Objectives: To evaluate the impact of tumor volume segmentation variability on the repeatability of radiomic features (RFs) and to determine how RF repeatability influences the generalizability of radiomic models for predicting overall survival (OS) in patients with oropharyngeal carcinoma (OPC).
Methods: We retrospectively analyzed CT images from 1017 patients with oropharyngeal carcinoma across three institutions. Perturbation methods were applied to simulate variations in gross tumor volume segmentation. RFs were extracted from both the original images and Laplacian of Gaussian-filtered images using different perturbation masks. RF repeatability was quantified using intra-class correlation coefficients (ICC). Repeatable RFs were progressively incorporated into the modeling process according to different ICC thresholds to assess the influence of feature repeatability on model generalizability.
Results: Incorporation of RFs with ICC values between 0.7 and 0.8 improved the AUC index of the two-year and three-year OS models in external validation cohorts. Using an ICC threshold of 0.7, RFs were classified into high- and low-repeatability groups, and OS models were trained and validated using the training, internal testing, and external validation cohorts. Across all cohorts, the OS model trained with high-repeatability RFs demonstrated significantly superior performance compared to the model trained with low-repeatability RFs.
Conclusion: The findings demonstrate that selecting RFs with ICC values greater than 0.7 substantially enhances both the generalizability and predictive performance of CT-based radiomic models for patients with OPC. This study further underscores the importance of considering RF repeatability, particularly in the presence of tumor volume segmentation variability, to improve the robustness and clinical reliability of radiomic models.
Purpose: To evaluate the efficacy and safety of the radiosensitizer-sodium glycididazole (CMNa) combined with definitive concurrent chemoradiotherapy (CCRT) versus CCRT alone in patients with locally advanced esophageal squamous cell carcinoma (ESCC).
Methods: Patients were enrolled and randomly assigned to receive CMNa plus CCRT (CMNa group) or CCRT alone (control group). CMNa (800 mg/m2) was administered three times per week during radiotherapy (1.8-2.0 Gy per fraction, total dose of 59.4-60.0 Gy). The primary endpoint was the objective response rate (ORR) and the secondary endpoint was the incidence of adverse events.
Results: Sixty-six patients with ESCC were recruited from six medical centers between 2016 and 2018. The ORRs in the CMNa and control groups were 90.32% and 68.57%, respectively (χ2 = 4.925, p = 0.0265). The proportions of patients with a complete response were 8/31 (25.81%) and 8/35 (22.86%) in the CMNa and control groups, respectively. The combination of CMNa and CCRT did not increase the incidence of acute or late adverse effects.
Conclusion: CMNa combined with CCRT improved the ORR in patients with ESCC compared with CCRT alone without increasing treatment-related toxicity.
Trial Registration: The protocol was registered at Clinicaltrials.gov (www.clinicaltrials.gov) (Clinical Trials ID: NCT02721563). Study Registration Date: March 29, 2016.
Objectives: Several clinical trials have demonstrated promising outcomes with thoracic radiotherapy (TRT) in patients with advanced lung adenocarcinoma (LUAD). However, a subset of patients derives no significant survival benefit from TRT. This study aimed to develop a risk model integrating biomarkers and clinical factors to identify patients most likely to benefit from TRT.
Methods: Prognostic proteins associated with LUAD survival were identified using data from The Cancer Proteome Atlas. Immunohistochemical analysis was performed to evaluate protein expression in patients with advanced LUAD treated at our institution between 2015 and 2019. Univariate and multivariate Cox regression analyses were conducted to determine clinical factors influencing prognosis. A risk model combining biomarkers and clinical variables was constructed to generate individualized risk scores.
Results: Four proteins, PAI-1, KU80, FOXO3A_pS318S321, and CKIT, were selected for further analysis. A total of 272 patients were divided into training (n = 181) and validation (n = 91) cohorts. Six prognostic factors including N-stage, presence of sensitive mutations, brain metastasis, adrenal metastasis, leukocyte count, and expression levels of PAI-1 and KU80 were incorporated into the risk model. Patients were stratified into low- and high-risk groups based on calculated risk scores. TRT significantly improved median survival time (69.0 vs. 39.3 months, p = 0.003) and overall survival (67.4 vs. 33.0 months, p = 0.035) in low-risk patients, but not in high-risk patients (median survival time: 19.8 vs. 18.2 months, p = 0.186; overall survival: 19.4 vs. 19.9 months, p = 0.607) for two cohorts.
