are analyzed. Pretreatment ctDNA‐based STK11(LKB1)/KEAP1 mutations are associated with poor prognosis and resistance to CRT but suggest benefits from consolidation immunotherapy after CRT. WGS/WES data confirm that STK11/KEAP1 ‐mutated tumors are radiotherapy‐resistant. RNA‐sequencing reveals an immunosuppressive tumor microenvironment for STK11/KEAP1 ‐mutated patients, characterized by strikingly decreased Th17 cells through the IL‐17 signaling downregulation, which could cause impaired response to upfront CRT but improved immunotherapy response after radiotherapy‐activated immunity. Predictive performance with individual ctDNA‐MRD detection is limited, while combining baseline STK11/KEAP1 mutations with ctDNA‐MRD effectively enhances prediction sensitivity, particularly in MRD‐negative patients. Integrating genomics with liquid biopsies could inform personalized and risk‐adaptive therapeutic decisions on consolidation immunotherapy.

Background: Stage III non-small-cell lung cancer (NSCLC) with anaplastic lymphoma kinase (ALK) gene rearrangements requires multimodal therapy. The ALINA trial demonstrated the efficacy of adjuvant ALK tyrosine kinase inhibitors (ALK TKIs) in early-stage ALK-positive NSCLC but provided limited long-term data for stage III patients. Real-world evidence is needed to validate and expand these findings. Methods: This multicenter, real-world cohort study analyzed treatment patterns and clinical outcomes in 176 patients with stage III ALK-positive NSCLC. The prognosis of different EML4-ALK variants was evaluated. Inverse probability treatment weighting (IPTW) and sensitivity analyses were performed to adjust for the confounding factors. Results: At a median follow-up of 48.9 months, the 5-year overall survival (OS) and progression-free survival (PFS) rates were 71.9 % and 14.8 %, respectively, with a median PFS of 19.5 months. Among all 176 patients, 144 (81.8 %) received definitive local therapy, including 132 who underwent surgery and 12 who received definitive chemoradiotherapy (CRT); the remaining 32 patients (18.2 %) received systemic therapy alone. The most common EML4-ALK variants were v1 (25.3 % of patients, n = 23) and v3 (38.5 % of patients, n = 35). EML4-ALK v1 variants was associated with significantly better OS compared to other variants (P < 0.05). A total of 126 (71.6 %) patients relapsed, and 97 (55.1 %) had distant metastasis. Local treatment (HR = 0.33, 95 % CI: 0.15-0.73; P = 0.007) and targeted therapy (HR = 0.34, 95 % CI: 0.17-0.69; P = 0.003) were significant independent prognostic factors for better OS. Patients receiving local therapy and adjuvant ALK TKIs achieved 100 % 5-year OS without progression. The sensitivity analysis yielded similar findings. Conclusions: This study provided long-term follow-up data that validated the findings of the ALINA trial. Stage III ALK-positive NSCLC is prone to relapse but local therapy combined with adjuvant ALK TKIs offers a promising strategy. Patients with EML4-ALK v1 mutations may show improved outcomes.

Purpose The role of consolidation radiation therapy (cRT) in patients with oligometastatic non-small cell lung cancer (oligo-NSCLC) without driver genetic alterations remains uncertain in the era of immunotherapy (IO). This study aimed to evaluate the efficacy of cRT combined with IO at various programmed death ligand 1 (PD-L1) expression levels using data from a multicenter cohort. Methods and Materials Patients with oligo-NSCLC without driver genetic alterations, treated with IO with or without cRT, and with available PD-L1 tumor proportion scores (TPS) were retrospectively reviewed across 3 institutions. Inverse probability of treatment weighting (IPTW) was applied to control for bias. Results This study included 240 patients, among which 30.4%, 35.0%, and 34.6% patients had PD-L1 TPS 0, 1% to 49%, and ≥50%, respectively. After inverse probability of treatment weighting adjustment, subgroup analysis revealed that cRT significantly improved progression-free and overall survival in the PD-L1 TPS 0% to 49% group (hazard ratio [HR]: 0.59; 95% CI, 0.38-0.92; P = .009; HR: 0.59; 95% CI, 0.35-0.99; P = .016; respectively); however, no additional benefit was found in the PD-L1 TPS ≥50% group. Multivariate Cox analysis identified PD-L1 TPS score as an independent prognostic factor only in the IO group (HR: 0.54; 95% CI, 0.34-0.88; P = .01). Adding cRT to IO in patients with PD-L1 TPS 0% to 49% improved survival to levels comparable with those of patients with PD-L1 TPS ≥50%. Moreover, cRT was associated with lower rate of progression at original sites in the overall cohort (HR: 0.51; 95% CI, 0.32-0.81; P = .005), particularly in the PD-L1 TPS 0% to 49% subgroup (HR: 0.38; 95%: CI, 0.21-0.68; P = .001). Conclusions The addition of cRT to IO may improve survival outcomes for driver-negative oligo-NSCLC patients with low or negative PD-L1 expression. The PD-L1 TPS may be a valuable biomarker to optimize cRT patient selection in the era of immunotherapy. Further prospective investigations into this stratification strategy are warranted.

