Journal of Digital Imaging

, Volume 25, Issue 4, pp 497–503 | Cite as

Computer-Aided Diagnosis for Detection of Lacunar Infarcts on MR Images: ROC Analysis of Radiologists’ Performance

  • Yoshikazu Uchiyama
  • Takahiko Asano
  • Hiroki Kato
  • Takeshi Hara
  • Masayuki Kanematsu
  • Hiroaki Hoshi
  • Toru Iwama
  • Hiroshi Fujita
Article

Abstract

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.

Keywords

Lacunar infarct Magnetic resonance (MR) Computer-aided diagnosis (CAD) Observer study Receiver operating characteristic (ROC) 

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Copyright information

© Society for Imaging Informatics in Medicine 2011

Authors and Affiliations

  • Yoshikazu Uchiyama
    • 1
  • Takahiko Asano
    • 2
  • Hiroki Kato
    • 2
  • Takeshi Hara
    • 3
  • Masayuki Kanematsu
    • 2
  • Hiroaki Hoshi
    • 2
  • Toru Iwama
    • 4
  • Hiroshi Fujita
    • 3
  1. 1.Department of Computer and Control EngineeringOita National College of TechnologyOita CityJapan
  2. 2.Department of Radiology, Graduate School of MedicineGifu UniversityGifuJapan
  3. 3.Department of Intelligent Image Information, Graduate School of MedicineGifu UniversityGifuJapan
  4. 4.Department of Neurosurgery, Graduate School of MedicineGifu UniversityGifuJapan

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