Conclusion: Multiple biomarkers and clinical variables are associated with prognosis in LUAD. The risk model developed herein indicates that TRT confers a survival benefit exclusively in patients classified as low risk.
Purpose: We evaluated the effect of thoracic radiotherapy (TRT) on extensive-stage small-cell lung cancer (ES-SCLC) in elderly patients (aged ≥ 60 years) in the era of immunotherapy (IO) and analyzed the prognostic factors to guide personalized treatment.
Methods: The clinical data of 178 elderly patients were reviewed. Kaplan-Meier curves were generated to estimate the survival rates. Multivariate prognostic analyses were performed using Cox proportional hazards models.
Results: The mOS in the CRT-IO group was superior to that in the CT-IO group (22.0 vs. 14.7 months, p = 0.014). In addition, the mPFS in the CRT-IO group was significantly longer than that in the CT-IO group (11.2 vs. 7.0 months, p = 0.023). The mOS in the CRT-IO group was better than that in the CRT group; however, the difference was not statistically significant (22.0 vs. 17.3 months, p = 0.103). Overall survival was the longest in the CRT-IO group, followed by the CRT and CT-IO groups.Patients in the low-dose group had longer survival times than those in the high-dose group; however, this difference was not statistically significant (all p > 0.05).Multivariate analysis suggested that a KPS (Karnofsky performance status) score ≥ 80 (p = 0.003) was a good predictor of longer OS, whereas liver metastasis (p = 0.004) was associated with shorter OS.
Conclusions: CRT-IO should be prioritized as a treatment for elderly patients with ES-SCLC with good performance status and liver metastasis. However, CRT could be a viable option for patients with a compromised performance status or for whom economic factors are a concern.
Background: Radiation therapy (RT) is a cornerstone of cancer treatment that not only directly kills tumor cells but also produces synergistic effects with immunotherapy by remodeling the tumor immune microenvironment (TIME). However, systematic bibliometric analyses of RT-TIME interactions remain unexplored.
Methods: This study analyzed all the literature related to RT and TIME from the Web of Science (WOS) Core Collection through 2024. It utilized R, VOSviewer, and CiteSpace to visually analyze authors, countries, institutions, keywords, co-cited references, research hotspots, and frontiers.
Results: China, the United States, and Germany emerged as the leading contributors, with 1,253, 581, and 162 publications, respectively. Frontiers in Immunology was the most active journal (n = 186). Co-occurrence analysis identified “radiotherapy” (n = 898) and “immunotherapy” (n = 895) as core themes, with sustained focus on “CD8(+) T cells” (citation burst = 8.81) and emerging interest in “(nature killer) NK cells.” Temporal evolution revealed three research phases: initial exploration (2007–2015) of RT's immunomodulatory mechanisms of RT, clinical validation of RT combined with Programmed Cell Death Protein 1 (PD-1)/ Cytotoxic T-Lymphocyte-Associated Protein 4 (CTLA-4) inhibitors (2015–2020), and recent diversification (2020–2024) toward technical optimization (e.g., stereotactic RT), tumor type expansion, and safety management.
Conclusions: This comprehensive bibliometric analysis highlights future priorities, including exploring optimal synergistic strategies for combination therapies, investigating spatiotemporally resolved immune mechanisms, and developing predictive biomarkers. These areas are currently experiencing rapid growth and require further research.
Objective: Soft tissue sarcoma (STS) is a rare and highly heterogeneous malignancy. Conventional radiotherapy (CRT) often shows limited efficacy, especially in radioresistant subtypes, such as liposarcoma and fibrosarcoma, with local recurrence rates ranging from 10% to 30%. Spatially fractionated radiotherapy (SFRT), a technique that delivers non-uniform high-dose distributions, has shown promise in improving tumor control and potentially stimulating immune responses in preliminary studies.
