Introduction: 3D models produced from medical imaging can be used to plan treatment, design prosthesis, teach and for communication. Despite the clinical benefit, few clinicians have experience of how 3D models are produced.This is the first study evaluating a training tool to teach clinicians to produce 3D models and reporting the perceived impact on their clinical practice.

Method: Following ethical approval, 10 clinicians completed a bespoke training tool, comprising written and video material alongside online support. Each clinician and 2 technicians (included as control) were sent 3 CT scans and asked to produce 6 fibula 3D models using an open-source software (3Dslicer). The produced models were compared to those produced by the technicians using Hausdorff distance calculation. Thematic analysis was used to study the post-intervention questionnaire.

Results: The mean Hausdorff distance between the final model produced by the clinicians and technicians was 0.65mm SD0.54mm. The first model made by clinicians took a mean time of 1hr 25mins and the final model took 16:04mins (5:00-46:00mins). 100% of learners reported finding the training tool useful and will employ it in future practice.

Discussion: The training tool described in this paper is able to successfully train clinicians to produce fibula models from CT scans. Learners were able to produce comparable models to technicians within an acceptable timeframe. This does not replace technicians. However, the learners perceived this training will allow them to use this technology in more cases, with appropriate case selection and they appreciate the limits of this technology.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614675PMC
http://dx.doi.org/10.1097/AS9.0000000000000275DOI Listing

Publication Analysis

Top Keywords

training tool
20
models
8
clinicians produce
8
produce fibula
8
fibula models
8
hausdorff distance
8
final model
8
clinicians
7
training
6
technicians
5

Similar Publications

ChatGPT: Friend or foe in medical writing? An example of how ChatGPT can be utilized in writing case reports.

Surg Pract Sci

September 2023

USF Department of General Surgery 2 Tampa General Circle, 7th Floor Tampa, FL 33606, United States.

ChatGPT is a chatbot built on a natural language processing model which can generate human-like responses to prompts given to it. Despite its lack of domain-specific training, ChatGPT has developed remarkable accuracy in interpreting clinical information. In this article, we aim to assess what role ChatGPT can serve in medical writing.

View Article and Find Full Text PDF

Background: General surgery residents frequently access YouTube® for educational walkthroughs of surgical procedures. The aim of this study is to evaluate the educational quality of YouTube® video walkthroughs on Laparoscopic Roux-en-Y gastric bypass (LRYGB) using a validated video assessment tool.

Methods: A retrospective review of YouTube® videos was conducted for "laparoscopic Roux-en-Y gastric bypass", "laparoscopic RYGB", and "laparoscopic gastric bypass.

View Article and Find Full Text PDF

Introduction: As resident evaluation moves to a competency-based system, validated tools for assessment of surgical skill are increasingly important. We created and validated a checklist to measure resident surgical skill for arthroscopic management of meniscal tear.

Materials And Methods: Using a Delphi survey method, we created an objective, structured assessment of surgical skill for treatment of meniscal tears.

View Article and Find Full Text PDF

Introduction: The Stigma Assessment and Reduction of Impact (SARI) Stigma Scale is an instrument developed to evaluate stigma in Leprosy patients. Despite existing versions in Indonesian, the absence of an endemic area language version of a reliable assessment tool presents a barrier to effective interventions in regions like Ambon. This study aims to evaluate the validity and reliability of the Ambonese-Malay Language of SARI Stigma Scale questionnaire.

View Article and Find Full Text PDF

Objective: The Surgical Training and Educational Platform (STEP) was developed by the American Society for Surgery of the Hand (ASSH) as a cost-effective set of surgical simulation modules designed to represent critical psychomotor skills in hand surgery. We hypothesize that increased training on these training modules, even with limited supervision, would improve resident performance on psychomotor skills.

Design: Baseline evaluation was conducted on four psychomotor skills to simulate surgical tasks: lag screw fixation, depth of plunge, skin graft harvest, and wrist arthroscopy.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!