Odor Identification and Regional Gray Matter Atrophy in Patients with Alzheimer’s Disease, Parkinson’s Disease, and the Healthy Elderly: A Cross-Sectional Structural MRI Study

Multiple associations between impaired olfactory performance and regional cortical and deep gray matter atrophy have been reported in separate studies of patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), and of the healthy elderly. We aimed to evaluate such possible associations among these populations in a unified manner. Twenty AD, twenty PD patients’ and twenty healthy age- and sex-matched controls’ odor identification performance was assessed with the Lithuanian adaptation of the Sniffin’ Sticks 12 odor identification test, followed by morphometric gray matter analysis by MRI using FreeSurfer. AD patients had significantly lower cognitive performance than both PD patients and the healthy elderly, as evaluated with the Mini-Mental State Examination (MMSE). Odor identification performance was significantly worse in AD and PD patients compared with the healthy elderly; AD patients performed slightly worse than PD patients, but the difference was not statistically significant. Among patients with AD, worse odor identification performance was initially correlated with atrophy of multiple cortical and deep gray matter regions known to be involved in olfactory processing, however, only two measures—decreased thicknesses of the right medial and left lateral orbitofrontal cortices—remained significant after adjustment for possible confounders (age, MMSE score, and global cortical thickness). Among patients with PD and the healthy elderly we found no similar statistically significant correlations. Our findings support the key role of the orbitofrontal cortex in odor identification among patients with AD, and suggest that correlations between impaired odor identification performance and regional gray matter atrophy may be relatively more pronounced in AD rather than in PD.

The Effect of Deep Learning-Based QSM Magnetic Resonance Imaging on the Subthalamic Nucleus

In order to study the influence of quantitative magnetic susceptibility mapping (QSM) on them. A 2.5D Attention U-Net Network based on multiple input and multiple output, a method for segmenting RN, SN, and STN regions in high-resolution QSM images is proposed, and deep learning realizes accurate segmentation of deep nuclei in brain QSM images. Experimental results show data first cuts each layer of 0 100 case data, based on the image center, from 384 × 288 to the size of 128 × 128. Image combination: each layer of the image in the layer direction combines with two adjacent images into a 2.5D image, i.e., (It − m It; It + i), where It represents the layer i image. At this time, the size of the image changes from 128 × 128 to 128 × 128 × 3, in which 3 represents three consecutive layers of images. The SNR of SWP I to STN is twice that of SWI. The small deep gray matter nuclei (RN, SN, and STN) in QSM images of the brain and the pancreas with irregular shape and large individual differences in abdominal CT images can be automatically segmented.

Clinical analysis of 33 cases with neonatal cerebral infarction

Objective: To investigate the etiology, clinical manifestations, diagnosis, treatment and prognosis of neonatal cerebral infarction (NCI) to further improve the understanding of the disease. Methods: Clinical data and follow-up results of 33 cases of NCI in neonatal intensive care unit of a first-class hospital from September 2009 to September 2019 were retrospectively analyzed. Results: All 33 patients were diagnosed with NCI by MRI. Among them, 31 cases (93.94%) were full-term infants, 25 cases (75.76%) were mother’s first birth, and 18 (54.55%) cases were males. Pregnancy complications were reported in 18 cases (54.55%), and 19 cases (57.58%) had perinatal hypoxia history. Seizures were the most common first symptom and clinical manifestation in the course of disease (81.8%). There were 27 cases (81.82%) of patent foramen ovale (PFO) among NCI cohort. Ischemic cerebral infarction occurred in 32 cases (96.97%). The middle cerebral artery and its branches were more frequently involved, mainly on the left side. The acute stage of NCI was managed by symptomatic support treatment, and the recovery stage involved mainly rehabilitation treatment. Among the 33 cases, five cases were lost to follow-up, two patients died, 26 patients survived without complications, one case had cerebral palsy, one case had language retardation, and six cases had dyskinesia. Poor prognosis was associated with the involvement of deep gray matter nuclei or multiple lobes, and intrapartum complications. Vaginal mode of delivery and longer hospital stay were associated with better prognosis. Conclusions: Complications leading to placental circulation disorder during pregnancy and perinatal hypoxia are common high-risk factors of NCI. The seizure is the most common clinical manifestation. There is a possible correlation between PFO and NCI. Involvement of deep gray matter or multiple lobes and intrapartum complications may indicate poor prognosis, while vaginal delivery and prolonged hospitalizations are associated with better prognosis of NCI. doi: https://doi.org/10.12669/pjms.37.7.4720 How to cite this:Yang N, He X, Yin C, Zhao L. Clinical analysis of 33 cases with neonatal cerebral infarction. Pak J Med Sci. 2021;37(7):---------. doi: https://doi.org/10.12669/pjms.37.7.4720 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Comparison of Thalamus and Basal Ganglia Signs Between Multiple Sclerosis and Primary Angiitis of the Central Nervous System: An Exploratory Study

Based on the symptoms, especially those affecting small vessels, it is difficult to distinguish multiple sclerosis (MS) from primary angiitis of the central nervous system (PACNS). Magnetic resonance imaging (MRI) helps understand the characteristics of deep gray matter lesions (DGML) in MS and PACNS. We aimed to compare the MRI characteristics of thalamus and basal ganglia lesions between relapsing-remitting MS and PACNS. In our study, 49 relapsing-remitting MS patients and 16 PACNS with MRI-confirmed thalamus or basal ganglia lesions were enrolled. Among the DGMLs in basal ganglia, putamen had significantly higher (P = 0.037) involvement in PACNS than in MS. More importantly, larger lesion sizes in thalamus helps to distinguish PACNS (12.4 ± 4.3 mm) from MS (7.9 ± 3.7 mm) (P = 0.006). But using lesions in basal ganglia, researchers were unable to differentiate the two disorders. Presently, our study shows that MRI performances of deep gray matter differ between MS and PACNS.

