AI Screening Tool Based on X-Rays Improves Early Detection of Decreased Bone Density in a Clinical Setting.

IF 3.7 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Andrew N Jayarajah, Angela Atinga, Linda Probyn, Thiru Sivakumaran, Monique Christakis, Anastasia Oikonomou
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引用次数: 0

Abstract

Purpose: Osteoporosis is an under-screened musculoskeletal disorder that results in diminished quality of life and significant burden to the healthcare system. We aimed to evaluate the ability of Rho, an artificial intelligence (AI) tool, to prospectively identify patients at-risk for low bone mineral density (BMD) from standard x-rays, its adoption rate by radiologists, and acceptance by primary care providers (PCPs).

Methods: Patients ≥50 years were recruited when undergoing an x-ray of a Rho-eligible body part for any clinical indication. Questionnaires were completed at baseline and 6-month follow-up, and PCPs of "Rho-Positive" patients (those likely to have low BMD) were asked for feedback. Positive predictive value (PPV) was calculated in patients who returned within 6 months for a DXA.

Results: Of 1145 patients consented, 987 had x-rays screened by Rho, and 655 were flagged as Rho-Positive. Radiologists included this finding in 524 (80%) of reports. Of all Rho-Positive patients, 125 had a DXA within 6 months; Rho had a 74% PPV for DXA T-Score <-1. From 51 PCP responses, 78% found Rho beneficial. Of 389 patients with follow-up questionnaire data, a greater proportion of Rho-Positive versus -negative patients had discussed bone health with their PCP since study start (36% vs 18%, P < .001), or were newly diagnosed with osteoporosis (11% vs 5%; P = .03).

Conclusion: By identifying patients at-risk of low BMD, with acceptability of reporting by radiologists and generally positive feedback from PCPs, Rho has the potential to improve low screening rates for osteoporosis by leveraging existing x-ray data.

基于x射线的人工智能筛查工具提高了临床环境中骨密度降低的早期检测。
目的:骨质疏松症是一种未被筛查的肌肉骨骼疾病,它会导致生活质量下降和医疗保健系统的重大负担。我们旨在评估Rho(一种人工智能(AI)工具)从标准x射线中前瞻性识别低骨密度(BMD)风险患者的能力,放射科医生的采用率以及初级保健提供者(pcp)的接受度。方法:招募年龄≥50岁的患者,并对符合rho条件的身体部位进行x线检查。在基线和6个月随访时完成问卷调查,并要求“rho阳性”患者(可能具有低骨密度的患者)的pcp反馈。在6个月内返回DXA的患者中计算阳性预测值(PPV)。结果:在1145名同意的患者中,987名患者接受了Rho x射线筛查,655名患者被标记为Rho阳性。放射科医生在524份(80%)报告中纳入了这一发现。在所有rh阳性患者中,125例在6个月内发生DXA;Rho的DXA T-Score PPV为74% (P = .03)。结论:通过识别低骨密度风险患者,放射科医生的报告可接受性和pcp的普遍积极反馈,Rho有可能利用现有的x射线数据改善骨质疏松症的低筛查率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.20
自引率
12.90%
发文量
98
审稿时长
6-12 weeks
期刊介绍: The Canadian Association of Radiologists Journal is a peer-reviewed, Medline-indexed publication that presents a broad scientific review of radiology in Canada. The Journal covers such topics as abdominal imaging, cardiovascular radiology, computed tomography, continuing professional development, education and training, gastrointestinal radiology, health policy and practice, magnetic resonance imaging, musculoskeletal radiology, neuroradiology, nuclear medicine, pediatric radiology, radiology history, radiology practice guidelines and advisories, thoracic and cardiac imaging, trauma and emergency room imaging, ultrasonography, and vascular and interventional radiology. Article types considered for publication include original research articles, critically appraised topics, review articles, guest editorials, pictorial essays, technical notes, and letter to the Editor.
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