ObjectiveTo systematically investigate the impact of adjusting the relative weight of the built-in Stereotactic Radiosurgery Normal Tissue Objective (SRS-NTO) on dosimetric quality, plan complexity, and delivery efficiency in HyperArc™ stereotactic radiosurgery (SRS) for brain oligometastases.MethodsIn this retrospective planning study, a cohort of 20 patients with 1-3 brain oligometastases was analyzed. For each case, six distinct HyperArc plans were designed and optimized using the Varian Eclipse™ Treatment Planning System. To precisely isolate its impact, the relative weight of the SRS-NTO to the PTV objective was systematically varied across six levels-50%, 75%, 100% (default), 125%, 150%, and 200%-while all other planning parameters were held constant. A comprehensive comparative evaluation was then performed to assess the plans across four key domains: (i) dosimetric quality, evaluated by metrics including the Paddick Conformity Index (CI), Gradient Index (GI), and dose to Organs at Risk (OARs); (ii) plan complexity, characterized by various modulation and aperture-based indices; (iii) delivery efficiency, primarily quantified by the total Monitor Units (MUs); and (iv) physical deliverability, verified via Gamma analysis.ResultsIncreasing NTO weight did not significantly alter dosimetric quality; key metrics for CI, GI, and OAR sparing remained statistically equivalent (p > .05). Conversely, higher NTO weights prompted a significant reduction in total MUs (p < .001) that reached an optimum at the 150% setting, and enhanced plan deliverability, evidenced by significantly higher Gamma passing rates under stricter verification criteria. An inflection point was observed beyond the 150% setting, with higher weights leading to degraded plan complexity and efficiency. Strategies within the 125% to 150% range demonstrated a superior balance, achieving optimal dosimetric trends while maximizing gains in efficiency and precision.ConclusionIn HyperArc SRS for brain oligometastases, moderately increasing the SRS-NTO weight from the default 100% into the 125% to 150% range is a superior clinical strategy. This adjustment significantly enhances treatment efficiency and delivery precision by reducing plan complexity, without compromising dosimetric quality, thereby achieving a superior overall performance.

Proton beam therapy has demonstrated significant clinical efficacy across multiple malignancies, primarily attributed to its distinct physical dose deposition characteristics. However, clinical implementation remains constrained by resource limitations and accumulated experience, particularly regarding radiation tolerance thresholds for organs at risk (OARs). Unlike photon-based radiotherapy where consensus guidelines like QUANTEC have been established, standardized dose constraints for proton therapy require further validation. This systematic review synthesizes decade-long evidence from peer-reviewed literature and clinical guidelines, critically evaluating current understanding of OARs tolerance in proton therapy. The comprehensive analysis aims to inform clinical decision-making and protocol development for emerging proton therapy.

Background: Liquid biopsy-based biomarkers, including circulating tumor DNA (ctDNA) and blood tumor mutational burden (bTMB), are recognized as promising predictors of prognoses and responses to immune checkpoint inhibitors (ICIs), despite insufficient sensitivity of single biomarker detection. This research aims to determine whether the combinatorial utility of longitudinal ctDNA with bTMB analysis could improve the prognostic and predictive effects. Methods: This prospective two-center cohort trial, consisting of discovery and validation datasets, enrolled unresectable locally advanced non-small-cell lung cancer (LA-NSCLC) patients and assigned them to chemoradiotherapy (CRT) or CRT + consolidation ICI cohorts from 2018 to 2022. Blood specimens were collected pretreatment, 4 weeks post-CRT, and at progression to assess bTMB and ctDNA using 486-gene next-generation sequencing. Dynamic ∆bTMB was calculated as post-CRT bTMB minus baseline bTMB levels. Decision curve analyses were performed to calculate Concordance index (C-index). Results: One hundred twenty-eight patients were enrolled. In the discovery dataset (n = 73), patients treated with CRT and consolidation ICI had significantly longer overall survival (OS; median not reached [NR] vs 20.2 months; P < 0.001) and progression-free survival (PFS; median 25.2 vs 11.4 months; P = 0.011) than those without ICI. Longitudinal analysis demonstrated a significant decrease in ctDNA abundance post-CRT (P < 0.001) but a relative increase with disease progression. Post-CRT detectable residual ctDNA correlated with significantly shorter OS (median 18.3 months vs NR; P = 0.001) and PFS (median 7.3 vs 25.2 months; P < 0.001). For patients with residual ctDNA, consolidation ICI brought significantly greater OS (median NR vs 14.8 months; P = 0.005) and PFS (median 13.8 vs 6.2 months; P = 0.028) benefit, but no significant difference for patients with ctDNA clearance. Dynamic ∆bTMB was predictive of prognosis. Patients with residual ctDNA and increased ∆bTMB (∆bTMB > 0) had significantly worse OS (median 9.0 vs 23.0 months vs NR; P < 0.001) and PFS (median 3.4 vs 7.3 vs 25.2 months; P < 0.001). The combinatorial model integrating post-CRT ctDNA with ∆bTMB had optimal predictive effects on OS (C-index = 0.723) and PFS (C-index = 0.693), outperforming individual features. In the independent validation set, we confirmed residual ctDNA predicted poorer PFS (median 50.8 vs 14.3 months; P = 0.026) but identified more consolidation ICI benefit (median NR vs 8.3 months; P = 0.039). The combined model exhibited a stable predictive advantage (C-index = 0.742 for PFS). Conclusions: The multiparameter assay integrating qualitative residual ctDNA testing with quantitative ∆bTMB dynamics improves patient prognostic risk stratification and efficacy predictions, allowing for personalized consolidation therapy for LA-NSCLC.

BACKGROUND AND PURPOSE:Respiratory movement has an important impact on the radiotherapy for lung tumor. Respiratory gating technology is helpful to improve the accuracy of target delineation. This study investigated the value of prospective and retrospective respiratory gating simulations in target delineation and radiotherapy plan design for solitary pulmonary tumors (SPTs) in radiotherapy. METHODS:The enrolled patients underwent CT simulation with three-dimensional (3D) CT non gating, prospective respiratory gating, and retrospective respiratory gating simulation. The target volumes were delineated on three sets of CT images, and radiotherapy plans were prepared accordingly. Tumor displacements and movement information obtained using the two respiratory gating approaches, as well as the target volumes and dosimetry parameters in the radiotherapy plan were compared. RESULTS:No significant difference was observed in tumor displacement measured using the two gating methods (p > 0.05). However, the internal gross tumor volumes (IGTVs), internal target volumes (ITVs), and planning target volumes (PTVs) based on the retrospective respiratory gating simulation were larger than those obtained using prospective gating (group A: pIGTV = 0.041, pITV = 0.003, pPTV = 0.008; group B: pIGTV = 0.025, pITV = 0.039, pPTV = 0.004). The two-gating PTVs were both smaller than those delineated on 3D non gating images (p < 0.001). V5Gy, V10Gy, V20Gy, V30Gy, and mean lung dose in the two gated radiotherapy plans were lower than those in the 3D non gating plan (p < 0.001); however, no significant difference was observed between the two gating plans (p > 0.05). CONCLUSIONS:The application of respiratory gating could reduce the target volume and the radiation dose that the normal lung tissue received. Compared to prospective respiratory gating, the retrospective gating provides more information about tumor movement in PTV.

