Testing quantitative magnetization transfer models with membrane lipids.

PURPOSE: Quantitative magnetization transfer (qMT) models aim to quantify the contributions of lipids and macromolecules to the MRI signal. Hence, a model system that relates qMT parameters and their molecular sources may improve the interpretation of the qMT parameters. Here we used membrane lipid phantoms as a meaningful tool to study qMT models. By controlling the fraction and type of membrane lipids, we could test the accuracy, reliability, and interpretability of different qMT models. METHODS: We formulated liposomes with various lipid types and water-to-lipids fractions and measured their signals with spoiled gradient-echo MT. We fitted three known qMT models and estimated six parameters for every model. We tested the accuracy and reproducibility of the models and compared the dependency among the qMT parameters. We compared the samples' qMT parameters with their water-to-lipid fractions and with a simple MTnorm (= MTon/MToff) calculation. RESULTS: We found that the three qMT models fit the membrane lipids signals well. We also found that the estimated qMT parameters are highly interdependent. Interestingly, the estimated qMT parameters are a function of the membrane lipid type and also highly related to the water-to-lipid fraction. Finally, we find that most of the lipid sample's information can be captured using the common and easy to estimate MTnorm analysis. CONCLUSION: qMT parameters are sensitive to both the water-to-lipid fraction and to the lipid type. Estimating the water-to-lipid fraction can improve the characterization of membrane lipids' contributions to qMT parameters. Similar characterizations can be obtained using the MTnorm analysis.

An amino-domino model described by a cross-peptide-bond Ramachandran plot defines amino acid pairs as local structural units.

Protein structure, both at the global and local level, dictates function. Proteins fold from chains of amino acids, forming secondary structures, α-helices and ß-strands, that, at least for globular proteins, subsequently fold into a three-dimensional structure. Here, we show that a Ramachandran-type plot focusing on the two dihedral angles separated by the peptide bond, and entirely contained within an amino acid pair, defines a local structural unit. We further demonstrate the usefulness of this cross-peptide-bond Ramachandran plot by showing that it captures ß-turn conformations in coil regions, that traditional Ramachandran plot outliers fall into occupied regions of our plot, and that thermophilic proteins prefer specific amino acid pair conformations. Further, we demonstrate experimentally that the effect of a point mutation on backbone conformation and protein stability depends on the amino acid pair context, i.e., the identity of the adjacent amino acid, in a manner predictable by our method.

Non-invasive assessment of normal and impaired iron homeostasis in the brain.

Strict iron regulation is essential for normal brain function. The iron homeostasis, determined by the milieu of available iron compounds, is impaired in aging, neurodegenerative diseases and cancer. However, non-invasive assessment of different molecular iron environments implicating brain tissue's iron homeostasis remains a challenge. We present a magnetic resonance imaging (MRI) technology sensitive to the iron homeostasis of the living brain (the r1-r2* relaxivity). In vitro, our MRI approach reveals the distinct paramagnetic properties of ferritin, transferrin and ferrous iron ions. In the in vivo human brain, we validate our approach against ex vivo iron compounds quantification and gene expression. Our approach varies with the iron mobilization capacity across brain regions and in aging. It reveals brain tumors' iron homeostasis, and enhances the distinction between tumor tissue and non-pathological tissue without contrast agents. Therefore, our approach may allow for non-invasive research and diagnosis of iron homeostasis in living human brains.

Exergaming in patients with a left ventricular assist device: a feasibility study.

AIMS: Exercise games (exergames) have been recently proposed as a mode of facilitating physical activity in patients with chronic diseases. Although patients supported with left ventricular assist devices (LVADs) benefit from physical activity, specific LVAD-related issues hinder their ability to exercise properly. The objective of this study was to assess the feasibility and safety of exergaming in LVAD-supported patients. METHODS AND RESULTS: Eleven LVAD-supported patients were enrolled in a 4 week exergaming programme using Nintendo Wii console with five sport games. Patients were instructed to play for 30 min a day, 5 days a week. Data on exercise capacity and exergaming were collected by using the 6 min walk test (6MWT) and a daily self-report diary, respectively. Feasibility of using the console and its safety was assessed by a semi-structured patient interview. Quality of life was assessed by the Minnesota Living with Heart failure Questionnaire (MLHFQ) and the Cantril's Ladder of Life. Safety was assessed by patient's report in interview and diary. The study group consisted of 10 male patients and 1 female patient, mean age of 67 ± 7 years, of whom 10 were supported with the HeartMate 3 LVAD for a median of 10 (interquartile range 3, 21) months. Baseline exercise capacity assessed by the 6MWT ranged from 240 to 570 m (mean 448 ± 112). After 4 weeks of exergaming, 6MWT distance increased from a mean of 448 ± 112 (evaluated in six patients) to 472 ± 113 m (P = 0.023). Patients' Cantril's Ladder of Life score improved numerically from an average of 6.13 to 7.67, as did their MLHFQ score from 45.9 ± 27 to 38.7 ± 18, with higher and lower scores, respectively, reflecting higher quality of life. No specific LVAD-related safety issues regarding exergaming were reported. CONCLUSIONS: Exergaming was found to be a safe and feasible mode for encouraging physical activity in LVAD-supported patients and carries a potential for improving exercise capacity and quality of life in these patients. Larger scale studies are warranted to further investigate the effect of exergaming in this patient population.

