Neuromelanin-sensitive MRI (NM-MRI) provides a noninvasive measure of the content of neuromelanin (NM), a product of dopamine metabolism that accumulates with age in dopamine neurons of the ...substantia nigra (SN). NM-MRI has been validated as a measure of both dopamine neuron loss, with applications in neurodegenerative disease, and dopamine function, with applications in psychiatric disease. Furthermore, a voxelwise-analysis approach has been validated to resolve substructures, such as the ventral tegmental area (VTA), within midbrain dopaminergic nuclei thought to have distinct anatomical targets and functional roles. NM-MRI is thus a promising tool that could have diverse research and clinical applications to noninvasively interrogate in vivo the dopamine system in neuropsychiatric illness. Although a test-retest reliability study by Langley et al. using the standard NM-MRI protocol recently reported high reliability, a systematic and comprehensive investigation of the performance of the method for various acquisition parameters and preprocessing methods has not been conducted. In particular, most previous studies used relatively thick MRI slices (~3 mm), compared to the typical in-plane resolution (~0.5 mm) and to the height of the SN (~15 mm), to overcome technical limitations such as specific absorption rate and signal-to-noise ratio, at the cost of partial-volume effects. Here, we evaluated the effect of various acquisition and preprocessing parameters on the strength and test-retest reliability of the NM-MRI signal to determine optimized protocols for both region-of-interest (including whole SN-VTA complex and atlas-defined dopaminergic nuclei) and voxelwise measures. Namely, we determined a combination of parameters that optimizes the strength and reliability of the NM-MRI signal, including acquisition time, slice-thickness, spatial-normalization software, and degree of spatial smoothing. Using a newly developed, detailed acquisition protocol, across two scans separated by 13 days on average, we obtained intra-class correlation values indicating excellent reliability and high contrast, which could be achieved with a different set of parameters depending on the measures of interest and experimental constraints such as acquisition time. Based on this, we provide detailed guidelines covering acquisition through analysis and recommendations for performing NM-MRI experiments with high quality and reproducibility. This work provides a foundation for the optimization and standardization of NM-MRI, a promising MRI approach with growing applications throughout clinical and basic neuroscience.
•A detailed NM-MRI volume placement protocol is described.•Guidelines covering acquisition through analysis for NM-MRI are given.•A test-retest study in 10 healthy subjects shows high reproducibility for region-of-interest (ROI) and voxelwise analyses.•~3 minutes of NM-MRI data is needed for high-quality ROI analysis.•~6 minutes of NM-MRI data is needed for high-quality voxelwise analysis.
Hierarchical perceptual-inference models of psychosis may provide a holistic framework for understanding psychosis in schizophrenia including heterogeneity in clinical presentations. Particularly, ...hypothesized alterations at distinct levels of the perceptual-inference hierarchy may explain why hallucinations and delusions tend to cluster together yet sometimes manifest in isolation. To test this, we used a recently developed resting-state fMRI measure of intrinsic neural timescale (INT), which reflects the time window of neural integration and captures hierarchical brain gradients. In analyses examining extended sensory hierarchies that we first validated, we found distinct hierarchical INT alterations for hallucinations versus delusions in the auditory and somatosensory systems, thus providing support for hierarchical perceptual-inference models of psychosis. Simulations using a large-scale biophysical model suggested local elevations of excitation-inhibition ratio at different hierarchical levels as a potential mechanism. More generally, our work highlights the robustness and utility of INT for studying hierarchical processes relevant to basic and clinical neuroscience.
MRI biomarkers in osseous tumors Fukuda, Takeshi; Wengler, Kenneth; de Carvalho, Ruben ...
