Quantitative relaxometry of the brain

Investigating the association between human brainstem microstructural integrity and hypertension using magnetic resonance relaxometry

The brainstem plays a vital role in regulating blood pressure, and disruptions to its neural pathways have been linked to hypertension. However, it remains unclear whether subtle microstructural changes in the brainstem are associated with an individual's blood pressure status. This exploratory, cross-sectional study investigated the relationship between brainstem microstructure, myelination, and hypertensive status in 116 cognitively unimpaired adults (aged 22-94 years). Advanced MRI techniques, including relaxometry (R1, R2) and myelin water fraction (MWF) analysis, were employed to assess microstructural integrity and myelin content in ten brainstem subregions. Our results revealed significant associations between higher microstructural damage or lower myelin content (indicated by lower R1, R2, or MWF values) and hypertensive status, particularly in the midbrain tegmentum. Notably, combining these MRI metrics yielded high classification accuracy (AUC > 0.85). Our findings suggest a potential link between disrupted brainstem tissue integrity, myelin content, and elevated blood pressure, warranting further longitudinal investigations to explore this relationship.

MRI-T2 Relaxometry is Increased in Mild Traumatic Brain Injury: Indications of Acute Brain Abnormalities After Injury

Mild traumatic brain injury (mTBI) is a common condition, particularly pervasive in contact sports environments. A range of symptoms can accompany this type of injury and negatively impact people's lives. As mTBI diagnosis and recovery largely rely on subjective reports, more objective injury markers are needed. The current study compared structural brain MRI-T2 relaxometry between a group of 40 male athletes with mTBI within 14 days of injury and 40 age-matched male controls. Voxel-averaged T2 relaxometry within the gray matter was increased for the mTBI group compared to controls (p < 0.001), with statistically significant increased T2 relaxometry particularly in superior cortical regions. Our findings indicate subtle brain abnormalities can be identified in acute mTBI using MRI-T2 relaxometry. These brain abnormalities may reflect inflammation present in the brain and could constitute an objective injury marker to supplement current subjective methods that dominate clinical decisions regarding diagnosis and prognosis. Future research should validate this potential marker with other data types, such as blood biomarkers or histological samples.

Longitudinal Placental Blood Volume Measurements in Zika-Infected Rhesus Macaques Using Ferumoxytol Enhanced MRI

Introduction

Measures of maternal fractional blood volume (mFBV) in the placenta holds potential to diagnose placental vasculature deficiencies. However, methods for quantitative mapping of blood volume are challenging to implement for clinical placenta evaluation. As a preliminary step towards human applications, this study assesses the feasibility of blood volume measurements using ferumoxytol enhanced variable flip angle (VFA) T1-mapping in Zika-infected rhesus macaques.

Methods

Seven pregnant rhesus macaques were imaged longitudinally at up to 3 timepoints across gestation (days 64.5±1.9, 100.8±3.9, and 145.3±1.8), corresponding to first, second, and third pregnancy trimester of the rhesus. Four animals received a Zika virus (ZIKV) injection into the amniotic fluid, while three control rhesus macaques received a saline injection. T1-weighted spoiled gradient echo sequences at four flip angles (2°, 6°, 10°, 14°) were used for quantitative mFBV assessment derived from pre- and post-contrast T1 mapping using ferumoxytol. Image quality assessment and segmentation assessment was performed on the full 3D coverage. Placental histopathology for all animals was analyzed by a professional pathologist with over 15 years of experience.

Results

All scans were successfully acquired and analyzed with no significant motion artifacts. 3D mFBV maps show regional heterogeneities within slices. FBV and total placental blood volume has an increasing trend with gestation.

Discussion

This study shows feasibilities to measure mFBV in non-human primates using ferumoxytol enhanced VFA T1-mapping.

Age-Related Differences in the Choroid Plexus Structural Integrity Are Associated with Changes in Cognition

The choroid plexus (CP) plays a critical role in maintaining central nervous system (CNS) homeostasis, producing cerebrospinal fluid, and regulating the entry of specific substances into the CNS from blood. CP dysfunction has been implicated in various neurological and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, and multiple sclerosis. This study investigates the relationship between CP structural integrity and cognitive decline in normative aging, using structural and advanced magnetic resonance imaging techniques, including CP volume, diffusion tensor imaging indices (mean diffusivity, MD, and fractional anisotropy, FA) and relaxometry metrics (longitudinal, T1, and transverse, T2, relaxation times). Our results show that diminished CP microstructural integrity, as reflected by higher T1, T2, and MD values, or lower FA values, is associated with lower cognitive performance in processing speed and fluency. Notably, CP microstructural measures demonstrated greater sensitivity to cognitive decline than macrostructural measures, i.e. CP volume. Longitudinal analysis revealed that individuals with reduced CP structural integrity exhibit steeper cognitive decline over time. Furthermore, structural equation modeling revealed that a latent variable representing CP integrity predicts faster overall cognitive decline, with an effect size comparable to that of age. These findings highlight the importance of CP integrity in maintaining cognitive health and suggest that a holistic approach to assessing CP integrity could serve as a sensitive biomarker for early detection of cognitive decline. Further research is needed to elucidate the mechanisms underlying the relationship between CP structural integrity and cognitive decline and to explore the potential therapeutic implications of targeting CP function to prevent or treat age-related cognitive deficits.

Ensemble learning-based radiomics model for discriminating brain metastasis from glioblastoma

OBJECTIVE

Differentiating between brain metastasis (BM) and glioblastoma (GBM) preoperatively is challenging due to their similar imaging features on conventional brain MRI. This study aimed to enhance diagnostic accuracy through a machine learning model based on MRI radiomics data.

METHODS

This retrospective study included 235 patients with confirmed solitary BM and 273 patients with GBM. Patients were randomly assigned to the training (n = 356) or the validation (n = 152) cohort. Conventional brain MRI sequences including T1-weighted imaging (T1WI), contrast-enhanced_T1WI, and T2-weighted imaging (T2WI) were acquired. Brain tumors were delineated on all three sequences and segmented. Features were selected from demographic, clinical, and radiomic data. An integrated ensemble machine learning model, i.e., the elastic regression-SVM-SVM model (ERSS) and a multivariable logistic regression (LR) model combining demographic, clinical, and radiomic data were built for predictive modeling. Model efficiency was evaluated using discrimination, calibration, and decision curve analyses. Additionally, external validation was performed using an independent cohort consisting of 47 patients with GBM and 43 patients with isolated BM to assess the ERSS model generalizability.

RESULTS

The ERSS model demonstrated more optimal classification performance (AUC: 0.9548, 95% CI: 0.9337-0.9734 in training cohort; AUC: 0.9716, 95% CI: 0.9485-0.9895 in validation cohort) as compared to the LR model according to the receiver operating characteristic (ROC) curve and decision curve for the internal cohort. The external validation cohort had less optimal but still robust performance (AUC: 0.7174, 95% CI: 0.6172-0.8024). The ERSS model with integration of multiple classifiers, including elastic net, random forest and support vector machine, produced robust predictive performance and outperformed the LR method.

CONCLUSION

The results suggested that the integrated machine learning model, i.e., the ERSS model, had the potential for efficient and accurate preoperative differentiation of BM from GBM, which may improve clinical decision-making and outcomes of patients with brain tumors.

T1 mapping using MP2RAGE in degenerative cervical myelopathy: a longitudinal study

BACKGROUND AND PURPOSE

Degenerative cervical myelopathy (DCM) is the most common cause of spinal cord (SC) dysfunction. In routine clinical practice, SC changes are well depicted using conventional MRI, especially T2-weighted imaging. However, this modality usually fails to provide satisfactory clinico-radiological correlations. In this context we assessed the potential value of quantitative changes measured with a T1 MP2RAGE sequence.

MATERIALS AND METHODS

18 patients diagnosed with chronic onset of DCM and 17 healthy controls (HC) were enrolled in the study. Clinical presentation was assessed using the modified Japanese Orthopaedic Association (mJOA) scale. Sagittal cervical SC T2-w 3D SPACE imaging and T1 MP2RAGE mapping were performed at baseline and 3-months postoperatively. Data were processed using Matlab and the SC Toolbox.

RESULTS

mJOA score increased from 13.3 ± 2.1 preoperatively to 14.4 ± 1.9 at follow-up (p = 0.027). Site of maximum compression (Cmax) was at C3-C4 cervical levels in 4 patients, C4-C5 in 8 patients, C5-C6 in 5 patients and C6-C7 in 1 patient. SC compression was multi-level in 7 patients and single-level in 11 patients. T2-w hyperintensity was present in 15 patients. Mean SC T1 values in the whole SC in the DCM group at baseline showed significant difference as compared to mean SC T1 values in HC group (962.2 ± 62 vs. 924.9 ± 34 ms, respectively (p < 0.0001)) but no differences could be observed between baseline and 3-month follow-up (962.4 ± 59 ms (p = 0.86)). Z-scores at baseline were - 0.05 ± 1 for mild, 1.2 ± 1.9 for moderate and 2.5 ± 1.2 for severe. Mean baseline and 3-month follow-up SC T1 values were weakly but significantly correlated to preoperative (R2 = 0.33 (p = 0.013) and postoperative mJOA (R2 = 0.29 (p = 0.024). Baseline T1 value at C2 level was significantly correlated with mJOA at 3-month follow-up (p = 0.048).

CONCLUSIONS

T1-MP2RAGE mapping in patients with DCM demonstrated both focal and diffuse cervical SC alteration. It could thus be a biomarker for patients with DCM managed surgically.

