Brain parenchymal fraction in an age-stratified healthy population – determined by MRI using manual segmentation and three automated segmentation methods

Deciphering the shift from benign to active relapsing-remitting multiple sclerosis: Insights into T regulatory cell dysfunction and apoptosis regulation

BACKGROUND

Relapsing-remitting multiple sclerosis (RRMS), a common demyelinating disease among young adults, follows a benign course in 10-15% of cases, where patients experience minimal neurological disability for a decade following disease onset. However, there is potential for these benign cases to transition into a clinically active, relapsing state.

OBJECTIVE

To elucidate the biological mechanisms underlying the transition from benign to active RRMS using gene expression analysis.

METHODS

We employed complementary-DNA microarrays to examine peripheral-blood gene expression patterns in patients with benign MS, defined as having a disease duration exceeding 10 years and an Expanded Disability Status Scale (EDSS) score of ≤3.0. We compared the gene expression pattern between patients who switched to active disease (Switching BMS) with those who maintained a benign state (Permanent-BMS) during an additional 5-year follow-up.

RESULTS

We identified two primary mechanisms linked to the transition from benign MS to clinically active disease. The first involves the suppression of regulatory T cell activity, and the second pertains to the dysfunction of nuclear receptor 4 A family-dependent apoptosis. These mechanisms collectively contribute to an augmented autoimmune response and increased disease activity.

CONCLUSIONS

The intricate gene regulatory networks that operate in switching-BMS are related to suppression of immune tolerance and aberrant apoptosis. These findings may lead to new therapeutic targets to prevent the escalation to active disease.

Age-stratified Assessment of Brain Volumetric Segmentation on the Indian Population Using Quantitative Magnetic Resonance Imaging

BACKGROUND AND PURPOSE

Automated methods for quantifying brain tissue volumes have gained clinical interest for their objective assessment of neurological diseases. This study aimed to establish reference curves for brain volumes and fractions in the Indian population using Synthetic MRI (SyMRI), a quantitative imaging technique providing multiple contrast-weighted images through fast postprocessing.

METHODS

The study included a cohort of 314 healthy individuals aged 15-65 years from multiple hospitals/centers across India. The SyMRI-quantified brain volumes and fractions, including brain parenchymal fraction (BPF), gray matter fraction (GMF), white matter fraction (WMF), and myelin.

RESULTS

Normative age-stratified quantification curves were created based on the obtained data. The results showed significant differences in brain volumes between the sexes, but not after normalization by intracranial volume.

CONCLUSION

The findings provide normative data for the Indian population and can be used for comparative analysis of brain structure values. Furthermore, our data indicate that the use of fractions rather than absolute volumes in normative curves, such as BPF, GMF, and WMF, can mitigate sex and population differences as they account for individual differences in head size or brain volume.

MER and increased operative time are not risk factors for the formation of pneumocephalus during DBS

Although only recently directional leads have proven their potential to compensate for sub-optimally placed electrodes, optimal lead positioning remains the most critical factor in determining Deep Brain Stimulation (DBS) outcome. Pneumocephalus is a recognized source of error, but the factors that contribute to its formation are still a matter of debate. Among these, operative time is one of the most controversial. Because cases of DBS performed with Microelectrode Recordings (MER) are affected by an increase in surgical length, it is useful to analyze whether MER places patients at risk for increased intracranial air entry. Data of 94 patients from two different institutes who underwent DBS for different neurologic and psychiatric conditions were analyzed for the presence of postoperative pneumocephalus. Operative time and use of MER, as well as other potential risk factors for pneumocephalus (age, awake vs. asleep surgery, number of MER passages, burr hole size, target and unilateral vs. bilateral implants) were examined. Mann-Whitney U and Kruskal-Wallis tests were utilized to compare intracranial air distributions across groups of categorical variables. Partial correlations were used to assess the association between time and volume. A generalized linear model was created to predict the effects of time and MER on the volume of intracranial air, controlling for other potential risk factors identified: age, number of MER passages, awake vs. asleep surgery, burr hole size, target, unilateral vs. bilateral surgery. Significantly different distributions of air volume were noted between different targets, unilateral vs. bilateral implants, and number of MER trajectories. Patients undergoing DBS with MER did not present a significant increase in pneumocephalus compared to patients operated without (p = 0.067). No significant correlation was found between pneumocephalus and time. Using multivariate analysis, unilateral implants exhibited lower volumes of pneumocephalus (p = 0.002). Two specific targets exhibited significantly different volumes of pneumocephalus: the bed nucleus of the stria terminalis with lower volumes (p < 0.001) and the posterior hypothalamus with higher volumes (p = 0.011). MER, time, and other parameters analyzed failed to reach statistical significance. Operative time and use of intraoperative MER are not significant predictors of pneumocephalus during DBS. Air entry is greater for bilateral surgeries and may be also influenced by the specific stimulated target.