Machine learning approaches demonstrate that protein structures carry information about their genetic coding.

Synonymous codons translate into the same amino acid. Although the identity of synonymous codons is often considered inconsequential to the final protein structure, there is mounting evidence for an association between the two. Our study examined this association using regression and classification models, finding that codon sequences predict protein backbone dihedral angles with a lower error than amino acid sequences, and that models trained with true dihedral angles have better classification of synonymous codons given structural information than models trained with random dihedral angles. Using this classification approach, we investigated local codon-codon dependencies and tested whether synonymous codon identity can be predicted more accurately from codon context than amino acid context alone, and most specifically which codon context position carries the most predictive power.

Spatial profiles provide sensitive MRI measures of the midbrain micro- and macrostructure.

The midbrain is the rostral-most part of the brainstem. It contains numerous nuclei and white matter tracts, which are involved in motor, auditory and visual processing, and changes in their structure and function have been associated with aging, as well as neurodegenerative disorders. Current tools for estimating midbrain subregions and their structure with MRI require high resolution and multi-parametric quantitative MRI measures. We propose an approach that relies on morphology to calculate profiles along the midbrain and show these profiles are sensitive to the underlying macrostructure of the midbrain. First, we show that the midbrain structure can be sampled, within subject space, along three main axes of the left and right midbrain, producing profiles that are similar across subjects. We use two data sets with different field strengths, that contain R1, R2* and QSM maps and show that the profiles are highly correlated both across subjects and between datasets. Next, we compare profiles of the midbrain that sample ROIs, and show that the profiles along the first two axes sample the midbrain in a way that reliably separates the main structures, i.e., the substantia nigra, the red nucleus, and periaqueductal gray. We further show that age differences which are localized to specific nuclei, are reflected in the profiles. Finally, we generalize the same approach to calculate midbrain profiles on a third clinically relevant dataset using HCP subjects, with metrics such as the diffusion tensor and semi-quantitative data such as T1w/T2w maps. Our results suggest that midbrain profiles, both of quantitative and semi-quantitative estimates are sensitive to the underlying macrostructure of the midbrain. The midbrain profiles are calculated in native space, and rely on simple measurements. We show that it is robust and can be easily expanded to different datasets, and as such we hope that it will be of great use to the community and to the study of the midbrain in particular.

Identification of protective biologic factors in patients with high cardiovascular risk, but normal coronary arteries (NormCorn).

BACKGROUND: Endothelial progenitor cells (EPCs) have an important role in repair following vascular injury. Telomere length has been shown to be correlated with genome stability and overall cell health. We hypothesized that both EPCs and telomere size are related to protective mechanisms against coronary artery disease. Our aim was to evaluate the level and function of circulating EPCs and telomere length in patients with multiple cardiovascular risk factors and anatomically normal coronary arteries vs. matched controls. METHODS: We included 24 patients, with coronary CTA demonstrating normal coronaries and a high risk of CAD of >10% by ASCVD risk estimator. Control groups included 17 patients with similar cardiovascular profiles but with established CAD and a group of 20 healthy volunteers. Circulating EPCs levels were assessed by flow cytometry for expression of vascular endothelial growth factor receptor 2, CD34 and CD133. The capacity of the cells to form colony forming units (CFUs) was quantified after 1 week of culture. Telomere length was determined by the southern blotting technique. RESULTS: Patients with high risk for CVD and normal coronaries had augmented EPCs function, compared with the CAD group (1.1 vs. 0.22 CFU/f; P = 0.04) and longer telomeres compared with the CAD group (10.7 kb vs. 2.8 kb P = 0.015). These patients displayed a similar profile to the healthy group. CONCLUSION: Patients with a high risk for CAD, but normal coronary arteries have EPCs function and telomere length which resemble healthy volunteers, and augmented compared with patients with established CAD, which could serve as a protective mechanism against atherosclerosis development in these high-risk patients.

