Diffusion tensor magnetic resonance imaging in multiple sclerosis

Advanced diffusion imaging reveals microstructural characteristics of primary CNS lymphoma, allowing differentiation from glioblastoma

Background

Primary CNS lymphoma (PCNSL) and glioblastoma (GBM) both represent frequent intracranial malignancies with differing clinical management. However, distinguishing PCNSL from GBM with conventional MRI can be challenging when atypical imaging features are present. We employed advanced dMRI for noninvasive characterization of the microstructure of PCNSL and differentiation from GBM as the most frequent primary brain malignancy.

Methods

Multiple dMRI metrics including Diffusion Tensor Imaging, Neurite Orientation Dispersion and Density Imaging, and Diffusion Microstructure Imaging were extracted from the contrast-enhancing tumor component in 10 PCNSL and 10 age-matched GBM on 3T MRI. Imaging findings were correlated with cell density and axonal markers obtained from histopathology.

Results

We found significantly increased intra-axonal volume fractions (V-intra and intracellular volume fraction) and microFA in PCNSL compared to GBM (all P < .001). In contrast, mean diffusivity (MD), axial diffusivity (aD), and microADC (all P < .001), and also free water fractions (V-CSF and V-ISO) were significantly lower in PCNSL (all P < .01). Receiver-operating characteristic analysis revealed high predictive values regarding the presence of a PCNSL for MD, aD, microADC, V-intra, ICVF, microFA, V-CSF, and V-ISO (area under the curve [AUC] in all >0.840, highest for MD and ICVF with an AUC of 0.960). Comparative histopathology between PCNSL and GBM revealed a significantly increased cell density in PCNSL and the presence of axonal remnants in a higher proportion of samples.

Conclusions

Advanced diffusion imaging enables the characterization of the microstructure of PCNSL and reliably distinguishes PCNSL from GBM. Both imaging and histopathology revealed a relatively increased cell density and a preserved axonal microstructure in PCNSL.

Understanding the Pathophysiology and Magnetic Resonance Imaging of Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders

Magnetic resonance imaging (MRI) has been extensively applied in the study of multiple sclerosis (MS), substantially contributing to diagnosis, differential diagnosis, and disease monitoring. MRI studies have significantly contributed to the understanding of MS through the characterization of typical radiological features and their clinical or prognostic implications using conventional MRI pulse sequences and further with the application of advanced imaging techniques sensitive to microstructural damage. Interpretation of results has often been validated by MRI-pathology studies. However, the application of MRI techniques in the study of neuromyelitis optica spectrum disorders (NMOSD) remains an emerging field, and MRI studies have focused on radiological correlates of NMOSD and its pathophysiology to aid in diagnosis, improve monitoring, and identify relevant prognostic factors. In this review, we discuss the main contributions of MRI to the understanding of MS and NMOSD, focusing on the most novel discoveries to clarify differences in the pathophysiology of focal inflammation initiation and perpetuation, involvement of normal-appearing tissue, potential entry routes of pathogenic elements into the CNS, and existence of primary or secondary mechanisms of neurodegeneration.

White matter changes measured by multi-component MR Fingerprinting in multiple sclerosis

T2-hyperintense lesions are the key imaging marker of multiple sclerosis (MS). Previous studies have shown that the white matter surrounding such lesions is often also affected by MS. Our aim was to develop a new method to visualize and quantify the extent of white matter tissue changes in MS based on relaxometry properties. We applied a fast, multi-parametric quantitative MRI approach and used a multi-component MR Fingerprinting (MC-MRF) analysis. We assessed the differences in the MRF component representing prolongedrelaxation time between patients with MS and controls and studied the relation between this component's volume and structural white matter damage identified on FLAIR MRI scans in patients with MS. A total of 48 MS patients at two different sites and 12 healthy controls were scanned with FLAIR and MRF-EPI MRI scans. MRF scans were analyzed with a joint-sparsity multi-component analysis to obtain magnetization fraction maps of different components, representing tissues such as myelin water, white matter, gray matter and cerebrospinal fluid. In the MS patients, an additional component was identified with increased transverse relaxation times compared to the white matter, likely representing changes in free water content. Patients with MS had a higher volume of the long- component in the white matter of the brain compared to healthy controls (B (95%-CI) = 0.004 (0.0006-0.008), p = 0.02). Furthermore, this MRF component had a moderate correlation (correlation coefficient R 0.47) with visible structural white matter changes on the FLAIR scans. Also, the component was found to be more extensive compared to structural white matter changes in 73% of MS patients. In conclusion, our MRF acquisition and analysis captured white matter tissue changes in MS patients compared to controls. In patients these tissue changes were more extensive compared to visually detectable white matter changes on FLAIR scans. Our method provides a novel way to quantify the extent of white matter changes in MS patients, which is underestimated using only conventional clinical MRI scans.

Texture feature analysis of MRI-ADC images to differentiate glioma grades using machine learning techniques

Apparent diffusion coefficient (ADC) of magnetic resonance imaging (MRI) is an indispensable imaging technique in clinical neuroimaging that quantitatively assesses the diffusivity of water molecules within tissues using diffusion-weighted imaging (DWI). This study focuses on developing a robust machine learning (ML) model to predict the aggressiveness of gliomas according to World Health Organization (WHO) grading by analyzing patients' demographics, higher-order moments, and grey level co-occurrence matrix (GLCM) texture features of ADC. A population of 722 labeled MRI-ADC brain image slices from 88 human subjects was selected, where gliomas are labeled as glioblastoma multiforme (WHO-IV), high-grade glioma (WHO-III), and low-grade glioma (WHO I-II). Images were acquired using 3T-MR systems and a region of interest (ROI) was delineated manually over tumor areas. Skewness, kurtosis, and statistical texture features of GLCM (mean, variance, energy, entropy, contrast, homogeneity, correlation, prominence, and shade) were calculated using ADC values within ROI. The ANOVA f-test was utilized to select the best features to train an ML model. The data set was split into training (70%) and testing (30%) sets. The train set was fed into several ML algorithms and selected most promising ML algorithm using K-fold cross-validation. The hyper-parameters of the selected algorithm were optimized using random grid search technique. Finally, the performance of the developed model was assessed by calculating accuracy, precision, recall, and F1 values reported for the test set. According to the ANOVA f-test, three attributes; patient gender (1.48), GLCM energy (9.48), and correlation (13.86) that performed minimum scores were excluded from the dataset. Among the tested algorithms, the random forest classifier(0.8772 ± 0.0237) performed the highest mean-cross-validation score and selected to build the ML model which was able to predict tumor categories with an accuracy of 88.14% over the test set. The study concludes that the developed ML model using the above features except for patient gender, GLCM energy, and correlation, has high prediction accuracy in glioma grading. Therefore, the outcomes of this study enable to development of advanced tumor classification applications that assist in the decision-making process in a real-time clinical environment.

High angular diffusion tensor imaging estimation from minimal evenly distributed diffusion gradient directions

Diffusion-weighted Imaging (DWI) is a non-invasive imaging technique based on Magnetic Resonance Imaging (MRI) principles to measure water diffusivity and reveal details of the underlying brain micro-structure. By fitting a tensor model to quantify the directionality of water diffusion a Diffusion Tensor Image (DTI) can be derived and scalar measures, such as fractional anisotropy (FA), can then be estimated from the DTI to summarise quantitative microstructural information for clinical studies. In particular, FA has been shown to be a useful research metric to identify tissue abnormalities in neurological disease (e.g. decreased anisotropy as a proxy for tissue damage). However, time constraints in clinical practice lead to low angular resolution diffusion imaging (LARDI) acquisitions that can cause inaccurate FA value estimates when compared to those generated from high angular resolution diffusion imaging (HARDI) acquisitions. In this work, we propose High Angular DTI Estimation Network (HADTI-Net) to estimate an enhanced DTI model from LARDI with a set of minimal and evenly distributed diffusion gradient directions. Extensive experiments have been conducted to show the reliability and generalisation of HADTI-Net to generate high angular DTI estimation from any minimal evenly distributed diffusion gradient directions and to explore the feasibility of applying a data-driven method for this task. The code repository of this work and other related works can be found at https://mri-synthesis.github.io/.

NfL and GFAP in serum are associated with microstructural brain damage in progressive multiple sclerosis

BACKGROUND

The potential of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) as biomarkers of disease activity and severity in progressive forms of multiple sclerosis (MS) is unclear.

OBJECTIVE

To investigate the relationship between serum concentrations of NfL, GFAP, and magnetic resonance imaging (MRI) in progressive MS.

METHODS

Serum concentrations of NfL and GFAP were measured in 32 healthy controls and 32 patients with progressive MS from whom clinical and MRI data including diffusion tensor imaging (DTI) were obtained during three years of follow-up.

RESULTS

Serum concentrations of NfL and GFAP at follow-up were higher in progressive MS patients than in healthy controls and serum NfL correlated with the EDSS score. Decreasing fractional anisotropy (FA) in normal-appearing white matter (NAWM) correlated with worsening EDSS scores and higher serum NfL. Higher serum NfL and increasing T2 lesion volume correlated with worsening paced autitory serial addition test scores. In multivariable regression analyses with serum GFAP and NfL as independent factors and DTI measures of NAWM as dependent factors, we showed that high serum NfL at follow-up was independently associated with decreasing FA and increasing MD in NAWM. Moreover, we found that high serum GFAP was independently associated with decreasing MD in NAWM and with decreasing MD and increasing FA in cortical gray matter.

