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PROJECT TITLE: AUTOMATIC TREATMENT PLANNING OF CERVICAL CANCER HIGH-DOSE RATE BRACHYTHERAPY FOR LOW-RESOURCE SETTINGS

PROJECT TITLE: AUTOMATIC TREATMENT PLANNING OF CERVICAL CANCER HIGH-DOSE RATE BRACHYTHERAPY FOR LOW-RESOURCE SETTINGS
项目名称:低资源环境下宫颈癌高剂量近距离治疗的自动治疗计划
批准号:
10707838
负责人:
RON LIANG
金额:
$40.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-09-15 至 2023-09-14

项目摘要

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中文摘要
翻译
宫颈癌是全球的一种主要疾病,85%的癌症负担发生在低收入和中等收入国家。治疗标准是高剂量率近距离外束放疗(HDRBT)。在治疗过程中增加近距离放疗可使总生存率提高12%,并减少局部复发。HDRBT治疗计划是一个复杂的过程。在资源匮乏的环境中,近距离放射治疗通常没有足够的专业知识来完成这项任务,这限制了这种有效治疗形式的广泛使用,并显著影响了治疗结果。针对这一问题,UT西南医学中心(UTSW)旗下的VeloxAI公司,与UT西南医学中心的临床专家合作,提出了一期SBIR项目,开发全球首个实现宫颈癌HDRBT全自动治疗计划的软件系统AutoBrachy。我们将追求两个具体目标:第一,开发自动分割工具,严格重构AutoBrachy,为商业化做准备;目标2:在包括中低收入国家在内的多个参与站点实施AutoBrachy,以评估其可行性和优点。我们项目的创新之处在于,它通过使用新颖的计算方法,提高了资源匮乏地区宫颈癌的HDRBT。通过广泛的初步研究和与互补的专业知识和资源的伙伴关系,确保了可交付性。
英文摘要
Cervical cancer is a major disease globally and 85% of the cancer burden occurs in low- and middle-income countries (LMICs). Standard of care is external-beam radiotherapy with high dose-rate brachytherapy (HDRBT). Adding brachytherapy to the treatment course improves overall survival by 12% and reduces local recurrence. HDRBT treatment planning is a complex process. Brachytherapy in low-resource settings often do not have adequate human expertise for this task, limiting the wide-spread use of this effective therapeutic form and significantly affecting treatment outcomes. Aiming at solving this problem, VeloxAI, a spin-off of UT Southwestern Medical Center (UTSW), proposes a Phase-I SBIR project in collaboration with clinical experts at UTSW to develop AutoBrachy, the world first software system to realize fully automatic treatment planning of cervical cancer HDRBT. We will pursue two specific aims: Aim1, to develop automatic segmentation tools and rigorously refactor AutoBrachy to plan for commercialization; Aim2, to implement AutoBrachy at multiple participating sites, including those in LMICs, to evaluate its feasibility and merit. The innovation of our project is that it enhances HDRBT of cervical cancer in low-resource settings by utilizing novel computational approaches. Deliverability is ensured by extensive preliminary studies and the partnership with complementary expertise and resources.
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