Voxel-based Quantification Research Articles

Metabolic-associated fatty liver voxel-based quantification on CT images using a contrast adapted automatic tool

Background & aimsMetabolic-dysfunction associated fatty liver disease (MAFLD) is highly prevalent and can lead to liver complications and comorbidities, with non-invasive tests such as vibration-controlled transient elastography (VCTE) and invasive liver biopsies being used for diagnosis The aim of the present study was to develop a new fully automatized method for quantifying the percentage of fat in the liver based on a voxel analysis on computed tomography (CT) images to solve previously unconcluded diagnostic deficiencies either in contrast (CE) or non-contrast enhanced (NCE) assessments. MethodsLiver and spleen were segmented using nn-UNet on CE- and NCE-CT images. Radiodensity values were obtained for both organs for defining the key benchmarks for fatty liver assessment: liver mean, liver-to-spleen ratio, liver-spleen difference, and their average. VCTE was used for validation. A classification task method was developed for detection of suitable patients to fulfill maximum reproducibility across cohorts and highlight subjects with other potential radiodensity-related diseases. ResultsBest accuracy was attained using the average of all proposed benchmarks being the liver-to-spleen ratio highly useful for CE and the liver-to-spleen difference for NCE. The proposed whole-organ automatic segmentation displayed superior potential when compared to the typically used manual region-of-interest drawing as it allows to accurately obtain the percent of fat in liver, among other improvements. Atypical patients were successfully stratified through a function based on biochemical data. ConclusionsThe developed method tackles the current drawbacks including biopsy invasiveness, and CT-related weaknesses such as lack of automaticity, dependency on contrast agent, no quantification of the percentage of fat in liver, and limited information on region-to-organ affectation. We propose this tool as an alternative for individualized MAFLD evaluation by an early detection of abnormal CT patterns based in radiodensity whilst abording detection of non-suitable patients to avoid unnecessary exposure to CT radiation. Furthermore, this work presents a surrogate aid for assessing fatty liver at a primary assessment of MAFLD using elastography data.

The bone morphogenetic protein 2 analogue L51P enhances spinal fusion in combination with BMP2 in an in vivo rat tail model

Bone morphogenic protein 2 (BMP2) is known to induce osteogenesis and is applied clinically to enhance spinal fusion despite adverse effects. BMP2 needs to be used in high doses to be effective due to the presence of BMP2 inhibitors. L51P is a BMP2 analogue that acts by inhibition of BMP2 inhibitors. Here, we hypothesized that mixtures of BMP2 and L51P could achieve better spinal fusion outcomes regarding ossification. To test whether mixtures of both cytokines are sufficient to improve ossification, 45 elderly Wistar rats (of which 21 were males) were assigned to seven experimental groups, all which received spinal fusion surgery, including discectomy at the caudal 4–5 level using an external fixator and a porous β-tricalcium phosphate (βTCP) carrier. These βTCP carriers were coated with varying concentrations of BMP2 and L51P. X-rays were taken immediately after surgery and again six and twelve weeks post-operatively. Histological sections and µCT were analyzed after twelve weeks. Spinal fusion was assessed using X-ray, µCT and histology according to the Bridwell scale by voxel-based quantification and a semi-quantitative histological score, respectively. The results were congruent across modalities and revealed high ossification for high-dose BMP2 (10 µg), while PBS induced no ossification. Low-dose BMP2 (1 µg) or 10 µg L51P alone did not induce relevant bone formation. However, all combinations of low-dose BMP2 with L51P (1 µg + 1/5/10 µg) were able to induce similar ossificationas high-dose BMP2. These results are of high clinical relevance, as they indicate L51P is sufficient to increase the efficacy of BMP2 and thus lower the required dose for spinal fusion. Statement of SignificanceSpinal fusion surgery is frequently applied to treat spinal pathologies. Bone Morphogenic Protein-2 (BMP2) has been approved by the U .S. Food and Drug Administration (FDA-) and by the “Conformité Européenne” (CE)-label. However, its application is expensive and high concentrations cause side-effects. This research targets the improvement of the efficacy of BMP2 in spinal fusion surgery.

