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Updated: Nov 28, 2025
High Frequency Ultrasound for the Analysis of Fetal and Placental Development In Vivo
Published on: November 8, 2018
3-D Ultrasound Imaging Reliability of Measuring Dysplasia Metrics in Infants
Niamul Quader1, Antony J Hodgson2, Kishore Mulpuri3
1Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, British Columbia, Canada.
Insights
This study introduces 3-D ultrasound (US) metrics for diagnosing developmental dysplasia of the hip. These new automated 3-D US metrics significantly reduce variability compared to traditional 2-D methods.
Area of Science:
- Medical Imaging
- Orthopedics
- Artificial Intelligence
Background:
- Developmental dysplasia of the hip (DDH) is a spectrum of hip abnormalities.
- Current 2-D ultrasound (US) metrics for DDH diagnosis exhibit high inter-exam variability.
- Improved reproducibility in DDH assessment is clinically needed.
Purpose of the Study:
- To develop and evaluate novel 3-D ultrasound (US)-derived dysplasia metrics for diagnosing developmental dysplasia of the hip.
- To demonstrate the enhanced reproducibility of automated 3-D US metrics compared to existing 2-D methods.
Main Methods:
- Utilized a random forest technique to exclude non-bone regions, reducing outliers.
- Employed rotation-invariant and intensity-invariant filters for robust bone segmentation.
- Developed a slice-based learning and 3-D reconstruction strategy for femoral head probability mapping.
- Formulated new 3-D US-derived dysplasia metrics.
Main Results:
- The proposed method automatically computes 3-D US-derived dysplasia metrics.
- Validation on 40 infant hip examinations showed approximately 70% reduction in variability for key metrics.
- Automated 3-D US metrics demonstrated considerably higher reproducibility than 2-D counterparts.
Conclusions:
- Automated 3-D ultrasound offers a more reproducible method for assessing developmental dysplasia of the hip.
- The novel 3-D US metrics have the potential to improve diagnostic accuracy and consistency in DDH evaluation.
Abstract:
Developmental dysplasia of the hip is a hip abnormality that ranges from mild acetabular dysplasia to irreducible femoral head dislocations. While 2-D B-mode ultrasound (US)-based dysplasia metrics or disease metrics are currently used clinically to diagnose developmental dysplasia of the hip, such estimates suffer from high inter-exam variability. In this work, we propose and evaluate 3-D US-derived dysplasia metrics that are automatically computed and demonstrate that these automatically derived dysplasia metrics are considerably more reproducible. The key features of our automatic method are (i) a random forest-based learning technique to remove regions across the coronal axis that do not contain bone structures necessary for dysplasia-metric extraction, thereby reducing outliers; (ii) a bone segmentation method that uses rotation-invariant and intensity-invariant filters, thus remaining robust to signal dropout and varying bone morphology; (iii) a novel slice-based learning and 3-D reconstruction strategy to estimate a probability map of the hypoechoic femoral head in the US volume; and (iv) formulae for calculating the 3-D US-derived dysplasia metrics. We validate our proposed method on real clinical data acquired from 40 infant hip examinations. Results show a considerable (around 70%) reduction in variability in two key 3-D US-derived dysplasia metrics compared with their 2-D counterparts.