Methods: This multicenter, prospective, randomized phase II trial aims to enroll 106 patients aged 18–70 years with pathologically confirmed STS and a minimum tumor diameter ≥5 cm. Participants will be randomized 1:1 into SFRT or CRT groups. CRT involves a uniform dose of 3.0 Gy per fraction over 15–20 fractions. SFRT employs a non-uniform dose distribution, supplementing CRT with high-dose spot irradiation of 8–15 Gy per fraction delivered for a total of 3–4 fractions. The primary endpoint was the objective response rate, and the secondary endpoints included local control, progression-free survival, and safety.
Discussion: This trial is the first randomized study to directly compare SFRT and CRT for STS. SFRT is expected to enhance tumor control and elicit immunomodulatory effects, particularly in radioresistant tumors. However, the potential acute toxicities and technical complexities warrant further evaluation. Future studies should investigate the synergistic potential of SFRT combined with immunotherapy.
Trial registration: The study was registered at ClinicalTrials.gov with the Identifier: NCT06980259 (Registered 12th May 2025).
Purpose: Hepatocellular carcinoma (HCC) is a lethal malignancy in which stereotactic body radiotherapy (SBRT) is used for inoperable cases. However, radiation-induced liver disease (RILD) remains a major risk, particularly in fibrotic livers. This study established rat models of RILD with and without preexisting fibrosis to evaluate the effects of radiation-fibrosis on liver damage.
Experimental design: Male Sprague-Dawley rats were divided into radiation therapy (RT) (n = 41; 25 Gy right liver irradiation) and thioacetamide (TAA)+RT (n = 46; 6-week TAA-induced fibrosis + 20 Gy RT) groups. Pathological assessments (Hematoxylin and Eosin, Masson's Trichrome, Picro-Sirius Red, and TGF-β/α-SMA immunohistochemistry) were performed at 2, 4, 8, and 12 weeks post-RT to quantify fibrosis, collagen, inflammation, and ballooning degeneration. Statistical analyses included independent sample t-tests, Mann-Whitney U tests, and one-way ANOVA, with p < 0.05 considered significant.
Results: The RT group exhibited mild edema (2–12 weeks), mild ballooning degeneration (4–12 weeks), and minimal inflammation (2–12 weeks). Collagen deposition and TGF-β expression increased significantly at 8–12 weeks (p < 0.05), whereas α-SMA remained mildly elevated at 4–12 weeks (p > 0.05). The TAA+RT group showed mild/severe ballooning degeneration, moderate inflammation, and markedly higher collagen/fibrosis compared with the RT group (p < 0.05). Both TGF-β and α-SMA increased progressively in the TAA+RT group, peaking at 12 weeks (p < 0.05).
Conclusions: Radiation combined with preexisting fibrosis exacerbates hepatic damage and stellate cell activation. This study provides validated RILD models for translational research and highlights the need for cautious radiation dose selection in patients with fibrosis to mitigate the risk of liver injury.
Background: Pulmonary ventilation–perfusion function plays a crucial role in both radiotherapy planning and prognosis assessment in patients with lung cancer. However, there remains a lack of rapid and cost-effective imaging modalities capable of accurately capturing this functional parameter.
Purpose: This study aimed to develop a lung functional image that reflects ventilation–perfusion characteristics by integrating computed tomography (CT) and (positron emission tomography) PET imaging techniques, with the objective of enhancing lung dose evaluation in radiotherapy planning.
Approach: A retrospective analysis was performed on twenty lung cancer patients using CT images acquired at two respiratory phases and FDG-PET/CT images. The Elastic Distortion algorithm was applied for deformable image registration, with the end-expiration phase CT serving as the baseline. Values derived from the determinant Jacobian matrices of ventilation CT (V-CT) images and the gray-value matrices of PET images were normalized to a range of 0 to 1. These normalized values were multiplied to generate a ventilation–perfusion matrix. Three types of lung functional images were produced from these matrices: ventilation-imaging (V-imaging), perfusion-imaging (P-imaging), and ventilation–perfusion- imaging (VP-imaging). The Dice Similarity Coefficient (DSC) and Bland–Altman plots were used to assess the correlations and discrepancies among the imaging modalities.
