Document Detail


Computer-aided diagnosis for detection of lacunar infarcts on MR images: ROC analysis of radiologists' performance.
MedLine Citation:
PMID:  22215250     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The purpose of this study was to retrospectively evaluate radiologist performance in detection of lacunar infarcts on T1- and T2-weighted images, without and with the use of a computer-aided diagnosis (CAD) scheme. Thirty T1-weighted and 30 T2-weighted MR images obtained from 30 patients were used for assessing observer performance. These images were acquired using the fast spin-echo sequence with a 1.5-T MR imaging scanner. The group included 15 patients (age range, 48-83 years; mean age, 67.2 years; 10 men and five women) with a lacunar infarct and 15 patients (age range, 39-76 years; mean age, 64.0 years; eight men and seven women) without lacunar infarcts. Nine radiologists participated in the study. The radiologists initially interpreted the T1- and T2-weighted images without and then with the use of CAD, which indicated their confidence levels regarding the presence (or absence) of lacunar infarcts and the most likely position of a lesion on each MR scan. The observers' performance without and with the computer output was evaluated by performing receiver operating characteristic analysis. For the nine radiologists, the mean area under the best-fit binormal receiver operating characteristic curve plotted for unit square values of radiologists who interpreted the images without and with the scheme were 0.891 and 0.937, respectively. The performance of the radiologists improved significantly when they used the computer output (p=0.032). The CAD scheme has potential to improve the accuracy of radiologists' performance in detection of lacunar infarcts.
Authors:
Yoshikazu Uchiyama; Takahiko Asano; Hiroki Kato; Takeshi Hara; Masayuki Kanematsu; Hiroaki Hoshi; Toru Iwama; Hiroshi Fujita
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of digital imaging     Volume:  25     ISSN:  1618-727X     ISO Abbreviation:  J Digit Imaging     Publication Date:  2012 Aug 
Date Detail:
Created Date:  2012-07-04     Completed Date:  2012-12-18     Revised Date:  2013-08-15    
Medline Journal Info:
Nlm Unique ID:  9100529     Medline TA:  J Digit Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  497-503     Citation Subset:  IM    
Affiliation:
Department of Computer and Control Engineering, Oita National College of Technology, 1666 Maki, Oita City, 870-0512, Japan. uchiyama@oita-ct.ac.jp
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MeSH Terms
Descriptor/Qualifier:
Adult
Aged
Aged, 80 and over
Clinical Competence / standards*,  statistics & numerical data
Diagnosis, Computer-Assisted / methods,  standards*
Female
Humans
Magnetic Resonance Imaging / methods*
Male
Middle Aged
ROC Curve*
Radiology / methods,  standards*,  statistics & numerical data
Retrospective Studies
Stroke, Lacunar / diagnosis*
Comments/Corrections

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


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