Mapping microstructural gradients of the human striatum in normal aging and Parkinson's disease.

Mapping structural spatial change (i.e., gradients) in the striatum is essential for understanding the function of the basal ganglia in both health and disease. We developed a method to identify and quantify gradients of microstructure in the single human brain in vivo. We found spatial gradients in the putamen and caudate nucleus of the striatum that were robust across individuals, clinical conditions, and datasets. By exploiting multiparametric quantitative MRI, we found distinct, spatially dependent, aging-related alterations in water content and iron concentration. Furthermore, we found cortico-striatal microstructural covariation, showing relations between striatal structural gradients and cortical hierarchy. In Parkinson's disease (PD) patients, we found abnormal gradients in the putamen, revealing changes in the posterior putamen that explain patients' dopaminergic loss and motor dysfunction. Our work provides a noninvasive approach for studying the spatially varying, structure-function relationship in the striatum in vivo, in normal aging and PD.

Combined mechanical circulatory support for ventricular fibrillation in left ventricular assist device patient.

Ventricular fibrillation, a life-threatening ventricular arrhythmia, may result in pulselessness, loss of consciousness and sudden cardiac death. In this case report, we describe our experience in managing a 54-year-old man with HeartMate3 left ventricular assist device (LVAD) as a bridge to transplantation due to dilated non-ischemic cardiomyopathy, presenting with incessant ventricular arrhythmia for 35 days despite multiple attempts to restore normal rhythm with external direct current cardioversion and anti-arrhythmic medications. The patient remained stable in ventricular arrhythmia with no progression to asystole, but hemodynamic collapse due to right heart failure occurred in the third week. Combined use of two mechanical circulatory support devices (LVAD with VA ECMO) was needed to achieve haemodynamic and metabolic stability, eventually leading to successful heart transplantation in the index admission. The patient was discharged home 2 weeks after transplantation in good clinical condition.

Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon.

Synonymous codons translate into chemically identical amino acids. Once considered inconsequential to the formation of the protein product, there is evidence to suggest that codon usage affects co-translational protein folding and the final structure of the expressed protein. Here we develop a method for computing and comparing codon-specific Ramachandran plots and demonstrate that the backbone dihedral angle distributions of some synonymous codons are distinguishable with statistical significance for some secondary structures. This shows that there exists a dependence between codon identity and backbone torsion of the translated amino acid. Although these findings cannot pinpoint the causal direction of this dependence, we discuss the vast biological implications should coding be shown to directly shape protein conformation and demonstrate the usefulness of this method as a tool for probing associations between codon usage and protein structure. Finally, we urge for the inclusion of exact genetic information into structural databases.

White matter properties underlying reading abilities differ in 8-year-old children born full term and preterm: A multi-modal approach.

Many diffusion magnetic resonance imaging (dMRI) studies document associations between reading skills and fractional anisotropy (FA) within brain white matter, suggesting that efficient transfer of information across the brain contributes to individual differences in reading. Use of complementary imaging methods can determine if these associations relate to myelin content of white matter tracts. Compared to children born at term (FT), children born preterm (PT) are at risk for reading deficits. We used two MRI methods to calculate associations of reading and white matter properties in FT and PT children. Participants (N=79: 36 FT and 43 PT) were administered the Gray's Oral Reading Test at age 8. We segmented three dorsal (left arcuate and bilateral superior longitudinal fasciculus) and four ventral (bilateral inferior longitudinal fasciculus and bilateral uncinate) tracts and quantified (1) FA from dMRI and (2) R1 from quantitative T1 relaxometry. We examined correlations between reading scores and these metrics along the trajectories of the tracts. Reading positively correlated with FA in segments of left arcuate and bilateral superior longitudinal fasciculi in FT children; no FA associations were found in PT children. Reading positively correlated with R1 in segments of the left superior longitudinal, right uncinate, and left inferior longitudinal fasciculi in PT children; no R1 associations were found in FT children. Birth group significantly moderated the associations of reading and white matter metrics. Myelin content of white matter may contribute to individual differences in PT but not FT children.

Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease.