Journal of magnetic resonance imaging,
September 2019, Letnik:
50, Številka:
3
Journal Article
Recenzirano
Although radiography continues to play a critical role in osseous tumor assessment, there have been remarkable advances in cross‐sectional imaging. MRI has taken a lead in this assessment due to high ...tissue contrast and spatial resolution, which are well suited for bone lesion assessment. More recently, although somewhat lagging other organ systems, quantitative parameters have shown promising potential as biomarkers for osseous tumors. Among these sequences are chemical shift imaging (CSI), apparent diffusion coefficient (ADC), and intravoxel incoherent motion (IVIM) from diffusion‐weighted imaging (DWI), quantitative dynamic contrast enhanced (DCE)‐MRI, and magnetic resonance spectroscopy (MRS). In this article, we review the background and recent roles of these quantitative MRI biomarkers for osseous tumors.
Level of Evidence: 3
Technical Efficacy Stage: 3
J. MAGN. RESON. IMAGING 2019. J. Magn. Reson. Imaging 2019;50:702–718.
Purpose
To evaluate the role of true diffusion and flow‐related pseudodiffusion in cerebral blood flow (CBF) quantification using arterial spin labeling (ASL) with single‐shot or segmented 3D ...gradient and spin echo (GRASE) readouts.
Theory
The extended phase graph (EPG) algorithm, originally designed to model the effects of T1/T2 relaxation and true diffusion in MRI acquisitions utilizing multiple refocusing RF pulses, was augmented (aEPG). This augmentation accounted for flow‐related pseudodiffusion attenuation of intravascular MRI signal in the k‐space domain during 3D‐GRASE acquisition, which leads to blur along the partition direction in the image domain. Blurring of ASL signal into neighboring voxels can lead to underestimation of CBF in small, high‐flow structures such as cortical gray matter (GM).
Methods
The diffusion sensitivity of 3D‐GRASE was evaluated through aEPG simulations and in vivo experiments in 13 healthy subjects. The CBF estimation bias for different postlabeling delays, crusher gradient strengths, and segmentation factors along the partition (PAR) and phase‐encoding (PE) directions was numerically assessed by simulations and experimentally validated.
Results
In vivo experiments demonstrated systematic underestimation of mean GM CBF measured with segmented 3D‐GRASE. The GM CBF underestimation depended on ASL preparation and imaging parameters; it reached up to 25% at low‐segmentation schemes (1PAR × 2PE) but was considerably lower at high‐segmentation schemes (4PAR × 2PE or 8PAR × 2PE). Theoretical predictions showed that conventional T1/T2 relaxation and true diffusion may account for at most ∼25% of GM CBF estimation bias, whereas the pseudodiffusion effect constituted the major fraction in a typical ASL experiment.
Conclusion
The pseudodiffusion effect leads to considerable estimation bias in ASL‐based CBF quantification using 3D‐GRASE readouts. This bias can be substantially reduced by increasing the segmentation factors. Magn Reson Med 80:736–747, 2018. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
Existing ultrashort echo time magnetic resonance imaging (UTE MRI) methods require prohibitively long acquisition times (~ 20-40 min) to quantitatively assess the clinically relevant fast decay T
* ...component in ligaments and tendons. The purpose of this study was to evaluate the feasibility and clinical translatability of a novel abbreviated quantitative UTE MRI paradigm for monitoring graft remodeling after anterior cruciate ligament (ACL) reconstruction.
Eight patients who had Graftlink™ hamstring autograft reconstruction were recruited for this prospective study. A 3D double-echo UTE sequence at 3.0 Tesla was performed at 3- and 6-months post-surgery. An abbreviated UTE MRI paradigm was established based on numerical simulations and in vivo validation from healthy knees. This proposed approach was used to assess the T
* for fast decay component (Formula: see text) and bound water signal fraction (f
) of ACL graft in regions of interest drawn by a radiologist.
Compared to the conventional bi-exponential model, the abbreviated UTE MRI paradigm achieved low relative estimation bias for Formula: see text and f
over a range of clinically relevant values for ACL grafts. A decrease in Formula: see text of the intra-articular graft was observed in 7 of the 8 ACL reconstruction patients from 3- to 6-months (- 0.11 ± 0.16 ms, P = 0.10). Increases in Formula: see text and f
from 3- to 6-months were observed in the tibial intra-bone graft (Formula: see text: 0.19 ± 0.18 ms, P < 0.05; Δf
: 4% ± 4%, P < 0.05). Lower Formula: see text (- 0.09 ± 0.11 ms, P < 0.05) was observed at 3-months when comparing the intra-bone graft to the graft/bone interface in the femoral tunnel. The same comparisons at the 6-months also yielded relatively lower Formula: see text (- 0.09 ± 0.12 ms, P < 0.05).