CONCLUSION

Serum concentrations of NfL and GFAP are increased in progressive MS and are associated with distinct microstructural changes in NAWM and CGM.

The Heterogeneous Multiple Sclerosis Lesion: How Can We Assess and Modify a Degenerating Lesion?

Multiple sclerosis (MS) is a heterogeneous disease of the central nervous system that is governed by neural tissue loss and dystrophy during its progressive phase, with complex reactive pathological cellular changes. The immune-mediated mechanisms that promulgate the demyelinating lesions during relapses of acute episodes are not characteristic of chronic lesions during progressive MS. This has limited our capacity to target the disease effectively as it evolves within the central nervous system white and gray matter, thereby leaving neurologists without effective options to manage individuals as they transition to a secondary progressive phase. The current review highlights the molecular and cellular sequelae that have been identified as cooperating with and/or contributing to neurodegeneration that characterizes individuals with progressive forms of MS. We emphasize the need for appropriate monitoring via known and novel molecular and imaging biomarkers that can accurately detect and predict progression for the purposes of newly designed clinical trials that can demonstrate the efficacy of neuroprotection and potentially neurorepair. To achieve neurorepair, we focus on the modifications required in the reactive cellular and extracellular milieu in order to enable endogenous cell growth as well as transplanted cells that can integrate and/or renew the degenerative MS plaque.

Longitudinal Assessment of Multiple Sclerosis Lesion Load With Synthetic Magnetic Resonance Imaging-A Multicenter Validation Study

INTRODUCTION

Double inversion recovery (DIR) has been validated as a sensitive magnetic resonance imaging (MRI) contrast in multiple sclerosis (MS). Deep learning techniques can use basic input data to generate synthetic DIR (synthDIR) images that are on par with their acquired counterparts. As assessment of longitudinal MRI data is paramount in MS diagnostics, our study's purpose is to evaluate the utility of synthDIR longitudinal subtraction imaging for detection of disease progression in a multicenter data set of MS patients.

METHODS

We implemented a previously established generative adversarial network to synthesize DIR from input T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences for 214 MRI data sets from 74 patients and 5 different centers. One hundred and forty longitudinal subtraction maps of consecutive scans (follow-up scan-preceding scan) were generated for both acquired FLAIR and synthDIR. Two readers, blinded to the image origin, independently quantified newly formed lesions on the FLAIR and synthDIR subtraction maps, grouped into specific locations as outlined in the McDonald criteria.

RESULTS

Both readers detected significantly more newly formed MS-specific lesions in the longitudinal subtractions of synthDIR compared with acquired FLAIR (R1: 3.27 ± 0.60 vs 2.50 ± 0.69 [ P = 0.0016]; R2: 3.31 ± 0.81 vs 2.53 ± 0.72 [ P < 0.0001]). Relative gains in detectability were most pronounced in juxtacortical lesions (36% relative gain in lesion counts-pooled for both readers). In 5% of the scans, synthDIR subtraction maps helped to identify a disease progression missed on FLAIR subtraction maps.

CONCLUSIONS

Generative adversarial networks can generate high-contrast DIR images that may improve the longitudinal follow-up assessment in MS patients compared with standard sequences. By detecting more newly formed MS lesions and increasing the rates of detected disease activity, our methodology promises to improve clinical decision-making.

Neuronal activity and NIBS in developmental myelination and remyelination - current state of knowledge

Oligodendrocytes are responsible for myelinating central nervous system (CNS) axons. and rapid electrical transmission through saltatory conduction of action potentials. Myelination and myelin repair rely partially on oligodendrogenesis, which comprises. oligodendrocyte precursor cell (OPC) migration, maturation, and differentiation into. oligodendrocytes (OL). In multiple sclerosis (MS), demyelination occurs due to an. inflammatory cascade with auto-reactive T-cells. When oligodendrogenesis fails, remyelination becomes aberrant and conduction impairments are no longer restored. Although current disease modifying therapies have achieved results in modulating the. faulty immune response, disease progression continues because of chronic. inflammation, neurodegeneration, and failure of remyelination. Therapies have been. tried to promote remyelination. Modulation of neuronal activity seems to be a very. promising strategy in preclinical studies. Additionally, studies in people with MS. (pwMS) have shown symptom improvement following non-invasive brain stimulation. (NIBS) techniques. The aforementioned mechanisms are yet unknown and probably. involve both the activation of neurons and glial cells. Noting neuronal activity. contributes to myelin plasticity and that NIBS modulates neuronal activity; we argue. that NIBS is a promising research horizon for demyelinating diseases. We review the. hypothesized pathways through which NIBS may affect both neuronal activity in the. CNS and how the resulting activity can affect oligodendrogenesis and myelination.

The Value of Various Post-Processing Modalities of Diffusion Weighted Imaging in the Detection of Multiple Sclerosis

Diffusion tensor imaging (DTI) showed its adequacy in evaluating the normal-appearing white matter (NAWM) and lesions in the brain that are difficult to evaluate with routine clinical magnetic resonance imaging (MRI) in multiple sclerosis (MS). Recently, MRI systems have been developed with regard to software and hardware, leading to different proposed diffusion analysis methods such as diffusion tensor imaging, q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, and axonal diameter measurement. These methods have the ability to better detect in vivo microstructural changes in the brain than DTI. These different analysis modalities could provide supplementary inputs for MS disease characterization and help in monitoring the disease’s progression as well as treatment efficacy. This paper reviews some of the recent diffusion MRI methods used for the assessment of MS in vivo.

Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset

Introduction

Conventional MRI is routinely used for the characterization of pathological changes in multiple sclerosis (MS), but due to its lack of specificity is unable to provide accurate prognoses, explain disease heterogeneity and reconcile the gap between observed clinical symptoms and radiological evidence. Quantitative MRI provides measures of physiological abnormalities, otherwise invisible to conventional MRI, that correlate with MS severity. Analyzing quantitative MRI measures through machine learning techniques has been shown to improve the understanding of the underlying disease by better delineating its alteration patterns.

Methods

In this retrospective study, a cohort of healthy controls (HC) and MS patients with different subtypes, followed up 15 years from clinically isolated syndrome (CIS), was analyzed to produce a multi-modal set of quantitative MRI features encompassing relaxometry, microstructure, sodium ion concentration, and tissue volumetry. Random forest classifiers were used to train a model able to discriminate between HC, CIS, relapsing remitting (RR) and secondary progressive (SP) MS patients based on these features and, for each classification task, to identify the relative contribution of each MRI-derived tissue property to the classification task itself.

Results and discussion

Average classification accuracy scores of 99 and 95% were obtained when discriminating HC and CIS vs. SP, respectively; 82 and 83% for HC and CIS vs. RR; 76% for RR vs. SP, and 79% for HC vs. CIS. Different patterns of alterations were observed for each classification task, offering key insights in the understanding of MS phenotypes pathophysiology: atrophy and relaxometry emerged particularly in the classification of HC and CIS vs. MS, relaxometry within lesions in RR vs. SP, sodium ion concentration in HC vs. CIS, and microstructural alterations were involved across all tasks.

T1w/FLAIR ratio standardization as a myelin marker in MS patients

INTRODUCTION

Calculation of a T1w/T2w ratio was introduced as a proxy for myelin integrity in the brain of multiple sclerosis (MS) patients. Since nowadays 3D FLAIR is commonly used for lesion detection instead of T2w images, we introduce a T1w/FLAIR ratio as an alternative for the T1w/T2w ratio.

OBJECTIVES

Bias and intensity variation are widely present between different scanners, between subjects and within subjects over time in T1w, T2w and FLAIR images. We present a standardized method for calculating a histogram calibrated T1w/FLAIR ratio to reduce bias and intensity variation in MR sequences from different scanners and at different time-points.

MATERIAL AND METHODS

207 Relapsing Remitting MS patients were scanned on 4 different 3 T scanners with a protocol including 3D T1w, 2D T2w and 3D FLAIR images. After bias correction, T1w/FLAIR ratio maps and T1w/T2w ratio maps were calculated in 4 different ways: without calibration, with linear histogram calibration as described by Ganzetti et al. (2014), and by using 2 methods of non-linear histogram calibration. The first nonlinear calibration uses a template of extra-cerebral tissue and cerebrospinal fluid (CSF) brought from Montreal Neurological Institute (MNI) space to subject space; for the second nonlinear method we used an extra-cerebral tissue and CSF template of our own subjects. Additionally, we segmented several brain structures such as Normal Appearing White Matter (NAWM), Normal Appearing Grey Matter (NAGM), corpus callosum, thalami and MS lesions using Freesurfer and Samseg.

RESULTS

The coefficient of variation of T1w/FLAIR ratio in NAWM for the no calibrated, linear, and 2 nonlinear calibration methods were respectively 24, 19.1, 9.5, 13.8. The nonlinear methods of calibration showed the best results for calculating the T1w/FLAIR ratio with a smaller dispersion of the data and a smaller overlap of T1w/FLAIR ratio in the different segmented brain structures. T1w/T2w and T1w/FLAIR ratios showed a wider range of values compared to MTR values.

CONCLUSIONS

Calibration of T1w/T2w and T1w/FLAIR ratio maps is imperative to account for the sources of variation described above. The nonlinear calibration methods showed the best reduction of between-subject and within-subject variability. The T1w/T2w and T1w/FLAIR ratio seem to be more sensitive to smaller changes in tissue integrity than MTR. Future work is needed to determine the exact substrate of T1w/FLAIR ratio and to obtain correlations with clinical outcome.