Brain microstructure alterations in subjective cognitive decline: a multi-component T2 relaxometry study

Previous research has revealed patterns of brain atrophy in subjective cognitive decline, a potential preclinical stage of Alzheimer's disease. However, the involvement of myelin content and microstructural alterations in subjective cognitive decline has not previously been investigated. This study included three groups of participants recruited from the Compostela Aging Study project: 53 cognitively unimpaired adults, 16 individuals with subjective cognitive decline and hippocampal atrophy and 70 with subjective cognitive decline and no hippocampal atrophy. Group differences were analysed across five MRI biomarkers derived from multi-component T2 relaxometry, each sensitive to variations in cerebral composition and microstructural tissue integrity. Although no significant differences in myelin content were observed between groups, the subjective cognitive decline with hippocampal atrophy group exhibited a larger free-water fraction, and reduced fraction and relaxation times of the intra/extracellular water compartment in frontal, parietal and medial temporal lobe brain regions and white matter tracts as compared with the other groups. Moreover, both subjective cognitive decline groups displayed lower total water content as compared with the control group and the subjective cognitive decline with hippocampal atrophy group showed lower total water content as compared with the subjective cognitive decline without hippocampal atrophy group. These changes are likely related to microstructural tissue differences related to neuroinflammation, axonal degeneration, iron accumulation or other physiologic variations, calling for further examinations.

Brain tumor enhancement prediction from pre-contrast conventional weighted images using synthetic multiparametric mapping and generative artificial intelligence

Background

Gadolinium-based contrast agents (GBCAs) are usually employed for glioma diagnosis. However, GBCAs raise safety concerns, lead to patient discomfort and increase costs. Parametric maps offer a potential solution by enabling quantification of subtle tissue changes without GBCAs, but they are not commonly used in clinical practice due to the need for specifically targeted sequences. This work proposes to predict post-contrast T1-weighted enhancement without GBCAs from pre-contrast conventional weighted images through synthetic parametric maps computed with generative artificial intelligence (deep learning).

Methods

In this retrospective study, three datasets have been employed: (I) a proprietary dataset with 15 glioma patients (hereafter, GLIOMA dataset); (II) relaxometry maps from 5 healthy volunteers; and (III) UPenn-GBM, a public dataset with 493 glioblastoma patients. A deep learning method for synthesizing parametric maps from only two conventional weighted images is proposed. Particularly, we synthesize longitudinal relaxation time (T1), transversal relaxation time (T2), and proton density (PD) maps. The deep learning method is trained in a supervised manner with the GLIOMA dataset, which comprises weighted images and parametric maps obtained with magnetic resonance image compilation (MAGiC). Thus, MAGiC maps were used as references for the training. For testing, a leave-one-out scheme is followed. Finally, the synthesized maps are employed to predict T1-weighted enhancement without GBCAs. Our results are compared with those obtained by MAGiC; specifically, both the maps obtained with MAGiC and the synthesized maps are used to distinguish between healthy and abnormal tissue (ABN) and, particularly, tissues with and without T1-weighted enhancement. The generalization capability of the method was also tested on two additional datasets (healthy volunteers and the UPenn-GBM).

Results

Parametric maps synthesized with deep learning obtained similar performance compared to MAGiC for discriminating normal from ABN (sensitivities: 88.37% vs. 89.35%) and tissue with and without T1-weighted enhancement (sensitivities: 93.26% vs. 87.29%) on the GLIOMA dataset. These values were comparable to those obtained on UPenn-GBM (sensitivities of 91.23% and 81.04% for each classification).

Conclusions

Our results suggest the feasibility to predict T1-weighted-enhanced tissues from pre-contrast conventional weighted images using deep learning for the synthesis of parametric maps.

Quantifying brain development in the HEALthy Brain and Child Development (HBCD) Study: The magnetic resonance imaging and spectroscopy protocol

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The acquisition of multimodal magnetic resonance-based brain development data is central to the study's core protocol. However, application of Magnetic Resonance Imaging (MRI) methods in this population is complicated by technical challenges and difficulties of imaging in early life. Overcoming these challenges requires an innovative and harmonized approach, combining age-appropriate acquisition protocols together with specialized pediatric neuroimaging strategies. The HBCD MRI Working Group aimed to establish a core acquisition protocol for all 27 HBCD Study recruitment sites to measure brain structure, function, microstructure, and metabolites. Acquisition parameters of individual modalities have been matched across MRI scanner platforms for harmonized acquisitions and state-of-the-art technologies are employed to enable faster and motion-robust imaging. Here, we provide an overview of the HBCD MRI protocol, including decisions of individual modalities and preliminary data. The result will be an unparalleled resource for examining early neurodevelopment which enables the larger scientific community to assess normative trajectories from birth through childhood and to examine the genetic, biological, and environmental factors that help shape the developing brain.

Physics-guided self-supervised learning for retrospective T1 and T2 mapping from conventional weighted brain MRI: Technical developments and initial validation in glioblastoma

PURPOSE

To develop a self-supervised learning method to retrospectively estimate T1 and T2 values from clinical weighted MRI.

METHODS

A self-supervised learning approach was constructed to estimate T1, T2, and proton density maps from conventional T1- and T2-weighted images. MR physics models were employed to regenerate the weighted images from the network outputs, and the network was optimized based on loss calculated between the synthesized and input weighted images, alongside additional constraints based on prior information. The method was evaluated on healthy volunteer data, with conventional mapping as references. The reproducibility was examined on two 3.0T scanners. Performance in tumor characterization was inspected by applying the method to a public glioblastoma dataset.

RESULTS

For T1 and T2 estimation from three weighted images (T1 MPRAGE, T1 gradient echo sequences, and T2 turbo spin echo), the deep learning method achieved global voxel-wise error ≤9% in brain parenchyma and regional error ≤12.2% in six types of brain tissues. The regional measurements obtained from two scanners showed mean differences ≤2.4% and correlation coefficients >0.98, demonstrating excellent reproducibility. In the 50 glioblastoma patients, the retrospective quantification results were in line with literature reports from prospective methods, and the T2 values were found to be higher in tumor regions, with sensitivity of 0.90 and specificity of 0.92 in a voxel-wise classification task between normal and abnormal regions.

CONCLUSION

The self-supervised learning method is promising for retrospective T1 and T2 quantification from clinical MR images, with the potential to improve the availability of quantitative MRI and facilitate brain tumor characterization.

Enhancing preoperative diagnosis of pancreatic ductal adenocarcinoma and mass-forming chronic pancreatitis: a study on normalized conventional MR imaging parameters

PURPOSE

To assess the utility of signal intensity ratio (SIR) in distinguishing between mass-forming chronic pancreatitis (MFCP) and pancreatic ductal adenocarcinoma (PDAC), thereby reducing unnecessary pancreatectomies or delayed diagnosis brought by misdiagnosis.

MATERIALS AND METHODS

This retrospective study included 170 participants (34 with MFCP and 136 with PDAC) who underwent radical pancreatic surgery and were diagnosed via specimen pathology. The study group was carefully selected with a 1:4 ratio matching for sex, age, and operation time between two entities. T1 SIR, T2 SIR, arterial phase (AP) SIR, portal venous phase (VP) SIR, delay phase (DP) SIR, DWI0-50 SIR, and DWI500-1000 SIR, were calculated by dividing the signal intensity of lesions by that of the paraspinal muscle, serving as a reference organ. Intraclass Correlation Coefficient (ICC) was estimated to evaluate the intraobserver and interobserver reliability. Wilcoxon tests were employed for univariate analysis, and receiver operating characteristic (ROC) curves were generated to determine optimal cutoff points and AUC values for selected predictors. A tenfold cross-validation method was applied to validate the robustness of the results.

RESULTS

The ICC demonstrated excellent correlation for both intraobserver and interobserver(ICCs > 0.8). T1 SIR, AP SIR, VP SIR, and DP SIR were significantly lower in the PDAC group compared to the MFCP group, and exhibited good independent predictive properties with the sensitivities of 61.8, 61.8, 70.6, and 73.5%, specificities of 66.2, 68.4, 59.6, and 55.9%, and AUCs of 0.620, 0.659, 0.670, and 0.668, respectively, hovering around 0.7. The tenfold cross-validation confirmed the reliability and robustness of our findings, with consistent AUC, sensitivity, specificity, and 95% confidence intervals over 1000 iterations.

CONCLUSION

T1 SIR, AP SIR, VP SIR, and DP SIR show promise as potential imaging biomarkers for distinguishing between MFCP and PDAC.

Association of Plasma Markers of Alzheimer's Disease, Neurodegeneration, and Neuroinflammation with the Choroid Plexus Integrity in Aging

The choroid plexus (CP) is a vital brain structure essential for cerebrospinal fluid (CSF) production. Moreover, alterations in the CP's structure and function are implicated in molecular conditions and neuropathologies including multiple sclerosis, Alzheimer's disease, and stroke. Our goal is to provide the first characterization of the association between variation in the CP microstructure and macrostructure/volume using advanced magnetic resonance imaging (MRI) methodology, and blood-based biomarkers of Alzheimer's disease (Aß42/40 ratio; pTau181), neuroinflammation and neuronal injury (GFAP; NfL). We hypothesized that plasma biomarkers of brain pathology are associated with disordered CP structure. Moreover, since cerebral microstructural changes can precede macrostructural changes, we also conjecture that these differences would be evident in the CP microstructural integrity. Our cross-sectional study was conducted on a cohort of 108 well-characterized individuals, spanning 22-94 years of age, after excluding participants with cognitive impairments and non-exploitable MR imaging data. Established automated segmentation methods were used to identify the CP volume/macrostructure using structural MR images, while the microstructural integrity of the CP was assessed using our advanced quantitative high-resolution MR imaging of longitudinal and transverse relaxation times (T1 and T2). After adjusting for relevant covariates, positive associations were observed between pTau181, NfL and GFAP and all MRI metrics. These associations reached significance (p<0.05) except for CP volume vs. pTau181 (p=0.14), CP volume vs. NfL (p=0.35), and T2 vs. NFL (p=0.07). Further, negative associations between Aß42/40 and all MRI metrics were observed but reached significance only for Aß42/40 vs. T2 (p=0.04). These novel findings demonstrate that reduced CP macrostructural and microstructural integrity is positively associated with blood-based biomarkers of AD pathology, neurodegeneration/neuroinflammation and neurodegeneration. Degradation of the CP structure may co-occur with AD pathology and neuroinflammation ahead of clinically detectable cognitive impairment, making the CP a potential structure of interest for early disease detection or treatment monitoring.

