Computer-aided detection of pulmonary embolism at CT pulmonary angiography: can it improve performance of inexperienced readers?
Purpose: To evaluate the effect of a computer-aided detection (CAD) algorithm on the performance of novice readers for detection of pulmonary embolism (PE) at CT pulmonary angiography (CTPA).Materials and Methods: We included CTPA examinations of 79 patients (50 female, 52 ± 18 years). Studies were...
| Published in: | European Radiology Vol. 21; no. 6; pp. 1214 - 1224 |
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| Main Authors: | , , , , , , , , , , , , , , , , , , , |
| Format: | research Journal Article |
| Published: |
Springer Nature
Jun2011
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104891255&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104891255 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Jun2011 vid: 21 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104891255 60411129 NLM21225269 2011040866 10.1007/s00330-010-2050-x NLM21225269 104891255 ppf: 1214 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Computer-aided detection of pulmonary embolism at CT pulmonary angiography: can it improve performance of inexperienced readers? aug: au: Blackmon KN Florin C Bogoni L McCain JW Koonce JD Lee H Bastarrika G Thilo C Costello P Salganicoff M Joseph Schoepf U Blackmon, Kevin N Florin, Charles Bogoni, Luca McCain, Joshua W Koonce, James D Lee, Heon Bastarrika, Gorka Thilo, Christian Costello, Philip affil: Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226 25 Courtenay Drive, Charleston, SC 29401, USA sug: subj: Algorithms Angiography Methods Professional Competence Pulmonary Artery Radiography Pulmonary Embolism Radiography Radiographic Image Interpretation, Computer-Assisted Methods Tomography, X-Ray Computed Methods Artificial Intelligence Female Male Middle Age Observer Bias Reproducibility of Results Sensitivity and Specificity South Carolina Middle Aged: 45-64 years Female Male ab: Purpose: To evaluate the effect of a computer-aided detection (CAD) algorithm on the performance of novice readers for detection of pulmonary embolism (PE) at CT pulmonary angiography (CTPA).Materials and Methods: We included CTPA examinations of 79 patients (50 female, 52 ± 18 years). Studies were evaluated by two independent inexperienced readers who marked all vessels containing PE. After 3 months all studies were reevaluated by the same two readers, this time aided by CAD prototype. A consensus read by three expert radiologists served as the reference standard. Statistical analysis used χ(2) and McNemar testing.Results: Expert consensus revealed 119 PEs in 32 studies. For PE detection, the sensitivity of CAD alone was 78%. Inexperienced readers' initial interpretations had an average per-PE sensitivity of 50%, which improved to 71% (p < 0.001) with CAD as a second reader. False positives increased from 0.18 to 0.25 per study (p = 0.03). Per-study, the readers initially detected 27/32 positive studies (84%); with CAD this number increased to 29.5 studies (92%; p = 0.125).Conclusion: Our results suggest that CAD significantly improves the sensitivity of PE detection for inexperienced readers with a small but appreciable increase in the rate of false positives. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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