The role of multiparametric MRI in predicting lymphovascular invasion in breast cancer patients.

Background: This study aims to investigate the efficacy of multifactorial MRI in diagnosing breast cancer, specifically in the context of predicting lymphovascular invasion (LVI).Materials & methods: The patients were stratified into two groups: the primary group (100 patients) and the validation group (100 patients), based on essential characteristics. Multifactorial MRI, encompassing tumor size evaluation, diffusion coefficient assessment and dynamic contrast enhancement, was employed for patient examination.Results: Statistically significant differences were observed in tumor size, diffusion coefficient and dynamic contrast enhancement between groups with LVI (LVI+) and those without (LVI-). Key parameters were identified for predicting the degree of invasion.Conclusion: The results affirm the effectiveness of multifactorial MRI in forecasting LVI.

[Box: see text].

Voxel-based morphometry and a deep learning model for the diagnosis of early Alzheimer's disease based on cerebral gray matter changes.

This study aimed to analyse cerebral grey matter changes in mild cognitive impairment (MCI) using voxel-based morphometry and to diagnose early Alzheimer's disease using deep learning methods based on convolutional neural networks (CNNs) evaluating these changes. Participants (111 MCI, 73 normal cognition) underwent 3-T structural magnetic resonance imaging. The obtained images were assessed using voxel-based morphometry, including extraction of cerebral grey matter, analyses of statistical differences, and correlation analyses between cerebral grey matter and clinical cognitive scores in MCI. The CNN-based deep learning method was used to extract features of cerebral grey matter images. Compared to subjects with normal cognition, participants with MCI had grey matter atrophy mainly in the entorhinal cortex, frontal cortex, and bilateral frontotemporal lobes (p < 0.0001). This atrophy was significantly correlated with the decline in cognitive scores (p < 0.01). The accuracy, sensitivity, and specificity of the CNN model for identifying participants with MCI were 80.9%, 88.9%, and 75%, respectively. The area under the curve of the model was 0.891. These findings demonstrate that research based on brain morphology can provide an effective way for the clinical, non-invasive, objective evaluation and identification of early Alzheimer's disease.

Evaluation of a continuous-time random-walk diffusion model for the differentiation of malignant and benign breast lesions and its association with Ki-67 expression.

The purpose of the current study was to evaluate the performance of a continuous-time random-walk (CTRW) diffusion model for differentiating malignant and benign breast lesions and to consider the potential association between CTRW parameters and the Ki-67 expression. Sixty-four patients (46.2 ± 11.4 years) with breast lesions (29 malignant and 35 benign) were evaluated with the CTRW model, intravoxel incoherent motion model, and diffusion-weighted imaging. Echo planar diffusion-weighted imaging was conducted using 13 b-values (0-3000 s/mm2 ). Three CTRW model parameters, including an anomalous diffusion coefficient Dm , and two parameters related to temporal and spatial diffusion heterogeneity, α and ß, respectively, were obtained, and had MRI b-values of 0-3000 s/mm2 . Receiver operating characteristic (ROC) analysis was conducted to determine the sensitivity, specificity, and diagnostic accuracy of CTRW parameters for differentiating malignant from benign breast lesions. In malignant breast lesions, the CTRW parameters Dm , α, and ß were significantly lower than the corresponding parameters of benign breast lesions. In the malignant breast lesion group, the CTRW parameter Dm was significantly lower in high Ki-67 expression than in low Ki-67 expression. In ROC analysis, the combination of CTRW parameters (Dm , α, ß) demonstrated the highest area under the curve value (0.985) and diagnostic accuracy (94.23%) in differentiating malignant and benign breast lesions. The CTRW model effectively differentiated malignant from benign breast lesions. The CTRW diffusion model offers a new way for noninvasive assessment of breast malignancy and better understanding of the proliferation of malignant lesions.

Application value of T2 fluid-attenuated inversion recovery sequence based on deep learning in static lacunar infarction.