Magnetic resonance metrics for identification of cuprizone-induced demyelination in the mouse model of neurodegeneration: a review

Neurodegenerative disorders, including Multiple Sclerosis (MS), are heterogenous disorders which affect the myelin sheath of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) provides a non-invasive method for studying, diagnosing, and monitoring disease progression. As an emerging research area, many studies have attempted to connect MR metrics to underlying pathophysiological presentations of heterogenous neurodegeneration. Most commonly, small animal models are used, including Experimental Autoimmune Encephalomyelitis (EAE), Theiler's Murine Encephalomyelitis (TMEV), and toxin models including cuprizone (CPZ), lysolecithin, and ethidium bromide (EtBr). A contrast and comparison of these models is presented, with focus on the cuprizone model, followed by a review of literature studying neurodegeneration using MRI and the cuprizone model. Conventional MRI methods including T1 Weighted (T1W) and T2 Weighted (T2W) Imaging are mentioned. Quantitative MRI methods which are sensitive to diffusion, magnetization transfer, susceptibility, relaxation, and chemical composition are discussed in relation to studying the CPZ model. Overall, additional studies are needed to improve both the sensitivity and specificity of MRI metrics for underlying pathophysiology of neurodegeneration and the relationships in attempts to clear the clinico-radiological paradox. We therefore propose a multiparametric approach for the investigation of MR metrics for underlying pathophysiology.

Magnetic resonance relaxometry in quantitative imaging of brain gliomas: A literature review

Magnetic resonance (MR) relaxometry is a quantitative imaging method that measures tissue relaxation properties. This review discusses the state of the art of clinical proton MR relaxometry for glial brain tumors. Current MR relaxometry technology also includes MR fingerprinting and synthetic MRI, which solve the inefficiencies and challenges of earlier techniques. Despite mixed results regarding its capability for brain tumor differential diagnosis, there is growing evidence that MR relaxometry can differentiate between gliomas and metastases and between glioma grades. Studies of the peritumoral zones have demonstrated their heterogeneity and possible directions of tumor infiltration. In addition, relaxometry offers T2* mapping that can define areas of tissue hypoxia not discriminated by perfusion assessment. Studies of tumor therapy response have demonstrated an association between survival and progression terms and dynamics of native and contrast-enhanced tumor relaxometric profiles. In conclusion, MR relaxometry is a promising technique for glial tumor diagnosis, particularly in association with neuropathological studies and other imaging techniques.

Joint MAPLE: Accelerated joint T1 and T 2 * $$ {{\mathrm{T}}_2}^{\ast } $$ mapping with scan-specific self-supervised networks

PURPOSE

Quantitative MRI finds important applications in clinical and research studies. However, it is encoding intensive and may suffer from prohibitively long scan times. Accelerated MR parameter mapping techniques have been developed to help address these challenges. Here, an accelerated joint T1,T 2 * $$ {{\mathrm{T}}_2}^{\ast } $$ , frequency and proton density mapping technique with scan-specific self-supervised network reconstruction is proposed to synergistically combine parallel imaging, model-based, and deep learning approaches to speed up parameter mapping.

METHODS

Proposed framework, Joint MAPLE, includes parallel imaging, signal modeling, and data consistency blocks which are optimized jointly in a combined loss function. A scan-specific self-supervised reconstruction is embedded into the framework, which takes advantage of multi-contrast data from a multi-echo, multi-flip angle, gradient echo acquisition.

RESULTS

In comparison with parallel reconstruction techniques powered by low-rank methods, emerging scan specific networks, and model-basedT 2 * $$ {{\mathrm{T}}_2}^{\ast } $$ estimation approaches, the proposed framework reduces the reconstruction error in parameter maps by approximately two-fold on average at acceleration rates as high as R = 16 with uniform sampling. It can outperform evaluated parallel reconstruction techniques up to four-fold on average in the presence of challenging sub-sampling masks. It is observed that Joint MAPLE performs well at extreme acceleration rates of R = 25 and R = 36 with error values less than 20%.

CONCLUSION

Joint MAPLE enables higher fidelity parameter estimation at high acceleration rates by synergistically combining parallel imaging and model-based parameter mapping and exploiting multi-echo, multi-flip angle datasets. Utilizing a scan-specific self-supervised reconstruction obviates the need for large data sets for training while improving the parameter estimation ability.

A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla

Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.

Quantitative T2 mapping-based longitudinal assessment of brain injury and therapeutic rescue in the rat following acute organophosphate intoxication

Acute intoxication with organophosphate (OP) cholinesterase inhibitors poses a significant public health risk. While currently approved medical countermeasures can improve survival rates, they often fail to prevent chronic neurological damage. Therefore, there is need to develop effective therapies and quantitative metrics for assessing OP-induced brain injury and its rescue by these therapies. In this study we used a rat model of acute intoxication with the OP, diisopropylfluorophosphate (DFP), to test the hypothesis that T2 measures obtained from brain magnetic resonance imaging (MRI) scans provide quantitative metrics of brain injury and therapeutic efficacy. Adult male Sprague Dawley rats were imaged on a 7T MRI scanner at 3, 7 and 28 days post-exposure to DFP or vehicle (VEH) with or without treatment with the standard of care antiseizure drug, midazolam (MDZ); a novel antiseizure medication, allopregnanolone (ALLO); or combination therapy with MDZ and ALLO (DUO). Our results show that mean T2 values in DFP-exposed animals were: (1) higher than VEH in all volumes of interest (VOIs) at day 3; (2) decreased with time; and (3) decreased in the thalamus at day 28. Treatment with ALLO or DUO, but not MDZ alone, significantly decreased mean T2 values relative to untreated DFP animals in the piriform cortex at day 3. On day 28, the DUO group showed the most favorable T2 characteristics. This study supports the utility of T2 mapping for longitudinally monitoring brain injury and highlights the therapeutic potential of ALLO as an adjunct therapy to mitigate chronic morbidity associated with acute OP intoxication.

X-ray-Sensitive Doped CaF2-Based MRI Contrast Agents for Local Radiation Dose Measurement

Ionizing radiation has become widely used in medicine, with application in diagnostic techniques, such as computed tomography (CT) and radiation therapy (RT), where X-rays are used to diagnose and treat tumors. The X-rays used in CT and, in particular, in RT can have harmful side effects; hence, an accurate determination of the delivered radiation dose is of utmost importance to minimize any damage to healthy tissues. For this, medical specialists mostly rely on theoretical predictions of the delivered dose or external measurements of the dose. To extend the practical use of ionizing radiation-based medical techniques, such as magnetic resonance imaging (MRI)-guided RT, a more precise measurement of the internal radiation dose internally is required. In this work, a novel approach is presented to measure dose in liquids for potential future in vivo applications. The strategy relies on MRI contrast agents (CAs) that provide a dose-sensitive signal. The demonstrated materials are (citrate-capped) CaF2 nanoparticles (NPs) doped with Eu3+ or Fe2+/Fe3+ ions. Free electrons generated by ionizing radiation allow the reduction of Eu3+, which produces a very small contrast in MRI, to Eu2+, which induces a strong contrast. Oxidative species generated by high-energy X-rays can be measured indirectly using Fe2+ because it oxidizes to Fe3+, increasing the contrast in MRI. Notably, in the results, a strong increase in the proton relaxation rates is observed for the Eu3+-doped NPs at 40 kV. At 6 MV, a significant increase in proton relaxation rates is observed using CaF2 NPs doped with Fe2+/Fe3+ after irradiation. The presented concept shows great promise for use in the clinic to measure in vivo local ionizing radiation dose, as these CAs can be intravenously injected in a saline solution.

Simulation of acquisition shifts in T2 weighted fluid-attenuated inversion recovery magnetic resonance images to stress test artificial intelligence segmentation networks

Purpose

To provide a simulation framework for routine neuroimaging test data, which allows for "stress testing" of deep segmentation networks against acquisition shifts that commonly occur in clinical practice for T2 weighted (T2w) fluid-attenuated inversion recovery magnetic resonance imaging protocols.

Approach

The approach simulates "acquisition shift derivatives" of MR images based on MR signal equations. Experiments comprise the validation of the simulated images by real MR scans and example stress tests on state-of-the-art multiple sclerosis lesion segmentation networks to explore a generic model function to describe the F1 score in dependence of the contrast-affecting sequence parameters echo time (TE) and inversion time (TI).

Results

The differences between real and simulated images range up to 19% in gray and white matter for extreme parameter settings. For the segmentation networks under test, the F1 score dependency on TE and TI can be well described by quadratic model functions (R 2 > 0.9 ). The coefficients of the model functions indicate that changes of TE have more influence on the model performance than TI.

Conclusions

We show that these deviations are in the range of values as may be caused by erroneous or individual differences in relaxation times as described by literature. The coefficients of the F1 model function allow for a quantitative comparison of the influences of TE and TI. Limitations arise mainly from tissues with a low baseline signal (like cerebrospinal fluid) and when the protocol contains contrast-affecting measures that cannot be modeled due to missing information in the DICOM header.

Cognitive decline in thrombotic thrombocytopenic purpura survivors: The role of white matter health as assessed by MRI

Immune-mediated thrombotic thrombocytopenic purpura (iTTP) is a rare condition caused by severe ADAMTS13 deficiency, leading to platelet aggregation and thrombosis. Despite treatment, patients are prone to cognitive impairment and depression. We investigated brain changes in iTTP patients during remission using advanced magnetic resonance imaging (MRI) techniques, correlating these changes with mood and neurocognitive tests. Twenty iTTP patients in remission (30 days post-haematological remission) were compared with six healthy controls. MRI scans, including standard and specialized sequences, were conducted to assess white matter health. Increased T1 relaxation times were found in the cingulate cortex (p < 0.05), and elevated T2 relaxation times were observed in the cingulate cortex, frontal, parietal and temporal lobes (p < 0.05). Pathological changes in these areas are correlated with impaired cognitive and depressive scores in concentration, short-term memory and verbal memory. This study highlights persistent white matter damage in iTTP patients, potentially contributing to depression and cognitive impairment. Key regions affected include the frontal lobe and cingulate cortex. These findings have significant implications for the acute and long-term management of iTTP, suggesting a need for re-evaluation of treatment approaches during both active phases and remission. Further research is warranted to enhance our understanding of these complexities.

