Neurodegenerative Changes in the Brains of the 5xFAD Alzheimer's Disease Model Mice Investigated by High-Field and High-Resolution Magnetic Resonance Imaging and Multi-Nuclei Magnetic Resonance Spectroscopy.

This study aimed to investigate morphological and metabolic changes in the brains of 5xFAD mice. Structural magnetic resonance imaging (MRI) and 1H magnetic resonance spectroscopy (MRS) were obtained in 10- and 14-month-old 5xFAD and wild-type (WT) mice, while 31P MRS scans were acquired in 11-month-old mice. Significantly reduced gray matter (GM) was identified by voxel-based morphometry (VBM) in the thalamus, hypothalamus, and periaqueductal gray areas of 5xFAD mice compared to WT mice. Significant reductions in N-acetyl aspartate and elevation of myo-Inositol were revealed by the quantification of MRS in the hippocampus of 5xFAD mice, compared to WT. A significant reduction in NeuN-positive cells and elevation of Iba1- and GFAP-positive cells supported this observation. The reduction in phosphomonoester and elevation of phosphodiester was observed in 11-month-old 5xFAD mice, which might imply a sign of disruption in the membrane synthesis. Commonly reported 1H MRS features were replicated in the hippocampus of 14-month-old 5xFAD mice, and a sign of disruption in the membrane synthesis and elevation of breakdown were revealed in the whole brain of 5xFAD mice by 31P MRS. GM volume reduction was identified in the thalamus, hypothalamus, and periaqueductal gray areas of 5xFAD mice.

An in vivo proton magnetic resonance spectroscopy study with optimized echo-time technique for concurrent quantification and T2 measurement targeting glutamate in the rat brain.

OBJECTIVE: The present study applied in vivo proton magnetic resonance spectroscopy (1H MRS) to concurrently measure the concentration and T2 relaxation time of glutamate with the concept of optimized-for-quantification-and-T2-measurement-of-glutamate (OpQT2-Glu). MATERIALS AND METHODS: 7T MRS scans of the OpQT2-Glu were acquired from the prefrontal cortex of five rats. The echo-time-(TE)-specific J-modulation of glutamate was investigated by spectral simulations and analyses for selecting the eight TEs appropriate for T2 estimation of glutamate. The OpQT2-Glu results were compared to those of the typical short-TE MRS and T2 measurements. RESULTS: No significant differences were observed between the OpQT2-Glu and typical short-TE MRS (p > 0.050). The estimated glutamate T2 (67.75 ms) of the OpQT2-Glu was similar to the multiple TE MRS for the T2 measurement (71.58 ms) with enhanced signal-to-noise ratio and reliability. DISCUSSION: The results revealed that the quantification reliability of the OpQT2-Glu was comparable to that of the single short-TE MRS and its estimation reliability for the T2 relaxation time of glutamate was enhanced compared to the multiple TE MRS for T2 measurement. Despite certain limitations, the quantification and T2 estimation of glutamate can be concurrently performed within an acceptable scan time via high-field in vivo 1H MRS with the OpQT2-Glu.

Conditions for (13)C NMR detection of 2-hydroxyglutarate in tissue extracts from isocitrate dehydrogenase-mutated gliomas.

(13)C NMR (nuclear magnetic resonance) spectroscopy of extracts from patient tumor samples provides rich information about metabolism. However, in isocitrate dehydrogenase (IDH)-mutant gliomas, (13)C labeling is obscured in oncometabolite 2-hydroxyglutaric acid (2 HG) by glutamate and glutamine, prompting development of a simple method to resolve the metabolites. J-coupled multiplets in 2 HG were similar to glutamate and glutamine and could be clearly resolved at pH 6. A cryogenically cooled (13)C probe, but not J-resolved heteronuclear single quantum coherence spectroscopy, significantly improved detection of 2 HG. These methods enable the monitoring of (13)C-(13)C spin-spin couplings in 2 HG expressing IDH-mutant gliomas.

Predicting Brain Age and Gender from Brain Volume Data Using Variational Quantum Circuits.

