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Suketu Bhavsar, Bhanu B. Gowda, Maulini Bhavsar | Journal of Paediatrics and Child Health | (2025)
Primary Link Pubmed DOI Openalex Full text (OA)

Abstract

AI demonstrated comparable effectiveness to physicians in detecting DDH. However, limited evaluation on external datasets restricts its generalisability. Further research incorporating diverse datasets and real-world applications is needed to assess its broader clinical impact on DDH diagnosis.

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Sample Definition And Size

The systematic review included 23 studies: 15 studies using ultrasound (US) images with a total of 8,315 images, and 8 studies using pelvic radiographs with a total of 7,091 images. The studies involved children under 16 years at risk of or suspected to have developmental dysplasia of the hip (DDH) ([pubmed.ncbi.nlm.nih.gov](https://pubmed.ncbi.nlm.nih.gov/41015898/?utm_source=openai)).

Study Type

This is a systematic review of prospective and retrospective cohort diagnostic accuracy studies, following Cochrane Collaboration Diagnostic Test Accuracy Working Group guidelines, with risk of bias assessed using the QUADAS‑2 tool ([pubmed.ncbi.nlm.nih.gov](https://pubmed.ncbi.nlm.nih.gov/41015898/?utm_source=openai)).

Conflicts Of Interest

The authors declared no conflicts of interest ([pubmed.ncbi.nlm.nih.gov](https://pubmed.ncbi.nlm.nih.gov/41015898/?utm_source=openai)).

Results Summary

For pelvic radiographs: area under the curve (AUC) ranged from 0.80 to 0.99; sensitivity ranged from 92.86% to 100%; specificity ranged from 95.65% to 99.82% ([pubmed.ncbi.nlm.nih.gov](https://pubmed.ncbi.nlm.nih.gov/41015898/?utm_source=openai)). For ultrasound images: AUC ranged from 0.90 to 0.99; sensitivity ranged from 86.54% to 100%; specificity ranged from 62.5% to 100% ([pubmed.ncbi.nlm.nih.gov](https://pubmed.ncbi.nlm.nih.gov/41015898/?utm_source=openai)).

Referenced In

Mercedes C.
a month ago
AI Papers and Discussion

🍼 Why reading baby hip ultrasounds is harder than you think—and how AI is stepping in to help.

Ever had an ultrasound? Now imagine trying to get a perfect picture of a squirming infant's hip joint while they're crying and moving. That's the reality of screening for developmental dysplasia of the hip (DDH), a condition affecting 1–3% of babies that can cause lifelong disability if missed.

The problem? 🎯 Too few experts, too many babies, and results that vary wildly depending on who's holding the probe.

A new systematic review & meta-analysis by Azmi et al., 2026, just published in Pediatric Radiology, brings together the strongest evidence yet on AI-assisted infant hip ultrasound—and the results are promising:

🔍 Key Findings from Azmi et al. (2026):

  • High diagnostic accuracy: Pooled sensitivity 92% (95% CI 86–95%) and specificity 96% (95% CI 91–98%) across 9 studies with 6,351 hips

    • Compiled 29 studies but analysed only 9 who provided 2×2 data using bivariate random-effects model.

  • Fast to learn: Operators need only ~1–2 hours of training to use AI-assisted systems

  • Quicker scans: Acquisition times drop by 20–50%

🤩 Compared to other reviews like Bhavsar et al., 2025 & Kamath et al., 2026, this meta-analysis analysed raw imaging data rather than final statistical predictions, making this a promising census for DDH. The authors then close the discussion by calling for multi-centre trials - testing that spans across different hospitals and environments.

What's your take? Is AI ready to assist or even replace the expert eye?

Fun Fact🤓: The "Graf method" requires precise positioning and angle measurements that take years to master. Miss the angle by a few degrees, and you miss the diagnosis or even send healthy babies for unnecessary treatments.

  • A 2022 paper by Oelen et al., 2022 claims that AI precision outperforms trained physicians, with an error of 3.9° vs. physician error of 7.1° for alpha angles

If you'd like a comprehensive read on the current trends in paediatric orthopaedic disorders, check out this review on recent developments: Current Trends and Future Directions in the Diagnosis and Management of Pediatric Orthopedic Disorders

Image credit: kidshealth.org

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