Global Effects of Focal Brain Tumors on Functional Complexity and Network Robustness: A Prospective Cohort Study

Abstract BACKGROUND Neurosurgical management of brain tumors has entered a paradigm of supramarginal resections that demands thorough understanding of peritumoral functional effects. Historically, the effects of tumors have been believed to be local, and long-range effects have not been considered. OBJECTIVE To test the hypothesis that tumors affect the brain globally, producing long-range gradients in cortical function. METHODS Resting-state functional magnetic resonance imaging (fMRI) data were acquired from 11 participants with glioblastoma and split into discovery and validation datasets in a single-center prospective cohort study. Fractal complexity was computed with a wavelet-based estimator of the Hurst exponent. Distance-related effects of the tumors were tested with a tumor mask-dilation technique and parcellation of the underlying Hurst maps. RESULTS Fractal complexity demonstrates a penumbra of suppression in the peritumoral region. At a global level, as distance from the tumor increases, this initial suppression is balanced by a subsequent overactivity before finally normalizing. These effects were best fit by a quadratic model and were consistent across different network construction pipelines. The Hurst exponent was correlated with graph theory measures of centrality including network robustness, but graph theory measures did not demonstrate distance-dependent effects. CONCLUSION This work provides evidence supporting the theory that focal brain tumors produce long-range gradients in function. Consequently, the effects of focal lesions need to be interpreted in terms of the global changes on functional complexity and network architecture rather than purely in terms of functional localization. Determining whether peritumoral changes represent potential plasticity may facilitate extended resection of tumors without functional cost. Connectome, Fractal, Functional MRI, Glioblastoma, Neurooncology ABBREVIATIONS ABBREVIATIONS   ANCOVA analysis of covariance   ANOVA analysis of variance   ANTs advanced normalization tools   BOLD blood oxygenation level-dependent   fMRI functional magnetic resonance imaging   ME-ICA multiecho independent component analysis A new philosophy of supra-marginal resection has entered the vocabulary of neuro-oncology whereby surgical excision is extended beyond the confines of a lesion as it is visible on standard structural imaging. This paradigm is based on the identification of tumor infiltration beyond the contrast-enhancing margin,1-4 fluorescence-guided imaging that can identify potentially infiltrated brain at surgery,5,6 clinical studies correlating extended resections with improved survival,7-10 and potentially improved effectiveness of adjuvant therapies.11 However, extending surgery outside the lesion margins comes with the risk of intruding on eloquent brain and consequently the potential of neurological impairment. Therefore, understanding the function of the peritumoral brain is of paramount importance. This requirement to accurately map brain function led to many notable contributions from neurosurgery in understanding functional neuroanatomy.12,13 However, the traditional approach to understanding the effects of focal tumors per se on brain function is somewhat limited. Firstly, the effects of brain lesions on the surrounding tissue are believed to be only local (ie, through structural disruption), and potential long-range effects are overlooked. Furthermore, function itself is viewed as being uniform and consequently represented as a binary outcome (ie, brain either is or is not eloquent); considering function as a continuous variable has not been investigated. Understanding putative long-range effects of brain tumors and nonbinary gradients in function may allow more accurate prediction of the effects of tumor removal and insight into mechanisms of plasticity-related recovery. Fractal analysis of resting-state functional magnetic resonance imaging (fMRI) data offers the potential to understanding putative long-range gradients in brain function. Fractals are signals that display scale invariance; that is, they have similar features regardless of the scale at which they are viewed. Fractal signals are pervasive in nature (examples include coastlines, snowflakes, and ocean waves) and in the brain (neuronal membrane potentials, neural field potentials as well as electroencephalography, magnetoencephalography, and blood oxygenation level-dependent [BOLD] contrast endogenous signals).14 From a fractal perspective, healthy homeostasis emphasizes the complexity of the underlying biological processes rather than regular steady-state behavior.15,16 In the brain, this complexity is believed to enable adaptation to stimuli or other challenges, while simpler and less complex dynamics are indicative of less advantageous function or disease.17-20 Connectomics is a novel multidisciplinary paradigm that naturally views the brain as a complex network of individual components interacting through continuous communication and offers a window into the effects of focal tumors at the global level.21 Furthermore, graph theory analysis of brain networks unlocks a new terminology with which to describe brain functional neuroanatomy and for predictive modeling of, for example, the effects of tumor removal and how this is related to network robustness.22 Combining fractal and network analysis methods provides a complimentary approach to identifying putative wide-ranging effects of focal brain tumors on signal complexity and network robustness. In this work, the concept that tumors only lead to local effects on brain function is challenged, and a new theory that considers the global effects of a tumor is proposed that can augment our current brain mapping techniques. BOLD sensitive, resting-state fMRI was used to map brain function with data-driven analysis of fractal complexity and functional connectivity at the whole brain level. It was hypothesized that tumors would produce long-range effects outside of their margin as depicted on structural magnetic resonance imaging (MRI) and that there would be gradients of BOLD signal and functional connectivity extending away from the tumor. Evidence is presented to support the theory that focal brain tumors produce long-range and nonlinear gradients in function. METHODS Design The study was approved by the Local Regional Ethics Committee (protocol number10/H0308/23) and was a single-center prospective cohort design. All participants provided written informed consent. Inclusion criteria were the MRI appearance of a tumor consistent with a glioblastoma. All participants had a confirmed glioblastoma at local histological review according to World Health Organization criteria.23 Resective surgery was performed in all cases under general anesthesia using an operating microscope (OPMI Pentero 900, Carl Zeiss Meditec AG, Oberkochen, Germany) with fluorescence guidanc (...truncated)