Whole-brain mapping of increased manganese levels in welders and its association with exposure and motor function

Although manganese (Mn) is a trace metal essential for humans, chronic exposure to Mn can cause accumulation of this metal ion in the brain leading to an increased risk of neurological and neurobehavioral health effects. This is a concern for welders exposed to Mn through welding fumes. While brain Mn accumulation in occupational settings has mostly been reported in the basal ganglia, several imaging studies also revealed elevated Mn in other brain areas. Since Mn functions as a magnetic resonance imaging (MRI) T1 contrast agent, we developed a whole-brain MRI approach to map in vivo Mn deposition differences in the brains of non-exposed factory controls and exposed welders. This is a cross-sectional analysis of 23 non-exposed factory controls and 36 exposed full-time welders from the same truck manufacturer. We collected high-resolution 3D MRIs of brain anatomy and R1 relaxation maps to identify regional differences using voxel-based quantification (VBQ) and statistical parametric mapping. Furthermore, we investigated the associations between excess Mn deposition and neuropsychological and motor test performance. Our results indicate that: (1) Using whole-brain MRI relaxometry methods we can generate excess Mn deposition maps in vivo, (2) excess Mn accumulation due to occupational exposure occurs beyond the basal ganglia in cortical areas associated with motor and cognitive functions, (3) Mn likely diffuses along white matter tracts in the brain, and (4) Mn deposition in specific brain regions is associated with exposure (cerebellum and frontal cortex) and motor metrics (cerebellum and hippocampus).

Usefulness of Voxel-Based Quantification (VBQ) Smoothing in Relaxation Time Mapping

Voxel-based quantification (VBQ) smoothing is a technique used to smooth quantitative parametric maps in the Montreal Neurological Institute standard space. Although VBQ smoothing could suppress changes in quantitative values at tissue boundaries, its effectiveness on relaxation time (T1 and T2 values and proton density PD) maps has not been investigated. The purpose of this study was to clarify the usefulness of VBQ smoothing in relaxation time mapping. T1 and T2 values and PD maps of the brains of 20 healthy participants were obtained using a two-dimensional multi-dynamic multi-echo sequence. VBQ and Gaussian smoothing were applied to the relaxation time maps by varying the kernel size by 1 mm from 1 to 6 mm. Changes in relaxation time before and after VBQ and Gaussian smoothing for the putamen, caudate nucleus, substantia nigra, and corpus callosum on the relaxation time maps were evaluated. The changes in relaxation time after VBQ smoothing application were smaller than those in that after Gaussian smoothing application. Although the differences in the relaxation time for all tissues before and after VBQ and Gaussian smoothing applications increased with increasing kernel size for all relaxation times for both methods, the changes in the relaxation time for VBQ smoothing were smaller than those in that for Gaussian smoothing. VBQ smoothing can suppress the change in the relaxation time on the boundary of the tissue and is thus a useful smoothing technique in relaxation time mapping.

Clinical correlates of R1 relaxometry and magnetic susceptibility changes in multiple sclerosis: a multi-parameter quantitative MRI study of brain iron and myelin

ObjectivesThe clinical impact of brain microstructural abnormalities in multiple sclerosis (MS) remains elusive. We aimed to characterize the topography of longitudinal relaxation rate (R1) and quantitative susceptibility (χ) changes, as indices of iron and myelin, together with brain atrophy, and to clarify their contribution to cognitive and motor disability in MS.MethodsIn this cross-sectional study, voxel-based morphometry, and voxel-based quantification analyses of R1 and χ maps were conducted in gray matter (GM) and white matter (WM) of 117 MS patients and 53 healthy controls. Voxel-wise between-group differences were assessed with nonparametric permutation tests, while correlations between MRI metrics and clinical variables (global disability, cognitive and motor performance) were assessed both globally and voxel-wise within clusters emerging from the between-group comparisons.ResultsMS patients showed widespread R1 decrease associated with more limited modifications of χ, with atrophy mainly involving deep GM, posterior and infratentorial regions (p < 0.02). While R1 and χ showed a parallel reduction in several WM tracts (p < 0.001), reduced GM R1 values (p < 0.001) were associated with decreased thalamic χ (p < 0.001) and small clusters of increased χ in the caudate nucleus and prefrontal cortex (p < 0.02). In addition to the atrophy, χ values in the cingulum and corona radiata correlated with global disability and motor performance, while focal demyelination correlated with cognitive performance (p < 0.04).ConclusionsWe confirmed the presence of widespread R1 changes, involving both GM and WM, and atrophy in MS, with less extensive modifications of tissue χ. While atrophy and χ changes are related to global and motor disability, R1 changes are meaningful correlates of cognition.Key Points• Compared to healthy controls, multiple sclerosis patients showed R1 and χ changes suggestive of iron increase within the basal ganglia and reduced iron and myelin content within (subnuclei of) the thalamus.• Thalamic volume and χ changes significantly predicted clinical disability, as well as pulvinar R1 and χ changes, independently from atrophy.• Atrophy-independent R1 and χ changes, suggestive of thalamic iron and myelin depletion, may represent a sensitive marker of subclinical inflammation.

