Neurite density imaging versus imaging of microscopic anisotropy in diffusion MRI: A model comparison using spherical tensor encoding.

In diffusion MRI (dMRI), microscopic diffusion anisotropy can be obscured by orientation dispersion. Separation of these properties is of high importance, since it could allow dMRI to non-invasively probe elongated structures such as neurites (axons and dendrites). However, conventional dMRI, based on single diffusion encoding (SDE), entangles microscopic anisotropy and orientation dispersion with intra-voxel variance in isotropic diffusivity. SDE-based methods for estimating microscopic anisotropy, such as the neurite orientation dispersion and density imaging (NODDI) method, must thus rely on model assumptions to disentangle these features. An alternative approach is to directly quantify microscopic anisotropy by the use of variable shape of the b-tensor. Along those lines, we here present the 'constrained diffusional variance decomposition' (CODIVIDE) method, which jointly analyzes data acquired with diffusion encoding applied in a single direction at a time (linear tensor encoding, LTE) and in all directions (spherical tensor encoding, STE). We then contrast the two approaches by comparing neurite density estimated using NODDI with microscopic anisotropy estimated using CODIVIDE. Data were acquired in healthy volunteers and in glioma patients. NODDI and CODIVIDE differed the most in gray matter and in gliomas, where NODDI detected a neurite fraction higher than expected from the level of microscopic diffusion anisotropy found with CODIVIDE. The discrepancies could be explained by the NODDI tortuosity assumption, which enforces a connection between the neurite density and the mean diffusivity of tissue. Our results suggest that this assumption is invalid, which leads to a NODDI neurite density that is inconsistent between LTE and STE data. Using simulations, we demonstrate that the NODDI assumptions result in parameter bias that precludes the use of NODDI to map neurite density. With CODIVIDE, we found high levels of microscopic anisotropy in white matter, intermediate levels in structures such as the thalamus and the putamen, and low levels in the cortex and in gliomas. We conclude that accurate mapping of microscopic anisotropy requires data acquired with variable shape of the b-tensor.

Associations between Metabolic Risk Factors and the Hypothalamic Volume in Childhood Leukemia Survivors Treated with Cranial Radiotherapy.

Metabolic complications are prevalent in individuals treated with cranial radiotherapy (CRT) for childhood acute lymphoblastic leukemia (ALL). The hypothalamus is a master regulator of endocrine and metabolic control. The aim of this study was to investigate whether the hypothalamic volume would be associated to metabolic parameters in ALL survivors. Thirty-eight (21 women) survivors participated in this study 34 years after diagnosis and with a median age of 38 (27-46) years. All were treated with a median CRT dose of 24 Gy and 11 years (3-13) of complete hormone supplementation. Comparisons were made to 31 matched controls. We performed analyses of fat mass, fat free mass, plasma (p)-glucose, p-insulin, Homa-Index (a measure of insulin resistance), serum (s)-leptin, s-ghrelin and of the hypothalamic volume in scans obtained by magnetic resonance imaging (MRI) at 3 Tesla. Serum leptin/kg fat mass (r = -0.4, P = 0.04) and fat mass (r = -0.4, P = 0.01) were negatively correlated with the HT volume among ALL survivors, but not among controls. We also detected significantly higher BMI, waist, fat mass, p-insulin, Homa-Index, leptin/kg fat mass and s-ghrelin and significantly lower fat free mass specifically among female ALL survivors (all P<0.01). Interestingly, s-ghrelin levels increased with time since diagnosis and with low age at diagnosis for childhood ALL. Our results showed that leptin/kg fat mass and fat mass were associated with a reduced HT volume 34 years after ALL diagnosis and that women treated with CRT after ALL are at high risk of metabolic abnormalities. Taken together our data suggest that the hypothalamus is involved in the metabolic consequences after CRT in ALL survivors.

Pregabalin rectifies aberrant brain chemistry, connectivity, and functional response in chronic pain patients.

BACKGROUND: Chronic pain remains a significant challenge for modern health care as its pathologic mechanisms are largely unknown and preclinical animal models suffer from limitations in assessing this complex subjective experience. However, human brain neuroimaging techniques enable the assessment of functional and neurochemical alterations in patients experiencing chronic pain and how these factors may dynamically change with pharmacologic treatment. METHODS: To identify the clinical action of pregabalin, a proven analgesic, the authors performed three complementary brain neuroimaging procedures: (proton magnetic resonance spectroscopy, functional magnetic resonance imaging, and functional connectivity magnetic resonance imaging) in 17 chronic pain patients diagnosed with fibromyalgia. RESULTS: The authors found that pregabalin but not placebo reduces combined glutamate + glutamine levels within the posterior insula (pregabalin P = 0.016; placebo P = 0.71). Interestingly, reductions in clinical pain were associated with reductions in brain connectivity of this structure to brain regions within the default mode network during pregabalin (r = 0.82; P = 0.001) but not placebo (r = -0.13; P = 0.63). Response of default mode network regions to experimental pain was also reduced with pregabalin (P = 0.018) but not placebo (P = 0.182). Perhaps most importantly, baseline values for all three neuroimaging markers predicted subsequent analgesic response to pregabalin but not placebo. CONCLUSIONS: The results of this study suggest that pregabalin works in part by reducing insular glutamatergic activity, leading to a reduction of the increased functional connectivity seen between brain regions in chronic pain states. The study also supports a role for human brain imaging in the development, assessment, and personalized use of central-acting analgesics.

Dynamic levels of glutamate within the insula are associated with improvements in multiple pain domains in fibromyalgia.

OBJECTIVE: Fibromyalgia (FM) is a chronic widespread pain condition that is thought to arise from augmentation of central neural activity. Glutamate (Glu) is an excitatory neurotransmitter that functions in pain-processing pathways. This study was carried out to investigate the relationship between changing levels of Glu within the insula and changes in multiple pain domains in patients with FM. METHODS: Ten patients with FM underwent 2 sessions of proton magnetic resonance spectroscopy (H-MRS) and 2 sessions of functional magnetic resonance imaging (FMRI), each conducted before and after a nonpharmacologic intervention to reduce pain. During H-MRS, the anterior and posterior insular regions were examined separately using single-voxel spectroscopy. The levels of Glu and other metabolites were estimated relative to levels of creatine (Cr) (e.g., the Glu/Cr ratio). During FMRI, painful pressures were applied to the thumbnail to elicit neuronal activation. Experimental pressure-evoked pain thresholds and clinical pain ratings (on the Short Form of the McGill Pain Questionnaire [SF-MPQ]) were also assessed prior to each imaging session RESULTS: Both experimental pain (P = 0.047 versus pretreatment) and SF-MPQ-rated clinical pain (P = 0.043 versus pretreatment) were reduced following treatment. Changes from pre- to posttreatment in Glu/Cr were negatively correlated with changes in experimental pain thresholds (r = -0.95, P < 0.001) and positively correlated with changes in clinical pain (r = 0.85, P = 0.002). Changes in the FMRI-determined blood oxygenation level-dependent effect (a measure of neural activation) were positively correlated with changes in Glu/Cr within the contralateral insula (r = 0.81, P = 0.002). CONCLUSION: Changes in Glu levels within the insula are associated with changes in multiple pain domains in patients with FM. Thus, H-MRS data may serve as a useful biomarker and surrogate end point for clinical trials of FM.