title: Interactive Feature Space Explorer© for multi-modal magnetic resonance imaging.
abstract: Wider information content of multi-modal biomedical imaging is advantageous for detection, diagnosis and prognosis of various pathologies. However, the necessity to evaluate a large number images might hinder these advantages and reduce the efficiency. Herein, a new computer aided approach based on the utilization of feature space (FS) with reduced reliance on multiple image evaluations is proposed for research and routine clinical use. The method introduces the physician experience into the discovery process of FS biomarkers for addressing biological complexity, e.g., disease heterogeneity. This, in turn, elucidates relevant biophysical information which would not be available when automated algorithms are utilized. Accordingly, the prototype platform was designed and built for interactively investigating the features and their corresponding anatomic loci in order to identify pathologic FS regions. While the platform might be potentially beneficial in decision support generally and specifically for evaluating outlier cases, it is also potentially suitable for accurate ground truth determination in FS for algorithm development. Initial assessments conducted on two different pathologies from two different institutions provided valuable biophysical perspective. Investigations of the prostate magnetic resonance imaging data resulted in locating a potential aggressiveness biomarker in prostate cancer. Preliminary findings on renal cell carcinoma imaging data demonstrated potential for characterization of disease subtypes in the FS.
authors: Arlington Innovation Center: Health Research, Virginia Polytechnic Institute and State University, 900 N. Glebe Road, Arlington VA 22203, USA. Electronic address: alpay@vt.edu.
authors: Alpay
authors: A
authors: Özcan
authors: Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr., MSC 1182, Bldg. 10, Rm. 1B40, Bethesda, MD 20892-1088, USA. Electronic address: turkbeyi@mail.nih.gov.
authors: Barış
authors: B
authors: Türkbey
authors: Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr., MSC 1182, Bldg. 10, Rm. 1B40, Bethesda, MD 20892-1088, USA. Electronic address: pchoyke@mail.nih.gov.
authors: Peter L
authors: PL
authors: Choyke
authors: Memorial Sloan Kettering Cancer Center, 1275 York Ave C276, New York, NY 10065, USA. Electronic address: akino@mskcc.org.
authors: Oguz
authors: O
authors: Akin
authors: Memorial Sloan Kettering Cancer Center, 1275 York Ave C276, New York, NY 10065, USA. Electronic address: araso@mskcc.org.
authors: Ömer
authors: Ö
authors: Aras
authors: Arlington Innovation Center: Health Research, Virginia Polytechnic Institute and State University, 900 N. Glebe Road, Arlington VA 22203, USA. Electronic address: munsk@vt.edu.
authors: Seong K
authors: SK
authors: Mun
mesh_terms: D000465:Algorithms; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D064847:Multimodal Imaging / Q000379:methods*; D011467:Prostate / Q000473:pathology; D011471:Prostatic Neoplasms / Q000175:diagnosis*
keywords: Cancer imaging; Computer-aided detection and diagnosis; Multi-modal imaging; Multi-parametric imaging; Prostate cancer; Renal cancer