Widespread, depth-dependent cortical microstructure alterations in pediatric focal epilepsy

OBJECTIVE

Tissue abnormalities in focal epilepsy may extend beyond the presumed focus. The underlying pathophysiology of these broader changes is unclear, and it is not known whether they result from ongoing disease processes or treatment-related side effects, or whether they emerge earlier. Few studies have focused on the period of onset for most focal epilepsies, childhood. Fewer still have utilized quantitative magnetic resonance imaging (MRI), which may provide a more sensitive and interpretable measure of tissue microstructural change. Here, we aimed to determine common spatial modes of changes in cortical architecture in children with heterogeneous drug-resistant focal epilepsy and, secondarily, whether changes were related to disease severity.

METHODS

To assess cortical microstructure, quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in 43 children with drug-resistant focal epilepsy (age range = 4-18 years) and 46 typically developing children (age range = 2-18 years). We assessed depth-dependent qT1 and qT2 values across the neocortex, as well as their gradient of change across cortical depths. We also determined whether global changes seen in group analyses were driven by focal pathologies in individual patients. Finally, as a proof-of-concept, we trained a classifier using qT1 and qT2 gradient maps from patients with radiologically defined abnormalities (MRI positive) and healthy controls, and tested whether this could classify patients without reported radiological abnormalities (MRI negative).

RESULTS

We uncovered depth-dependent qT1 and qT2 increases in widespread cortical areas in patients, likely representing microstructural alterations in myelin or gliosis. Changes did not correlate with disease severity measures, suggesting they may represent antecedent neurobiological alterations. Using a classifier trained with MRI-positive patients and controls, sensitivity was 71.4% at 89.4% specificity on held-out MRI-negative patients.

SIGNIFICANCE

These findings suggest the presence of a potential imaging endophenotype of focal epilepsy, detectable irrespective of radiologically identified abnormalities.

Longitudinal analysis of T2 relaxation time variations following radiotherapy for prostate cancer

Aim of this paper is to evaluate short and long-term changes in T 2 relaxation times after radiotherapy in patients with low and intermediate risk localized prostate cancer. A total of 24 patients were selected for this retrospective study. Each participant underwent 1.5T magnetic resonance imaging on seven separate occasions: initially after the implantation of gold fiducials, the required step for Cyberknife therapy guidance, followed by MRI scans two weeks post-therapy and monthly thereafter. As part of each MRI scan, the prostate region was manually delineated, and the T 2 relaxation times were calculated for quantitative analysis. The T 2 relaxation times between individual follow-ups were analyzed using Repeated Measures Analysis of Variance that revealed a significant difference across all measurements (F (6, 120) = 0.611, p << 0.001). A Bonferroni post hoc test revealed significant differences in median T 2 values between the baseline and subsequent measurements, particularly between pre-therapy (M 0 ) and two weeks post-therapy (M 1 ), as well as during the monthly interval checks (M 2 - M 6 ). Some cases showed a delayed decrease in relaxation times, indicating the prolonged effects of therapy. The changes in T 2 values during the course of radiotherapy can help in monitoring radiotherapy response in unconfirmed patients, quantifying the scarring process, and recognizing the therapy failure.

A preliminary study of the effects of an antimuscarinic agent on anxious behaviors and white matter microarchitecture in nonhuman primates

Myelination subserves efficient neuronal communication, and alterations in white matter (WM) microstructure have been implicated in numerous psychiatric disorders, including pathological anxiety. Recent work in rodents suggests that muscarinic antagonists may enhance myelination with behavioral benefits; however, the neural and behavioral effects of muscarinic antagonists have yet to be explored in non-human primates (NHP). Here, as a potentially translatable therapeutic strategy for human pathological anxiety, we present data from a first-in-primate study exploring the effects of the muscarinic receptor antagonist solifenacin on anxious behaviors and WM microstructure. 12 preadolescent rhesus macaques (6 vehicle control, 6 experimental; 8F, 4M) were included in a pre-test/post-test between-group study design. The experimental group received solifenacin succinate for ~60 days. Subjects underwent pre- and post-assessments of: 1) anxious temperament (AT)-related behaviors in the potentially threatening no-eye-contact (NEC) paradigm (30-min); and 2) WM and regional brain metabolism imaging metrics, including diffusion tensor imaging (DTI), quantitative relaxometry (QR), and FDG-PET. In relation to anxiety-related behaviors expressed during the NEC, significant Group (vehicle control vs. solifenacin) by Session (pre vs. post) interactions were found for freezing, cooing, and locomotion. Compared to vehicle controls, solifenacin-treated subjects exhibited effects consistent with reduced anxiety, specifically decreased freezing duration, increased locomotion duration, and increased cooing frequency. Furthermore, the Group-by-Session-by-Sex interaction indicated that these effects occurred predominantly in the males. Exploratory whole-brain voxelwise analyses of post-minus-pre differences in DTI, QR, and FDG-PET metrics revealed some solifenacin-related changes in WM microstructure and brain metabolism. These findings in NHPs support the further investigation of the utility of antimuscarinic agents in targeting WM microstructure as a means to treat pathological anxiety.

MD Simulations to Calculate NMR Relaxation Parameters of Vanadium(IV) Complexes: A Promising Diagnostic Tool for Cancer and Alzheimer's Disease

Early phase diagnosis of human diseases has still been a challenge in the medicinal field, and one of the efficient non-invasive techniques that is vastly used for this purpose is magnetic resonance imaging (MRI). MRI is able to detect a wide range of diseases and conditions, including nervous system disorders and cancer, and uses the principles of NMR relaxation to generate detailed internal images of the body. For such investigation, different metal complexes have been studied as potential MRI contrast agents. With this in mind, this work aims to investigate two systems containing the vanadium complexes [VO(metf)2]·H2O (VC1) and [VO(bpy)2Cl]+ (VC2), being metformin and bipyridine ligands of the respective complexes, with the biological targets AMPK and ULK1. These biomolecules are involved in the progression of Alzheimer's disease and triple-negative breast cancer, respectively, and may act as promising spectroscopic probes for detection of these diseases. To initially evaluate the behavior of the studied ligands within the aforementioned protein active sites and aqueous environment, four classical molecular dynamics (MD) simulations including VC1 + H2O (1), VC2 + H2O (2), VC1 + AMPK + H2O (3), and VC2 + ULK1 + H2O (4) were performed. From this, it was obtained that for both systems containing VCs and water only, the theoretical calculations implied a higher efficiency when compared with DOTAREM, a famous commercially available contrast agent for MRI. This result is maintained when evaluating the system containing VC1 + AMPK + H2O. Nevertheless, for the system VC2 + ULK1 + H2O, there was observed a decrease in the vanadium complex efficiency due to the presence of a relevant steric hindrance. Despite that, due to the nature of the interaction between VC2 and ULK1, and the nature of its ligands, the study gives an insight that some modifications on VC2 structure might improve its efficiency as an MRI probe.

Assessment of white matter hyperintensity severity using multimodal magnetic resonance imaging

White matter hyperintensities are radiological abnormalities reflecting cerebrovascular dysfunction detectable using MRI. White matter hyperintensities are often present in individuals at the later stages of the lifespan and in prodromal stages in the Alzheimer's disease spectrum. Tissue alterations underlying white matter hyperintensities may include demyelination, inflammation and oedema, but these are highly variable by neuroanatomical location and between individuals. There is a crucial need to characterize these white matter hyperintensity tissue alterations in vivo to improve prognosis and, potentially, treatment outcomes. How different MRI measure(s) of tissue microstructure capture clinically-relevant white matter hyperintensity tissue damage is currently unknown. Here, we compared six MRI signal measures sampled within white matter hyperintensities and their associations with multiple clinically-relevant outcomes, consisting of global and cortical brain morphometry, cognitive function, diagnostic and demographic differences and cardiovascular risk factors. We used cross-sectional data from 118 participants: healthy controls (n = 30), individuals at high risk for Alzheimer's disease due to familial history (n = 47), mild cognitive impairment (n = 32) and clinical Alzheimer's disease dementia (n = 9). We sampled the median signal within white matter hyperintensities on weighted MRI images [T1-weighted (T1w), T2-weighted (T2w), T1w/T2w ratio, fluid-attenuated inversion recovery (FLAIR)] as well as the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. qT2* and fluid-attenuated inversion recovery signals within white matter hyperintensities displayed different age- and disease-related trends compared to normal-appearing white matter signals, suggesting sensitivity to white matter hyperintensity-specific tissue deterioration. Further, white matter hyperintensity qT2*, particularly in periventricular and occipital white matter regions, was consistently associated with all types of clinically-relevant outcomes in both univariate and multivariate analyses and across two parcellation schemes. qT1 and fluid-attenuated inversion recovery measures showed consistent clinical relationships in multivariate but not univariate analyses, while T1w, T2w and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to white matter hyperintensities. Our results suggest that combining volumetric and signal measures of white matter hyperintensity should be considered to fully characterize the severity of white matter hyperintensities in vivo. These findings may have implications in determining the reversibility of white matter hyperintensities and the potential efficacy of cardio- and cerebrovascular treatments.

Brain MRI Biomarkers in Isolated Rapid Eye Movement Sleep Behavior Disorder: Where Are We? A Systematic Review

The increasing number of MRI studies focused on prodromal Parkinson's Disease (PD) demonstrates a strong interest in identifying early biomarkers capable of monitoring neurodegeneration. In this systematic review, we present the latest information regarding the most promising MRI markers of neurodegeneration in relation to the most specific prodromal symptoms of PD, namely isolated rapid eye movement (REM) sleep behavior disorder (iRBD). We reviewed structural, diffusion, functional, iron-sensitive, neuro-melanin-sensitive MRI, and proton magnetic resonance spectroscopy studies conducted between 2000 and 2023, which yielded a total of 77 relevant papers. Among these markers, iron and neuromelanin emerged as the most robust and promising indicators for early neurodegenerative processes in iRBD. Atrophy was observed in several regions, including the frontal and temporal cortices, limbic cortices, and basal ganglia, suggesting that neurodegenerative processes had been underway for some time. Diffusion and functional MRI produced heterogeneous yet intriguing results. Additionally, reduced glymphatic clearance function was reported. Technological advancements, such as the development of ultra-high field MRI, have enabled the exploration of minute anatomical structures and the detection of previously undetectable anomalies. The race to achieve early detection of neurodegeneration is well underway.

