Exploring functional information among various brain regions across time enables understanding of healthy aging process and holds great promise for age-related brain disease diagnosis. This paper proposed a method to explore fractal complexity of the resting-state functional magnetic resonance imaging (rs-fMRI) signal in the human brain across the adult lifespan using Hurst exponent (HE). We took advantage of the examined rs-fMRI data from 116 adults 19 to 85 years of age (44.3 ± 19.4 years, 49 females) from NKI/Rockland sample. Region-wise and voxel-wise analyses were performed to investigate the effects of age, gender, and their interaction on complexity. In region-wise analysis, we found that the healthy aging is accompanied by a loss of complexity in frontal and parietal lobe and increased complexity in insula, limbic, and temporal lobe. Meanwhile, differences in HE between genders were found to be significant in parietal lobe (p = 0.04, corrected). However, there was no interaction between gender and age. In voxel-wise analysis, the significant complexity decrease with aging was found in frontal and parietal lobe, and complexity increase was found in insula, limbic lobe, occipital lobe, and temporal lobe with aging. Meanwhile, differences in HE between genders were found to be significant in frontal, parietal, and limbic lobe. Furthermore, we found age and sex interaction in right parahippocampal gyrus (p = 0.04, corrected). Our findings reveal HE variations of the rs-fMRI signal across the human adult lifespan and show that HE may serve as a new parameter to assess healthy aging process.

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Major depressive disorder (MDD) is a leading world-wide psychiatric disorder with high recurrence rate, therefore, it is desirable to identify current MDD (cMDD) and remitted MDD (rMDD) for their appropriate therapeutic interventions. In the study, 19 cMDD, 19 rMDD and 19 well-matched healthy controls (HC) were enrolled and scanned with the resting-state functional magnetic resonance imaging (rs-fMRI). The Hurst exponent (HE) of rs-fMRI in AAL-90 and AAL-1024 atlases were calculated and compared between groups. Then, a radial basis function (RBF) based support vector machine was proposed to identify every pair of the cMDD, rMDD and HC groups using the abnormal HE features, and a leave-one-out cross-validation was used to evaluate the classification performance. Applying the proposed method with AAL-1024 and AAL-90 atlas respectively, 87% and 84% subjects were correctly identified between cMDD and HC, 84% and 71% between rMDD and HC, and 89% and 74% between cMDD and rMDD. Our results indicated that the HE was an effective feature to distinguish cMDD and rMDD from HC, and the recognition performances with AAL-1024 parcellation were better than that with the conventional AAL-90 parcellation.

The inflow angle of intracranial aneurysms (IAs) can impact the hemodynamics of IAs, therefore it is likely to contribute to IA clinical rupture risk stratification. This study aimed to assess the effect of inflow angle on the hemodynamics of IAs, as well as its potential ability to predict IA rupture risk. A novel algorithm was developed to build a series of inflow angle models on patient-specific IA models, which were reconstructed from IA 3DRA image data of eleven clinical patients. Fully coupled fluid-structure interaction (FSI) simulations were performed to quantify hemodynamic characteristics of the established IA models with various inflow angles. Hemodynamic parameters including wall shear stress (WSS), flow velocity, flow pattern, inflow zone, impingement region, pressure, and energy loss (EL) were calculated and analyzed. It was demonstrated from the analysis that a rise in the IA inflow angle is associated with the following hemodynamic changes: more direct blood flowed into the aneurysm sac, higher velocity at the upside of the aneurysm, upregulated flow velocity and WSS in the aneurysm, more complicated flow patterns, extended inflow zone, the impingement region moving upward from the neck to the apex of the aneurysm, and higher WSS and larger flow velocity at the inflow zone of the IAs. Therefore, the proposed method may be helpful in exploring the hemodynamic variations of IAs with inflow angles. The findings could be conducive to hemodynamic studies on the association between IA inflow angle and its rupture risk.

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