BACKGROUND: Regular monitoring of static lacunar infarction (SLI) lesions plays an important role in preventing disease development and managing prognosis. Magnetic resonance imaging is one method used to monitor SLI lesions. PURPOSE: To evaluate the image quality of the T2 fluid-attenuated inversion recovery (T2-FLAIR) sequence using artificial intelligence-assisted compressed sensing (ACS) in detecting SLI lesions and assess its clinical applicability. METHODS: A total of 42 patients were prospectively enrolled and scanned by T2-FLAIR. Two independent readers reviewed the images acquired with accelerated modes 1D (acceleration factor 2) and ACS (acceleration factors 2, 3, and 4). The overall image quality and lesion image quality were analyzed, as were signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and number of lesions between groups. RESULTS: The subjective assessment of overall brain image quality and lesion image quality was consistent between the two readers. The lesion display quality and the overall image quality were better with the traditional 1D acceleration method than with the ACS accelerated method. There was no significant difference in the SNR of the lacunar infarction in the images between the groups. The CNR of the images with the 1D acceleration mode was significantly lower than that of images with the ACS acceleration mode. Images with the 1D, ACS2, and ACS3 acceleration modes showed no significant differences in terms of detecting lesions but scan time can be reduced by 40% (1D vs. ACS3). CONCLUSION: ACS acceleration mode can greatly reduce the scan time. In addition, the images have good SNR, high CNR, and strong SLI lesion detection ability.

High-resolution NMR metabolomics of patients with subjective cognitive decline plus: Perturbations in the metabolism of glucose and branched-chain amino acids.

BACKGROUND: "Subjective cognitive decline plus" (SCD plus) increases the risk of Alzheimer's disease (AD), and this may be an early stage of AD that precedes amnestic mild cognitive impairment (aMCI). We examined alterations of serum metabolites and metabolic pathways in SCD plus subjects using 1H-magnetic resonance spectroscopy (1H NMR) metabolomics. METHODS: Serum samples from subjects with SCD plus (n = 32), aMCI (n = 33), and elderly controls (ECs, n = 41) were analyzed using an 800MHz NMR spectrometer. Multivariate analyses were used to identify serum metabolites, and two machine-learning methods were used to evaluate the diagnostic power of these metabolites in distinguishing SCD plus subjects, aMCI subjects, and ECs. RESULTS: Eight metabolites differentiated SCD plus from EC subjects. A random forest (RF) model discriminated SCD plus from EC subjects with an accuracy of 0.883 and an area under the receiver operating characteristic curve (AUROC) of 0.951. A support vector machine (SVM) model had an accuracy of 0.857 and an AUROC of 0.946. Nine other metabolites distinguished SCD plus from aMCI subjects. An RF model discriminated SCD plus from aMCI subjects (accuracy: 0.975, AUROC: 0.998) and an SVM model also discriminated these two groups (accuracy: 0.955, AUROC: 0.991). Disturbances of glucose and branched-chain amino acid (BCAA) metabolism were the most striking features of SCD plus subjects, and valine was positively correlated with Auditory Verbal Learning Test delayed-recall score. CONCLUSIONS: Serum metabolomics using 1H NMR provided noninvasive identification of perturbations in glucose and BCAA metabolism in subjects with SCD plus.

Application of machine learning in the analysis of multiparametric MRI data for the differentiation of treatment responses in breast cancer: retrospective study.

OBJECTIVE: The objective of this study is to develop and validate a multiparametric MRI model employing machine learning to predict the effectiveness of treatment and the stage of breast cancer. METHODS: The study encompassed 400 female patients diagnosed with breast cancer, with 200 individuals allocated to both the control and experimental groups, undergoing examinations in Shenzhen, China, during the period 2017-2023. This study pertains to retrospective research. Multiparametric MRI was employed to extract data concerning tumor size, blood flow, and metabolism. RESULTS: The model achieved high accuracy, predicting treatment outcomes with an accuracy of 92%, sensitivity of 88%, and specificity of 95%. The model effectively classified breast cancer stages: stage I, 38% ( P = 0.027); stage II, 72% ( P = 0.014); stage III, 50% ( P = 0.032); and stage IV, 45% ( P = 0.041). CONCLUSIONS: The developed model, utilizing multiparametric MRI and machine learning, exhibits high accuracy in predicting the effectiveness of treatment and breast cancer staging. These findings affirm the model's potential to enhance treatment strategies and personalize approaches for patients diagnosed with breast cancer. Our study presents an innovative approach to the diagnosis and treatment of breast cancer, integrating MRI data with machine learning algorithms. We demonstrate that the developed model exhibits high accuracy in predicting treatment efficacy and differentiating cancer stages. This underscores the importance of utilizing MRI and machine learning algorithms to enhance the diagnosis and individualization of treatment for this disease.