The morphology of the brain undergoes changes throughout the aging process, and accurately predicting a person's brain age and gender using brain morphology features can aid in detecting atypical brain patterns. Neuroimaging-based estimation of brain age is commonly used to assess an individual's brain health relative to a typical aging trajectory, while accurately classifying gender from neuroimaging data offers valuable insights into the inherent neurological differences between males and females. In this study, we aimed to compare the efficacy of classical machine learning models with that of a quantum machine learning method called a variational quantum circuit in estimating brain age and predicting gender based on structural magnetic resonance imaging data. We evaluated six classical machine learning models alongside a quantum machine learning model using both combined and sub-datasets, which included data from both in-house collections and public sources. The total number of participants was 1157, ranging from ages 14 to 89, with a gender distribution of 607 males and 550 females. Performance evaluation was conducted within each dataset using training and testing sets. The variational quantum circuit model generally demonstrated superior performance in estimating brain age and gender classification compared to classical machine learning algorithms when using the combined dataset. Additionally, in benchmark sub-datasets, our approach exhibited better performance compared to previous studies that utilized the same dataset for brain age prediction. Thus, our results suggest that variational quantum algorithms demonstrate comparable effectiveness to classical machine learning algorithms for both brain age and gender prediction, potentially offering reduced error and improved accuracy.

Experimental Basis Sets of Quantification of Brain 1H-Magnetic Resonance Spectroscopy at 3.0 T.

In vivo short echo time (TE) proton magnetic resonance spectroscopy (1H-MRS) is a useful method for the quantification of human brain metabolites. The purpose of this study was to evaluate the performance of an in-house, experimentally measured basis set and compare it with the performance of a vendor-provided basis set. A 3T clinical scanner with 32-channel receive-only phased array head coil was used to generate 16 brain metabolites for the metabolite basis set. For voxel localization, point-resolved spin-echo sequence (PRESS) was used with volume of interest (VOI) positioned at the center of the phantoms. Two different basis sets were subjected to linear combination of model spectra of metabolite solutions in vitro (LCModel) analysis to evaluate the in-house acquired in vivo 1H-MR spectra from the left prefrontal cortex of 22 healthy subjects. To evaluate the performance of the two basis sets, the Cramer-Rao lower bounds (CRLBs) of each basis set were compared. The LCModel quantified the following metabolites and macromolecules: alanine (Ala), aspartate (Asp), γ-amino butyric acid (GABA), glucose (Glc), glutamine (Gln), glutamate (Glu), glutathione (GHS), Ins (myo-Inositol), lactate (Lac), N-acetylaspartate (NAA), N-acetylaspartylglutamate (NAAG), taurine (Tau), phosphoryl-choline + glycerol-phosphoryl-choline (tCho), N-acetylaspartate + N-acetylaspartylglutamate (tNA), creatine + phosphocreatine (tCr), Glu + Gln (Glx) and Lip13a, Lip13b, Lip09, MM09, Lip20, MM20, MM12, MM14, MM17, Lip13a + Lip13b, MM14 + Lip13a + Lip13b + MM12, MM09 + Lip09, MM20 + Lip20. Statistical analysis showed significantly different CRLBs: Asp, GABA, Gln, GSH, Ins, Lac, NAA, NAAG, Tau, tCho, tNA, Glx, MM20, MM20 + Lip20 (p < 0.001), tCr, MM12, MM17 (p < 0.01), and Lip20 (p < 0.05). The estimated ratio of cerebrospinal fluid (CSF) in the region of interest was calculated to be about 5%. Fitting performances are better, for the most part, with the in-house basis set, which is more precise than the vendor-provided basis set. In particular, Asp is expected to have reliable CRLB (<30%) at high field (e.g., 3T) in the left prefrontal cortex of human brain. The quantification of Asp was difficult, due to the inaccuracy of Asp fitting with the vendor-provided basis set.

Diffusion Measures of Subcortical Structures Using High-Field MRI.

The pathology of Parkinson's disease (PD) involves the death of dopaminergic neurons in the substantia nigra (SN), which slowly influences downstream basal ganglia pathways as dopamine transport diminishes. Diffusion magnetic resonance imaging (MRI) has been used to diagnose PD by assessing white matter connectivity in some brain areas. For this study, we applied Lead-DBS to human connectome project data to automatically segment 11 subcortical structures of 49 human connectome project subjects, reducing the reliance on manual segmentation for more consistency. The Lead-connectome pipeline, which utilizes DSI Studio to generate structural connectomes from each 3T and 7T diffusion image, was applied to 3T and 7T data to investigate possible differences in diffusion measures due to different acquisition protocols. Significantly higher fractional anisotropy (FA) values were found in the 3T left SN; significantly higher MD values were found in the 3T left SN and the right amygdala, SN, and subthalamic nucleus (STN); significantly higher AD values were found in the right RN and STN; and significantly higher RD values were found in the left RN and right amygdala. We illustrate a methodology for obtaining diffusion measures of basal ganglia and basal ganglia connectivity using diffusion images, as well as show possible differences in diffusion measures that can arise due to the differences in MRI acquisitions.

