Quality assessment of expedited AI generated reformatted images for ED acquired CT abdomen and pelvis imaging

IF 2.3 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Abdominal Radiology Pub Date : 2024-09-18 DOI:10.1007/s00261-024-04578-0
Daniel Freedman, Barun Bagga, Kira Melamud, Thomas O’Donnell, Emilio Vega, Malte Westerhoff, Bari Dane
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Abstract

Purpose

Retrospectively compare image quality, radiologist diagnostic confidence, and time for images to reach PACS for contrast enhanced abdominopelvic CT examinations created on the scanner console by technologists versus those generated automatically by thin-client artificial intelligence (AI) mechanisms.

Methods

A retrospective PACS search identified adults who underwent an emergency department contrast-enhanced abdominopelvic CT in 07/2022 (Console Cohort) and 07/2023 (Server Cohort). Coronal and sagittal multiplanar reformatted images (MPR) were created by AI software in the Server cohort. Time to completion of MPR images was compared using 2-sample t-tests for all patients in both cohorts. Two radiologists qualitatively assessed image quality and diagnostic confidence on 5-point Likert scales for 50 consecutive examinations from each cohort. Additionally, they assessed for acute abdominopelvic findings. Continuous variables and qualitative scores were compared with the Mann-Whitney U test. A p < .05 indicated statistical significance.

Results

Mean[SD] time to exam completion in PACS was 8.7[11.1] minutes in the Console cohort (n = 728) and 4.6[6.6] minutes in the Server cohort (n = 892), p < .001. 50 examinations in the Console Cohort (28 women 22 men, 51[19] years) and Server cohort (27 women 23 men, 57[19] years) were included for radiologist review. Age, sex, CTDlvol, and DLP were not statistically different between the cohorts (all p > .05). There was no significant difference in image quality or diagnostic confidence for either reader when comparing the Console and Server cohorts (all p > .05).

Conclusion

Examinations utilizing AI generated MPRs on a thin-client architecture were completed approximately 50% faster than those utilizing reconstructions generated at the console with no statistical difference in diagnostic confidence or image quality.

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针对急诊室获取的腹部和盆腔 CT 成像,对加速人工智能生成的重新格式化图像进行质量评估
目的回顾性比较技术人员在扫描仪控制台上创建的对比增强腹盆腔 CT 检查图像与瘦客户端人工智能 (AI) 机制自动生成的检查图像在图像质量、放射医师诊断信心和图像到达 PACS 的时间方面的差异。方法回顾性 PACS 搜索确定了在 2022 年 7 月(控制台队列)和 2023 年 7 月(服务器队列)接受急诊科对比增强腹盆腔 CT 检查的成人。服务器队列中的冠状面和矢状面多平面重新格式化图像(MPR)由人工智能软件创建。对两个队列中的所有患者完成 MPR 图像的时间采用 2 样本 t 检验进行比较。两名放射科医生对每个队列中的 50 次连续检查使用 5 点李克特量表对图像质量和诊断信心进行定性评估。此外,他们还对急性腹盆腔发现进行了评估。连续变量和定性评分采用 Mann-Whitney U 检验进行比较。结果 控制台队列(n = 728)和服务器队列(n = 892)在 PACS 中完成检查的平均[标码]时间分别为 8.7[11.1]分钟和 4.6[6.6]分钟,p <.001。控制台队列(28 名女性,22 名男性,51[19]岁)和服务器队列(27 名女性,23 名男性,57[19]岁)中的 50 次检查被纳入放射科医生的审查范围。两组患者的年龄、性别、CTDlvol 和 DLP 均无统计学差异(均为 p >.05)。结论使用瘦客户端架构上人工智能生成的 MPR 完成检查比使用控制台生成的重建快约 50%,但在诊断信心或图像质量方面没有统计学差异。
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来源期刊
Abdominal Radiology
Abdominal Radiology Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
5.20
自引率
8.30%
发文量
334
期刊介绍: Abdominal Radiology seeks to meet the professional needs of the abdominal radiologist by publishing clinically pertinent original, review and practice related articles on the gastrointestinal and genitourinary tracts and abdominal interventional and radiologic procedures. Case reports are generally not accepted unless they are the first report of a new disease or condition, or part of a special solicited section. Reasons to Publish Your Article in Abdominal Radiology: · Official journal of the Society of Abdominal Radiology (SAR) · Published in Cooperation with: European Society of Gastrointestinal and Abdominal Radiology (ESGAR) European Society of Urogenital Radiology (ESUR) Asian Society of Abdominal Radiology (ASAR) · Efficient handling and Expeditious review · Author feedback is provided in a mentoring style · Global readership · Readers can earn CME credits
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