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 ). The primary end point was a decrease in hepatic triglycerides by magnetic resonance spectroscopy at 52 weeks with a dose of 600 mg of Aramchol. Key secondary end points included liver histology and alanine aminotransferase (ALT). Aramchol 600 mg produced a placebo-corrected decrease in liver triglycerides without meeting the prespecified significance (-3.1, 95% confidence interval (CI) -6.4 to 0.2, P = 0.066), precluding further formal statistical analysis. NASH resolution without worsening fibrosis was achieved in 16.7% (13 out of 78) of Aramchol 600 mg versus 5% (2 out of 40) of the placebo arm (odds ratio (OR) = 4.74, 95% CI = 0.99 to 22.7) and fibrosis improvement by ≥1 stage without worsening NASH in 29.5% versus 17.5% (OR = 1.88, 95% CI = 0.7 to 5.0), respectively. The placebo-corrected decrease in ALT for 600 mg was -29.1 IU l^-1 (95% CI = -41.6 to -16.5). Early termination due to adverse events (AEs) was <5%, and Aramchol 600 and 400 mg were safe, well tolerated and without imbalance in serious or severe AEs between arms. Although the primary end point of a reduction in liver fat did not meet the prespecified significance level with Aramchol 600 mg, the observed safety and changes in liver histology and enzymes provide a rationale for SCD1 modulation as a promising therapy for NASH and fibrosis and are being evaluated in an ongoing phase 3 program.

Classification of High-Grade Glioma into Tumor and Nontumor Components Using Support Vector Machine

BACKGROUND AND PURPOSE

Current imaging assessment of high-grade brain tumors relies on the Response Assessment in Neuro-Oncology criteria, which measure gross volume of enhancing and nonenhancing lesions from conventional MRI sequences. These assessments may fail to reliably distinguish tumor and nontumor. This study aimed to classify enhancing and nonenhancing lesion areas into tumor-versus-nontumor components.

MATERIALS AND METHODS

A total of 140 MRI scans obtained from 32 patients with high-grade gliomas and 6 patients with brain metastases were included. Classification of lesion areas was performed using a support vector machine classifier trained on 4 components: enhancing and nonenhancing, tumor and nontumor, based on T1-weighted, FLAIR, and dynamic-contrast-enhancing MRI parameters. Classification results were evaluated by 2-fold cross-validation analysis of the training set and MR spectroscopy. Longitudinal changes of the component volumes were compared with Response Assessment in Neuro-Oncology criteria.

RESULTS

Normalized T1-weighted values, FLAIR, plasma volume, volume transfer constant, and bolus-arrival-time parameters differentiated components. High sensitivity and specificity (100%) were obtained within the enhancing and nonenhancing areas. Longitudinal changes in component volumes correlated with the Response Assessment in Neuro-Oncology criteria in 27 patients; 5 patients (16%) demonstrated an increase in tumor component volumes indicating tumor progression. These changes preceded Response Assessment in Neuro-Oncology assessments by several months. Seven patients treated with bevacizumab showed a shift to an infiltrative pattern of progression.

CONCLUSIONS

This study proposes an automatic classification method: segmented Response Assessment in Neuro-Oncology criteria based on advanced imaging that reliably differentiates tumor and nontumor components in high-grade gliomas. The segmented Response Assessment in Neuro-Oncology criteria may improve therapy-response assessment and provide earlier indication of progression.

Fast reference based MRI

In many clinical MRI scenarios, existing imaging information can be used to significantly shorten acquisition time or improve Signal to Noise Ratio (SNR). In those cases, a previously acquired image can serve as a reference image, that may exhibit similarity in some sense to the image being acquired. Examples include similarity between adjacent slices in high resolution MRI, similarity between various contrasts in the same scans and similarity between different scans of the same patients. In this paper we present a general framework for utilizing reference images for fast MRI. We take into account that the reference image may exhibit low similarity with the acquired image and develop a hybrid adaptive-weighted approach for sampling and reconstruction. Experiments demonstrate the performance of the method in three different clinical MRI scenarios: SNR improvement in high resolution brain MRI, utilizing similarity between T2-weighted and fluid-attenuated inversion recovery (FLAIR) for fast FLAIR scanning and utilizing similarity between baseline and follow-up scans for fast follow-up scanning.

