Prof. Cai Jing introduces LungRT Pro that enhances lung radiotherapy

Prof. Cai Jing introduces LungRT Pro that enhances lung radiotherapy

Prof. Jing CAI, Management Committee Member of The Research Institute for Smart Ageing, Head and Professor of the Department of Health Technology and Informatics at The Hong Kong Polytechnic University, was recently interviewed by Ta Kung Pao to share his insights on the LungRT Pro: Advanced Radiotherapy Support System, developed by his research team to enhance lung radiotherapy.

In the interview, Prof. Cai explained that LungRT Pro automates the analysis of patient CT images and streamlines clinical procedures. With just a few clicks, the system identifies organs and generates lung ventilation and perfusion maps, providing clinicians with a comprehensive visual representation of lung function. Prof. Cai highlighted that the reliability and safety of AI-assisted systems like LungRT Pro are built on systematic research and clinical validation, with the current system achieving an accuracy rate of 85% to 90%. He emphasized the importance of clinical trial data in verifying the system’s suitability for clinical use, and noted that established quality control measures in radiotherapy ensure the safety and reliability of the system. Prof. Cai also advised that individual patient differences should be considered, and that clinicians should combine their own expertise with the system’s recommendations to ensure optimal treatment plans.

Prof. Cai’s comments shed light on the potential of AI technology to improve clinical efficiency and patient outcomes in lung radiotherapy. This innovation demonstrates PolyU’s commitment to advancing healthcare technology and fostering innovative solutions for the benefit of the community.

Online coverage:
Ta Kung Pao – https://polyu.me/3K9PTsG

理大蔡璟教授團隊研發LungRT Pro 助力提升肺部放射治療

香港理工大學智齡研究院管理委員會成員醫療科技、資訊學系系主任及教授 蔡璟，近日接受《大公報》專訪，分享她和團隊最新研發的「LungRT Pro先進放射治療支援系統」，為肺部放射治療帶來新突破。

蔡教授在訪問中表示，LungRT Pro能自動分析病人的電腦斷層（CT）影像，簡化臨床操作流程。醫護人員只需簡單幾個步驟，系統便能自動識別器官，並生成肺部通氣及灌注圖，讓臨床醫生能夠更全面地掌握病人的肺功能狀況。他指出，這套人工智能輔助系統的可靠性和安全性，來自嚴謹的科學研究和臨床驗證，目前系統的準確率已達85%至90%。蔡教授特別強調，臨床試驗數據對驗證系統的實用性非常重要，而現有的放射治療質量控制措施，也進一步保障了系統的安全性。

同時，蔡教授提醒，臨床應用時要考慮每位病人的個別差異，醫生應結合自身專業判斷和系統建議，為病人制定最合適的治療方案。

蔡教授的分享，讓大家看到人工智能技術在提升肺部放射治療效率和病人治療效果方面的巨大潛力。這項創新成果也展現了理大在推動醫療科技發展、造福社會方面的努力和承諾。

網上報導：
《大公報》- https://polyu.me/3K9PTsG