Diffusion kurtosis imaging can efficiently assess the glioma grade and cellular proliferation

Abstract

// Rifeng Jiang 1, * , Jingjing Jiang 1, * , Lingyun Zhao 1 , Jiaxuan Zhang 1 , Shun Zhang 1 , Yihao Yao 1 , Shiqi Yang 1 , Jingjing Shi 1 , Nanxi Shen 1 , Changliang Su 1 , Ju Zhang 1 , Wenzhen Zhu 1 1 Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China * These authors have contributed equally to this work Correspondence to: Wenzhen Zhu, e-mail: zhuwenzhen@hotmail.com Keywords: diffusion kurtosis imaging, glioma, grading, cellular proliferation, Ki-67 Received: April 29, 2015      Accepted: October 22, 2015      Published: November 03, 2015 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.