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1.
J Pediatr Orthop ; 42(4): e315-e323, 2022 Apr 01.
Artículo en Inglés | MEDLINE | ID: mdl-35125417

RESUMEN

BACKGROUND: Ultrasound for developmental dysplasia of the hip (DDH) is challenging for nonexperts to perform and interpret. Recording "sweep" images allows more complete hip assessment, suitable for automation by artificial intelligence (AI), but reliability has not been established. We assessed agreement between readers of varying experience and a commercial AI algorithm, in DDH detection from infant hip ultrasound sweeps. METHODS: We selected a full spectrum of poor-to-excellent quality images and normal to severe dysplasia, in 240 hips (120 single 2-dimensional images, 120 sweeps). For 12 readers (radiologists, sonographers, clinicians and researchers; 3 were DDH subspecialists), and a ultrasound-FDA-cleared AI software package (Medo Hip), we calculated interobserver reliability for alpha angle measurements by intraclass correlation coefficient (ICC2,1) and for DDH classification by Randolph Kappa. RESULTS: Alpha angle reliability was high for AI versus subspecialists (ICC=0.87 for sweeps, 0.90 for single images). For DDH diagnosis from sweeps, agreement was high between subspecialists (kappa=0.72), and moderate for nonsubspecialists (0.54) and AI (0.47). Agreement was higher for single images (kappa=0.80, 0.66, 0.49). AI reliability deteriorated more than human readers for the poorest-quality images. The agreement of radiologists and clinicians with the accepted standard, while still high, was significantly poorer for sweeps than 2D images (P<0.05). CONCLUSIONS: In a challenging exercise representing the wide spectrum of image quality and reader experience seen in real-world hip ultrasound, agreement on DDH diagnosis from easily obtained sweeps was only slightly lower than from single images, likely because of the additional step of selecting the best image. AI performed similarly to a nonsubspecialist human reader but was more affected by low-quality images.


Asunto(s)
Luxación Congénita de la Cadera , Luxación de la Cadera , Inteligencia Artificial , Luxación Congénita de la Cadera/diagnóstico por imagen , Humanos , Lactante , Variaciones Dependientes del Observador , Reproducibilidad de los Resultados , Ultrasonografía/métodos
2.
Ultrasound Q ; 30(2): 101-17, 2014 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-24850026

RESUMEN

Sonography is a commonly used modality for the investigation of abdominal symptoms in the pediatric population. It is a highly sensitive, readily available imaging modality that does not require ionizing radiation, iodinated contrast material, or anesthesia and can be performed at the bedside if necessary. Abdominal ultrasound is therefore often the first examination performed. This article presents an overview of the ultrasound characteristics of some of the most frequently encountered pathologies as well as some more rarely encountered entities. Our aim was to present a series of characteristic images of a wide gamut of pediatric abdominal conditions. The goal was to familiarize the reader with key sonographic features of both congenital and acquired gastrointestinal pathologies in children, making them more easily recognizable.


Asunto(s)
Abdomen/diagnóstico por imagen , Enfermedades Gastrointestinales/diagnóstico por imagen , Tracto Gastrointestinal/diagnóstico por imagen , Aumento de la Imagen/métodos , Posicionamiento del Paciente/métodos , Ultrasonografía/métodos , Adolescente , Niño , Preescolar , Femenino , Humanos , Lactante , Recién Nacido , Masculino
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