Evidence map›Paper›PMID 31030233›Full record

ArticleSurgical and radiologic anatomy : SRA2019

Application of three-dimensional reconstruction and printing as an elective course for undergraduate medical students: an exploratory trial.

Xiaoqin Zhang, Zhou Xu, Liwen Tan, Ying Li, Li Liu, Na Chen, Shaoxiang Zhang, Wouter H Lamers, Chunling Wu, Yi Wu

Abstract read
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In one paragraph

Article in Surgical and radiologic anatomy : SRA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Xiaoqin ZhangInstitute of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
Zhou XuInstitute of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
Liwen TanInstitute of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
Ying LiInstitute of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
Li LiuInstitute of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
Na ChenInstitute of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
Shaoxiang ZhangInstitute of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
Wouter H LamersTytgat Institute for Liver and Intestinal Research, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Chunling WuInstitute of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
Yi WuInstitute of Digital Medicine, School of Biomedical Engineering and Medical Imaging, Army Medical University (Third Military Medical University), Chongqing, 400038, China. wuy1979@tmmu.edu.cn.ORCID http://orcid.org/0000-0002-2322-6825

Funding

Graduate Education and Teaching Reform Research Project of Chongqing yjg183144Military Youth Science Foundation of China 16QNP100National Key Research and Development Program of China 2016YFC0106402National Natural Science Foundation of China 31771324
6 · The paper itself

Abstract

backgroundMedical three-dimensional (3D) digital reconstruction and printing have become common tools in medicine, but few undergraduate medical students understand its whole process and teaching and clinical application. Therefore, we designed an elective course of 3D reconstruction and printing for students and studied its significance and practicability.

methodsThirty undergraduate medical students in their second-year of study volunteered to participate in the course. The course started with three lessons on the theory of 3D digital reconstruction and printing in medicine. The students were then randomly divided into ten groups. Each group randomly selected its own original data set, which could contain a series of 2D images including sectional anatomical images, histological images, CT and MRI. Amira software was used to segment the structures of interest, to 3D reconstruct them and to smooth and simplify the models. These models were 3D printed and post-processed. Finally, the 3D digital and printed models were scored, and the students produced brief reports of their work and knowledge acquisition and filled out an anonymous questionnaire about their study perceptions.

resultsAll the students finished this course. The average score of the 30 students was 83.1 ± 2.7. This course stimulated the students' learning interest and satisfied them. It was helpful for undergraduate students to understand anatomical structures and their spatial relationship more deeply. Students understood the whole process of 3D reconstruction and printing and its teaching and clinical applications through this course.

conclusionIt is significant and necessary to develop this course for undergraduate medical students.

Indexed as

Imaging, Three-DimensionalModels, AnatomicPrinting, Three-DimensionalAnatomyDatasets as TopicEducational MeasurementEducation, Medical, UndergraduateFemaleHumansMagnetic Resonance ImagingMaleSoftwareStudents, MedicalTeachingTomography, X-Ray ComputedYoung Adult3D printing3D reconstructionMedical educationMedical image segmentationUndergraduate education

Identifiers

What OpenQuestion holds

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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.