Uncertainty-Aware and Lesion-Specific Image Synthesis in Multiple Sclerosis Magnetic Resonance Imaging: A Multicentric Validation Study

Generative adversarial networks (GANs) can synthesize high-contrast MRI from lower-contrast input. Targeted translation of parenchymal lesions in multiple sclerosis (MS), as well as visualization of model confidence further augment their utility, provided that the GAN generalizes reliably across different scanners. We here investigate the generalizability of a refined GAN for synthesizing high-contrast double inversion recovery (DIR) images and propose the use of uncertainty maps to further enhance its clinical utility and trustworthiness. A GAN was trained to synthesize DIR from input fluid-attenuated inversion recovery (FLAIR) and T1w of 50 MS patients (training data). In another 50 patients (test data), two blinded readers (R1 and R2) independently quantified lesions in synthetic DIR (synthDIR), acquired DIR (trueDIR) and FLAIR. Of the 50 test patients, 20 were acquired on the same scanner as training data (internal data), while 30 were scanned at different scanners with heterogeneous field strengths and protocols (external data). Lesion-to-Background ratios (LBR) for MS-lesions vs. normal appearing white matter, as well as image quality parameters were calculated. Uncertainty maps were generated to visualize model confidence. Significantly more MS-specific lesions were found in synthDIR compared to FLAIR (R1: 26.7 ± 2.6 vs. 22.5 ± 2.2 p < 0.0001; R2: 22.8 ± 2.2 vs. 19.9 ± 2.0, p = 0.0005). While trueDIR remained superior to synthDIR in R1 [28.6 ± 2.9 vs. 26.7 ± 2.6 (p = 0.0021)], both sequences showed comparable lesion conspicuity in R2 [23.3 ± 2.4 vs. 22.8 ± 2.2 (p = 0.98)]. Importantly, improvements in lesion counts were similar in internal and external data. Measurements of LBR confirmed that lesion-focused GAN training significantly improved lesion conspicuity. The use of uncertainty maps furthermore helped discriminate between MS lesions and artifacts. In conclusion, this multicentric study confirms the external validity of a lesion-focused Deep-Learning tool aimed at MS imaging. When implemented, uncertainty maps are promising to increase the trustworthiness of synthetic MRI.

Diffusion Tensor Imaging Revealed Microstructural Changes in Normal-Appearing White Matter Regions in Relapsing–Remitting Multiple Sclerosis

Background

Axons and myelin sheaths are the physical foundation for white matter (WM) to perform normal functions. Our previous study found the metabolite abnormalities in frontal, parietal, and occipital normal-appearing white matter (NAWM) regions in relapsing–remitting multiple sclerosis (RRMS) patients by applying a 2D 1H magnetic resonance spectroscopic imaging method. Since the metabolite changes may associate with the microstructure changes, we used the diffusion tensor imaging (DTI) method to assess the integrity of NAWM in this study.

Method

Diffusion tensor imaging scan was performed on 17 clinically definite RRMS patients and 21 age-matched healthy controls on a 3.0-T scanner. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were extracted from 19 predefined regions of interest (ROIs), which were generated by removing a mask of manually drawn probabilistic lesion map from the Johns Hopkins University white-matter atlas. The mean values of FA, MD, AD, and RD were compared between different groups in the same ROIs.

Results

A probabilistic lesion map was successfully generated, and the lesion regions were eliminated from the WM atlas. We found that the RRMS patients had significantly lower FA in the entire corpus callosum (CC), bilateral of anterior corona radiata, and right posterior thalamic radiation (PTR). At the same time, RRMS patients showed significantly higher MD in the bilateral anterior corona radiata and superior corona radiata. Moreover, all AD values increased, and the bilateral external capsule, PTR, and left tapetum NAWM show statistical significance. What is more, all NAWM tracts showed increasing RD values in RRMS patients, and the bilateral superior corona radiata, the anterior corona radiata, right PTR, and the genu CC reach statistical significance.

Conclusion

Our study revealed widespread microstructure changes in NAWM in RRMS patients through a ready-made WM atlas and probabilistic lesion map. These findings support the hypothesis of demyelination, accumulation of inflammatory cells, and axonal injury in NAWM for RRMS. The DTI-based metrics could be considered as potential non-invasive biomarkers of disease severity.

The forgotten tract of vision in multiple sclerosis: vertical occipital fasciculus, its fiber properties, and visuospatial memory

Visual disturbances are a common disease manifestation in multiple sclerosis (MS) due to lesions damaging white matter tracts involved in vision. Vertical occipital fasciculus (VOF), a tract located vertically in the occipital lobe, was neglected for more than a century. We hypothesize that VOF is involved in integrating information between dorsal and ventral visual streams. Thus, its damage in MS, as well as its probable role in visual processing (by using MS as a VOF damage model) needs to be clarified. To study fiber characteristics of VOF in MS, and their clinical and visual learning associations, 57 relapsing-remitting MS (RRMS) and 25 healthy controls (HC) were recruited. We acquired MS Functional Composite, Expanded Disability Status Scale (EDSS), and Brief Visuospatial Memory Test-Revised (BVMT-R), and diffusion MRI scans. Tractography of VOF and optic radiation (OR) was done. VOF's metrics were statistically tested for between-group differences and clinical and visual tests associations. Along-tract analysis and laterality were also tested. RRMS patients had higher mean, axial, and radial diffusivity (nearly in all fiber points), and lower fractional anisotropy in bilateral VOFs compared to HC. No laterality was noted. These were associated with poor clinical outcomes, poor visual scores in EDSS, and lower total immediate and delayed recall in BVMT-R in RRMS, after adjusting for age, gender, and fiber metrics of OR. VOF damage is present in RRMS and is associated with visual symptoms and visuospatial learning impairments. It seems VOF is involved in integrating information between visual streams.

OUP accepted manuscript

Genetic variants in the human leukocyte antigen and killer cell immunoglobulin-like receptor regions have been associated with many brain-related diseases, but how they shape brain structure and function remains unclear. To identify the genetic variants in HLA and KIR genes associated with human brain phenotypes, we performed a genetic association study of ∼30 000 European unrelated individuals using brain MRI phenotypes generated by the UK Biobank (UKB). We identified 15 HLA alleles in HLA class I and class II genes significantly associated with at least one brain MRI-based phenotypes (P < 5 × 10⁻⁸). These associations converged on several main haplotypes within the HLA. In particular, the human leukocyte antigen alleles within an ancestral haplotype 8.1 were associated with multiple MRI measures, including grey matter volume, cortical thickness (TH) and diffusion MRI (dMRI) metrics. These alleles have been strongly associated with schizophrenia. Additionally, associations were identified between HLA-DRB1*04∼DQA1*03:01∼DQB1*03:02 and isotropic volume fraction of diffusion MRI in multiple white matter tracts. This haplotype has been reported to be associated with Parkinson’s disease. These findings suggest shared genetic associations between brain MRI biomarkers and brain-related diseases. Additionally, we identified 169 associations between the complement component 4 (C4) gene and imaging phenotypes. We found that C4 gene copy number was associated with cortical TH and dMRI metrics. No KIR gene copy numbers were associated with image-derived phenotypes at genome-wide threshold. To address the multiple testing burden in the phenome-wide association study, we performed a multi-trait association analysis using trait-based association test that uses extended Simes procedure and identified MRI image-specific associations. This study contributes to insight into how critical immune genes affect brain-related traits as well as the development of neurological and neuropsychiatric disorders.

Elucidating distinct clinico-radiologic signatures in the borderland between neuromyelitis optica and multiple sclerosis

BACKGROUND

Separating antibody-negative neuromyelitis optica spectrum disorders (NMOSD) from multiple sclerosis (MS) in borderline cases is extremely challenging due to lack of biomarkers. Elucidating different pathologies within the likely heterogenous antibody-negative NMOSD/MS overlap syndrome is, therefore, a major unmet need which would help avoid disability from inappropriate treatment.

OBJECTIVE

In this study we aimed to identify distinct subgroups within the antibody-negative NMOSD/MS overlap syndrome.

METHODS

Twenty-five relapsing antibody-negative patients with NMOSD features underwent a prospective brain and spinal cord MRI. Subgroups were identified by an unsupervised algorithm based on pre-selected NMOSD/MS discriminators.

RESULTS

Four subgroups were identified. Patients from Group 1 termed "MS-like" (n = 6) often had central vein sign and cortical lesions (83% and 67%, respectively). All patients from Group 2 ("spinal MS-like", 8) had short-segment myelitis and no MS-like brain lesions. Group 3 ("classic NMO-like", 6) had high percentage of bilateral optic neuritis and longitudinally extensive transverse myelitis (LETM, 80% and 60%, respectively) and normal brain appearance (100%). Group 4 ("NMO-like with brain involvement", 5) typically had a history of NMOSD-like brain lesions and LETM. When compared with other groups, Group 4 had significantly decreased fractional anisotropy in non-lesioned tracts (0.46 vs. 0.49, p = 0.003) and decreased thalamus volume (0.84 vs. 0.98, p = 0.04).

CONCLUSIONS

NMOSD/MS cohort contains distinct subgroups likely corresponding to different pathologies and requiring tailored treatment. We propose that non-conventional MRI might help optimise diagnosis in these challenging patients.

