Cerebellum and neurodegenerative diseases: Beyond conventional magnetic resonance imaging

The cerebellum plays a key role in movement control and in cognition and cerebellar involvement is described in several neurodegenerative diseases. While conventional magnetic resonance imaging (MRI) is widely used for brain and cerebellar morphologic evaluation, advanced MRI techniques allow the investigation of cerebellar microstructural and functional characteristics. Volumetry, voxel-based morphometry, diffusion MRI based fiber tractography, resting state and task related functional MRI, perfusion, and proton MR spectroscopy are among the most common techniques applied to the study of cerebellum. In the present review, after providing a brief description of each technique's advantages and limitations, we focus on their application to the study of cerebellar injury in major neurodegenerative diseases, such as multiple sclerosis, Parkinson's and Alzheimer's disease and hereditary ataxia. A brief introduction to the pathological substrate of cerebellar involvement is provided for each disease, followed by the review of MRI studies exploring structural and functional cerebellar abnormalities and by a discussion of the clinical relevance of MRI measures of cerebellar damage in terms of both clinical status and cognitive performance

Cerebellum and neurodegenerative diseases: Beyond conventional magnetic resonance imaging

The cerebellum plays a key role in movement control and in cognition and cerebellar involvement is described in several neurodegenerative diseases. While conventional magnetic resonance imaging (MRI) is widely used for brain and cerebellar morphologic evaluation, advanced MRI techniques allow the investigation of cerebellar microstructural and functional characteristics. Volumetry, voxel-based morphometry, diffusion MRI based fiber tractography, resting state and task related functional MRI, perfusion, and proton MR spectroscopy are among the most common techniques applied to the study of cerebellum. In the present review, after providing a brief description of each technique's advantages and limitations, we focus on their application to the study of cerebellar injury in major neurodegenerative diseases, such as multiple sclerosis, Parkinson's and Alzheimer's disease and hereditary ataxia. A brief introduction to the pathological substrate of cerebellar involvement is provided for each disease, followed by the review of MRI studies exploring structural and functional cerebellar abnormalities and by a discussion of the clinical relevance of MRI measures of cerebellar damage in terms of both clinical status and cognitive performance

Fully Bayesian Inference for Structural MRI: Application to Segmentation and Statistical Analysis of T2-Hypointensities.

Aiming at iron-related T2-hypointensity, which is related to normal aging and neurodegenerative processes, we here present two practicable approaches, based on Bayesian inference, for preprocessing and statistical analysis of a complex set of structural MRI data. In particular, Markov Chain Monte Carlo methods were used to simulate posterior distributions. First, we rendered a segmentation algorithm that uses outlier detection based on model checking techniques within a Bayesian mixture model. Second, we rendered an analytical tool comprising a Bayesian regression model with smoothness priors (in the form of Gaussian Markov random fields) mitigating the necessity to smooth data prior to statistical analysis. For validation, we used simulated data and MRI data of 27 healthy controls (age: [Formula: see text]; range, [Formula: see text]). We first observed robust segmentation of both simulated T2-hypointensities and gray-matter regions known to be T2-hypointense. Second, simulated data and images of segmented T2-hypointensity were analyzed. We found not only robust identification of simulated effects but also a biologically plausible age-related increase of T2-hypointensity primarily within the dentate nucleus but also within the globus pallidus, substantia nigra, and red nucleus. Our results indicate that fully Bayesian inference can successfully be applied for preprocessing and statistical analysis of structural MRI data

Magnetic resonance imaging techniques for diagnostics in Parkinson’s disease and atypical parkinsonism

