Fernando F. Paiva

Magnetic resonance imaging quantification of regional cerebral blood flow and cerebrovascular reactivity to carbon dioxide in normotensive and hypertensive rats

Hypertension afflicts 25% of the general population and over 50% of the elderly. In the present work, arterial spin labeling MRI was used to non-invasively quantify regional cerebral blood flow (CBF), cerebrovascular resistance and CO(2) reactivity in spontaneously hypertensive rats (SHR) and in normotensive Wistar Kyoto rats (WKY), at two different ages (3 months and 10 months) and under the effects of two anesthetics, α-chloralose and 2% isoflurane (1.5 MAC). Repeated CBF measurements were highly consistent, differing by less than 10% and 18% within and across animals, respectively. Under α-chloralose, whole brain CBF at normocapnia did not differ between groups (young WKY: 61 ± 3ml/100g/min; adult WKY: 62 ± 4ml/100g/min; young SHR: 70 ± 9ml/100g/min; adult SHR: 69 ± 8ml/100g/min), indicating normal cerebral autoregulation in SHR. At hypercapnia, CBF values increased significantly, and a linear relationship between CBF and PaCO(2) levels was observed. In contrast, 2% isoflurane impaired cerebral autoregulation. Whole brain CBF in SHR was significantly higher than in WKY rats at normocapnia (young SHR: 139 ± 25ml/100g/min; adult SHR: 104 ± 23ml/100g/min; young WKY: 55± 9ml/100g/min; adult WKY: 71 ± 19ml/100g/min). CBF values increased significantly with increasing CO(2); however, there was a clear saturation of CBF at PaCO(2) levels greater than 70mmHg in both young and adult rats, regardless of absolute CBF values, suggesting that isoflurane interferes with the vasodilatory mechanisms of CO(2). This behavior was observed for both cortical and subcortical structures. Under either anesthetic, CO(2) reactivity values in adult SHR were decreased, confirming that hypertension, when combined with age, increases cerebrovascular resistance and reduces cerebrovascular compliance.

A Neural Signature of Affiliative Emotion in the Human Septohypothalamic Area

Comparative studies have established that a number of structures within the rostromedial basal forebrain are critical for affiliative behaviors and social attachment. Lesion and neuroimaging studies concur with the importance of these regions for attachment and the experience of affiliation in humans as well. Yet it remains obscure whether the neural bases of affiliative experiences can be differentiated from the emotional valence with which they are inextricably associated at the experiential level. Here we show, using functional MRI, that kinship-related social scenarios evocative of affiliative emotion induce septal–preoptic–anterior hypothalamic activity that cannot be explained by positive or negative emotional valence alone. Our findings suggest that a phylogenetically conserved ensemble of basal forebrain structures, especially the septohypothalamic area, may play a key role in enabling human affiliative emotion. Our finding of a neural signature of human affiliative experience bears direct implications for the neurobiological mechanisms underpinning impaired affiliative experiences and behaviors in neuropsychiatric conditions.

Functional Dissociation of Ventral Frontal and Dorsomedial Default Mode Network Components During Resting State and Emotional Autobiographical Recall

Humans spend a substantial share of their lives mind‐wandering. This spontaneous thinking activity usually comprises autobiographical recall, emotional, and self‐referential components. While neuroimaging studies have demonstrated that a specific brain “default mode network” (DMN) is consistently engaged by the “resting state” of the mind, the relative contribution of key cognitive components to DMN activity is still poorly understood. Here we used fMRI to investigate whether activity in neural components of the DMN can be differentially explained by active recall of relevant emotional autobiographical memories as compared with the resting state. Our study design combined emotional autobiographical memory, neutral memory and resting state conditions, separated by a serial subtraction control task. Shared patterns of activation in the DMN were observed in both emotional autobiographical and resting conditions, when compared with serial subtraction. Directly contrasting autobiographical and resting conditions demonstrated a striking dissociation within the DMN in that emotional autobiographical retrieval led to stronger activation of the dorsomedial core regions (medial prefrontal cortex, posterior cingulate cortex), whereas the resting state condition engaged a ventral frontal network (ventral striatum, subgenual and ventral anterior cingulate cortices) in addition to the IPL. Our results reveal an as yet unreported dissociation within the DMN. Whereas the dorsomedial component can be explained by emotional autobiographical memory, the ventral frontal one is predominantly associated with the resting state proper, possibly underlying fundamental motivational mechanisms engaged during spontaneous unconstrained ideation. Hum Brain Mapp 35:3302–3313, 2014.