Tumor burden evaluation in NF1 patients with plexiform neurofibromas in daily clinical practice

BACKGROUND

Existing volumetric measurements of plexiform neurofibromas (PNs) are time consuming and error prone, as they require delineation of PN boundaries, a procedure that is not practical in the typical clinical setting. The aim of this study is to assess the Plexiform Neurofibroma Instant Segmentation Tool (PNist), a novel semi-automated segmentation program that we developed for PN delineation in a clinical context. PNist was designed to greatly simplify volumetric assessment of PNs through use of an intuitive user interface while providing objectively consistent results with minimal interobserver and intraobserver variabilities in reasonable time.

MATERIALS AND METHODS

PNs were measured in 30 magnetic resonance imaging (MRI) scans from 12 patients with neurofibromatosis 1. Volumetric measurements were performed using PNist and compared to a standard semi-automated volumetric method (Analyze 9.0).

RESULTS

High correlation was detected between PNist and the semi-automated method (R(2) = 0.996), with a mean volume overlap error of 9.54 % and low intraobserver and interobserver variabilities. The segmentation time required for PNist was 60 % of the time required for Analyze 9.0 (360 versus 900 s, respectively). PNist was also reliable when assessing changes in tumor size over time, compared to the existing commercial method.

CONCLUSIONS

Our study suggests that the new PNist method is accurate, intuitive, and less time consuming for PN segmentation compared to existing commercial volumetric methods. The workflow is simple and user-friendly, making it an important clinical tool to be used by radiologists, neurologists and neurosurgeons on a daily basis, helping them deal with the complex task of evaluating PN burden and progression.

MRI-based radiologic scoring system for extent of brain injury in children with hemiplegia

BACKGROUND AND PURPOSE

Brain MR imaging is recommended in children with cerebral palsy. Descriptions of MR imaging findings lack uniformity, due to the absence of a validated quantitative approach. We developed a quantitative scoring method for brain injury based on anatomic MR imaging and examined the reliability and validity in correlation to motor function in children with hemiplegia.

MATERIALS AND METHODS

Twenty-seven children with hemiplegia underwent MR imaging (T1, T2-weighted sequences, DTI) and motor assessment (Manual Ability Classification System, Gross Motor Functional Classification System, Assisting Hand Assessment, Jebsen Taylor Test of Hand Function, and Children's Hand Experience Questionnaire). A scoring system devised in our center was applied to all scans. Radiologic score covered 4 domains: number of affected lobes, volume and type of white matter injury, extent of gray matter damage, and major white matter tract injury. Inter- and intrarater reliability was evaluated and the relationship between radiologic score and motor assessments determined.

RESULTS

Mean total radiologic score was 11.3 ± 4.5 (range 4-18). Good inter- (ρ = 0.909, P < .001) and intrarater (ρ = 0.926, P = < .001) reliability was demonstrated. Radiologic score correlated significantly with manual ability classification systems (ρ = 0.708, P < .001), and with motor assessments (assisting hand assessment [ρ = -0.753, P < .001]; Jebsen Taylor test of hand function [ρ = 0. 766, P < .001]; children's hand experience questionnaire [ρ = -0. 716, P < .001]), as well as with DTI parameters.

CONCLUSIONS

We present a novel MR imaging-based scoring system that demonstrated high inter- and intrarater reliability and significant associations with manual ability classification systems and motor evaluations. This score provides a standardized radiologic assessment of brain injury extent in hemiplegic patients with predominantly unilateral injury, allowing comparison between groups, and providing an additional tool for counseling families.

Isolated mild white matter signal changes in preterm infants: a regional approach for comparison of cranial ultrasound and MRI findings

OBJECTIVE

To compare echogenicity detected using cranial ultrasound (cUS) and diffuse excessive high signal intensity (DEHSI) detected using magnetic resonance imaging (MRI) by identical region-based scoring criteria in preterm infants. To explore the association between these white matter (WM) signal changes with early neurobehavior.

STUDY DESIGN

Forty-nine pre-selected premature infants with only echogenicity on a first routine cUS1 underwent MRI and a repeated cUS2 at term equivalent age. Echogenicity and DEHSI were graded in various brain areas and diffusivity values were calculated. Neurobehavior was assessed using the Rapid Neonatal Neurobehavioral Assessment Procedure.