Complex diseases, such as coronary artery disease (CAD), are often multifactorial, caused by multiple underlying pathological mechanisms. Here, to study the multifactorial nature of CAD, we performed comprehensive clinical and multi-omic profiling, including serum metabolomics and gut microbiome data, for 199 patients with acute coronary syndrome (ACS) recruited from two major Israeli hospitals, and validated these results in a geographically distinct cohort. ACS patients had distinct serum metabolome and gut microbial signatures as compared with control individuals, and were depleted in a previously unknown bacterial species of the Clostridiaceae family. This bacterial species was associated with levels of multiple circulating metabolites in control individuals, several of which have previously been linked to an increased risk of CAD. Metabolic deviations in ACS patients were found to be person specific with respect to their potential genetic or environmental origin, and to correlate with clinical parameters and cardiovascular outcomes. Moreover, metabolic aberrations in ACS patients linked to microbiome and diet were also observed to a lesser extent in control individuals with metabolic impairment, suggesting the involvement of these aberrations in earlier dysmetabolic phases preceding clinically overt CAD. Finally, a metabolomics-based model of body mass index (BMI) trained on the non-ACS cohort predicted higher-than-actual BMI when applied to ACS patients, and the excess BMI predictions independently correlated with both diabetes mellitus (DM) and CAD severity, as defined by the number of vessels involved. These results highlight the utility of the serum metabolome in understanding the basis of risk-factor heterogeneity in CAD.

Six-months immunogenicity of BNT162b2 mRNA vaccine in heart transplanted and ventricle assist device-supported patients.

AIMS: To assess the 6 months immunogenicity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccine in a population of heart transplanted (HTx) recipients and left ventricular assist device (LVAD)-supported patients. METHODS AND RESULTS: A prospective single-centre cohort study of HTx recipients and LVAD-supported patients who received a two-dose SARSCoV-2 mRNA vaccine (BNT162b2, Pfizer-BioNTech). Whole blood for anti-spike IgG (S-IgG) antibodies were drawn at 6 months after the first vaccine dose. S-IgG data at 6 weeks were available for a subgroup of HTx recipients. S-IgG ≥ 50 AU/mL were interpreted positive. The cohort included 53 HTx recipients and 18 LVAD-supported patients. The median time from HTx or LVAD implantation to the 1st vaccine dose was 90 (IQR 30, 172) months and 22 (IQR 6, 78) months, respectively. The seropositivity rates of S-IgG antibodies and their titre levels in HTx recipients and LVAD-supported patients were 45% and 83% respectively, (P = 0.006), and 35 (IQR 7, 306) AU/mL and 311 (IQR 86, 774) AU/mL, respectively, (P = 0.006). Reduced SARSCoV-2 vaccine immunogenicity in HTx recipients was associated with older age [odds ratio (OR) 0.917 confidence interval (CI 0.871, 0.966), P = 0.011] and with the use of anti-metabolites-based immunosuppressive regimens [OR 0.224 (CI 0.065, 0.777), P = 0.018]. mTOR inhibitors were associated with higher immunogenicity [OR 3.1 (CI 1.01, 9.65), P = 0.048]. Out of 13 HTx recipients who were S-IgG seropositive at 6 weeks after the first vaccine dose, 85% remained S-IgG seropositive at 6 month follow-up. CONCLUSIONS: At 6 months post-vaccination, S-IgG immunogenicity in HTx recipients is low, particularly in older HTx recipients and in those treated with anti-metabolites drugs.

Infants' cortex undergoes microstructural growth coupled with myelination during development.

Development of cortical tissue during infancy is critical for the emergence of typical brain functions in cortex. However, how cortical microstructure develops during infancy remains unknown. We measured the longitudinal development of cortex from birth  to six months of age  using multimodal quantitative imaging of cortical microstructure. Here we show that infants' cortex undergoes profound microstructural tissue growth during the first six months of human life. Comparison of postnatal to prenatal transcriptomic gene expression data demonstrates that myelination and synaptic processes are dominant contributors to this postnatal microstructural tissue growth. Using visual cortex as a model system, we find hierarchical microstructural growth: higher-level visual areas have less mature tissue at birth than earlier visual areas but grow at faster rates. This overturns the prominent view that visual areas that are most mature at birth develop fastest. Together, in vivo, longitudinal, and quantitative measurements, which we validated with ex vivo transcriptomic data, shed light on the rate, sequence, and biological mechanisms of developing cortical systems during early infancy. Importantly, our findings propose a hypothesis that cortical myelination is a key factor in cortical development during early infancy, which has important implications for diagnosis of neurodevelopmental disorders and delays in infants.