Transcriptomic Analysis Reveals Diverse Expression of Scorpion Toxin Genes in Mesobuthus martensii.

Scorpions, an ancient group of venomous invertebrates, have existed for over 430 million years. Their toxins, important for predation and defense, exhibit a variety of biological and pharmacological activities. Research on scorpion toxins has spanned decades. Notably, the toxin genes of Mesobuthus martensii (Scorpiones: Buthidae), a well-known Chinese herbal medicine, have been described at genomic and proteomic levels. However, previous studies primarily focused on the toxin genes expressed in the venom glands, overlooking their expression in multiple tissues. This study analyzed transcriptomes from 14 tissues of M. martensii. Gene annotation revealed 83 toxin and toxin-like genes, including those affecting sodium, potassium, calcium, and chloride ion channels. Approximately 70% of toxin genes were highly expressed in the vesicle; additionally, some exhibited low or no expression in the vesicle while showing high expression in other tissues. Beyond the vesicle, high expression levels of toxin genes were observed in metasoma segments II-V, blood, lateral eyes, chelicerae, legs, pedipalp chelae, femurs, and patellae. This expression pattern suggests that toxin genes are recruited from multiple tissues and may help prevent intraspecific harm during courtship and competition for prey. These findings inspire further research into the evolutionary recruitment process of scorpion toxins.

Quantification of Iron Deposition in the Brain of Hypertensive Patients Using 3D-enhanced Susceptibility-weighted Angiography (ESWAN).

BACKGROUND: Cerebral microbleeds (CMBs) are commonly present in patients with hypertension, producing iron-containing metabolites. A small amount of regional iron deposition is hardly discernible on conventional magnetic resonance imaging (MRI). Three-dimensional enhanced susceptibility-weighted angiography (ESWAN) provides tissue images with high spatial resolution and signal-noise ratio, and has been widely used to measure brain iron deposition in neurodegenerative diseases and intracranial hemorrhage. OBJECTIVE: The study aimed to demonstrate iron deposition in the brain of hypertensive patients using ESWAN. METHOD: Twenty-seven hypertension patients, with or without CMBs, and 16 matched healthy controls (HCs) were enrolled. From the post-processed ESWAN images, phase and magnitude values of the regions of interest (ROIs) were calculated. Two-sample t-test and one-way variance analysis were applied to compare groups. The relationship between ESWAN parameters and clinical variables was assessed using Pearson's correlation coefficient. RESULTS: Compared to HCs, the phase value of the hippocampus, head of caudate nucleus (HCN), and substantia nigra (SN) was decreased in hypertension with the CMBs subgroup, while that of HCN and SN was decreased in hypertension without CMBs subgroup. Similarly, the magnitude value of the hippocampus, HCN, thalamus red nucleus, and SN was significantly lower in the hypertension group than HCs. In addition, the phase and magnitude values showed a correlation with clinical variables, including disease duration and blood pressure. CONCLUSION: Deep grey matter nuclei displayed greater iron content in hypertension patients. Iron deposition may precede the appearance of CMBs on MRI, serving as a potential marker of microvascular damage.

Quantitative multivoxel proton MR spectroscopy study of brain metabolites in patients with amnestic mild cognitive impairment: a pilot study.

