Radiological markers of CSF α-synuclein aggregation in Parkinson's disease patients.

Alpha-synuclein (αS) aggregation is a widely regarded hallmark of Parkinson's disease (PD) and can be detected through synuclein amplification assays (SAA). This study investigated the association between cerebrospinal fluid (CSF) radiological measures in 41 PD patients (14 iPD, 14 GBA1-PD, 13 LRRK2-PD) and 14 age-and-sex-matched healthy controls. Quantitative measures including striatal binding ratios (SBR), whole-brain and deep gray matter volumes, neuromelanin-MRI (NM-MRI), functional connectivity (FC), and white matter (WM) diffusion-tensor imaging (DTI) were calculated.

Fetal body composition reference charts and sexual dimorphism using magnetic resonance imaging.

Background: The American Academy of Pediatrics advises that the nutrition of preterm infants should target a body composition similar to that of a fetus in utero. Still, reference charts for intrauterine body composition are missing. Moreover, data on sexual differences in intrauterine body composition during pregnancy are limited.

Brain Metabolite Differences in Fetuses With Cytomegalovirus Infection: A Magnetic Resonance Spectroscopy Study.

Background: Cytomegalovirus (CMV) is the most common intrauterine infection and may be associated with unfavorable outcomes. While some CMV-infected fetuses may show gross or subtle brain abnormalities on MRI, their clinical significance may be unclear. Conversely, normal development cannot be guaranteed in CMV-infected fetuses with normal MRI.

Fetal MRI-Based Body and Adiposity Quantification for Small for Gestational Age Perinatal Risk Stratification.

Background: Small for gestational age (SGA) fetuses are at risk for perinatal adverse outcomes. Fetal body composition reflects the fetal nutrition status and hold promise as potential prognostic indicator. MRI quantification of fetal anthropometrics may enhance SGA risk stratification.

Deep learning-based segmentation of whole-body fetal MRI and fetal weight estimation: assessing performance, repeatability, and reproducibility.

Objectives: To develop a deep-learning method for whole-body fetal segmentation based on MRI; to assess the method's repeatability, reproducibility, and accuracy; to create an MRI-based normal fetal weight growth chart; and to assess the sensitivity to detect fetuses with growth restriction (FGR).

Methods: Retrospective data of 348 fetuses with gestational age (GA) of 19-39 weeks were included: 249 normal appropriate for GA (AGA), 19 FGR, and 80 Other (having various imaging abnormalities). A fetal whole-body segmentation model with a quality estimation module was developed and evaluated in 169 cases.

Reduced adipose tissue in growth-restricted fetuses using quantitative analysis of magnetic resonance images.

Objectives: Fat-water MRI can be used to quantify tissues' lipid content. We aimed to quantify fetal third trimester normal whole-body subcutaneous lipid deposition and explore differences between appropriate for gestational age (AGA), fetal growth restriction (FGR), and small for gestational age fetuses (SGAs).

Methods: We prospectively recruited women with FGR and SGA-complicated pregnancies and retrospectively recruited the AGA cohort (sonographic estimated fetal weight [EFW] ≥ 10th centile).

Utilizing the TractSeg Tool for Automatic Corticospinal Tract Segmentation in Patients With Brain Pathology.

White-matter tract segmentation in patients with brain pathology can guide surgical planning and can be used for tissue integrity assessment. Recently, TractSeg was proposed for automatic tract segmentation in healthy subjects. The aim of this study was to assess the use of TractSeg for corticospinal-tract (CST) segmentation in a large cohort of patients with brain pathology and to evaluate its consistency in repeated measurements.

Model-free dynamic contrast-enhanced MRI analysis: differentiation between active tumor and necrotic tissue in patients with glioblastoma.

Objective: Treatment response assessment in patients with high-grade gliomas (HGG) is heavily dependent on changes in lesion size on MRI. However, in conventional MRI, treatment-related changes can appear as enhancing tissue, with similar presentation to that of active tumor tissue. We propose a model-free data-driven method for differentiation between these tissues, based on dynamic contrast-enhanced (DCE) MRI.

