Evidence map›Paper›PMID 38862455›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2024

[The "E-bone" - a one-stop preoperative planning system for reverse total shoulder arthroplasty].

M Li, Y Mi, S Shen, X Wu, J Yan, B Chen, L Cao

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Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

M LiDepartment of Information, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Y MiSchool of Biomedical Engineering//Guangdong Provincial Key Laboratory of Medical Image Processing//Guangdong Provincial Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510515, China.
S ShenDepartment of Orthopedics, Jinling Hospital, School of Clinical Medicine, Nanjing University/General Hospital of Eastern Theater Command of PLA, Nanjing 210002, China.
X WuDepartment of Orthopedics, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
J YanDepartment of Information, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
B ChenDepartment of Orthopedics, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
L CaoSchool of Biomedical Engineering//Guangdong Provincial Key Laboratory of Medical Image Processing//Guangdong Provincial Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510515, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop the'E-Bone', a comprehensive one-stop preoperative planning system for reverse total shoulder arthroplasty with improved accuracy and efficiency.

methodsThe nnU-net deep neural network was utilized for scapula segmentation to obtain precise scapula segmentation results. Based on the 3 key factors, namely bone density, upward and downward angle and nail length, the base was automatically positioned. The quantitative parameters required for surgical planning were calculated. A personalized guide plate was generated by combining glenoid morphology and base positioning information. The system interface was developed to modularize various functions for easy use, providing interactive operation and real-time display.

resultsCompared with the Mimics system, the'E-bone'preoperative planning system reduced complex manual adjustments during the planning process. The average planned nail length was longer than that of the Mimics system, and the planning time was reduced by 86%. The scapula segmentation accuracy of this system reached 99.93%, better than that of Mimics to achieve a higher precision.

conclusionThe"E-bone"system provides a one-stop, efficient, and accurate preoperative planning system for reverse shoulder replacement and potentially broader clinical applications.

Indexed as

Arthroplasty, Replacement, ShoulderHumansNeural Networks, ComputerScapulaSurgery, Computer-Assistedbase positioningone-stop surgical planningpreoperative planning systemreverse total shoulder arthroplastyscapula segmentation

Identifiers

PMID38862455
PMCPMC11166726

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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.