Functional and Structural Brain Abnormalities and Clinical Characteristics of Male Patients with Alcohol Dependence.

Even though many previous studies have reported structural or functional brain abnormalities in patients with alcohol dependence (ADPs), studies observing the structural and functional abnormalities associated with the clinical characteristics of ADPs utilizing a multimodal approach are still scarce. The aim of this study was to demonstrate structural and functional brain abnormalities and their association with the clinical characteristics of alcoholism in male ADPs. Fifteen healthy male controls (HCs) and 15 male ADPs who had been diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders 5 criteria underwent T1-weighted imaging and resting-state functional magnetic resonance imaging (MRI) scans. The MRI data were postprocessed using statistical parametric mapping for structural analysis and CONN-fMRI functional connectivity (FC) tools for functional analysis. In comparison with male HCs, male ADPs were characterized by significantly reduced volumes of the white matter in the left globus pallidus (GP) (p-FDR < 0.05). This region affected the altered resting-state FC patterns in male ADPs. Interestingly, an abnormal FC in the precuneus and its positive correlation with the alcohol-use disorder identification test score were observed in ADPs (r = 0.546, p = 0.036). Based on the observations, it could be concluded that the GP serves as a neural marker that impacts abnormal functional networks in men with alcohol dependence. These findings have important clinical implications as they provide insights into the neural mechanism underlying the anatomical, functional, and clinical features of alcoholism.

Salvia miltiorrhiza Alleviates Memory Deficit Induced by Ischemic Brain Injury in a Transient MCAO Mouse Model by Inhibiting Ferroptosis.

Salvia miltiorrhiza (SM) has been used in oriental medicine for its neuroprotective effects against cardiovascular diseases and ischemic stroke. In this study, we investigated the therapeutic mechanism underlying the effects of SM on stroke using a transient middle cerebral artery occlusion (tMCAO) mouse model. Our results showed that SM administration significantly attenuated acute brain injury, including brain infarction and neurological deficits, 3 days after tMCAO. This was confirmed by our magnetic resonance imaging (MRI) study, which revealed a reduction in brain infarction with SM administration, as well as our magnetic resonance spectroscopy (MRS) study, which demonstrated the restoration of brain metabolites, including taurine, total creatine, and glutamate. The neuroprotective effects of SM were associated with the reduction in gliosis and upregulation of inflammatory cytokines, such as interleukin-6 (IL-6) and Tumor necrosis factor-α (TNF-α), along with the upregulation of phosphorylated STAT3 in post-ischemic brains. SM also reduced the levels of 4-Hydroxynonenal (4-HNE) and malondialdehyde (MDA), which are markers of lipid peroxidation, induced by oxidative stress upregulation in the penumbra of the tMCAO mouse brain. SM administration attenuated ischemic neuronal injury by inhibiting ferroptosis. Additionally, post-ischemic brain synaptic loss and neuronal loss were alleviated by SM administration, as demonstrated by Western blot and Nissl staining. Moreover, daily administration of SM for 28 days after tMCAO significantly reduced neurological deficits and improved survival rates in tMCAO mice. SM administration also resulted in improvement in post-stroke cognitive impairment, as measured by the novel object recognition and passive avoidance tests in tMCAO mice. Our findings suggest that SM provides neuroprotection against ischemic stroke and has potential as a therapeutic agent.

Compressive sensing could accelerate 1H MR metabolic imaging in the clinic.

