Establishing ground truth of polyp size, morphology, and volume using three-dimensional scanning Comprehensive artificial intelligence (AI) solutions that should cover detecting polyp morphology, size, and volume are being developed. To train such AI solutions, it is essential to obtain high quality reference (ground truth data) on polyp morphology, size, and volume.

We explored the feasibility of three-dimensional (3D) scanning of colorectal polyps to obtain computer-aided design (CAD) 3D rendering information on polyp morphology, size, and volume. During the colonoscopy, a novel virtual scale endoscope (VSE; Scale eye, EW10-VM01; Fujifilm, Tokyo, Japan) with an integrated virtual scale function was used, which allows for polyp size measurement [11] [22] [33] ([Video 1Video 1]). Two detected polyps had their size measured during the colonoscopy using VSE ([Fig. 1Fig. 1] a,d), then were removed from the colon as intact en bloc specimens with a healthy resection margin. The polyps were measured using a digital Vernier caliper (eSync with 32 feeler gauge with 0.01-mm intervals) directly after resection ([Fig. 1Fig. 1] b,e). The polyps were then 3D scanned for volumetric information (Artec Space Spider; Artec 3D, Luxembourg) [44] ([Fig. 1Fig. 1] c,f). The 3D scanner processes up to 1 million individual points per second at 7.5 frames per second with a resolution of 0.1 mm. Polyp 1 was measured as being 8 mm using the VSE, 8.88 mm using the caliper, and 9.68 mm in the 3D model. The total polyp volume was 291.8 mm3. Polyp 2 was measured as being 14 mm using the VSE, 15.16 mm using the caliper, and 15.20 mm in the 3D model. The total polyp volume was 968.1 mm3.

Fig. 1 Fig. 1 Images showing the measurement of two polyps using: a,d the virtual scale endoscope; b,e a vernier caliper; c,f 3D rendering after the polyps’ resection.

We found that it is possible to obtain spatial polyp information through 3D scanning. 3D scanning of polyps can capture their shape, geometries, and textures, translating them into data files in which size, volume, and shape becomes measurable. These 3D models can then be used in the context of AI development to provide ground truth data to train models to automatically recognize size, volume, and Paris classification.

E-Videosis an open access online section of the journal Endoscopy, reporting on interesting cases and new techniques in gastroenterological endoscopy. All papers include a high-quality video and are published with a Creative Commons CC-BY license. Endoscopy E-Videos qualify for HINARI discounts and waivers and eligibility is automatically checked during the submission process. We grant 100% waivers to articles whose corresponding authors are based in Group A countries and 50% waivers to those who are based in Group B countries as classified by Research4Life (see: https://www.research4life.org/access/eligibility/).

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Article published online:
28 March 2024

© 2023. The Author(s). This article was originally published by Thieme in Endoscopy 2023; 55: E1260–E1261 as an open access article under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/).

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