Assessment of hypoxia and its dynamic evolution in glioblastoma via qBOLD MRI: a comparative study with metformin treatment.

Background: To investigate the accuracy of quantitative blood oxygen level-dependent (qBOLD) magnetic resonance imaging (MRI) in identifying hypoxia within glioblastoma and explore dynamic changes in oxygenation status of glioblastoma with and without metformin administration.

Methods: Three healthy and seven C6-bearing rats underwent 7-T qBOLD MRI. Oxygen extraction fraction (OEF) and cerebral metabolism rate of O (CMRO) were calculated from qBOLD data.

Changes in the relaxivity of water-organic solvent miscible systems: Hidden forces beyond metal ions.

Background: The relaxivity of magnetic resonance imaging (MRI) contrast agents is primarily attributed to metal ions such as gadolinium (Gd) and iron. However, the impact of organic solutes on relaxivity, particularly through alterations in water molecule dynamics, has not been thoroughly investigated. This research was aimed to explore how organic solutes affect the relaxivities of water and Gd-based contrast agents (GBCAs), potentially revealing new aspects for the development of contrast agents.

Modulation of Neurotransmission by Acid-Sensing Ion Channels.

Interstitial pH fluctuations occur normally in the brain and significantly modulate neuronal functions. Acid-sensing ion channels (ASICs), which serve as neuronal acid chemosensors, play important roles in synaptic plasticity, learning, and memory. However, the specific mechanisms by which ASICs influence neurotransmission remain elusive.

Non-invasive diagnosis of liver fibrosis via MRI using targeted gadolinium-based nanoparticles.

Introduction: Accurate diagnosis of liver fibrosis is crucial for preventing cirrhosis and liver tumors. Liver fibrosis is driven by activated hepatic stellate cells (HSCs) with elevated CD44 expression. We developed hyaluronic acid (HA)-coated gadolinium-based nanoprobes to specifically target CD44 for diagnosing liver fibrosis using T1-weighted magnetic resonance imaging (MRI).

Thyroid imaging reporting and data system with MRI morphological features for thyroid nodules: diagnostic performance and unnecessary biopsy rate.

Background: To assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules.

Methods: A retrospective analysis was performed on 728 thyroid nodules (453 benign and 275 malignant) that postoperative pathology confirmed. Univariate and multivariate logistic regression analyses were used to find independent predictors of MRI morphological features in benign and malignant thyroid nodules.

Prediction of Follicular Thyroid Neoplasm and Malignancy of Follicular Thyroid Neoplasm Using Multiparametric MRI.

The study aims to evaluate multiparametric magnetic resonance imaging (MRI) for differentiating Follicular thyroid neoplasm (FTN) from non-FTN and malignant FTN (MFTN) from benign FTN (BFTN). We retrospectively analyzed 702 postoperatively confirmed thyroid nodules, and divided them into training (n = 482) and validation (n = 220) cohorts. The 133 FTNs were further split into BFTN (n = 116) and MFTN (n = 17) groups.

MRI Manifestations of Breast Cancer Stroma and their Role in Predicting Molecular Subtype: A Case-control Study.

Objective: This study explored whether breast MRI manifestations could be used to predict the stroma distribution of breast cancer (BC) and the role of tumor stroma-based MRI manifestations in molecular subtype prediction.

Methods: 57 patients with pathologically confirmed invasive BC (non-special type) who had lumpy BC on MRI within one week before surgery were retrospectively collected in the study. Stroma distributions were classified according to their characteristics in the pathological sections.

Prediction model based on MRI morphological features for distinguishing benign and malignant thyroid nodules.

Background: The low specificity of Thyroid Imaging Reporting and Data System (TI-RADS) for preoperative benign-malignant diagnosis leads to a large number of unnecessary biopsies. This study developed and validated a predictive model based on MRI morphological features to improve the specificity.

Methods: A retrospective analysis was conducted on 825 thyroid nodules pathologically confirmed postoperatively.

Quantitative evaluation of diffusion-weighted MRI for differentiating benign and malignant thyroid nodules larger than 4 cm.

