Harnessing Big Data in Amyotrophic Lateral Sclerosis: Machine Learning Applications for Clinical Practice and Pharmaceutical Trials.

The arrival of genotype-specific therapies in amyotrophic lateral sclerosis (ALS) signals the dawn of precision medicine in motor neuron diseases (MNDs). After decades of academic studies in ALS, we are now witnessing tangible clinical advances. An ever increasing number of well-designed descriptive studies have been published in recent years, characterizing typical disease-burden patterns in vivo and post mortem. Phenotype- and genotype-associated traits and "typical" propagation patterns have been described based on longitudinal clinical and biomarker data. The practical caveat of these studies is that they report "group-level", stereotyped trajectories representative of ALS as a whole. In the clinical setting, however, "group-level" biomarker signatures have limited practical relevance and what matters is the meaningful interpretation of data from a single individual. The increasing availability of large normative data sets, national registries, extant academic data, consortium repositories, and emerging data platforms now permit the meaningful interpretation of individual biomarker profiles and allow the categorization of single patients into relevant diagnostic, phenotypic, and prognostic categories. A variety of machine learning (ML) strategies have been recently explored in MND to demonstrate the feasibility of interpreting data from a single patient. Despite the considerable clinical prospects of classification models, a number of pragmatic challenges need to be overcome to unleash the full potential of ML in ALS. Cohort size limitations, administrative hurdles, data harmonization challenges, regulatory differences, methodological obstacles, and financial implications and are just some of the barriers to readily implement ML in routine clinical practice. Despite these challenges, machine-learning strategies are likely to be firmly integrated in clinical decision-making and pharmacological trials in the near future.

Language deficits in primary lateral sclerosis: cortical atrophy, white matter degeneration and functional disconnection between cerebral regions.

BACKGROUND: Primary lateral sclerosis (PLS) is traditionally regarded as a pure upper motor neuron disorder, but recent cases series have highlighted cognitive deficits in executive and language domains. METHODS: A single-centre, prospective neuroimaging study was conducted with comprehensive clinical and genetic profiling. The structural and functional integrity of language-associated brain regions and networks were systematically evaluated in 40 patients with PLS in comparison to 111 healthy controls. The structural integrity of the arcuate fascicle, frontal aslant tract, inferior occipito-frontal fascicle, inferior longitudinal fascicle, superior longitudinal fascicle and uncinate fascicle was evaluated. Functional connectivity between the supplementary motor region and the inferior frontal gyrus and connectivity between Wernicke's and Broca's areas was also assessed. RESULTS: Cortical thickness reductions were observed in both Wernicke's and Broca's areas. Fractional anisotropy reduction was noted in the aslant tract and increased radical diffusivity (RD) identified in the aslant tract, arcuate fascicle and superior longitudinal fascicle in the left hemisphere. Functional connectivity was reduced along the aslant track, i.e. between the supplementary motor region and the inferior frontal gyrus, but unaffected between Wernicke's and Broca's areas. Cortical thickness alterations, structural and functional connectivity changes were also noted in the right hemisphere. CONCLUSIONS: Disease-burden in PLS is not confined to motor regions, but there is also a marked involvement of language-associated tracts, networks and cortical regions. Given the considerably longer survival in PLS compared to ALS, the impact of language impairment on the management of PLS needs to be carefully considered.

The involvement of language-associated networks, tracts, and cortical regions in frontotemporal dementia and amyotrophic lateral sclerosis: Structural and functional alterations.