Connection between microstructural alterations detected by diffusion MRI and cognitive dysfunction in MS: A model-free analysis approach

BACKGROUND

Cognitive decline is a prominent symptom of MS. Clear connection between cognitive status and white matter microstructural changes has not been unequivocally observed to date.

OBJECTIVE

To characterise the relationship between white matter microstructure and cognitive performance a partial least squares (PLS) approach was used.

METHODS

53 RR MS patients' T1 and DTI images and BICAMS subtests were used in our analysis. Standard FSL pipeline was used to obtain diffusion parameters. A PLS approach was applied to reveal the diffusion parameter patterns responsible for the cognitive dysfunction.

RESULTS

The first latent variable (LV) was mainly associated with demyelination, while the second and third explained axonal damage. While the first two LV represented mainly Brief Visuospatial Memory Test (BVMT) and Single Digit Modality Test (SDMT), the third LV depicted diffusion alterations mainly the verbal subtest. The first LVs spatial map showed demyelination in the corpus callosum. The second LVs spatial map showed the diffusion alterations in the thalamus. The third LV depicted diffusion alterations in the putative left superior longitudinal fascicle.

CONCLUSION

Visual memory demanding tasks versus language functions depend on distinct patterns of diffusion parameters and the spatial organisation. Axial diffusivity alterations, a putative marker of irreversible axonal loss explained around 20% of variability in the cognitive functions.

Loes Score: Clinical and Radiological Profile of 22 Patients of X-Linked Adrenoleukodystrophy: Case Series from a Single Center

Introduction X-linked adrenoleukodystrophy (X-ALD) is a devastating disease with a wide spectrum of presentation ranging from asymptomatic to a rapidly progressive childhood cerebral form. The gene responsible for adrenoleukodystrophy is ABCD1 gene, required for β oxidation of fatty acids in various tissues. While biochemical and molecular techniques are available to confirm the diagnosis, brain magnetic resonance imaging (MRI) utilizing Loes score has been used for both prognosis and timely direction of hematopoietic stem cell therapy. Materials and Methods During the study period of 2016 to 2020, 22 individuals including 19 individuals with features suggestive of X-ALD and 3 asymptomatic siblings were evaluated from a single center in North India. After biochemical and molecular confirmation of the disease, detailed clinical and radiological findings using MRI brain were documented. A radiological scoring pattern proposed by Loes was employed to identify the severity of the disorder. Results The most common clinical presentations were visual difficulty and muscular weakness (58%). All symptomatic individuals had classic neuroimaging findings in the form of hyperintensities involving the parieto-occipital area and splenium of corpus callosum. Severe involvement in the form of global atrophy was observed in 52.6% of individuals. Asymptomatic siblings also showed neurological involvement based on MRI with highest Loes score of 9 in one individual. Conclusion This case series describes the clinical and radiological profile and employment of Loes score in individuals with X-ALD. Early identification of asymptomatic individuals by neuroimaging and use of Loes severity score for monitoring and disease progression will help in making therapeutic decisions in a timely manner.

Diffusion tensor imaging reveals neuronal microstructural changes in myalgic encephalomyelitis/chronic fatigue syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) patients suffer from a variety of physical and neurological complaints indicating the central nervous system plays a role in ME/CFS pathophysiology. Diffusion tensor imaging (DTI) has been used to study microstructural changes in neurodegenerative diseases. In this study, we evaluated DTI parameters to investigate microstructural abnormalities in ME/CFS patients. We estimated DTI parameters in 25 ME/CFS patients who met Fukuda criteria (ME/CFS_Fukuda ), 18 ME/CFS patients who met International Consensus Criteria (ICC) (ME/CFS_ICC ) only and 26 healthy control (HC) subjects. In addition to voxel-based DTI-parameter group comparisons, we performed voxel-based DTI-parameter interaction-with-group regressions with clinical and autonomic measures to test for abnormal regressions. Group comparisons between ME/CFS_ICC and HC detected significant clusters (a) with decreased axial diffusivity (p = .001) and mean diffusivity (p = .01) in the descending cortico-cerebellar tract in the midbrain and pons and (b) with increased transverse diffusivity in the medulla. The mode of anisotropy was significantly decreased (p = .001) in a cluster in the superior longitudinal fasciculus region. Voxel-based group comparisons between ME/CFS_Fukuda and HC did not detect significant clusters. For ME/CFS_ICC and HC, DTI parameter interaction-with-group regressions were abnormal for the clinical measures of information processing score, SF36 physical, sleep disturbance score and respiration rate in both grey and white matter regions. Our study demonstrated that DTI parameters are sensitive to microstructural changes in ME/CFS_ICC and could potentially act as an imaging biomarker of abnormal pathophysiology in ME/CFS. The study also shows that strict case definitions are essential in investigation of the pathophysiology of ME/CFS.

Impact of the acquisition protocol on the sensitivity to demyelination and axonal loss of clinically feasible DWI techniques: a simulation study

OBJECTIVE

To evaluate: (a) the specific effect that the demyelination and axonal loss have on the DW signal, and (b) the impact of the sequence parameters on the sensitivity to damage of two clinically feasible DWI techniques, i.e. DKI and NODDI.

METHODS

We performed a Monte Carlo simulation of water diffusion inside a novel synthetic model of white matter in the presence of axonal loss and demyelination, with three compartments with permeable boundaries between them. We compared DKI and NODDI in their ability to detect and assess the damage, using several acquisition protocols. We used the F test statistic as an index of the sensitivity for each DWI parameter to axonal loss and demyelination, respectively.

RESULTS

DKI parameters significantly changed with increasing axonal loss, but, in most cases, not with demyelination; all the NODDI parameters showed sensitivity to both the damage processes (at p < 0.01). However, the acquisition protocol strongly affected the sensitivity to damage of both the DKI and NODDI parameters and, especially for NODDI, the parameter absolute values also.

DISCUSSION

This work is expected to impact future choices for investigating white matter microstructure in focusing on specific stages of the disease, and for selecting the appropriate experimental framework to obtain optimal data quality given the purpose of the experiment.

White matter correlates of slowed information processing speed in unimpaired multiple sclerosis patients with young age onset

Slowed information processing speed is among the earliest markers of cognitive impairment in multiple sclerosis (MS) and has been associated with white matter (WM) structural integrity. Localization of WM tracts associated with slowing, but not significant impairment, on specific cognitive tasks in pediatric and young age onset MS can facilitate early and effective therapeutic intervention. Diffusion tensor imaging data were collected on 25 MS patients and 24 controls who also underwent the Symbol Digit Modalities Test (SDMT) and the computer-based Cogstate simple and choice reaction time tests. Fractional anisotropy (FA), mean (MD), radial (RD) and axial (AD) diffusivities were correlated voxel-wise with processing speed measures. All DTI metrics of several white matter tracts were significantly different between groups (p < 0.05). Notably, higher MD, RD, and AD, but not FA, in the corpus callosum correlated with lower scores on both SDMT and simple reaction time. Additionally, all diffusivity metrics in the left corticospinal tract correlated negatively with SDMT scores, whereas only MD in the right superior fronto-occipital fasciculus correlated with simple reaction time. In conclusion, subtle slowing of processing speed is correlated with WM damage in the visual-motor processing pathways in patients with young age of MS onset.

Contrast-Free Detection of Focused Ultrasound-Induced Blood-Brain Barrier Opening Using Diffusion Tensor Imaging

OBJECTIVE

Focused ultrasound (FUS) has emerged as a non-invasive technique to locally and reversibly disrupt the blood-brain barrier (BBB). Here, we investigate the use of diffusion tensor imaging (DTI) as a means of detecting FUS-induced BBB opening at the absence of an MRI contrast agent. A non-human primate (NHP) was repeatedly treated with FUS and preformed circulating microbubbles to transiently disrupt the BBB (n = 4). T1- and diffusion-weighted MRI scans were acquired after the ultrasound treatment, with and without gadolinium-based contrast agent, respectively. Both scans were registered with a high-resolution T1-weighted scan of the NHP to investigate signal correlations. DTI detected an increase in fractional anisotropy from 0.21 ± 0.02 to 0.38 ± 0.03 (82.6 ± 5.2% change) within the targeted area one hour after BBB opening. Enhanced DTI contrast overlapped by 77.22 ± 9.2% with hyper-intense areas of gadolinium-enhanced T1-weighted scans, indicating diffusion anisotropy enhancement only within the BBB opening volume. Diffusion was highly anisotropic and unidirectional within the treated brain region, as indicated by the direction of the principal diffusion eigenvectors. Polar and azimuthal angle ranges decreased by 35.6% and 82.4%, respectively, following BBB opening. Evaluation of the detection methodology on a second NHP (n = 1) confirmed the across-animal feasibility of the technique. In conclusion, DTI may be used as a contrast-free MR imaging modality in lieu of contrast-enhanced T1 mapping for detecting BBB opening during focused-ultrasound treatment or evaluating BBB integrity in brain-related pathologies.

Diffusion tensor imaging reveals greater microstructure damage in lesional tissue that shrinks into cerebrospinal fluid in multiple sclerosis

BACKGROUND AND PURPOSE

Atrophied T2 lesion volume (LV), reflecting the complete transformation of lesions into cerebrospinal fluid (CSF), has been associated with disease progression in multiple sclerosis (MS). The underlying damage leading to lesion destruction remains poorly understood. The objective of this study was to use diffusion tensor imaging (DTI) to investigate the extent of microstructural tissue damage at baseline in lesions that subsequently transform into CSF.