Dear Editor, The efficacy of definitive concurrent or sequential chemoradiotherapy (dCRT) varies significantly among limited-stage small-cell lung cancer (LS-SCLC) patients, with about 10%–13% of patients achieving 5-year survival, while 58% of patients die within 1 year.1-3 Therefore, there is an urgent need to find biomarkers for early prediction of the efficacy of dCRT in LS-SCLC in support of risk stratification. Tumourigenesis and progression are heterogeneous at the phenotypic, physiologic and genomic levels, making predictive information obtained via radiomic or genomic profiling alone of limited value for clinical decision making.4-6 The present study aimed to develop a combination of genomic, radiomic and fused radiogenomic biomarkers for predicting the response of LS-SCLC to dCRT in training and validation cohorts, and to provide optimised multi-omics prediction models based on their predictive power for LS-SCLC. Totally 154 patients with LS-SCLC who received dCRT in Shandong Cancer Hospital and Institute were included, and were randomly divided into a training group and test group at a ratio of 7:3. No significant differences in clinical or genomic characteristics were found between the two cohorts (Table S1). The median PFS (progression free survival, mPFS) among all patients was 12.7 months (range, 2.4−60.5 months). In the training cohort, LASSO regression7 was performed to obtain the most significant radiomic features related to PFS according to a λmin of .046 (Figure 1A,B). The radiomic signature (Rad-score) was then constructed by linearly combining the 10 selected features and corresponding weighting coefficients, as listed in Table S2. The best threshold was .35,8 which divided patients into a high-risk group (Rad-score ≥ .35) and a low-risk group (Rad-score < .35). Rad-score was identified as an independent biomarker for PFS on both univariate and multivariate Cox analyses. The correlation between Rad-score and PFS was significant in the training cohort (mPFS, 14.83 vs. 10.63 months, p = .006; hazard ratio = 2.152, 95% confidence interval: 1.236−3.749, p = .007), as shown in Figure 2 and Table S3. The C-index for the ability of the Rad-score to predict PFS in the training set was .574, and the area under the curve (AUC) values for prediction of 6- and 12-month PFS were .583 and .601, respectively (Figure 3 and Table S4). A significant association between Rad-score and PFS was also demonstrated in the validation cohort (mPFS, 14.20 vs. 7.83 months, p = .015; C-index = .656; AUC for 6- and 12-month PFS: .746 and .640, respectively). We previously identified novel biomarkers of alterations in the CDK4, GATA6 and MAPK/ERK pathway genes as well as tumour mutational burden (TMB) status as predictors of the response to dCRT in a large cohort of LS-SCLC patients.9 According to the prior genomic model (Genes-scorepr) combined by these four features, patients with low Genes-scorepr (no gene mutations and high TMB) showed significant improved PFS in training and validation cohorts (mPFS, low Genes-scorepr vs. high Genes-scorepr, 18.43 vs. 11.13 months, p < .001; mPFS, low Genes-scorepr vs. high Genes-scorepr, 9.27 vs. 5.8 months, p = .014) (Figure 2). And, posterior genomic biomarkers (Genes-scorepo) of CDK4 and TMB status were recognised as significant factors (Table S3) according to the univariate and multivariate Cox analyses. In the training group, patients with a low Genes-scorepo (no CDK4 amplification and high TMB) showed significantly prolonged PFS compared with patients with high Gene-scorepo (CDK4 amplification and/or low TMB) (mPFS, 16.03 vs. 9.03 months, p = .006) (Figure 2). In the validation set, Kaplan–Meier analysis showed that the Genes-scorepo model could effectively distinguish SCLC patients with different PFS durations (mPFS, low Genes-scorepo vs. high Genes-scorepo, 17.77 vs. 9.27 months, p = .001) (Figure 2). As shown in Figure 3 and Table S4, the corresponding combination of radiogenomic models (Rad-Genespr and Rad-Genespo) all demonstrated higher C-index and 6- and 12-month AUC values of the ability to predict PFS than individual radiomic (Rad-score) or genomic models (Genes-scorepr and Genes-scorepo), respectively. To the best of our knowledge, no research has been conducted to date to determine the ability of fused radiogenomic features to predict the efficacy of dCRT in LS-SCLC.10 According to the Rad-score, Genes-scorepr and Genes-scorepo, Kaplan–Meier analyses were conducted according to the combination signature (Rad-Genespr/po) built from the radiogenomic factors (Figure 2). Significant associations (log-rank p < .05) were found between Rad-Genespo and PFS in the training and validation subgroups. The mPFS durations for the high-risk, intermediate-risk and low-risk groups were 6.70, 12.17 and 16.10 months, respectively, in the training cohort and 6.7, 10.5 and 17.77 months, respectively, in the validation cohort. However, Rad-Genespr model was only associated with PFS in the training cohort (mPFS, 17.77 vs. 13.07 vs. 7.67 months, p < .001), there was no statistical difference in the validation cohort (mPFS, 9.27 vs. 5.87 vs. 5.4 months, p = .121). Overall, we identified several radiomic, genomic and radiogenomic biomarkers with the potential to identify LS-SCLC patients with reduced risk of progression after dCRT, and a combination of radiogenomic features was found to form the optimal prediction model based on the higher C-index and AUC values compared with individual radiomic and genomic models. Given that the Rad-Genespr model failed to show a survival difference in the validation cohort, Genes-scorepo developed by CDK4 and TMB maybe better genomic models. The radiogenomic model combining the Rad-score model, CDK4 amplification and TMB status could successfully stratify patients into high-risk, intermediate-risk and low-risk groups, and thus, may be conducive for screening SCLC patients according to the likelihood of improved PFS. As our research was conducted by retrospective, single centre and relatively small sample size of patients, which may limit the generalisability of the results. And the combined radiogenomic predictive model established in this study requires external validation with a larger sample size of data collected from more medical centres. Li Li designed this study. Li Li and Ying Yin acquired clinical data and performed patient follow-ups. Li Li, Jinghao Duan, Yongsheng Gao and Fengchang Yang performed data analysis. Li Li, Wenjie Tang, Xiaoyu Song, Jinfeng Cui and Tao Hu edited the manuscript. Jinming Yu and Shuanghu Yuan conceived and supervised the study. We would like to thank all the patients and family members who gave their consent for use of their data in this study. This study was supported in part by the National Natural Science Foundation of China (NSFC82073345), the Natural Science Foundation of Shandong Province Innovation and Development Joint Fund (ZR202209010002), the Taishan Scholars Program and Jinan Clinical Medicine Science and Technology Innovation Plan (202019060) to Shuanghu Yuan and the Major Basic Research Program of the National Natural Science Foundation of Shandong(ZR2022ZD16), Natural Science Youth Foundation of Shandong (ZR2023QH155), and Postdoctoral Science Foundation of China (2023M742159) to Li Li. The authors declare they have no conflicts of interest. All authors read and approved the final manuscript. The study was approved by the Ethics Committee of Shandong Cancer Hospital and Institute (No. SDTHEC2020004042). Written informed consent was obtained from each patient before sample collection. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Background:The combination of immune checkpoint inhibitors (ICIs) and radiotherapy (RT) may increase the risk of radiation esophagitis (RE). This study aimed to establish and validate a new nomogram to predict RE in patients with non-small cell lung cancer (NSCLC) undergoing immunochemotherapy followed by RT (ICI-RT). Methods:The 102 eligible patients with NSCLC treated with ICI-RT were divided into training (n = 71) and validation (n = 31) cohorts. Clinicopathologic features, dosimetric parameters, inflammatory markers, and radiomic score (Rad-score) were included in the univariate logistic regression analysis, and factors with p < 0.05 in the univariate analysis were included in the multivariate logistic regression analysis. Factors with significant predictive values were obtained and used for developing the nomogram. The area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve were used to validate the model. Results:A total of 38 (37.3%) patients developed RE. Univariate and multivariate analyses identified the following independent predictors of RE: a maximum dose delivered to the esophagus >58.4 Gy, a mean esophagus dose >13.3 Gy, and the Rad-score. The AUCs of the nomogram in the training and validation cohorts were 0.918 (95% confidence interval [CI]: 0.824-1.000) and 0.833 (95% CI: 0.697-0.969), respectively, indicating good discrimination. The calibration curves showed good agreement between the predicted occurrence of RE and the actual observations. The decision curve showed a satisfactory positive net benefit at most threshold probabilities, suggesting a good clinical effect. Conclusions:We developed and validated a nomogram based on imaging histological features and RT dosimetric parameters. This model can effectively predict the occurrence of RE in patients with NSCLC treated using ICI-RT.

