Observational studyThe international journal of cardiovascular imaging2018
Computer-aided analysis of 64- and 320-slice coronary computed tomography angiography: a comparison with expert human interpretation.
Observational study in The international journal of cardiovascular imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Do plaque-related factors affect the diagnostic performance of an artificial intelligence coronary-assisted diagnosis system? Comparison with invasive coronary angiography.European radiology · 2022Article
- Artificial Intelligence: A Shifting Paradigm in Cardio-Cerebrovascular Medicine.Journal of clinical medicine · 2021Review
- Cardiovascular imaging 2018 in the International Journal of Cardiovascular Imaging.The international journal of cardiovascular imaging · 2019Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Routine use of CCTA to triage Emergency Department (ED) chest pain can reduce ED length of stay while providing accurate diagnoses. We evaluated the effectiveness of using Computer Aided Diagnosis in the triage of low to intermediate risk emergency chest pain patients with Coronary Computed Tomographic Angiography (CCTA). Using 64 and 320 slice CT scanners, we compared the diagnostic capability of computer aided diagnosis to human readers in 923 ED patients with chest pain. We calculated sensitivity, specificity, Positive Predictive Value and Negative Predictive Value for cases performed on each scanner. We calculated the area under the Receiver Operator Curve (ROC) comparing results for the two scanners to Computer Aided Diagnosis performance as compared to the human reader. We examined index and 30 Day outcomes by diagnosis for each scanner and the human reader. 60% of cases could be triaged by the computer. Sensitivity was approximately 85% for both scanners, with specificity at 50.6% for the 64 slice and at 56.5% for the 320 slice scanner (per person measures). The NPV was 97.8 and 97.1 for the 64 and 320 slice scanners, respectively. Results for the four major vessels were similar with negative predictive values ranging from 97 to 100%. The ROC for Computer Aided Diagnosis for the 64 and 320 Slice Scanners, using the human reader as the gold standard was 0.6794 and 0.7097 respectively. The index and 30 day outcomes were consistent for the human reader and Computer Aided Diagnosis interpretation. Although Computer Aided Diagnosis with CCTA cannot serve completely as a substitute for human reading, it offers excellent potential as a triage tool in busy EDs.
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Registered trials
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