Advertisement for orthosearch.org.uk
Results 1 - 3 of 3
Results per page:
The Bone & Joint Journal
Vol. 106-B, Issue 5 Supple B | Pages 3 - 10
1 May 2024
Heimann AF Murmann V Schwab JM Tannast M

Aims

The aim of this study was to investigate whether anterior pelvic plane-pelvic tilt (APP-PT) is associated with distinct hip pathomorphologies. We asked: is there a difference in APP-PT between young symptomatic patients being evaluated for joint preservation surgery and an asymptomatic control group? Does APP-PT vary among distinct acetabular and femoral pathomorphologies? And does APP-PT differ in symptomatic hips based on demographic factors?

Methods

This was an institutional review board-approved, single-centre, retrospective, case-control, comparative study, which included 388 symptomatic hips in 357 patients who presented to our tertiary centre for joint preservation between January 2011 and December 2015. Their mean age was 26 years (SD 2; 23 to 29) and 50% were female. They were allocated to 12 different morphological subgroups. The study group was compared with a control group of 20 asymptomatic hips in 20 patients. APP-PT was assessed in all patients based on supine anteroposterior pelvic radiographs using validated HipRecon software. Values in the two groups were compared using an independent-samples t-test. Multiple regression analysis was performed to examine the influences of diagnoses and demographic factors on APP-PT. The minimal clinically important difference (MCID) for APP-PT was defined as > 1 SD.


Bone & Joint Open
Vol. 4, Issue 11 | Pages 825 - 831
1 Nov 2023
Joseph PJS Khattak M Masudi ST Minta L Perry DC

Aims

Hip disease is common in children with cerebral palsy (CP) and can decrease quality of life and function. Surveillance programmes exist to improve outcomes by treating hip disease at an early stage using radiological surveillance. However, studies and surveillance programmes report different radiological outcomes, making it difficult to compare. We aimed to identify the most important radiological measurements and develop a core measurement set (CMS) for clinical practice, research, and surveillance programmes.

Methods

A systematic review identified a list of measurements previously used in studies reporting radiological hip outcomes in children with CP. These measurements informed a two-round Delphi study, conducted among orthopaedic surgeons and specialist physiotherapists. Participants rated each measurement on a nine-point Likert scale (‘not important’ to ‘critically important’). A consensus meeting was held to finalize the CMS.


Bone & Joint Open
Vol. 3, Issue 11 | Pages 877 - 884
14 Nov 2022
Archer H Reine S Alshaikhsalama A Wells J Kohli A Vazquez L Hummer A DiFranco MD Ljuhar R Xi Y Chhabra A

Aims. Hip dysplasia (HD) leads to premature osteoarthritis. Timely detection and correction of HD has been shown to improve pain, functional status, and hip longevity. Several time-consuming radiological measurements are currently used to confirm HD. An artificial intelligence (AI) software named HIPPO automatically locates anatomical landmarks on anteroposterior pelvis radiographs and performs the needed measurements. The primary aim of this study was to assess the reliability of this tool as compared to multi-reader evaluation in clinically proven cases of adult HD. The secondary aims were to assess the time savings achieved and evaluate inter-reader assessment. Methods. A consecutive preoperative sample of 130 HD patients (256 hips) was used. This cohort included 82.3% females (n = 107) and 17.7% males (n = 23) with median patient age of 28.6 years (interquartile range (IQR) 22.5 to 37.2). Three trained readers’ measurements were compared to AI outputs of lateral centre-edge angle (LCEA), caput-collum-diaphyseal (CCD) angle, pelvic obliquity, Tönnis angle, Sharps angle, and femoral head coverage. Intraclass correlation coefficients (ICC) and Bland-Altman analyses were obtained. Results. Among 256 hips with AI outputs, all six hip AI measurements were successfully obtained. The AI-reader correlations were generally good (ICC 0.60 to 0.74) to excellent (ICC > 0.75). There was lower agreement for CCD angle measurement. Most widely used measurements for HD diagnosis (LCEA and Tönnis angle) demonstrated good to excellent inter-method reliability (ICC 0.71 to 0.86 and 0.82 to 0.90, respectively). The median reading time for the three readers and AI was 212 (IQR 197 to 230), 131 (IQR 126 to 147), 734 (IQR 690 to 786), and 41 (IQR 38 to 44) seconds, respectively. Conclusion. This study showed that AI-based software demonstrated reliable radiological assessment of patients with HD with significant interpretation-related time savings. Cite this article: Bone Jt Open 2022;3(11):877–884