Objectives The purpose of this study was to investigate the prognostic significance of radiomics in conjunction with hematological parameters in relation to the overall survival (OS) of individuals diagnosed with esophageal squamous cell carcinoma (ESCC) following definitive chemoradiotherapy (dCRT). Methods In this retrospective analysis, a total of 122 patients with locally advanced ESCC were included. These patients were randomly assigned to either the training cohort ( n = 85) or the validation cohort ( n = 37). In the training group, the least absolute shrinkage and selection operator (LASSO) regression was utilized to choose the best radiomic features for calculating the Rad-score. To develop a nomogram model, both univariate and multivariate analyses were conducted to identify the clinical factors and hematologic parameters that could predict the OS. The performance of the predictive model was evaluated using the C-index, while the accuracy was assessed through the calibration curve. Results The Rad-score was calculated by selecting 10 radiomic features through LASSO regression. OS was predicted independently by neutrophil-to-monocyte ratio (NMR) and Rad-score according to the results of multivariate analysis. Patients who had a Rad-score > 0.47 and an NMR > 9.76 were at a significant risk of mortality. A nomogram was constructed using the findings from the multivariate analysis. In the training cohort, the nomogram had a C-index of 0.619, while in the validation cohort, it was 0.573. The model’s accuracy was demonstrated by the calibration curve, which was excellent. Conclusion A prognostic model utilizing radiomics and hematologic parameters was developed, enabling the prediction of OS in patients with ESCC following dCRT. Critical relevance statement Patients with esophageal cancer who underwent definitive chemoradiotherapy may benefit from including CT radiomics in the nomogram model. Key points • Predicting the prognosis of ESCC patients before treatment is particularly important. • Patients with a Rad-score > 0.47 and neutrophil-to-monocyte ratio > 9.76 had a high risk of mortality. • CT-based radiomics nomogram model could be used to predict the survival of patients. Graphical Abstract