Clinical phenotype modulates brain\u2019s myelin and iron content in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is associated with brain pathology extending beyond temporal lobe structures. We sought to look for informative patterns of brain tissue properties in TLE that go beyond the established morphometry differences. We hypothesised that volume differences, particularly in hippocampus, will be paralleled by changes in brain microstructure. The cross-sectional study included TLE patients (n = 25) from a primary care center and sex-/age-matched healthy controls (n = 55). We acquired quantitative relaxometry-based magnetic resonance imaging (MRI) data yielding whole-brain maps of grey matter volume, magnetization transfer (MT) saturation, and effective transverse relaxation rate R2* indicative for brain tissue myelin and iron content. For statistical analysis, we used the computational anatomy framework of voxel-based morphometry and voxel-based quantification. There was a positive correlation between seizure activity and MT saturation measures in the ipsilateral hippocampus, paralleled by volume differences bilaterally. Disease duration correlated positively with iron content in the mesial temporal lobe, while seizure freedom was associated with a decrease of iron in the very same region. Our findings demonstrate the link between TLE clinical phenotype and brain anatomy beyond morphometry differences to show the impact of disease burden on specific tissue properties. We provide direct evidence for the differential effect of clinical phenotype characteristics on processes involving tissue myelin and iron in mesial temporal lobe structures. This study offers a proof-of-concept for the investigation of novel imaging biomarkers in focal epilepsy.

Region- and voxel-based quantification in human brain of [18F]LSN3316612, a radioligand for O-GlcNAcase

BackgroundPrevious studies found that the positron emission tomography (PET) radioligand [18F]LSN3316612 accurately quantified O-GlcNAcase in human brain using a two-tissue compartment model (2TCM). This study sought to assess kinetic model(s) as an alternative to 2TCM for quantifying [18F]LSN3316612 binding, particularly in order to generate good-quality parametric images.MethodsThe current study reanalyzed data from a previous study of 10 healthy volunteers who underwent both test and retest PET scans with [18F]LSN3316612. Kinetic analysis was performed at the region level with 2TCM using 120-min PET data and arterial input function, which was considered as the gold standard. Quantification was then obtained at both the region and voxel levels using Logan plot, Ichise's multilinear analysis-1 (MA1), standard spectral analysis (SA), and impulse response function at 120 min (IRF120). To avoid arterial sampling, a noninvasive relative quantification (standardized uptake value ratio (SUVR)) was also tested using the corpus callosum as a pseudo-reference region. Venous samples were also assessed to see whether they could substitute for arterial ones.ResultsLogan and MA1 generated parametric images of good visual quality and their total distribution volume (VT) values at both the region and voxel levels were strongly correlated with 2TCM-derived VT (r = 0.96–0.99) and showed little bias (up to − 8%). SA was more weakly correlated to 2TCM-derived VT (r = 0.93–0.98) and was more biased (~ 16%). IRF120 showed a strong correlation with 2TCM-derived VT (r = 0.96) but generated noisier parametric images. All techniques were comparable to 2TCM in terms of test–retest variability and reliability except IRF120, which gave significantly worse results. Noninvasive SUVR values were not correlated with 2TCM-derived VT, and arteriovenous equilibrium was never reached.ConclusionsCompared to SA and IRF, Logan and MA1 are more suitable alternatives to 2TCM for quantifying [18F]LSN3316612 and generating good-quality parametric images.

Early brainstem [18F]THK5351 uptake is linked to cortical hyperexcitability in healthy aging.

