利用人工智能对可能为良性乳腺超声发现的延迟随访患者进行分诊。

IF 2.4 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Ultrasonography Pub Date : 2025-03-01 Epub Date: 2025-01-21 DOI:10.14366/usg.24206
Tali Amir, Kristen Coffey, Jeffrey S Reiner, Varadan Sevilimedu, Victoria L Mango
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引用次数: 0

摘要

目的:本研究旨在评估我院使用人工智能(AI)决策支持(DS)作为临床工作流程的一部分,对2019冠状病毒病(COVID-19)大流行期间延迟随访的乳腺成像报告和数据系统(BI-RADS) 3超声病变患者进行分类,并对照随后的成像和/或病理随访结果。方法:本回顾性研究纳入了2019年8月至2019年12月进行BI-RADS 3类(即可能为良性)乳房超声评估的患者,这些患者的随访在COVID-19大流行期间被推迟,使用Koios DS breast AI对其乳房超声进行了重新审查,作为对这些患者进行分类的临床工作流程的一部分。将Koios DS的输出与乳腺癌存在与否的真实结果进行比较,该结果由影像学随访至少2年的分辨率/稳定性或病理结果确定。结果:本研究纳入161名女性(平均年龄52岁),BI-RADS 3类超声病变221例。221例病变中,2例确诊为恶性肿瘤(恶性率0.9%)。Koios DS评估112/221例病变为良性(50.7%),42/221例病变为可能良性(19.0%),64/221例病变为可疑(29.0%),3/221例病变为可能恶性(1.4%)。Koios DS的灵敏度为100% (2/2;95%置信区间[CI], 16%至100%),特异性为70% (154/219;95% CI, 64% ~ 76%),阴性预测值100% (154/154;95% CI, 98% ~ 100%),假阳性率为30% (65/219;95% CI, 24% - 36%)。结论:在自然灾害或资源有限的情况下,当许多随访预约被推迟时,乳腺超声AI DS可以帮助筛选可能是良性乳腺超声的患者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Utilization of artificial intelligence to triage patients with delayed follow-up of probably benign breast ultrasound findings.

Purpose: This study aimed to evaluate our institution's experience in using artificial intelligence (AI) decision support (DS) as part of the clinical workflow to triage patients with Breast Imaging Reporting and Data System (BI-RADS) 3 sonographic lesions whose follow-up was delayed during the coronavirus disease 2019 (COVID-19) pandemic, against subsequent imaging and/or pathologic follow-up results.

Methods: This retrospective study included patients with a BI-RADS category 3 (i.e., probably benign) breast ultrasound assessment from August 2019-December 2019 whose follow-up was delayed during the COVID-19 pandemic and whose breast ultrasounds were re-reviewed using Koios DS Breast AI as part of the clinical workflow for triaging these patients. The output of Koios DS was compared with the true outcome of a presence or absence of breast cancer defined by resolution/stability on imaging follow-up for at least 2 years or pathology results.

Results: The study included 161 women (mean age, 52 years) with 221 BI-RADS category 3 sonographic lesions. Of the 221 lesions, there were two confirmed cancers (0.9% malignancy rate). Koios DS assessed 112/221 lesions (50.7%) as benign, 42/221 lesions (19.0%) as probably benign, 64/221 lesions (29.0%) as suspicious, and 3/221 lesions (1.4%) as probably malignant. Koios DS had a sensitivity of 100% (2/2; 95% confidence interval [CI], 16% to 100%), specificity of 70% (154/219; 95% CI, 64% to 76%), negative predictive value of 100% (154/154; 95% CI, 98% to 100%), and false-positive rate of 30% (65/219; 95% CI, 24% to 36%).

Conclusion: When many follow-up appointments are delayed, e.g., natural disaster, or scenarios where resources are limited, breast ultrasound AI DS can help triage patients with probably benign breast ultrasounds.

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来源期刊
Ultrasonography
Ultrasonography Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
5.10
自引率
6.50%
发文量
78
审稿时长
15 weeks
期刊介绍: Ultrasonography, the official English-language journal of the Korean Society of Ultrasound in Medicine (KSUM), is an international peer-reviewed academic journal dedicated to practice, research, technology, and education dealing with medical ultrasound. It is renamed from the Journal of Korean Society of Ultrasound in Medicine in January 2014, and published four times per year: January 1, April 1, July 1, and October 1. Original articles, technical notes, topical reviews, perspectives, pictorial essays, and timely editorial materials are published in Ultrasonography covering state-of-the-art content. Ultrasonography aims to provide updated information on new diagnostic concepts and technical developments, including experimental animal studies using new equipment in addition to well-designed reviews of contemporary issues in patient care. Along with running KSUM Open, the annual international congress of KSUM, Ultrasonography also serves as a medium for cooperation among physicians and specialists from around the world who are focusing on various ultrasound technology and disease problems and relevant basic science.
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