Technical and clinical validation of commercial automated volumetric MRI tools for dementia diagnosis-a systematic review

Developments in neuroradiological MRI analysis offer promise in enhancing objectivity and consistency in dementia diagnosis through the use of quantitative volumetric reporting tools (QReports). Translation into clinical settings should follow a structured framework of development, including technical and clinical validation steps. However, published technical and clinical validation of the available commercial/proprietary tools is not always easy to find and pathways for successful integration into the clinical workflow are varied. The quantitative neuroradiology initiative (QNI) framework highlights six necessary steps for the development, validation and integration of quantitative tools in the clinic. In this paper, we reviewed the published evidence regarding regulatory-approved QReports for use in the memory clinic and to what extent this evidence fulfils the steps of the QNI framework. We summarize unbiased technical details of available products in order to increase the transparency of evidence and present the range of reporting tools on the market. Our intention is to assist neuroradiologists in making informed decisions regarding the adoption of these methods in the clinic. For the 17 products identified, 11 companies have published some form of technical validation on their methods, but only 4 have published clinical validation of their QReports in a dementia population. Upon systematically reviewing the published evidence for regulatory-approved QReports in dementia, we concluded that there is a significant evidence gap in the literature regarding clinical validation, workflow integration and in-use evaluation of these tools in dementia MRI diagnosis.

Brain volumetric and fractal analysis of synthetic MRI: A comparative study with conventional 3D T1-weighted images

PURPOSE

The estimation of brain volumetric measurements based on Synthetic MRI (SyMRI) is easy and fast, however, the consistency of brain volumetric and morphologic measurements based on SyMRI and 3D T1WI should be further addressed. The current study evaluated the impact of spatial resolution on brain volumetric and morphologic measurements using SyMRI, and test whether the brain measurements derived from SyMRI were consistent with those resulted from 3D T1WI.

METHOD

Brain volumetric and fractal analysis were applied to thirty healthy subjects, each underwent four SyMRI acquisitions with different spatial resolutions (1 × 1 × 2 mm, 1 × 1x3mm, 1 × 1 × 4 mm, 2 × 2 × 2 mm) and a 3D T1WI (1 × 1 × 1 mm isotropic). The consistency of the SyMRI measurements was tested using one-way non-parametric Kruskal-Wallis test and post hoc Dwass-Steel-Critchlow-Fligner test. The association between SyMRI and 3D T1WI derived measurements was evaluated using linear regression models.

RESULTS

Our results demonstrated that both in- and through-plane resolutions show an impact on brain volumetric measurements, while brain parenchymal volume showed high consistency across the SyMRI acquisitions, and high association with the measurements from 3D T1WI. In addition, SyMRI with 1 × 1 × 4 mm resolution showed the strongest association with 3D T1WI compared to other SyMRI acquisitions in both volumetric and fractal analyses. Moreover, substantial differences were found in fractal dimension of both gray and white matter between the SyMRI and 3D T1WI tissue segmentations.

CONCLUSIONS

Our results suggested that the measurements from SyMRI with relatively higher in-plane and lower through-plane resolution (1 × 1 × 4 mm) are much closer to 3D T1WI.