Neuromelanin and T*-MRI for the assessment of genetically at-risk, prodromal, and symptomatic Parkinson's disease.

MRI was suggested as a promising method for the diagnosis and assessment of Parkinson's Disease (PD). We aimed to assess the sensitivity of neuromelanin-MRI and T* with radiomics analysis for detecting PD, identifying individuals at risk, and evaluating genotype-related differences. Patients with PD and non-manifesting (NM) participants [NM-carriers (NMC) and NM-non-carriers (NMNC)], underwent MRI and DAT-SPECT.

BV-GAN: 3D time-of-flight magnetic resonance angiography cerebrovascular vessel segmentation using adversarial CNNs.

Cerebrovascular vessel segmentation is a key step in the detection of vessel pathology. Brain time-of-flight magnetic resonance angiography (TOF-MRA) is a main method used clinically for imaging of blood vessels using magnetic resonance imaging. This method is primarily used to detect narrowing, blockage of the arteries, and aneurysms.

Improved differentiation between hypo/hypertelorism and normal fetuses based on MRI using automatic ocular biometric measurements, ocular ratios, and machine learning multi-parametric classification.

Objectives: To differentiate hypo-/hypertelorism (abnormal) from normal fetuses using automatic biometric measurements and machine learning (ML) classification based on MRI.

Methods: MRI data of normal (n = 244) and abnormal (n = 52) fetuses of 22-40 weeks' gestational age (GA), scanned between March 2008 and June 2020 on 1.5/3T systems with various T-weighted sequences and image resolutions, were included.

Ex-Vivo MRI of the Normal Human Placenta: Structural-Functional Interplay and the Association With Birth Weight.

Background: Advanced magnetic resonance imaging (MRI) methods are increasingly being used to assess the human placenta. Yet, the structure-function interplay in normal placentas and their associations with pregnancy risks are not fully understood.

Purpose: To characterize the normal human placental structure (volume and umbilical cord centricity index (CI)) and function (perfusion) ex-vivo using MRI, to assess their association with birth weight (BW), and identify imaging-markers for placentas at risk for dysfunction.

Aramchol in patients with nonalcoholic steatohepatitis: a randomized, double-blind, placebo-controlled phase 2b trial.

Nonalcoholic steatohepatitis (NASH), a chronic liver disease without an approved therapy, is associated with lipotoxicity and insulin resistance and is a major cause of cirrhosis and hepatocellular carcinoma. Aramchol, a partial inhibitor of hepatic stearoyl-CoA desaturase (SCD1) improved steatohepatitis and fibrosis in rodents and reduced steatosis in an early clinical trial. ARREST, a 52-week, double-blind, placebo-controlled, phase 2b trial randomized 247 patients with NASH (n = 101, n = 98 and n = 48 in the Aramchol 400 mg, 600 mg and placebo arms, respectively; NCT02279524 ).

Whole brain and deep gray matter structure segmentation: Quantitative comparison between MPRAGE and MP2RAGE sequences.

Objective: T1-weighted MRI images are commonly used for volumetric assessment of brain structures. Magnetization prepared 2 rapid gradient echo (MP2RAGE) sequence offers superior gray (GM) and white matter (WM) contrast. This study aimed to quantitatively assess the agreement of whole brain tissue and deep GM (DGM) volumes obtained from MP2RAGE compared to the widely used MP-RAGE sequence.

Automatic linear measurements of the fetal brain on MRI with deep neural networks.

Purpose: Timely, accurate and reliable assessment of fetal brain development is essential to reduce short and long-term risks to fetus and mother. Fetal MRI is increasingly used for fetal brain assessment. Three key biometric linear measurements important for fetal brain evaluation are cerebral biparietal diameter (CBD), bone biparietal diameter (BBD), and trans-cerebellum diameter (TCD), obtained manually by expert radiologists on reference slices, which is time consuming and prone to human error.

Fetal and Perinatal Outcome Following First and Second Trimester COVID-19 Infection: Evidence from a Prospective Cohort Study.

