Abnormal Cingulum Bundle Induced by Type 2 Diabetes Mellitus: A Diffusion Tensor Tractography Study

Insulin Resistance and Cognitive Impairment: Evidence From Neuroimaging

Insulin is a peptide well known for its role in regulating glucose metabolism in peripheral tissues. Emerging evidence from human and animal studies indicate the multifactorial role of insulin in the brain, such as neuronal and glial metabolism, glucose regulation, and cognitive processes. Insulin resistance (IR), defined as reduced sensitivity to the action of insulin, has been consistently proposed as an important risk factor for developing neurodegeneration and cognitive impairment. Although the exact mechanism of IR-related cognitive impairment still awaits further elucidation, neuroimaging offers a versatile set of novel contrasts to reveal the subtle cerebral abnormalities in IR. These imaging contrasts, including but not limited to brain volume, white matter (WM) microstructure, neural function and brain metabolism, are expected to unravel the nature of the link between IR, cognitive decline, and brain abnormalities, and their changes over time. This review summarizes the current neuroimaging studies with multiparametric techniques, focusing on the cerebral abnormalities related to IR and therapeutic effects of IR-targeting treatments. According to the results, brain regions associated with IR pathophysiology include the medial temporal lobe, hippocampus, prefrontal lobe, cingulate cortex, precuneus, occipital lobe, and the WM tracts across the globe. Of these, alterations in the temporal lobe are highly reproducible across different imaging modalities. These structures have been known to be vulnerable to Alzheimer's disease (AD) pathology and are critical in cognitive processes such as memory and executive functioning. Comparing to asymptomatic subjects, results are more mixed in patients with metabolic disorders such as type 2 diabetes and obesity, which might be attributed to a multifactorial mechanism. Taken together, neuroimaging, especially MRI, is beneficial to reveal early abnormalities in cerebral structure and function in insulin-resistant brain, providing important evidence to unravel the underlying neuronal substrate that reflects the cognitive decline in IR. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

White Matter Characteristics of Damage Along Fiber Tracts in Patients with Type 2 Diabetes Mellitus

Purpose

The white matter (WM) of the brain of type 2 diabetes mellitus (T2DM) patients is susceptible to neurodegenerative processes, but the specific types and positions of microstructural lesions along the fiber tracts remain unclear.

Methods

In this study 61 T2DM patients and 61 healthy controls were recruited and underwent diffusion spectrum imaging (DSI). The results were reconstructed with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). WM microstructural abnormalities were identified using tract-based spatial statistics (TBSS). Pointwise WM tract differences were detected through automatic fiber quantification (AFQ). The relationships between WM tract abnormalities and clinical characteristics were explored with partial correlation analysis.

Results

TBSS revealed widespread WM lesions in T2DM patients with decreased fractional anisotropy and axial diffusivity and an increased orientation dispersion index (ODI). The AFQ results showed microstructural abnormalities in T2DM patients in specific portions of the right superior longitudinal fasciculus (SLF), right arcuate fasciculus (ARC), left anterior thalamic radiation (ATR), and forceps major (FMA). In the right ARC of T2DM patients, an aberrant ODI was positively correlated with fasting insulin and insulin resistance, and an abnormal intracellular volume fraction was negatively correlated with fasting blood glucose. Additionally, negative associations were found between blood pressure and microstructural abnormalities in the right ARC, left ATR, and FMA in T2DM patients.

Conclusion

Using AFQ, together with DTI and NODDI, various kinds of microstructural alterations in the right SLF, right ARC, left ATR, and FMA can be accurately identified and may be associated with insulin and glucose status and blood pressure in T2DM patients.

Disrupted white matter integrity in the brain of type 1 diabetes is associated with peripheral neuropathy and abnormal brain metabolites

AIMS

We aimed to quantify microstructural white matter abnormalities using magnetic resonance imaging and examine their associations with 1) brain metabolite and volumes and 2) clinical diabetes-specific characteristics and complications in adults with type 1 diabetes mellitus (T1DM) and distal symmetric peripheral neuropathy (DSPN).

METHODS

Diffusion tensor images (DTI) obtained from 46 adults with T1DM and DSPN and 28 healthy controls were analyzed using tract-based spatial statistics and were then associated with 1) brain metabolites and volumes and 2) diabetes-specific clinical characteristics (incl. HbA_1c, diabetes duration, level of retinopathy, nerve conduction assessment).

RESULTS

Adults with T1DM and DSPN had reduced whole-brain FA skeleton (P = 0.018), most prominently in the inferior longitudinal fasciculus and retrolenticular internal capsule (P < 0.001). Reduced fractional anisotropy (FA) was associated with lower parietal N-acetylaspartate/creatine metabolite ratio (r = 0.399, P = 0.006), brain volumes (P ≤ 0.002), diabetes duration (r = -0.495, P < 0.001) and sural nerve amplitude (r = 0.296, P = 0.046). Additionally, FA was reduced in the subgroup with concomitant proliferative retinopathy compared to non-proliferative retinopathy (P = 0.03). No association was observed between FA and HbA_1c.