Purpose: Our study aimed to diagnose benign or malignant thyroid nodules larger than 4 cm using quantitative diffusion-weighted imaging (DWI) analysis.

Methods: Eighty-two thyroid nodules were investigated retrospectively and divided them into benign (n = 62) and malignant groups (n = 20). We calculated quantitative features DWI and apparent diffusion coefficient (ADC) signal intensity standard deviation (DWI and ADC), DWI and ADC signal intensity ratio (DWI and ADC), mean ADC and minimum ADC value (ADC and ADC) and ADC value standard deviation (ADC).

Neuromelanin-sensitive MRI of the substantia nigra distinguishes bipolar from unipolar depression.

Depression in bipolar disorder (BD-II) is frequently misdiagnosed as unipolar depression (UD) leading to inappropriate treatment and downstream complications for many bipolar sufferers. In this study, we evaluated whether neuromelanin-MR signal and volume changes in the substantia nigra (SN) can be used as potential biomarkers to differentiate BD-II from UD. The signal intensities and volumes of the SN regions were measured, and contrast-to-noise ratio (CNR) to the decussation of the superior cerebellar peduncles were calculated and compared between healthy controls (HC), BD-II and UD subjects.

Predicting peritumoral edema development after gamma knife radiosurgery of meningiomas using machine learning methods: a multicenter study.

Objectives: Edema is a complication of gamma knife radiosurgery (GKS) in meningioma patients that leads to a variety of consequences. The aim of this study is to construct radiomics-based machine learning models to predict post-GKS edema development.

Methods: In total, 445 meningioma patients who underwent GKS in our institution were enrolled and partitioned into training and internal validation datasets (8:2).

Diffusion-weighted, intravoxel incoherent motion, and diffusion kurtosis tensor MR imaging in chronic kidney diseases: Correlations with histology.

Objectives: To probe the correlations of parameters derived from standard DWI and its extending models including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) with the pathological and functional alterations in CKD.

Material And Methods: Seventy-nine CKD patients with renal biopsy and 10 volunteers were performed with DWI, IVIM, diffusion kurtosis tensor imaging (DKTI) scanning. Correlations between imaging results and the pathological damage [glomerulosclerosis index (GSI) and tubulointerstitial fibrosis index (TBI)], as well as eGFR, 24 h urinary protein and Scr) were evaluated.

Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging.

Background: The aim of this study was to investigate the value of unenhanced magnetic resonance imaging (MRI) with diffusion kurtosis imaging (DKI) in diagnosing papillary thyroid carcinoma (PTC).

Methods: In all, 77 consecutive patients comprising a total of 77 thyroid nodules were enrolled in this study. Of these nodules, 41 were histopathologically confirmed PTCs and 36 were benign nodules.

Preoperative Cervical Lymph Node Metastasis Prediction in Papillary Thyroid Carcinoma: A Noninvasive Clinical Multimodal Radiomics (CMR) Nomogram Analysis.

This study aimed to evaluate the feasibility of applying a clinical multimodal radiomics nomogram based on ultrasonography (US) and multiparametric magnetic resonance imaging (MRI) for the prediction of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) preoperatively. We performed retrospective evaluations of 133 patients with pathologically confirmed PTC, who were assigned to the training cohort and validation cohort (7 : 3), and extracted radiomics features from the preoperative US, T2-weighted (T2WI),diffusion-weighted (DWI), and contrast-enhanced T1-weighted (CE-T1WI) images. Optimal subsets were selected using minimum redundancy, maximum relevance, and recursive feature elimination in the support vector machine (SVM).

MRI-Based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid Carcinoma.

Purpose: BRAF V600E mutation can compensate for the low detection rate by fine-needle aspiration (FNA) and is related to aggressiveness and lymph node metastasis. This study aimed to investigate the relationship between texture analysis features based on magnetic resonance imaging (MRI) and mutations.

Methods: Retrospective analysis was performed on patients with postoperative pathology confirmed papillary thyroid carcinoma (PTC) from 2017 to 2021.