Microstructural MRI Correlates of Cognitive Impairment in Multiple Sclerosis: The Role of Deep Gray Matter

Although cognitive impairment (CI) is frequently observed in people with multiple sclerosis (pwMS), its pathogenesis is still controversial. Conflicting results emerged concerning the role of microstructural gray matter (GM) damage especially when involving the deep GM structures. In this study, we aimed at evaluating whether differences in cortical and deep GM structures between apparently cognitively normal (ACN) and CI pwMS (36 subjects in total) are present, using an extensive set of diffusion MRI (dMRI) indices and conventional morphometry measures. The results revealed increased anisotropy and restriction over several deep GM structures in CI compared with ACN pwMS, while no changes in volume were present in the same areas. Conversely, reduced anisotropy/restriction values were detected in cortical regions, mostly the pericalcarine cortex and precuneus, combined with reduced thickness of the superior frontal gyrus and insula. Most of the dMRI metrics but none of the morphometric indices correlated with the Symbol Digit Modality Test. These results suggest that deep GM microstructural damage can be a strong anatomical substrate of CI in pwMS and might allow identifying pwMS at higher risk of developing CI.

Iron Deposition Characteristics of Deep Gray Matter in Elderly Individuals in the Community Revealed by Quantitative Susceptibility Mapping and Multiple Factor Analysis

PurposeThe objective of this study was to determine which factors influence brain iron concentrations in deep gray matter in elderly individuals and how these factors influence regional brain iron concentrations.MethodsA total of 105 elderly individuals were enrolled in this study. All participants underwent detailed magnetic resonance imaging (MRI) examinations from October 2018 to August 2019. Among them, 44 individuals had undergone a previous MRI examination from July 2010 to August 2011. Quantitative susceptibility mapping (QSM) was utilized as an indirect quantitative marker of brain iron, and the susceptibility values of deep gray matter structures were obtained. Univariate analysis and multiple linear regression analysis were used to investigate 11 possible determinants for cerebral iron deposition.ResultsOur results showed no sex- or hemisphere-related differences in susceptibility values in any of the regions studied. Aging was significantly correlated with increased insusceptibility values in almost all analyzed brain regions (except for the thalamus) when we compared the susceptibility values at the two time points. In a cross-sectional analysis, the relationship between gray matter nucleus susceptibility values and age was conducted using Pearson’s linear regression. Aging was significantly correlated with the susceptibility values of the globus pallidus (GP), putamen (Put), and caudate nucleus (CN), with the Put having the strongest correlations. In multiple linear regression models, associations with increased susceptibility values were found in the CN, Put, red nucleus, and dentate nucleus for individuals with a history of type 2 diabetes mellitus (T2DM). However, the patients with hypertension showed significantly reduced susceptibility values in the red nucleus and dentate nucleus. Our data suggested that smokers had increased susceptibility values in the thalamus. No significant associations were found for individuals with a history of hypercholesterolemia and Apolipoprotein E4 carrier status.ConclusionOur data revealed that aging, T2DM, and smoking could increase iron deposition in some deep gray matter structures. However, hypertension had the opposite effects in the red nuclei and dentate nuclei. Brain iron metabolism could be influenced by many factors in different modes. In future studies, we should strictly control for confounding factors.

Neuroradiologic Features Associated With Severe Restriction of Functional Mobility in Children With Cerebral Palsy in North India

Background: Few studies have focused on magnetic resonance imaging (MRI) brain findings associated with functional mobility in cerebral palsy. Objective: To determine association between MRI findings and Gross Motor Functional Classification System (GMFCS) levels in cerebral palsy. Methods: Prospective-observational study conducted in Pediatric Neurology Clinic at a public teaching hospital, Northern India. First 3 new cases of cerebral palsy were enrolled on particular neuro-clinic day per week for 1 year. Functional mobility was classified according to GMFCS. Association between MRI findings, cerebral palsy type, and GMFCS levels were evaluated using χ2 test. Results: A total of 138 cases (mean age 2.71 [SD = 1.91] years; male [64.5%]) were enrolled. Reported types of cerebral palsy were as follows: spastic quadriplegia (47.8%), spastic diplegia (28.35%), spastic hemiplegia (11.6%), extrapyramidal (6.5%), and ataxic/hypotonic (5.8%). GMFCS were classified into level 1 (13%), level 2 (7.2%), level 3 (4.3%), level 4 (10.9%), and level 5 (64.5%). Spastic quadriplegia and extrapyramidal cerebral palsy were significantly associated with higher (severe) levels (IV and V), whereas spastic diplegia and hemiplegia were significantly associated with lower (mild) levels (I-III) of GMFCS. MRI features of periventricular white matter injury, deep gray matter injury, basal ganglia and thalamic changes, and superficial gray matter injury were significantly associated with severe levels of GMFCS (V and IV). MRI was normal in 8 children (5 = mild category, 3 = severe category). Conclusion: Severe cerebral palsy is most often associated with spastic quadriplegia, extrapyramidal cerebral palsy, superficial gray matter lesions, deep gray matter lesions, and periventricular white matter injury. This information is useful for anticipating and addressing the needs of children with cerebral palsy and for prognostication.