Rcadia Medical Imaging, 157 Yafo str., 35251 Haifa, Israel.
Int J Comput Assist Radiol Surg. 2011 Sep;6(5):705-11. doi: 10.1007/s11548-011-0552-x. Epub 2011 Apr 16.
Computer-aided detection (CAD) established its role in medical imaging as second reader aimed to boost the diagnostic accuracy of human interpreter. As the diagnostic performance of CAD systems improves and more imaging modalities are covered, CAD steps forward to fill new, more demanding positions in medical practice. In this paper, we investigate how the introduction of CAD for emergency diagnostic imaging shifts the use case paradigm from second reader to initial interpreter and triage tool.
We start from extracting common characteristics of exiting CAD systems and compare them to those for emergency diagnostic imaging modalities. Based on the deduced requirements, we define a new class of CAD systems-Computer-aided simple triage (CAST) and explore its properties, use case scenarios and clinical benefits. We also discuss the differences between the CAST, CAD, and automated computer diagnosis.
A CAST system should serve as a simple triage tool performing a fully automatic analysis and providing initial classification at "per study" level. Positive studies are then immediately analyzed by expert reader, thus reducing delay for patients with critical conditions, while negative studies can be initially dealt with by less experienced staff. Automatic image quality and study complexity assessment can serve as reading prioritization key. CAST system should exhibit sufficiently high specificity, while not compromising the high sensitivity per study.
CAST systems have a potential to become an "enabling technology" allowing introduction of advanced imaging techniques into the emergency workflow protocols by addressing the reader unavailability and reading prioritization problems.
计算机辅助检测 (CAD) 作为第二位读者,旨在提高人类解释器的诊断准确性,在医学成像中确立了其地位。随着 CAD 系统诊断性能的提高,以及涵盖更多的成像方式,CAD 逐渐在医疗实践中填补新的、更具挑战性的职位。在本文中,我们研究了将 CAD 引入急诊诊断成像如何将用例范例从第二位读者转变为初始解释器和分诊工具。
我们从提取现有 CAD 系统的共同特征开始,并将其与急诊诊断成像方式的特征进行比较。基于推导的要求,我们定义了一类新的 CAD 系统——计算机辅助简单分诊 (CAST),并探索了其特性、用例场景和临床效益。我们还讨论了 CAST、CAD 和自动计算机诊断之间的区别。
CAST 系统应作为一种简单的分诊工具,执行全自动分析,并在“每个研究”级别提供初步分类。阳性研究立即由专家读者进行分析,从而减少了危急情况下患者的延迟,而阴性研究可以由经验较少的工作人员初步处理。自动图像质量和研究复杂性评估可以作为阅读优先级的关键。CAST 系统应具有足够高的特异性,同时不影响每个研究的高灵敏度。
CAST 系统有可能成为一种“使能技术”,通过解决读者可用性和阅读优先级问题,将先进的成像技术引入急诊工作流程协议。