Lower Myelin Content Is Associated With Lower Gait Speed in Cognitively Unimpaired Adults

Mounting evidence indicates that abnormal gait speed predicts the progression of neurodegenerative diseases, including Alzheimer's disease. Understanding the relationship between white matter integrity, especially myelination, and motor function is crucial to the diagnosis and treatment of neurodegenerative diseases. We recruited 118 cognitively unimpaired adults across an extended age range of 22-94 years to examine associations between rapid or usual gait speeds and cerebral myelin content. Using our advanced multicomponent magnetic resonance relaxometry method, we measured myelin water fraction (MWF), a direct measure of myelin content, as well as longitudinal and transverse relaxation rates (R1 and R2), sensitive but nonspecific magnetic resonance imaging measures of myelin content. After adjusting for covariates and excluding 22 data sets due to cognitive impairments or artifacts, our results indicate that participants with higher rapid gait speed exhibited higher MWF, R1, and R2 values, that is, higher myelin content. These associations were statistically significant within several white matter brain regions, particularly the frontal and parietal lobes, splenium, anterior corona radiata, and superior fronto-occipital and longitudinal fasciculus. In contrast, we did not find any significant associations between usual gait speed and MWF, R1, or R2, which suggests that rapid gait speed may be a more sensitive marker of demyelination than usual gait speed. These findings advance our understanding on the implication of myelination in gait impairment among cognitively unimpaired adults, providing further evidence of the interconnection between white matter integrity and motor function.

Evidence of An Association Between Cerebral Blood Flow and Microstructural Integrity in Normative Aging Using a Holistic MRI Approach

BACKGROUND

Cerebral tissue integrity decline and cerebral blood flow (CBF) alteration are major aspects of motor and cognitive dysfunctions and neurodegeneration. However, little is known about the association between blood flow and brain microstructural integrity, especially in normal aging.

PURPOSE

To assess the association between CBF and cerebral microstructural integrity.

STUDY TYPE

Cross sectional.

POPULATION

A total of 94 cognitively unimpaired adults (mean age 50.7 years, age range between 22 and 88 years, 56 Men).

FIELD STRENGTH/SEQUENCE

A 3 T; pseudo-continuous arterial spin labeling (pCASL), diffusion tensor imaging (DTI), Bayesian Monte Carlo analysis of multicomponent driven equilibrium steady-state observation of T1 and T2 (BMC-mcDESPOT).

ASSESSMENT

Lobar associations between CBF derived from pCASL, and longitudinal relaxation rate (R1 ), transverse relaxation rate (R2 ) and myelin water fraction (MWF) derived from BMC-mcDESPOT, or radial diffusivity (RD), axial diffusivity (AxD), mean diffusivity (MD) and fractional anisotropy (FA) derived from DTI were assessed.

STATISTICAL TESTS

Multiple linear regression models were used using the mean region of interest (ROI) values for MWF, R1 , R2 , FA, MD, RD, or AxD as the dependent variable and CBF, age, age2 , and sex as the independent variables. A two-sided P value of <0.05 defined statistical significance.

RESULTS

R1 , R2 , MWF, FA, MD, RD, and AxD parameters were associated with CBF in most of the cerebral regions evaluated. Specifically, higher CBF values were significantly associated with higher FA, MWF, R1 and R2 , or lower MD, RD and AxD values.

DATA CONCLUSION

These findings suggest that cerebral tissue microstructure may be impacted by global brain perfusion, adding further evidence to the intimate relationship between cerebral blood supply and cerebral tissue integrity.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 4.

Lower myelin content is associated with more rapid cognitive decline among cognitively unimpaired individuals

INTRODUCTION

The influence of myelination on longitudinal changes in cognitive performance remains unclear.

METHODS

For each participant (N = 123), longitudinal cognitive scores were calculated. Myelin content was probed using myelin water fraction (MWF) or longitudinal relaxation rate (R1 ); both are MRI measures sensitive to myelin, with MWF being specific.

RESULTS

Lower MWF was associated with steeper declines in executive function (p < .02 in all regions) and lower R1 was associated with steeper declines in verbal fluency (p < .03 in all regions). Additionally, lower R1 was associated with steeper declines in executive function (p < .02 in all regions) and memory (p < .04 in occipital and cerebral white matter) but did not survive Bonferroni correction.

DISCUSSION

We demonstrate significant relationships between myelin content and the rates of change in cognitive performance among cognitively normal individuals. These findings highlight the importance of myelin in cognitive functioning and suggest MWF and R1 as imaging biomarkers to predict cognitive changes.

Cortical Structure Differences in Relation to Age, Sexual Attractions, and Gender Dysphoria in Adolescents: An Examination of Mean Diffusivity and T1 Relaxation Time

Recent research found that the combination of masculine gender identity and gynephilia was associated with cortical T1 relaxation time, which is considered to reflect gray matter density. We hypothesized that mean diffusivity (MD), a diffusion tensor imaging metric that reflects the degree to which water movement is free versus constrained, in combination with T1 relaxation time would provide further insight regarding cortical tissue characteristics. MD and T1 relaxation time were measured in 76 cortical regions in 15 adolescents assigned female at birth who experience gender dysphoria (GD AFAB) and were not receiving hormone therapy, 17 cisgender girls, and 14 cisgender boys (ages 12-17 years). Sexual orientation was represented by the degree of androphilia-gynephilia and the strength of sexual attraction. In multivariate analyses, cortical T1 relaxation time showed a weak but statistically significant positive association with MD across the cortex, suggesting that macromolecule-rich cortical tissue also tends to show water movement that is somewhat more constrained. In further multivariate analyses, in several left frontal, parietal, and temporal regions, the combination of shorter T1 relaxation time and faster MD was associated with older age and greater gynephilia in GD AFAB individuals and cisgender boys and with stronger attractions in cisgender boys only. Thus, for these cortical regions in these groups, older age, gynephilia, and stronger attractions (cisgender boys only) were associated with macromolecule-rich tissue in which water movement was freer-a pattern that some prior research suggests is associated with greater cell density and size. Overall, this study indicates that investigating T1 relaxation time and MD together can further inform how cortical gray matter tissue characteristics relate to age and psychosexuality.

Cartesian vs radial MR-STAT: An efficiency and robustness study

MR Spin TomogrAphy in Time-domain ("MR-STAT") is quantitative MR technique in which multiple quantitative parameters are estimated from a single short scan by solving a large-scale non-linear optimization problem. In this work we extended the MR-STAT framework to non-Cartesian gradient trajectories. Cartesian MR-STAT and radial MR-STAT were compared in terms of time-efficiency and robustness in simulations, gel phantom measurements and in vivo measurements. In simulations, we observed that both Cartesian and radial MR-STAT are highly robust against undersampling. Radial MR-STAT does have a lower spatial encoding power because the outer corners of k-space are never sampled. However, especially in T2, this is compensated by a higher dynamic encoding power that comes from sampling the k-space center with each readout. In gel phantom measurements, Cartesian MR-STAT was observed to be robust against overfitting whereas radial MR-STAT suffered from high-frequency artefacts in the parameter maps at later iterations. These artefacts are hypothesized to be related to hardware imperfections and were (partially) suppressed with image filters. The time-efficiencies were higher for Cartesian MR-STAT in all vials. In-vivo, the radial reconstruction again suffered from overfitting artefacts. The robustness of Cartesian MR-STAT over the entire range of experiments may make it preferable in a clinical setting, despite radial MR-STAT resulting in a higher T1 time-efficiency in white matter.

T1 relaxation time is prolonged in healthy aging: a whole brain study

BACKGROUND

: Measurement of tissue characteristics such as the longitudinal relaxation time (T1) provides complementary information to the volumetric and surface based structural analyses. We aimed to investigate T1 relaxation time characteristics in healthy aging via an exploratory design in the whole brain. The data processing pipeline was designed to minimize errors related to aging effects such as atrophy.

METHODS

Sixty healthy participants underwent MRI scanning (28 F, 32 M, age range: 18-78, 30 young and 30 old) in November 2017-March 2018 at the Bilkent University UMRAM Center. Four images with varying flip angles with FLASH (fast low angle shot magnetic resonance imaging) sequence and a high-resolution structural image with MP-RAGE (Magnetization Prepared - RApid Gradient Echo) were acquired. T1 relaxation times of the entire brain were mapped by using the region of interest (ROI) based method on 134 brain areas in young and old populations.

RESULTS

T1 prolongation was observed in various subcortical (bilateral hippocampus, caudate and thalamus) and cortical brain structures (bilateral precentral gyrus, bilateral middle frontal gyrus, bilateral supplementary motor area (SMA), left middle occipital gyrus, bilateral postcentral gyrus and bilateral Heschl's gyrus) as well as cerebellar regions (GM regions of cerebellum: bilateral cerebellum III, cerebellum IV V, cerebellum X, cerebellar vermis u 4 5, cerebellar vermis u 9 and WM cerebellar regions: left cerebellum IX, bilateral cerebellum X and cerebellar vermis u 4 5).

DISCUSSION

T1 mapping provides a practical quantitative MRI (qMRI) methodology for studying the tissue characteristics in healthy aging. T1 values are significantly increased in the aging group among half of the studied ROIs (57 ROIs out of 134).

Submillimeter T1 atlas for subject-specific abnormality detection at 7T

PURPOSE

Studies at 3T have shown that T₁ relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T₁ values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T.