BACKGROUNDNeuronal hyperexcitability characterizes the early stages of Alzheimer’s disease (AD). In animals, early misfolded tau and amyloid-β (Aβ) protein accumulation — both central to AD neuropathology — promote cortical excitability and neuronal network dysfunction. In healthy humans, misfolded tau and Aβ aggregates are first detected, respectively, in the brainstem and frontomedial and temporobasal cortices, decades prior to the onset of AD cognitive symptoms. Whether cortical excitability is related to early brainstem tau — and its associated neuroinflammation — and cortical Aβ aggregations remains unknown.METHODSWe probed frontal cortex excitability, using transcranial magnetic stimulation combined with electroencephalography, in a sample of 64 healthy late-middle–aged individuals (50–69 years; 45 women and 19 men). We assessed whole-brain [18F]THK5351 PET uptake as a proxy measure of tau/neuroinflammation, and we assessed whole-brain Aβ burden with [18F]Flutemetamol or [18F]Florbetapir radiotracers.RESULTSWe found that higher [18F]THK5351 uptake in a brainstem monoaminergic compartment was associated with increased cortical excitability (r = 0.29, P = 0.02). By contrast, [18F]THK5351 PET signal in the hippocampal formation, although strongly correlated with brainstem signal in whole-brain voxel-based quantification analyses (P value corrected for family-wise error [PFWE-corrected] < 0.001), was not significantly associated with cortical excitability (r = 0.14, P = 0.25). Importantly, no significant association was found between early Aβ cortical deposits and cortical excitability (r = –0.20, P = 0.11).CONCLUSIONThese findings reveal potential brain substrates for increased cortical excitability in preclinical AD and may constitute functional in vivo correlates of early brainstem tau accumulation and neuroinflammation in humans.TRIAL REGISTRATIONEudraCT 2016-001436-35.FUNDINGF.R.S.-FNRS Belgium, Wallonie-Bruxelles International, ULiège, Fondation Simone et Pierre Clerdent, European Regional Development Fund.

The relationship between hippocampal-dependent task performance and hippocampal grey matter myelination and iron content.

Individual differences in scene imagination, autobiographical memory recall, future thinking and spatial navigation have long been linked with hippocampal structure in healthy people, although evidence for such relationships is, in fact, mixed. Extant studies have predominantly concentrated on hippocampal volume. However, it is now possible to use quantitative neuroimaging techniques to model different properties of tissue microstructure in vivo such as myelination and iron. Previous work has linked such measures with cognitive task performance, particularly in older adults. Here we investigated whether performance on scene imagination, autobiographical memory, future thinking and spatial navigation tasks was associated with hippocampal grey matter myelination or iron content in young, healthy adult participants. Magnetic resonance imaging data were collected using a multi-parameter mapping protocol (0.8 mm isotropic voxels) from a large sample of 217 people with widely-varying cognitive task scores. We found little evidence that hippocampal grey matter myelination or iron content were related to task performance. This was the case using different analysis methods (voxel-based quantification, partial correlations), when whole brain, hippocampal regions of interest, and posterior:anterior hippocampal ratios were examined, and across different participant sub-groups (divided by gender and task performance). Variations in hippocampal grey matter myelin and iron levels may not, therefore, help to explain individual differences in performance on hippocampal-dependent tasks, at least in young, healthy individuals.

In chronic complete spinal cord injury supraspinal changes detected by quantitative MRI are confined to volume reduction in the caudal brainstem

There is much controversy about the potential impact of spinal cord injury (SCI) on brain anatomy and function, which is mirrored in the substantial divergence of findings between animal models and human imaging studies. Given recent advances in quantitative magnetic resonance imaging (MRI) we sought to tackle the unresolved question about the link between the presumed injury associated volume differences and underlying brain tissue property changes in a cohort of chronic complete SCI patients. Using the established computational anatomy methods of voxel-based morphometry (VBM) and voxel-based quantification (VBQ), we performed statistical analyses on grey and white matter volumes as well as on parameter maps indicative for myelin, iron, and free tissue water content in the brain of complete SCI patients (n = 14) and healthy individuals (n = 14). Our regionally unbiased white matter analysis showed a significant volume reduction of the dorsal aspect at the junction between the most rostral part of the spinal cord and the medulla oblongata consistent with Wallerian degeneration of proprioceptive axons in the dorsal column tracts in SCI subjects. This observation strongly correlated with spinal cord atrophy assessed by quantification of the spinal cord cross-sectional area at the cervical level C2/3. These findings suggest that Wallerian degeneration of the dorsal column tracts represents a main contributor to the observed spinal cord atrophy, which is highly consistent with preclinical histological evidence of remote changes in the central nervous system secondary to SCI. Structural changes in other brain regions representing remote changes in the course of chronic SCI could neither be confirmed by conventional VBM nor by VBQ analysis. Whether and how MRI based brain morphometry and brain tissue property analysis will inform clinical decision making and clinical trial outcomes in spinal cord medicine remains to be determined.

Predictive Modeling for Voxel-Based Quantification of Imaging-Based Subtypes of Pancreatic Ductal Adenocarcinoma (PDAC): A Multi-Institutional Study.