INTRODUCTION: The purpose of this study is to investigate brain metabolic changes in patients with amnestic mild cognitive impairment (aMCI) using multivoxel proton MR spectroscopy ((1)H-MVS). METHODS: Fourteen aMCI patients and fifteen healthy control subjects participated in this experiment. All MR measurements were acquired using a 1.5-T GE scanner. (1)H-MVS point resolved spectroscopy (2D PROBE-CSI PRESS) pulse sequence (TE = 35 ms; TR = 1,500 ms; phase × frequency, 18 × 18) was used for acquiring MRS data. All data were post-processed using Spectroscopy Analysis by General Electric software and linear combination of model (LCModel). The absolute concentrations of N-acetylaspartate (NAA), choline (Cho), myoinositol (MI), creatine (Cr), and the metabolite ratios of NAA/Cr, Cho/Cr, MI/Cr, and NAA/MI were measured bilaterally in the posterior cingulate gyrus (PCG), inferior precuneus (Pr), paratrigonal white matter (PWM), dorsal thalamus (DT), and lentiform nucleus (LN). RESULTS: Patients with aMCI displayed significantly lower NAA levels in the bilateral PCG (p < 0.01), PWM (p < 0.05), and left inferior Pr (p < 0.05). The metabolite ratio of NAA/MI was decreased in the bilateral PCG (p < 0.01) and PWM (p < 0.05) and in the left DT (p < 0.01). NAA/Cr was decreased in the left PCG (p < 0.01), DT (p < 0.05), right PWM (p < 0.05), and LN (p < 0.05). However, MI/Cr was elevated in the right PCG (p < 0.01) and left PWM (p < 0.05). Significantly increased Cho level was also evident in the left PWM (p < 0.05). CONCLUSIONS: Our observations of decreased NAA, NAA/Cr, and NAA/MI, in parallel with increased Cho and MI/Cr might be characteristic of aMCI patients.

Value of Intravoxel Incoherent Motion (IVIM) Imaging for Differentiation between Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma.

Efficient noninvasive imaging techniques in the differentiation of intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are very important because of their different management and prognosis. Our purpose was to evaluate the difference of parameters extracted from intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) between the two groups and their performance for the differentiation, as well as the significance of perfusion information. IVIM studies (9 b-values) in 41 patients with either ICC or HCC were reviewed retrospectively by two observers. Diffusion coefficient (D), pseudodiffusion coefficient (D∗), perfusion fraction (f), ADC, and the mean percentage of parenchymal enhancement (MPPE) at 30 s after contrast-enhancement were calculated and compared between ICC and HCC. The relationship between D∗, f values, and MPPE was evaluated by Spearman's correlation test. The diagnostic efficacy of all parameters was analyzed by the receiver operating characteristic (ROC) curve. Interobserver and intraobserver agreements were analyzed. The parameters (D and ADC) of ICC were distinctly higher than those of HCC; whereas the parameters (f and MPPE of arterial phase) were distinctly lower (all false discovery rate [FDR]-corrected P < 0.05). The metric D∗ value of ICC was slightly higher than that of HCC (71.44 vs 69.41) with FDR-corrected P > 0.05. Moreover, the value of parameter D was significantly lower than that of ADC (FDR-corrected P < 0.05). The parameters (D and f values) extracted from IVIM showed excellent diagnostic efficiency in the identification, and the diagnostic efficiency of D value was significantly higher than that of the ADC. There were positive correlations between perfusion-related parameters (D∗, f values) and MPPE. Interobserver and intraobserver agreements were excellent or perfect in measurements of all parameters. Parameters derived from IVIM were valuable for distinguishing ICC and HCC. Moreover, the D value showed better diagnostic efficiency for the differential diagnosis than monoexponential fitting-derived ADC value. Meanwhile, the significant correlation between perfusion-related parameters and MPPE demonstrates that specific IVIM metrics may serve as a noninvasive indicator for the vascular perfusion information of ICC and HCC.

Proton Magnetic Resonance Spectroscopy for Diagnosis of Non-Motor Symptoms in Parkinson's Disease.

