Joint Total Variation ESTATICS for Robust Multi-Parameter Mapping

Quantitative magnetic resonance imaging (qMRI) derives tissue-specific parameters -- such as the apparent transverse relaxation rate R2*, the longitudinal relaxation rate R1 and the magnetisation transfer saturation -- that can be compared across sites and scanners and carry important information about the underlying microstructure. The multi-parameter mapping (MPM) protocol takes advantage of multi-echo acquisitions with variable flip angles to extract these parameters in a clinically acceptable scan time. In this context, ESTATICS performs a joint loglinear fit of multiple echo series to extract R2* and multiple extrapolated intercepts, thereby improving robustness to motion and decreasing the variance of the estimators. In this paper, we extend this model in two ways: (1) by introducing a joint total variation (JTV) prior on the intercepts and decay, and (2) by deriving a nonlinear maximum \emph{a posteriori} estimate. We evaluated the proposed algorithm by predicting left-out echoes in a rich single-subject dataset. In this validation, we outperformed other state-of-the-art methods and additionally showed that the proposed approach greatly reduces the variance of the estimated maps, without introducing bias.Comment: 11 pages, 2 figures, 1 table, conference paper, accepted at MICCAI 202

Model-based multi-parameter mapping

Quantitative MR imaging is increasingly favoured for its richer information content and standardised measures. However, computing quantitative parameter maps, such as those encoding longitudinal relaxation rate (R1), apparent transverse relaxation rate (R2*) or magnetisation-transfer saturation (MTsat), involves inverting a highly non-linear function. Many methods for deriving parameter maps assume perfect measurements and do not consider how noise is propagated through the estimation procedure, resulting in needlessly noisy maps. Instead, we propose a probabilistic generative (forward) model of the entire dataset, which is formulated and inverted to jointly recover (log) parameter maps with a well-defined probabilistic interpretation (e.g., maximum likelihood or maximum a posteriori). The second order optimisation we propose for model fitting achieves rapid and stable convergence thanks to a novel approximate Hessian. We demonstrate the utility of our flexible framework in the context of recovering more accurate maps from data acquired using the popular multi-parameter mapping protocol. We also show how to incorporate a joint total variation prior to further decrease the noise in the maps, noting that the probabilistic formulation allows the uncertainty on the recovered parameter maps to be estimated. Our implementation uses a PyTorch backend and benefits from GPU acceleration. It is available at https://github.com/balbasty/nitorch.Comment: 20 pages, 6 figures, accepted at Medical Image Analysi

Simultaneous assessment of regional distributions of atrophy across the neuraxis in MS patients

BACKGROUND: The ability to assess brain and cord atrophy simultaneously would improve the efficiency of MRI to track disease evolution. OBJECTIVE: To test a promising tool to simultaneously map the regional distribution of atrophy in multiple sclerosis (MS) patients across the brain and cord. METHODS: Voxel-based morphometry combined with a statistical parametric mapping probabilistic brain-spinal cord (SPM-BSC) template was applied to standard T1-weighted magnetic resonance imaging (MRI) scans covering the brain and cervical cord from 37 MS patients and 20 healthy controls (HC). We also measured the cord area at C2-C3 with a semi-automatic segmentation method using (i) the same T1-weighted acquisitions used for the new voxel-based analysis and (ii) dedicated spinal cord phase sensitive inversion recovery (PSIR) acquisitions. Cervical cord findings derived from the three approaches were compared to each other and the goodness to fit to clinical scores was assessed by regression analyses. RESULTS: The SPM-BSC approach revealed a severity-dependent pattern of atrophy across the cervical cord and thalamus in MS patients when compared to HCs. The magnitude of cord atrophy was confirmed by the semi-automatic extraction approach at C2-C3 using both standard brain T1-weighted and advanced cord dedicated acquisitions. Associations between atrophy of cord and thalamus with disability and cognition were demonstrated. CONCLUSION: Atrophy in the brain and cervical cord of MS patients can be identified simultaneously and rapidly at the voxel-level. The SPM-BSC approach yields similar results as available standard processing tools with the added advantage of performing the analysis simultaneously and faster

Coherent, time-shifted patterns of microstructural plasticity during motor-skill learning

