Radiation Oncology最新文献

Background: Brain metastases are common complications in patients with cancer and significantly affect prognosis and treatment strategies. The accurate segmentation of brain metastases is crucial for effective radiation therapy planning. However, in resource-limited areas, the unavailability of MRI imaging is a significant challenge that necessitates the development of reliable segmentation models for computed tomography images (CT).

Purpose: This study aimed to develop and evaluate a Diffusion-CSPAM-U-Net model for the segmentation of brain metastases on CT images and thereby provide a robust tool for radiation oncologists in regions where magnetic resonance imaging (MRI) is not accessible.

Methods: The proposed Diffusion-CSPAM-U-Net model integrates diffusion models with channel-spatial-positional attention mechanisms to enhance the segmentation performance. The model was trained and validated on a dataset consisting of CT images from two centers (n = 205) and (n = 45). Performance metrics, including the Dice similarity coefficient (DSC), intersection over union (IoU), accuracy, sensitivity, and specificity, were calculated. Additionally, this study compared models proposed for brain metastases of different sizes with those proposed in other studies.

Results: The diffusion-CSPAM-U-Net model achieved promising results on the external validation set. Overall average DSC of 79.3% ± 13.3%, IoU of 69.2% ± 13.3%, accuracy of 95.5% ± 11.8%, sensitivity of 80.3% ± 12.1%, specificity of 93.8% ± 14.0%, and HD of 5.606 ± 0.990 mm were measured. These results demonstrate favorable improvements over existing models.

Conclusions: The diffusion-CSPAM-U-Net model showed promising results in segmenting brain metastases in CT images, particularly in terms of sensitivity and accuracy. The proposed diffusion-CSPAM-U-Net model provides an effective tool for radiation oncologists for the segmentation of brain metastases in CT images.

Mathematical modeling has long been a cornerstone of radiotherapy for cancer, guiding treatment prescription, planning, and delivery through versatile applications. As we enter the era of medical big data, where the integration of molecular, imaging, and clinical data at both the tumor and patient levels could promise more precise and personalized cancer treatment, the role of mathematical modeling has become even more critical. This comprehensive narrative review aims to summarize the main applications of mathematical modeling in radiotherapy, bridging the gap between classical models and the latest advancements. The review covers a wide range of applications, including radiobiology, clinical workflows, stereotactic radiosurgery/stereotactic body radiotherapy (SRS/SBRT), spatially fractionated radiotherapy (SFRT), FLASH radiotherapy (FLASH-RT), immune-radiotherapy, and the emerging concept of radiotherapy digital twins. Each of these areas is explored in depth, with a particular focus on how newer trends and innovations are shaping the future of radiation cancer treatment. By examining these diverse applications, this review provides a comprehensive overview of the current state of mathematical modeling in radiotherapy. It also highlights the growing importance of these models in the context of personalized medicine and multi-scale, multi-modal data integration, offering insights into how they can be leveraged to enhance treatment precision and patient outcomes. As radiotherapy continues to evolve, the insights gained from this review will help guide future research and clinical practice, ensuring that mathematical modeling continues to propel innovations in radiation cancer treatment.

Background: This study reports the single-institution clinical experience of multifield pencil beam scanning (PBS) intensity-modulated proton therapy (IMPT) and dosimetric comparison to proton arc for uveal melanoma (UM) in a regular PBS gantry room.

Methods: Eleven consecutive UM patients were treated with IMPT to 50 Gy in 5 fractions. A customized gaze-fixation device attached to the thermoplastic mask was used to reproduce the globe position for each patient. IMPT plans were robustly optimized with perturbations of 3 mm setup and 3.5% range uncertainties using 3-4 fields without apertures. Each plan was robustly reoptimized (using the same perturbation parameters) using two non-coplanar arc fields in the RayStation treatment planning system. Treatment quality for both plans was evaluated daily using CBCT-generated synthetic CT. Target coverage, conformity, and mean/maximum doses to adjacent organs were assessed.

Results: Proton arc plans provided comparable plan quality compared to IMPT plans. Similar target coverage was achieved, with an average GTV D95% equal to 101.1% [Formula: see text] 1.0% and 101.4% [Formula: see text] 0.4% for IMPT and proton arc plans, respectively. Proton arc improves the conformity index (RTOG) compared to IMPT plans (average 0.96 [Formula: see text] 0.23 vs. 0.88 [Formula: see text] 0.18, p = 0.11). Both modalities met all the clinical goals for organs-at-risk (OARs), while proton arc significantly reduced the maximum dose for the retina from, on average, 54.5 [Formula: see text] 0.7 to 53.2 [Formula: see text] 0.3 Gy (p < 0.01). Treatment evaluation on synthetic CT showed that the doses received by patients were highly consistent with the planned doses, with a relative target coverage (D95%) difference within 3.5% for IMPT and 3.1% for proton arc, and the D95% of actual delivery exceeding 98.7% and 98.2%, respectively. The doses delivered to OARs did not exceed clinical constraints.

