Radiotherapy and Oncology最新文献

Background and purpose

Treatment modalities for patients with brain metastases consist of surgery, radiotherapy, and systemic treatments such as immunotherapy and targeted therapy. Although much is known about local control of brain metastases after radiotherapy and surgery alone, more understanding is needed of the additional effect of new systemic treatments. Our study presents real-world data about the combined effects of different local and systemic treatment strategies on local response of irradiated brain metastases.

Materials and methods

We performed a retrospective consecutive cohort study of patients that presented with brain metastases in our institution between June 2018 and May 2020, reporting the impact of radiotherapy alone versus radiotherapy combined with systemic treatment on local control of irradiated brain metastases and toxicity. Chemotherapy and targeted therapy were temporarily discontinued around irradiation.

Results

262 consecutively treated patients were included in the study. Median time to local failure of irradiated brain metastases was 18 months (IQR 9–34), median overall survival was 20 months (IQR 10–36). 211 (81 %) patients received systemic treatment. Patients with breast cancer had a worse local control (HR 2.3, 95 % CI 1.0–5.0, p = 0.038), as did patients without any systemic treatment (HR 2.1, 95 % CI 1.1–4.3, p = 0.034). Symptomatic radiation necrosis occurred in 36 (14 %) patients. A diameter > 2.5 cm was associated with a higher risk of radiation necrosis. No association was found between systemic treatment in combination with local radiotherapy and symptomatic radiation necrosis.

Conclusion

Patients who received any form of systemic treatment had better local control after stereotactic radiosurgery for brain metastases. We did not find an association between systemic treatment and the incidence of radiation necrosis.

Background and purpose

Our goal was to develop a workflow to automatically evaluate delivered dose on daily cone beam computed tomography (CBCT) in all breast cancer patients to assess dosimetric impact of anatomical changes and guide decision-making for offline plan adaptation.

Materials and methods

The workflow automatically processes the daily CBCTs of all breast cancer patients receiving local and locoregional radiotherapy. The planning-CT is registered to the CBCT to create a synthetic CT and propagate contours. A forward dose calculation is performed, and DVH parameters are extracted and printed in a report. We evaluated the workflow on a group level and in a subset of 30 patients on a patient-specific level, including comparison to clinical evaluation on additional planning-CT in 10 patients.

Results

7454 fractions in 647 patients were analyzed over a period of seven months. Median breast clinical target volume V95% was ≥ 95 % for 97 % of the patients. The workflow would have provided useful additional insights for decision-making for the requirement of plan adaptation, based on debatable disagreement with the clinical decision in half of the cases with an additional planning-CT. The workflow also identified cases with suboptimal coverage not identified in the clinical procedure.

Conclusion

We developed a fully automated workflow for dose evaluation on daily CBCT for local and locoregional breast radiotherapy. We have demonstrated its potential for aiding decision-making for plan adaptation in patients with changing anatomy and its capability to highlight patients that may receive suboptimal treatment and require closer clinical evaluation of treatment quality.

Oral cancer remains a significant global health concern and its early detection plays a crucial role in improving patient outcomes. Identifying reliable prognostic markers is essential to guide treatment decisions and enhance survival rates. Fructose 1,6-bisphosphate aldolase (FBA), a glycolytic enzyme, has emerged as a promising candidate for prognostic assessment of oral cancer. This review highlights the role of FBA in tumorigenesis, its potential utility in predicting disease progression and patient survival, and its influence on response to radiotherapy. Recent studies have suggested that dysregulated metabolic pathways involving FBA may contribute to radiation resistance in oral cancer, emphasizing the need for further exploration of FBA-targeted therapeutic strategies. Understanding the role of FBA in oral cancer pathogenesis could pave the way for the development of personalized treatment strategies, including combined radiotherapy.

Background and purpose

Overcoming radioresistance is a critical challenge in pancreatic ductal adenocarcinoma (PDAC). Our study investigates the targeting of Cyclin-dependent kinase-1 (CDK1) through genetic and pharmaceutical inhibition to radiosensitize PDAC cells.

