Impact of intelligent virtual and AI-based automated collimation functionalities on the efficiency of radiographic acquisitions

IF 2.5 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Radiography Pub Date : 2024-05-18 DOI:10.1016/j.radi.2024.05.002
A. Rasche , P. Brader , J. Borggrefe , H. Seuss , Z. Carr , A. Hebecker , G. ten Cate
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Abstract

Introduction

Intelligent virtual and AI-based collimation functionalities have the potential to enable an efficient workflow for radiographers, but the specific impact on clinical routines is still unknown. This study analyzes primarily the influence of intelligent collimation functionalities on the examination time and the number of needed interactions with the radiography system.

Methods

An observational study was conducted on the use of three camera-based intelligent features at five clinical sites in Europe and the USA: AI-based auto thorax collimation (ATC), smart virtual ortho (SVO) collimation for stitched long-leg and full-spine examinations, and virtual collimation (VC) at the radiography system workstation. Two people conducted semi-structured observations during routine examinations to collect data with the functionalities either activated or deactivated.

Results

Median exam duration was 31 vs. 45 s (p < 0.0001) for 95 thorax examinations with ATC and 94 without ATC. For stitched orthopedic examinations, 34 were performed with SVO and 40 without SVO, and the median exam duration was 62 vs. 82 s (p < 0.0001). The median time for setting the ortho range – i.e., the time between setting the upper and the lower limits of the collimation field – was 7 vs. 16 s for 39 examinations with SVO and 43 without SVO (p < 0.0001). In 109 thorax examinations with ATC and 112 without ATC, the median number of system interactions was 1 vs. 2 (p < 0.0001). VC was used to collimate in 2.4% and to check the collimation field in 68.5% of 292 observed chest and other examinations.

Conclusion

ATC and SVO enable the radiographer to save time during chest or stitched examinations. Additionally, ATC reduces machine interactions during chest examinations.

Implications for practice

System and artificial intelligence can support the radiographer during the image acquisition by providing a more efficient workflow.

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智能虚拟和基于人工智能的自动准直功能对射线采集效率的影响。
导言:基于虚拟和人工智能的智能准直功能有可能为放射技师提供高效的工作流程,但其对临床常规工作的具体影响尚不清楚。本研究主要分析了智能准直功能对检查时间的影响以及与放射成像系统的交互次数:方法:在欧洲和美国的五个临床基地对三种基于相机的智能功能的使用情况进行了观察研究:基于人工智能的自动胸部准直(ATC)、用于拼接长腿和全脊柱检查的智能虚拟正位(SVO)准直,以及放射成像系统工作站的虚拟准直(VC)。两人在常规检查过程中进行了半结构化观察,以收集激活或关闭这些功能时的数据:结果:检查时间的中位数为 31 秒对 45 秒(PATC 和 SVO 可使放射技师在进行胸部或缝合检查时节省时间。此外,ATC 还能减少胸部检查过程中的机器交互:对实践的启示:系统和人工智能可以通过提供更高效的工作流程,在图像采集过程中为放射技师提供支持。
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来源期刊
Radiography
Radiography RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.70
自引率
34.60%
发文量
169
审稿时长
63 days
期刊介绍: Radiography is an International, English language, peer-reviewed journal of diagnostic imaging and radiation therapy. Radiography is the official professional journal of the College of Radiographers and is published quarterly. Radiography aims to publish the highest quality material, both clinical and scientific, on all aspects of diagnostic imaging and radiation therapy and oncology.
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