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新型图像增强技术有助于在内镜黏膜下剥离术治疗胃肿瘤时发现出血点。

Novel image enhancement technology that helps find bleeding points during endoscopic submucosal dissection of gastric neoplasms.

机构信息

Department of Gastroenterology and Hepatology, Fujita Health University, Toyoake, Aichi, Japan.

出版信息

J Gastroenterol Hepatol. 2022 Oct;37(10):1955-1962. doi: 10.1111/jgh.15975. Epub 2022 Aug 16.

Abstract

BACKGROUND AND AIM

The management of bleeding during endoscopic submucosal dissection (ESD) is critical and related to the procedure time. We collaborated on a new image enhancement algorithm with parameter optimization for clinical use being developed by FUJIFILM Co. and processed white light image data offline to evaluate the effectiveness of this technology. This study aims to evaluate the clinical usefulness of this technology.

METHODS

Eighteen video scenes of bleeding points from five gastric ESDs were selected and processed by the new image enhancement algorithm. The time until a bleeding point was found, visibility of a bleeding point, and color abnormality of the submucosal layer were evaluated by ESD experts, ESD trainees, and endoscopy trainees. The color differences between the bleeding point and the surroundings in CIE-Lab* color space were calculated in the original and enhanced images.

RESULTS

The time until a bleeding point was found in the enhanced videos was significantly shorter than that in the original videos (11.10 s vs 13.85 s) (P = 0.017). On a 5-point (-2 to +2) Likert scale of visibility, the enhanced image was slightly superior to the original (+0.45), and the appearance of the submucosa was comparable between images (+0.14). The color difference among the bleeding areas on the enhanced images was significantly larger than that on the original images (10.93 vs 8.36).

CONCLUSION

This novel image enhancement algorithm emphasizes the color difference between a bleeding point and the surrounding area, which would help find bleeding points faster during ESD for the less experienced endoscopists.

摘要

背景与目的

内镜黏膜下剥离术(ESD)过程中出血的处理至关重要,与手术时间相关。我们与富士胶片公司合作开发了一种新的图像增强算法,并对其进行了参数优化,旨在将其应用于临床。本研究旨在评估该技术的临床应用价值。

方法

选择五例胃 ESD 术中出血点的 18 个视频场景,并使用新的图像增强算法对其进行处理。由 ESD 专家、ESD 学员和内镜学员评估发现出血点的时间、出血点的可视性和黏膜下层颜色异常。计算 CIE-Lab*颜色空间中出血点与周围组织的颜色差异。

结果

增强视频中发现出血点的时间明显短于原始视频(11.10 s 比 13.85 s)(P = 0.017)。在 5 分制(-2 到+2)的可视性评分中,增强图像略优于原始图像(+0.45),且图像之间黏膜下层的外观相似(+0.14)。增强图像上出血区域的颜色差异明显大于原始图像(10.93 比 8.36)。

结论

这种新的图像增强算法强调了出血点与周围区域之间的颜色差异,有助于经验较少的内镜医生在 ESD 过程中更快地发现出血点。

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