Conclusions: This is a novel report on proton arc for ocular tumors and gantry-based multifield PBS proton treatment for these tumors. This study demonstrated that both modalities can meet the clinical goals. The IMPT is currently clinically implanted, and 2-field non-coplanar proton arc plans can achieve comparable dosimetric metrics to those of IMPT plans when the deliver technique is matured.

Background: This study aimed to identify key risk factors in locally advanced cervical cancer (LACC) patients receiving radical radiotherapy and to evaluate the prognostic significance of MRI-determined tumor volume regression (TVR) among varying risk groups.

Methods: We retrospectively analyzed a cohort of 176 cervical cancer patients (stages IIA-IVA) treated with intensity-modulated radiotherapy from January 2012 to December 2020. Three-dimensional MRI scans were utilized to measure TVR and lymph node volume regression (NVR). Kaplan-Meier analysis was employed to assess overall survival (OS), progression-free survival (PFS), local relapse-free survival (LRFS), and distant metastasis-free survival (DMFS). Prognostic factors were further analyzed using Cox proportional hazards models.

Results: A tumor TVR of ≥ 94% was significantly associated with improved 5-year overall survival (OS; 82.7% vs. 49.8%, p < 0.001) and progression-free survival (PFS; 82.5% vs. 51.1%, p < 0.001). Patients with TVR ≥ 94% also demonstrated superior LRFS and DMFS compared to those with TVR < 94% (p < 0.001 and p = 0.012, respectively). In the concurrent chemoradiotherapy (CCRT) subgroup, higher TVR correlated with better prognosis, whereas in patients receiving radiotherapy alone, an increased TVR did not significantly impact OS. Notably, the prognostic value of TVR was most evident in patients with CYFRA21-1 levels below 7.7 ng/ml. In the NVR ≥ 94% subgroup, OS, PFS, and LRFS were significantly better than in patients with NVR < 94% (p < 0.01), with a trend towards improved DMFS observed (p = 0.138).

Conclusion: TVR serves as a pivotal prognostic marker in LACC patients with CYFRA21-1 levels below 7.7 ng/ml undergoing CCRT. Additionally, within the lymph node metastasis subgroup, patients achieving a NVR of ≥ 94% demonstrated a notably improved prognosis.

Background: There is a substantial body of literature addressing the prevention, acute management, and follow-up care of radiation induced dermatitis (RID). The quality and application of this evidence, however, is inconsistent and its interpretation varies widely. While several national guidelines have been developed to standardise practices locally, many of these resources are not publicly available. On behalf of the European Society for Radiotherapy and Oncology (ESTRO) Radiation Therapist (RTT) Committee, an international writing group consisting of 12 experts from radiotherapy and two patient representatives composed a recommendation document for the management of RID.

Main body: The consensus for these recommendations was generated based on available international guidelines, and supplemented with evidence-based review articles on the topic. These recommendations focus on the prevention and practical management of early stage RID by avoiding skin trauma and maintaining hygiene. Addressing pain and inflammation in higher grades is also covered. The current literature refutes some of the traditional recommendations, especially restricting washing as well as the use of deodorant or the potential dose build-up of lotions which has been included and rectified in recent guidelines. In addition, the importance of grading the severity, including a baseline assessment is presented. The benefit of clear, and non-contradictory communication within the multidisciplinary team as well as patient involvement (e.g. PROMs or similar) is highlighted. Furthermore, the importance of recognising different skin types and skin tones, and the impact on how RID changes these in their appearance is stressed.

Conclusion: This document provides practical, actionable recommendations for the clinical management of RID, referencing the supporting literature. These recommendations have, however, identified a lack of high-level evidence, especially for agent-specific recommendations.

Objective: To evaluate the impact of smoking on acute and chronic toxicity in early breast cancer patients treated with hypofractionated intensity-modulated radiation therapy (IMRT) and a brachytherapy boost following breast-conserving surgery.

Methods: A retrospective study of 638 patients treated between 2009 and 2017, with 566 having recorded smoking status. Acute toxicity was assessed at treatment end and chronic toxicity at least one-year post-treatment, using Common Terminology Criteria for Adverse Events v4.0. Statistical analyses included chi-square tests and relative risk (RR) calculations.

