Precision Radiation Oncology最新文献

Neutropenia is the most common hematological toxicity of concurrent chemoradiotherapy (CCRT), and leads to subsequent treatment delays and/or dose reductions. Neutropenia often advances to febrile neutropenia and serious infections, which can affect the prognosis and safety of patients. The reasonable prevention and management of neutropenia is vital for patients with malignancies undergoing CCRT. Pegylated recombinant human granulocyte colony-stimulating factor (PEG-rhG-CSF), a long-acting recombinant human granulocyte colony-stimulating factor, can prevent and treat neutropenia in more convenient clinical settings. Based on relevant guidelines and the most recent clinical data, the Chinese Association for Therapeutic Radiation Oncologists, China Society for Radiation Oncology, and Chinese Association of Radiation Therapy have evaluated the safety and efficacy of PEG-rhG-CSF during CCRT, clearly defined the clinical pathway and route of administration for the prevention and treatment of neutropenia, and formed a Chinese expert consensus on PEG-rhG-CSF application during CCRT, with the goal of promoting the reasonable clinical use of this treatment.

Purpose: The aim of this study is to quantify the potential benefits of a flattening filter-free (FFF) beam and implement a dose-computation algorithm for cervical radiotherapy through dosimetric and radiobiological analyses using RapidArc.

Methods: Thirty-three patients were enrolled, and four RapidArc plans were created for each patient using a dual-arc flattening filter and 6-MV FFF photon beams for the two calculation algorithms. Homogeneity index (HI), conformity index (CI), target coverage, monitor units (MUs), and organ-at-risk (OAR) dosimetric characteristics were compared between the plans. Radiobiological characteristics and normal tissue complication probability (NTCP) scores were computed for the OAR using different biological models.

Results: No significant differences were observed in the D_max, D_98%, and CI in the planning target volume (PTV). Both computations estimated a significant difference in V_95%, D_2%, and HI for the PTV. Furthermore, the FFF beam showed a significant increase in the MUs and a significant reduction in V_30% for the femoral heads. The NTCP score showed a significant increase in the late effects on the bladder, rectum, and bowel with FFF beams.

Conclusion: The current study recommends FFF beams for better conformity, comparable dose coverage for the target, and OAR sparing invariable to the dose computation algorithm. The difference in the NTCP score for OAR was minimal with the FFF beam.

Purpose: For postoperative vaginal brachytherapy (POVBT), the diversity of applicators complicates the creation of a generalized auto-segmentation model, and creating models for each applicator seems difficult due to the large amount of data required. We construct an auto-segmentation model of POVBT using small data via domain-adversarial neural networks (DANNs).

Methods: CT images were obtained postoperatively from 90 patients with gynaecological cancer who underwent vaginal brachytherapy, including 60 and 30 treated with applicators A and X, respectively. A basal model was devised using data from the patients treated with applicator A; next, a DANN model was constructed using these same 60 patients as well as 10 of those treated with applicator X through transfer learning techniques. The remaining 20 patients treated with applicator X comprised the validation set. The model's performance was assessed using objective metrics and manual clinical evaluation.

Results: The DANN model outperformed the basal model on both objective metrics and subjective evaluation (p<0.05 for all). The median DSC and 95HD values were 0.97 and 3.68 mm in the DANN model versus 0.94 and 5.61 mm in the basal model, respectively. Multi-centre subjective evaluation by three clinicians showed that 99%, 98%, and 81% of CT slices contoured by the DANN model were acceptable versus only 73%, 77%, and 57% of those contoured by the basal model. One clinician deemed the DANN model comparable to manual delineation.

Conclusion: DANNs provides a realistic approach for the wide application of automatic segmentation of POVBT and can potentially be used to construct auto-segmentation models from small datasets.

Small-cell lung cancer (SCLC) is a highly aggressive neuroendocrine tumor that is prone to spread extensively. Compared to non-small-cell lung cancer (NSCLC), SCLC treatment progresses slowly. Although SCLC is highly sensitive to chemotherapy during the initial treatment, most patients still experience resistance and recurrence after receiving chemotherapy. A meta-analysis demonstrated that thoracic radiotherapy (TRT) improves overall survival in SCLC. The results of the CALGB and CONVERT trials provide evidence for the efficacy of once-daily high-dose TRT. TRT at 60 Gy administered twice daily significantly improved survival without increasing toxicity. The long-standing debate over the optimal timing of radiotherapy has not been fully resolved. SBRT has excellent local control rates and is a safe and effective treatment option for patients with stage I or II SCLC. Prophylactic cranial irradiation (PCI) is used to reduce treatment-related neurotoxicity to the extent that there has been a recent discussion on whether magnetic resonance imaging (MRI) monitoring can replace PCI. Radiotherapy combined with immunotherapy significantly improves the survival rate of patients with NSCLC; however, its clinical effectiveness has not been systematically explored in patients with SCLC. Therefore, we summarize the evolving therapeutic strategies, (TRT for limited stage-SCLC and consolidative TRT for extensive stage-SCLC) and improved radiotherapy techniques (role of SBRT in stage I or II node-negative SCLC, progress of PCI, and stereotactic radiosurgery), and discuss the possibilities and prospects of radiotherapy combined with immunotherapy for SCLC.