Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2026-03-26 @ 3:19 PM
Ignite Modification Date:
2026-03-26 @ 3:19 PM
NCT ID:
NCT07488260
Brief Summary:
The goal of this prospective, multicentre clinical investigation is to evaluate whether an artificial intelligence (AI)-supported software application (Prelux) can assist clinicians in the diagnostic assessment of developmental dysplasia of the hip (DDH) during routine ultrasound screening in infants.
The main questions it aims to answer are: Does the diagnostic classification generated by the Prelux application agree with the classification obtained by physicians using standard ultrasound examination according to the Graf method? Can the Prelux application reliably identify key anatomical landmarks and angles required for DDH assessment?
Researchers will compare the AI-generated diagnostic results with those obtained from standard ultrasound examinations performed by physicians to evaluate the level of agreement between the two approaches.
Participants will:
undergo a routine hip ultrasound examination performed by a physician according to the Graf method,
have ultrasound images analyzed by the Prelux application,
have the AI-generated results compared with the physician's assessment.
Detailed Description:
The purpose of this prospective, multicentre clinical investigation is to evaluate the effectiveness of the Prelux application in routine clinical settings, specifically by comparing the application-generated diagnostic results with those obtained from standard ultrasound examinations conducted by physicians.
The IMD was chosen for clinical evaluation because its AI algorithms have shown promising results in identifying key anatomical landmarks, justifying its transition from development to clinical investigation. This study has been designed based on comprehensive pre-clinical verification and validation data, including reliability, usability, and cybersecurity testing, to demonstrate the device's effectiveness in supporting clinicians during DDH assessment. Unlike traditional physical medical devices, the IMD is a digital solution composed of several integrated modules, including a Physician Portal, an AI diagnostic suite, and a Decision-Support Module. The potential indications for using AI-based diagnostic tools like the IMD are extensive in pediatric orthopedics. Such digital tools could increasingly be used to support the early identification of DDH, which affects approximately
1 in 100 infants. Early detection is critical, as late diagnosis could be associated with degenerative joint disease and the need for complex surgical interventions. In cases of routine screening, AI-based diagnostic tools are expected to help maintain the integrity of the diagnostic workflow by ensuring that only high-quality, standard-plane images are used for classification. In future clinical practice, AI-supported tools may meaningfully improve diagnostic quality and efficiency, potentially setting new standards for early intervention.
Within this framework, the IMD represents a new generation of diagnostic aids that enhance the benefits of ultrasound screening, especially for high-risk groups (female sex, breech presentation, or family history).
Study:
NCT07488260
Study Brief:
Protocol Section:
NCT07488260