BACKGROUND: Language deficits are cardinal manifestations of some frontotemporal dementia (FTD) phenotypes and also increasingly recognized in sporadic and familial amyotrophic lateral sclerosis (ALS). They have considerable social and quality-of-life implications, and adaptive strategies are challenging to implement. While the neuropsychological profiles of ALS-FTD phenotypes are well characterized, the neuronal underpinnings of language deficits are less well studied. METHODS: A multiparametric, quantitative neuroimaging study was conducted to characterize the involvement of language-associated networks, tracts, and cortical regions with a panel of structural, diffusivity, and functional magnetic resonance imaging (MRI) metrics. Seven study groups were evaluated along the ALS-FTD spectrum: healthy controls (HC), individuals with ALS without cognitive impairment (ALSnci), C9orf72-negative ALS-FTD, C9orf72-positive ALS-FTD, behavioral-variant FTD (bvFTD), nonfluent variant primary progressive aphasia (nfvPPA), and semantic variant PPA (svPPA). The integrity of the Broca's area, Wernicke's area, frontal aslant tract (FAT), arcuate fascicle (AF), inferior occipitofrontal fascicle (IFO), inferior longitudinal fascicle (ILF), superior longitudinal fascicle (SLF), and uncinate fascicle (UF) was quantitatively evaluated. The functional connectivity (FC) between Broca's and Wernicke' areas and FC along the FAT was also specifically assessed. RESULTS: Patients with nfvPPA and svPPA exhibit distinctive patterns of gray and white matter degeneration in language-associated brain regions. Individuals with bvFTD exhibit Broca's area, right FAT, right IFO, and UF degeneration. The ALSnci group exhibits Broca's area atrophy and decreased FC along the FAT. Both ALS-FTD cohorts, irrespective of C9orf72 status, show bilateral FAT, AF, and IFO pathology. Interestingly, only C9orf72-negative ALS-FTD patients exhibit bilateral uncinate and right ILF involvement, while C9orf72-positive ALS-FTD patients do not. CONCLUSIONS: Language-associated tracts and networks are not only affected in language-variant FTD phenotypes but also in ALS and bvFTD. Language domains should be routinely assessed in ALS irrespective of the genotype.

Thalamic pathology in frontotemporal dementia: Predilection for specific nuclei, phenotype-specific signatures, clinical correlates, and practical relevance.

BACKGROUND: Frontotemporal dementia (FTD) phenotypes are classically associated with distinctive cortical atrophy patterns and regional hypometabolism. However, the spectrum of cognitive and behavioral manifestations in FTD arises from multisynaptic network dysfunction. The thalamus is a key hub of several corticobasal and corticocortical circuits. The main circuits relayed via the thalamic nuclei include the dorsolateral prefrontal circuit, the anterior cingulate circuit, and the orbitofrontal circuit. METHODS: In this paper, we have reviewed evidence for thalamic pathology in FTD based on radiological and postmortem studies. Original research papers were systematically reviewed for preferential involvement of specific thalamic regions, for phenotype-associated thalamic disease burden patterns, characteristic longitudinal changes, and genotype-associated thalamic signatures. Moreover, evidence for presymptomatic thalamic pathology was also reviewed. Identified papers were systematically scrutinized for imaging methods, cohort sizes, clinical profiles, clinicoradiological associations, and main anatomical findings. The findings of individual research papers were amalgamated for consensus observations and their study designs further evaluated for stereotyped shortcomings. Based on the limitations of existing studies and conflicting reports in low-incidence FTD variants, we sought to outline future research directions and pressing research priorities. RESULTS: FTD is associated with focal thalamic degeneration. Phenotype-specific thalamic traits mirror established cortical vulnerability patterns. Thalamic nuclei mediating behavioral and language functions are preferentially involved. Given the compelling evidence for considerable thalamic disease burden early in the course of most FTD subtypes, we also reflect on the practical relevance, diagnostic role, prognostic significance, and monitoring potential of thalamic metrics in FTD. CONCLUSIONS: Cardinal manifestations of FTD phenotypes are likely to stem from thalamocortical circuitry dysfunction and are not exclusively driven by focal cortical changes.

Neuroimaging in hereditary spastic paraplegias: from qualitative cues to precision biomarkers.