METHODS

Ninety-nine MS patients (67 relapsing-remitting MS [RRMS] and 32 progressive PMS [PMS]) were imaged at baseline and after an average of 5.3 ± 0.6 years of follow-up. Assessments included T2 LV and DTI at baseline and atrophied T2 LV over follow-up. Lesioned areas that became atrophied T2 LV were compared to those that did not. Baseline lesional DTI metrics were compared between RRMS versus PMS patients and between patients with disability progression (DP, n = 35) versus non-DP (n = 64), using ANCOVA models.

RESULTS

Lesion tissue that developed into atrophied T2 LV had significantly different baseline DTI parameters compared to nonatrophied T2-LV tissue (p<0.001), with the largest effect for free-water (d = 2.739). Baseline tissue characteristics of future atrophied T2 LV were not significantly different between groups. However, DP patients developed greater atrophied T2 LV (377 vs. 83 mm³ , p < 0.001).

CONCLUSIONS

Extensive microstructural damage characterizes lesions replaced by CSF, independently of disease phenotype or future DP. Greater atrophied T2 LV predicts DP.

Cortical diffusion kurtosis imaging and thalamic volume are associated with cognitive and walking performance in relapsing-remitting multiple sclerosis

BACKGROUND

In multiple sclerosis (MS), pronounced neurodegeneration manifests itself as cerebral gray matter (GM) atrophy, which is associated with cognitive and physical impairments. Microstructural changes in GM estimated by diffusion kurtosis imaging (DKI) may reveal neurodegeneration that is undetectable by conventional structural MRI and thus serve as a more sensitive marker of disease progression.

OBJECTIVE

The primary objective was to investigate the relationships between morphological and diffusional properties in cerebral GM and physical and cognitive performance in relapsing-remitting MS (RRMS) patients. A secondary objective was to investigate the relationship between GM microstructure and white matter (WM) injury, estimated by the volume of WM lesions.

METHODS

Sixty-seven RRMS patients performed the brief repeatable battery of neuropsychological tests (BRB-N), the 6-minute walk test (6MWT), the six spot step test (SSST), and underwent MRI scans using structural and DKI protocols. GM volumetrics and DKI measurements were analyzed in the cortex and deep GM structures using a general linear model with demographics, physical- and cognitive performance as covariates.

RESULTS

Mean diffusivity (MD) in the cortex was associated with the SSST, 6MWT, information processing, global cognitive performance, and volume of WM lesions. In addition, thalamic volume was associated with SSST (r² = 0.21, 6MWT (r² = 0.18), information processing (r² = 0.21), and WM lesion volume (r² = 0.60).

CONCLUSION

Cortical diffusion and thalamic volume are associated with walking and cognitive performance in RRMS patients and are highly affected by the presence of WM lesions.

Initial findings in traumatic peripheral nerve injury and repair with diffusion tensor imaging

OBJECTIVE

Management of peripheral nerve injuries requires physicians to rely on qualitative measures from patient history, electromyography, and physical exam. Determining a successful nerve repair can take months to years for proximal injuries, and the resulting delays in clinical decision-making can lead to a negative impact on patient outcomes. Early identification of a failed nerve repair could prevent permanent muscle atrophy and loss of function. This study aims to test the feasibility of performing diffusion tensor imaging (DTI) to evaluate injury and recovery following repair of wrist trauma. We hypothesize that DTI provides a noninvasive and reliable assessment of regeneration, which may improve clinical decision-making and alter the clinical course of surgical interventions.

METHODS

Clinical and MRI measurements from subjects with traumatic peripheral nerve injury, carpal tunnel syndrome, and healthy control subjects were compared to evaluate the relationship between DTI metrics and injury severity.

RESULTS

Fractional anisotropy from DTI was sensitive to differences between damaged and healthy nerves, damaged and compressed nerves, and injured and healthy contralateral nerves. Longitudinal measurements in two injury subjects also related to clinical outcomes. Implications of other diffusion measures are also discussed.

INTERPRETATION

DTI is a sensitive tool for wrist nerve injuries and can be utilized for monitoring nerve recovery. Across three subjects with nerve injuries, this study has shown how DTI can detect abnormalities between injured and healthy nerves, measure recovery, and determine if re-operation was successful. Additional comparisons to carpal tunnel syndrome and healthy nerves show that DTI is sensitive to the degree of impairment.

Covariation Between Brain Function (MEG) and Structure (DTI) Differentiates Adolescents with Fetal Alcohol Spectrum Disorder from Typically Developing Controls

The behavioral, cognitive, and sensory difficulties experienced by individuals exposed to alcohol prenatally currently fail to provide early identification for fetal alcohol spectrum disorder (FASD). Attempting to advance this pursuit through a multivariate analysis, we collected magnetoencephalography (MEG) data during auditory, somatosensory, visual paradigms, DTI, and behavior in adolescents ages 12-21 years (FASD: N = 13; HC: N = 20). We assessed the relationship between brain function (MEG) and structure (fractional anisotropy (FA)) utilizing joint independent component analysis (jICA), and examined how this measure relates to behavior. We identified 5 components that reveal group differences in co-variation between MEG and FA. For example, component 5 (t = 3.162, p = 0.003, Hedges' g = 1.13) contained MEG activity corresponding to all three sensory modalities, most robustly in occipital lobes, and DTI-derived cerebellar FA, underlying the role of the cerebellum in sensory processing. Further, in HCs component 5's loading factor was positively correlated with verbal ability (r = 0.646, p = 0.002), indicating higher covariation was associated with better verbal performance. Interestingly, this relationship is lacking in FASD (r = 0.009, p = 0.979). Also, component 5 loading factor negatively correlated with impulsivity (r = -0.527, p = 0.002), indicating that stronger function-structure associations were associated with individuals with lower impulsivity. These findings suggest that multimodal integration of MEG and FA provides novel associations between structure and function that may help differentiate adolescents with FASD from HC.

Characterization of multiple sclerosis lesions with distinct clinical correlates through quantitative diffusion MRI

Diffusion magnetic resonance imaging can reveal quantitative information about the tissue changes in multiple sclerosis. The recently developed multi-compartment spherical mean technique can map different microscopic properties based only on local diffusion signals, and it may provide specific information on the underlying microstructural modifications that arise in multiple sclerosis. Given that the lesions in multiple sclerosis may reflect different degrees of damage, we hypothesized that quantitative diffusion maps may help characterize the severity of lesions "in vivo" and correlate these to an individual's clinical profile. We evaluated this in a cohort of 59 multiple sclerosis patients (62% female, mean age 44.7 years), for whom demographic and disease information was obtained, and who underwent a comprehensive physical and cognitive evaluation. The magnetic resonance imaging protocol included conventional sequences to define focal lesions, and multi-shell diffusion imaging was used with b-values of 1000, 2000 and 3000 s/mm² in 180 encoding directions. Quantitative diffusion properties on a macro- and micro-scale were used to discriminate distinct types of lesions through a k-means clustering algorithm, and the number and volume of those lesion types were correlated with parameters of the disease. The combination of diffusion tensor imaging metrics (fractional anisotropy and radial diffusivity) and multi-compartment spherical mean technique values (microscopic fractional anisotropy and intra-neurite volume fraction) differentiated two type of lesions, with a prediction strength of 0.931. The B-type lesions had larger diffusion changes compared to the A-type lesions, irrespective of their location (P < 0.001). The number of A and B type lesions was similar, although in juxtacortical areas B-type lesions predominated (60%, P < 0.001). Also, the percentage of B-type lesion volume was higher (64%, P < 0.001), indicating that these lesions were larger. The number and volume of B-type lesions was related to the severity of disease evolution, clinical disability and cognitive decline (P = 0.004, Bonferroni correction). Specifically, more and larger B-type lesions were correlated with a worse Multiple Sclerosis Severity Score, cerebellar function and cognitive performance. Thus, by combining several microscopic and macroscopic diffusion properties, the severity of damage within focal lesions can be characterized, further contributing to our understanding of the mechanisms that drive disease evolution. Accordingly, the classification of lesion types has the potential to permit more specific and better-targeted treatment of patients with multiple sclerosis.

Probing myelin content of the human brain with MRI: A review

Rapid and efficient transmission of electric signals among neurons of vertebrates is ensured by myelin-insulating sheaths surrounding axons. Human cognition, sensation, and motor functions rely on the integrity of these layers, and demyelinating diseases often entail serious cognitive and physical impairments. Magnetic resonance imaging radically transformed the way these disorders are monitored, offering an irreplaceable tool to noninvasively examine the brain structure. Several advanced techniques based on MRI have been developed to provide myelin-specific contrasts and a quantitative estimation of myelin density in vivo. Here, the vast offer of acquisition strategies developed to date for this task is reviewed. Advantages and pitfalls of the different approaches are compared and discussed.

Are electrophysiological and oligodendrocyte alterations an element in the development of multiple sclerosis at the same time as or before the immune response?