METHODS

T₁ maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template-based brain segmentation algorithm was adapted to ultra-high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T₁ values was established by modeling the T₁ inter-subject variability. A method for single-subject comparisons restricted to white matter and subcortical structures was developed by computing Z-scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept.

RESULTS

The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single-subject comparisons at 7T, and showed greater anatomical details compared with 3T results.

CONCLUSION

A high-resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high-resolution single-subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice.

Novel 3D magnetic resonance fingerprinting radiomics in adult brain tumors: a feasibility study

OBJECTIVES

To test the feasibility of using 3D MRF maps with radiomics analysis and machine learning in the characterization of adult brain intra-axial neoplasms.

METHODS

3D MRF acquisition was performed on 78 patients with newly diagnosed brain tumors including 33 glioblastomas (grade IV), 6 grade III gliomas, 12 grade II gliomas, and 27 patients with brain metastases. Regions of enhancing tumor, non-enhancing tumor, and peritumoral edema were segmented and radiomics analysis with gray-level co-occurrence matrices and gray-level run-length matrices was performed. Statistical analysis was performed to identify features capable of differentiating tumors based on type, grade, and isocitrate dehydrogenase (IDH1) status. Receiver operating curve analysis was performed and the area under the curve (AUC) was calculated for tumor classification and grading. For gliomas, Kaplan-Meier analysis for overall survival was performed using MRF T1 features from enhancing tumor region.

RESULTS

Multiple MRF T1 and T2 features from enhancing tumor region were capable of differentiating glioblastomas from brain metastases. Although no differences were identified between grade 2 and grade 3 gliomas, differentiation between grade 2 and grade 4 gliomas as well as between grade 3 and grade 4 gliomas was achieved. MRF radiomics features were also able to differentiate IDH1 mutant from the wild-type gliomas. Radiomics T1 features for enhancing tumor region in gliomas correlated to overall survival (p < 0.05).

CONCLUSION

Radiomics analysis of 3D MRF maps allows differentiating glioblastomas from metastases and is capable of differentiating glioblastomas from metastases and characterizing gliomas based on grade, IDH1 status, and survival.

KEY POINTS

• 3D MRF data analysis using radiomics offers novel tissue characterization of brain tumors. • 3D MRF with radiomics offers glioma characterization based on grade, IDH1 status, and overall patient survival.

White matter microstructure and longitudinal relaxation time anisotropy in human brain at 3 and 7 T

A high degree of structural order by white matter (WM) fibre tracts creates a physicochemical environment where water relaxations are rendered anisotropic. Recently, angularly dependent longitudinal relaxation has been reported in human WM. We have characterised interrelationships between T1 relaxation and diffusion MRI microstructural indices at 3 and 7 T. Eleven volunteers consented to participate in the study. Multishell diffusion MR images were acquired with b-values of 0/1500/3000 and 0/1000/2000 s/mm² at 1.5 and 1.05 mm³ isotropic resolutions at 3 and 7 T, respectively. DTIFIT was used to compute DTI indices; the fibre-to-field angle (θ_FB ) maps were obtained using the principal eigenvector images. The orientations and volume fractions of multiple fibre populations were estimated using BedpostX in FSL, and the orientation dispersion index (ODI) was estimated using the NODDI protocol. MP2RAGE was used to acquire images for T1 maps at 1.0 and 0.9 mm³ isotropic resolutions at 3 and 7 T, respectively. At 3 T, T1 as a function of θ_FB in WM with high fractional anisotropy and one-fibre orientation volume fraction or low ODI shows a broad peak centred at 50^o , but a flat baseline at 0^o and 90^o . The broad peak amounted up to 7% of the mean T1. At 7 T, the broad peak appeared at 40^o and T1 in fibres running parallel to B0 was longer by up to 75 ms (8.3% of the mean T1) than in those perpendicular to the field. The peak at 40^o was approximately 5% of mean T1 (i.e., proportionally smaller than that at 54^o at 3 T). The data demonstrate T1 anisotropy in WM with high microstructural order at both fields. The angular patterns are indicative of the B0-dependency of T1 anisotropy. Thus myelinated WM fibres influence T1 contrast both by acting as a T1 contrast agent and rendering T1 dependent on fibre orientation with B0.

Brainstem white matter microstructure is associated with hyporesponsiveness and overall sensory features in autistic children

BACKGROUND

Elevated or reduced responses to sensory stimuli, known as sensory features, are common in autistic individuals and often impact quality of life. Little is known about the neurobiological basis of sensory features in autistic children. However, the brainstem may offer critical insights as it has been associated with both basic sensory processing and core features of autism.

METHODS

Diffusion-weighted imaging (DWI) and parent-report of sensory features were acquired from 133 children (61 autistic children with and 72 non-autistic children, 6-11 years-old). Leveraging novel DWI processing techniques, we investigated the relationship between sensory features and white matter microstructure properties (free-water-elimination-corrected fractional anisotropy [FA] and mean diffusivity [MD]) in precisely delineated brainstem white matter tracts. Follow-up analyses assessed relationships between microstructure and sensory response patterns/modalities and analyzed whole brain white matter using voxel-based analysis.

RESULTS

Results revealed distinct relationships between brainstem microstructure and sensory features in autistic children compared to non-autistic children. In autistic children, more prominent sensory features were generally associated with lower MD. Further, in autistic children, sensory hyporesponsiveness and tactile responsivity were strongly associated with white matter microstructure in nearly all brainstem tracts. Follow-up voxel-based analyses confirmed that these relationships were more prominent in the brainstem/cerebellum, with additional sensory-brain findings in the autistic group in the white matter of the primary motor and somatosensory cortices, the occipital lobe, the inferior parietal lobe, and the thalamic projections.

LIMITATIONS

All participants communicated via spoken language and acclimated to the sensory environment of an MRI session, which should be considered when assessing the generalizability of this work to the whole of the autism spectrum.

CONCLUSIONS

These findings suggest unique brainstem white matter contributions to sensory features in autistic children compared to non-autistic children. The brainstem correlates of sensory features underscore the potential reflex-like nature of behavioral responses to sensory stimuli in autism and have implications for how we conceptualize and address sensory features in autistic populations.

Pre-contrast MAGiC in treated gliomas: a pilot study of quantitative MRI

Quantitative MR imaging is becoming more feasible to be used in clinical work since new approaches have been proposed in order to substantially accelerate the acquisition and due to the possibility of synthetically deriving weighted images from the parametric maps. However, their applicability has to be thoroughly validated in order to be included in clinical practice. In this pilot study, we acquired Magnetic Resonance Image Compilation scans to obtain T1, T2 and PD maps in 14 glioma patients. Abnormal tissue was segmented based on conventional images and using a deep learning segmentation technique to define regions of interest (ROIs). The quantitative T1, T2 and PD values inside ROIs were analyzed using the mean, the standard deviation, the skewness and the kurtosis and compared to the quantitative T1, T2 and PD values found in normal white matter. We found significant differences in pre-contrast T1 and T2 values between abnormal tissue and healthy tissue, as well as between T1w-enhancing and non-enhancing regions. ROC analysis was used to evaluate the potential of quantitative T1 and T2 values for voxel-wise classification of abnormal/normal tissue (AUC = 0.95) and of T1w enhancement/non-enhancement (AUC = 0.85). A cross-validated ROC analysis found high sensitivity (73%) and specificity (73%) with AUCs up to 0.68 on the a priori distinction between abnormal tissue with and without T1w-enhancement. These results suggest that normal tissue, abnormal tissue, and tissue with T1w-enhancement are distinguishable by their pre-contrast quantitative values but further investigation is needed.

Protocol for a multicenter, double-blinded placebo-controlled randomized controlled trial comparing intravenous ferric derisomaltose to oral ferrous sulfate for the treatment of iron deficiency anemia in pregnancy: The IVIDA2 trial

BACKGROUND

Iron deficiency anemia (IDA) is common during pregnancy and associated with adverse maternal and neonatal outcomes. Treatment with iron supplementation is recommended during pregnancy, but the optimal delivery route is unclear. Oral iron risks has high risk of gastrointestinal side effects and low absorption. Intravenous iron is infused directly but is expensive. The American College of Obstetricians and Gynecologists currently recommends oral iron to treat IDA in pregnancy with intravenous iron reserved as second-line therapy, if needed. This approach is associated with persistent anemia, increasing the risk of peripartum blood transfusion. We aim to provide data on optimal route of iron repletion for IDA in pregnancy.

METHODS

In IVIDA2, a double-blind, placebo controlled, multicenter randomized trial in the United States, 746 pregnant people with moderate-to-severe IDA (hemoglobin <10 g/dL and ferritin <30 ng/mL) at 24-28 weeks' gestation will be randomized 1:1 to either a single 1000 mg dose of intravenous ferric derisomaltose and oral placebo (1-3 times daily) or a single placebo infusion with 1-3 times daily 325 mg ferrous sulfate (65 mg elemental iron) tablet. The primary outcome is peripartum blood transfusion (blood transfusion from delivery to 7 days postpartum). Secondary outcomes include adverse medication reactions, maternal and neonatal hematologic indices, and offspring neurodevelopment.

ETHICS AND DISSEMINATION

A central ethical review board-Advarra-granted ethical approval (Pro00060930). Participating centers-Women & Infants Hospital of Rhode Island, University of Michigan Medical Center, Washington University School of Ethics and dissemination: A central ethical review board-Advarra-granted ethical approval (Pro00060930). Participating centers-Women & Infants Hospital of Rhode Island, University of Michigan Medical Center, Washington University School of.

Iron- and Neuromelanin-Weighted Neuroimaging to Study Mitochondrial Dysfunction in Patients with Parkinson's Disease

The underlying causes of Parkinson's disease are complex, and besides recent advances in elucidating relevant disease mechanisms, no disease-modifying treatments are currently available. One proposed pathophysiological hallmark is mitochondrial dysfunction, and a plethora of evidence points toward the interconnected nature of mitochondria in neuronal homeostasis. This also extends to iron and neuromelanin metabolism, two biochemical processes highly relevant to individual disease manifestation and progression. Modern neuroimaging methods help to gain in vivo insights into these intertwined pathways and may pave the road to individualized medicine in this debilitating disorder. In this narrative review, we will highlight the biological rationale for studying these pathways, how distinct neuroimaging methods can be applied in patients, their respective limitations, and which challenges need to be overcome for successful implementation in clinical studies.

