Evidence map›Paper›PMID 42717048›Full record

ArticleSurgical endoscopy2026

Agreement and precision of an AI-based measurement tool during robotic-assisted sleeve gastrectomy.

Hector Garcia Navas, Nicholas Dahlgren, Shubham Bhatia, Carlos Galvani, Denise M Danos, Philip R Schauer, Vance L Albaugh, Michael W Cook

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Article in Surgical endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Hector Garcia NavasMetamor Institute, Pennington Biomedical Research Center at Louisiana State University, Baton Rouge, LA, USA.
Nicholas DahlgrenDepartment of Surgery, School of Medicine, LSU Health, 2021 Perdido St. Room 8146, New Orleans, LA, USA.
Shubham BhatiaDepartment of Surgery, School of Medicine, LSU Health, 2021 Perdido St. Room 8146, New Orleans, LA, USA.
Carlos GalvaniDepartment of Surgery, School of Medicine, LSU Health, 2021 Perdido St. Room 8146, New Orleans, LA, USA.
Denise M DanosDepartment of Behavioral & Community Health, Louisiana State University Health Sciences Center, New Orleans, LA, USA.
Philip R SchauerMetamor Institute, Pennington Biomedical Research Center at Louisiana State University, Baton Rouge, LA, USA.
Vance L AlbaughMetamor Institute, Pennington Biomedical Research Center at Louisiana State University, Baton Rouge, LA, USA.
Michael W CookDepartment of Surgery, School of Medicine, LSU Health, 2021 Perdido St. Room 8146, New Orleans, LA, USA. mcoo11@lsuhsc.edu.ORCID http://orcid.org/0000-0001-6719-7379

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSize and shape of the stomach following a sleeve gastrectomy (SG) appear to impact operative outcomes; however, standardization of these variables is difficult without accurate measurements. Manual measurement techniques are prone to inter-operator variability and can be cumbersome. Artificial Intelligence (AI)-based measurement tools integrated in robotic platforms may provide real-time, precise anatomical assessment. The purpose of this study is to evaluate the preliminary agreement of an AI-based measurement tool relative to conventional ruler measurement during robotic-assisted sleeve gastrectomy (SG) surgery, the most common type of bariatric surgery performed worldwide.

methodsAdult patients (n = 12, > 18 years) undergoing robotic-assisted SG between August 2025 and January 2026 were included. Measurements (cm) at the widest point of the gastroesophageal (GE) junction and the narrowest point at the incisura were obtained using both point-to-point (P2P) and contour approaches. Data were summarized using mean ± standard deviation (SD). Agreement was assessed using Pearson's correlation analysis with 95% confidence intervals, partial correlation adjusting for BMI, and Bland-Altman analysis.

resultsAll 12 patients were female with a mean BMI of 46.3 ± 6.5 kg/m

conclusionThis pilot study demonstrates preliminary agreement between commercially available robotic-integrated AI measurement tool and standard ruler measurement during live SG, particularly for P2P measurements. These hypothesis-generating findings support the potential of AI-assisted measurement to enhance surgical precision and efficiency, providing a foundation for future larger-scale, multicenter validation studies.

Indexed as

AccuracyArtificial intelligence (AI)Bariatric surgeryRobotic surgerySleeve gastrectomy (SG)

Identifiers

PMID42717048

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.