Efficient communication between the glial cells and neurons is a bi-directional process that is essential for conserving normal functioning in the central nervous system (CNS). Neurons dynamically regulate other brain cells in the healthy brain, yet little is known about the first pathways involving oligodendrocytes and neurons. Oligodendrocytes are the myelin-forming cells in the CNS that are needed for the propagation of action potentials along axons and additionally serve to support neurons by neurotrophic factors (NFTs). In demyelinating diseases, like multiple sclerosis (MS), oligodendrocytes are thought to be the victims. Axonal damage begins early and remains silent for years, and neurological disability develops when a threshold of axonal loss is reached, and the compensatory mechanisms are depleted. Three hypotheses have been proposed to explain axonal damage: 1) the damage is caused by an inflammatory process; 2) there is an excessive accumulation of intra-axonal calcium levels; and, 3) demyelinated axons evolve to a degenerative process resulting from the lack of trophic support provided by myelin or myelin-forming cells. Although MS was traditionally considered to be a white matter disease, the demyelination process also occurs in the cerebral cortex. Recent data supports the notion that initial response is triggered by CNS injury. Thus, the understanding of the role of neuron-glial neurophysiology would help provide us with further explanations. We should take in account the suggestion that MS is in part an autoimmune disease that involves genetic and environmental factors, and the pathological response leads to demyelination, axonal loss and inflammatory infiltrates.

Prognostic Prediction of Dysphagia by Analyzing the Corticobulbar Tract in the Early Stage of Intracerebral Hemorrhage

We investigated the predictive value of the corticobulbar tract (CBT) for dysphagia using diffusion tensor tractography in the early stage of intracerebral hemorrhage (ICH) for dysphagia. Forty-two patients with spontaneous ICH ± intraventricular hemorrhage (IVH) and 22 control subjects were recruited. The patients were classified into three groups: group A-could remove nasogastric tube (NGT) in the acute stage of ICH, group B-could remove NGT within 6 months after onset, and group C-could not remove NGT until 6 months after onset. The CBT were reconstructed, and fractional anisotropy (FA) and tract volume (TV) values were determined. The FA of the CBT in the affected hemisphere in group A was lower than in the control group (p < 0.05). The FA and TV of the CBT in the affected hemisphere in group B were lower than those in the control group (p < 0.05). In group C, the FA and TV in the affected hemisphere and unaffected hemispheres were lower than in the control group (p < 0.05). The TV of the CBT in the affected hemisphere in group B showed a moderate negative correlation with the length of time until NGT removal (r = 0.430, p < 0.05). We found that patients with CBT injuries in both hemispheres were not able to remove the NGT until 6 months after onset, whereas patients who were injured only in the affected hemisphere were able to remove NGT within 6 months of onset. The severity of injury to the CBT in the affected hemisphere appeared to be related to the length of time until NGT removal.

Placental diffusion-weighted MRI in normal pregnancies and those complicated by placental dysfunction due to vascular malperfusion

INTRODUCTION

Our aim was to assess placental function by diffusion-weighted magnetic resonance imaging (MRI) using intravoxel incoherent motion (IVIM) analysis in uncomplicated pregnancies and pregnancies complicated by placental dysfunction.

METHODS

31 normal pregnancies and 9 pregnancies complicated by placental dysfunction (birthweight ≤ -2SD and histological signs of placental vascular malperfusion) were retrieved from our placental MRI research database. MRI was performed at gestational weeks 20.1-40.6 in a 1.5 T system using 10 b-values (0-1000 s/mm²). Regions of interest were drawn covering the entire placenta in five transverse slices. Diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f) were estimated by IVIM analysis.

RESULTS

In normal pregnancies, placental f decreased linearly with gestational age (r = -0.522, p = 0.002) being 26.2% at week 20 and 18.8% at week 40. D and D* were 1.57 ± 0.03 and 31.7 ± 3.1 mm²/s (mean ± SD), respectively, and they were not correlated with gestational age. In complicated pregnancies, f was significantly reduced (mean Z-score = -1.16; p = 0.02) when compared to the group of normal pregnancies, whereas D and D* did not differ significantly between groups. Subgroup analysis demonstrated that f was predominantly reduced in dysfunctional placentas characterized by fetal vascular malperfusion (mean Z-score = -2.11, p < 0.001) rather than maternal vascular malperfusion (mean Z-score = -0.40, p = 0.42). In addition, f was negatively correlated with uterine artery pulsatility index (r = -0.396, p = 0.01).

DISCUSSION

Among parameters obtained by the IVIM analysis, only f revealed significant differences between the normal and the dysfunctional placentas. Subgroup analysis suggests that placental f may be able to discriminate non-invasively between different histological types of vascular malperfusion.

Modeling Resilience to Damage in Multiple Sclerosis: Plasticity Meets Connectivity

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS) characterized by demyelinating white matter lesions and neurodegeneration, with a variable clinical course. Brain network architecture provides efficient information processing and resilience to damage. The peculiar organization characterized by a low number of highly connected nodes (hubs) confers high resistance to random damage. Anti-homeostatic synaptic plasticity, in particular long-term potentiation (LTP), represents one of the main physiological mechanisms underlying clinical recovery after brain damage. Different types of synaptic plasticity, including both anti-homeostatic and homeostatic mechanisms (synaptic scaling), contribute to shape brain networks. In MS, altered synaptic functioning induced by inflammatory mediators may represent a further cause of brain network collapse in addition to demyelination and grey matter atrophy. We propose that impaired LTP expression and pathologically enhanced upscaling may contribute to disrupting brain network topology in MS, weakening resilience to damage and negatively influencing the disease course.

Tractography in the presence of multiple sclerosis lesions

Accurate anatomical localisation of specific white matter tracts and the quantification of their tract-specific microstructural damage in conditions such as multiple sclerosis (MS) can contribute to a better understanding of symptomatology, disease evolution and intervention effects. Diffusion MRI-based tractography is being used increasingly to segment white matter tracts as regions-of-interest for subsequent quantitative analysis. Since MS lesions can interrupt the tractography algorithm’s tract reconstruction, clinical studies frequently resort to atlas-based approaches, which are convenient but ignorant to individual variability in tract size and shape. Here, we revisit the problem of individual tractography in MS, comparing tractography algorithms using: (i) The diffusion tensor framework; (ii) constrained spherical deconvolution (CSD); and (iii) damped Richardson-Lucy (dRL) deconvolution. Firstly, using simulated and in vivo data from 29 MS patients and 19 healthy controls, we show that the three tracking algorithms respond differentially to MS pathology. While the tensor-based approach is unable to deal with crossing fibres, CSD produces spurious streamlines, in particular in tissue with high fibre loss and low diffusion anisotropy. With dRL, streamlines are increasingly interrupted in pathological tissue. Secondly, we demonstrate that despite the effects of lesions on the fibre orientation reconstruction algorithms, fibre tracking algorithms are still able to segment tracts that pass through areas with a high prevalence of lesions. Combining dRL-based tractography with an automated tract segmentation tool on data from 131 MS patients, the corticospinal tracts and arcuate fasciculi could be reconstructed in more than 90% of individuals. Comparing tract-specific microstructural parameters (fractional anisotropy, radial diffusivity and magnetisation transfer ratio) in individually segmented tracts to those from a tract probability map, we show that there is no systematic disease-related bias in the individually reconstructed tracts, suggesting that lesions and otherwise damaged parts are not systematically omitted during tractography. Thirdly, we demonstrate modest anatomical correspondence between the individual and tract probability-based approach, with a spatial overlap between 35 and 55%. Correlations between tract-averaged microstructural parameters in individually segmented tracts and the probability-map approach ranged between r = .53 (p < .001) for radial diffusivity in the right cortico-spinal tract and r = .97 (p < .001) for magnetisation transfer ratio in the arcuate fasciculi. Our results show that MS white matter lesions impact fibre orientation reconstructions but this does not appear to hinder the ability to anatomically reconstruct white matter tracts in MS. Individual tract segmentation in MS is feasible on a large scale and could prove a powerful tool for investigating diagnostic and prognostic markers.

Quantitative magnetic resonance imaging indicates brain tissue alterations in patients after liver transplantation

PURPOSE

To investigate cerebral microstructural alterations in patients treated with calcineurin inhibitors (CNI) after orthotopic liver transplantation (OLT) using quantitative magnetic resonance imaging (qMRI) and a cross-sectional study design.

METHODS

Cerebral qMRI was performed in 85 patients in a median 10 years after OLT compared to 31 healthy controls. Patients were treated with different dosages of CNI or with a CNI-free immunosuppression (CNI-free: n = 19; CNI-low: n = 36; CNI-standard: n = 30). T2-, T2*- and T2'- relaxation times, as well as apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were measured in brain gray and white matter by using the regions of interest method.

RESULTS

In comparison to controls, patients revealed significantly increased T2, T2*, T2', ADC and reduced FA, predominantly in the frontal white matter, indicating microstructural brain alterations represented by increased free water (increased T2), reduced neuronal metabolism (increased T2') and a lower degree of spatial organization of the nervous fibers (reduced FA). CNI-low and CNI-free patients showed more alterations than CNI-standard patients. Analysis of their history revealed impairment of kidney function while under standard CNI dose suggesting that these patients may be more vulnerable to toxic CNI side-effects.

CONCLUSION

Our findings suggest that the individual sensitivity to toxic side effects should be considered when choosing an appropriate immunosuppressive regimen in patients after liver transplantation.