Simple SummaryPreviously, we demonstrated that qualitative scoring of pancreatic ductal adenocarcinoma (PDAC) tumors on computed tomography (CT) scans (delta) is biologically and clinically relevant, whereby tumors with a conspicuous border (high delta) show more aggressive biology and are associated with worse clinical outcomes when compared to those with an inconspicuous border (low delta). However, in some cases, a visual classification can be challenging and subjective. Here, we used machine learning and quantitative approaches for a multi-institutional dataset to build a biologically and clinically relevant model that can quantitatively identify these imaging-based subtypes of PDAC from routine CT scans. Our results showed that the quantitative classification (q-delta) had high correlation with the gold standard qualitative scoring in internal and external datasets. Further, q-delta classification was demonstrated to be associated with the clinical outcome and the stromal heterogeneity of the PDAC tumors. High intra- and interrater agreement scores indicate the reproducibility of the results.Previously, we characterized qualitative imaging-based subtypes of pancreatic ductal adenocarcinoma (PDAC) on computed tomography (CT) scans. Conspicuous (high delta) PDAC tumors are more likely to have aggressive biology and poorer clinical outcomes compared to inconspicuous (low delta) tumors. Here, we developed a quantitative classification of this imaging-based subtype (quantitative delta; q-delta). Retrospectively, baseline pancreatic protocol CT scans of three cohorts (cohort#1 = 101, cohort#2 = 90 and cohort#3 = 16 [external validation]) of patients with PDAC were qualitatively classified into high and low delta. We used a voxel-based method to volumetrically quantify tumor enhancement while referencing normal-pancreatic-parenchyma and used machine learning-based analysis to build a predictive model. In addition, we quantified the stromal content using hematoxylin- and eosin-stained treatment-naïve PDAC sections. Analyses revealed that PDAC quantitative enhancement values are predictive of the qualitative delta scoring and were used to build a classification model (q-delta). Compared to high q-delta, low q-delta tumors were associated with improved outcomes, and the q-delta class was an independent prognostic factor for survival. In addition, low q-delta tumors had higher stromal content and lower cellularity compared to high q-delta tumors. Our results suggest that q-delta classification provides a clinically and biologically relevant tool that may be integrated into ongoing and future clinical trials.

Kinetic Modelling and Test\u2013Retest Reproducibility for the Dopamine D1R Radioligand [11C]SCH23390 in Healthy and Diseased Mice

PurposeOur aim in this study was to compare different non-invasive pharmacokinetic models and assess test–retest reproducibility of the radioligand [11C]SCH23390 for the quantification of dopamine D1-like receptor (D1R) in both wild-type (WT) mice and heterozygous (HET) Q175DN mice as Huntington’s disease (HD) model.ProceduresAdult WT (n = 9) and HET (n = 14) mice underwent a 90-min [11C]SCH23390 positron emission tomography (PET) scan followed by computed tomography (CT) to evaluate the pharmacokinetic modelling in healthy and diseased conditions. Additionally, 5 WT mice and 7 HET animals received a second [11C]SCH23390 PET scan for test–retest reproducibility. Parallel assessment of the simplified reference tissue model (SRTM), the multilinear reference tissue model (MRTM) and the Logan reference tissue model (Logan Ref) using the striatum as a receptor-rich region and the cerebellum as a receptor-free (reference) region was performed to define the most suitable method for regional- and voxel-based quantification of the binding potential (BPND). Finally, standardised uptake value ratio (SUVR-1) was assessed as a potential simplified measurement.ResultsFor all models, we measured a significant decline in dopamine D1R density (e.g. SRTM = − 38.5 ± 5.0 %, p < 0.0001) in HET mice compared to WT littermates. Shortening the 90-min scan duration resulted in large underestimation of striatal BPND in both WT mice (SRTM 60 min: − 17.7 ± 2.8 %, p = 0.0078) and diseased HET (SRTM 60 min: − 13.1 ± 4.1 %, p = 0.0001). Striatal BPND measurements were very reproducible with an average test–retest variability below 5 % when using both MRTM and SRTM. Parametric BPND maps generated with SRTM were highly reliable, showing nearly perfect agreement to the regional analysis (r2 = 0.99, p < 0.0001). Finally, SRTM provided the most accurate estimate for relative tracer delivery R1 with both regional- and voxel-based analyses. SUVR-1 at different time intervals were not sufficiently reliable when compared to BPND (r2 < 0.66).ConclusionsNinety-minute acquisition and the use of SRTM for pharmacokinetic modelling is recommended. [11C]SCH23390 PET imaging demonstrates optimal characteristics for the study of dopamine D1R density in models of psychiatric and neurological disorders as exemplified in the Q175DN mouse model of HD.

Voxel-Based quantitative MRI reveals spatial patterns of grey matter alteration in multiple sclerosis.

