Evidence map›Paper›PMID 40009557›Full record

SynthesisInternational journal of surgery (London, England)2025

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

Henry Douglas Robb, Aksaan Arif, Rithvik Mahadev Narendranath, Bibek Das, Khaled Alyaqout, William Lynn, Yasser Abul Aal, Hutan Ashrafian, Matyas Fehervari

Abstract readSystematic ReviewMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in International journal of surgery (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Henry Douglas RobbDepartment of Surgery and Cancer, Imperial College London, London UK.ORCID 0000-0003-4898-2173
Aksaan ArifDepartment of Surgery and Cancer, Imperial College London, London UK.
Rithvik Mahadev NarendranathDepartment of Surgery and Cancer, Imperial College London, London UK.
Bibek DasDepartment of Surgery and Cancer, Imperial College London, London UK.
Khaled AlyaqoutJaber Al Ahmad Hospital, , Kuwait City Kuwait.
William LynnGastrointestinal Surgery, Maidstone and Tunbridge Wells NHS Trust, Tunbridge Wells, London UK.
Yasser Abul AalGastrointestinal Surgery, Maidstone and Tunbridge Wells NHS Trust, Tunbridge Wells, London UK.
Hutan AshrafianDepartment of Surgery and Cancer, Imperial College London, London UK.
Matyas FehervariDepartment of Surgery and Cancer, Imperial College London, London UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThree-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.

methodsFollowing 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.

resultsTwenty-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.

conclusionsThis 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.

Indexed as

Bariatric SurgeryImaging, Three-DimensionalObesityHumans3D printingaugmented realitycomputer-generated 3D imaginggastrointestinal diseasegeneral surgerymetabolic surgeryvirtual reality

Identifiers

PMID40009557
PMCPMC12165527

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Registered trials

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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.