Background: The current diagnosis of Parkinson's disease (PD) is mainly based on the typical clinical manifestations. However, 60% dopaminergic neurons have died when the typical clinical manifestations occur. Predictive neurobiomarkers may help identify those PD patients having non-motor disorders or in different stage and achieving the aim of early diagnosis. Up to date, few if any neuroimaging techniques have been described useful for non-movement disorders diagnosis in PD patients. Here, we investigated the alteration of metabolites in PD patients in different stage of PD and non-motor symptoms including sleep, gastrointestinal and cognitive dysfunction, by using the 1H-MRS. Methods: A total of 48 subjects were included between 2017 and 2019: 37 PD (15 men, age 47-82 years) and 11 healthy people (8 men, age 49-74 years). All participants underwent MRI and multi-voxel 1H-MRS examination within 3 days in admission. Six kinds of metabolites, such as creatine (Cr), N-acetyl aspartate/creatine (NAA/Cr), N-acetyl aspartate/choline (NAA/Cho), choline/creatine (Cho/Cr), lipid/creatine (LL/Cr), and myo-Inositol/creatine ratio (mI/Cr) were tested among the PD group and the control groups. Statistical analyses and correlation analyses were performed by using SPSS. The p < 0.05 was considered statistically significant. Results: Compared late PD group with a control group or early group, higher Cr ratio and lower NAA/Cr ratio were observed in the late PD group (p < 0.05). The mI/Cr in the late PD group was also lower than that in the early PD group (p < 0.05). Regarding the relationship between metabolites and NMS, Cho/Cr was higher in the sleep disorder group, whereas mI/Cr was lower in the gastrointestinal dysfunction group in comparison with the non-symptom groups. Moreover, Cr, Cho/Cr, mI/Cr, and LL/Cr were identified to have higher concentrations in the cognitive group in thalamus. Conclusions: Proton magnetic resonance spectroscopy is an advanced tool to quantify the metabolic changes in PD. Three biomarkers (Cr, NAA/Cr, and mI/Cr) were detected in the late stage of PD, suggesting that these markers might be potential to imply the progression of PD. In addition, subgroups analysis showed that MRS of thalamus is a sensitive region for the detection of cognitive decline in PD, and the alteration of neurochemicals (involving Cr, Cho, mI, and LL) may be promising biomarkers to predict cognitive decline in PD.

Brain neurometabolites differences in individuals with subjective cognitive decline plus: a quantitative single- and multi-voxel proton magnetic resonance spectroscopy study.

BACKGROUND: Subjective cognitive decline plus could be an extremely early phase of Alzheimer's disease; however, changes of N-acetylaspartate, myoinositol, and N-acetylaspartate/myoinositol is still unknown at this stage. This study aimed to explore brain neurometabolic alterations in patients with subjective cognitive decline plus using quantitative single-voxel and multi-voxel 1H-magnetic resonance spectroscopy. METHODS: A total of 91 participants were enrolled and underwent a GE 3.0-T magnetic resonance imaging, including 33 elderly controls, 27 patients with subjective cognitive decline plus, and 31 patients with amnestic mild cognitive impairment (MCI). Single-voxel and multi-voxel 1H-magnetic resonance spectroscopy were used to investigate the differences in neurometabolite levels among the three groups. RESULTS: Compared with elderly controls, patients with subjective cognitive decline plus showed significant decline in N-acetylaspartate and N-acetylaspartate/myoinositol values in multiple regions, and amnestic MCI participants demonstrated more significant decreased N-acetylaspartate and N-acetylaspartate/myoinositol levels in multiple regions. The combined concentrations of N-acetylaspartate with myoinositol showed an excellent discrimination between those with subjective cognitive decline plus and elderly controls as compared to that obtained using N-acetylaspartate/myoinositol ratios with the area under the receiver operating characteristic curve of 0.895 and 0.860, respectively. Likewise, the combined area under the curve for differentiating patients with subjective cognitive decline plus from amnestic MCI was obtained using the combined levels of N-acetylaspartate with myoinositol was 0.892. This was also higher than the combined area under the curve of 0.836 obtained using N-acetylaspartate/myoinositol ratios. Moreover, N-acetylaspartate levels in the left hippocampus and left posterior cingulate cortex (PCC) was positively related to the Auditory Verbal Learning Test delayed recall scores in patients with subjective cognitive decline plus, whereas only the N-acetylaspartate/myoinositol ratio was positively related to this scale scores in the left hippocampus. CONCLUSIONS: Quantitative single-voxel and multi-voxel 1H-magnetic resonance spectroscopy can provide valuable information to detect alterative brain neurometabolites characteristics in patients with subjective cognitive decline plus. N-acetylaspartate concentrations may be used as one of the earliest neuroimaging markers at this stage, while N-acetylaspartate/myoinositol ratio could be more suitable for monitoring Alzheimer's disease progression.

