Document Detail


Efficacy of computer-aided detection as a second reader for 6-9-mm lesions at CT colonography: multicenter prospective trial.
MedLine Citation:
PMID:  23151831     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
PURPOSE: To assess the effect of computer-aided detection (CAD) as a second reader on the sensitivity and specificity of computed tomographic (CT) colonography in detecting 6-9-mm colorectal cancer (CRC) lesions.
MATERIALS AND METHODS: Individuals with clinical indications for colonoscopy--either for symptoms or as part of participating in a surveillance program or CRC screening--were prospectively enrolled at one of 10 academic centers between July 2007 and May 2009. Institutional review board approval was obtained at each clinical site, and all participants provided written informed consent. All participants underwent CT colonography and colonoscopy on the same day. Experienced readers interpreted the CT colonography images unassisted and then reviewed all colorectal lesion-like structures pinpointed by the CAD algorithm. Segmental unblinding of CT colonoscopy findings at colonoscopy was utilized. The sensitivity and specificity of unassisted and CAD-assisted reading in identifying individuals with 6-9-mm lesions were calculated and compared by means of pairwise analysis.
RESULTS: A total of 618 participants (mean age, 57.9 years; 54.5% male) were included in the final analysis. Of these participants, 464 (75.1%) had no lesions 6 mm or larger, and 52 (8.4%) had 6-9-mm lesions. The sensitivity of CT colonography with unassisted reading and that with CAD-assisted reading in identifying individuals with 6-9-mm lesions was 65.4% (95% confidence interval [CI]: 50.9%, 78.0%) and 76.9% (95% CI: 63.2%, 87.5%; P = .016), respectively. No significant change in specificity was observed: The specificity of CT colonography with unassisted and that with CAD-assisted reading was 91.8% (95% CI: 88.9%, 94.1%) and 90.9% (95% CI: 88.0%, 93.4%; P = .063), respectively. Evaluation of CAD candidates required an additional 1.6 minutes (25th-75th percentile: 1.0 minute to 3.4 minutes).
CONCLUSION: The addition of CAD to reading performed by experienced readers resulted in a significant benefit in the detection of 6-9-mm polyps at CT colonography in this cohort.
SUPPLEMENTAL MATERIAL: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12120376/-/DC1.
Authors:
Daniele Regge; Patrizia Della Monica; Giovanni Galatola; Cristiana Laudi; Antonella Zambon; Loredana Correale; Roberto Asnaghi; Brunella Barbaro; Claudia Borghi; Delia Campanella; Maria Carla Cassinis; Riccardo Ferrari; Andrea Ferraris; Cesare Hassan; Rita Golfieri; Franco Iafrate; Gabriella Iussich; Andrea Laghi; Roberto Massara; Emanuele Neri; Lapo Sali; Silvia Venturini; Giovanni Gandini
Publication Detail:
Type:  Clinical Trial; Journal Article; Multicenter Study; Research Support, Non-U.S. Gov't     Date:  2012-11-14
Journal Detail:
Title:  Radiology     Volume:  266     ISSN:  1527-1315     ISO Abbreviation:  Radiology     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2012-12-24     Completed Date:  2013-02-12     Revised Date:  2013-04-02    
Medline Journal Info:
Nlm Unique ID:  0401260     Medline TA:  Radiology     Country:  United States    
Other Details:
Languages:  eng     Pagination:  168-76     Citation Subset:  AIM; IM    
Copyright Information:
RSNA, 2012
Affiliation:
Radiology Unit, Institute for Cancer Research and Treatment, Candiolo, Italy.
Data Bank Information
Bank Name/Acc. No.:
ClinicalTrials.gov/NCT01399710
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Colonography, Computed Tomographic / methods*
Colorectal Neoplasms / radiography*
Female
Humans
Italy
Male
Middle Aged
Observer Variation
Pattern Recognition, Automated / methods*
Prospective Studies
Radiographic Image Enhancement / methods
Radiographic Image Interpretation, Computer-Assisted / methods*
Reproducibility of Results
Sensitivity and Specificity
Comments/Corrections
Erratum In:
Radiology. 2013 Mar;266(3):1000
Note: Golfieri, Rita [added]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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