Automated detection of pulmonary embolism in CT pulmonary angiograms using an AI-powered algorithm

Performance of an artificial intelligence tool with real-time clinical workflow integration – Detection of intracranial hemorrhage and pulmonary embolism

“…For our PE study we achieved a rather low sensitivity of 0.73 when compared to the study by Weikert et al, who reached a sensitivity level of 0.93 [18]. Firstly, this can be explained by a high prevalence of chronic emboli in our study population (9/19 cases).…”

“…However, the sensitivity and PPV were 0.84 and 0.61 in our study, and remain moderate in comparison with previous studies, in which a sensitivity of 0.95 and 0.98 PPV was obtained [19]. Weikert et al, stated that prior research with a sensitivity above 0.85 accepted more false positive findings, which increase the amount of false positive cases, thereby increasing the radiologist's workload and time to therapy initiation [18].…”

“…A commercially available, FDA-and CE-cleared (European Medical Devices Directive 93/42/EEC M5) AI tool, based on convolutional neural networks (Aidoc version 1.3, Tel Aviv, Israel) was implemented in our radiological workflow. The algorithm was trained and tested by a dataset that included approximately 50,000 non-contrast head CT studies for the detection of ICH [17] and 28,000 CTPA studies for the detection of PE [18], collected from 9 different sites and 17 different scanner models. According to the manufacturer's specifications, CT acquisition should be performed with a 64-slice scanner or higher and with a reconstructed slice thickness between 0.625 and 5.1 mm for ICH and 0.5-3.0 mm for PE.…”

“…However, certain roles within specific pathologies have not yet been fully investigated. Implementing an AI tool during a realtime radiology work stream, has the potential to react earlier and/or even notice lesions that can be easily overlooked by a radiologist [13,[15][16][17][18].…”

“…They found a falsenegative rate of radiologists for ICH detection at 1.6%, and thus the technology could serve by minimizing false negatives [19]. Weikert et al found a high degree of diagnostic accuracy for PE detection on CTPAs, and a balanced sensitivity and specificity of 0.93 and 0.96 [18]. Also with PE, sensitivity, specificity, positive and negative predictive values and accuracy compared with gold standard senior radiologists were reported, 0.85, 0.97, 0.85, 0.97 and 0.95 respectively [18].…”