Computer-Aided Detection of Pulmonary Nodules in Computed Tomography Using ClearReadCT.
This study evaluates the accuracy of a computer-aided detection (CAD) application for pulmonary nodular lesions (PNL) in computed tomography (CT) scans, the ClearReadCT (Riverain Technologies). The study was retrospective for 106 biopsied PNLs from 100 patients. Seventy-five scans were Contrast-Enha...
| Published in: | Journal of Medical Systems Vol. 43; no. 3; pp. 1 - 2 |
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| Main Authors: | , , , , , |
| Format: | diagnostic images research tables/charts Journal Article |
| Published: |
Springer Nature
Mar2019
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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=135041247&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 135041247 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Mar2019 vid: 43 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 135041247 135041247 135041247 10.1007/s10916-019-1180-1 135041247 ppf: 1 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Computer-Aided Detection of Pulmonary Nodules in Computed Tomography Using ClearReadCT. aug: au: Wagner, Anne-Kathrin Hapich, Arno Psychogios, Marios Nikos Teichgräber, Ulf Malich, Ansgar Papageorgiou, Ismini affil: Institute of Diagnostic and Interventional Radiology, University Hospital Jena, Am Klinikum 1, 07747, Jena, Germany sug: subj: Solitary Pulmonary Nodule Diagnosis Tomography, X-Ray Computed Methods Software Radiographic Image Interpretation, Computer-Assisted Evaluation Human Retrospective Design Biopsy Contrast Media Diagnostic Use Image Enhancement Descriptive Statistics Fisher's Exact Test McNemar's Test Predictive Value of Tests Lung Radiography Multidetector Computed Tomography Equipment and Supplies Picture Archiving and Communication Systems Equipment and Supplies Data Analysis Software Chi Square Test Linear Regression Pearson's Correlation Coefficient Spearman's Rank Correlation Coefficient One-Way Analysis of Variance Mann-Whitney U Test ROC Curve kappa Statistic Interrater Reliability ab: This study evaluates the accuracy of a computer-aided detection (CAD) application for pulmonary nodular lesions (PNL) in computed tomography (CT) scans, the ClearReadCT (Riverain Technologies). The study was retrospective for 106 biopsied PNLs from 100 patients. Seventy-five scans were Contrast-Enhanced (CECT) and 25 received no enhancer (NECT). Axial reconstructions in soft-tissue and lung kernel were applied at three different slice thicknesses, 0.75 mm (CECT/NECT n = 25/6), 1.5 mm (n = 18/9) and 3.0 mm (n = 43/18). We questioned the effect of (1) enhancer, (2) kernel and (3) slice thickness on the CAD performance. Our main findings are: (1) Vessel suppression is effective and specific in both NECT and CECT. (2) Contrast enhancement significantly increased the CAD sensitivity from 60% in NECT to 80% in CECT, P = 0.025 Fischer's exact test. (3) The CAD sensitivity was 84% in 3 mm slices compared to 68% in 0.75 mm slices, P > 0.2 Fischer's exact test. (4) Small lesions of low attenuation were detected with higher sensitivity. (5) Lung kernel reconstructions increased the false positive rate without affecting the sensitivity (P > 0.05 McNemar's test). In conclusion, ClearReadCT showed an optimized sensitivity of 84% and a positive predictive value of 67% in enhanced lung scans with thick, soft kernel reconstructions. NECT, thin slices and lung kernel reconstruction were associated with inferior performance. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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