Dear Editor, Responses to consolidation immune checkpoint inhibitor (ICI) in locally advanced non-small-cell lung cancer (LA-NSCLC) are heterogeneous, and current decision-making procedures have little accuracy.1 This prospective cohort study provided the first evidence for dynamic circulating tumour DNA (ctDNA) predicting failure patterns in LA-NSCLC patients receiving chemoradiotherapy (CRT), allowing the early identification of the potentially curable population with radical CRT and different therapeutic benefits from consolidation ICI. Exploring effective biomarkers to guide personalized consolidation immunotherapy, avoid overtreatment, and reduce the potential risk of immune-related toxicities is of clinical importance.1-3 In this prospective multicenter trial (NCT04014465), 105 patients with unresectable LA-NSCLC were assigned to CRT or CRT plus consolidation ICI cohorts, with balanced baseline characteristics (Figure 1A and Table S1). As expected, patients undergoing consolidation ICI had significantly improved overall and progression-free survival (PFS) (Figure 1B,C). All patients have collected blood samples at baseline, on-CRT (radiotherapy reached 40 Gy/4 weeks), post-CRT (1 month after CRT), and progressive timepoints, subjected to 486-gene next-generation sequencing to analyze longitudinal ctDNA. Detailed information about ctDNA assay techniques and study procedures is attached as the Supporting Information. No significant difference in ctDNA abundance across cohorts at any time point (Figure 1D). Notably, quantitative ctDNA could reflect tumour burden,4 since ctDNA levels significantly decreased with effective CRT but increased at disease progression, and baseline ctDNA positively correlated with the clinical stage (Figure 1E–G). We further explored the prognostic value of ctDNA at longitudinal landmark timepoints. Post-CRT detectable ctDNA, rather than baseline or on-CRT ctDNA, was associated with significantly worse survival (Figure 2A–C). In patients with detectable ctDNA post-CRT, 75% of non-progression patients received consolidation ICI, while 63.3% of non-progression patients used ICI in the undetectable population (Figure 2D,E). Survival analyses were confirmed in patients with detectable ctDNA post-CRT, those receiving consolidation ICI had significantly longer PFS than those without ICI, yet no significant difference in patients with ctDNA clearance (Figure 2F,G). According to post-CRT ctDNA minus baseline ctDNA levels, the dynamic change pattern of longitudinal ctDNA included decreased (n = 54), stably undetectable (n = 30), and increased (n = 19; Figure 2H). Strikingly, the majority of patients with increased ctDNA (73.7%) developed disease progression (Figure 2I). Next, we investigated the predictive effect of longitudinal ctDNA on first failure patterns, which were categorized as local-regional, distant, or both, as presented in Figure 3A. The primary failure pattern for patients with decreased ctDNA in the CRT cohort was distant metastasis (51.9%), and consolidation ICI significantly reduced the incidence of distant metastasis (18.5%; p = .019). However, in the stably undetectable ctDNA group, the incidence of local-regional failure (21.4% vs. 37.5%) and distant metastasis (28.6% vs. 31.3%) was both similar between patients with and without consolidation ICI (p = .592). In the increased ctDNA group, simultaneously local-regional and distant failure was the most predominant failure pattern (36.4%) for patients with CRT, and consolidation ICI brought a tendency (p = .583) of a reduced proportion of local-regional (18.2% vs. 12.5%), distant (27.3% vs. 25.0%), and simultaneously local-regional and distant (36.4% vs. 12.5%) failure. For patients with decreased ctDNA post-CRT, although consolidation ICI brought significant PFS benefit (p = .046; Figure 3B), a more obvious distant metastasis-free survival (DMFS) benefit was observed (p = .003; Figure 3C). In the increased ctDNA population (Figure 3D,E), patients with consolidation ICI had significantly improved PFS (p = .005) and DMFS (p = .020). In contrast, in the stably undetectable ctDNA group (Figure 3F,G), no significant difference in PFS (p = .427) or DMFS (p = .773) between patients with and without ICI. These data suggest that dynamic ctDNA could identify different failure patterns and therapeutic responses to ICI: 1) Decreased ctDNA dynamics predict a higher risk of distant metastasis but more DMFS benefit from ICI, presumably because effective radiotherapy could cause localized tumour cell death and accordingly decreased release of tumour-derived products into the peripheral blood, whereas it is difficult for local radiotherapy to completely eradicate disseminated ctDNA pre-existed in the circulation.5 Consolidation ICI as a potent systemic treatment would effectively reduce the risk of overt metastases and micrometastases, thereby bringing DMFS benefit to this patient subset; 2) Increased ctDNA, reflecting resistance to definitive CRT, is associated with a higher risk of distant and local-regional failure, and subsequent ICI improves DMFS as well as PFS. In the clinical setting, for patients with solitary lesions of suspected metastasis,6 dynamic ctDNA testings may contribute to differential diagnosis between primary and metastatic diseases, as increased ctDNA indicates the hematogenous spread of tumour cells in the peripheral circulation7 3) Stably undetectable ctDNA predicts excellent outcomes irrespective of consolidation ICI, suggesting the potentially curable population with CRT.2 Cox regression analysis demonstrated consolidation ICI, post-CRT ctDNA, and dynamic ctDNA changes were significant variables in predicting PFS (Table S2 and Figure S1). Lastly, we compared the prediction effects and clinical decision-making benefits of single-time ctDNA detection with longitudinal ctDNA dynamics. Time-dependent receiver operating characteristic curves indicated that post-CRT ctDNA was the optimal predictor of PFS (Figure 4A,B). In terms of dynamic ctDNA assessments, as shown in Figure 4C,D, patients with increased ctDNA had the significantly worst PFS and DMFS, and patients with stably undetectable ctDNA had the longest survival. Furthermore, decision curve analysis suggested the combined model integrating qualitative post-CRT ctDNA detection with quantitative ctDNA dynamics had superior usefulness in predicting PFS and DMFS, compared to individual features (Figure 4E,F). Based on this combinatorial model, patients with decreased ctDNA were further divided into two groups, and patients with post-CRT detectable/decreased ctDNA had significantly worse PFS and DMFS than those with undetectable/decreased ctDNA (Figure 4G-H), in both CRT and CRT + consolidation ICI cohorts (Figure S2). In conclusion, we determined that the multiparameter assay integrating qualitative with quantitative ctDNA metrics could improve patient risk stratification, consistent with previous findings.8-10 Moreover, we innovatively discovered dynamic ctDNA could predict failure patterns, potential curability with CRT, and different responses to consolidation ICI, thereby serving as a robust prognostic and predictive model with improved usefulness to facilitate ctDNA-guided treatment personalization. Our findings warrant independent validation in a larger-scale clinical cohort. The ongoing randomized, phase II trial (InTRist, NCT05888402) will further validate the predictive value of longitudinal ctDNA dynamics and provide high-quality evidence for translational application of ctDNA in LA-NSCLC. Yu Wang and Tao Zhang performed data analysis and interpretation, investigation, as well as manuscript drafting. Yin Yang, Jianyang Wang, Canjun Li, Xin Xu, Yuqi Wu, Ying Jiang and Jinghao Duan assisted with data acquisition and curation, project administration, and independent validation. Luhua Wang and Nan Bi supervised this study, provided resources, acquired funding, and critically revised the manuscript. All authors contributed to the study conceptualization and approved the final version. We thank the patients, caregivers, and their families for participating in this study. The authors declare no conflict of interest. This work was founded by the National Natural Sciences Foundation Key Program (No. 82173348), CAMS Innovation Fund for Medical Sciences (No. 2021-1-I2M-1-012), and the Special Research Fund for Central Universities, Peking Union Medical College (No. 3332023133). This study was approved by the institutional review board of the Chinese Academy of Medical Sciences (No. 19/098-1883). All patients provided written informed consent. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Purpose:This study aims to identify risk factors associated with symptomatic radiation pneumonitis (RP, Grade ≥ 2) following immunotherapy preceding thoracic radiotherapy (ICI-TRT) and establish safe dose constraints. Patients and Methods:This retrospective study enrolled patients diagnosed with non-small-cell lung cancer (NSCLC) who underwent thoracic radiotherapy (TRT) following immune checkpoint inhibitors (ICIs) treatment. The primary endpoint was the occurrence of symptomatic RP (Grade ≥ 2), as defined by the Common Terminology Criteria for Adverse Events version 5.0. Clinical and lung dosimetric parameters were analyzed to determine their associations with symptomatic RP. Dosimetric parameters included mean lung dose (MLD) and the percentage of lung volume receiving ≥10 Gy (V10), ≥20 Gy (V20), ≥30 Gy (V30), and ≥40 Gy (V40). Receiver operating characteristic curves were used to predict the risk of developing symptomatic RP to establish optimal threshold values for each dosimetric predictor. Results:Among the 118 patients included, the incidence of symptomatic RP was 25.4%. Tumor locations, intervals between immunotherapy and radiotherapy, and MLD, V10, V20, V30, and V40 were identified as independent risk factors for symptomatic RP. The area under the curve (AUC) values for MLD, V10, V20, V30, and V40 were 0.788 (95% confidence interval [CI] 0.704-0.873), 0.789 (95% CI 0.705-0.874), 0.791 (95% CI 0.706-0.876), 0.784 (95% CI 0.697-0.871), and 0.749 (95% CI 0.656-0.842), respectively. The optimal threshold values for MLD, V10, V20, V30, and V40 were 9.7 Gy, 26.3%, 15.9%, 13.3%, and 8.6%, respectively. These thresholds are lower than current guideline recommendations, and maintaining dosimetric parameters below these values resulted in a cumulative symptomatic RP incidence of <12%. Conclusion:The recommended dose thresholds for MLD, V10, V20, V30, and V40 are lower than the current guidelines, underscoring the importance of radiotherapy planning to minimize symptomatic RP occurrence in patients receiving ICI-TRT.