Results: The DSC values for the entire lung, regions with low 30% functionality, and regions with high 40% functionality were 0.39 ± 0.05, 0.50 ± 0.03, and 0.20 ± 0.05 for V–P; 0.58 ± 0.03, 0.73 ± 0.03, and 0.32 ± 0.02 for V–VP; and 0.68 ± 0.04, 0.78 ± 0.04, and 0.34 ± 0.04 for P–VP, respectively. Notably, significant concordance was observed between V–VP and P–VP images within the delineated functional lung regions.#x02013;Altman analysis supported the DSC results, revealing high correlation coefficients in the low 30% functional lung region: 0.628 for V–P, 0.857 for V–VP, and 0.779 for P–VP. In contrast, similarity within the high 40% functional regions was markedly lower.
Conclusion: This study developed a novel method for generating a fused VP map by integrating CT-derived ventilation and FDG-PET data. The method demonstrated feasibility, and the resulting VP map provided a balanced representation of both ventilation and perfusion signals, particularly in regions with reduced lung function.
Problem: The clinical feasibility, dosimetric reproducibility, and in vivo accuracy of a tomotherapy-based total-body irradiation (TBI) protocol in a large cohort of patients undergoing hematopoietic stem cell transplantation (HSCT) is evaluated.
Methods: Patients (128 patients with hematological malignancies undergoing TBI with helical tomotherapy) were simulated in dual orientations (head-first and feet-first supine) to accommodate extended anatomical lengths. Plans were generated as separate upper and lower components with structured gradient overlap zones and then composited for delivery. Quality assurance included an ArcCHECK 3D diode array for patient-specific gamma analysis (3%/3 mm criteria), point-dose verification, and in vivo dosimetry. The gamma pass rates, regional dose deviations, and Pearson correlation coefficients were analyzed. Statistical evaluation was performed using the Shapiro–Wilk test, Levene's test, and ANOVA.
Results: All treatment plans met the institutional constraints for planning target volume (PTV) coverage and organs at risk sparing. The mean D95% of the PTV consistently exceeded 95% of the prescribed dose, ensuring robust target coverage. This reflects excellent conformity with the planned dose distribution. Region-wise gamma pass rates exceeded 97% in all areas except junctions, where rates were slightly lower owing to dose gradients. The point-dose agreement showed tight clustering within the ±3% range, with the pelvis exhibiting the most significant positive shift. The in vivo optically stimulated luminescence dosimeter dose remained within the clinically acceptable range of 0.8–1.2 Gy. A strong interregional correlation (r > 0.90) was observed, confirming reproducibility. ANOVA identified statistically significant but clinically acceptable regional dose variations (p = 0.030).
Conclusion: Tomotherapy-based TBI demonstrated high dosimetric precision, reproducibility, and workflow efficiency. This protocol offers a clinically reliable approach for modern TBI delivery in transplant conditioning.
Neoadjuvant chemoradiotherapy (nCRT) followed by total mesorectal excision is standard treatment for locally advanced rectal cancer (LARC). This approach allows a subset of patients to achieve a pathological complete response (pCR), thereby improving surgical outcomes, anal preservation rates, and disease-free survival. An accurate preoperative assessment of pCR is crucial for guiding treatment decisions. Magnetic resonance imaging (MRI), owing to its superior soft-tissue contrast and spatial resolution, has become the preferred noninvasive modality for assessing nCRT efficacy. Advances in functional MRI (fMRI) techniques include diffusion-weighted imaging, derived sequences, perfusion-weighted imaging, and neuro-fMRI. fMRI sequences provide not only a qualitative assessment but also quantitative parameters derived from various imaging principles, thereby significantly enhancing the clinical utility of MRI. Beyond conventional and functional MRI, this field is rapidly evolving with the integration of radiomics and deep learning approaches. Radiomics involves the high-throughput extraction of minimal quantitative features from medical images, which can reveal tumor heterogeneity and phenotypic characteristics that are invisible to the human eye. This review summarizes current research and future perspectives on MRI-based qualitative, quantitative, radiomic, and deep-learning approaches for assessing nCRT efficacy in patients with LARC.