Background: Parkinson’s disease (PD) is a neurodegenerative disease characterized by rigidity, hypokinesia, tremor and postural instability. PD is a clinical diagnosis based on neurological examination, patient history and treatment response. Similar symptoms can be caused by other movement disorders such as progressive supranuclear palsy (PSP) and multiple system atrophy (MSA), making it difficult to clinically separate them in early stages. However, these diseases differ in underlying pathology, treatment and prognosis. PSP and MSA have more rapid deterioration and develop additional symptoms such as impaired eye movements or autonomic dysfunction. Magnetic resonance imaging (MRI) is commonly performed as part of the clinical work-up in patients presenting with parkinsonism. There are no overt changes on structural MRI in PD. In atypical parkinsonian syndromes there are typically no visible changes until later disease stages. Purpose: The aim of this thesis is to evaluate novel MRI techniques for diagnostics and for investigation of disease processes in Parkinson’s disease, PSP and MSA. Paper I: A retrospective cohort from Karolinska University Hospital (102 participants; 62 PD, 15 PSP, 11 MSA, 14 controls) was assessed using susceptibility mapping processed from susceptibility weighted imaging. We show that there is elevated susceptibility in the red nucleus and the globus pallidus in PSP compared to PD, MSA and controls. Higher susceptibility levels were also seen in MSA compared to PD in the putamen, and in PD compared to controls in the substantia nigra. Using the red nucleus susceptibility as a diagnostic biomarker, PSP could be separated from PD with an accuracy of 97% (based on the area under the receiver operating characteristic curve, AUC), from MSA with AUC 75% and from controls with AUC 98%. We concluded that susceptibility changes, particularly in the red nucleus in PSP, could be potential biomarkers for differential diagnostics in parkinsonism. Paper II: A prospective cohort from Lund, the BioFINDER study (199 participants; 134 PD, 11 PSP, 10 MSA, 44 controls), was investigated using the susceptibility mapping pipeline developed for Paper I. The finding from Paper I with elevated susceptibility in the red nucleus was validated for PSP compared to PD, MSA and controls. The elevated putaminal susceptibility was also confirmed in MSA compared to PD. The potential role of red nucleus susceptibility as a biomarker for separating PSP from PD and MSA was also similar to the results in Paper I, with AUC 98% for separating PSP from PD and AUC 96% for separating PSP from MSA. We concluded that we could confirm our previous findings from Paper I, with the red nucleus susceptibility being a potential biomarker for separating PSP from PD and MSA. Paper III: A retrospective cohort from Karolinska University Hospital (196 participants; 140 PD, 29 PSP, 27 MSA) was evaluated to employ automated volumetric brainstem segmentation using FreeSurfer. The volumetric approach was compared to manual planimetric measurements: midbrain-pons ratio, magnetic resonance parkinsonism index 1.0 and 2.0. Intra- and inter-scanner as well as intra- and inter-rater reliability were calculated. We found good repeatability in both automated volumetric and manual planimetric measurements. Normalized midbrain volume performed better than the planimetric measurements for separating PSP from PD. We concluded that, if further developed and incorporated in a radiology workflow, automated brainstem volumetry could increase availability of brainstem metrics and possibly save time for radiologists conducting manual measurements. Paper IV: Two cohorts, a retrospective from Karolinska University Hospital (184 participants; 129 PD, 28 PSP, 27 MSA) and a prospective from Lund (185 participants; 125 PD, 11 PSP, 8 MSA, 41 controls), were studied to investigate a new method of creating T1-/T2-weighted ratio images and its diagnostic capabilities in differentiating parkinsonian disorders. In the explorative retrospective cohort, differences in white matter normalized T1-/T2- weighted ratios were seen in the caudate nucleus, putamen, thalamus, subthalamic nucleus and red nucleus in PSP compared to PD; in the caudate nucleus and putamen in MSA compared to PD and in the subthalamic nucleus and the red nucleus in PSP compared to MSA. These differences were validated externally in the prospective cohort, where the changes could be confirmed in the subthalamic nucleus and the red nucleus in PSP compared to PD and MSA. We concluded that there are different patterns of white matter normalized T1-/T2-weighted ratio between the disorders and that this reflects differences in underlying pathophysiology. The T1-/T2-weighted ratio should be further investigated for better understanding of pathological processes in parkinsonian disorders and could possibly be utilized for diagnostic purposes if further developed