CONCLUSIONS

This hypothesis-generating study provided that altered white matter microstructural abnormalities in T1DM with DSPN were associated with reduced metabolites central for neuronal communications and diabetes complications, indicating that peripheral neuropathic complications are often accompanied by central neuropathy.

Association between Type 2 Diabetes Mellitus and Brain Atrophy: A Meta-Analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) is known to be associated with cognitive decline and brain structural changes. This study systematically reviews and estimates human brain volumetric differences and atrophy associated with T2DM.

METHODS

PubMed, PsycInfo and Cochrane Library were searched for brain imaging studies reporting on brain volume differences between individuals with T2DM and healthy controls. Data were examined using meta-analysis, and association between age, sex, diabetes characteristics and brain volumes were tested using meta-regression.

RESULTS

A total of 14,605 entries were identified; after title, abstract and full-text screening applying inclusion and exclusion criteria, 64 studies were included and 42 studies with compatible data contributed to the meta-analysis (n=31,630; mean age 71.0 years; 44.4% male; 26,942 control; 4,688 diabetes). Individuals with T2DM had significantly smaller total brain volume, total grey matter volume, total white matter volume and hippocampal volume (approximately 1% to 4%); meta-analyses of smaller samples focusing on other brain regions and brain atrophy rate in longitudinal investigations also indicated smaller brain volumes and greater brain atrophy associated with T2DM. Meta-regression suggests that diabetes-related brain volume differences start occurring in early adulthood, decreases with age and increases with diabetes duration.

CONCLUSION

T2DM is associated with smaller total and regional brain volume and greater atrophy over time. These effects are substantial and highlight an urgent need to develop interventions to reduce the risk of T2DM for brain health.

Towards the Interpretability of Deep Learning Models for Multi-modal Neuroimaging: Finding Structural Changes of the Ageing Brain

Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with Layer-wise Relevance Propagation (LRP) to detect which brain features contribute to BA. Trained on magnetic resonance imaging (MRI) data of a population-based study (n=2637, 18-82 years), our models estimated age accurately based on single and multiple modalities, regionally restricted and whole-brain images (mean absolute errors 3.37-3.86 years). We find that BA estimates capture aging at both small and large-scale changes, revealing gross enlargements of ventricles and subarachnoid spaces, as well as white matter lesions, and atrophies that appear throughout the brain. Divergence from expected aging reflected cardiovascular risk factors and accelerated aging was more pronounced in the frontal lobe. Applying LRP, our study demonstrates how superior deep learning models detect brain-aging in healthy and at-risk individuals throughout adulthood.

Tractography in Type 2 Diabetes Mellitus With Subjective Memory Complaints: A Diffusion Tensor Imaging Study

The brain white matter (WM) structural injury caused by type 2 diabetes mellitus (T2DM) has been linked to cognitive impairment. However, the focus was mainly on the mild cognitive impairment (MCI) stage in most previous studies, with little attention made to subjective memory complaints (SMC). The main purpose of the current study was to investigate the characteristics of WM injury in T2DM patients and its correlation with SMC symptoms. In a group of 66 participants (33 HC and 33 T2DM-S), pointwise differences along WM tracts were identified using the automated fiber quantification (AFQ) approach. Then we investigated the utility of DTI properties along major WM tracts as features to distinguish patients with T2DM-S from HC via the support vector machine (SVM). Based on AFQ analysis, 10 primary fiber tracts that represent the subtle alterations of WM in T2DM-S were identified. Lower fractional anisotropy (FA) in the right SLF tract (r = −0.538, p = 0.0013), higher radial diffusivity (RD) in the thalamic radiation (TR) tract (r = 0.433, p = 0.012), and higher mean diffusivity (MD) in the right inferior fronto-occipital fasciculus (IFOF) tract (r = 0.385, p = 0.0029) were significantly associated with a long period of disease. Decreased axial diffusivity (AD) in the left arcuate was associated with HbA_1c (r = −0.368, p = 0.049). In addition, we found a significant negative correlation between delayed recall and abnormal MD in the left corticospinal tract (r = −0.546, p = 0.001). The FA of the right SLF tracts and bilateral arcuate can be used to differentiate the T2DM-S and the HC at a high accuracy up to 88.45 and 87.8%, respectively. In conclusion, WM microstructure injury in T2DM may be associated with SMC, and these abnormalities identified by DTI can be used as an effective biomarker.

Brain Imaging Changes and Related Risk Factors of Cognitive Impairment in Patients With Heart Failure

Background/Aims

To explore the imaging changes and related risk factors of heart failure (HF) patients with cognitive impairment (CI).

Methods

A literature search was systematically carried out in PubMed, Web of Science, Embase, and Cochrane Library. In this systematic review, important relevant information was extracted according to the inclusion and exclusion criteria. The methodological quality was assessed by three scales according to the different study types.