Development of a prediction model for gross residual in high-grade serous ovarian cancer by combining preoperative assessments of abdominal and pelvic metastases and multiparametric MRI.

Rationale And Objectives: To preoperatively predict residual tumor (RT) in patients with high-grade serous ovarian carcinoma (HGSOC) via a radiomic-clinical nomogram.

Methods: A total of 128 patients with advanced HGSOC were enrolled (training cohort: n=106; validation cohort: n=22). Serum cancer antigen-125 (CA125), serum human epididymis protein 4 (HE-4) level, and neutrophil-to-lymphocyte ratio (NLR) were obtained from the medical records.

T1 and ADC histogram parameters may be an in vivo biomarker for predicting the grade, subtype, and proliferative activity of meningioma.

Objective: To investigate the value of histogram analysis of T1 mapping and diffusion-weighted imaging (DWI) in predicting the grade, subtype, and proliferative activity of meningioma.

Methods: This prospective study comprised 69 meningioma patients who underwent preoperative MRI including T1 mapping and DWI. The histogram metrics, including mean, median, maximum, minimum, 10th percentiles (C10), 90th percentiles (C90), kurtosis, skewness, and variance, of T1 and apparent diffusion coefficient (ADC) values were extracted from the whole tumour and peritumoural oedema using FeAture Explorer.

Evaluation of HIF-1α Expression in a Rat Glioma Model Using Intravoxel Incoherent Motion and R2* Mapping.

Accurate evaluation of HIF-1α levels can facilitate the detection of hypoxia niches in glioma and treatment decisions. To investigate the feasibility of intravoxel incoherent motion (IVIM) and R2* Mapping for detecting HIF-1α expression levels, sixteen rats with intracranial C6 gliomas were subjected to IVIM and R2* Mapping using a 7 Tesla MRI scanner. For each model, the brain tissue on the HIF-1α-stained slices was subdivided into multiple square regions of interest (ROIs) with areas of 1 mm, for which HIF-1α expression was assessed by HALO software to form a maps of HIF scores with a 0-300 range.

Assessment of Fasudil on Contrast-Associated Acute Kidney Injury Using Multiparametric Renal MRI.

To evaluate the utility of fasudil in a rat model of contrast-associated acute kidney injury (CA-AKI) and explore its underlying mechanism through multiparametric renal magnetic resonance imaging (mpMRI). Experimental rats ( = 72) were grouped as follows: controls ( = 24), CA-AKI ( = 24), or CA-AKI + Fasudil ( = 24). All animals underwent two mpMRI studies (arterial spin labeling, T1 and T2 mapping) at baseline and post iopromide/fasudil injection (Days 1, 3, 7, and 13 respectively).

MRI whole-lesion texture analysis on ADC maps for the prognostic assessment of ischemic stroke.

Background: This study aims is to explore whether it is feasible to use magnetic resonance texture analysis (MRTA) in order to distinguish favorable from unfavorable function outcomes and determine the prognostic factors associated with favorable outcomes of stroke.

Methods: The retrospective study included 103 consecutive patients who confirmed unilateral anterior circulation subacute ischemic stroke by computed tomography angiography between January 2018 and September 2019. Patients were divided into favorable outcome (modified Rankin scale, mRS ≤ 2) and unfavorable outcome (mRS > 2) groups according to mRS scores at day 90.

Aberrant Spontaneous Brain Activity in Coronary Heart Disease Using Fractional Amplitude of Low-Frequency Fluctuations: A Preliminary Resting-State Functional MRI Study.

Objective: This study is aimed at exploring the spontaneous brain activity changes by measuring the fractional amplitude of low-frequency fluctuations (fALFF) and their relationship with clinical characteristics in patients with coronary heart disease (CHD).

Methods: Coronary heart disease patients ( = 25) and age, gender, and education level-matched control subjects (controls, = 35) were included. The grey matter volume (GMV) and fALFF values were calculated to assess the difference in brain structure and function between the two groups, respectively.