INTRODUCTION: Hereditary spastic paraplegias (HSP) include a clinically and genetically heterogeneous group of conditions. Novel imaging modalities have been increasingly applied to HSP cohorts, which help to develop monitoring markers for both clinical care and future clinical trials. AREAS COVERED: Advances in HSP imaging are systematically reviewed with a focus on cohort sizes, imaging modalities, study design, clinical correlates, methodological approaches, and key findings. EXPERT OPINION: A wide range of imaging techniques have been recently applied to HSP cohorts. Common shortcomings of existing studies include the evaluation of genetically admixed cohorts, limited sample sizes, lack of postmortem validation, and a limited clinical battery. A number of innovative methodological approaches have also been identified, such as robust longitudinal study designs, the implementation of multimodal imaging protocols, complementary cognitive assessments, and the comparison of HSP cohorts to MND cohorts. Collaborative multicenter initiatives may overcome sample limitations, and comprehensive clinical profiling with motor, extrapyramidal, cerebellar, and neuropsychological assessments would permit systematic clinico-radiological correlations. Academic achievements in HSP imaging have the potential to be developed into viable clinical applications to expedite the diagnosis and monitor disease progression.

Pre-symptomatic radiological changes in frontotemporal dementia: propagation characteristics, predictive value and implications for clinical trials.

Computational imaging and quantitative biomarkers offer invaluable insights in the pre-symptomatic phase of neurodegenerative conditions several years before clinical manifestation. In recent years, there has been a focused effort to characterize pre-symptomatic cerebral changes in familial frontotemporal dementias using computational imaging. Accordingly, a systematic literature review was conducted of original articles investigating pre-symptomatic imaging changes in frontotemporal dementia focusing on study design, imaging modalities, data interpretation, control cohorts and key findings. The review is limited to the most common genotypes: chromosome 9 open reading frame 72 (C9orf72), progranulin (GRN), or microtubule-associated protein tau (MAPT) genotypes. Sixty-eight studies were identified with a median sample size of 15 (3-141) per genotype. Only a minority of studies were longitudinal (28%; 19/68) with a median follow-up of 2 (1-8) years. MRI (97%; 66/68) was the most common imaging modality, and primarily grey matter analyses were conducted (75%; 19/68). Some studies used multimodal analyses 44% (30/68). Genotype-associated imaging signatures are presented, innovative study designs are highlighted, common methodological shortcomings are discussed and lessons for future studies are outlined. Emerging academic observations have potential clinical implications for expediting the diagnosis, tracking disease progression and optimising the timing of pharmaceutical trials.

Alterations in somatosensory, visual and auditory pathways in amyotrophic lateral sclerosis: an under-recognised facet of ALS.

BACKGROUND: While amyotrophic lateral sclerosis (ALS) is widely recognised as a multi-network disorder with extensive frontotemporal and cerebellar involvement, sensory dysfunction is relatively under evaluated. Subtle sensory deficits have been sporadically reported, but there is a prevailing notion that sensory pathways may be relatively spared in ALS. METHODS: In a prospective neuroimaging study we have systematically evaluated cerebral grey and white matter structures involved in the processing, relaying and mediation of sensory information. Twenty two C9orf72 positive ALS patients (C9+ ALS), 138 C9orf72 negative ALS patients (C9- ALS) and 127 healthy controls were included. RESULTS: Widespread cortical alterations were observed in C9+ ALS including both primary and secondary somatosensory regions. In C9- ALS, cortical thickness reductions were observed in the postcentral gyrus. Thalamic nuclei relaying somatosensory information as well as the medial and lateral geniculate nuclei exhibited volume reductions. Diffusivity indices revealed posterior thalamic radiation pathology and a trend of left medial lemniscus degeneration was also observed in C9- ALS (p = 0.054). Our radiology data confirm the degeneration of somatosensory, visual and auditory pathways in ALS, which is more marked in GGGGCC hexanucleotide repeat expansion carriers. CONCLUSIONS: In contrast to the overwhelming focus on motor system degeneration and frontotemporal dysfunction in recent research studies, our findings confirm that sensory circuits are also affected in ALS. The involvement of somatosensory, auditory and visual pathways in ALS may have important clinical ramifications which are easily overlooked in the context of unremitting motor decline. Subtle sensory deficits may exacerbate mobility, contribute to fall risk, impair dexterity, and worsen bulbar dysfunction, therefore comprehensive sensory testing should also be performed as part of the clinical assessments in ALS.

Cerebellar remodelling decades after spinal cord insult: neuroplasticity in poliomyelitis survivors.

