Feasibility of Simultaneous Artificial Intelligence-Assisted and NIR Fluorescence Navigation for Anatomical Recognition in Laparoscopic Colorectal Surgery.

IF 2.6 4区 化学 Q2 BIOCHEMICAL RESEARCH METHODS Journal of Fluorescence Pub Date : 2024-11-22 DOI:10.1007/s10895-024-04030-y
Shunjin Ryu, Yuta Imaizumi, Keisuke Goto, Sotaro Iwauchi, Takehiro Kobayashi, Ryusuke Ito, Yukio Nakabayashi
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Abstract

Ureters can be visualized on a monitor via fluorescence observation technology and an near-infrared (NIR) fluorescent ureteral catheter (NIRFUC). Eureka, an artificial intelligence (AI) platform, can be used to analyze surgical videos and highlight nerves and loose connective tissue (LCT) in the dissection layer. In this study, we aimed to evaluate the feasibility of using simultaneous NIRFUC and AI assistance for anatomical recognition during laparoscopic surgery. The research target was video recordings of laparoscopic colorectal surgery in which the ureters were visualized using an NIRFUC (n = 56, November 2022 to May 2024). Eureka was used to analyze the nerves and LCTs in these videos. Three physicians reviewed and analyzed the videos, scoring the fluorescence visualization of the ureters and LCT by Eureka, the fluorescence visualization of the ureters and hypogastric nerve by Eureka, and the fluorescence visualization of the ureters and lumbar splanchnic nerves by Eureka, using a Likert scale. The scoring system was as follows: 0, very poor; 1, poor; 2, acceptable; 3, good; and 4, very good. The mean Likert scale score was 3.99 for the ureters and LCT, 3.11 for the ureters and hypogastric nerve, and 3.53 for the ureters and lumbar splanchnic nerves. The training data used for this AI model did not include NIR fluorescence image observations. Anatomical highlighting with AI and fluorescence visualization of the ureters were possible in the images analyzed by Eureka. These findings suggest that both AI and NIR can be used simultaneously for real-time navigation in the future.

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人工智能辅助和近红外荧光导航同时用于腹腔镜结直肠手术解剖识别的可行性。
通过荧光观察技术和近红外(NIR)荧光输尿管导管(NIRFUC),输尿管可以在监视器上可视化。人工智能(AI)平台 Eureka 可用于分析手术视频,并突出显示解剖层中的神经和疏松结缔组织(LCT)。在这项研究中,我们旨在评估在腹腔镜手术中同时使用近红外荧光UC和人工智能辅助进行解剖识别的可行性。研究对象是腹腔镜结直肠手术的视频记录,其中使用 NIRFUC 对输尿管进行了可视化(n = 56,2022 年 11 月至 2024 年 5 月)。Eureka 用于分析这些视频中的神经和 LCT。三位医生对视频进行了审查和分析,采用李克特量表对 Eureka 的输尿管和 LCT 荧光显像、Eureka 的输尿管和胃下神经荧光显像以及 Eureka 的输尿管和腰脾神经荧光显像进行评分。评分标准如下0,很差;1,差;2,可接受;3,好;4,非常好。输尿管和 LCT 的平均李克特量表得分为 3.99,输尿管和胃下神经的平均李克特量表得分为 3.11,输尿管和腰脾神经的平均李克特量表得分为 3.53。该人工智能模型使用的训练数据不包括近红外荧光图像观察结果。在 Eureka 分析的图像中,可以用人工智能和荧光可视化技术突出显示输尿管的解剖结构。这些发现表明,人工智能和近红外可同时用于未来的实时导航。
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来源期刊
Journal of Fluorescence
Journal of Fluorescence 化学-分析化学
CiteScore
4.60
自引率
7.40%
发文量
203
审稿时长
5.4 months
期刊介绍: Journal of Fluorescence is an international forum for the publication of peer-reviewed original articles that advance the practice of this established spectroscopic technique. Topics covered include advances in theory/and or data analysis, studies of the photophysics of aromatic molecules, solvent, and environmental effects, development of stationary or time-resolved measurements, advances in fluorescence microscopy, imaging, photobleaching/recovery measurements, and/or phosphorescence for studies of cell biology, chemical biology and the advanced uses of fluorescence in flow cytometry/analysis, immunology, high throughput screening/drug discovery, DNA sequencing/arrays, genomics and proteomics. Typical applications might include studies of macromolecular dynamics and conformation, intracellular chemistry, and gene expression. The journal also publishes papers that describe the synthesis and characterization of new fluorophores, particularly those displaying unique sensitivities and/or optical properties. In addition to original articles, the Journal also publishes reviews, rapid communications, short communications, letters to the editor, topical news articles, and technical and design notes.
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