The glial framework reveals white matter fiber architecture in human and primate brains.

Uncovering the architecture of white matter axons is fundamental to the study of brain networks. We developed a method for quantifying axonal orientations at a resolution of ~15 micrometers. This method is based on the common Nissl staining technique for postmortem histological slices. Nissl staining reveals the spatial organization of glial cells along axons. Using structure tensor analysis, we leveraged this patterned organization to uncover local axonal orientation. We used Nissl-based structure tensor analysis to extract fine details of axonal architecture and demonstrated its applicability in multiple datasets of humans and nonhuman primates. Nissl-based structure tensor analysis can be used to compare fine-grained features of axonal architecture across species and is widely applicable to existing datasets.

Opening the Schrödinger Box: Short- and Long-Range Mammalian Heart Rate Variability.

BACKGROUND: The interactions between the autonomic nervous system (ANS), intrinsic systems (e.g., endocrine), and internal pacemaker mechanisms govern short (milliseconds-seconds)- and long (seconds-minutes)-range heart rate variability (HRV). However, there is a debate regarding the identity of the mechanism underlying HRV on each time scale. We aim to design a general method that accurately differentiates between the relative contribution of the ANS and pacemaker mechanisms to HRV in various mammals, without the need for drug perturbations or organ isolation. Additionally, we aim to explore the universality of the relative contribution of the ANS and pacemaker system of different mammals. METHODS: This work explored short- and long-range HRVs using published ECG data from dogs, rabbits, and mice. To isolate the effects of ANS on HRV, ECG segments recorded before and after ANS-blockade were compared. RESULTS: Differentiation of the ANS from extrinsic and intrinsic pacemaker mechanisms was successfully achieved. In dogs, the internal pacemaker mechanisms were the main contributors to long-range and the ANS to short-range HRV. In rabbits and mice, the ANS and the internal pacemaker mechanisms affected both time scales, and anesthesia changed the relative contribution of the pacemaker mechanism to short- and long-range HRVs. In mice, the extrinsic mechanisms affected long-range HRV, while their effect was negligible in rabbits. CONCLUSION: We offer a novel approach to determine the relative contributions of ANS and extrinsic and intrinsic pacemaker mechanisms to HRV and highlight the importance of selecting mammalian research models with HRV mechanisms representative of the target species of interest.

Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis.

Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically meaningful terms, handling the presence of unknown medical conditions, and transparency regarding the system's limitations, both in terms of statistical performance as well as recognizing situations for which the system's predictions are irrelevant. We articulate these unmet clinical needs as machine-learning (ML) problems and systematically address them with cutting-edge ML techniques. We focus on electrocardiogram (ECG) analysis as an example domain in which AI has great potential and tackle two challenging tasks: the detection of a heterogeneous mix of known and unknown arrhythmias from ECG and the identification of underlying cardio-pathology from segments annotated as normal sinus rhythm recorded in patients with an intermittent arrhythmia. We validate our methods by simulating a screening for arrhythmias in a large-scale population while adhering to statistical significance requirements. Specifically, our system 1) visualizes the relative importance of each part of an ECG segment for the final model decision; 2) upholds specified statistical constraints on its out-of-sample performance and provides uncertainty estimation for its predictions; 3) handles inputs containing unknown rhythm types; and 4) handles data from unseen patients while also flagging cases in which the model's outputs are not usable for a specific patient. This work represents a significant step toward overcoming the limitations currently impeding the integration of AI into clinical practice in cardiology and medicine in general.

Immunogenicity of the BNT162b2 mRNA vaccine in heart transplant recipients - a prospective cohort study.

