Impact of a Computer-Aided Detection (CAD) System Integrated into a Picture Archiving and Communication System (PACS) on Reader Sensitivity and Efficiency for the Detection of Lung Nodules in Thoracic CT Exams.
The objective of this study is to assess the impact on nodule detection and efficiency using a computer-aided detection (CAD) device seamlessly integrated into a commercially available picture archiving and communication system (PACS). Forty-eight consecutive low-dose thoracic computed tomography st...
| Published in: | Journal of Digital Imaging Vol. 25; no. 6; pp. 771 - 782 |
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| Main Authors: | , , , , , , , , , , , |
| Format: | diagnostic images research tables/charts Journal Article |
| Published: |
Springer Nature
Dec2012
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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=104432752&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104432752 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Dec2012 vid: 25 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104432752 83184793 10.1007/s10278-012-9496-0 NLM22710985 104432752 ppf: 771 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Impact of a Computer-Aided Detection (CAD) System Integrated into a Picture Archiving and Communication System (PACS) on Reader Sensitivity and Efficiency for the Detection of Lung Nodules in Thoracic CT Exams. aug: au: Bogoni, Luca Ko, Jane Alpert, Jeffrey Anand, Vikram Fantauzzi, John Florin, Charles Koo, Chi Mason, Derek Rom, William Shiau, Maria Salganicoff, Marcos Naidich, David affil: Siemens Healthcare, Malvern 19355 USA sug: subj: Picture Archiving and Communication Systems Diagnosis, Computer Assisted Systems Integration Lung Pathology Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Algorithms Diagnosis, Computer Assisted Equipment and Supplies Time Factors Radiography, Thoracic Lung Neoplasms Diagnosis Retrospective Design Sample Size Sensitivity and Specificity P-Value Evaluation Research Descriptive Statistics Confidence Intervals Funding Source Human ab: The objective of this study is to assess the impact on nodule detection and efficiency using a computer-aided detection (CAD) device seamlessly integrated into a commercially available picture archiving and communication system (PACS). Forty-eight consecutive low-dose thoracic computed tomography studies were retrospectively included from an ongoing multi-institutional screening study. CAD results were sent to PACS as a separate image series for each study. Five fellowship-trained thoracic radiologists interpreted each case first on contiguous 5 mm sections, then evaluated the CAD output series (with CAD marks on corresponding axial sections). The standard of reference was based on three-reader agreement with expert adjudication. The time to interpret CAD marking was automatically recorded. A total of 134 true-positive nodules, measuring 3 mm and larger were included in our study; with 85 ≥ 4 and 50 ≥ 5 mm in size. Readers detection improved significantly in each size category when using CAD, respectively, from 44 to 57 % for ≥3 mm, 48 to 61 % for ≥4 mm, and 44 to 60 % for ≥5 mm. CAD stand-alone sensitivity was 65, 68, and 66 % for nodules ≥3, ≥4, and ≥5 mm, respectively, with CAD significantly increasing the false positives for two readers only. The average time to interpret and annotate a CAD mark was 15.1 s, after localizing it in the original image series. The integration of CAD into PACS increases reader sensitivity with minimal impact on interpretation time and supports such implementation into daily clinical practice. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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