Microstructural and Cerebral Blood Flow Abnormalities in Subjective Cognitive Decline Plus: Diffusional Kurtosis Imaging and Three-Dimensional Arterial Spin Labeling Study.

Objective: To explore microstructural and cerebral blood flow (CBF) abnormalities in individuals with subjective cognitive decline plus (SCD plus) using diffusional kurtosis imaging (DKI) and three-dimensional (3D) arterial spin labeling (ASL). Methods: Twenty-seven patients with SCD plus, 31 patients with amnestic mild cognitive impairment (aMCI), and 33 elderly controls (ECs) were recruited and underwent DKI and 3D ASL using a GE 3.0-T MRI. Mean kurtosis (MK), fractional anisotropy (FA), mean diffusivity (MD), and CBF values were acquired from 24 regions of interest (ROIs) in the brain, including the bilateral hippocampal (Hip) subregions (head, body, and tail), posterior cingulate cortex (PCC), precuneus, dorsal thalamus subregions (anterior nucleus, ventrolateral nucleus, and medial nucleus), lenticular nucleus, caput nuclei caudati, white matter (WM) of the frontal lobe, and WM of the occipital lobe. Pearson's correlation analysis was performed to assess the relationships among the DKI-derived parameters, CBF values, and key neuropsychological tests for SCD plus. Results: Compared with ECs, participants with SCD plus showed a significant decline in MK and CBF values, mainly in the Hip head and PCC, and participants with aMCI exhibited more significant abnormalities in the MK and CBF values than individuals with ECs and SCD plus in multiple regions. Combined MK values showed better discrimination between patients with SCD plus and ECs than that obtained using CBF levels, with areas under the receiver operating characteristic (ROC) curve (AUC) of 0.874 and 0.837, respectively. Similarly, the AUC in discriminating SCD plus from aMCI patients obtained using combined MK values was 0.823, which was also higher than the combined AUC of 0.779 obtained using CBF values. Moreover, MK levels in the left Hip (h) and left PCC positively correlated with the auditory verbal learning test-delayed recall (AVLT-DR) score in participants with SCD plus. By contrast, only the CBF value in the left Hip head positively correlated with the AVLT-DR score. Conclusions: Our results provide new evidence of microstructural and CBF changes in patients with SCD plus. MK may be used as an early potential neuroimaging biomarker and may be a more sensitive DKI parameter than CBF at the very early stage of Alzheimer's disease (AD).

CircRNA hsa_circ_0004771 promotes esophageal squamous cell cancer progression via miR-339-5p/CDC25A axis.

Aim: The role of circRNAs in esophageal squamous cell cancer (ESCC) remains unclear. Materials & methods: Here we profiled six pair plasma circRNA in ESCC based on RNA sequencing, and then verified the elevation of hsa_circ_0004771 in 20 cancer tissues and 105 pair case-control plasma samples by quantitative reverse transcriptase PCR. Results: The upregulation of hsa_circ_0004771 was correlated with heavier tumor burden and poor prognosis, knockdown of it inhibited the ESCC cells proliferation both in vitro and in vivo. Mechanistically, hsa_circ_0004771 positively regulated CDC25A by acting as a molecular sponge of miR-339-5p and rescue assay confirmed this regulatory relationship. Conclusion: These results suggested that hsa_circ_0004771 can serve as a general less-invasive biomarker and may provide diagnostic and prognostic value in carcinoma.

Noninvasive Detection of Extracellular pH in Human Benign and Malignant Liver Tumors Using CEST MRI.

