title: Automatic estimation of midline shift in patients with cerebral glioma based on enhanced voigt model and local symmetry.
abstract: Cerebral glioma is one of the most aggressive space-occupying diseases, which will exhibit midline shift (MLS) due to mass effect. MLS has been used as an important feature for evaluating the pathological severity and patients' survival possibility. Automatic quantification of MLS is challenging due to deformation, complex shape and complex grayscale distribution. An automatic method is proposed and validated to estimate MLS in patients with gliomas diagnosed using magnetic resonance imaging (MRI). The deformed midline is approximated by combining mechanical model and local symmetry. An enhanced Voigt model which takes into account the size and spatial information of lesion is devised to predict the deformed midline. A composite local symmetry combining local intensity symmetry and local intensity gradient symmetry is proposed to refine the predicted midline within a local window whose size is determined according to the pinhole camera model. To enhance the MLS accuracy, the axial slice with maximum MSL from each volumetric data has been interpolated from a spatial resolution of 1 mm to 0.33 mm. The proposed method has been validated on 30 publicly available clinical head MRI scans presenting with MLS. It delineates the deformed midline with maximum MLS and yields a mean difference of 0.61 ± 0.27 mm, and average maximum difference of 1.89 ± 1.18 mm from the ground truth. Experiments show that the proposed method will yield better accuracy with the geometric center of pathology being the geometric center of tumor and the pathological region being the whole lesion. It has also been shown that the proposed composite local symmetry achieves significantly higher accuracy than the traditional local intensity symmetry and the local intensity gradient symmetry. To the best of our knowledge, for delineation of deformed midline, this is the first report on both quantification of gliomas and from MRI, which hopefully will provide valuable information for diagnosis and therapy. The study suggests that the size of the whole lesion and the location of tumor (instead of edema or the sum of edema and tumor) are more appropriate to determine the extent of deformation. Composite local symmetry is recommended to represent the local symmetry around the deformed midline. The proposed method could be potentially used to quantify the severity of patients with cerebral gliomas and other brain pathology, as well as to approximate midsagittal surface for brain quantification.
authors: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|University of Chinese Academy of Sciences, Beijing, China.
authors: Mingyang
authors: M
authors: Chen
authors: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|University of Chinese Academy of Sciences, Beijing, China.
authors: Ahmed
authors: A
authors: Elazab
authors: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|University of Chinese Academy of Sciences, Beijing, China.
authors: Fucang
authors: F
authors: Jia
authors: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|University of Chinese Academy of Sciences, Beijing, China.
authors: Jianhuang
authors: J
authors: Wu
authors: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|University of Chinese Academy of Sciences, Beijing, China.
authors: Guanglin
authors: G
authors: Li
authors: Linyi People's Hospital, Linyi, China.
authors: Xiaodong
authors: X
authors: Li
authors: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. qm.hu@siat.ac.cn.|University of Chinese Academy of Sciences, Beijing, China. qm.hu@siat.ac.cn.
authors: Qingmao
authors: Q
authors: Hu
mesh_terms: D001932:Brain Neoplasms / Q000473:pathology*; D004548:Elasticity; D005910:Glioma / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008962:Models, Theoretical; D014783:Viscosity
keywords: Cerebral glioma; Deformed midline; Local symmetry; Magnetic resonance imaging; Mechanical model