Age-Related Changes in Relaxation Times, Proton Density, Myelin, and Tissue Volumes in Adult Brain Analyzed by 2-Dimensional Quantitative Synthetic Magnetic Resonance Imaging

OBJECTIVES

Quantitative synthetic magnetic resonance imaging (MRI) enables the determination of fundamental tissue properties, namely, T1 and T2 relaxation times and proton density (PD), in a single scan. Myelin estimation and brain segmentation based on these quantitative values can also be performed automatically. This study aimed to reveal the changes in tissue characteristics and volumes of the brain according to age and provide age-specific reference values obtained by quantitative synthetic MRI.

MATERIALS AND METHODS

This was a prospective study of healthy subjects with no history of brain diseases scanned with a multidynamic multiecho sequence for simultaneous measurement of relaxometry of T1, T2, and PD. We performed myelin estimation and brain volumetry based on these values. We performed volume-of-interest analysis on both gray matter (GM) and white matter (WM) regions for T1, T2, PD, and myelin volume fraction maps. Tissue volumes were calculated in the whole brain, producing brain parenchymal volume, GM volume, WM volume, and myelin volume. These volumes were normalized by intracranial volume to a brain parenchymal fraction, GM fraction, WM fraction, and myelin fraction (MyF). We examined the changes in the mean regional quantitative values and segmented tissue volumes according to age.

RESULTS

We analyzed data of 114 adults (53 men and 61 women; median age, 66.5 years; range, 21-86 years). T1, T2, and PD values showed quadratic changes according to age and stayed stable or decreased until around 60 years of age and increased thereafter. Myelin volume fraction showed a reversed trend. Brain parenchymal fraction and GM fraction decreased throughout all ages. The approximation curves showed that WM fraction and MyF gradually increased until around the 40s to 50s and decreased thereafter. A significant decline in MyF was first noted in the 60s age group (Tukey test, P < 0.001).

CONCLUSIONS

Our study showed changes according to age in tissue characteristic values and brain volumes using quantitative synthetic MRI. The reference values for age demonstrated in this study may be useful to discriminate brain disorders from healthy brains.

Estimation of intracranial volume: A comparative study between synthetic MRI and FSL-brain extraction tool (BET)2

Brain extraction represents an important step in numerous neuroimaging analyses. The brain extraction tool (BET)2 is a widely used deformable model-based approach for extraction of intracranial volume (ICV). The aim of this study is to estimate the ICV extraction accuracy using synthetic MR(SyMRI) method and BET2 in healthy adult participants and patients with Sturge-Weber Syndrome (SWS), including infants. 'Quantification of relaxation times and proton density by multi-echo acquisition of saturation recovery with turbo-spin-echo readout' (QRAPMASTER) with a 3.0 T magnetic resonance image (MRI) system was used for data acquisition. Statistical evaluations were performed with linear regression analysis and the Jaccard similarity coefficient (J). ICV extraction accuracy with synthetic MR method is found to be higher than BET2, for both aged healthy participants and SWS.

Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI database

When analyzing large multicenter databases, the effects of multiple confounding covariates increase the variability in the data and may reduce the ability to detect changes due to the actual effect of interest, for example, changes due to disease. Efficient ways to evaluate the effect of covariates toward the data harmonization are therefore important. In this article, we showcase techniques to assess the "goodness of harmonization" of covariates. We analyze 7,656 MR images in the multisite, multiscanner Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We present a comparison of three methods for estimating total intracranial volume to assess their robustness and correct the brain structure volumes using the residual method and the proportional (normalization by division) method. We then evaluated the distribution of brain structure volumes over the entire ADNI database before and after accounting for multiple covariates such as total intracranial volume, scanner field strength, sex, and age using two techniques: (a) Zscapes, a panoramic visualization technique to analyze the entire database and (b) empirical cumulative distributions functions. The results from this study highlight the importance of assessing the goodness of data harmonization as a necessary preprocessing step when pooling large data set with multiple covariates, prior to further statistical data analysis.