PURPOSE: To retrospectively evaluate the fidelity of magnetic resonance (MR) spectroscopic imaging data preservation at a range of accelerations by using compressed sensing. MATERIALS AND METHODS: The protocols were approved by the institutional review board of the university, and written informed consent to acquire and analyze MR spectroscopic imaging data was obtained from the subjects prior to the acquisitions. This study was HIPAA compliant. Retrospective application of compressed sensing was performed on 10 clinical MR spectroscopic imaging data sets, yielding 600 voxels from six normal brain data sets, 163 voxels from two brain tumor data sets, and 36 voxels from two prostate cancer data sets for analysis. The reconstructions were performed at acceleration factors of two, three, four, five, and 10 and were evaluated by using the root mean square error (RMSE) metric, metabolite maps (choline, creatine, N-acetylaspartate [NAA], and/or citrate), and statistical analysis involving a voxelwise paired t test and one-way analysis of variance for metabolite maps and ratios for comparison of the accelerated reconstruction with the original case. RESULTS: The reconstructions showed high fidelity for accelerations up to 10 as determined by the low RMSE (< 0.05). Similar means of the metabolite intensities and hot-spot localization on metabolite maps were observed up to a factor of five, with lack of statistically significant differences compared with the original data. The metabolite ratios of choline to NAA and choline plus creatine to citrate did not show significant differences from the original data for up to an acceleration factor of five in all cases and up to that of 10 for some cases. CONCLUSION: A reduction of acquisition time by up to 80%, with negligible loss of information as evaluated with clinically relevant metrics, has been successfully demonstrated for hydrogen 1 MR spectroscopic imaging.

Prediction of pathologic response to neoadjuvant chemotherapy in patients with breast cancer using diffusion-weighted imaging and MRS.

The aim of this study was to determine whether tumor size, MRS parameters and apparent diffusion coefficient (ADC) measurements could be applied to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC). Ninety patients with breast cancer (median size, 4.5 cm; range, 1.6-9.5 cm) were evaluated with single-voxel ¹H MRS and dynamic contrast-enhanced MRI. Diffusion-weighted imaging was performed in 41 of these patients using a 1.5-T scanner before and after completion of NAC. Pre- and post-treatment measurements and changes in tumor size, MRS parameters [absolute and normalized total choline-containing compound (tCho) integral and tCho signal-to-noise ratio (SNR)] and ADCs in pCR versus non-pCR were compared using the nonparametric Mann-Whitney test. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance of each parameter. After NAC, 30 patients (33%) showed pCR and 60 (67%) showed non-pCR. At pretreatment, ADC was the only significant parameter in differentiating between pCR and non-pCR [(0.83 ± 0.05) × 10⁻³ versus (0.97 ± 0.14) × 10⁻³ mm²/s] (p = 0.014). Post-treatment measurements after completion of NAC and changes in tumor size (both p < 0.001), MRS parameters (p = 0.027 and p = 0.020 for absolute tCho integral, p = 0.036 and p = 0.023 for normalized tCho integral, and p = 0.032 and p = 0.061 for tCho SNR) and ADC (p = 0.003 and p < 0.001) were significantly different between the pCR and non-pCR groups, except for changes in tCho SNR. In ROC analysis, the areas under the ROC curve (AUCs) of 0.63-0.73 were obtained for tumor size and MRS parameters. AUCs for pre- and post-treatment ADC and changes in ADC were 0.75, 0.80 and 0.96, respectively. The optimal cut-off of the percentage change in ADC for predicting pCR was 40.7%, yielding 100% sensitivity and 91% specificity. Patients with pCR showed significantly lower pretreatment ADCs than those with non-pCR. The change in ADC after NAC was the most accurate predictor of pCR.

Evaluation of breast cancer using proton MR spectroscopy: total choline peak integral and signal-to-noise ratio as prognostic indicators.

OBJECTIVE: The purpose of this article is to determine whether the peak integral and signal-to-noise ratio (SNR) of total choline-containing compounds obtained by MR spectroscopy (MRS) correlate with histologic biomarkers currently used for predicting prognosis in patients with breast cancer. MATERIALS AND METHODS: Single-voxel proton MRS using a 1.5-T scanner was performed in 184 patients (mean age, 48 years; range, 28-72 years) with breast cancer. We obtained absolute total choline-containing compound peak integral, total choline-containing compound peak integral normalized for the volume of interest, and SNR after MRI. On surgical pathology, pathologic subtype and prognostic factors such as nuclear grade, histologic grade, estrogen receptor (ER), HER-2≠neu, extensive intraductal component (EIC), lymphovascular invasion, and lymph node metastasis were also evaluated. Statistical analysis was performed using Mann-Whitney U test and Spearman rank correlation. RESULTS: The total choline-containing compound SNR, absolute total choline-containing compound peak integral, and normalized total choline-containing compound integral were significantly higher for invasive ductal carcinoma, cancer of high nuclear or histologic grade, and EIC-negative cancer (p < 0.001) than for in situ or other invasive carcinomas (p = 0.005), cancer of low nuclear or histologic grade (p = 0.009), and EIC-positive cancer (p = 0.017). There was a significant difference in the total choline-containing compound SNR between ER-positive and -negative groups (p = 0.007) and between triple-negative and non-triple-negative groups (p = 0.002). A positive correlation was found between the volume of interest (p < 0.001), tumor size (p = 0.011), and three MRS parameters (p = 0.003). CONCLUSION: Our study suggests that proton MRS can play a role in predicting prognostic indicators of tumor aggressiveness in patients with newly diagnosed breast cancer.