BackgroundThe purpose of the study was to evaluate the dosimetry of the Halcyon in prophylactic cranial irradiation (PCI) with volumetric modulated arc therapy (VMAT) and hippocampal-sparing for small cell lung cancer (SCLC).MethodsFive VMAT plans were designed on CT images of 15 patients diagnosed with SCLC and received PCI. Three plans with two full arcs were generated on the Trilogy and the TrueBeam accelerators, and flattening filter (FF) and flattening filter free (FFF) modes were used on TrueBeam. Two Halcyon plans with two and three full arcs were generated, referred to as H-2A and H-3A, respectively. The prescription dose was 25 Gy in 2.5-Gy fractions. The dose limit for hippocampus were D100 ≤ 9Gy and Dmax ≤ 16Gy. The Wilcoxon matched-paired signed-rank test was used to evaluate the significance of the observed differences between the five plans.ResultsH-2A plans significantly increased the D2 of PTV, and H-3A plans showed comparable or even better target dosimetry (better conformity) compared to the three plans on C-arm accelerators. Compared to T and TB plans, the two Halcyon plans significantly reduced the D100 and mean doses of bilateral hippocampus, the mean doses of eyeballs, and the maximum doses of lenses. D100 of hippocampus was reduced in TrueBeam plans comparing to Trilogy plans. The FFF plans on TrueBeam also represented advantages in Dmean and D100 of hippocampas, Dmean and Dmax of eyeballs, and the Dmax of lenses compared to FF plans. Halcyon plans and TrueBeam plans with FFF mode increased the MUs compared to FF plans. Comparing to H-2A, the H-3A plans exhibited additional dosimetric advantages, including D2, CI and HI of PTV, as well as the maximum and mean doses of hippocampus and eyeballs, and the maximum doses of optic nerves and brainstem. The two Halcyon plans significantly reduced the delivery time and showed the higher gamma passing rate than the three plans of C-arm accelerators.ConclusionsCompared with the C-arm accelerators, the dose of hippocampus and the delivery times on Halcyon are relatively significantly reduced for hippocampal-sparing PCI. Three arcs are recommended for VMAT plans with the Halcyon in hippocampal-sparing PCI.