Despite robust postmortem evidence and potential clinical importance of gray matter (GM) pathology in multiple sclerosis (MS), assessing GM damage by conventional magnetic resonance imaging (MRI) remains challenging. This prospective cross‐sectional study aimed at characterizing the topography of GM microstructural and volumetric alteration in MS using, in addition to brain atrophy measures, three quantitative MRI (qMRI) parameters—magnetization transfer (MT) saturation, longitudinal (R1), and effective transverse (R2*) relaxation rates, derived from data acquired during a single scanning session. Our study involved 35 MS patients (14 relapsing–remitting MS; 21 primary or secondary progressive MS) and 36 age‐matched healthy controls (HC). The qMRI maps were computed and segmented in different tissue classes. Voxel‐based quantification (VBQ) and voxel‐based morphometry (VBM) statistical analyses were carried out using multiple linear regression models. In MS patients compared with HC, three configurations of GM microstructural/volumetric alterations were identified. (a) Co‐localization of GM atrophy with significant reduction of MT, R1, and/or R2*, usually observed in primary cortices. (b) Microstructural modifications without significant GM loss: hippocampus and paralimbic cortices, showing reduced MT and/or R1 values without significant atrophy. (c) Atrophy without significant change in microstructure, identified in deep GM nuclei. In conclusion, this quantitative multiparametric voxel‐based approach reveals three different spatially‐segregated combinations of GM microstructural/volumetric alterations in MS that might be associated with different neuropathology.

Integrating Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging to Improve the Predictive Capabilities of CED Models

This paper aims to develop a comprehensive and subject-specific model to predict the drug reach in Convection-Enhanced Delivery (CED) interventions. To this end, we make use of an advance diffusion imaging technique, namely the Neurite Orientation Dispersion and Density Imaging (NODDI), to incorporate a more precise description of the brain microstructure into predictive computational models. The NODDI dataset is used to obtain a voxel-based quantification of the extracellular space volume fraction that we relate to the white matter (WM) permeability. Since the WM can be considered as a transversally isotropic porous medium, two equations, respectively for permeability parallel and perpendicular to the axons, are derived from a numerical analysis on a simplified geometrical model that reproduces flow through fibre bundles. This is followed by the simulation of the injection of a drug in a WM area of the brain and direct comparison of the outcomes of our results with a state-of-the-art model, which uses conventional diffusion tensor imaging. We demonstrate the relevance of the work by showing the impact of our newly derived permeability tensor on the predicted drug distribution, which differs significantly from the alternative model in terms of distribution shape, concentration profile and infusion linear penetration length.

Mapping of pathological change in chronic fatigue syndrome using the ratio of T1- and T2-weighted MRI scans

Myalgic Encephalomyelitis or Chronic Fatigue Syndrome (ME/CFS) subjects suffer from a variety of cognitive complaints indicating that the central nervous system plays a role in its pathophysiology. Recently, the ratio T1w/T2w has been used to study changes in tissue myelin and/or iron levels in neurodegenerative diseases such as multiple sclerosis and schizophrenia. In this study, we applied the T1w/T2w method to detect changes in tissue microstructure in ME/CFS patients relative to healthy controls. We mapped the T1w/T2w signal intensity values in the whole brain for forty-five ME/CFS patients who met Fukuda criteria and twenty-seven healthy controls and applied both region- and voxel-based quantification. We also performed interaction-with-group regressions with clinical measures to test for T1w/T2w relationships that are abnormal in ME/CFS at the population level. Region-based analysis showed significantly elevated T1w/T2w values (increased myelin and/or iron) in ME/CFS in both white matter (WM) and subcortical grey matter. The voxel-based group comparison with sub-millimetre resolution voxels detected very significant clusters with increased T1w/T2w in ME/CFS, mostly in subcortical grey matter, but also in brainstem and projection WM tracts. No areas with decreased T1w/T2w were found in either analysis. ME/CFS T1w/T2w regressions with heart-rate variability, cognitive performance, respiration rate and physical well-being were abnormal in both gray and white matter foci. Our study demonstrates that the T1w/T2w approach is very sensitive and shows increases in myelin and/or iron in WM and basal ganglia in ME/CFS.