Quantitative MRI of chronic pancreatitis: results from a multi-institutional prospective study, magnetic resonance imaging as a non-invasive method for assessment of pancreatic fibrosis (MINIMAP)

PURPOSE

To determine if quantitative MRI techniques can be helpful to evaluate chronic pancreatitis (CP) in a setting of multi-institutional study.

METHODS

This study included a subgroup of participants (n = 101) enrolled in the Prospective Evaluation of Chronic Pancreatitis for Epidemiologic and Translational Studies (PROCEED) study (NCT03099850) from February 2019 to May 2021. MRI was performed on 1.5 T using Siemens and GE scanners at seven clinical centers across the USA. Quantitative MRI parameters of the pancreas included T1 relaxation time, extracellular volume (ECV) fraction, apparent diffusion coefficient (ADC), and fat signal fraction. We report the diagnostic performance and mean values within the control (n = 50) and CP (n = 51) groups. The T1, ECV and fat signal fraction were combined to generate the quantitative MRI score (Q-MRI).

RESULTS

There was significantly higher T1 relaxation time; mean 669 ms (± 171) vs. 593 ms (± 82) (p = 0.006), ECV fraction; 40.2% (± 14.7) vs. 30.3% (± 11.9) (p < 0.001), and pancreatic fat signal fraction; 12.2% (± 5.5) vs. 8.2% (± 4.4) (p < 0.001) in the CP group compared to controls. The ADC was similar between groups (p = 0.45). The AUCs for the T1, ECV, and pancreatic fat signal fraction were 0.62, 0.72, and 0.73, respectively. The composite Q-MRI score improved the diagnostic performance (cross-validated AUC: 0.76).

CONCLUSION

Quantitative MR parameters evaluating the pancreatic parenchyma (T1, ECV fraction, and fat signal fraction) are helpful in the diagnosis of CP. A Q-MRI score that combines these three MR parameters improves diagnostic performance. Further studies are warranted with larger study populations including patients with acute and recurrent acute pancreatitis and longitudinal follow-ups.

Relaxometry and brain myelin quantification with synthetic MRI in MS subtypes and their associations with spinal cord atrophy

Immune-mediated demyelination and neurodegeneration are pathophysiological hallmarks of Multiple Sclerosis (MS) and main drivers of disease related disability. The principal method for evaluating qualitatively demyelinating events in the clinical context is contrast-weighted magnetic resonance imaging (MRI). Moreover, advanced MRI sequences provide reliable quantification of brain myelin offering new opportunities to study tissue pathology in vivo. Towards neurodegenerative aspects of the disease, spinal cord atrophy - besides brain atrophy - is a powerful and validated predictor of disease progression. The etiology of spinal cord volume loss is still a matter of research, as it remains unclear whether the impact of local lesion pathology or the interaction with supra- and infratentorial axonal degeneration and demyelination of the long descending and ascending fiber tracts are the determining factors. Quantitative synthetic MR using a multiecho acquisition of saturation recovery pulse sequence provides fast automatic brain tissue and myelin volumetry based on R1 and R2 relaxation rates and proton density quantification, making it a promising modality for application in the clinical routine. In this cross sectional study a total of 91 MS patients and 31 control subjects were included to investigate group differences of global and regional measures of brain myelin and relaxation rates, in different MS subtypes, using QRAPMASTER sequence and SyMRI postprocessing software. Furthermore, we examined associations between these quantitative brain parameters and spinal cord atrophy to draw conclusions about possible pathophysiological relationships. Intracranial myelin volume fraction of the global brain exhibited statistically significant differences between control subjects (10.4%) and MS patients (RRMS 9.4%, PMS 8.1%). In a LASSO regression analysis with total brain lesion load, intracranial myelin volume fraction and brain parenchymal fraction, the intracranial myelin volume fraction was the variable with the highest impact on spinal cord atrophy (standardized coefficient 4.52). Regional supratentorial MRI metrics showed altered average myelin volume fraction, R1, R2 and proton density in MS patients compared to controls most pronounced in PMS. Interestingly, quantitative MRI parameters in supratentorial regions showed strong associations with upper cord atrophy, suggesting an important role of brain diffuse demyelination on spinal cord pathology possibly in the context of global disease activity. R1, R2 or proton density of the thalamus, cerebellum and brainstem correlated with upper cervical cord atrophy, probably reflecting the direct functional connection between these brain structures and the spinal cord as well as the effects of retrograde and anterograde axonal degeneration. By using Synthetic MR-derived myelin volume fraction, we were able to effectively detect significant differences of myelination in relapsing and progressive MS subtypes. Total intracranial brain myelin volume fraction seemed to predict spinal cord volume loss better than brain atrophy or total lesion load. Furthermore, demyelination in highly myelinated supratentorial regions, as an indicator of diffuse disease activity, as well as alterations of relaxation parameters in adjacent infratentorial and midbrain areas were strongly associated with upper cervical cord atrophy.

Qualitative and Quantitative Performance of Magnetic Resonance Image Compilation (MAGiC) Method: An Exploratory Analysis for Head and Neck Imaging

The present exploratory study investigates the performance of a new, rapid, synthetic MRI method for diagnostic image quality assessment and measurement of relaxometry metric values in head and neck (HN) tumors and normal-appearing masseter muscle. The multi-dynamic multi-echo (MDME) sequence was used for data acquisition, followed by synthetic image reconstruction on a 3T MRI scanner for 14 patients (3 untreated and 11 treated). The MDME enables absolute quantification of physical tissue properties, including T1 and T2, with a shorter scan time than the current state-of-the-art methods used for relaxation measurements. The vendor termed the combined package MAGnetic resonance imaging Compilation (MAGiC). In total, 48 regions of interest (ROIs) were analyzed, drawn on normal-appearing masseter muscle and tumors in the HN region. Mean T1 and T2 values obtained from normal-appearing muscle were 880 ± 52 ms and 46 ± 3 ms, respectively. Mean T1 and T2 values obtained from tumors were 1930 ± 422 ms and 77 ± 13 ms, respectively, for the untreated group, 1745 ± 410 ms and 107 ± 61 ms, for the treated group. A total of 1552 images from both synthetic MRI and conventional clinical imaging were assessed by the radiologists to provide the rating for T1w and T2w image contrasts. The synthetically generated qualitative T2w images were acceptable and comparable to conventional diagnostic images (93% acceptability rating for both). The acceptability ratings for MAGiC-generated T1w, and conventional images were 64% and 100%, respectively. The benefit of MAGiC in HN imaging is twofold, providing relaxometry maps in a clinically feasible time and the ability to generate a different combination of contrast images in a single acquisition.

Data-driven myelin water imaging based on T1 and T2 relaxometry

Long acquisition times preclude the application of multiecho spin echo (MESE) sequences for myelin water fraction (MWF) mapping in daily clinical practice. In search of alternative methods, previous studies of interest explored the biophysical modeling of MWF from measurements of different tissue properties that can be obtained in scan times shorter than those required for the MESE. In this work, a novel data-driven estimation of MWF maps from fast relaxometry measurements is proposed and investigated. T₁ and T₂ relaxometry maps were acquired in a cohort of 20 healthy subjects along with a conventional MESE sequence. Whole-brain quantitative mapping was achieved with a fast protocol in 6 min 24 s. Reference MWF maps were derived from the MESE sequence (TA = 11 min 17 s) and their data-driven estimation from relaxometry measurements was investigated using three different modeling strategies: two general linear models (GLMs) with linear and quadratic regressors, respectively; a random forest regression model; and two deep neural network architectures, a U-Net and a conditional generative adversarial network (cGAN). Models were validated using a 10-fold crossvalidation. The resulting maps were visually and quantitatively compared by computing the root mean squared error (RMSE) between the estimated and reference MWF maps, the intraclass correlation coefficients (ICCs) between corresponding MWF values in different brain regions, and by performing Bland-Altman analysis. Qualitatively, the estimated maps appear to generally provide a similar, yet more blurred MWF contrast in comparison with the reference, with the cGAN model best capturing MWF variabilities in small structures. By estimating the average adjusted coefficient of determination of the GLM with quadratic regressors, we showed that 87% of the variability in the MWF values can be explained by relaxation times alone. Further quantitative analysis showed an average RMSE smaller than 0.1% for all methods. The ICC was greater than 0.81 for all methods, and the bias smaller than 2.19%. It was concluded that this work confirms the notion that relaxometry parameters contain a large part of the information on myelin water and that MWF maps can be generated from T₁ /T₂ data with minimal error. Among the investigated modeling approaches, the cGAN provided maps with the best trade-off between accuracy and blurriness. Fast relaxometry, like the 6 min 24 s whole-brain protocol used in this work in conjunction with machine learning, may thus have the potential to replace time-consuming MESE acquisitions.

A Magnetic Resonance-Relaxometry-Based Technique to Identify Blood Products in Brain Parenchyma: An Experimental Study on a Rabbit Model

Magnetic resonance relaxometry is a quantitative technique that estimates T1/T2 tissue relaxation times. This has been proven to increase MRI diagnostic accuracy of brain disorders in human medicine. However, literature in the veterinary field is scarce. In this work, a T1 and T2-based relaxometry approach has been developed. The aim is to investigate its performance in characterizing subtle brain lesions obtained with autologous blood injections in rabbits. This study was performed with a low-field scanner, typically present in veterinary clinics. The approach consisted of a semi-automatic hierarchical classification of different regions, selected from a T2 map. The classification was driven according to the relaxometry properties extracted from a set of regions selected by the radiologist to compare the suspected lesion with the healthy parenchyma. Histopathological analyses were performed to estimate the performance of the proposed classifier through receiver operating characteristic curve analyses. The classifier resulted in moderate accuracy in terms of lesion characterization.