The profile of blunt traumatic infratentorial cranial bleed types

Infratentorial traumatic intracranial bleeds (ICBs) are rare and the distribution of subtypes is unknown. To characterize this distribution the National Trauma Data Bank (NTDB) 2014 was queried for adults with single type infratentorial ICB, n = 1,821: subdural hemorrhage (SDH), subarachnoid hemorrhage (SAH), epidural hemorrhage (EDH), and intraparenchymal hemorrhage (IPH). Comparisons were made between the groups with statistical significance determined using chi squared and t-tests. SDH occurred in 29% of patients, mostly in elderly on anti-coagulants (13%) after a fall (77%), 42% of them underwent craniotomy, their mortality was the lowest (4%). SAH was the most common (56%) occurring mostly from traffic related injuries (27%). Furthermore, 9% of them had a severe head injury Glasgow Coma Scale ≤8 (GCS), but had the lowest Injury Severity Score (ISS, median 8) as well as a short hospital length of stay, 5.1 ± 6.2 days. These patients were most likely to be discharged to home (64%). They had the lowest mortality (4%). EDH was the least common ICB (5%), occurred in younger patients (median age 49 years), and it had the highest percentage of associated injuries (13%). EDH patients presented with the poorest neurological status (26% GCS ≤8, ISS median 25) and were operated on more than any other ICB type (55%). EDH was the highest mortality (9%) ICB type and had a low discharge to home rate (58%). IPH was uncommon (10%). Infratentorial bleeds types have different clinical courses, and outcomes. Understanding these differences can be useful in managing these patients.

Application of Synthetic MRI for Direct Measurement of Magnetic Resonance Relaxation Time and Tumor Volume at Multiple Time Points after Contrast Administration: Preliminary Results in Patients with Brain Metastasis

Objective

The purpose of this study was to investigate the time-dependent effects of contrast medium on multi-dynamic, multi-echo (MDME) sequence in patients with brain metastases.

Materials and Methods

This study included 7 patients with 15 brain metastases who underwent magnetic resonance (MR) examination which included MDME sequences at 1 minute, 10 minutes and 20 minutes after contrast injection. Two volumes of interests, covering an entire tumor (whole tumor) and the enhancing portion of the tumor, were derived from post-contrast synthetic T1-weighted images. Statistical comparisons were performed for three different time delays for histogram parameters of the longitudinal relaxation rate (R₁) and the transverse relaxation rate (R₂), and lesion volumes.

Results

The mean and the median of R₁ and the mean of R₂ in both the whole tumor and the inner enhancing portion were larger on the 10 minutes delayed images than on the 1 minute or 20 minutes delayed images (mean of R₁ in the whole tumor on the 1 minute, 10 minutes, and 20 minutes delayed images: 1.26 ms, 1.39 ms, and 1.37 ms; mean of R₁ in the inner enhancing portion: 1.43 ms, 1.53 ms and 1.44 ms; all p < 0.017). The volumes of the whole tumor and the inner enhancing portion were significantly larger in the 10 minutes and 20 minutes delayed images than on the 1 minute delayed images (all p < 0.017).

Conclusion

Magnetic resonance relaxation times and the volumes of the whole tumor and the inner enhancing portion were measured larger on the 10 minutes or 20 minutes delayed images than on the 1 minute delayed images. The MDME sequence immediately after contrast injection cannot fully reflect the effects of gadolinium-based contrast agent leakage in the tissue.

SyMRI of the Brain: Rapid Quantification of Relaxation Rates and Proton Density, With Synthetic MRI, Automatic Brain Segmentation, and Myelin Measurement

Conventional magnetic resonance images are usually evaluated using the image signal contrast between tissues and not based on their absolute signal intensities. Quantification of tissue parameters, such as relaxation rates and proton density, would provide an absolute scale; however, these methods have mainly been performed in a research setting. The development of rapid quantification, with scan times in the order of 6 minutes for full head coverage, has provided the prerequisites for clinical use. The aim of this review article was to introduce a specific quantification method and synthesis of contrast-weighted images based on the acquired absolute values, and to present automatic segmentation of brain tissues and measurement of myelin based on the quantitative values, along with application of these techniques to various brain diseases. The entire technique is referred to as “SyMRI” in this review. SyMRI has shown promising results in previous studies when used for multiple sclerosis, brain metastases, Sturge-Weber syndrome, idiopathic normal pressure hydrocephalus, meningitis, and postmortem imaging.

Searching for neurodegeneration in multiple sclerosis at clinical onset: Diagnostic value of biomarkers

BACKGROUND

Neurodegeneration occurs during the early stages of multiple sclerosis. It is an essential, devastating part of the pathophysiology. Tools for measuring the degree of neurodegeneration could improve diagnostics and patient characterization.

