Patients with Type 2 diabetes mellitus (T2DM) show cognitive and mood impairment, indicating potential for brain injury in regions that control these functions. However, brain tissue integrity in cognition, anxiety, and depression regulatory sites, and their associations with these functional deficits in T2DM subjects remain unclear. We examined gray matter (GM) changes in 34 T2DM and 88 control subjects using high-resolution T1-weighted images, collected from a 3.0-Tesla magnetic resonance imaging scanner, and assessed anxiety [Beck Anxiety Inventory], depressive symptoms [Beck Depression Inventory-II], and cognition [Montreal Cognitive Assessment]. We also investigated relationships between GM status of cognitive and mood control sites and these scores in T2DM. Significantly increased anxiety (p = 0.003) and depression (p = 0.001), and reduced cognition (p = 0.002) appeared in T2DM over controls. Decreased GM volumes appeared in several regions in T2DM patients, including the prefrontal, hippocampus, amygdala, insular, cingulate, cerebellum, caudate, basal-forebrain, and thalamus areas (p < 0.01). GM volumes were significantly associated with anxiety (r = −0.456,p = 0.009), depression (r = −0.465,p = 0.01), and cognition (r = 0.455,p = 0.009) scores in regions associated with those regulations (prefrontal cortices, hippocampus, para hippocampus, amygdala, insula, cingulate, caudate, thalamus, and cerebellum) in T2DM patients. Patients with T2DM show brain damage in regions that are involved in cognition, anxiety, and depression control, and these tissue alterations are associated with functional deficits. The findings indicate that mood and cognitive deficits in T2DM patients has brain structural basis in the condition.

Purpose: Single ventricle heart disease (SVHD) patients show injury in brain sites that regulate autonomic, mood, and cognitive functions. However, the nature (acute or chronic changes) and extent of brain injury in SVHD are unclear. Our aim was to examine regional brain tissue damage in SVHD over controls using DTI-based mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and fractional anisotropy (FA) procedures. Methods:We collected two DTI series (3.0-Tesla MRI), mood and cognitive data from 27 SVHD and 35 control adolescents. Whole-brain MD, AD, RD, and FA maps were calculated from each series, realigned and averaged, normalized to a common space, smoothed, and compared between groups using ANCOVA (covariates, age and sex; false-discovery-rate, p<0.05).

Patients with obstructive sleep apnea (OSA) show autonomic, mood, cognitive, and breathing dysfunctions that are linked to increased morbidity and mortality, which can be improved with early screening and intervention. The gold standard and other available methods for OSA diagnosis are complex, require whole-night data, and have significant wait periods that potentially delay intervention. Our aim was to examine whether using faster and less complicated machine learning models, including support vector machine (SVM) and random forest (RF), with brain diffusion tensor imaging (DTI) data can classify OSA from healthy controls. We collected two DTI series from 59 patients with OSA [age: 50.2 ± 9.9 years; body mass index (BMI): 31.5 ± 5.6 kg/m 2 ; apnea-hypopnea index (AHI): 34.1 ± 21.2 events/h 23 female] and 96 controls (age: 51.8 ± 9.7 years; BMI: 26.2 ± 4.1 kg/m 2 ; 51 female) using a 3.0-T magnetic resonance imaging scanner. Using DTI data, mean diffusivity maps were calculated from each series, realigned and averaged, normalised to a common space, and used to conduct cross-validation for model training and selection and to predict OSA. The RF model showed 0.73 OSA and controls classification accuracy and 0.85 area under the curve (AUC) value on the receiver-operator curve. Cross-validation showed the RF model with comparable fitting over SVM for OSA and control data (SVM; accuracy, 0.77; AUC, 0.84). The RF ML model performs similar to SVM, indicating the comparable statistical fitness to DTI data. The findings indicate that RF model has similar AUC Bo Pang and Suraj Doshi contributed equally to this study.

BACKGROUND AND PURPOSE Patients with pulmonary arterial hypertension (PAH) frequently present with anxiety, depression, autonomic, and cognitive deterioration, which may indicate brain changes in regions that control these functions. However, the precise regional brain‐injury in sites that regulate cognitive, autonomic, and mood functions in PAH remains unclear. We examined the shifts in regional gray matter (GM) volume, using high‐resolution T1‐weighted images, and brain tissue alterations, using T2‐relaxometry procedures, in PAH compared to healthy subjects. METHODS We collected two high‐resolution T1‐weighted series, and proton‐density and T2‐weighted images using a 3.0‐Tesla magnetic resonance imaging scanner from 9 PAH and 19 healthy subjects. Both high‐resolution T1‐weighted images were realigned and averaged, partitioned to GM tissue type, normalized to a common space, and smoothed. Using proton‐density and T2‐weighted images, T2‐relaxation maps were calculated, normalized to a common space, and smoothed. Whole‐brain GM volume and T2‐relaxation maps were compared between PAH and controls using analysis of covariance (covariates, age, sex, and total‐brain‐volume; false discover rate corrections). RESULTS Significantly decreased GM volumes, indicating tissue injury, emerged in multiple brain regions, including the hippocampus, insula, cerebellum, parahippocampus, temporal, frontal, and occipital gyri, cingulate, amygdala, and thalamus. Higher T2‐relaxation values, suggesting tissue damage, appeared in the cerebellum, hippocampus, parahippocampus, frontal, lingual, and temporal and occipital gyri, and cingulate areas in PAH compared to healthy subjects. CONCLUSIONS PAH patients showed significant GM injury and brain tissue changes in sites that regulate cognition, autonomic, and mood functions. These findings indicate a brain structural basis for functional deficits in PAH patients.

Heart failure (HF) leads to brain injury in autonomic, respiratory, mood, and cognitive control sites, revealed as tissue volume loss, altered metabolites, and impaired diffusion tissue properties. The extent of myelin changes in HF and variations within sexes are unclear. Our aim was to examine regional brain subcortical and white matter myelin integrity in HF patients over control subjects, as well as differences between sexes using T1‐ and T2‐weighted clinical images. We acquired T1‐ and T2‐weighted images from 63 HF patients and 129 controls using a 3.0‐Tesla MRI scanner. Using T1‐ and T2‐weighted images, ratio maps were computed, normalized to a common space, smoothed, and compared between groups (ANCOVA; covariates: age and sex; SPM12, false discovery rate, p < .010), as well as between male versus female HF (ANCOVA; covariate: age; SPM12, uncorrected p < .005). Multiple brain areas in HF showed decreased myelin integrity, including the amygdala, hippocampus, cingulate, insula, cerebellum, prefrontal cortices, and multiple white matter areas, compared to controls. Female HF patients showed more brain injuries in the parietal, prefrontal and frontal, hippocampus, amygdala, pons, cerebellar, insula, and corpus callosum compared to male HF patients. HF subjects showed compromised subcortical and white matter myelin integrity, especially in sites regulating autonomic, respiratory, mood, and cognition, with more changes in females over males. These findings provide a structural basis for the enhanced symptoms identified in female over male HF patients with similar disease severity.