Literature DB >> 22215250

Computer-aided diagnosis for detection of lacunar infarcts on MR images: ROC analysis of radiologists' performance.

Yoshikazu Uchiyama1, Takahiko Asano, Hiroki Kato, Takeshi Hara, Masayuki Kanematsu, Hiroaki Hoshi, Toru Iwama, Hiroshi Fujita.   

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.

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Year:  2012        PMID: 22215250      PMCID: PMC3389095          DOI: 10.1007/s10278-011-9444-4

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  30 in total

1.  Computer-aided diagnosis to distinguish benign from malignant solitary pulmonary nodules on radiographs: ROC analysis of radiologists' performance--initial experience.

Authors:  Junji Shiraishi; Hiroyuki Abe; Roger Engelmann; Masahito Aoyama; Heber MacMahon; Kunio Doi
Journal:  Radiology       Date:  2003-05       Impact factor: 11.105

2.  Computerized detection of intracranial aneurysms for three-dimensional MR angiography: feature extraction of small protrusions based on a shape-based difference image technique.

Authors:  Hidetaka Arimura; Qiang Li; Yukunori Korogi; Toshinori Hirai; Shigehiko Katsuragawa; Yasuyuki Yamashita; Kazuhiro Tsuchiya; Kunio Doi
Journal:  Med Phys       Date:  2006-02       Impact factor: 4.071

3.  Improvement of automated detection method of lacunar infarcts in brain MR images.

Authors:  Yoshikazu Uchiyama; Ryujiro Yokoyama; Hiromichi Ando; Takahiko Asano; Hiroki Kato; Hiroyasu Yamakawa; Haruki Yamakawa; Takeshi Hara; Toru Iwama; Hiroaki Hoshi; Hiroshi Fujita
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2007

4.  Effect of a computer-aided diagnosis scheme on radiologists' performance in detection of lung nodules on radiographs.

Authors:  T Kobayashi; X W Xu; H MacMahon; C E Metz; K Doi
Journal:  Radiology       Date:  1996-06       Impact factor: 11.105

5.  Computer-aided detection with screening mammography in a university hospital setting.

Authors:  Robyn L Birdwell; Parul Bandodkar; Debra M Ikeda
Journal:  Radiology       Date:  2005-08       Impact factor: 11.105

6.  Screening mammography with computer-aided detection: prospective study of 12,860 patients in a community breast center.

Authors:  T W Freer; M J Ulissey
Journal:  Radiology       Date:  2001-09       Impact factor: 11.105

7.  Computer-aided detection versus independent double reading of masses on mammograms.

Authors:  Nico Karssemeijer; Johannes D M Otten; Andre L M Verbeek; Johanna H Groenewoud; Harry J de Koning; Jan H C L Hendriks; Roland Holland
Journal:  Radiology       Date:  2003-02-28       Impact factor: 11.105

8.  Silent lacunar infarction on magnetic resonance imaging (MRI): risk factors.

Authors:  S Shintani; T Shiigai; T Arinami
Journal:  J Neurol Sci       Date:  1998-09-18       Impact factor: 3.181

9.  Silent brain infarcts and white matter lesions increase stroke risk in the general population: the Rotterdam Scan Study.

Authors:  Sarah E Vermeer; Monika Hollander; Ewoud J van Dijk; Albert Hofman; Peter J Koudstaal; Monique M B Breteler
Journal:  Stroke       Date:  2003-04-10       Impact factor: 7.914

10.  Computer-aided detection of colorectal polyps: can it improve sensitivity of less-experienced readers? Preliminary findings.

Authors:  Mark E Baker; Luca Bogoni; Nancy A Obuchowski; Chandra Dass; Renee M Kendzierski; Erick M Remer; David M Einstein; Pascal Cathier; Anna Jerebko; Sarang Lakare; Andrew Blum; Dina F Caroline; Michael Macari
Journal:  Radiology       Date:  2007-10       Impact factor: 11.105

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  4 in total

1.  Eigenspace template matching for detection of lacunar infarcts on MR images.

Authors:  Yoshikazu Uchiyama; Akiko Abe; Chisako Muramatsu; Takeshi Hara; Junji Shiraishi; Hiroshi Fujita
Journal:  J Digit Imaging       Date:  2015-02       Impact factor: 4.056

2.  Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin.

Authors:  Mohsen Ghafoorian; Nico Karssemeijer; Tom Heskes; Mayra Bergkamp; Joost Wissink; Jiri Obels; Karlijn Keizer; Frank-Erik de Leeuw; Bram van Ginneken; Elena Marchiori; Bram Platel
Journal:  Neuroimage Clin       Date:  2017-02-04       Impact factor: 4.881

3.  A CAD System for Hemorrhagic Stroke.

Authors:  Wieslaw L Nowinski; Guoyu Qian; Daniel F Hanley
Journal:  Neuroradiol J       Date:  2014-08-29

Review 4.  Multi-reader multi-case studies using the area under the receiver operator characteristic curve as a measure of diagnostic accuracy: systematic review with a focus on quality of data reporting.

Authors:  Thaworn Dendumrongsup; Andrew A Plumb; Steve Halligan; Thomas R Fanshawe; Douglas G Altman; Susan Mallett
Journal:  PLoS One       Date:  2014-12-26       Impact factor: 3.240

  4 in total

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