通过高分辨率超声波成像进行新型人工智能驱动的婴儿脑膜炎筛查

Hassan Sial, Francesc Carandell, Sara Ajanovic, Javier Jiménez, Rita Quesada, Fabião Santos, W. Chris Buck, Muhammad Sidat, UNITED Study Consortium, Quique Bassat, Beatrice Jobst, Paula Petrone
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摘要

背景 婴儿脑膜炎是一种危及生命的疾病,需要及时准确的诊断,以防止严重后果或死亡。金标准诊断需要进行腰椎穿刺(LP),以获取和分析脑脊液(CSF)。尽管腰椎穿刺是标准做法,但它是侵入性的,对病人有风险,而且结果往往是阴性的,这可能是由于穿刺本身产生的红细胞污染,也可能是由于这种疾病的发病率相对较低,尽管其发病率相对较低,但由于协议要求做腰椎穿刺以排除危及生命的感染。此外,在发病率最高的低收入地区,LP 和 CSF 检查很少可行,疑似脑膜炎病例通常采用经验性治疗。现在越来越需要无创、准确的诊断方法。
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Novel AI-Driven Infant Meningitis Screening from High Resolution Ultrasound Imaging
Background Infant meningitis can be a life-threatening disease and requires prompt and accurate diagnosis to prevent severe outcomes or death. Gold-standard diagnosis requires lumbar punctures (LP), to obtain and analyze cerebrospinal fluid (CSF). Despite being standard practice, LPs are invasive, pose risks for the patient and often yield negative results, either because of the contamination with red blood cells derived from the puncture itself, or due to the disease’s relatively low incidence due to the protocolized requirement to do LPs to discard a life-threatening infection in spite its relatively low incidence. Furthermore, in low-income settings, where the incidence is the highest, LPs and CSF exams are rarely feasible, and suspected meningitis cases are generally treated empirically. There’s a growing need for non-invasive, accurate diagnostic methods.
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