RESULT

WM signal changes were significantly higher on cUS1 than cUS2; and higher in MRI than cUS2 in posterior regions. Infants with DEHSI demonstrated reduced tissue integrity. Imaging findings were not correlated with early neurobehavior.

CONCLUSION

Echogenicity and DEHSI likely represent the same phenomenon. Reduction of over-interpretation of WM signal changes may help define criteria for the judicious use of imaging in routine follow-up of premature infants.

MRI multiparametric hemodynamic characterization of the normal brain

Characterization of the brain's vascular system is of major clinical importance in the assessment of patients with cerebrovascular disease. The aim of this study was to characterize brain hemodynamics using multiparametric methods and to obtain reference values from the healthy brain. A multimodal magnetic resonance imaging (MRI) study was performed in twenty healthy subjects, including dynamic susceptibility contrast imaging and blood oxygen level dependence (BOLD) during hypercapnia and carbogen challenges. Brain tissues were defined using unsupervised cluster analysis based on these three methods, and several hemodynamic parameters were calculated for gray matter (GM), white matter (WM), blood vessels and dura (BVD); the three main vascular territories within the GM; and arteries and veins defined within the BVD cluster. The carbogen challenge produced a BOLD signal twice as high as the hypercapnia challenge, in all brain tissues. The three brain tissues differed significantly from each other in their hemodynamic characteristics, supporting the graded vascularity of the tissues, with BVD>GM>WM. Within the GM cluster, a significant delay of ∼1.2 s of the bolus arrival time was detected within the posterior cerebral artery territory relative to the middle and anterior cerebral artery territories. No differences were detected between right and left middle cerebral artery territories for all hemodynamic parameters. Within the BVD cluster, a significant delay of ∼1.9 s of the bolus arrival time was detected within the veins relative to the arteries. This parameter enabled to differentiate between the various blood vessels, including arteries, veins and choroid plexus. This study provides reference values for several hemodynamic parameters, obtained from healthy brains, and may be clinically important in the assessment of patients with various vascular pathologies.

Automatic segmentation, internal classification, and follow-up of optic pathway gliomas in MRI

This paper presents an automatic method for the segmentation, internal classification and follow-up of optic pathway gliomas (OPGs) from multi-sequence MRI datasets. Our method starts with the automatic localization of the OPG and its core with an anatomical atlas followed by a binary voxel classification with a probabilistic tissue model whose parameters are estimated from the MR images. The method effectively incorporates prior location, tissue characteristics, and intensity information for the delineation of the OPG boundaries in a consistent and repeatable manner. Internal classification of the segmented OPG volume is then obtained with a robust method that overcomes grey-level differences between learning and testing datasets. Experimental results on 25 datasets yield a mean surface distance error of 0.73 mm as compared to manual segmentation by experienced radiologists. Our method exhibits reliable performance in OPG growth follow-up MR studies, which are crucial for monitoring disease progression. To the best of our knowledge, this is the first method that addresses automatic segmentation, internal classification, and follow-up of OPG.

Vase or face? A neural correlate of shape-selective grouping processes in the human brain

Recent neuroimaging studies have described a differential activation pattern associated with specific object images (e.g., face-related and building-related activation) in human occipito-temporal cortex. However, it is as yet unclear to what extent this selectivity is due to differences in the statistics of local object features present in the different object categories, and to what extent it reflects holistic grouping processes operating across the entire object image. To resolve this question it is essential to use images in which identical sets of local features elicit the perception of different object categories. The classic Rubin vase-face illusion provides an excellent experimental set to test this question. In the illusion, the same local contours lead to the perception of different objects (vase or face). Here we employed a modified Rubin vase-face illusion to explore to what extent the activation in face-related regions is attributable to the presence of local face features, or is due to a more holistic grouping process that involves the entire face figure. Biasing cues (gratings and color) were used to control the perceptual state of the observer. We found enhanced activation in face-related regions during the "face profile" perceptual state compared to the "vase" perceptual state. Control images ruled out the involvement of the biasing cues in the effect. Thus, object-selective activation in human face-related regions entails global grouping processes that go beyond the local processing of stimulus features.