Evidence map›Paper›PMID 32364146›Full record

ArticleTechnology and health care : official journal of the European Society for Engineering and Medicine2020

The manufacturing procedure of 3D printed models for endoscopic endonasal transsphenoidal pituitary surgery.

Zhen Shen, Yi Xie, Xiuqin Shang, Gang Xiong, Shi Chen, Yong Yao, Zhouxian Pan, Hui Pan, Xisong Dong, Yuqing Li and 2 more

Abstract read
In one paragraph

Article in Technology and health care : official journal of the European Society for Engineering and Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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

  1. Pooled it
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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

12 authors.

Zhen ShenState Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Yi XieState Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Xiuqin ShangState Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Gang XiongState Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Shi ChenDepartment of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Yong YaoDepartment of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Zhouxian PanDepartment of Allergy, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Hui PanDepartment of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Xisong DongState Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Yuqing LiState Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Chao GuoState Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Fei-Yue WangState Key Laboratory for Management and Control of Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEndoscopic endonasal transsphenoidal pituitary surgery is usually difficult and risky. With limited sources of cadaveric skulls, traditional methods of using virtual images to study the surgery are difficult for neurosurgeons and students because the surgery requires spatial imagination and good understanding of the patient's conditions as well as practical experience. The three-dimensional (3D) printing technique has played an important role in clinical medicine due to its advantages of low cost, high-efficiency and customization.

objectiveCT images are used as the source data of 3D printing. The data obtained directly from the CT machine has limited accuracy, which cannot be printed without processing. Some commercial platforms can help build an accurate model but the cost and customization are not satisfactory. In this situation, a tactile, precise and low-cost 3D model is highly desirable.

methodsFive kinds of computer software are used in the manufacturing of medical 3D models and the processing procedure is easy to understand and operate.

resultsThis study proposes a practical and cost-effective method to obtain the corrected digital model and produce the 3D printed skull with complete structures of nasal cavity, sellar region and different levels of pituitary tumors. The model is used for the endoscopic endonasal transsphenoidal pituitary surgery preparation.

conclusionThe 3D printed medical model can directly help neurosurgeons and medical students to practice their surgery skills on both general and special cases with customized structures and different levels of tumors.

Indexed as

Models, AnatomicPrinting, Three-DimensionalCosts and Cost AnalysisEndoscopyHumansImage Processing, Computer-AssistedPituitary NeoplasmsSkullTomography, X-Ray Computed3D printingEndoscopic endonasal transsphenoidal pituitary surgerypituitary tumorsurgery simulation

Identifiers

PMID32364146
PMCPMC7369091

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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.