Motor skill learning relies on neural plasticity in the motor and limbic systems. However, the spatial and temporal characteristics of these changes-and their microstructural underpinnings-remain unclear. Eighteen healthy males received 1 hour of training in a computer-based motion game, 4 times a week, for 4 consecutive weeks, while 14 untrained participants underwent scanning only. Performance improvements were observed in all trained participants. Serial myelin- and iron-sensitive multiparametric mapping at 3T during this period of intensive motor skill acquisition revealed temporally and spatially distributed, performance-related microstructural changes in the grey and white matter across a corticospinal-cerebellar-hippocampal circuit. Analysis of the trajectory of these transient changes suggested time-shifted cascades of plasticity from the dominant sensorimotor system to the contralateral hippocampus. In the cranial corticospinal tracts, changes in myelin-sensitive metrics during training in the posterior limb of the internal capsule were of greater magnitude in those who trained their upper limbs vs. lower limb trainees. Motor skill learning is associated with waves of grey and white matter plasticity, across a broad sensorimotor network

Coherent, time-shifted patterns of microstructural plasticity during motor-skill learning

Motor skill learning relies on neural plasticity in the motor and limbic systems. However, the spatial and temporal characteristics of these changes-and their microstructural underpinnings-remain unclear. Eighteen healthy males received 1 h of training in a computer-based motion game, 4 times a week, for 4 consecutive weeks, while 14 untrained participants underwent scanning only. Performance improvements were observed in all trained participants. Serial myelin- and iron-sensitive multiparametric mapping at 3T during this period of intensive motor skill acquisition revealed temporally and spatially distributed, performance-related microstructural changes in the grey and white matter across a corticospinal-cerebellar-hippocampal circuit. Analysis of the trajectory of these transient changes suggested time-shifted cascades of plasticity from the dominant sensorimotor system to the contralateral hippocampus. In the cranial corticospinal tracts, changes in myelin-sensitive metrics during training in the posterior limb of the internal capsule were of greater magnitude in those who trained their upper limbs vs. lower limb trainees. Motor skill learning is associated with waves of grey and white matter plasticity, across a broad sensorimotor network

Microstructural plasticity in nociceptive pathways after spinal cord injury.

OBJECTIVE To track the interplay between (micro-) structural changes along the trajectories of nociceptive pathways and its relation to the presence and intensity of neuropathic pain (NP) after spinal cord injury (SCI). METHODS A quantitative neuroimaging approach employing a multiparametric mapping protocol was used, providing indirect measures of myelination (via contrasts such as magnetisation transfer (MT) saturation, longitudinal relaxation (R1)) and iron content (via effective transverse relaxation rate (R2*)) was used to track microstructural changes within nociceptive pathways. In order to characterise concurrent changes along the entire neuroaxis, a combined brain and spinal cord template embedded in the statistical parametric mapping framework was used. Multivariate source-based morphometry was performed to identify naturally grouped patterns of structural variation between individuals with and without NP after SCI. RESULTS In individuals with NP, lower R1 and MT values are evident in the primary motor cortex and dorsolateral prefrontal cortex, while increases in R2* are evident in the cervical cord, periaqueductal grey (PAG), thalamus and anterior cingulate cortex when compared with pain-free individuals. Lower R1 values in the PAG and greater R2* values in the cervical cord are associated with NP intensity. CONCLUSIONS The degree of microstructural changes across ascending and descending nociceptive pathways is critically implicated in the maintenance of NP. Tracking maladaptive plasticity unravels the intimate relationships between neurodegenerative and compensatory processes in NP states and may facilitate patient monitoring during therapeutic trials related to pain and neuroregeneration

Development of Image Processing Tools for the Simultaneous Analysis of Brain and Spinal Cord Multi-Parametric Maps: implication for Spinal Cord Injury

