详情页 - 四川省肿瘤医院知识库

当前位置：首页 > 详情页

Advances in determining the gross tumor target volume for radiotherapy of brain metastases

文献详情

资源类型：

Pubmed体系：

作者：

机构： [1]Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China. [2]Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.

出处：

DOI：

ISSN：

关键词： brain metastases MRI GTV delineation artificial intelligence

摘要：

Brain metastases (BMs) are the most prevalent intracranial malignant tumors in adults and are the leading cause of mortality attributed to malignant brain diseases. Radiotherapy (RT) plays a critical role in the treatment of BMs, with local RT techniques such as stereotactic radiosurgery (SRS)/stereotactic body radiotherapy (SBRT) showing remarkable therapeutic effectiveness. The precise determination of gross tumor target volume (GTV) is crucial for ensuring the effectiveness of SRS/SBRT. Multimodal imaging techniques such as CT, MRI, and PET are extensively used for the diagnosis of BMs and GTV determination. With the development of functional imaging and artificial intelligence (AI) technology, there are more innovative ways to determine GTV for BMs, which significantly improve the accuracy and efficiency of the determination. This article provides an overview of the progress in GTV determination for RT in BMs.Copyright © 2024 Du, Gong, Liu, Meng and Yin.

基金：

语种：

PubmedID：

中科院(CAS)分区：

出版当年[2024]版：

无

最新[2023]版：

大类 | 3 区医学

小类 | 3 区肿瘤学

第一作者：

第一作者机构： [1]Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China. [2]Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.

通讯作者：

通讯机构： [1]Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China. [2]Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.

推荐引用方式(GB/T 7714)：

APA：

MLA：

相关文献

[1]Artificial intelligence in brachytherapy [2]Modeling of artificial intelligence-based respiratory motion prediction in MRI-guided radiotherapy: a review [3]Artificial intelligence applications in pathological diagnosis of gastric cancer [4]Predicting Rectal Cancer Response to Total Neoadjuvant Treatment Using an Artificial Intelligence Model Based on Magnetic Resonance Imaging and Clinical Data [5]Application of Artificial Intelligence in Oncology [6]Artificial intelligence aids in development of nanomedicines for cancer management [7]Screening Cancer Immunotherapy: When Engineering Approaches Meet Artificial Intelligence. [8]Differentiation between high-grade gliomas and solitary brain metastases based on multidiffusion MRI model quantitative analysis [9]Radiomics: A radiological evidence-based artificial intelligence technique to facilitate personalized precision medicine in hepatocellular carcinoma [10]Artificial Intelligence-Based Psoriasis Severity Assessment: Real-world Study and Application