Materials and Methods

Mass spectrometry and phosphoproteomics were used to analyze engineered radiation-resistant PDAC cell lines (MIA PaCa-2 and PANC-1) compared to parental controls. The TCGA PDAC database was queried for clinical outcomes and patients were dichotomized based on the median CDK1 mRNA expression. We generated a microRNA-based TET-on inducible shRNA to inhibit CDK1 expression in two PDAC cell lines. We used an orthotopic model of PDAC to test the radiation sensitivity of PDAC tumors with or without doxycycline treatment. We targeted CDK1 activation with a selective CDK1 inhibitor, RO-3306, followed by in vitro experiments employing immunoblotting, immunocytochemistry, and clonogenic assays.

Results

Phosphoproteomics analysis revealed that phospho-CDK1 (Tyr15) was significantly elevated in the resistant clones. We found that high CDK1 expression was associated with worse OS in PDAC patients. Radiation exposure increased CDK1 phosphorylation. In MIA PaCa-2 and PANC-1 cells, CDK1 inhibition synergized with radiation therapy to delay tumor growth in vivo. CDK1 inhibition via. RO-3306 resulted in a significant shift of cells into the G2/M phase and disrupted DNA repair after radiation exposure. In vitro, pre-treatment with RO-3306 led to enhanced radiosensitivity of PDAC cells.

Conclusion

CDK1 plays a crucial role in PDAC radioresistance. Targeting CDK1 with radiotherapy holds promise for further investigation in PDAC treatment.

Background

Patients with rectal cancer are often treated with neoadjuvant chemoradiotherapy, followed by a waiting period and surgical resection. Good or complete response to neoadjuvant chemoradiotherapy might enable organ preservation, which highlights the need to increase response rates. Pre-clinical studies suggest that physical activity during neoadjuvant chemoradiotherapy may improve tumor downstaging.

Purpose

To investigate whether physical activity and physical functioning of patients with rectal cancer at diagnosis are associated with tumor downstaging after neoadjuvant chemoradiotherapy.

Materials and methods

Patients were included if they participated in the Dutch Prospective ColoRectal Cancer Cohort, a nationwide cohort providing an infrastructure for scientific research, and received neoadjuvant chemoradiotherapy for rectal cancer. Tumor downstaging was dichotomized into good/complete or moderate/poor downstaging. Physical activity (total physical activity, moderate-to-vigorous physical activity (MVPA), and Dutch physical activity guideline adherence) and physical functioning were assessed using questionnaires. Logistic regression analyses were performed to examine associations of physical activity and physical functioning with tumor downstaging, adjusted for relevant confounders.

Results

268 patients (aged 62 ± 11 years, 33 % female) with rectal cancer were included. Patients with moderate (OR = 2.07; 95%CI = 1.07 – 4.07; p = 0.03) or high (OR = 2.05; 95%CI = 1.05 – 4.07; p = 0.04) levels of MVPA were more likely to have good/complete tumor downstaging than patients with low levels. No significant associations with tumor downstaging were found for total physical activity, Dutch physical activity guideline adherence, and physical functioning.

Conclusions

We found augmented tumor downstaging in patients with rectal cancer with moderate or high levels of self-reported MVPA before the start of neoadjuvant chemoradiotherapy compared to patients with low levels.

Background and objectives

The aim of this study is to establish dosimetric constraints for the brachial plexus at risk of developing grade ≥ 2 brachial plexopathy in the context of stereotactic body radiation therapy (SBRT).

Patients and Methods

Individual patient data from 349 patients with 356 apical lung malignancies who underwent SBRT were extracted from 5 articles. The anatomical brachial plexus was delineated following the guidelines provided in the atlases developed by Hall, et al. and Kong, et al.. Patient characteristics, pertinent SBRT dosimetric parameters, and brachial plexopathy grades (according to CTCAE 4.0 or 5.0) were obtained. Normal tissue complication probability (NTCP) models were used to estimate the risk of developing grade ≥ 2 brachial plexopathy through maximum likelihood parameter fitting.

