Physiological significance of R-fMRI indices: Can functional metrics differentiate structural lesions (brain tumors)?

Zhen Fan; Xiao Chen; Zeng-Xin Qi; Le Li; Bin Lu; Cong-Lin Jiang; Ren-Qing Zhu; Chao-Gan Yan; Liang Chen

doi:10.1016/j.nicl.2019.101741

Physiological significance of R-fMRI indices: Can functional metrics differentiate structural lesions (brain tumors)?

Neuroimage Clin. 2019:22:101741. doi: 10.1016/j.nicl.2019.101741. Epub 2019 Mar 1.

Authors

Zhen Fan¹, Xiao Chen², Zeng-Xin Qi¹, Le Li³, Bin Lu², Cong-Lin Jiang¹, Ren-Qing Zhu¹, Chao-Gan Yan⁴, Liang Chen⁵

Affiliations

¹ Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai Neurosurgical Clinical Center, Shanghai, China.
² CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
³ CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China; Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
⁴ CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China; Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Child and Adolescent Psychiatry, NYU Langone Medical Center School of Medicine, New York, NY, USA. Electronic address: ycg.yan@gmail.com.
⁵ Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai Neurosurgical Clinical Center, Shanghai, China. Electronic address: chenlianghs@126.com.

Abstract

Resting-state functional MRI (R-fMRI) research has recently entered the era of "big data", however, few studies have provided a rigorous validation of the physiological underpinnings of R-fMRI indices. Although studies have reported that various neuropsychiatric disorders exhibit abnormalities in R-fMRI measures, these "biomarkers" have not been validated in differentiating structural lesions (brain tumors) as a concept proof. We enrolled 60 patients with intracranial tumors located in the unilateral cranialcavity and 60 matched normal controls to test whether R-fMRI indices can differentiate tumors, which represents a prerequisite for adapting such indices as biomarkers for neuropsychiatric disorders. Common R-fMRI indices of tumors and their counterpart control regions, which were defined as the contralateral normal areas (for amplitude of low frequency fluctuations (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo) and degree centrality (DC)) and ipsilateral regions surrounding the tumors (for voxel-mirrored homotopic connectivity (VMHC)), were comprehensively assessed. According to robust paired t-tests with a Bonferroni correction, only VMHC (Fisher's r-to-z transformed) could successfully differentiate substantial tumors from their counterpart normal regions in patients. Furthermore, ALFF and DC were not able to differentiate tumor from normal unless Z-standardization was employed. To validate the lower power of the between-subject design compared to the within-subject design, each metric was calculated in a matched control group, and robust two-sample t-tests were used to compare the patient tumors and the normal controls at the same place. Similarly, only VMHC succeeded in differentiating significant differences between tumors and the sham tumor areas of normal controls. This study tested the premise of R-fMRI biomarkers for differentiating lesions, and brings a new understanding to physical significance of the Z-standardization.

Keywords: Biomarker; Cerebellum; Resting-state fMRI; Standardization; Tumor.

Publication types

Comparative Study
Research Support, Non-U.S. Gov't

MeSH terms

Adult
Aged
Brain Mapping / methods*
Brain Neoplasms / diagnostic imaging*
Brain Neoplasms / physiopathology
Cerebellum / diagnostic imaging*
Cerebellum / physiology*
Female
Humans
Magnetic Resonance Imaging / methods*
Male
Middle Aged
Young Adult