Manganese-enhanced magnetic resonance imaging detects mossy fiber sprouting in the pilocarpine model of epilepsy

Purpose:  Mossy fiber sprouting (MFS) is a frequent finding following status epilepticus (SE). The present study aimed to test the feasibility of using manganese‐enhanced magnetic resonance imaging (MEMRI) to detect MFS in the chronic phase of the well‐established pilocarpine (Pilo) rat model of temporal lobe epilepsy (TLE).

Manganese-Enhanced MRI: Biological Applications in Neuroscience

Magnetic resonance imaging (MRI) is an excellent non-invasive tool to investigate biological systems. The administration of the paramagnetic divalent ion manganese (Mn2+) enhances MRI contrast in vivo. Due to similarities between Mn2+ and calcium (Ca2+), the premise of manganese-enhanced MRI (MEMRI) is that the former may enter neurons and other excitable cells through voltage-gated Ca2+ channels. As such, MEMRI has been used to trace neuronal pathways, define morphological boundaries, and study connectivity in morphological and functional imaging studies. In this article, we provide a brief overview of MEMRI and discuss recently published data to illustrate the usefulness of this method, particularly in animal models.

Intravoxel Incoherent Motion Diffusion Weighted MR Imaging at 3.0 T: Assessment of Steatohepatitis and Fibrosis Compared with Liver Biopsy in Type 2 Diabetic Patients.

Objective To evaluate the capability of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) to assess steatohepatitis and fibrosis determined by histopathology in type 2 diabetic patients. Methods Fifty-nine type 2 diabetic patients (49 women, 10 men; mean age, 54 ± 9 years) were submitted to liver biopsy for the evaluation of non-alcoholic fatty liver disease (NAFLD) and underwent DWI on a 3.0T MR system using 10 b values. Institutional approval and patient consent were obtained. Pure molecular-based (D), perfusion-related (D*), and vascular fraction (f) were calculated using a double exponential model and least squares curve fitting. D, D*, and f were compared between patients with and without steatohepatitis and between patients with and without fibrosis. The variables were compared by using the Ranksum test and Student t-test. Results Steatohepatitis was observed in 22 patients and fibrosis in 16 patients. A lower D median (0.70 s/mm2 vs. 0.83 s/mm2, p<0.05) and a lower D* median (34.39 s/mm2 vs. 45.23 s/mm2, p<0.05) were observed among those with steatohepatitis. A lower D median (0.70 s/mm2 vs. 0.82 s/mm2, p<0.05) and a lower D* median (35.01 s/mm2 vs. 44.76 s/mm2, p=0.05) were also observed among those with fibrosis. Conclusion IVIM-DWI has the potential to aid in the characterization of steatohepatitis and fibrosis.

Is MR Spectroscopy Really the Best MR-Based Method for the Evaluation of Fatty Liver in Diabetic Patients in Clinical Practice?

