Chalopin Claire, Nickel Felix, Pfahl Annekatrin, Köhler Hannes, Maktabi Marianne, Thieme René, Sucher Robert, Jansen-Winkeln Boris, Studier-Fischer Alexander, Seidlitz Silvia, Maier-Hein Lena, Neumuth Thomas, Melzer Andreas, Müller-Stich Beat Peter, Gockel Ines
Innovation Center Computer Assisted Surgery, Universität Leipzig, Semmelweisstr. 14, 04103, Leipzig, Deutschland.
Klinik für Allgemein‑, Viszeral- und Transplantationschirurgie, Universitätsklinikum Heidelberg, Heidelberg, Deutschland.
Chirurgie (Heidelb). 2022 Oct;93(10):940-947. doi: 10.1007/s00104-022-01677-w. Epub 2022 Jul 7.
Intraoperative imaging assists surgeons during minimally invasive procedures. Hyperspectral imaging (HSI) is a noninvasive and noncontact optical technique with great diagnostic potential in medicine. The combination with artificial intelligence (AI) approaches to analyze HSI data is called intelligent HSI in this article.
What are the medical applications and advantages of intelligent HSI for minimally invasive visceral surgery?
Within various clinical studies HSI data from multiple in vivo tissue types and oncological resections were acquired using an HSI camera system. Different AI algorithms were evaluated for detection and discrimination of organs, risk structures and tumors.
In an experimental animal study 20 different organs could be differentiated with high precision (> 95%) using AI. In vivo, the parathyroid glands could be discriminated from surrounding tissue with an F1 score of 47% and sensitivity of 75%, and the bile duct with an F1 score of 79% and sensitivity of 90%. Furthermore, ex vivo tumor tissue could be successfully detected with an area under the receiver operating characteristic (ROC) curve (AUC) larger than 0.91.
This study demonstrates that intelligent HSI can automatically and accurately detect different tissue types. Despite great progress in the last decade intelligent HSI still has limitations. Thus, accurate AI algorithms that are easier to understand for the user and an extensive standardized and continuously growing database are needed. Further clinical studies should support the various medical applications and lead to the adoption of intelligent HSI in the clinical routine practice.
术中成像在微创手术过程中辅助外科医生。高光谱成像(HSI)是一种非侵入性、非接触式光学技术,在医学领域具有巨大的诊断潜力。本文中,将人工智能(AI)方法与高光谱成像数据相结合的分析方式称为智能高光谱成像。
智能高光谱成像在微创内脏手术中的医学应用及优势有哪些?
在各项临床研究中,使用高光谱成像相机系统获取来自多种体内组织类型和肿瘤切除手术的高光谱成像数据。评估了不同的人工智能算法用于检测和区分器官、危险结构及肿瘤。
在一项实验动物研究中,使用人工智能能够高精度(>95%)区分20种不同器官。在活体中,甲状旁腺与周围组织的F1分数为47%,灵敏度为75%;胆管的F1分数为79%,灵敏度为90%。此外,体外肿瘤组织能够被成功检测,受试者工作特征(ROC)曲线下面积(AUC)大于0.91。
本研究表明智能高光谱成像能够自动且准确地检测不同组织类型。尽管在过去十年取得了巨大进展,但智能高光谱成像仍存在局限性。因此,需要用户更易于理解的精确人工智能算法以及广泛的标准化且持续增长的数据库。进一步的临床研究应支持各种医学应用,并促使智能高光谱成像在临床常规实践中得到应用。