How is 3D modeling in metabolic surgery utilized and what is its clinical benefit: a systematic review and meta-analysis.

Abstract

Background: Three-dimensional (3D) modeling is an emerging technology in surgery, with applications in operative planning, surgical education, and patient engagement. Metabolic surgery, the most effective treatment for obesity, is increasingly prevalent leading to new complex clinical challenges. This systematic review aims to understand the use of 3D modeling in metabolic surgery and its impact on clinical outcomes.

Methods: Following a registered protocol (PROSPERO: CRD42024545311), a comprehensive search using MEDLINE, Embase, and CENTRAL Cochrane Library was conducted. Eligible papers underwent screening and full-text review. A qualitative thematic analysis was performed alongside meta-analyses on available volumetric data. Results were reported as directed by the PRISMA guidelines.

Results: Twenty-nine studies were included, with most at Level II evidence ( n = 19, 66%). Studies focused on operative planning and surgical practice (90%, n = 26) and were subdivided into preoperative planning (14%, n = 4), postoperative diagnosis (31%, n = 9), and postoperative assessment and prediction (45%, n = 13). Only three papers addressed surgical education (10%). 3D modeling for patient education was unexplored. To assess 3D modeling's cross-study consistency, pooled meta-analyses on preoperative and postoperative 3D gastric volumetry and abdominal circumference were performed. Average preoperative stomach volume was 794.93 mL (95% confidence interval [CI]: 518.61-1071.26 mL). Postoperative LSG and RYGB/OAGB gastric volumes were 171.71 mL (95% CI: 113.37-288.58 mL) and 35.73 mL (95% CI: 29.32-42.14 mL) respectively. Average abdominal circumference was 120.04 cm (95% CI: 100.72-139.35 cm). All volumes were consistent with published data.

Conclusions: This systematic review highlighted the accuracy of 3D modeling for volumetric assessments and its developing role in surgical planning and training. However, its potential benefits in AR or 3DP models, in patient education or for answering bariatric surgical debates using 3D volumetric studies remain underutilized.