Purpose:Accurate lesion segmentation is a prerequisite for radiomic feature extraction. It helps to reduce the features variability so as to improve the reporting quality of radiomics study. In this research, we aimed to conduct a radiomic feature reproducibility test of inter-/intra-observer delineation variability in hepatocellular carcinoma using 3D-CT images, 4D-CT images and multiple-parameter MR images.Materials and Methods:For this retrospective study, 19 HCC patients undergoing 3D-CT, 4D-CT and multiple-parameter MR scans were included in this study. The gross tumor volume (GTV) was independently delineated twice by two observers based on contrast-enhanced computed tomography (CECT), maximum intensity projection (MIP), LAVA-Flex, T2W FRFSE and DWI-EPI images. We also delineated the peritumoral region, which was defined as 0 to 5 mm radius surrounding the GTV. 107 radiomic features were automatically extracted from CECT images using 3D-Slicer software. Quartile coefficient of dispersion (QCD) and intraclass correlation coefficient (ICC) were applied to assess the variability of each radiomic feature. QCD<10% and ICC≥0.75 were considered small variations and excellent reliability. Finally, the principal component analysis (PCA) was used to test the feasibility of dimensionality reduction.Results:For tumor tissues, the numbers of radiomic features with QCD<10% indicated no obvious inter-/intra-observer differences or discrepancies in 3D-CT, 4D-CT and multiple-parameter MR delineation. However, the number of radiomic features (mean 89) with ICC≥0.75 was the highest in the multiple-parameter MR group, followed by the 3DCT group (mean 77) and the MIP group (mean 73). The peritumor tissues also showed similar results. A total of 15 and 7 radiomic features presented excellent reproducibility and small variation in tumor and peritumoral tissues, respectively. Two robust features showed excellent reproducibility and small variation in tumor and peritumoral tissues. In addition, the values of the two features both represented statistically significant differences among tumor and peritumoral tissues (P<0.05). The PCA results indicated that the first seven principal components could preserve at least 90% of the variance of the original set of features.Conclusion:Delineation on multiple-parameter MR images could help to improve the reproducibility of the HCC CT radiomic features and weaken the inter-/intra-observer influence.

目的 比较不同模态图像下(3DCT、4DCT和多参数MR)原发性肝癌靶区勾画的差异,并在此基础上分别制定逆向调强放疗计划,比较靶区和肝脏正常组织的剂量学参数,以期寻找最佳的肝癌靶区勾画图像.方法 回顾性选取2019-12-01-2021-03-31山东省肿瘤医院15例已行放疗的原发性肝癌患者模拟定位数据.由同一位高年资影像医师分别在3DCT图像、4DCT图像中的最大密度投影(MIP)图像和多参数MR图像上勾画大体肿瘤体积(GTV),分别命名为GTV-3D、GTV-4D和GTV-MR.然后由另一位高年资放疗医师对靶区进行确认,在2人意见不一致的情况下经共同商榷确定最后的勾画结果.将GTV-MR边界均匀外扩5 mm得到计划靶区体积(PTV)-MR.以PTV-MR为基准,对GTV-3D和GTV-4D分别外扩若干毫米,得到PTV-3D和PTV-4D,使得95％体积的PTV-MR被PTV-3D和PTV-4D覆盖.针对以上3个靶区,由同一位计划经验丰富的高年资物理师采用Varian Eclipse计划系统设计逆向调强计划.计算不同靶区体积,使用戴斯相似性系数(DSC)评估2个靶区之间的相似程度.计划评价指标包括靶区适形指数和均匀指数,靶区剂量D2％、D98％、Dmean及肝脏正常组织受量.结果 GTV-3D、GTV-4D和GTV-MR靶区中位体积分别为8.81、10.28和13.89 cm3;要保证95％体积的PTV-MR被PTV-3D和PTV-4D覆盖,GTV-3D、GTV-4D边界需分别外扩12和10 mm.PTV-3D、PTV-4D和PTV-MR靶区中位体积分别为69.53、62.79和54.53 cm3.PTV-3D和PTV-4D的DSC最大,为0.68;PTV-3D和PTV-MR的DSC最小,为0.44.所有计划靶区均能达到临床要求,不同计划之间的靶区剂量学参数总体差异无统计学意义,均P>0.05.肝脏正常组织中位平均剂量在PTV-3D计划、PTV-4D计划和PTV-MR计划中分别为15.97、12.89和11.97 Gy,总体差异有统计学意义,H=12.57,P=0.029.结论 不同模态影像勾画的原发性肝癌靶区差异较大,基于多参MR勾画的PTV体积小于基于3DCT和4DCT勾画的PTV体积.基于多参MR有可能会缩小肝癌靶区外扩边界,降低肝脏正常组织受量,建议在原发性肝癌放疗靶区勾画时尽可能地参考多参MR影像学信息.

目的:研究McGill大学开发的蒙特卡罗治疗计划系统MMCTP(McGill Monte Carlo treatment planning system)用于临床剂量学研究的可行性.方法:选取某院2012年6月至2016年12月采用RapidArc加速器治疗的40例患者,按照治疗部位分为头部组、胸部组、腹部组和盆腔组,每组10例患者.通过Eclipse计划系统导出40例患者的治疗计划信息,并导入MMCTP,通过MMCTP调用EGSnrc程序进行蒙特卡罗模拟,并计算得到新的剂量学结果.比较2种治疗计划系统的靶区和危及器官的物理剂量学参数及Gamma通过率.采用IBM SPSS 26.0软件进行统计学分析.结果:2种治疗计划系统的靶区剂量学参数中,除胸部组的Dg8、Dmean和HI差异有统计学意义外(t分别为-3.947、--4.385和3.959,P＜0.05),其余3组病例的靶区剂量学参数差异均无统计学意义(P＞0.05).2种治疗计划系统的危及器官剂量学参数和Gamma通过率差异均无统计学意义(P＞0.05).结论:MMCTP的剂量计算结果准确、可靠,可用于放疗剂量学的研究.