OBJECTIVE

This study aimed to determine the diagnostic value of biomarkers of degeneration in patients with recent clinical onset of suspected multiple sclerosis, and to evaluate these biomarkers for characterizing disease course.

METHODS

This cross-sectional study included 271 patients with clinical features of suspected multiple sclerosis onset and was the baseline of a prospective study. After diagnostic investigations, the patients were classified into the following disease groups: patients with clinically isolated syndrome (n = 4) or early relapsing remitting multiple sclerosis (early RRMS; n = 93); patients with relapsing remitting multiple sclerosis with disease durations ≥2 years (established RRMS; n = 39); patients without multiple sclerosis, but showing symptoms (symptomatic controls; n = 89); and patients diagnosed with other diseases (n = 46). In addition, we included healthy controls (n = 51) and patients with progressive multiple sclerosis (n = 23). We analyzed six biomarkers of neurodegeneration: cerebrospinal fluid neurofilament light chain levels; cerebral spinal fluid glial fibrillary acidic protein; cerebral spinal fluid tau; retinal nerve fiber layer thickness; macula volume; and the brain parenchymal fraction.

RESULTS

Except for increased cerebral spinal fluid neurofilament light chain levels, median 670 ng/L (IQR 400-2110), we could not find signs of early degeneration in the early disease group with recent clinical onset. However, the intrathecal immunoglobin G production and cerebral spinal fluid neurofilament light chain levels showed diagnostic value. Moreover, elevated levels of cerebral spinal fluid glial fibrillary acidic protein, thin retinal nerve fiber layers, and low brain parenchymal fractions were associated with progressive disease, but not with the other phenotypes. Thin retinal nerve fiber layers and low brain parenchymal fractions, which indicated neurodegeneration, were associated with longer disease duration.

CONCLUSIONS

In clinically suspected multiple sclerosis, intrathecal immunoglobin G production and neurofilament light chain levels had diagnostic value. Therefore, these biomarkers could be included in diagnostic work-ups for multiple sclerosis. We found that the thickness of the retinal nerve fiber layer and the brain parenchymal fraction were not different between individuals that were healthy, symptomatic, or newly diagnosed with multiple sclerosis. This finding suggested that neurodegeneration had not reached a significant magnitude in patients with a recent clinical onset of multiple sclerosis.

Improved Precision of Automatic Brain Volume Measurements in Patients with Clinically Isolated Syndrome and Multiple Sclerosis Using Edema Correction

BACKGROUND AND PURPOSE

The presence of edema will result in increased brain volume, which may obscure progressing brain atrophy. Similarly, treatment-induced edema reduction may appear as accelerated brain tissue loss (pseudoatrophy). The purpose of this study was to correlate brain tissue properties to brain volume, to investigate the possibilities for edema correction and the resulting improvement of the precision of automated brain volume measurements.

MATERIALS AND METHODS

A group of 38 patients with clinically isolated syndrome or newly diagnosed MS were imaged at inclusion and after 1, 2, and 4 years using an MR quantification sequence. Brain volume, relaxation rates (R₁ and R₂), and proton density were measured by automated software.

RESULTS

The reduction of normalized brain volume with time after inclusion was 0.273%/year. The mean SDs were 0.508%, 0.526%, 0.454%, and 0.687% at baseline and 1, 2, and 4 years. Linear regression of the relative change of normalized brain volume and the relative change of R₁, R₂, and proton density showed slopes of -0.198 (P < .001), 0.156 (P = .04), and 0.488 (P < .001), respectively. After we applied the measured proton density as a correction factor, the mean SDs decreased to 24.2%, 4.8%, 33.3%, and 17.4%, respectively. The observed atrophy rate reduced from 0.273%/year to 0.238%/year.

CONCLUSIONS

Correlations between volume and R₁, R₂, and proton density were observed in the brain, suggesting that a change of brain tissue properties can affect brain volume. Correction using these parameters decreased the variation of brain volume measurements and may have reduced the effect of pseudoatrophy.