A group-level comparison of volumetric and combined volumetric-surface normalization for whole brain analyses of myelin and iron maps

Quantitative MRI (qMRI) provides surrogate brain maps of myelin and iron content. After spatial normalization to a common standard brain space, these may be used to detect altered myelination and iron accumulation in clinical populations. Here, volumetric and combined volumetric and surface-based (CVS) normalization were compared to identify which procedure would afford the greatest sensitivity to inter-regional differences (contrast), and the lowest inter-subject variability (under normal conditions), of myelin- and iron-related qMRI parameters, in whole-brain group-level studies.Ten healthy volunteers were scanned twice at 3 Tesla. Three-dimensional T1-weighted, T2-weighted and multi-parametric mapping sequences for brain qMRI were used to map myelin and iron content over the whole brain. Parameter maps were spatially normalized using volumetric (DARTEL) and CVS procedures. Tissue probability weighting and isotropic Gaussian smoothing were integrated in DARTEL for voxel-based quantification (VBQ). Contrasts, coefficients of variations and sensitivity to detecting differences in the parameters were estimated in standard space for each approach on region of interest (ROI) and voxel-by-voxel bases.The contrast between cortical and subcortical ROIs with respectively different myelin and iron content was higher following CVS, compared to DARTEL-VBQ, normalization. Across cortical voxels, the inter-individual variability of myelin and iron qMRI maps were comparable between CVS (with no smoothing) and DARTEL-VBQ (with smoothing).CVS normalization of qMRI maps preserves higher myelin and iron contrast than DARTEL-VBQ over the entire brain, while exhibiting comparable variability in the cerebral cortex without extra smoothing. Thus, CVS may prove useful for detecting small microstructural differences in whole-brain group-level qMRI studies.

Voxel-by-voxel 4D flow MRI-based assessment of regional reverse flow in the aorta.

Complex and reverse flow in the aorta has been implicated in aneurysm development and stroke via retrograde embolization. To evaluate global and regional differences between standard 2D plane-based and volumetric voxel-based quantification of regional forward/reverse flow, and reverse flow fraction (RFF) in the aorta. Retrospective. In all, 35 subjects: 10 healthy controls (age: 57 ± 7 years, nine male), nine patients without aortic valve regurgitation (AR) (age: 63 ± 10 years, seven male), six patients with mild AR (age: 66 ± 6 years, five male), and 10 with moderate or severe AR (age: 60 ± 16 years, eight male). 4D flow MRI (3T and 1.5T) was employed to acquire 3D blood flow velocities with entire thoracic aorta in all subjects. Data analysis included standard 2D plane-based quantification of forward/reverse flow, and RFF-plane. In addition, a new semiautomatic workflow based on 3D segmentation and extraction of an aorta centerline was developed for voxel-by-voxel visualization (forward/reverse flow and RFF-voxel maps) and quantification of regional voxel-by-voxel forward/reverse flow in the entire thoracic aorta. Kruskal-Wallis tests were performed to test for differences between groups. A two-sample t-test or Wilcoxon rank sum test was used to compare voxel-based and plane-based results. Semiautomatic plane-based analysis showed excellent agreement with standard manual plane-based analysis for net flow and RFF-plane (RFF-plane: y = 0.99x-0.0, net flow: y = 1.00x-0.21, R > 0.99, P < 0.0001). Voxel-by-voxel maps demonstrated marked regional flow reversal in the ascending aorta in all patients and RFF-voxel was significantly increased (P < 0.001) compared to RFF-plane for all four groups, with the most pronounced differences for mild AR (18.0 ± 15.2% vs. 4.7 ± 5.4%). Voxel-based flow and RFF-voxel along the aorta showed areas with marked regional flow reversal (eg, vortex flow) compared to plane-based analysis. Voxel-based analysis demonstrated regional flow reversal that was not detected by plane-based analysis. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1276-1286.

Absorbed-dose calculation for treatment of liver neoplasms with 90Y-microspheres

The aim of this review article is to present a state-of-the-art of the absorbed-dose calculation for the selective internal radiation therapy (SIRT) of liver neoplasms with 90Y-microspheres. The review focuses on the following aspects: activity quantification, partition model, medical internal radiation dose (MIRD) formalism, three-dimensional dosimetry, micro-scale dosimetry, and radiobiological modeling. 99mTc-macro-aggregated albumin (MAA) with single-photon emission tomography (SPECT) serves as a surrogate for 90Y-microspheres for treatment planning and predictive dosimetry. Iterative reconstruction with physic modeling to compensate quantification biases is now a standard for activity quantification. For post-implantation dosimetry, direct 90Y quantification with time of flight positron emission tomography has demonstrated good accuracy. The partition model is a simple and well-known approach for tumor, normal liver, and lung dosimetry measured from 99mTc-MAA-SPECT, while the MIRD equations can provide more detailed schemes for pre- and post-implantation dosimetry. 3D dosimetry allows considering heterogeneous activity and material distribution thanks to voxel-based quantification and energy deposition modeling. For the latter, dose-kernel convolution or local energy deposition approaches are widespread. Micro-scale dosimetry studies have highlighted high-absorbed-dose heterogeneities at the microscopic level. Microscopic models were developed and can be incorporated into macro-scale dosimetry. More recently, radiobiological models have been applied to calculate the biological effective dose. 90Y-microspheres dosimetry for SIRT is an active field of research in all its aspects. Its ease of implementation in a clinical setting along with the development of microscopic and radiobiological models should contribute to better handle treatment outcomes.