PURPOSE: In this study, we aimed to use 3T magnetic resonance imaging (MRI), which is clinically available, to determine the extracellular pH (pHe) of liver tumors and prospectively evaluate the ability of chemical exchange saturation transfer (CEST) MRI to distinguish between benign and malignant liver tumors. METHODS: Different radiofrequency irradiation schemes were assessed for ioversol-based pH measurements at 3T. CEST effects were quantified in vitro using the asymmetric magnetization transfer ratio (MTRasym) at 4.3 ppm from the corrected Z spectrum. Generalized ratiometric analysis was conducted by rationing resolved ioversol CEST effects at 4.3 ppm at a flip angle of 60 and 350°. Fifteen patients recently diagnosed with hepatic carcinoma and five patients diagnosed with hepatic hemangioma [1 male; mean age, 48.6 (range, 37-59) years] were assessed. RESULTS: By conducting dual-power CEST MRI, the pH of solutions was determined to be 6.0-7.2 at 3T in vitro. In vivo, ioversol signal intensities in the tumor region showed that the extracellular pH in hepatic carcinoma was acidic(mean ± standard deviation, 6.66 ± 0.19), whereas the extracellular pH was more physiologically neutral in hemangioma (mean ± standard deviation, 7.34 ± 0.09).The lesion size was similar between CEST pH MRI and T2-weighted imaging. CONCLUSION: dual-power CEST MRI can detect extracellular pH in human liver tumors and can provide molecular-level diagnostic tools for differentiating benign and malignant liver tumors at 3T.

Exploring potential biomarkers of early stage esophageal squamous cell carcinoma in pre- and post-operative serum metabolomic fingerprint spectrum using 1H-NMR method.

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancy. Here, we used 1H nuclear magnetic resonance spectroscopy (1H-NMR) to identify potential pre- and post-operative serum biomarkers in patients with early stage ESCC using metabolomic fingerprint spectrum. Serum samples from preoperative patients with ESCC (ESCC, n = 25), postoperative patients with ESCC (PO, n = 24), and controls (n = 40) were analysed using 1H-NMR spectroscopy. Using orthogonal partial least squares-discriminant analysis, 31 altered serum metabolites were successfully identified among the three groups. These metabolites are indicative of the changes that occur with glycometabolism, the metabolism of fatty acids, amino acids, choline, ketone bodies, nucleotides, and lipids. Based on receiver operating characteristic (ROC) curve analysis and a biomarker panel with an area under the curve (AUC) of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential diagnostic biomarkers for early stage ESCC. Additionally, four potential PO biomarkers (α-glucose, pyruvate, glutamate, and valine) with an AUC of 0.985 were selected to distinguish ESCC and PO. Many metabolites trended towards normalisation in PO patients, with only choline remaining high with an AUC of 0.858, suggesting that it may be a valuable potential biomarker for neoplasm progression, recurrence, chemoradiotherapy, and prognosis. 1H-NMR spectroscopy may be a useful tumour detection approach in the early diagnosis of ESCC. These results also indicate that it is useful to differentiate pre- and post-operative ESCC, evaluate surgery therapeutic responses, and monitor postoperative chemoradiotherapy.

1H-NMR spectroscopy identifies potential biomarkers in serum metabolomic signatures for early stage esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancies. Here, we used 1H nuclear magnetic resonance spectroscopy (1H-NMR) to identify potential serum biomarkers in patients with early stage ESCC. METHODS: Sixty-five serum samples from early stage ESCC patients (n = 25) and healthy controls (n = 40) were analysed using 1H-NMR spectroscopy. We distinguished between different metabolites through principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P+ version 14.0 software. Receiver operating characteristic (ROC) analysis was conducted to verify potential biomarkers. RESULTS: Using OPLS-DA, 31 altered serum metabolites were successfully identified between the groups. Based on the area under the ROC curve (AUROC), and the biomarker panel with AUROC of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential biomarkers for early stage ESCC. Dihydrothymine particularly was selected as a new feasible biomarker associated with tumor occurrence. CONCLUSIONS: 1H-NMR spectroscopy may be a useful tumour detection approach in identifying useful metabolic ESCC biomarkers for early diagnosis and in the exploration of the molecular pathogenesis of ESCC.

The Neurochemical and Microstructural Changes in the Brain of Systemic Lupus Erythematosus Patients: A Multimodal MRI Study.

