Computer-aided detection of metastatic brain tumors using magnetic resonance black-blood imaging

Seungwook Yang, Yoonho Nam, Min Oh Kim, Eung Yeop Kim, Jaeseok Park, Dong Hyun Kim

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)


Objectives: The objective of this study was to develop a computer-aided detection system for automated brain metastases detection using magnetic resonance black-blood imaging and compare its applicability with conventional magnetization-prepared rapid gradient echo (MP-RAGE) imaging. Materials and Methods: Twenty-six patients with brain metastases were imaged with a contrast-enhanced, 3-dimensional, whole-brain magnetic resonance black-blood pulse sequence. Approval from the institutional review board and informed consent from the patients were obtained. Preprocessing steps included B1 inhomogeneity correction and brain extraction. The computer-aided detection system used 3-dimensional template matching, which measured normalized cross-correlation coefficient to generate possible metastases candidates. An artificial neural network was used for classification after various volume features were extracted. The same detection procedure was tested with contrast-enhanced MP-RAGE, which was also acquired from the same patients. Results: The performance of the proposed detection method was measured by the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity values. In the black-blood case, detection process displayed an AUROC of 0.9355, a sensitivity value of 81.1%, and a specificity value of 98.2%. Magnetization-prepared rapid gradient echo data showed an AUROC of 0.6508, a sensitivity value of 30.2%, and a specificity value of 99.97%. Conclusions: The results demonstrate that accurate automated detection of metastatic brain tumors using contrast-enhanced black-blood imaging sequence is possible compared with using conventional contrast-enhanced MP-RAGE sequence.

Original languageEnglish
Pages (from-to)113-119
Number of pages7
JournalInvestigative radiology
Issue number2
Publication statusPublished - 2013 Feb


  • artificial neural network
  • black-blood imaging
  • brain metastases
  • computer-aided detection

ASJC Scopus subject areas

  • Medicine(all)


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