Diagnostic value of breast proton magnetic resonance spectroscopy at 1.5T in different histopathological types.

The purpose of this study was to investigate the usefulness of quantitative proton magnetic resonance spectroscopy ((1)H-MRS) for characterizing breast lesions at 1.5T, and to evaluate the diagnostic performance of in vivo breast (1)H-MRS using receiver operating characteristics (ROC) analysis. 112 patients (99 malignant and 13 benign tumors) who were scanned with the MRI/MRS protocol were included in this study. Choline-containing compounds (tCho) levels were measured and compared with histological findings. The measured tCho levels in this work had range of 0.08-9.99 mmol/kg from 65 (66%) of 99 patients with malignant tumors. Of the 13 benign lesions, (1)H-MRS detected one as false positive, with tCho level of 0.66 mmol/kg. The optimal tCho level cutoff point that yielded the highest accuracy was found to be >0.0 mmol/kg. The resulting sensitivity was 66% and specificity 92% for distinguishing benign from malignant lesions. The tCho levels were found to be higher in invasive cancer compared to ductal carcinoma in situ or benign lesions, possibly associated with more aggressive behavior or faster cell replication in invasive cancer. Quantitative in vivo (1)H-MRS may provide useful information for characterizing histopatholoigical types in breast cancer.

White Matter Microstructural Alterations in Newly Diagnosed Parkinson's Disease: A Whole-Brain Analysis Using dMRI.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by cardinal motor symptoms and other non-motor symptoms. Studies have investigated various brain areas in PD by detecting white matter alterations using diffusion magnetic resonance imaging processing techniques, which can produce diffusion metrics such as fractional anisotropy and quantitative anisotropy. In this study, we compared the quantitative anisotropy of whole brain regions throughout the subcortical and cortical areas between newly diagnosed PD patients and healthy controls. Additionally, we evaluated the correlations between the quantitative anisotropy of each region and respective neuropsychological test scores to identify the areas most affected by each neuropsychological dysfunction in PD. We found significant quantitative anisotropy differences in several subcortical structures such as the basal ganglia, limbic system, and brain stem as well as in cortical structures such as the temporal lobe, occipital lobe, and insular lobe. Additionally, we found that quantitative anisotropy of some subcortical structures such as the basal ganglia, cerebellum, and brain stem showed the highest correlations with motor dysfunction, whereas cortical structures such as the temporal lobe and occipital lobe showed the highest correlations with olfactory dysfunction in PD. Our study also showed evidence regarding potential neural compensation by revealing higher diffusion metric values in early-stage PD than in healthy controls. We anticipate that our results will improve our understanding of PD's pathophysiology.

White Matter Connectivity between Structures of the Basal Ganglia using 3T and 7T.

Analysis of the basal ganglia has been important in investigating the effects of Parkinson's disease as well as treatments for Parkinson's disease. One method of analysis has been using MRI for non-invasively segmenting the basal ganglia, then investigating significant parameters that involve the basal ganglia, such as fiber orientations and positional markers for deep brain stimulation (DBS). Following enhancements to optimizations and improvements to 3T and 7T MRI acquisitions, we utilized Lead-DBS on human connectome project data to automatically segment the basal ganglia of 49 human connectome project subjects, reducing the reliance on manual segmentation for more consistency. We generated probabilistic tractography streamlines between each segmentation pair using 3T and 7T human connectome diffusion data to observe any major differences in tractography streamline patterns that can arise due to tradeoffs from different field strengths and acquisitions. Tractography streamlines generated between basal ganglia structures using 3T images showed less standard deviation in streamline count than using 7T images. Mean tractography streamline counts generated using 3T diffusion images were all higher in count than streamlines generated using 7T diffusion images. We illustrate a potential method for analyzing the structural connectivity between basal ganglia structures, as well as visualize possible differences in probabilistic tractography that can arise from different acquisition protocols.