The diagnosis and pathology of neuropsychiatric systemic lupus erythematosus (NPSLE) remains challenging. Herein, we used multimodal imaging to assess anatomical and functional changes in brains of SLE patients instead of a single MRI approach generally used in previous studies. Twenty-two NPSLE patients, 21 non-NPSLE patients and 20 healthy controls (HCs) underwent 3.0 T MRI with multivoxel magnetic resonance spectroscopy, T1-weighted volumetric images for voxel based morphometry (VBM) and diffusional kurtosis imaging (DKI) scans. While there were findings in other basal ganglia regions, the most consistent findings were observed in the posterior cingulate gyrus (PCG). The reduction of multiple metabolite concentration was observed in the PCG in the two patient groups, and the NPSLE patients were more prominent. The two patient groups displayed lower diffusional kurtosis (MK) values in the bilateral PCG compared with HCs (p < 0.01) as assessed by DKI. Grey matter reduction in the PCG was observed in the NPSLE group using VBM. Positive correlations among cognitive function scores and imaging metrics in bilateral PCG were detected. Multimodal imaging is useful for evaluating SLE subjects and potentially determining disease pathology. Impairments of cognitive function in SLE patients may be interpreted by metabolic and microstructural changes in the PCG.

2D-1H proton magnetic resonance spectroscopic imaging study on brain metabolite alterations in patients with diabetic hypertension.

The aim of the present study was to investigate the possible metabolic alterations in the frontal cortex and parietal white matter in patients with diabetic hypertension (DHT) using proton magnetic resonance (MR) spectroscopic imaging. A total of 33 DHT patients and 30 healthy control subjects aged between 45 and 75 were included in the present study. All subjects were right­handed. The spectroscopy data were collected using a GE Healthcare 1.5T MR scanner. The multi­voxels were located in the semioval center (repetition time/echo time=1,500 ms/35 ms). The area of interest was 8x10x2 cm in volume and contained the two sides of the frontal cortex and the parietal white matter. The spectra data were processed using SAGE software. The ratios of brain metabolite concentrations, particularly for N­acetylaspartate (NAA)/creatine (Cr) and Choline (Cho)/Cr were calculated and analyzed. Statistical analyses were performed using SPSS 17.0. The NAA/Cr ratio of the bilateral prefrontal cortex of the DHT group was significantly lower than that of the control group (left t=­7.854, P=0.000 and right t=­5.787, P=0.000), The Cho/Cr ratio was also much lower than the control group (left t=2.422, P=0.024 and right t=2.920, P=0.007). NAA/Cr ratio of the left parietal white matter of the DHT group was extremely lower than that of the control group (t=­4.199, P=0.000). Therefore, DHT may result in metabolic disorders in the frontal cortex and parietal white matter but the metabolic alterations are different in various regions of the brain. The alteration in cerebral metabolism is associated with diabetes and hypertension. The ratios of NAA/Cr and Cho/Cr are potential metabolic markers for the brain damage induced by DHT.

Magnetic Resonance Spectroscopy Study of Amnestic Mild Cognitive Impairment and Vascular Cognitive Impairment With No Dementia.

Amnestic mild cognitive impairment (aMCI) and vascular cognitive impairment with no dementia (VCIND) are highly predictive of Alzheimer's disease and vascular dementia. In this study, a 2-dimensional magnetic resonance spectroscopy was performed in 25 patients with aMCI, 28 patients with VCIND, and 32 normal controls (NCs). The concentrations of N-acetyl aspartate (NAA), choline (Cho), myoinositol (MI), and creatine (Cr) were measured, and their ratios were calculated. The patients with aMCI displayed significantly lower NAA/MI bilaterally in the posterior cingulate gyrus (PCG) and white matter of occipital lobe (OLWM) than NC participants or patients with VCIND , whereas patients with VCIND displayed markedly lower NAA/Cho bilaterally in the white matter of frontal lobe (FLWM) and left OLWM, and right dorsal thalamus (DT) than patients with NC or aMCI. Compared with the controls, patients with aMCI displayed lower NAA and NAA/Cr in bilateral PCG, left precuneus, and DT, whereas patients with VCIND displayed lower NAA/Cr in bilateral DT and FLWM. In addition, increased MI in right PCG of patients with aMCI and increased Cho in left FLWM of patients with VCIND were also observed. The results might help guide a clinical differentiation between the 2 disorders.