Longitudinal assessment of early-life white matter development with quantitative relaxometry in nonhuman primates

Alterations in white matter (WM) development are associated with many neuropsychiatric and neurodevelopmental disorders. Most MRI studies examining WM development employ diffusion tensor imaging (DTI), which relies on estimating diffusion patterns of water molecules as a reflection of WM microstructure. Quantitative relaxometry, an alternative method for characterizing WM microstructural changes, is based on molecular interactions associated with the magnetic relaxation of protons. In a longitudinal study of 34 infant non-human primates (NHP) (Macaca mulatta) across the first year of life, we implement a novel, high-resolution, T1-weighted MPnRAGE sequence to examine WM trajectories of the longitudinal relaxation rate (qR1) in relation to DTI metrics and gestational age at scan. To the best of our knowledge, this is the first study to assess developmental WM trajectories in NHPs using quantitative relaxometry and the first to directly compare DTI and relaxometry metrics during infancy. We demonstrate that qR1 exhibits robust logarithmic growth, unfolding in a posterior-anterior and medial-lateral fashion, similar to DTI metrics. On a within-subject level, DTI metrics and qR1 are highly correlated, but are largely unrelated on a between-subject level. Unlike DTI metrics, gestational age at birth (time in utero) is a strong predictor of early postnatal qR1 levels. Whereas individual differences in DTI metrics are maintained across the first year of life, this is not the case for qR1. These results point to the similarities and differences in using quantitative relaxometry and DTI in developmental studies, providing a basis for future studies to characterize the unique processes that these measures reflect at the cellular and molecular level.

Rapid MR relaxometry using deep learning: An overview of current techniques and emerging trends

Quantitative mapping of MR tissue parameters such as the spin-lattice relaxation time (T1 ), the spin-spin relaxation time (T2 ), and the spin-lattice relaxation in the rotating frame (T1ρ ), referred to as MR relaxometry in general, has demonstrated improved assessment in a wide range of clinical applications. Compared with conventional contrast-weighted (eg T1 -, T2 -, or T1ρ -weighted) MRI, MR relaxometry provides increased sensitivity to pathologies and delivers important information that can be more specific to tissue composition and microenvironment. The rise of deep learning in the past several years has been revolutionizing many aspects of MRI research, including image reconstruction, image analysis, and disease diagnosis and prognosis. Although deep learning has also shown great potential for MR relaxometry and quantitative MRI in general, this research direction has been much less explored to date. The goal of this paper is to discuss the applications of deep learning for rapid MR relaxometry and to review emerging deep-learning-based techniques that can be applied to improve MR relaxometry in terms of imaging speed, image quality, and quantification robustness. The paper is comprised of an introduction and four more sections. Section 2 describes a summary of the imaging models of quantitative MR relaxometry. In Section 3, we review existing "classical" methods for accelerating MR relaxometry, including state-of-the-art spatiotemporal acceleration techniques, model-based reconstruction methods, and efficient parameter generation approaches. Section 4 then presents how deep learning can be used to improve MR relaxometry and how it is linked to conventional techniques. The final section concludes the review by discussing the promise and existing challenges of deep learning for rapid MR relaxometry and potential solutions to address these challenges.

Differential associations between apolipoprotein E alleles and cerebral myelin content in normative aging

Mounting evidence indicates that myelin breakdown may represent an early phenomenon in neurodegeneration, including Alzheimer's disease (AD). Understanding the factors influencing myelin synthesis and breakdown will be essential for the development and evaluation of therapeutic interventions. In this work, we assessed associations between genetic variance in apolipoprotein E (APOE) and cerebral myelin content. Quantitative magnetic resonance imaging (qMRI) was performed on a cohort of 92 cognitively unimpaired adults ranging in age from 24 to 94 years. We measured whole-brain myelin water fraction (MWF), a direct measure of myelin content, as well as longitudinal and transverse relaxation rates (R₁ and R₂), sensitive measures of myelin content, in carriers of the APOE ε4 or APOE ε2 alleles and individuals with the ε33 genotype. Automated brain mapping algorithms and statistical models were used to evaluate the relationships between MWF or relaxation rates and APOE isoforms, accounting for confounding variables including age, sex, and race, in several cerebral structures. Our results indicate that carriers of APOE ε2 exhibited significantly higher myelin content, that is, higher MWF, R₁ or R₂ values, in most brain regions investigated as compared to noncarriers, while ε4 carriers exhibited trends toward lower myelin content compared to noncarriers. Finally, all qMRI metrics exhibited quadratic, inverted U-shape, associations with age; attributed to the development of myelination from young to middle age followed by progressive loss of myelin afterwards. Sex and race effects on myelination were, overall, nonsignificant. These findings suggest that individual genetic background may influence cerebral myelin maintenance. Although preliminary, this work lays the foundation for further investigations to clarify the relationship between APOE genotype and myelination, which may suggest potential targets in treatment or prevention of AD.

Multimodal Investigation of Neuroinflammation in Aviremic Patients With HIV on Antiretroviral Therapy and HIV Elite Controllers

BACKGROUND AND OBJECTIVES

The presence of HIV in the CNS has been related to chronic immune activation and cognitive dysfunction. The aim of this work was to investigate (1) the presence of neuroinflammation in aviremic people with HIV (PWH) on therapy and in nontreated aviremic PWH (elite controllers [ECs]) using a translocator protein 18 kDa radioligand; (2) the relationship between neuroinflammation and cognitive function in aviremic PWH; and (3) the relationship between [¹¹C]-PBR28 signal and quantitative MRI (qMRI) measures of brain tissue integrity such as T1 and T2 relaxation times (rts).

METHODS

[¹¹C]-PBR28 (standard uptake value ratio, SUVR) images were generated in 36 participants (14 PWH, 6 ECs, and 16 healthy controls) using a statistically defined pseudoreference region. Group comparisons of [¹¹C]-PBR28 SUVR were performed using region of interest-based and voxelwise analyses. The relationship between inflammation, qMRI measures, and cognitive function was studied.

RESULTS

In region of interest analyses, ECs exhibited significantly lower [¹¹C]-PBR28 signal in the thalamus, putamen, superior temporal gyrus, prefrontal cortex, and cerebellum compared with the PWH. In voxelwise analyses, differences were observed in the thalamus, precuneus cortex, inferior temporal gyrus, occipital cortex, cerebellum, and white matter (WM). [¹¹C]-PBR28 signal in the WM and superior temporal gyrus was related to processing speed and selective attention in PWH. In a subset of PWH (n = 12), [¹¹C]-PBR28 signal in the thalamus and WM regions was related to a decrease in T2 rt and to an increase in T1 rt suggesting a colocalization of increased glial metabolism, decrease in microstructural integrity, and iron accumulation.

DISCUSSION

This study casts a new light onto the role of neuroinflammation and related microstructural alterations of HIV infection in the CNS and shows that ECs suppress neuroinflammation more effectively than PWH on therapy.

Differences in the choroid plexus volume and microstructure are associated with body adiposity

The choroid plexus (CP) is a cerebral structure located in the ventricles that functions in producing most of the brain's cerebrospinal fluid (CSF) and transporting proteins and immune cells. Alterations in CP structure and function has been implicated in several pathologies including aging, multiple sclerosis, Alzheimer's disease, and stroke. However, identification of changes in the CP remains poorly characterized in obesity, one of the main risk factors of neurodegeneration, including in the absence of frank central nervous system alterations. Our goal here was to characterize the association between obesity, measured by the body mass index (BMI) or waist circumference (WC) metrics, and CP microstructure and volume, assessed using advanced magnetic resonance imaging (MRI) methodology. This cross-sectional study was performed in the clinical unit of the National Institute on Aging and included a participant population of 123 cognitively unimpaired individuals spanning the age range of 22 - 94 years. Automated segmentation methods from FreeSurfer were used to identify the CP structure. Our analysis included volumetric measurements, quantitative relaxometry measures (T ₁ and T ₂), and the diffusion tensor imaging (DTI) measure of mean diffusivity (MD). Strong positive associations were observed between WC and all MRI metrics, as well as CP volume. When comparing groups based on the established cutoff point by the National Institutes of Health for WC, a modest difference in MD and a significant difference in T ₁ values were observed between obese and lean individuals. We also found differences in T1 and MD between obese and overweight individuals as defined using the BMI cutoff. We conjecture that these observations in CP volume and microstructure are due to obesity-induced inflammation, diet, or, very likely, dysregulations in leptin binding and transport. These findings demonstrate that obesity is strongly associated with a decline in CP microstructural integrity. We expect that this work will lay the foundation for further investigations on obesity-induced alterations in CP structure and function.

Quantitative MRI Evidence for Cognitive Reserve in Healthy Elders and Prodromal Alzheimer's Disease

BACKGROUND

Cognitive reserve (CR) has been postulated to contribute to the variation observed between neuropathology and clinical outcomes in Alzheimer's disease (AD).

OBJECTIVE

We investigated the effect of an education-occupation derived CR proxy on biological properties of white matter tracts in patients with amnestic mild cognitive impairment (aMCI) and healthy elders (HC).

METHODS

Educational attainment and occupational complexity ratings (complexity with data, people, and things) from thirty-five patients with aMCI and twenty-eight HC were used to generate composite CR scores. Quantitative magnetic resonance imaging (qMRI) and multi-shell diffusion MRI were used to extract macromolecular tissue volume (MTV) across major white matter tracts.

RESULTS

We observed significant differences in the association between CR and white matter tract MTV in aMCI versus HC when age, gender, intracranial volume, and memory ability were held constant. Particularly, in aMCI, higher CR was associated with worse tract pathology (lower MTV) in the left and right dorsal cingulum, callosum forceps major, right inferior fronto-occipital fasciculus, and right superior longitudinal fasciculus (SLF) tracts. Conversely higher CR was associated with higher MTV in the right parahippocampal cingulum and left SLF in HC.

CONCLUSION

Our results support compensatory CR mechanisms in aMCI and neuroprotective mechanisms in HC and suggest differential roles for CR on white matter macromolecular properties in healthy elders versus prodromal AD patients.