Results

Finally, 66 studies were included, involving 33,579 patients. In the imaging changes, the severity of medial temporal lobe atrophy (MTA) and the decrease of gray Matter (GM) volume were closely related to the cognitive decline. The reduction of cerebral blood flow (CBF) may be correlated with CI. However, the change of white matter (WM) volume was possibly independent of CI in HF patients. Specific risk factors were analyzed, and the data indicated that the increased levels of B-type natriuretic peptide (BNP)/N-terminal pro-B-type natriuretic peptide (NT-proBNP), and the comorbidities of HF, including atrial fibrillation (AF), diabetes mellitus (DM) and anemia were definitely correlated with CI in patients with HF, respectively. Certain studies had also obtained independent correlation results. Body mass index (BMI), depression and sleep disorder exhibited a tendency to be associated with CI. Low ejection fraction (EF) value (<30%) was inclined to be associated with the decline in cognitive function. However, no significant differences were noted between heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF) in cognitive scores.

Conclusion

BNP/NT-proBNP and the comorbidities of HF including AF, DM and anemia were inextricably correlated with CI in patients with HF, respectively. These parameters were independent factors. The severity of MTA, GM volume, BMI index, depression, sleep disorder, and low EF value (<30%) have a disposition to associated with CI. The reduction in the CBF volume may be related to CI, whereas the WM volume may not be associated with CI in HF patients. The present systematic review provides an important basis for the prevention and treatment of CI following HF.

Abnormalities of Brain White Matter in Type 2 Diabetes Mellitus: A Meta-Analysis of Diffusion Tensor Imaging

Aims: The study aimed to conduct a meta-analysis to determine the abnormalities of white matter in patients with type 2 diabetes mellitus (T2DM) by identifying the consistency of diffusion tensor imaging (DTI). Method: The literature for DTI comparing patients with T2DM with controls published before October 30, 2020, were reviewed in PubMed, Web of Science, Embase, CNKI, and Wan Fang databases. The meta-analysis was performed using the activation likelihood estimation (ALE) method, including 12 reports and 381 patients with T2DM. Results: The meta-analysis identified 10 white matter regions that showed a consistent reduction of fractional anisotropy (FA) in patients with T2DM, including genu of the corpus callosum, the body of corpus callosum, bilateral anterior corona radiata, bilateral superior corona radiata, bilateral cingulum, and bilateral superior fronto-occipital fasciculus. Conclusion: This study revealed the abnormal characteristics of white matter in T2DM, which would be helpful to understand the underlying neuropathological and physiological mechanisms of T2DM and provide evidence for clinical diagnosis and treatment.

Disturbed Interhemispheric Functional and Structural Connectivity in Type 2 Diabetes

BACKGROUND

Type 2 diabetes mellitus (T2DM) is associated with cognitive decline and altered brain structure and function. However, the interhemispheric coordination of T2DM patients is unclear.

PURPOSE

To investigate interhemispheric functional and anatomic connectivity in T2DM, and their associations with cognitive performance and endocrine parameters.

STUDY TYPE

Prospective.

SUBJECTS

38 T2DM patients and 42 matched controls.

FIELD STRENGTH/SEQUENCES

3.0 T magnetic resonance imaging (MRI) scanner; magnetization-prepared rapid acquisition gradient echo sequence; fluid-attenuated inversion recovery sequence; single-shot, gradient-recalled echo-planar imaging sequence (resting-state functional MRI); and diffusion-weighted spin-echo-based echo-planar sequence (diffusion tensor imaging).

ASSESSMENT

Voxel-mirrored homotopic connectivity (VMHC) value was calculated based on the functional images. Fibers passing through the regions with significant VMHC differences were identified using an atlas-guided track recognition. The mean fractional anisotropy (FA), mean diffusivity (MD), and fiber length were extracted and compared between the two groups. Finally, correlational analyses were performed to examine the relationships between abnormal interhemispheric connectivity, cognitive performances, and endocrine parameters.

STATISTICAL TESTS

Two-sample t-tests were performed controlling for confounding factors, with partial correlation analysis. False discovery rate (FDR) correction was used for multiple comparisons. A P value <0.05 was considered statistically significant.

RESULTS

T2DM patients exhibited significantly decreased VMHC between bilateral lingual gyrus and sensorimotor cortex. The fibers connecting lingual gyrus in patients showed significantly lower FA (P = 0.011) and shorter fiber length (P < 0.001), while the differences in sensorimotor fibers were insignificant (P = 0.096 for FA, P = 0.739 for fiber length and P = 0.150 for MD). The FA value in the lingual fibers was negatively correlated with insulin resistance (IR) level in T2DM group after FDR correction (R = -0.635).

DATA CONCLUSION

We noted disruptions in interhemispheric coordination in T2DM patients, involving both functional and anatomical connectivities. IR might be a promising therapeutic target in the intervention of T2DM-related cognitive impairment.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.