Results

The prescription dose/fractionation schedules for SBRT ranged from 27 to 60 Gy in 1 to 8 fractions. During a follow-up period spanning from 6 to 113 months, 22 patients (6.3 %) developed grade ≥2 brachial plexopathy (4.3 % grade 2, 2.0 % grade 3); the median time to symptoms onset after SBRT was 8 months (ranged, 3–54 months). NTCP models estimated a 10 % risk of grade ≥2 brachial plexopathy with an anatomic brachial plexus maximum dose (D_max) of 20.7 Gy, 34.2 Gy, and 42.7 Gy in one, three, and five fractions, respectively. Similarly, the NTCP model estimates the risks of grade ≥2 brachial plexopathy as 10 % for BED D_max at 192.3 Gy and EQD₂ D_max at 115.4 Gy with an α/β ratio of 3, respectively. Symptom persisted after treatment in nearly half of patients diagnosed with grade ≥2 brachial plexopathy (11/22, 50 %).

Conclusions

This study establishes dosimetric constraints ranging from 20.7 to 42.7 Gy across 1–5 fractions, aimed at mitigating the risk of developing grade ≥2 brachial plexopathy following SBRT. These findings provide valuable guidance for future ablative SBRT in apical lung malignancies.

Purpose

Radioresistance is a significant challenge in the radiotherapy of non-small cell lung cancer (NSCLC). This study aimed to investigate the role of R-spondin 3 (RSPO3) in regulating NSCLC radioresistance.

Methods and Materials

RNA sequencing was performed to analyze genes that are differentially expressed in radioresistant NSCLC cell lines. RSPO3 overexpression and knockdown experiments were conducted to assess its impact on radiosensitivity. The involvement of the β-catenin-NF-κB signaling pathway and the NLRP3 inflammasome in RSPO3-mediated radiosensitivity was also evaluated. In vivo experiments were conducted using a clinical-grade anti-RSPO3 antibody (OMP-131R10/rosmantuzumab) to assess its impact on radiation-induced pyroptosis and subsequent anti-tumor immunity.

Results

RSPO3 expression was downregulated in radioresistant NSCLC cells. Overexpression of RSPO3 increased NSCLC radiosensitivity through the induction of pyroptosis, which was mediated by the β-catenin-NF-κB signaling pathway and the NLRP3 inflammasome. The anti-RSPO3 antibody effectively blocked radiation-induced pyroptosis and anti-tumor immunity in vivo. Conversely, upregulation of RSPO3 enhanced NSCLC tumor radiosensitivity.

Conclusions

The findings demonstrated that RSPO3 plays a crucial role in regulating NSCLC radioresistance via NLRP3 mediated pyroptosis. Targeting the RSPO3-NLRP3 inflammasome axis may offer a potential therapeutic strategy to enhance the efficacy of radiotherapy for NSCLC patients.

Background

To assess the long-term outcome of large brain arteriovenous malformations (AVMs) (volume > 10 ml) underwent combined embolization and stereotactic radiosurgery (E+SRS) versus SRS alone.

Methods

Patients were recruited from a nationwide multicenter prospective collaboration registry (MATCH study, August 2011–August 2021) and categorized into E+SRS and SRS alone cohorts. Propensity score-matched survival analysis was employed to control for potential confounding variables. The primary outcome was a composite event of non-fatal hemorrhagic stroke or death. Secondary outcomes were favorable patient outcomes, AVM obliteration, favorable neurological outcomes, seizure, worsened mRS score, radiation-induced changes (RIC), and embolization complications. Furthermore, the efficacy of distinct embolization strategies was evaluated. Hazard ratios (HRs) were computed utilizing Cox proportional hazard models.