Advanced MRI techniques in the study of cerebellar cortex

The cerebellum (from the Latin "little brain") is the dorsal portion of the metencephalon and is located in the posterior cranial fossa. Although representing only 10% of the total brain volume, it contains more than 50% of the total number of neurons of the central nervous system (CNS). Its organization resembles the one found in the telencephalon, with the presence of a superficial mantle of gray matter (GM) known as the cerebellar cortex, covering the cerebellar white matter (WM) in which three pairs of deep cerebellar GM nuclei are embedded. The number of studies dedicated to the study of the cerebellum and its function has significantly increased during the last years. Nevertheless, although many theories on the cerebellar function have been proposed, to date we still are not able to answer the question about the exact function of this structure. Indeed, the classical theories focused on the role of the cerebellum in fine-tuning for muscle control has been widely reconsidered during the last years, with new hypotheses that have been advanced. These include its role as sensory acquisition device, extending beyond a pure role in motor control and learning, as well as a pivotal role in cognition, with a recognized cerebellar participation in a variety of cognitive functions, ranging from mood control to language, memory, attention and spatial data management. A huge contribution to our understanding of how the cerebellum participates in all these different aspects of motor and non-motor behavior comes from the application of advanced imaging techniques. In particular, Magnetic Resonance Imaging (MRI) can provide a non-invasive evaluation of anatomical integrity, as well as information about functional connections with other brain regions. This thesis is organized as follows: - In Chapter 1 is presented a general introduction to the cerebellar anatomy and functions, with particular reference to the anatomical organization of cerebellar cortex and its connections with the telencephalon - Chapter 2 will contain a general overview about some of the major advanced MRI methods that can be applied to investigate the anatomical integrity and functional status of the cerebellar cortex - In Chapter 3 will be presented a new method to evaluate the anatomy and integrity of cerebellar cortex using ultra-high field MRI scanners - Chapters 4, 5 and 6 will contain data obtained from the application of some of the previously described advanced imaging techniques to the study of cerebellar cortex in neurodegenerative and neuroinflammatory disorders affecting the CNS

Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort

Bocchetta et al. quantified brain anomalies on MRI in a large cohort of C9orf72, MAPT, and GRN mutation carriers. They defined the imaging markers associated with the largest clinical and behavioral changes over one year in presymptomatic carriers, providing important data to inform participants' stratification in trials. Biomarkers that can predict disease progression in individuals with genetic frontotemporal dementia are urgently needed. We aimed to identify whether baseline MRI-based grey and white matter abnormalities are associated with different clinical progression profiles in presymptomatic mutation carriers in the GENetic Frontotemporal dementia Initiative. Three hundred eighty-seven mutation carriers were included (160 GRN, 160 C9orf72, 67 MAPT), together with 240 non-carrier cognitively normal controls. Cortical and subcortical grey matter volumes were generated using automated parcellation methods on volumetric 3T T1-weighted MRI scans, while white matter characteristics were estimated using diffusion tensor imaging. Mutation carriers were divided into two disease stages based on their global CDR (R)+NACC-FTLD score: presymptomatic (0 or 0.5) and fully symptomatic (1 or greater). The w-scores in each grey matter volumes and white matter diffusion measures were computed to quantify the degree of abnormality compared to controls for each presymptomatic carrier, adjusting for their age, sex, total intracranial volume, and scanner type. Presymptomatic carriers were classified as 'normal' or 'abnormal' based on whether their grey matter volume and white matter diffusion measure w-scores were above or below the cut point corresponding to the 10th percentile of the controls. We then compared the change in disease severity between baseline and one year later in both the 'normal' and 'abnormal' groups within each genetic subtype, as measured by the CDR (R)+NACC-FTLD sum-of-boxes score and revised Cambridge Behavioural Inventory total score. Overall, presymptomatic carriers with normal regional w-scores at baseline did not progress clinically as much as those with abnormal regional w-scores. Having abnormal grey or white matter measures at baseline was associated with a statistically significant increase in the CDR (R)+NACC-FTLD of up to 4 points in C9orf72 expansion carriers, and 5 points in the GRN group as well as a statistically significant increase in the revised Cambridge Behavioural Inventory of up to 11 points in MAPT, 10 points in GRN, and 8 points in C9orf72 mutation carriers. Baseline regional brain abnormalities on MRI in presymptomatic mutation carriers are associated with different profiles of clinical progression over time. These results may be helpful to inform stratification of participants in future trials