Objective To investigate if magnetic resonance spectroscopy (MRS) is the best Magnetic Resonance (MR)-based method when compared to gradient-echo magnetic resonance imaging (MRI) for the detection and quantification of liver steatosis in diabetic patients in the clinical practice using liver biopsy as the reference standard, and to assess the influence of steatohepatitis and fibrosis on liver fat quantification. Methods Institutional approval and patient consent were obtained for this prospective study. Seventy-three patients with type 2 diabetes (60 women and 13 men; mean age, 54±9 years) underwent MRI and MRS at 3.0 T. The liver fat fraction was calculated from triple- and multi-echo gradient-echo sequences, and MRS data. Liver specimens were obtained in all patients. The accuracy for liver fat detection was estimated by receiver operator characteristic (ROC) analysis, and the correlation between fat quantification by imaging and histolopathology was analyzed by Spearmans correlation coefficients. Results The prevalence of hepatic steatosis was 92%. All gradient-echo MRI and MRS findings strongly correlated with biopsy findings (triple-echo, rho = 0.819; multi-echo, rho = 0.773; MRS, rho = 0.767). Areas under the ROC curves to detect mild, moderate, and severe steatosis were: triple-echo sequences, 0.961, 0.975, and 0.962; multi-echo sequences, 0.878, 0.979, and 0.961; and MRS, 0.981, 0.980, and 0.954. The thresholds for mild, moderate, and severe steatosis were: triple-echo sequences, 4.09, 9.34, and 12.34, multi-echo sequences, 7.53, 11.75, and 15.08, and MRS, 1.71, 11.69, and 14.91. Quantification was not significantly influenced by steatohepatitis or fibrosis. Conclusions Liver fat quantification by MR methods strongly correlates with histopathology. Due to the wide availability and easier post-processing, gradient-echo sequences may represent the best imaging method for the detection and quantification of liver fat fraction in diabetic patients in the clinical practice.

Predicting malignant involvement in a thyroid nodule: role of ultrasonography.

OBJECTIVE To assess how ultrasonography can contribute during the evaluation of a thyroid nodule and whether this technique can have a role in predicting malignant involvement. METHODS In this retrospective study, data were analyzed on 220 consecutive patients (with 348 thyroid nodules) who underwent thyroidectomy and had previously undergone assessment by high-resolution thyroid ultrasonography. Nodule size, echogenicity, regularity of margins, halo sign, presence or absence of calcifications, and invasion of surrounding tissues were evaluated. The nodules were classified as low, medium, or high risk for malignant involvement on the basis of nodule characteristics found on ultrasonography. All nodules were submitted to cytologic examination by fine-needle aspiration (FNA) before thyroidectomy. Ultrasound, FNA, and pathologic postoperative results were compared. RESULTS Among the 348 thyroid nodules, 56 were ultrasonographically classified as low risk, 268 as medium risk, and 24 as high risk for malignant potential. Fifty of 56 (89.3%) low-risk nodules and 213 of 268 (79.5%) medium-risk nodules were diagnosed as benign at pathologic postoperative examination. In contrast, however, only 6 of 24 (25%) high-risk nodules were diagnosed as benign. Among the 18 high-risk nodules of 1-cm diameter or larger, FNA showed a 20% false-negative result. CONCLUSION High-risk classification of a thyroid nodule on ultrasonography had a positive predictive value for malignant involvement of 75%. Nodule characteristics analyzed by ultrasonography should be considered at the time of surgical intervention.

Real-Time fMRI Pattern Decoding and Neurofeedback Using FRIEND: An FSL-Integrated BCI Toolbox

The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI)-based neurofeedback emerged as a promising method, given its superior spatial resolution and ability to gauge deep cortical and subcortical brain regions. In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM), fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. Expansion in this field and its applications critically depend on the existence of freely available, integrated and user-friendly tools for the neuroimaging research community. Here, we introduce FRIEND, a graphic-oriented user-friendly interface package for fMRI neurofeedback and real-time multivoxel pattern decoding. The package integrates routines for image preprocessing in real-time, ROI-based feedback (single-ROI BOLD level and functional connectivity) and brain decoding-based feedback using SVM. FRIEND delivers an intuitive graphic interface with flexible processing pipelines involving optimized procedures embedding widely validated packages, such as FSL and libSVM. In addition, a user-defined visual neurofeedback module allows users to easily design and run fMRI neurofeedback experiments using ROI-based or multivariate classification approaches. FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available.

Arterial Spin Labeling of Cerebral Perfusion Territories Using a Separate Labeling Coil

To obtain cerebral perfusion territories of the left, the right, and the posterior circulation in humans with high signal‐to‐noise ratio (SNR) and robust delineation.