BACKGROUND: The cerebellum integrates a multitude of motor and cognitive processes through ample spinal and supratentorial projections. Despite emerging evidence of adaptive neuroplasticity, cerebellar reorganisation in response to severe spinal insult early in life is poorly characterised. The objective of this study is the systematic characterisation of cerebellar integrity metrics in a cohort of adult poliomyelitis survivors as a template condition for longstanding lower motor neuron injury. METHODS: A total of 143 participants, comprising 43 adult poliomyelitis survivors and 100 age- and sex-matched healthy controls were recruited in a prospective, single-centre neuroimaging study with a uniform structural and diffusion imaging protocol. First, standard voxelwise grey and white matter analyses were performed. Then, the cerebellum was anatomically segmented into lobules, and cortical thickness and grey matter volumes were evaluated in each lobule. The integrity of cerebellar peduncles was also assessed based on their diffusivity profiles. RESULTS: Compared to healthy controls, poliomyelitis survivors exhibited greater cortical thickness in lobules I, II, and III in the right hemisphere and in lobules VIIIA and VIIIB bilaterally. A trend of higher cortical thickness was also detected lobules I, II and III in the left hemisphere. Enhanced cerebellar peduncle organisation was detected, particularly within the middle cerebellar peduncles. CONCLUSIONS: Increased cerebellar integrity measures in poliomyelitis survivors are primarily identified in lobules associated with sensorimotor functions. The identified pattern of cerebellar reorganisation may represent compensatory changes in response to severe lower motor neuron injury in childhood and ensuing motor disability.

Clusters of anatomical disease-burden patterns in ALS: a data-driven approach confirms radiological subtypes.

Amyotrophic lateral sclerosis (ALS) is associated with considerable clinical heterogeneity spanning from diverse disability profiles, differences in UMN/LMN involvement, divergent progression rates, to variability in frontotemporal dysfunction. A multitude of classification frameworks and staging systems have been proposed based on clinical and neuropsychological characteristics, but disease subtypes are seldom defined based on anatomical patterns of disease burden without a prior clinical stratification. A prospective research study was conducted with a uniform imaging protocol to ascertain disease subtypes based on preferential cerebral involvement. Fifteen brain regions were systematically evaluated in each participant based on a comprehensive panel of cortical, subcortical and white matter integrity metrics. Using min-max scaled composite regional integrity scores, a two-step cluster analysis was conducted. Two radiological clusters were identified; 35.5% of patients belonging to 'Cluster 1' and 64.5% of patients segregating to 'Cluster 2'. Subjects in Cluster 1 exhibited marked frontotemporal change. Predictor ranking revealed the following hierarchy of anatomical regions in decreasing importance: superior lateral temporal, inferior frontal, superior frontal, parietal, limbic, mesial inferior temporal, peri-Sylvian, subcortical, long association fibres, commissural, occipital, 'sensory', 'motor', cerebellum, and brainstem. While the majority of imaging studies first stratify patients based on clinical criteria or genetic profiles to describe phenotype- and genotype-associated imaging signatures, a data-driven approach may identify distinct disease subtypes without a priori patient categorisation. Our study illustrates that large radiology datasets may be potentially utilised to uncover disease subtypes associated with unique genetic, clinical or prognostic profiles.

The changing landscape of neuroimaging in frontotemporal lobar degeneration: from group-level observations to single-subject data interpretation.

INTRODUCTION: While the imaging signatures of frontotemporal lobar degeneration (FTLD) phenotypes and genotypes are well-characterized based on group-level descriptive analyses, the meaningful interpretation of single MRI scans remains challenging. Single-subject MRI classification frameworks rely on complex computational models and large training datasets to categorize individual patients into diagnostic subgroups based on distinguishing imaging features. Reliable individual subject data interpretation is hugely important in the clinical setting to expedite the diagnosis and classify individuals into relevant prognostic categories. AREAS COVERED: This article reviews (1) single-subject MRI classification strategies in symptomatic and pre-symptomatic FTLD, (2) practical clinical implications, and (3) the limitations of current single-subject data interpretation models. EXPERT OPINION: Classification studies in FTLD have demonstrated the feasibility of categorizing individual subjects into diagnostic groups based on multiparametric imaging data. Preliminary data indicate that pre-symptomatic FTLD mutation carriers may also be reliably distinguished from controls. Despite momentous advances in the field, significant further improvements are needed before these models can be developed into viable clinical applications.