A novel coronavirus termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new strain of coronavirus causing coronavirus disease 2019 (COVID-19) disease, which emerged as a global pandemic. Data regarding the implications of COVID-19 disease at early gestation on fetal and obstetric outcomes is scarce. Thus, our aim was to investigate the effect of first and second trimester maternal COVID-19 disease on fetal and perinatal outcomes.

Cervical Cordotomy for Intractable Pain: Do Postoperative Imaging Features Correlate with Pain Outcomes and Mirror Pain?

Background And Purpose: Percutaneous cervical cordotomy offers relief of unilateral intractable oncologic pain. We aimed to find anatomic and postoperative imaging features that may correlate with clinical outcomes, including pain relief and postoperative contralateral pain.

Materials And Methods: We prospectively followed 15 patients with cancer who underwent cervical cordotomy for intractable pain during 2018 and 2019 and underwent preoperative and up to 1-month postoperative cervical MR imaging.

Semiautomatic cerebrovascular territory mapping based on dynamic ASL MR angiography without vessel-encoded labeling.

Purpose: Characterizing vessel territories can provide crucial information for evaluation of cerebrovascular disorders. In this study, we present a novel postprocessing pipeline for vascular territorial imaging of cerebral arteries based on a noncontrast enhanced time-resolved 4D magnetic resonance angiography (MRA).

Methods: Eight healthy participants, 1 Moyamoya patient, and 1 arteriovenous malformations patient were recruited.

Automatic segmentation, classification, and follow-up of optic pathway gliomas using deep learning and fuzzy c-means clustering based on MRI.

Purpose: Optic pathway gliomas (OPG) are low-grade pilocytic astrocytomas accounting for 3-5% of pediatric intracranial tumors. Accurate and quantitative follow-up of OPG using magnetic resonance imaging (MRI) is crucial for therapeutic decision making, yet is challenging due to the complex shape and heterogeneous tissue pattern which characterizes these tumors. The aim of this study was to implement automatic methods for segmentation and classification of OPG and its components, based on MRI.

Placental vascular tree characterization based on ex-vivo MRI with a potential application for placental insufficiency assessment.

Introduction: Understanding regarding the whole placental vascular network structure is limited. Our aim was to quantitatively characterize the human placental vascular tree ex-vivo using high-resolution MRI.

Methods: 34 normal placentas were rinsed and injected with a solution of gelatin and contrast agent through the umbilical vessels.

Placental vascular tree characterization based on ex-vivo MRI with a potential application for placental insufficiency assessment.

Introduction: Understanding regarding the whole placental vascular network structure is limited. Our aim was to quantitatively characterize the human placental vascular tree ex-vivo using high-resolution MRI.

Methods: 34 normal placentas were rinsed and injected with a solution of gelatin and contrast agent through the umbilical vessels.

Differentiation between glioblastoma, brain metastasis and subtypes using radiomics analysis.

Background: Differentiation between glioblastoma and brain metastasis is highly important due to differing medical treatment strategies. While MRI is the modality of choice for the assessment of patients with brain tumors, differentiation between glioblastoma and solitary brain metastasis may be challenging due to their similar appearance on MRI.

Purpose: To differentiate between glioblastoma and brain metastasis subtypes using radiomics analysis based on conventional post-contrast T -weighted (T W) MRI.

Repeatability of dynamic contrast enhanced v parameter in healthy subjects and patients with brain tumors.

Purpose: To study the repeatability of plasma volume (v) extracted from dynamic-contrast-enhanced (DCE) MRI in order to define threshold values for significant longitudinal changes, and to assess changes in patients with high-grade-glioma (HGG).

Methods: Twenty eight healthy subjects, of which eleven scanned twice, were used to assess the repeatability of v within the normal-appearing brain tissue and to define threshold values for significant changes based on least-detected-differences (LDD) of mean v values and histogram comparisons using earth-mover's-distance (EMD). Sixteen patients with HGG were scanned longitudinally with eight patients scanned before and following bevacizumab therapy.