title: Diffusion kurtosis imaging can efficiently assess the glioma grade and cellular proliferation.
abstract: Conventional diffusion imaging techniques are not sufficiently accurate for evaluating glioma grade and cellular proliferation, which are critical for guiding glioma treatment. Diffusion kurtosis imaging (DKI), an advanced non-Gaussian diffusion imaging technique, has shown potential in grading glioma; however, its applications in this tumor have not been fully elucidated. In this study, DKI and diffusion weighted imaging (DWI) were performed on 74 consecutive patients with histopathologically confirmed glioma. The kurtosis and conventional diffusion metric values of the tumor were semi-automatically obtained. The relationships of these metrics with the glioma grade and Ki-67 expression were evaluated. The diagnostic efficiency of these metrics in grading was further compared. It was demonstrated that compared with the conventional diffusion metrics, the kurtosis metrics were more promising imaging markers in distinguishing high-grade from low-grade gliomas and distinguishing among grade II, III and IV gliomas; the kurtosis metrics also showed great potential in the prediction of Ki-67 expression. To our best knowledge, we are the first to reveal the ability of DKI to assess the cellular proliferation of gliomas, and to employ the semi-automatic method for the accurate measurement of gliomas. These results could have a significant impact on the diagnosis and subsequent therapy of glioma.
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Rifeng
authors.initials: R
authors.lastname: Jiang
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Jingjing
authors.initials: J
authors.lastname: Jiang
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Lingyun
authors.initials: L
authors.lastname: Zhao
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Jiaxuan
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Shun
authors.initials: S
authors.lastname: Zhang
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Yihao
authors.initials: Y
authors.lastname: Yao
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Shiqi
authors.initials: S
authors.lastname: Yang
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Jingjing
authors.initials: J
authors.lastname: Shi
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Nanxi
authors.initials: N
authors.lastname: Shen
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Changliang
authors.initials: C
authors.lastname: Su
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Ju
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Wenzhen
authors.initials: W
authors.lastname: Zhu
mesh_terms: D000328:Adult; D000704:Analysis of Variance; D001921:Brain / Q000000981:diagnostic imaging / Q000378:metabolism / Q000473:pathology; D001932:Brain Neoplasms / Q000175:diagnosis / Q000000981:diagnostic imaging*; D049109:Cell Proliferation; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D005910:Glioma / Q000175:diagnosis / Q000000981:diagnostic imaging*; D006801:Humans; D007150:Immunohistochemistry; D019394:Ki-67 Antigen / Q000378:metabolism; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D011446:Prospective Studies; D012372:ROC Curve; D011859:Radiography; D015203:Reproducibility of Results; D055815:Young Adult
chemical_list: D019394:Ki-67 Antigen
keywords: Ki-67; cellular proliferation; diffusion kurtosis imaging; glioma; grading