Evidence map›Paper›PMID 42835561›Full record

ArticleJPRAS open2026

A validated high-fidelity synthetic model for internal mammary vessel preparation in autologous breast reconstruction.

Iulia Marinescu, Adam F Roche, Caoimhin O'Conghaile, Claire Condron, Omar Quidwai, Stephanie Bollard, Barry O'Sullivan, Jamie Martin Smith, Jack Woods, Colin Morrison and 3 more

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Iulia MarinescuDepartment of Plastic and Reconstructive Surgery, St. Vincent's University Hospital, Dublin, Ireland.
Adam F RocheRCSI SIM Centre for Simulation Education and Research, RCSI University of Medicine and Health Sciences, Dublin, Ireland.
Caoimhin O'ConghaileRCSI SIM Centre for Simulation Education and Research, RCSI University of Medicine and Health Sciences, Dublin, Ireland.
Claire CondronRCSI SIM Centre for Simulation Education and Research, RCSI University of Medicine and Health Sciences, Dublin, Ireland.
Omar QuidwaiDepartment of Plastic and Reconstructive Surgery, St. Vincent's University Hospital, Dublin, Ireland.
Stephanie BollardDepartment of Plastic and Reconstructive Surgery, St. Vincent's University Hospital, Dublin, Ireland.
Barry O'SullivanDepartment of Plastic and Reconstructive Surgery, Beaumont Hospital, Dublin, Ireland.
Jamie Martin SmithDepartment of Plastic and Reconstructive Surgery, Beaumont Hospital, Dublin, Ireland.
Jack WoodsDepartment of Plastic and Reconstructive Surgery, St. Vincent's University Hospital, Dublin, Ireland.
Colin MorrisonDepartment of Plastic and Reconstructive Surgery, St. Vincent's University Hospital, Dublin, Ireland.
Adrian McArdleDepartment of Surgery, Division of Plastic, Reconstructive & Aesthetic Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada.
Anton FriesDivision of Plastic Surgery, UT Health San Antonio, San Antonio, TX, United States.
Roisin DolanDepartment of Plastic and Reconstructive Surgery, St. Vincent's University Hospital, Dublin, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: The precise and safe preparation of internal mammary vessels (IMVs) is a critical step in microvascular autologous breast reconstruction. These vessels lie within a confined, dynamic space, requiring refined dexterity and careful tissue handling. Opportunities for structured training remain limited. This study aimed to develop and validate a high-fidelity synthetic model for IMV preparation and assess its educational value. Materials & Methods: A synthetic post-mastectomy chest model was designed in collaboration with specialist technicians with expertise in simulation design and implementation, with iterative input from consultant microsurgeons. Five novice and five expert surgeons participated. Face and content validity were assessed by independent expert evaluation. Construct validity was examined using a task-specific checklist and the Objective Structured Assessment of Technical Skills (OSATS), scored by two blinded assessors. Novice confidence was assessed pre- and post-training. Results: Expert evaluation demonstrated good face validity, with high ratings for overall realism and anatomical fidelity (4.5/5), vessel dissection (3.25/5) and teaching suitability and utility for higher surgical training (4.25/5). Construct validity was supported by higher expert performance (OSATS: 23.5 vs 18.9; checklist: 10.0 vs 9.4), and faster task completion time (13.8 vs 15.8 min). Inter-rater reliability was moderate to strong (ICC 0.575-0.820). Novice confidence improved significantly following training (mean increase 2.6, t = 6.50, p = 0.003). Conclusions: This realistically responsive training model demonstrates strong face, content and construct validity. It provides a practical and objective platform for training and assessing internal mammary vessel preparation and supports safer skill acquisition before progression to the operating theatre.

Indexed as

Breast reconstructionInternal mammary vesselsMicrosurgeryObjective structured assessment of technical skillsSurgical simulationTechnical skills assessment

Identifiers

PMID42835561
PMCPMC13636305

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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.