Cortical and Subcortical Changes in Alzheimer's Disease: A Longitudinal and Quantitative MRI Study.

Quantitative MRI provides important information about tissue properties in brain both in normal ageing and in degenerative disorders. Although it is well known that those with Alzheimer's disease (AD) show a specific pattern and faster rate of atrophy than controls, the precise spatial and temporal patterns of quantitative MRI in AD are unknown. We aimed to investigate neuroimaging correlates of AD using serial quantitative MRI. In our study, twenty-one subjects with AD and thirty-two similar-aged healthy controls underwent two serial MRI scans at baseline and 12 months. Tissue characteristics were captured using two quantitative MRI parameters: longitudinal relaxation time (qT1) and transverse relaxation time (qT2). The two groups (AD and controls) were statistically compared using a voxel based quantification (VBQ) method based on Matlab and SPM8. At baseline, subjects with AD showed a significant reduction of qT1 and qT2 compared to controls in bilateral temporal and parietal lobes, hippocampus, and basal ganglia. This pattern was also observed at follow-up. Longitudinally, in AD we found a significant increase rather than further reduction of qT1 and qT2 from the baseline in bilateral hippocampus, thalamus and right caudate nucleus. In addition, the longitudinal change of qT1 in left hippocampus was negatively correlated with cognitive decline in AD over the 1-year period, and the general disease severity significantly predicted the amount of increase of qT1 in bilateral hippocampus over 12 months. The longitudinal change of qT2 in left parahippocampus correlated with change in neuropsychiatric features over time. In summary, quantitative MRI parameters were reduced in AD cross-sectionally, but increased over time, showing distinct spatiotemporal patterns from the atrophy in AD. We also showed the clinical relevance of quantitative MRI parameters, indicating their potential promise as new imaging markers in AD.

Longitudinal patterns of leukoaraiosis and brain atrophy in symptomatic small vessel disease.

Cerebral small vessel disease is a common condition associated with lacunar stroke, cognitive impairment and significant functional morbidity. White matter hyperintensities and brain atrophy, seen on magnetic resonance imaging, are correlated with increasing disease severity. However, how the two are related remains an open question. To better define the relationship between white matter hyperintensity growth and brain atrophy, we applied a semi-automated magnetic resonance imaging segmentation analysis pipeline to a 3-year longitudinal cohort of 99 subjects with symptomatic small vessel disease, who were followed-up for ≥1 years. Using a novel two-stage warping pipeline with tissue repair step, voxel-by-voxel rate of change maps were calculated for each tissue class (grey matter, white matter, white matter hyperintensities and lacunes) for each individual. These maps capture both the distribution of disease and spatial information showing local rates of growth and atrophy. These were analysed to answer three primary questions: first, is there a relationship between whole brain atrophy and magnetic resonance imaging markers of small vessel disease (white matter hyperintensities or lacune volume)? Second, is there regional variation within the cerebral white matter in the rate of white matter hyperintensity progression? Finally, are there regionally specific relationships between the rates of white matter hyperintensity progression and cortical grey matter atrophy? We demonstrate that the rates of white matter hyperintensity expansion and grey matter atrophy are strongly correlated (Pearson's R = -0.69, P < 1 × 10(-7)), and significant grey matter loss and whole brain atrophy occurs annually (P < 0.05). Additionally, the rate of white matter hyperintensity growth was heterogeneous, occurring more rapidly within long association fasciculi. Using voxel-based quantification (family-wise error corrected P < 0.05), we show the rate of white matter hyperintensity progression is associated with increases in cortical grey matter atrophy rates, in the medial-frontal, orbito-frontal, parietal and occipital regions. Conversely, increased rates of global grey matter atrophy are significantly associated with faster white matter hyperintensity growth in the frontal and parietal regions. Together, these results link the progression of white matter hyperintensities with increasing rates of regional grey matter atrophy, and demonstrate that grey matter atrophy is the major contributor to whole brain atrophy in symptomatic cerebral small vessel disease. These measures provide novel insights into the longitudinal pathogenesis of small vessel disease, and imply that therapies aimed at reducing progression of white matter hyperintensities via end-arteriole damage may protect against secondary brain atrophy and consequent functional morbidity.