Advertisement for orthosearch.org.uk
Results 1 - 3 of 3
Results per page:
Orthopaedic Proceedings
Vol. 105-B, Issue SUPP_7 | Pages 56 - 56
4 Apr 2023
Sun Y Zheng H Kong D Yin M Chen J Lin Y Ma X Tian Y Wang Y
Full Access

Using deep learning and image processing technology, a standardized automatic quantitative analysis systerm of lumbar disc degeneration based on T2MRI is proposed to help doctors evaluate the prognosis of intervertebral disc (IVD) degeneration.

A semantic segmentation network BianqueNet with self-attention mechanism skip connection module and deep feature extraction module is proposed to achieve high-precision segmentation of intervertebral disc related areas. A quantitative method is proposed to calculate the signal intensity difference (SI) in IVD, average disc height (DH), disc height index (DHI), and disc height-to-diameter ratio (DHR). According to the correlation analysis results of the degeneration characteristic parameters of IVDs, 1051 MRI images from four hospitals were collected to establish the quantitative ranges for these IVD parameters in larger population around China.

The average dice coefficients of the proposed segmentation network for vertebral bodies and intervertebral discs are 97.04% and 94.76%, respectively. The designed parameters of intervertebral disc degeneration have a significant negative correlation with the Modified Pfirrmann Grade. This procedure is suitable for different MRI centers and different resolution of lumbar spine T2MRI (ICC=.874~.958). Among them, the standard of intervertebral disc signal intensity degeneration has excellent reliability according to the modified Pfirrmann Grade (macroF1=90.63%~92.02%).

we developed a fully automated deep learning-based lumbar spine segmentation network, which demonstrated strong versatility and high reliability to assist residents on IVD degeneration grading by means of IVD degeneration quantitation.


Bone & Joint Research
Vol. 8, Issue 11 | Pages 544 - 549
1 Nov 2019
Zheng W Liu C Lei M Han Y Zhou X Li C Sun S Ma X

Objectives

The objective of this study was to investigate the association of four single-nucleotide polymorphisms (SNPs) of the cannabinoid receptor 2 (CNR2) gene, gene-obesity interaction, and haplotype combination with osteoporosis (OP) susceptibility.

Methods

Chinese patients with OP were recruited between March 2011 and December 2015 from our hospital. In this study, a total of 1267 post-menopausal female patients (631 OP patients and 636 control patients) were selected. The mean age of all subjects was 69.2 years (sd 15.8). A generalized multifactor dimensionality reduction (GMDR) model and logistic regression model were used to examine the interaction between SNP and obesity on OP. For OP patient-control haplotype analyses, the SHEsis online haplotype analysis software (http://analysis.bio-x.cn/) was employed.


Bone & Joint Research
Vol. 2, Issue 12 | Pages 255 - 263
1 Dec 2013
Zhang Y Xu J Wang X Huang J Zhang C Chen L Wang C Ma X

Objective

The objective of this study was to evaluate the rotation and translation of each joint in the hindfoot and compare the load response in healthy feet with that in stage II posterior tibial tendon dysfunction (PTTD) flatfoot by analysing the reconstructive three-dimensional (3D) computed tomography (CT) image data during simulated weight-bearing.

Methods

CT scans of 15 healthy feet and 15 feet with stage II PTTD flatfoot were taken first in a non-weight-bearing condition, followed by a simulated full-body weight-bearing condition. The images of the hindfoot bones were reconstructed into 3D models. The ‘twice registration’ method in three planes was used to calculate the position of the talus relative to the calcaneus in the talocalcaneal joint, the navicular relative to the talus in talonavicular joint, and the cuboid relative to the calcaneus in the calcaneocuboid joint.