Effect of acetabular morphological parameters applied in proximal femoral varus osteotomy on the treatment of developmental dysplasia of the hip in children

Abstract Background It was previously reported that pelvises with developmental dysplasia of the hip are tilted anteriorly, which increases bony coverage of the femoral head. This study aimed to investigate the correlation between anatomical parameters of the pelvis such as pelvic incidence and anatomical pelvic tilt and functional parameters of the spine and pelvis such as tilt of the anterior pelvic plane. Methods We examined 84 female patients with bilateral developmental dysplasia of the hip who had undergone curved periacetabular osteotomy at author’s institution. Radiographs of the thoracic to lumbar spines and the pelvis were obtained in the standing position to measure spino-pelvic parameters before surgery. Morphological parameters of the acetabulum such as the anterior center-edge (CE) angle, posterior CE angle, lateral CE angle, and acetabular anteversion were measured using a preoperative three-dimensional pelvic model reconstructed from computed tomography images. Pearson’s correlation analysis was conducted to evaluate the relationship of these parameters. Results With regard to correlations between pelvic incidence (PI) and other parameters, the sacral slope (SS) value (r = 0.666) was the highest among functional parameters and the anatomical-SS value (r = 0.789) was the highest among morphological parameters. There were moderate correlations of the anterior pelvic plane angle (APPA) with pelvic tilt (PT) (r = − 0.594) and anatomical-PT (r = 0.646). With regard to correlations between spino-pelvic parameters and bony morphological parameters of the acetabulum, there was a moderate correlation between anatomical-PT and acetabular anteversion (AA) (r = 0.424). There were moderate correlations of APPA with the anterior CE angle (r = − 0.478), posterior CE angle (r = 0.432), and AA (r = 0.565). APPA had a stronger correlation with anatomical-PT (r = 0.646) than with AA. Conclusions The tilt of the pelvis may be more dependent on anatomical-PT, a morphological parameter of the pelvis, than the lateral CE angle, anterior CE angle, posterior CE angle, and acetabular anteversion on bony coverage of the acetabulum. This study is the first to investigate the correlation between functional parameters of the pelvis and spine and morphological parameters of the pelvis and acetabulum besides PI.

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4-year follow-up of ultrasound-based diagnosis and non-surgical treatment of developmental dysplasia of the hip in mongolia: a prospective cohort study

Ultraschall in der Medizin - European Journal of Ultrasound ◽

10.1055/s-0036-1587724 ◽

2016 ◽

Vol 37 (S 01) ◽

Cited By ~ 1

Author(s):

T Baumann ◽

B Munkhuu ◽

B Chuluunbaatar ◽

R Schmid ◽

S Essig

Keyword(s):

Cohort Study ◽

Surgical Treatment ◽

Prospective Cohort Study ◽

Prospective Cohort ◽

Developmental Dysplasia ◽

Dysplasia Of The Hip ◽

Non Surgical Treatment

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Faculty Opinions recommendation of Avascular necrosis following closed reduction for treatment of developmental dysplasia of the hip: a systematic review.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.729524230.793540307 ◽

2017 ◽

Author(s):

Edilson Forlin

Keyword(s):

Systematic Review ◽

Avascular Necrosis ◽

Closed Reduction ◽

Developmental Dysplasia ◽

Dysplasia Of The Hip

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Screening of Developmental Dysplasia of the Hip in Neonates with Breech Presentation

مجلة دراسات الطفولة ◽

10.21608/jsc.2015.60708 ◽

2015 ◽

Vol 18 (10.2015) ◽

pp. 0-0

Keyword(s):

Breech Presentation ◽

Developmental Dysplasia ◽

Dysplasia Of The Hip

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Prediction of the requirement of open reduction for developmental dysplasia of the hip

Journal of International Medical Research ◽

10.1177/0300060517717357 ◽

2017 ◽

Vol 46 (1) ◽

pp. 54-61 ◽

Cited By ~ 8

Author(s):

Nabil Alassaf

Keyword(s):

Open Reduction ◽

Area Under The Curve ◽

Internal Validity ◽

Developmental Dysplasia ◽

Estimation Model ◽

Cross Sectional ◽

Noninvasive Treatment ◽

Dysplasia Of The Hip ◽

Logistic Regression Equation ◽

Objective Tool

Objective Closed reduction (CR) is a noninvasive treatment for developmental dysplasia of the hip (DDH), and this treatment is confirmed intraoperatively. This study aimed to develop a preoperative estimation model of the probability of requiring open reduction (OR) for DDH. Methods The study design was cross-sectional by screening all patients younger than 2 years who had attempted CR between October 2012 and July 2016 by a single surgeon. Potential diagnostic determinants were sex, age, side, bilaterality, International Hip Dysplasia Institute (IHDI) grade, and acetabular index (AI). An intraoperative arthrogram was the reference standard. A logistic regression equation was built from a reduced model. Bootstrapping was performed for internal validity. Results A total of 164 hips in 104 patients who met the inclusion criteria were analysed. The prevalence of CR was 72.2%. Independent factors for OR were older age, higher IHDI grade, and lower AI. The probability of OR = 1/[1 + exp − (−2.753 + 0.112 × age (months) + 1.965 × IHDI grade III (0 or 1) + 3.515 × IHDI grade IV (0 or 1) − 0.058 × AI (degrees)]. The area under the curve was 0.79. Conclusion This equation is an objective tool that can be used to estimate the requirement for OR.

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Accuracy of New Deep Learning Model-Based Segmentation and Key-Point Multi-Detection Method for Ultrasonographic Developmental Dysplasia of the Hip (DDH) Screening

Diagnostics ◽

10.3390/diagnostics11071174 ◽

2021 ◽

Vol 11 (7) ◽

pp. 1174

Author(s):

Si-Wook Lee ◽

Hee-Uk Ye ◽

Kyung-Jae Lee ◽

Woo-Young Jang ◽

Jong-Ha Lee ◽

...

Keyword(s):

Deep Learning ◽

Intraclass Correlation ◽

Alpha Angle ◽

Learning Model ◽

Developmental Dysplasia ◽

Human Observer ◽

Intraobserver Variability ◽

Cad System ◽

Deep Learning Model ◽

Dysplasia Of The Hip

Hip joint ultrasonographic (US) imaging is the golden standard for developmental dysplasia of the hip (DDH) screening. However, the effectiveness of this technique is subject to interoperator and intraobserver variability. Thus, a multi-detection deep learning artificial intelligence (AI)-based computer-aided diagnosis (CAD) system was developed and evaluated. The deep learning model used a two-stage training process to segment the four key anatomical structures and extract their respective key points. In addition, the check angle of the ilium body balancing level was set to evaluate the system’s cognitive ability. Hence, only images with visible key anatomical points and a check angle within ±5° were used in the analysis. Of the original 921 images, 320 (34.7%) were deemed appropriate for screening by both the system and human observer. Moderate agreement (80.9%) was seen in the check angles of the appropriate group (Cohen’s κ = 0.525). Similarly, there was excellent agreement in the intraclass correlation coefficient (ICC) value between the measurers of the alpha angle (ICC = 0.764) and a good agreement in beta angle (ICC = 0.743). The developed system performed similarly to experienced medical experts; thus, it could further aid the effectiveness and speed of DDH diagnosis.

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