Focal thalamus pathology in frontotemporal dementia: Phenotype-associated thalamic profiles.

BACKGROUND: The clinical phenotypes of frontotemporal dementia (FTD) are defined by distinctive clinical features and associated with unique cortical atrophy patterns. Clinical manifestations in FTD however are not solely driven by cortical pathology, but stem from the selective dysfunction of corticobasal circuits, the majority of which are relayed through thalamic nuclei. The objective of this study is the systematic radiological characterisation of thalamic pathology across the clinical spectrum of FTD to describe phenotype-associated thalamic signatures. METHODS: 170 participants were included in a multimodal, prospective neuroimaging study to evaluate thalamic degeneration at a nuclear, vertex, and morphometric level using a uniform imaging protocol and a multimodal analysis approach. RESULTS: Patients with behavioural variant FTD (bvFTD), non-fluent variant primary progressive aphasia (nfvPPA), semantic variant primary progressive aphasia (svPPA) and amyotrophic lateral sclerosis-FTD (ALS-FTD) exhibit distinctive thalamic disease-burden profiles with the preferential degeneration of specific thalamic nuclei. While vertex analyses reveal largely overlapping thalamic atrophy patterns, morphometric analyses successfully capture focal intra-thalamic degeneration. CONCLUSIONS: Mirroring selective cortical vulnerability, focal rather than global thalamic atrophy characterises the clinical subtypes of FTD. Thalamic degeneration is a likely contributor to the heterogeneity of clinical manifestations observed in FTD. As thalamic imaging techniques capture different facets of pathological change and differ in their sensitivity to detect distinguishing features, future studies should implement a multimodal approach with complementary MRI techniques.

White matter microstructure alterations in frontotemporal dementia: Phenotype-associated signatures and single-subject interpretation.

BACKGROUND: Frontotemporal dementias (FTD) include a genetically heterogeneous group of conditions with distinctive molecular, radiological and clinical features. The majority of radiology studies in FTD compare FTD subgroups to healthy controls to describe phenotype- or genotype-associated imaging signatures. While the characterization of group-specific imaging traits is academically important, the priority of clinical imaging is the meaningful interpretation of individual datasets. METHODS: To demonstrate the feasibility of single-subject magnetic resonance imaging (MRI) interpretation, we have evaluated the white matter profile of 60 patients across the clinical spectrum of FTD. A z-score-based approach was implemented, where the diffusivity metrics of individual patients were appraised with reference to demographically matched healthy controls. Fifty white matter tracts were systematically evaluated in each subject with reference to normative data. RESULTS: The z-score-based approach successfully detected white matter pathology in single subjects, and group-level inferences were analogous to the outputs of standard track-based spatial statistics. CONCLUSIONS: Our findings suggest that it is possible to meaningfully evaluate the diffusion profile of single FTD patients if large normative datasets are available. In contrast to the visual review of FLAIR and T2-weighted images, computational imaging offers objective, quantitative insights into white matter integrity changes even at single-subject level.

Propagation patterns in motor neuron diseases: Individual and phenotype-associated disease-burden trajectories across the UMN-LMN spectrum of MNDs.

Motor neuron diseases encompass a divergent group of conditions with considerable differences in clinical manifestations, survival, and genetic vulnerability. One of the key aspects of clinical heterogeneity is the preferential involvement of upper (UMN) and lower motor neurons (LMN). While longitudinal imaging patters are relatively well characterized in ALS, progressive cortical changes in UMN,- and LMN-predominant conditions are seldom evaluated. Accordingly, the objective of this study is the juxtaposition of longitudinal trajectories in 3 motor neuron phenotypes; a UMN-predominant syndrome (PLS), a mixed UMN-LMN condition (ALS), and a lower motor neuron condition (poliomyelitis survivors). A standardized imaging protocol was implemented in a prospective, multi-timepoint longitudinal study with a uniform follow-up interval of 4 months. Forty-five poliomyelitis survivors, 61 patients with amyotrophic lateral sclerosis (ALS), and 23 patients with primary lateral sclerosis (PLS) were included. Cortical thickness alterations were evaluated in a dual analysis pipeline, using standard cortical thickness analyses, and a z-score-based individualized approach. Our results indicate that PLS patients exhibit rapidly progressive cortical thinning primarily in motor regions; ALS patients show cortical atrophy in both motor and extra-motor regions, while poliomyelitis survivors exhibit cortical thickness gains in a number of cerebral regions. Our findings suggest that dynamic cortical changes in motor neuron diseases may depend on relative UMN and/or LMN involvement, and increased cortical thickness in LMN-predominant conditions may represent compensatory, adaptive processes.