Magnetic resonance imaging (MRI) allows to non-invasively characterize brain and spinal cord tissue, in-vivo. This has proven to be a powerful mean to improve diagnostics. Quantitative MRI (qMRI) is an emerging field in MRI which can provide information, not only on the macrostructural aspects of the central nervous systems, as does conventional MRI, but also provides insights into the underlying microstructure. Specifically, quantitative multi-parameter mapping (MPM) provides several maps which are sensitive to myelin, iron and water content. The application of qMRI in the brain has provided crucial insights into how, for example, myelin content is distributed across cortical layers in the visual cortex. However, the application of qMRI techniques in the spinal cord lags behind the brain due to the inherent small size of the cord, low signal-to-noise ratio and the particularly challenging imaging environment characterized by cardiac and respiratory pulsation, proximity of bones, air, cartilage, and fat around the spinal cord. Together, these factors have greatly impacted the quality of spinal cord qMRI and limited its clinical application. Recent technical advances such as specialized acquisition sequences, complex shimming, custom receive coils and substantial post-processing for artefacts correction (i.e. motion, aliasing and others) have made this approach more applicable to the spinal cord. Despite these advances in imaging sequences, few postprocessing tools are available for the analysis of spinal cord qMRI. Common brain software’s are unfortunately not optimized for spinal cord image processing. For example, the deformation of the spinal cord does not allow the application of standard motion-correction algorithms based on rigid or affine transformation, as well as segmentation and registration/normalization tools. In addition, common brain MRI templates and atlases do not include the spinal cord and therefore cannot be used for spinal cord analysis. The aim of this thesis is to promote the clinical adoption of spinal cord qMRI. Specifically, based on brain approaches, new tools for the simultaneous analysis of brain and spinal cord are optimized and applied to investigate microstructural changes after a spinal cord injury (SCI) across the brain and spinal cord, simultaneously. The developed tools are also used to detect the microstructural signature of neuropathic pain in SCI-patients. Additionally, longitudinal pre-processing pipelines were optimized and used to investigate training-induces neuroplasticity in healthy subjects. The methodological and clinical advances from this work have resulted in four studies. 3 In the first study, a processing tool for the simultaneous analysis of brain and cervical spinal cord was implemented in the statistical parametric mapping (SPM) framework. This open source tool allows the investigation of macro- and microstructural changes using voxel-based morphometry (VBM) and voxelbased quantification (VBQ) pipelines, respectively. In order to extend available brain VBM/VBQ pipelines, a new template covering brain and cervical spinal cord was generated using a generative semi-supervised modelling approach. The template was incorporated in the pre-processing pipeline of VBM/VBQ analysis in SPM and was validated on T1-weighted MRI and multi-parameter mapping (MPM) maps, by assessing trauma-induced changes in SCI patients and comparing the findings with the existing outcome from analytical tools assessing the brain and cord, separately. Validation based on a SCI cohort demonstrated that the new processing approach based on the brain and spinal cord is as sensitive as available processing tools in detecting changes in SCI-patients offering the advantage of performing the analysis and statistics simultaneously, in the brain and spinal cord. In the second study, the developed tool for the simultaneous analysis of brain and cervical spinal cord was used to assess the microstructural changes associated with neuropathic-pain (NP) in SCI-patients. In this study, myelin- and iron-sensitive changes along the ascending and descending nociceptive pathways are identified in those patients who suffer from NP when compared to pain-free patients. Crucially, myelin- and iron changes were associated with NP intensity suggesting specific maladaptive plastic processes in the ascending and descending nociceptive pathways. Therefore, tracking microstructural plasticity might facilitate the understanding and monitoring of the complex pathophysiology of NP. In the third study, a longitudinal processing pipeline was optimized for qMRI of the brain and cervical cord and used to assess training induced changes in healthy subjects and SCI-patients. In this thesis we only report findings from healthy controls. This study was motivated by the fact that even if motor training induces neuroplastic changes in the brain, still little is known about the underlying microstructural changes and their dynamics. In this study, training-induced neuroplasticity was investigated in terms of myelin and volume changes. During the acquisition of a motor skill task, transient changes within the motor cortex and its descending projections and in the hippocampus were shown. Performance improvements related to the transient myelin-sensitive changes across the hippocampus suggesting experience-dependent microstructural changes. Interestingly training lower limbs led to greater changes in the myelin-sensitive MT in the posterior part of the internal capsula when compared to upper limb trained participants, suggesting a somatotopy of learning. This study 4 showed that MPM maps can be used not only as a biomarker of neurodegeneration but also for neuroplasticity. In the fourth and last study, MPM maps in the cervical cord of chronic SCI patients were used to quantify a gradient of neurodegenerative changes along the cervical cord by taking advantage of available routines which were optimized for the assessment of MPM from the spinal cord toolbox (SCT). In this study a gradient of neurodegeneration was evident after traumatic SCI; its magnitude is reduced with increasing distance from the lesion level. In addition, the degeneration was more pronounced in the ascending as compared to the descending spinal pathways. The associations with clinical measurements suggest that remote secondary neurodegenerative changes are clinically eloquent and that monitoring the neurodegenerative gradient could track treatment effects of regenerative and neuroprotective agents. In conclusion, several methodological developments and improvements have been addressed in this thesis to facilitate the use of qMRI for spinal cord imaging in health and disease. Specifically, the development of tools for the simultaneous analysis of brain and cervical spinal cord can be used to assess trauma-induced changes, as well as the underlying pathophysiological changes related to neuropathic pain, in SCI-patients; and provide valuable biomarkers that might facilitate patient monitoring, and track treatment effects of regenerative and neuroprotective agents. The optimization of longitudinal processing pipelines for MPM maps provides for the first-time evidence of subtle and transient microstructural changes across a motor-hippocampus loop. Such approach could therefore be used to track the efficacy of rehabilitation