Results

Among 1063 AVMs who underwent SRS with or without prior embolization, 176 patients met the enrollment criteria. Following propensity score matching, the final analysis encompassed 98 patients (49 pairs). Median (interquartile range) follow-up duration for primary outcomes spanned 5.4 (2.7–8.4) years. Overall, the E+SRS strategy demonstrated a trend toward reduced incidence of primary outcomes compared to the SRS alone strategy (1.44 vs 2.37 per 100 patient-years; HR, 0.58 [95 % CI, 0.17–1.93]). Regardless of embolization degree or strategy, stratified analyses further consistently revealed a similar trend, albeit without achieving statistical significance. Secondary outcomes generally exhibited equivalence, but the combined approach showed potential superiority in most measures.

Conclusions

This study suggests a trend toward lower long-term non-fatal hemorrhagic stroke or death risks with the E+SRS strategy when compared to SRS alone in large AVMs (volume > 10 ml).

Background and purpose

Fast and automated generation of treatment plans is desirable for magnetic resonance imaging (MRI)-guided adaptive radiotherapy (MRIgART). This study proposed a novel patient-specific auto-planning method and validated its feasibility in improving the existing online planning workflow.

Materials and methods

Data from 40 patients with prostate cancer were collected retrospectively. A patient-specific auto-planning method was proposed to generate adaptive treatment plans. First, a population dose-prediction model (M₀) was trained using data from previous patients. Second, a patient-specific model (M_ps) was created for each new patient by fine-tuning M₀ with the patient’s data. Finally, an auto plan was optimized using the parameters derived from the predicted dose distribution by M_ps. The auto plans were compared with manual plans in terms of plan quality, efficiency, dosimetric verification, and clinical evaluation.

Results

The auto plans improved target coverage, reduced irradiation to the rectum, and provided comparable protection to other organs-at-risk. Target coverage for the planning target volume (+0.61 %, P = 0.023) and clinical target volume 4000 (+1.60 %, P < 0.001) increased. V_2900cGy (−1.06 %, P = 0.004) and V_1810cGy (−2.49 %, P < 0.001) to the rectal wall and V_1810cGy (−2.82 %, P = 0.012) to the rectum were significantly reduced. The auto plans required less planning time (−3.92 min, P = 0.001), monitor units (−46.48, P = 0.003), and delivery time (−0.26 min, P = 0.004), and their gamma pass rates (3 %/2 mm) were higher (+0.47 %, P = 0.014).

Conclusion

The proposed patient-specific auto-planning method demonstrated a robust level of automation and was able to generate high-quality treatment plans in less time for MRIgART in prostate cancer.

Background and purpose

This study aimed to evaluate the plan quality of our deep learning-based automated treatment planning method for robustly optimized intensity-modulated proton therapy (IMPT) plans in patients with oropharyngeal carcinoma (OPC). The assessment was conducted through a retrospective and prospective study, blindly comparing manual plans with deep learning plans.

Materials and methods

A set of 95 OPC patients was split into training (n = 60), configuration (n = 10), test retrospective study (n = 10), and test prospective study (n = 15). Our deep learning optimization (DLO) method combines IMPT dose prediction using a deep learning model with a robust mimicking optimization algorithm. Dosimetrists manually adjusted the DLO plan for individual patients. In both studies, manual plans and manually adjusted deep learning (mDLO) plans were blindly assessed by a radiation oncologist, a dosimetrist, and a physicist, through visual inspection, clinical goal evaluation, and comparison of normal tissue complication probability values. mDLO plans were completed within an average time of 2.5 h. In comparison, the manual planning process typically took around 2 days.

Results

In the retrospective study, in 10/10 (100%) patients, the mDLO plans were preferred, while in the prospective study, 9 out of 15 (60%) mDLO plans were preferred. In 4 out of the remaining 6 cases, the manual and mDLO plans were considered comparable in quality. Differences between manual and mDLO plans were limited.

Conclusion

This study showed a high preference for mDLO plans over manual IMPT plans, with 92% of cases considering mDLO plans comparable or superior in quality for OPC patients.