Results: A total of 566 patients were included in the study, with 31.3% being smokers. The cohort was followed for a median of 6 years (range: 1-11 years). Acute toxicity was primarily characterized by radiodermatitis, with 87.6% of patients developing grade 1 and 5.5% experiencing grade 2. No cases of grade ≥ 3 were observed, and 6.9% of patients did not experience radiodermatitis. Bleeding was rare (1.1%) and infections occurred in 2.0% of patients. Regarding chronic toxicity, 67.1% of patients had no fibrosis, while 27.4% had grade 1 fibrosis. Grade 2 and grade 3 fibrosis were observed in 4.9% and 0.6% of patients, respectively, with no cases of grade 4 fibrosis. Edema was present in 8.0%, and 4.4% of patients reported chronic pain. When comparing smokers and nonsmokers, acute toxicity incidence, particularly radiodermatitis, was similar between the two groups. Smokers had a significantly higher incidence of chronic fibrosis (35.6% vs. 24.7%, p = 0.013) and chronic pain (7.9% vs. 3.3%, p = 0.024) compared to nonsmokers. However, there were no significant differences in the occurrence of edema between smokers and nonsmokers (7.9% vs. 8.0%, p = 0.879).

Conclusion: While advanced radiation techniques such as hypofractionated IMRT improve overall toxicity profiles, smoking significantly exacerbates chronic toxicity in breast cancer patients. This study underscores the urgent need for comprehensive smoking cessation programs as part of cancer care, addressing lifestyle factors to improve patient outcomes and quality of life.

Background and purpose: To explore the feasibility and advantages of the visualized thermosensitive color-changing personalized bolus in post-mastectomy radiotherapy (PMRT).

Materials and methods: Forty PMRT patients (June 2023-June 2024) were randomized into two groups. Group A (experimental group, 20 patients) underwent two CT scans: A₁ (without compensator) and A₂ (with the visualized thermosensitive color-changing personalized bolus), followed by treatment with the thermosensitive color-changing personalized bolus. Group B (control group, 20 patients) also underwent two CT scans: B₁ (without bolus) and B₂ (with a conventional commercial bolus), followed by treatment with the commercial bolus. Treatment plans were generated for virtual bolus (A₁-Plan, B₁-Plan) and real bolus (A₂-Plan, B₂-Plan). A₃-Plan (A₁-Plan applied to thermosensitive bolus treatment) and B₂-Plan (B₁-Plan applied to commercial bolus treatment) were compared to evaluate dosimetric differences in target volumes, organs at risk (OARs), and skin toxicity.

Results: In Group A, A₁-Plan and A₂-Plan showed no significant differences in OAR doses (e.g., ipsilateral lung, heart, contralateral breast, skin D_max/D_mean) or target metrics (V_50Gy, D_max, homogeneity index (HI), conformity index (CI), monitor units (MU)). A₃-Plan compared to A₁-Plan had minor differences in target coverage (94.05% vs. 95.14%), HI (0.148 vs. 0.147), and CI (0.83 vs. 0.84). In Group B, B₂-Plan had significantly reduced target coverage (89.9% vs. 95%), homogeneity (0.153 vs. 0.136), and conformity (0.817 vs. 0.810) compared to B₁-Plan, attributed to air gaps from the commercial bolus. The thermosensitive color-changing personalized bolus had better skin adherence, significantly reduced air cavity volumes (3833 mm³ vs. 21498 mm³), and maintained equivalent dosimetric performance to virtual boluses. Skin toxicity was Grade I in all patients without differences between groups.

Conclusions: The visualized thermosensitive color-changing personalized bolus demonstrated superior skin adherence, smaller air gaps, and better positional reproducibility compared to commercial boluses. Its dosimetric performance was consistent with virtual bolus plans, ensuring target coverage and OAR protection without increased skin toxicity. These findings support its clinical application in PMRT.

Background: Patients with synchronous metastatic nasopharyngeal carcinoma (smNPC) exhibit significant heterogeneity, and clinical prognostic models suitable for this cohort remain limited. We aimed to develop a prognostic prediction tool to facilitate personalised prognostic assessments and inform treatment decisions for these patients.

Methods: This retrospective multicentre study enrolled 556 patients with smNPC. The training cohort comprised 386 patients from Guangxi Medical University Cancer Hospital, while the external validation cohort comprised 170 patients from Wuzhou Red Cross Hospital and Xiangtan Central Hospital. We applied the Cox proportional hazards model to determine factors associated with overall survival (OS). A nomogram prognostic model was developed to predict OS based on the identified prognostic factors. The model's predictive performance was evaluated for discrimination and calibration, and patients were stratified based on their calculated prognostic risk scores. Kaplan-Meier survival curves were employed to assess prognostic differences across the stratified groups.