Phenotypic categorisation of individual subjects with motor neuron disease based on radiological disease burden patterns: A machine-learning approach.

Motor neuron disease is an umbrella term encompassing a multitude of clinically heterogeneous phenotypes. The early and accurate categorisation of patients is hugely important, as MND phenotypes are associated with markedly different prognoses, progression rates, care needs and benefit from divergent management strategies. The categorisation of patients shortly after symptom onset is challenging, and often lengthy clinical monitoring is needed to assign patients to the appropriate phenotypic subgroup. In this study, a multi-class machine-learning strategy was implemented to classify 300 patients based on their radiological profile into diagnostic labels along the UMN-LMN spectrum. A comprehensive panel of cortical thickness measures, subcortical grey matter variables, and white matter integrity metrics were evaluated in a multilayer perceptron (MLP) model. Additional exploratory analyses were also carried out using discriminant function analyses (DFA). Excellent classification accuracy was achieved for amyotrophic lateral sclerosis in the testing cohort (93.7%) using the MLP model, but poor diagnostic accuracy was detected for primary lateral sclerosis (43.8%) and poliomyelitis survivors (60%). Feature importance analyses highlighted the relevance of white matter diffusivity metrics and the evaluation of cerebellar indices, cingulate measures and thalamic radiation variables to discriminate MND phenotypes. Our data suggest that radiological data from single patients may be meaningfully interpreted if large training data sets are available and the provision of diagnostic probability outcomes may be clinically useful in patients with short symptom duration. The computational interpretation of multimodal radiology datasets herald viable diagnostic, prognostic and clinical trial applications.

Mapping cortical disease-burden at individual-level in frontotemporal dementia: implications for clinical care and pharmacological trials.

Imaging studies of FTD typically present group-level statistics between large cohorts of genetically, molecularly or clinically stratified patients. Group-level statistics are indispensable to appraise unifying radiological traits and describe genotype-associated signatures in academic studies. However, in a clinical setting, the primary objective is the meaningful interpretation of imaging data from individual patients to assist diagnostic classification, inform prognosis, and enable the assessment of progressive changes compared to baseline scans. In an attempt to address the pragmatic demands of clinical imaging, a prospective computational neuroimaging study was undertaken in a cohort of patients across the spectrum of FTD phenotypes. Cortical changes were evaluated in a dual pipeline, using standard cortical thickness analyses and an individualised, z-score based approach to characterise subject-level disease burden. Phenotype-specific patterns of cortical atrophy were readily detected with both methodological approaches. Consistent with their clinical profiles, patients with bvFTD exhibited orbitofrontal, cingulate and dorsolateral prefrontal atrophy. Patients with ALS-FTD displayed precentral gyrus involvement, nfvPPA patients showed widespread cortical degeneration including insular and opercular regions and patients with svPPA exhibited relatively focal anterior temporal lobe atrophy. Cortical atrophy patterns were reliably detected in single individuals, and these maps were consistent with the clinical categorisation. Our preliminary data indicate that standard T1-weighted structural data from single patients may be utilised to generate maps of cortical atrophy. While the computational interpretation of single scans is challenging, it offers unrivalled insights compared to visual inspection. The quantitative evaluation of individual MRI data may aid diagnostic classification, clinical decision making, and assessing longitudinal changes.

Imaging data reveal divergent longitudinal trajectories in PLS, ALS and poliomyelitis survivors: Group-level and single-subject traits.