Performing Sparse Regularization and Dimension Reduction Simultaneously in Multimodal Data Fusion

Collecting multiple modalities of neuroimaging data on the same subject is increasingly becoming the norm in clinical practice and research. Fusing multiple modalities to find related patterns is a challenge in neuroimaging analysis. Canonical correlation analysis (CCA) is commonly used as a symmetric data fusion technique to find related patterns among multiple modalities. In CCA-based data fusion, principal component analysis (PCA) is frequently applied as a preprocessing step to reduce data dimension followed by CCA on dimension-reduced data. PCA, however, does not differentiate between informative voxels from non-informative voxels in the dimension reduction step. Sparse PCA (sPCA) extends traditional PCA by adding sparse regularization that assigns zero weights to non-informative voxels. In this study, sPCA is incorporated into CCA-based fusion analysis and applied on neuroimaging data. A cross-validation method is developed and validated to optimize the parameters in sPCA. Different simulations are carried out to evaluate the improvement by introducing sparsity constraint to PCA. Four fusion methods including sPCA+CCA, PCA+CCA, parallel ICA and sparse CCA were applied on structural and functional magnetic resonance imaging data of mild cognitive impairment subjects and normal controls. Our results indicate that sPCA significantly can reduce the impact of non-informative voxels and lead to improved statistical power in uncovering disease-related patterns by a fusion analysis.

Exploratory MRI measures after intravenous autologous culture-expanded mesenchymal stem cell transplantation in multiple sclerosis

Background

Mesenchymal stem cells (MSC) have immunomodulatory and neuro-protective properties and are being studied for treatment of multiple sclerosis (MS). Tractography-based diffusion tensor imaging (DTI), cortical thickness (Cth) and T2 lesion volume (T2LV) can provide insight into treatment effects.

Objective

The objective of this study was to analyse the effects of MSC transplantation in MS on exploratory MRI measures.

Methods

MRIs were obtained from 24 MS patients from a phase 1 open-label study of autologous MSC transplantation. DTI metrics were obtained in lesions and normal-appearing white matter motor tracts (NAWM). T2LV and Cth were derived. Longitudinal evolution of MRI outcomes were modelled using linear mixed effects. Pearson’s correlation was calculated between MRI and clinical measures.

Results

Lesional radial diffusivity (RD) and axial diffusivity (AD) decreased pre-transplant and showed no changes post-transplant. There were mixed trends in NAWM RD and AD pre/post-transplant. Transplantation stabilized T2LV growth. NAWM RD and AD correlated with Cth, T2LV and with leg and arm function but not with cognition. Lesional DTI demonstrated similar but less robust correlations.

Conclusions

Microstructural tissue integrity is altered in MS. DTI changes pre-transplant may be influenced by concomitant lesion accrual. Contributor to DTI stabilization post-transplant is multifactorial. DTI of major motor tracts correlated well with clinical measures, highlighting its sensitivity to clinically meaningful changes.

From micro- to macro-structures in multiple sclerosis: what is the added value of diffusion imaging

Diffusion imaging has been instrumental in understanding damage to the central nervous system as a result of its sensitivity to microstructural changes. Clinical applications of diffusion imaging have grown exponentially over the past couple of decades in many neurological and neurodegenerative diseases, such as multiple sclerosis (MS). For several reasons, MS has been extensively researched using advanced neuroimaging techniques, which makes it an 'example disease' to illustrate the potential of diffusion imaging for clinical applications. In addition, MS pathology is characterized by several key processes competing with each other, such as inflammation, demyelination, remyelination, gliosis and axonal loss, enabling the specificity of diffusion to be challenged. In this review, we describe how diffusion imaging can be exploited to investigate micro-, meso- and macro-scale properties of the brain structure and discuss how they are affected by different pathological substrates. Conclusions from the literature are that larger studies are needed to confirm the exciting results from initial investigations before current trends in diffusion imaging can be translated to the neurology clinic. Also, for a comprehensive understanding of pathological processes, it is essential to take a multiple-level approach, in which information at the micro-, meso- and macroscopic scales is fully integrated.

Evidence of early microstructural white matter abnormalities in multiple sclerosis from multi-shell diffusion MRI

Irreversible white matter (WM) damage, including severe demyelination and axonal loss, is a main determinant of long-term disability in multiple sclerosis (MS). Non-invasive detection of changes in microstructural WM integrity in the disease is challenging since commonly used imaging metrics lack the necessary sensitivity, especially in the early phase of the disease. This study aims at assessing microstructural WM abnormalities in early-stage MS by using ultra-high gradient strength multi-shell diffusion MRI and the restricted signal fraction (FR) from the Composite Hindered and Restricted Model of Diffusion (CHARMED), a metric sensitive to the volume fraction of axons. In 22 early MS subjects (disease duration ≤5 years) and 15 age-matched healthy controls, restricted fraction estimates were obtained through the CHARMED model along with conventional Diffusion Tensor Imaging (DTI) metrics. All imaging parameters were compared cross-sectionally between the MS subjects and controls both in WM lesions and normal-appearing white matter (NAWM). We found a significant reduction in FR focally in WM lesions and widespread in the NAWM in MS patients relative to controls (corrected p < .05). Signal fraction changes in NAWM were not driven by perilesional tissue, nor were they influenced by proximity to the ventricles, challenging the hypothesis of an outside-in pathological process driven by CSF-mediated immune cytotoxic factors. No significant differences were found in conventional DTI parameters. In a cross-validated classification task, FR showed the largest effect size and outperformed all other diffusion imaging metrics in discerning lesions from contralateral NAWM. Taken together, our data provide evidence for the presence of widespread microstructural changes in the NAWM in early MS stages that are, at least in part, unrelated to focal demyelinating lesions. Interestingly, these pathological changes were not yet detectable by conventional diffusion imaging at this early disease stage, highlighting the sensitivity and value of multi-shell diffusion imaging for better characterizing axonal microstructure in MS.

The Contribution of Various MRI Parameters to Clinical and Cognitive Disability in Multiple Sclerosis

Next to the disseminated clinical symptoms, cognitive dysfunctions are common features of multiple sclerosis (MS). Over the recent years several different MRI measures became available representing the various features of the pathology, but the contribution to various clinical and cognitive functions is not yet fully understood. In this multiparametric MRI study we set out to identify the set of parameters that best predict the clinical and cognitive disability in MS. High resolution T1 weighted structural and high angular resolution diffusion MRI images were measured in 53 patients with relapsing remitting MS and 53 healthy controls. Clinical disability was inflicted by EDSS and cognitive functions were evaluated with the BICAMS tests. The contribution of lesion load, partial brain, white matter, gray matter and subcortical volumes as well as the diffusion parameters in the area of the lesions and the normal appearing white matter were examined by model free, partial least square (PLS) approach. Significance of the predictors was tested with Variable Importance in the Projection (VIP) score and 1 was used for threshold of significance. The PLS analysis indicated that the axial diffusivity of the NAWM contributed the most to the clinical disability (VIP score: 1.979). For the visuo-spatial working memory the most critical contributor was the size of the bilateral hippocampi (VIP scores: 1.183 and 1.2 left and right respectively). For the verbal memory the best predictors were the size of the right hippocampus (VIP score: 1.972), lesion load (VIP score: 1.274) and the partial brain volume (VIP score: 1.119). In case of the information processing speed the most significant contribution was from the diffusion parameters (fractional anisotropy, mean and radial diffusivity, VIP scores: 1.615, 1.321 respectively) of the normal appearing white matter. Our results indicate that various MRI measurable factors of MS pathology contribute differently to clinical and cognitive disability. These results point out the importance of the volumetry of the subcortical structures and the diffusion measures of the white matter in understanding the disability progression.

Magnetic Resonance Techniques for Imaging White Matter

The white matter is a complex network of brain fibers connecting different information processing regions in the brain. In recent years, the investigation of white matter in humans and in animal models has greatly benefitted from the introduction of in vivo noninvasive magnetic resonance imaging (MRI) techniques. MRI allows for multiple in vivo time-point whole-brain acquisition in the same subject, thus it can be used longitudinally to monitor white matter brain change, intervention effects, as well as disease progression. However, MRI has low spatial resolution compared to gold standard cellular techniques and MRI measures are sensitive to a number of tissue properties resulting in a lack of specificity.The following chapter describes in simple technical terms to non-imaging experts some common MRI techniques that can be used to investigate white matter structure noninvasively, covering some of the advantages and pitfalls of each technique.

Detecting white matter alterations in multiple sclerosis using advanced diffusion magnetic resonance imaging

Multiple sclerosis is a neurodegenerative and inflammatory disease, a hallmark of which is demyelinating lesions in the white matter. We hypothesized that alterations in white matter microstructures can be non-invasively characterized by advanced diffusion magnetic resonance imaging. Seven diffusion metrics were extracted from hybrid diffusion imaging acquisitions via classic diffusion tensor imaging, neurite orientation dispersion and density imaging, and q-space imaging. We investigated the sensitivity of the diffusion metrics in 36 sets of regions of interest in the brain white matter of six female patients (age 52.8 ± 4.3 years) with multiple sclerosis. Each region of interest set included a conventional T2-defined lesion, a matched perilesion area, and normal-appearing white matter. Six patients with multiple sclerosis (n = 5) or clinically isolated syndrome (n = 1) at a mild to moderate disability level were recruited. The patients exhibited microstructural alterations from normal-appearing white matter transitioning to perilesion areas and lesions, consistent with decreased tissue restriction, decreased axonal density, and increased classic diffusion tensor imaging diffusivity. The findings suggest that diffusion compartment modeling and q-space analysis appeared to be sensitive for detecting subtle microstructural alterations between perilesion areas and normal-appearing white matter.

