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解决放射肿瘤学领域的全球专业知识差距:放射计划助手。

Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant.

机构信息

The University of Texas MD Anderson Cancer Center, Houston, TX.

Guy's and St Thomas' Hospital, London, United Kingdom.

出版信息

JCO Glob Oncol. 2023 Jul;9:e2200431. doi: 10.1200/GO.22.00431.

DOI:10.1200/GO.22.00431
PMID:37471671
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10581646/
Abstract

PURPOSE

Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access).

DESIGN

In this review, we discuss the development of the RPA, with a particular focus on clinical acceptability and safety/risk across jurisdictions as these are important indicators for the successful future deployment of the RPA to increase radiotherapy availability and ameliorate global disparities in access to radiation oncology.

RESULTS

RPA tools will be offered through a webpage, where users can upload computed tomography data sets and download automatically generated contours and treatment plans. All interfaces have been designed to maximize ease of use and minimize risk. The current version of the RPA includes automated contouring and planning for head and neck cancer, cervical cancer, breast cancer, and metastases to the brain.

CONCLUSION

The RPA has been designed to bring high-quality treatment planning to more patients across the world, and it may encourage greater investment in treatment devices and other aspects of cancer treatment.

摘要

目的

自动化,包括人工智能的使用,已被确定为缩小放疗和癌症护理其他方面的获取和质量差距的一个潜在机会。放射计划助手(RPA)项目于 2015 年(并于 2016 年获得资助)构想,旨在使用自动化轮廓和治疗计划算法来支持中低收入国家肿瘤学家的工作,使他们能够扩大工作规模,更安全、更有效地治疗更多患者(以增加可及性)。

设计

在这篇综述中,我们讨论了 RPA 的开发,特别关注跨司法管辖区的临床可接受性和安全性/风险,因为这些是成功未来部署 RPA 以增加放疗可及性和改善全球放疗获取差距的重要指标。

结果

RPA 工具将通过网页提供,用户可以在该网页上上传计算机断层扫描数据集,并下载自动生成的轮廓和治疗计划。所有接口都经过精心设计,以最大限度地提高易用性并最小化风险。目前的 RPA 版本包括对头颈癌、宫颈癌、乳腺癌和脑转移的自动轮廓和规划。

结论

RPA 的设计目的是为全世界更多的患者提供高质量的治疗计划,并可能鼓励对治疗设备和癌症治疗的其他方面进行更多投资。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4871/10581646/99a46f6a62ad/go-9-e2200431-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4871/10581646/5bd781150c26/go-9-e2200431-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4871/10581646/241577bc919c/go-9-e2200431-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4871/10581646/abb523ed2297/go-9-e2200431-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4871/10581646/99a46f6a62ad/go-9-e2200431-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4871/10581646/5bd781150c26/go-9-e2200431-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4871/10581646/241577bc919c/go-9-e2200431-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4871/10581646/abb523ed2297/go-9-e2200431-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4871/10581646/99a46f6a62ad/go-9-e2200431-g004.jpg

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