Tracking the neurodegenerative gradient after spinal cord injury

OBJECTIVE: To quantify neurodegenerative changes along the cervical spinal cord rostral to a spinal cord injury (SCI) by means of quantitative MRI (qMRI) and to determine its relationship with clinical impairment. METHODS: Thirty chronic SCI patients (15 tetraplegics and 15 paraplegics) and 23 healthy controls underwent a high-resolution T1-weighted and myelin-sensitive magnetization transfer (MT) MRI. We assessed macro- and microstructural changes along the cervical cord from levels C1 to C4, calculating cross-sectional spinal cord area, its anterior-posterior and left-right width and myelin content (i.e. MT). Regression analysis determined associations between qMRI parameters and clinical impairment. RESULTS: In SCI patients, cord area decreased by 2.67 mm$^{2}$ (p = 0.004) and left-right width decreased by 0.35 mm (p = 0.002) per cervical cord level in the caudal direction when compared to the healthy controls. This gradient of neurodegeneration was greater in tetraplegic than paraplegics in the cross-sectional cervical cord area (by 3.28 mm$^{2}$, p = 0.011), left-right width (by 0.36 mm, p = 0.03), and mean cord MT (by 0.13%, p = 0.04), but independant of lesion severity (p > 0.05). Higher lesion level was associated with greater magnitudes of neurodegeneration. Greater loss in myelin content in the dorsal columns and spinothalamic tract was associated with worse light touch (p = 0.016) and pin prick score (p = 0.024), respectively. CONCLUSIONS: A gradient of neurodegeneration is evident in the cervical cord remote from a SCI. Tract-specific associations with appropriate clinical outcomes highlight that remote neurodegenerative changes are clinically eloquent. Monitoring the neurodegenerative gradient could be used to track treatment effects of regenerative and neuroprotective agents, both in trials targeting cervical and thoracic SCI patients

Simultaneous voxel-wise analysis of brain and spinal cord morphometry and microstructure within the SPM framework

To validate a simultaneous analysis tool for the brain and cervical cord embedded in the statistical parametric mapping (SPM) framework, we compared trauma-induced macro- and microstructural changes in spinal cord injury (SCI) patients to controls. The findings were compared with results obtained from existing processing tools that assess the brain and spinal cord separately. A probabilistic brain-spinal cord template (BSC) was generated using a generative semi-supervised modelling approach. The template was incorporated into the pre-processing pipeline of voxel-based morphometry and voxel-based quantification analyses in SPM. This approach was validated on T1-weighted scans and multiparameter maps, by assessing trauma-induced changes in SCI patients relative to controls and comparing the findings with the outcome from existing analytical tools. Consistency of the MRI measures was assessed using intraclass correlation coefficients (ICC). The SPM approach using the BSC template revealed trauma-induced changes across the sensorimotor system in the cord and brain in SCI patients. These changes were confirmed with established approaches covering brain or cord, separately. The ICC in the brain was high within regions of interest, such as the sensorimotor cortices, corticospinal tracts and thalamus. The simultaneous voxel-wise analysis of brain and cervical spinal cord was performed in a unique SPM-based framework incorporating pre-processing and statistical analysis in the same environment. Validation based on a SCI cohort demonstrated that the new processing approach based on the brain and cord is comparable to available processing tools, while offering the advantage of performing the analysis simultaneously across the neuraxis

Simultaneous assessment of regional distributions of atrophy across the neuraxis in MS patients

BACKGROUND The ability to assess brain and cord atrophy simultaneously would improve the efficiency of MRI to track disease evolution. OBJECTIVE To test a promising tool to simultaneously map the regional distribution of atrophy in multiple sclerosis (MS) patients across the brain and cord. METHODS Voxel-based morphometry combined with a statistical parametric mapping probabilistic brain-spinal cord (SPM-BSC) template was applied to standard T1-weighted magnetic resonance imaging (MRI) scans covering the brain and cervical cord from 37 MS patients and 20 healthy controls (HC). We also measured the cord area at C2-C3 with a semi-automatic segmentation method using (i) the same T1-weighted acquisitions used for the new voxel-based analysis and (ii) dedicated spinal cord phase sensitive inversion recovery (PSIR) acquisitions. Cervical cord findings derived from the three approaches were compared to each other and the goodness to fit to clinical scores was assessed by regression analyses. RESULTS The SPM-BSC approach revealed a severity-dependent pattern of atrophy across the cervical cord and thalamus in MS patients when compared to HCs. The magnitude of cord atrophy was confirmed by the semi-automatic extraction approach at C2-C3 using both standard brain T1-weighted and advanced cord dedicated acquisitions. Associations between atrophy of cord and thalamus with disability and cognition were demonstrated. CONCLUSION Atrophy in the brain and cervical cord of MS patients can be identified simultaneously and rapidly at the voxel-level. The SPM-BSC approach yields similar results as available standard processing tools with the added advantage of performing the analysis simultaneously and faster