OBJECTIVE To investigate the following hypotheses: (1) ExacTrac X-ray Snap Verification (ET-SV) is an alternative to CBCT for positioning patients with esophageal carcinoma (EC), (2) ET-SV can detect displacement in EC patients during radiotherapy (RT) and (3) EC patients can be feasibly monitored in quasi-real-time with ET-SV during RT. METHODS Anthropomorphic phantoms and 13 patients were included in this study. CBCT and ET-SV were both implemented before treatment delivery to detect displacement, and their correction results were compared. For the patient tests, positional correction in 3 translational directions and the yaw direction were applied using the ET-SV correction results. The residual error was detected immediately using ET-SV. Finally, to acquire the intrafractional motion, ET-SV was implemented when the gantry was at 0°, 90°, 180° and 270°, respectively. RESULTS In phantom tests, the maximum value of the difference in displacement between the CBCT and ET systems was 1.16 mm for translation and 0.31° for yaw. According to Bland-Altman analysis of the patient test results, 5% (5/98), 5% (5/98), 5% (5/98), and 4% (4/98) of points were beyond the upper and lower limits of agreement in the AP, SI, LR and yaw directions, respectively. The mean residual error was -0.482 mm, 1.215 mm, 1.0 mm, -0.487°, 0.105°, and 0.003° in the AP, SI, LR, pitch, roll and yaw directions, respectively. The intrafractional displacement ranged from -0.21 mm to 0 mm for translation and from -0.63° to 0.21° for rotation. The mean total translational error for intrafractional motion increased from 0.47 mm to 1.14 mm during the treatment. CONCLUSION The accuracy of ET-SV for EC RT positional correction is comparable to that of CBCT. Thus, Quasi-real-time intrafractional monitoring can be used to detect EC patient displacement during radiotherapy.

In this study, we explore the diagnostic value of a novel PET/CT imaging tracer that specifically targets fibroblast activation protein (FAP), 18F-NOTA-FAPI, in a radiation induced lung damage (RILD) rat model. High focal radiation (40, 60, or 90 Gy) was administered to a 5-mm diameter area of the right lung in Wistar rats for evaluation of RILD induction. Lung tissues exposed to 90 Gy radiation were scanned with 18F-NOTA-FAPI PET/CT and with 18F-FDG. Dynamic 18F-NOTA-FAPI PET/CT scanning was performed on day 42 post-irradiation. After in vivo scanning, lung cryosections were prepared for autoradiography, hematoxylin and eosin (HE) and immunohistochemical (IHC) staining. An animal model of RILD was established and validated by histopathological analysis. On 18F-NOTA-FAPI PET/CT, RILD was first observed on days 42, 35 and 7 in the 40, 60 and 90 Gy groups, respectively. After treatment with 90 Gy, 18F-NOTA-FAPI uptake in an area of RILD emerged on day 7 (0.65 ± 0.05%ID/ml) and reappeared on day 28 (0.81 ± 0.09%ID/ml), remaining stable for 4–6 weeks. Autoradiography and HE staining IHC staining revealed that 18F-NOTA-FAPI accumulated mainly in the center of the irradiated area. IHC staining confirmed the presence of FAP+ macrophages in the RILD area, while FAP+ fibroblasts were observed in the peripheral area of irradiated lung tissue. 18F-NOTA-FAPI represents a promising radiotracer for in vivo imaging of RILD in a dose- and time-dependent manner. Noninvasive imaging of FAP may potentially aiding in the clinical management of radiotherapy patients.

Background Although surgical pathology or biopsy are considered the gold standard for glioma grading, these procedures have limitations. This study set out to evaluate and validate the predictive performance of a deep learning radiomics model based on contrast-enhanced T1-weighted multiplanar reconstruction images for grading gliomas. Methods Patients from three institutions who diagnosed with gliomas by surgical specimen and multiplanar reconstructed (MPR) images were enrolled in this study. The training cohort included 101 patients from institution 1, including 43 high-grade glioma (HGG) patients and 58 low-grade glioma (LGG) patients, while the test cohorts consisted of 50 patients from institutions 2 and 3 (25 HGG patients, 25 LGG patients). We then extracted radiomics features and deep learning features using six pretrained models from the MPR images. The Spearman correlation test and the recursive elimination feature selection method were used to reduce the redundancy and select most predictive features. Subsequently, three classifiers were used to construct classification models. The performance of the grading models was evaluated using the area under the receiver operating curve, sensitivity, specificity, accuracy, precision, and negative predictive value. Finally, the prediction performances of the test cohort were compared to determine the optimal classification model. Results For the training cohort, 62% (13 out of 21) of the classification models constructed with MPR images from multiple planes outperformed those constructed with single-plane MPR images, and 61% (11 out of 18) of classification models constructed with both radiomics features and deep learning features had higher area under the curve (AUC) values than those constructed with only radiomics or deep learning features. The optimal model was a random forest model that combined radiomic features and VGG16 deep learning features derived from MPR images, which achieved AUC of 0.847 in the training cohort and 0.898 in the test cohort. In the test cohort, the sensitivity, specificity, and accuracy of the optimal model were 0.840, 0.760, and 0.800, respectively. Conclusions Multiplanar CE-T1W MPR imaging features are more effective than features from single planes when differentiating HGG and LGG. The combination of deep learning features and radiomics features can effectively grade glioma and assist clinical decision-making.