The proposed abbreviated 3D UTE MRI paradigm is capable of assessing the ACL graft remodeling process in a clinically translatable acquisition time. Longitudinal changes in Formula: see text and f
of the ACL graft were observed.
Pretreatment positron emission tomography (PET) with 2-deoxy-2-18Ffluoro-D-glucose (FDG) and magnetic resonance spectroscopy (MRS) may identify biomarkers for predicting remission (absence of ...depression). Yet, no such image-based biomarkers have achieved clinical validity. The purpose of this study was to identify biomarkers of remission using machine learning (ML) with pretreatment FDG-PET/MRS neuroimaging, to reduce patient suffering and economic burden from ineffective trials.
This study used simultaneous PET/MRS neuroimaging from a double-blind, placebo-controlled, randomized antidepressant trial on 60 participants with major depressive disorder (MDD) before initiating treatment. After eight weeks of treatment, those with ≤7 on 17-item Hamilton Depression Rating Scale were designated a priori as remitters (free of depression, 37%). Metabolic rate of glucose uptake (metabolism) from 22 brain regions were acquired from PET. Concentrations (mM) of glutamine and glutamate and gamma-aminobutyric acid (GABA) in anterior cingulate cortex were quantified from MRS. The data were randomly split into 67% train and cross-validation (n=40), and 33% test (n=20) sets. The imaging features, along with age, sex, handedness, and treatment assignment (selective serotonin reuptake inhibitor or SSRI vs. placebo) were entered into the eXtreme Gradient Boosting (XGBoost) classifier for training.
In test data, the model showed 62% sensitivity, 92% specificity, and 77% weighted accuracy. Pretreatment metabolism of left hippocampus from PET was the most predictive of remission.
The pretreatment neuroimaging takes around 60 minutes but has potential to prevent weeks of failed treatment trials. This study effectively addresses common issues for neuroimaging analysis, such as small sample size, high dimensionality, and class imbalance.
•Pretreatment imaging can predict remission with 77% weighted accuracy.•The predictive performance does not differ by sex or treatment assignment.•Pretreatment metabolism of left hippocampus is the most predictive of remission.•Outlier removal improves model performance for predicting remission.•Synthetic data generation is an effective way to address class imbalance.
Abstract
Patients with schizophrenia have a high prevalence of cigarette smoking and respond poorly to conventional treatments, highlighting the need for new therapies. We conducted a mechanistic, ...proof-of-concept study using bilateral deep repetitive transcranial magnetic stimulation (dTMS) of insular and prefrontal cortices at high frequency, using the specialized H4 coil. Feasibility of dTMS was tested for disruption of tobacco self-administration, insula target engagement, and insula circuit modulation, all of which were a priori outcomes of interest. Twenty patients completed the study, consisting of weekday dTMS sessions (randomization to active dTMS or sham; double-blind; 10 patients per group), a laboratory tobacco self-administration paradigm (pre/post assessments), and multimodal imaging (three MRI total sessions). Results showed that participants assigned to active dTMS were slower to initiate smoking their first cigarette compared with sham, consistent with smoking disruption. The imaging analyses did not reveal significant Time × Group interactions, but effects were in the anticipated directions. In arterial spin labeling analyses testing for target engagement, an overall decrease in insula blood flow, measured during a post-treatment MRI versus baseline, was numerically more pronounced in the active dTMS group than sham. In fMRI analyses, resting-state connectivity between the insula and default mode network showed a numerically greater change from baseline in the active dTMS group than sham, consistent with a functional change to insula circuits. Exploratory analyses further suggested a therapeutic effect of dTMS on symptoms of psychosis. These initial observations pave the way for future confirmatory studies of dTMS in smoking patients with schizophrenia.
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