The relationship between corticospinal tract integrity and lower-extremity strength is attenuated when controlling for age and sex in multiple sclerosis

Muscle weakness, particularly in the lower-extremities, is common in multiple sclerosis (MS) and seemingly results from damage along white matter pathways in the central nervous system including the corticospinal tract (CST). This study examined CST structural integrity indicated by diffusion tensor imaging (DTI) related metrics (fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD], and axial diffusivity [AD]) as correlates of knee flexor (KF) and knee extensor (KE) muscle strength in MS. We included 36 persons with MS who underwent MRI and measurements of peak KE and KF strength using an isokinetic dynamometer. We examined associations using bivariate Spearman (rs) and partial Spearman correlation (prs) analyses controlling for age and sex. Peak KF strength was significantly associated with FA (rs = 0.42) and RD (rs = -0.36) and peak KE strength was significantly associated with MD (rs = -0.47) and RD (rs = -0.36). The correlations were attenuated after controlling for age and sex, but the relationship between KF strength and FA demonstrated a trend towards significance (prs = 0.33, p = 0.056). We provide evidence that the anatomical integrity of the CST may be associated with lower-extremity strength in MS. The attenuated correlations when controlling for age and sex suggest these factors, rather than MS per se, may be important contributors toward an association between CST DTI-metrics and KF and KE strength. Future rehabilitation trials of resistance training should consider including CST integrity as an outcome and/or predictor of strength adaptations.

Characterization of normal-appearing white matter in multiple sclerosis using quantitative susceptibility mapping in conjunction with diffusion tensor imaging

PURPOSE

Quantitative susceptibility mapping (QSM) is influenced by iron as well as myelin, which makes interpretation of pathologic changes challenging. Concurrent acquisition of MR sequences that are sensitive to axonal/myelin integrity, such as diffusion tensor imaging (DTI), may provide context for interpreting quantitative susceptibility (QS) signal. The purpose of our study was to investigate alterations in normal-appearing white matter (NAWM) in multiple sclerosis (MS) using QSM in conjunction with DTI.

METHODS

Twenty relapsing-remitting MS patients and 20 age-matched healthy controls (HC) were recruited for this prospective study. QS, radial diffusivity (RD), fractional anisotropy (FA), and R2* maps within the whole brain as well as individual tracts were generated for comparison between NAWM and HC white matter (HCWM).

RESULTS

MS lesions demonstrated significant differences in QS, FA, RD, and R2* compared to HCWM (p < 0.03). These metrics did not show a significant difference between whole-brain NAWM and HCWM. Among NAWM tracts, the cingulate gyri demonstrated significantly decreased QS compared to HCWM (p = 0.004). The forceps major showed significant differences in FA and RD without corresponding changes in QS (p < 0.01).

CONCLUSION

We found discordant changes in QSM and DTI metrics within the cingulate gyri and forceps major. This may potentially reflect the influence of paramagnetic substrates such as iron, which could be decreased along these NAWM tracts. Our results point to the potential role of QSM as a unique biomarker, although additional validation studies are needed.

Exploring individual multiple sclerosis lesion volume change over time: Development of an algorithm for the analyses of longitudinal quantitative MRI measures

Background

Magnetic resonance imaging (MRI) is used to follow-up multiple sclerosis (MS) and evaluate disease progression and therapy response via lesion quantification. However, there is a lack of automated post-processing techniques to quantify individual MS lesion change.

Objective

The present study developed a secondary post-processing algorithm for MS lesion segmentation routine to quantify individual changes in volume over time.

Methods

An Automatic Follow-up of Individual Lesions (AFIL) algorithm was developed to process time series of pre-segmented binary lesion masks. The resulting consistently labelled lesion masks allowed for the evaluation of individual lesion volumes. Algorithm performance testing was executed in seven early MS patients with four MRI visits, and MS experienced readers verified the accuracy.

Results

AFIL distinguished 328 individual MS lesions with a 0.9% error rate to track persistent or new lesions based on expert assessment. A total of 121 new lesions evolved within the observed time period. The proportional courses of 69.1% lesions in the persistent lesion population exhibited varying volume, 16.9% exhibited stable volume, 3.4% exhibiting continuously increasing, and 0.5% exhibited continuously decreasing volume.

Conclusion

This algorithm tracked individual lesions to automatically create an individual lesion growth profile of MS patients. This approach may allow for characterization of patients based on their individual lesion progression.

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This algorithm can be used for individual tracking of lesion volumes or can read-out parameter changes of quantitative MR images in lesions.

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This method allows the characterization of patients based on their individual lesion growth profile.

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In early MS most lesions had varying volume, few were stable, and very few increased or decreased continuously.

Altered white matter connectivity in patients with schizophrenia: An investigation using public neuroimaging data from SchizConnect

Several studies have produced extensive evidence on white matter abnormalities in schizophrenia (SZ). However, optimum consistency and reproducibility have not been achieved, and reported low white matter tract integrity in patients with SZ varies between studies. A whole-brain imaging study with a large sample size is needed. This study aimed to investigate white matter integrity in the corpus callosum and connections between regions of interests (ROIs) in the same hemisphere in 122 patients with SZ and 129 healthy controls with public neuroimaging data from SchizConnect. For each diffusion-weighted image (DWI), two-tensor full-brain tractography was performed; DWIs were parcellated by processing and registering T1 images with FreeSurfer and Advanced Normalization Tools. White matter query language was used to extract white matter fiber tracts. We evaluated group differences in means of diffusion measures between the patients and controls, and correlations of diffusion measures with the severity of clinical symptoms and cognitive impairment in the patients using the Positive and Negative Syndrome Scale (PANSS), a letter-number sequencing (LNS) test, vocabulary test, letter fluency test, category fluency test, and trail-making test, part A. To correct for multiple comparisons, a false discovery rate of q < 0.05 was applied. In patients with SZ, we observed significant radial diffusivity (RD) and trace (TR) increases in left thalamo-occipital tracts and the right uncinate fascicle, and a significant RD increase in the right middle longitudinal fascicle (MDLF) and the right superior longitudinal fascicle ii. Correlations were present between TR of left thalamo-occipital tracts, and the letter fluency test and the LNS test, and RD in the right MDLF and PANSS positive subscale score. However, these correlations were not significant after correction for multiple comparisons. These results indicated widespread white matter fiber tract abnormalities in patients with SZ, contributing to SZ pathophysiology.

Spatial coherence of oriented white matter microstructure: Applications to white matter regions associated with genetic similarity

We present a method to discover differences between populations with respect to the spatial coherence of their oriented white matter microstructure in arbitrarily shaped white matter regions. This method is applied to diffusion MRI scans of a subset of the Human Connectome Project dataset: 57 pairs of monozygotic and 52 pairs of dizygotic twins. After controlling for morphological similarity between twins, we identify 3.7% of all white matter as being associated with genetic similarity (35.1 k voxels, p<10^-4, false discovery rate 1.5%), 75% of which spatially clusters into twenty-two contiguous white matter regions. Furthermore, we show that the orientation similarity within these regions generalizes to a subset of 47 pairs of non-twin siblings, and show that these siblings are on average as similar as dizygotic twins. The regions are located in deep white matter including the superior longitudinal fasciculus, the optic radiations, the middle cerebellar peduncle, the corticospinal tract, and within the anterior temporal lobe, as well as the cerebellum, brain stem, and amygdalae. These results extend previous work using undirected fractional anisotrophy for measuring putative heritable influences in white matter. Our multidirectional extension better accounts for crossing fiber connections within voxels. This bottom up approach has at its basis a novel measurement of coherence within neighboring voxel dyads between subjects, and avoids some of the fundamental ambiguities encountered with tractographic approaches to white matter analysis that estimate global connectivity.

Evaluation of periprostatic neurovascular fibers before and after radical prostatectomy by means of 1.5 T MRI diffusion tensor imaging

OBJECTIVE

To evaluate if diffusion tensor imaging (DTI) is able to detect changes of periprostatic neurovascular fibers (PNFs) before and after radical prostatectomy (RP), and if these changes are related to post-surgical urinary incontinence and erectile dysfunction.

METHODS

22 patients (mean age 62.6 years) with biopsy-proven prostate cancer underwent 1.5 T DTI before and after RP. The number, fractional anisotropy (FA) values and length of PNFs before and after RP were compared using Student's t-test. Each patient filled out two questionnaires before and after RP, one for the evaluation of urinary continence (ICIQ-SF) and one for the evaluation of erectile function (IIEF-5). The ratios of the number, FA values and length of PNFs before and after RP (DTI B-A RATIOs) and the ratios between the scores obtained before and after RP for both ICIQ-SF and IIEF-2 (ICIQ-SF B-A RATIOs and IIEF-2 B-A RATIOs) were calculated to perform the Kendall's τ-test between them.

RESULTS

There was a statistically significant decrease of the number of PNFs after RP at base, midgland, and apex (p < 0.01) and of FA values at midgland (p < 0.05), with positive statistically significant correlation between the DTI B-A RATIOs of the number of PNFs and IIEF-2 B-A RATIOs (p < 0.05, ρ = 0.47).

CONCLUSION

DTI was able to detect that the decrease of the number of the PNFs after RP was statistically related to the post-surgical erectile dysfunction (p < 0.05). Advances in knowledge: This work demonstrates that: (1) 1.5 T MRI DTI is able to detect the decrease of the number and of the FA of PNFs after prostatectomy; (2) the decrease of the number of PNFs after prostatectomy is related with the post-surgical erectile dysfunction; (3) 1.5 T MRI DTI has demonstrated to be a reproducible technique in detecting the changes of the PNFs induced by RP, with high interobserver agreement.