Department of Radiology & Diagnostic Imaging, University of Alberta, Edmonton, Canada.
Exo Inc, Santa Clara, USA.
Sci Rep. 2023 Jun 7;13(1):9224. doi: 10.1038/s41598-023-35603-9.
Developmental dysplasia of the hip (DDH) is a common cause of premature osteoarthritis. This osteoarthritis can be prevented if DDH is detected by ultrasound and treated in infancy, but universal DDH screening is generally not cost-effective due to the need for experts to perform the scans. The purpose of our study was to evaluate the feasibility of having non-expert primary care clinic staff perform DDH ultrasound using handheld ultrasound with artificial intelligence (AI) decision support. We performed an implementation study evaluating the FDA-cleared MEDO-Hip AI app interpreting cine-sweep images obtained from handheld Philips Lumify probe to detect DDH. Initial scans were done by nurses or family physicians in 3 primary care clinics, trained by video, powerpoint slides and brief in-person. When the AI app recommended follow-up (FU), we first performed internal FU by a sonographer using the AI app; cases still considered abnormal by AI were referred to pediatric orthopedic clinic for assessment. We performed 369 scans in 306 infants. Internal FU rates were initially 40% for nurses and 20% for physicians, declining steeply to 14% after ~ 60 cases/site: 4% technical failure, 8% normal at sonographer FU using AI, and 2% confirmed DDH. Of 6 infants referred to pediatric orthopedic clinic, all were treated for DDH (100% specificity); 4 had no risk factors and may not have otherwise been identified. Real-time AI decision support and a simplified portable ultrasound protocol enabled lightly trained primary care clinic staff to perform hip dysplasia screening with FU and case detection rates similar to costly formal ultrasound screening, where the US scan is performed by a sonographer and interpreted by a radiologist/orthopedic surgeon. This highlights the potential utility of AI-supported portable ultrasound in primary care.
发育性髋关节发育不良（DDH）是导致早发性骨关节炎的常见原因。如果通过超声检查发现 DDH 并在婴儿期进行治疗，这种骨关节炎是可以预防的，但由于需要专家进行扫描，因此普遍进行 DDH 筛查通常是不划算的。我们的研究目的是评估非专业的初级保健诊所工作人员使用带有人工智能（AI）决策支持的手持式超声进行 DDH 超声检查的可行性。我们进行了一项实施研究，评估了使用经过 FDA 批准的 MEDO-Hip AI 应用程序对从手持式飞利浦 Lumify 探头获得的电影扫描图像进行 DDH 检测的可行性。最初的扫描由 3 家初级保健诊所的护士或家庭医生完成，他们通过视频、幻灯片和简短的面对面培训接受培训。当 AI 应用程序建议进行随访（FU）时，我们首先由超声科医生使用 AI 应用程序进行内部 FU；如果 AI 仍然认为病例异常，则将其转诊至小儿矫形科诊所进行评估。我们对 306 名婴儿进行了 369 次扫描。护士的内部 FU 率最初为 40%，医生为 20%，在每个诊所完成大约 60 例后急剧下降至 14%：4%的技术故障、4%的 AI 超声 FU 正常、2%的确诊 DDH。转诊至小儿矫形科诊所的 6 名婴儿均接受了 DDH 治疗（特异性 100%）；其中 4 名婴儿无风险因素，否则可能无法识别。实时 AI 决策支持和简化的便携式超声协议使经过轻度培训的初级保健诊所工作人员能够进行髋关节发育不良筛查，其 FU 和病例检出率与昂贵的正式超声筛查相似，在正式超声筛查中，超声扫描由超声科医生进行，由放射科医生/矫形外科医生进行解释。这突显了 AI 支持的便携式超声在初级保健中的潜在应用。
