A Novel Computer-based Method for Measuring the Acetabular Angle on Hip Radiographs

Overview

Journal Acta Orthop Traumatol Turc

Specialties Emergency Medicine
Orthopedics

Date 2017 Jan 17

PMID 28089510

Citations 4

Authors

Seda Sahin

Emin Akata

Orcun Sahin

Cengiz Tuncay

Huseyin Ozkan

Affiliations

Soon will be listed here.

Abstract

Objective: The aim of this study was to propose a new computer based method for measuring acetabular angles on hip radiographs and to assess its practicality, sensitivity and reliability for acetabular angle measurement.

Methods: A total of 314 acetabulum were assessed on 157 pelvic X-ray images. Acetabular angles were measured with both the conventional method (Method 1) and our proposed method (Method 2). All the Acetabular Index (AI) angle, Acetabular Angle (AA) and Acetabular Center (ACM) angle were measured with both methods.

Results: The mean AI angle for Method 1 is 11.02° ± 2.7° and the mean AI angle for Method 2 is 10.08° ± 1.88°, the mean AA angle for Method 1 is 39.5° ± 5.3° and the mean AA angle for Method 2 is 39.36° ± 4.68°, the mean ACM angle for Method 1 is 50.5° ± 6.01° and the mean ACM angle for Method 2 is 55.42° ± 12.43°.

Conclusion: Our novel automated method appear to be reliable and practical for acetabular angle measurement on hip radiographs.

Level Of Evidence: Level III, Diagnostic study.

Citing Articles

Enhancing YOLO5 for the Assessment of Irregular Pelvic Radiographs with Multimodal Information.

Chen J, Fan X, Chen Z, Peng Y, Liang L, Su C J Imaging Inform Med. 2024; 37(2):744-755.

PMID: 38315343 PMC: 11031542. DOI: 10.1007/s10278-024-00986-2.

Diagnostic accuracy of a deep learning model using YOLOv5 for detecting developmental dysplasia of the hip on radiography images.

Den H, Ito J, Kokaze A Sci Rep. 2023; 13(1):6693.

PMID: 37095189 PMC: 10126130. DOI: 10.1038/s41598-023-33860-2.

Detection of developmental dysplasia of the hip in X-ray images using deep transfer learning.

Fraiwan M, Al-Kofahi N, Ibnian A, Hanatleh O BMC Med Inform Decis Mak. 2022; 22(1):216.

PMID: 35964072 PMC: 9375244. DOI: 10.1186/s12911-022-01957-9.

Diagnostic Performance of a New Convolutional Neural Network Algorithm for Detecting Developmental Dysplasia of the Hip on Anteroposterior Radiographs.

Park H, Jeon K, Cho Y, Kim S, Lee S, Choi G Korean J Radiol. 2020; 22(4):612-623.

PMID: 33289354 PMC: 8005351. DOI: 10.3348/kjr.2020.0051.

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