Dose or treatment planning management is necessary for the re-irradiation of intracranial relapses after focal irradiation, radiosurgery, or stereotactic radiotherapy. The current clinical guidelines for metastatic brain tumors are the use of focal irradiation if the patient presents with 4 lesions or less. Salvage treatments with the use of whole brain radiation therapy (WBRT) can then be used to limit disease progression if there is an intracranial relapse. However, salvage WBRT poses a number of challenges in dose planning to limit disease progression and preserve neurocognitive function. This work presents the dose planning management that addresses a method of delineating previously treated volumes, dose level matching, and the dose delivery techniques for WBRT.
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http://dx.doi.org/10.1016/j.meddos.2016.05.004 | DOI Listing |
Cancer Sci
January 2025
Department of Experimental Therapeutics, National Cancer Center Hospital, Chuo-ku, Japan.
CBA-1205 is a novel humanized antibody targeting delta-like 1 homolog (DLK1) that enhances antibody-dependent cellular cytotoxicity activity. DLK1 overexpression has been reported in various cancer types, such as hepatocellular carcinoma and neuroblastoma. CBA-1205 demonstrates potent antitumor activity in multiple tumor models, making it a potential treatment option for DLK1-expressing cancers.
View Article and Find Full Text PDFTransl Lung Cancer Res
December 2024
Department of Radiation Oncology, Tongji University Affiliated Shanghai Pulmonary Hospital, Shanghai, China.
Background: Stereotactic body radiation therapy (SBRT) is crucial for treating early-stage inoperable non-small cell lung cancer (NSCLC) due to its precision and high-dose delivery. This study aimed to investigate the dosimetric deviations in gated (GR) versus non-gated radiotherapy (NGR), analyzing the impact of tumor location, target volume, and tumor motion range on dose distribution accuracy.
Methods: Sixty patients treated with either gated (n=30) or non-gated (n=30) SBRT for early-stage NSCLC were retrospectively analyzed.
Front Oncol
January 2025
Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
Purpose: Recent deep-learning based synthetic computed tomography (sCT) generation using magnetic resonance (MR) images have shown promising results. However, generating sCT for the abdominal region poses challenges due to the patient motion, including respiration and peristalsis. To address these challenges, this study investigated an unsupervised learning approach using a transformer-based cycle-GAN with structure-preserving loss for abdominal cancer patients.
View Article and Find Full Text PDFFront Oncol
January 2025
Department of Radiation Oncology, Jiangxi Cancer Hospital & Institute, Jiangxi Clinical Research Center for Cancer, The Second Affiliated Hospital of Nanchang Medical College, Nanchang, China.
Objectives: Implementing pre-treatment patient-specific quality assurance (prePSQA) for cancer patients is a necessary but time-consuming task, imposing a significant workload on medical physicists. Currently, the prediction methods used for prePSQA fall under the category of supervised learning, limiting their generalization ability and resulting in poor performance on new data. In the context of this work, the limitation of traditional supervised models was broken by proposing a conditional generation method utilizing unsupervised diffusion model.
View Article and Find Full Text PDFPurpose: Radiation Therapy (RT) can modulate the immune system and generate anti-tumor T cells. However, this anti-tumor-activity is countered by radiation-induced immunosuppression (RIIS). Clinical advantages of proactively sparing RT dose to immune rich organs have not previously been evaluated.
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