Imaging profiles from a longitudinal single-centre motor neuron disease study are presented. A standardized T1-weighted MRI protocol was implemented to characterise cortical disease burden trajectories across the UMN (upper motor neuron) - LMN (lower motor neuron) spectrum of motor neuron diseases (MNDs) (Tahedl et al., 2021). Patients with amyotrophic lateral sclerosis (ALS n = 61), patients with primary lateral sclerosis (PLS n = 23) and poliomyelitis survivors (PMS n = 45) were included. Up to four longitudinal scans were available for each patient, separated by an inter-scan-interval of four months. Individual and group-level cortical thickness profiles were appraised using a normalisation procedure with reference to subject-specific control groups. A z-scoring approach was utilised, where each patients' cortex was first segmented into 1000 cortical regions, and then rated as 'thin', 'thick', or 'comparable' to the corresponding region of a demographically-matched control cohort. Fractions of significantly 'thin' and 'thick' patches were calculated across the entire cerebral vertex as well as in specific brain regions, such as the motor cortex, parietal, frontal and temporal cortices. This approach allows the characterisation of disease burden in individual subjects as well as at a group-level, both cross-sectionally and longitudinally. The presented framework may aid the interpretation of individual cortical disease burden in other patient cohorts.

Imaging data indicate cerebral reorganisation in poliomyelitis survivors: Possible compensation for longstanding lower motor neuron pathology.

A standardised, single-centre cross-sectional imaging protocol was utilised to investigate cortical grey matter and cerebral white matter alterations in 36 poliomyelitis survivors in contrast to healthy individuals and patients with amyotrophic lateral sclerosis (ALS) as a 'disease-control' group. [1] T1-weighted imaging and 32-direction diffusion tensor imaging data were obtained on a 3 Tesla Philips Achieva MRI system, using an IR-SPGR sequence and SE-EPI sequence respectively. Raw region-of-interest data and percentage change with respect to reference estimated marginal mean values are presented for grey and white matter metrics in key anatomical regions. Poliomyelitis survivors exhibit no frank grey or white matter degeneration. To the contrary, increased partial volumes can be detected in the brainstem, cerebellum and occipital lobes compared to healthy individuals. Higher fractional anisotropy was also noted in the corticospinal tracts, cerebellum, bilateral mesial temporal lobes and inferior frontal brain regions in poliomyelitis survivors in contrast to controls. Anatomical patterns of superior integrity metrics in polio survivors were concordant with anatomical regions of focal degeneration in ALS. Our imaging data indicate cortical and white matter reorganisation in polio survivors, which may be interpreted as compensatory adaptation to severe lower motor neuron injury acquired in infancy.

Evaluation and categorisation of individual patients based on white matter profiles: Single-patient diffusion data interpretation in neurodegeneration.

The majority of radiology studies in neurodegenerative conditions infer group-level imaging traits from group comparisons. While this strategy is helpful to define phenotype-specific imaging signatures for academic use, the meaningful interpretation of single scans of individual subjects is more important in everyday clinical practice. Accordingly, we present a computational method to evaluate individual subject diffusion tensor data to highlight white matter integrity alterations. Fifty white matter tracts were quantitatively evaluated in 132 patients with amyotrophic lateral sclerosis (ALS) with respect to normative values from 100 healthy subjects. Fractional anisotropy and radial diffusivity alterations were assessed individually in each patient. The approach was validated against standard tract-based spatial statistics and further scrutinised by the assessment of 78 additional data sets with a blinded diagnosis. Our z-score-based approach readily detected white matter degeneration in individual ALS patients and helped to categorise single subjects with a 'blinded diagnosis' as likely 'ALS' or 'control'. The group-level inferences from the z-score-based approach were analogous to the standard TBSS output maps. The benefit of the z-score-based strategy is that it enables the interpretation of single DTI datasets as well as the comparison of study groups. Outputs can be summarised either visually by highlighting the affected tracts, or, listing the affected tracts in a text file with reference to normative data, making it particularly useful for clinical applications. While individual diffusion data cannot be visually appraised, our approach provides a viable framework for single-subject imaging data interpretation.