Dynamic synovial fibroblasts are modulated by NBCn1 as a potential target in rheumatoid arthritis.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by aggressive fibroblast-like synoviocytes (FLSs) and pannus formation. Various therapeutic strategies have been developed against inflammatory cytokines in RA in recent decades. Based on the migratory features of FLSs, we examined whether modulation of the migratory module attenuates RA severity. In this study, inflamed synovial fluid-stimulated FLSs exhibited enhanced migration and migratory apparatus expression, and sodium bicarbonate cotransporter n1 (NBCn1) was identified in primary cultured RA-FLSs for the first time. The NBC inhibitor S0859 attenuated the migration of FLSs induced with synovial fluid from patients with RA or with TNF-α stimulation. Inhibition of NBCs with S0859 in a collagen-induced arthritis (CIA) mouse model reduced joint swelling and destruction without blood, hepatic, or renal toxicity. Primary FLSs isolated from the CIA-induced mouse model also showed reduced migration in the presence of S0859. Our results suggest that inflammatory mediators in synovial fluid, including TNF-α, recruit NBCn1 to the plasma membrane of FLSs to provide dynamic properties and that modulation of NBCn1 could be developed into a therapeutic strategy for RA.

Signal-to-Noise Ratio Enhancement of Single-Voxel In Vivo 31P and 1H Magnetic Resonance Spectroscopy in Mice Brain Data Using Low-Rank Denoising.

Magnetic resonance spectroscopy (MRS) is a noninvasive technique for measuring metabolite concentration. It can be used for preclinical small animal brain studies using rodents to provide information about neurodegenerative diseases and metabolic disorders. However, data acquisition from small volumes in a limited scan time is technically challenging due to its inherently low sensitivity. To mitigate this problem, this study investigated the feasibility of a low-rank denoising method in enhancing the quality of single voxel multinuclei (31P and 1H) MRS data at 9.4 T. Performance was evaluated using in vivo MRS data from a normal mouse brain (31P and 1H) and stroke mouse model (1H) by comparison with signal-to-noise ratios (SNRs), Cramer-Rao lower bounds (CRLBs), and metabolite concentrations of a linear combination of model analysis results. In 31P MRS data, low-rank denoising resulted in improved SNRs and reduced metabolite quantification uncertainty compared with the original data. In 1H MRS data, the method also improved the SNRs, CRLBs, but it performed better for 31P MRS data with relatively simpler patterns compared to the 1H MRS data. Therefore, we suggest that the low-rank denoising method can improve spectra SNR and metabolite quantification uncertainty in single-voxel in vivo 31P and 1H MRS data, and it might be more effective for 31P MRS data. The main contribution of this study is that we demonstrated the effectiveness of the low-rank denoising method on small-volume single-voxel MRS data. We anticipate that our results will be useful for the precise quantification of low-concentration metabolites, further reducing data acquisition voxel size, and scan time in preclinical MRS studies.

In vivo 1H MRS in the assessment of the therapeutic response of breast cancer patients.

MRI and in vivo MRS have rapidly evolved as sensitive tools for diagnosis and therapeutic monitoring in cancer research. In vivo MRS provides information on tumor metabolism, which is clinically valuable in the diagnosis and assessment of tumor response to therapy for the management of women with breast diseases. Several centers complement breast MRI studies with (1)H MRS to improve the specificity of diagnosis. Malignant breast tissues show elevated water-to-fat ratio and choline-containing compounds (total choline, tCho), and any effect of therapy on tissue viability or metabolism will be manifested as changes in these levels. Sequential (1)H MRS studies have shown significantly reduced tCho levels during the course of therapy in patients who were responders. However, there are challenges in using in vivo MRS because of the relatively low sensitivity in detecting the tCho resonance with decreased lesion size or significant reduction in the tumor volume during therapy. MRS is also technically challenging because of the low signal-to-noise ratio and heterogeneous distribution of fat and glandular tissues in the breast. MRS is best utilized for the diagnosis of focal masses, most commonly seen in patients with ductal-type neoplasms; however, it has limitations in detecting nonfocal masses, such as the linear pattern of tumors seen in invasive lobular carcinoma. Further work is required to assess the clinical utility of quantitative MRS, with the goal of automation, which will reduce the subjectivity currently inherent in both qualitative and semi-quantitative MRS.