AIMS: To assess the short-term immunogenicity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccine in a population of heart transplant (HTx) recipients. A prospective single-centre cohort study of HTx recipients who received a two-dose SARS-CoV-2 mRNA vaccine (BNT162b2, Pfizer-BioNTech). METHODS AND RESULTS: Whole blood for anti-spike IgG (S-IgG) antibodies was drawn at days 21-26 and at days 35-40 after the first vaccine dose. Geometric mean titres (GMT) ≥50 AU/mL were interpreted positive. Included were 42 HTx recipients at a median age of 61 [interquartile range (IQR) 44-69] years. Median time from HTx to the first vaccine dose was 9.1 (IQR 2.6-14) years. Only 15% of HTx recipients demonstrated the presence of positive S-IgG antibody titres in response to the first vaccine dose [GMT 90 (IQR 54-229) AU/mL]. Overall, 49% of HTx recipients induced S-IgG antibodies in response to either the first or the full two-dose vaccine schedule [GMT 426 (IQR 106-884) AU/mL]. Older age [68 (IQR 59-70) years vs. 46 (IQR 34-63) years, P = 0.034] and anti-metabolite-based immunosuppression protocols (89% vs. 44%, P = 0.011) were associated with low immunogenicity. Importantly, 36% of HTx recipients who were non-responders to the first vaccine dose became S-IgG seropositive in response to the second vaccine dose. Approximately a half of HTx recipients did not generate S-IgG antibodies following SARS-CoV-2 two-dose vaccine. CONCLUSIONS: The generally achieved protection from SARS-CoV-2 mRNA vaccination should be regarded with caution in the population of HTx recipients. The possible benefit of additive vaccine should be further studied.

Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use.

Pulse oximetry is routinely used to non-invasively monitor oxygen saturation levels. A low oxygen level in the blood means low oxygen in the tissues, which can ultimately lead to organ failure. Yet, contrary to heart rate variability measures, a field which has seen the development of stable standards and advanced toolboxes and software, no such standards and open tools exist for continuous oxygen saturation time series variability analysis. The primary objective of this research was to identify, implement and validate key digital oximetry biomarkers (OBMs) for the purpose of creating a standard and associated reference toolbox for continuous oximetry time series analysis. We review the sleep medicine literature to identify clinically relevant OBMs. We implement these biomarkers and demonstrate their clinical value within the context of obstructive sleep apnea (OSA) diagnosis on a total of n = 3806 individual polysomnography recordings totaling 26,686 h of continuous data. A total of 44 digital oximetry biomarkers were implemented. Reference ranges for each biomarker are provided for individuals with mild, moderate, and severe OSA and for non-OSA recordings. Linear regression analysis between biomarkers and the apnea hypopnea index (AHI) showed a high correlation, which reached [Formula: see text]. The resulting python OBM toolbox, denoted "pobm", was contributed to the open software PhysioZoo ( physiozoo.org ). Studying the variability of the continuous oxygen saturation time series using pbom may provide information on the underlying physiological control systems and enhance our understanding of the manifestations and etiology of diseases, with emphasis on respiratory diseases.

Conduction delays in the visual pathways of progressive multiple sclerosis patients covary with brain structure.

In developed countries, multiple sclerosis (MS) is the leading cause of non-traumatic neurological disability in young adults. MS is a chronic demyelinating disease of the central nervous system, in which myelin is attacked, changing white matter structure and leaving lesions. The demyelination has a direct effect on white matter conductivity. This effect can be examined in the visual system, where damage is highly prevalent in MS, leading to substantial delays in conduction, commonly measured with visual evoked potentials (VEPs). The structural damage to the visual system in MS is often estimated with MRI measurements in the white matter. Recent developments in quantitative MRI (qMRI) provide improved sensitivity to myelin content and new structural methods allow better modeling of the axonal structure, leading researchers to link white matter microstructure to conduction properties of action potentials along fiber tracts. This study attempts to explain the variance in conduction latencies down the visual pathway using structural measurements of both the retina and the optic radiation (OR). Forty-eight progressive MS patients, participants in a longitudinal stem-cell therapy clinical trial, were included in this study, three and six months post final treatment. Twenty-seven patients had no history of optic neuritis, and were the main focus of this study. All participants underwent conventional MRI scans, as well as diffusion MRI and qMRI sequences to account for white matter microstructure. Optical coherence tomography scans were also obtained, and peripapillary retinal nerve fiber layer (pRNFL) thickness and macular volume measurements were extracted. Finally, latencies of recorded VEPs were estimated. Our results show that in non-optic neuritis progressive MS patients there is a relationship between the VEP latency and both retinal damage and OR lesion load. In addition, we find that qMRI values, sampled along the OR, are also correlated with VEP latency. Finally, we show that combining these parameters using PCA we can explain more than 40% of the inter-subject variance in VEP latency. In conclusion, this study contributes to understanding the relationship between the structural properties and conduction in the visual system in disease. We focus on the visual system, where the conduction latencies can be estimated, but the conclusions could be generalized to other brain systems where the white matter structure can be measured. It also highlights the importance of having multiple parameters when assessing the clinical stages of MS patients, which could have major implications for future studies of other white matter diseases.