Results: Multivariate analysis identified that M classification, primary tumour radiotherapy, and immunotherapy were significantly associated with OS. A prognostic nomogram integrating these variables exhibited good discrimination (C-index: 0.743) and calibration, which was validated in an external validation cohort. Patients stratified by the model-derived risk scores into high- and low-risk groups showed a significant difference in survival disparity.

Conclusions: We established a nomogram prognostic model that effectively facilitated individualised prognostic prediction and risk stratification in patients with smNPC, thereby assisting clinicians in treatment decision-making.

Background: We explored the dynamic changes of major leukocyte subsets during definitive treatment of patients with inoperable stage II/III NSCLC lung cancer and correlated it to survival to identify subpopulations associated with maximal patient benefit.

Methods: We analyzed peripheral blood of 20 patients, either treated with thoracic radiotherapy (RT), concurrent chemo-radiotherapy (cCRT), or cCRT with additional immune-checkpoint inhibition therapy. Peripheral blood of 20 patients was collected at 9 timepoints before, during, and up to 1 year post treatment and analyzed by multi-color flow cytometry. Statistical analysis was conducted for leukocyte subpopulations, IL-6, progression-free survival (PFS) and overall survival (OS).

Results: Increase of absolute lymphocyte counts (ALC) after the end of RT until 6 months thereafter was a predictor of PFS. Baseline lymphocyte counts showed no significant correlation to PFS or OS. Early recovery of absolute counts (AC) at 3 weeks after RT, total CD3 + T-cells, and CD8 + cytotoxic T-cells distinguished those patients with favorable PFS (≥ 12 months) from all other patients. Discriminant analysis identified B-cells, neutrophil-lymphocyte-ratio (NLR), CD4 + T-helper-cells, and NK-cells as predictors of favorable PFS. High variability in IL-6 plasma concentration of consecutive measurements within 6 months after the end of RT correlated negatively with PFS.

Conclusion: Our results suggest that two parameters commonly assessed in clinical routine can be used to predict patient outcome. These are: early increase in CD8 + T-cell lymphocyte count and variability in IL-6 plasma concentration, that are correlated to patients with favorable, respectively, poor outcome after definitive therapy independent of treatment regimen.

Background: To assess the rate and predictors of lower extremity lymphedema (LEL) after radiotherapy (RT) following radical prostatectomy (RP) ± pelvic lymph node dissection (PLND) for prostate cancer.

Methods: Patients (pts) treated with adjuvant or salvage RT after RP ± PLND and a minimum 2-year follow-up were included. LEL was defined as a volume difference ≥ 10% between limbs evaluated using circumferential measurements with a flexible non-stretch tape. The following predictors were investigated at logistic regression: age (continuous); body mass index (BMI, continuous); exercise level (low vs. medium/high); smoking (yes vs. no); cigarette pack/year (continuous); hypertension (yes ns no); vascular comorbidity (yes vs. no); diabetes (yes vs. no); PLND (yes vs. no); number of examined nodes (continuous); whole pelvis radiotherapy (WPRT) (yes vs. no); time between RP and RT (continuous); planning target volume (PTV) volume (continuous); PTV/BMI (continuous). Statistical significance was claimed for p < 0.05.

Results: 101 pts were examined. The median time from surgery to RT was 36.1 months (mths) (IQR: 15.0-68.3), the median time from RT to the date of study examination was 51.1 months (IQR: 36.8-65.3). 14 pts developed LEL (13.9%), 3 pts (2.9%) before RT, 11 pts (10.8%) after RT. The median time from RT to LEL was 4 mths (IQR: 0.5-17.3). At multivariable analysis (MVA) diabetes mellitus (DM) (OR = 32.8, p = 0.02), time between surgery and RT (OR = 0.966, p = 0.039) and exercise (OR = 0.03, p = 0.002) were independently correlated to LEL. The number of examined nodes was highly correlated to LEL at univariate analysis (OR = 1.066, p = 0.025) but was not confirmed at MVA (p = 0.719). Interestingly, the distribution of the examined nodes was statistically different between pts with low (median N = 12) vs. medium/high (N = 5) exercise (p = 0.034).

Conclusions: Clinically detectable LEL involves a minority of pts after RT. DM is a predisposing factor, while awaiting RT delivery has a protective effect favoring salvage over adjuvant RT.