Diffusion Measure Changes of Substantia Nigra Subregions and the Ventral Tegmental Area in Newly Diagnosed Parkinson's Disease.

Historically, studies have extensively examined the basal ganglia in Parkinson's disease for specific characteristics that can be observed with medical imaging. One particular methodology used for detecting changes that occur in Parkinson's disease brains is diffusion tensor imaging, which yields diffusion indices such as fractional anisotropy and radial diffusivity that have been shown to correlate with axonal damage. In this study, we compare the diffusion measures of basal ganglia structures (with substantia nigra divided into subregions, pars compacta, and pars reticula), as well as the diffusion measures of the diffusion tracts that pass through each pair of basal ganglia structures to see if significant differences in diffusion measures can be observed in structures or tracts in newly diagnosed Parkinson's disease patients. Additionally, we include the ventral tegmental area, a structure connected to various basal ganglia structures affected by dopaminergic neuronal loss and have historically shown significant alterations in Parkinson's disease, in our analysis. We found significant fractional anisotropy differences in the putamen, and in the diffusion tracts that pass through pairs of both substantia nigra subregions, subthalamic nucleus, parabrachial pigmental nucleus, ventral tegmental area. Additionally, we found significant radial diffusivity differences in diffusion tracts that pass through the parabrachial nucleus, putamen, both substantia nigra subregions, and globus pallidus externa. We were able to find significant diffusion measure differences in structures and diffusion tracts, potentially due to compensatory mechanisms in response to dopaminergic neuronal loss that occurs in newly diagnosed Parkinson's disease patients.

Association between Changes in Cortical Thickness and Functional Connectivity in Male Patients with Alcohol-dependence.

Many studies have reported structural or functional brain changes in patients with alcohol-dependence (ADPs). However, there has been an insufficient number of studies that were able to identify functional changes along with structural abnormalities in ADPs. Since neuronal cell death can lead to abnormal brain function, a multimodal approach combined with structural and functional studies is necessary to understand definitive neural mechanisms. Here, we explored regional difference in cortical thickness and their impact on functional connection along with clinical relevance. Fifteen male ADPs who have been diagnosed by the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5) underwent highresolution T1 and resting-state functional magnetic resonance imaging (MRI) scans together with 15 male healthy controls (HCs). The acquired MRI data were post-processed using the Computational Anatomy Toolbox (CAT 12) and CONN-fMRI functional connectivity (FC) toolbox with Statistical Parametric Mapping (SPM 12). When compared with male HCs, the male ADPs showed significantly reduced cortical thickness in the left postcentral gyrus (PoCG), an area responsible for altered resting-state FC patterns in male ADPs. Statistically higher FCs in PoCG-cerebellum (Cb) and lower FCs in PoCG-supplementary motor area (SMA) were observed in male ADPs. In particular, the FCs with PoCG-Cb positively correlated with alcohol use disorders identification test (AUDIT) scores in male ADPs. Our findings suggest that the association of brain structural abnormalities and FC changes could be a characteristic difference in male ADPs. These findings can be useful in understanding the neural mechanisms associated with anatomical, functional and clinical features of individuals with alcoholism.

Deterministic Tractography Analysis of Rat Brain Using SIGMA Atlas in 9.4T MRI.

Preclinical studies using rodents have been the choice for many neuroscience researchers due totheir close reflection of human biology. In particular, research involving rodents has utilized MRI to accurately identify brain regions and characteristics by acquiring high resolution cavity images with different contrasts non-invasively, and this has resulted in high reproducibility and throughput. In addition, tractographic analysis using diffusion tensor imaging to obtain information on the neural structure of white matter has emerged as a major methodology in the field of neuroscience due to its contribution in discovering significant correlations between altered neural connections and various neurological and psychiatric diseases. However, unlike image analysis studies with human subjects where a myriad of human image analysis programs and procedures have been thoroughly developed and validated, methods for analyzing rat image data using MRI in preclinical research settings have seen significantly less developed. Therefore, in this study, we present a deterministic tractographic analysis pipeline using the SIGMA atlas for a detailed structural segmentation and structural connectivity analysis of the rat brain's structural connectivity. In addition, the structural connectivity analysis pipeline presented in this study was preliminarily tested on normal and stroke rat models for initial observation.