Automated brain tissue and myelin volumetry based on quantitative MR imaging with various in-plane resolutions

BACKGROUND AND PURPOSE

Segmented brain tissue and myelin volumes can now be automatically calculated using dedicated software (SyMRI), which is based on quantification of R₁ and R₂ relaxation rates and proton density. The aim of this study was to determine the validity of SyMRI brain tissue and myelin volumetry using various in-plane resolutions.

METHODS

We scanned 10 healthy subjects on a 1.5T MR scanner with in-plane resolutions of 0.8, 2.0 and 3.0mm. Two scans were performed for each resolution. The acquisition time was 7-min and 24-sec for 0.8mm, 3-min and 9-sec for 2.0mm and 1-min and 56-sec for 3.0mm resolutions. The volumes of white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), non-WM/GM/CSF (NoN), brain parenchymal volume (BPV), intracranial volume (ICV) and myelin were compared between in-plane resolutions. Repeatability for each resolution was then analyzed.

RESULTS

No significant differences in volumes measured were found between the different in-plane resolutions, except for NoN between 0.8mm and 2.0mm and between 2.0mm and 3.0mm. The repeatability error value for the WM, GM, CSF, NoN, BPV and myelin volumes relative to ICV was 0.97%, 1.01%, 0.65%, 0.86%, 1.06% and 0.25% in 0.8mm; 1.22%, 1.36%, 0.73%, 0.37%, 1.18% and 0.35% in 2.0mm and 1.18%, 1.02%, 0.96%, 0.45%, 1.36%, and 0.28% in 3.0mm resolutions.

CONCLUSION

SyMRI brain tissue and myelin volumetry with low in-plane resolution and short acquisition times is robust and has a good repeatability so could be useful for follow-up studies.

A six-month longitudinal evaluation significantly improves accuracy of predicting incipient Alzheimer's disease in mild cognitive impairment

RATIONALE AND OBJECTIVES

Early prediction of incipient Alzheimer's disease (AD) dementia in individuals with mild cognitive impairment (MCI) is important for timely therapeutic intervention and identifying participants for clinical trials at greater risk of developing AD. Methods to predict incipient AD in MCI have mostly utilized cross-sectional data. Longitudinal data enables estimation of the rate of change of variables, which along with the variable levels have been shown to improve prediction power. While some efforts have already been made in this direction, all previous longitudinal studies have been based on observation periods longer than one year, hence limiting their practical utility. It remains to be seen if follow-up evaluations within shorter intervals can significantly improve the accuracy of prediction in this problem. Our aim was to determine the added value of incorporating 6-month longitudinal data for predicting progression from MCI to AD.

MATERIALS AND METHODS

Using 6-months longitudinal data from 247 participants with MCI, we trained two Random Forest classifiers to distinguish between progressive MCI (n=162) and stable MCI (n=85) cases. These models utilized structural MRI, neurocognitive assessments, and demographic information. The first model (cross-sectional) only used baseline data. The second model (longitudinal) used data from both baseline and a 6-month follow-up evaluation allowing the model to additionally incorporate biomarkers' rate of change.

RESULTS

The longitudinal model (AUC=0.87; accuracy=80.2%) performed significantly better (P<0.05) than the cross-sectional model (AUC=0.82; accuracy=71.7%).

CONCLUSION

Short-term longitudinal assessments significantly enhance the performance of AD prediction models.

Brain Parenchymal Fraction in Healthy Adults-A Systematic Review of the Literature

Brain atrophy is an important feature of many neurodegenerative disorders. It can be described in terms of change in the brain parenchymal fraction (BPF). In order to interpret the BPF in disease, knowledge on the BPF in healthy individuals is required. The aim of this study was to establish a normal range of values for the BPF of healthy individuals via a systematic review of the literature. The databases PubMed and Scopus were searched and 95 articles, including a total of 9269 individuals, were identified including the required data. We present values of BPF from healthy individuals stratified by age and post-processing method. The mean BPF correlated with mean age and there were significant differences in age-adjusted mean BPF between methods. This study contributes to increased knowledge about BPF in healthy individuals, which may assist in the interpretation of BPF in the setting of disease. We highlight the differences between post-processing methods and the need for a consensus gold standard.