title: Cerebral Glioma Grading Using Bayesian Network with Features Extracted from Multiple Modalities of Magnetic Resonance Imaging.
abstract: Many modalities of magnetic resonance imaging (MRI) have been confirmed to be of great diagnostic value in glioma grading. Contrast enhanced T1-weighted imaging allows the recognition of blood-brain barrier breakdown. Perfusion weighted imaging and MR spectroscopic imaging enable the quantitative measurement of perfusion parameters and metabolic alterations respectively. These modalities can potentially improve the grading process in glioma if combined properly. In this study, Bayesian Network, which is a powerful and flexible method for probabilistic analysis under uncertainty, is used to combine features extracted from contrast enhanced T1-weighted imaging, perfusion weighted imaging and MR spectroscopic imaging. The networks were constructed using K2 algorithm along with manual determination and distribution parameters learned using maximum likelihood estimation. The grading performance was evaluated in a leave-one-out analysis, achieving an overall grading accuracy of 92.86% and an area under the curve of 0.9577 in the receiver operating characteristic analysis given all available features observed in the total 56 patients. Results and discussions show that Bayesian Network is promising in combining features from multiple modalities of MRI for improved grading performance.
authors.affiliation: The Laboratory for Medical Electronics, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, Jiangsu, China.|Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, China.
authors.forename: Jisu
authors.initials: J
authors.lastname: Hu
authors.affiliation: Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Wenbo
authors.initials: W
authors.lastname: Wu
authors.affiliation: Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Bin
authors.initials: B
authors.lastname: Zhu
authors.affiliation: Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Huiting
authors.initials: H
authors.lastname: Wang
authors.affiliation: Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Renyuan
authors.initials: R
authors.lastname: Liu
authors.affiliation: Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Ming
authors.initials: M
authors.lastname: Li
authors.affiliation: Department of Neurosurgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Yongbo
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Department of Oncology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Yan
authors.affiliation: Department of Pathology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Fengnan
authors.initials: F
authors.lastname: Niu
authors.affiliation: Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Chuanshuai
authors.initials: C
authors.lastname: Tian
authors.affiliation: Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Kun
authors.initials: K
authors.lastname: Wang
authors.affiliation: Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Haiping
authors.initials: H
authors.lastname: Yu
authors.affiliation: Philips Healthcare, Shanghai, China.
authors.forename: Weibo
authors.initials: W
authors.lastname: Chen
authors.affiliation: The Laboratory for Medical Electronics, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, Jiangsu, China.
authors.forename: Suiren
authors.initials: S
authors.lastname: Wan
authors.affiliation: The Laboratory for Medical Electronics, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, Jiangsu, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Sun
authors.affiliation: Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
authors.forename: Bing
authors.initials: B
authors.lastname: Zhang
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D019540:Area Under Curve; D001499:Bayes Theorem; D001932:Brain Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology*; D017352:Echo-Planar Imaging; D005260:Female; D005910:Glioma / Q000000981:diagnostic imaging / Q000473:pathology*; D006801:Humans; D016013:Likelihood Functions; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D012372:ROC Curve; D011859:Radiography; D059629:Signal-To-Noise Ratio