Use of MRI to measure whole brain atrophy in MS patients

Nowadays magnetic resonance imaging is used for anatomical assessment of human brain structures in neurodegenerative disorders causing brain atrophy for instance in multiple sclerosis (MS) or in Alzheimer Disease. Pathological brain tissue loss can be described in terms of change in the brain parenchymal fraction (BPF). This work shows the impact of segmentation method in SPM12 and additional segmentation in Computational Anatomy Toolbox (CAT12) on calculated BPF value for patients suffer from with MS no treated and treated with disease-modifying drug (DMD) interferon-beta (INFb) for one year and two years. Both methods confirm that brain parenchymal fraction decreases with age, nevertheless for patients not treated INFb decreases faster than for treated. An usability of Lesion Segmentation Tool toolbox in process of automatic detection and segmentation T2 hyperintense lesions in FLAIR images is discussed[…

BRAIM: A computer-aided diagnosis system for neurodegenerative diseases and brain lesion monitoring from volumetric analyses

[EN] Background and objective: This paper presents BRAIM, a computer-aided diagnosis (CAD) system to help clinicians in diagnosing and treatment monitoring of brain diseases from magnetic resonance image processing. BRAIM can be used for early diagnosis of neurodegenerative diseases such as Parkinson, Alzheimer or Multiple Sclerosis and also for brain lesion diagnosis and monitoring. Methods: The developed CAD system includes different user-friendly tools for segmenting and determining whole brain and brain structure volumes in an easy and accurate way. Specifically, three types of measurements can be performed: (1) total volume of white, gray matter and cerebrospinal fluid; (2) brain structure volumes (volume of putamen, thalamus, hippocampus and caudate nucleus); and (3) brain lesion volumes. Results: As a proof of concept, some study cases were analyzed with the presented system achieving promising results. In addition to be used to quantify treatment effectiveness in patients with brain lesions, it was demonstrated that BRAIM is able to classify a subject according to the brain volume measurements using as reference a healthy control database created for this purpose. Conclusions: The CAD system presented in this paper simplifies the daily work of clinicians and provides them with objective and quantitative volume data for prospective and retrospective analyses. (C) 2017 Elsevier B.V. All rights reserved.This work has been supported by the Centro para el Desarrollo Tecnologico Industrial (CDTI) under the project BRAIM (IDI-20130020)Morales, S.; Bernabeu-Sanz, A.; López-Mir, F.; Gonzalez, P.; Luna, L.; Naranjo Ornedo, V. (2017). BRAIM: A computer-aided diagnosis system for neurodegenerative diseases and brain lesion monitoring from volumetric analyses. Computer Methods and Programs in Biomedicine. 145:167-179. https://doi.org/10.1016/j.cmpb.2017.04.006S16717914

T1/T2-weighted ratio in multiple sclerosis: A longitudinal study with clinical associations

Clinically isolated syndrome; Magnetic resonance imaging; Multiple sclerosisSíndrome clínicamente aislado; Imágenes por resonancia magnética; Esclerosis múltipleSíndrome clínicament aïllat; Imatges per ressonància magnètica; Esclerosi múltipleBackground T1w/T2-w ratio has been proposed as a clinically feasible MRI biomarker to assess tissue integrity in multiple sclerosis. However, no data is available in the earliest stages of the disease and longitudinal studies analysing clinical associations are scarce. Objective To describe longitudinal changes in T1-w/T2-w in patients with clinically isolated syndrome (CIS) and multiple sclerosis, and to investigate their clinical associations. Methods T1-w/T2-w images were generated and the mean value obtained in the corresponding lesion, normal-appearing grey (NAGM) and white matter (NAWM) masks. By co-registering baseline to follow-up MRI, evolved lesions were assessed; and by placing the mask of new lesions to the baseline study, the pre-lesional tissue integrity was measured. Results We included 171 CIS patients and 22 established multiple sclerosis patients. In CIS, evolved lesions showed significant T1-w/T2-w increases compared to baseline (+7.6%, P < 0.001). T1-w/T2-w values in new lesions were lower than in pre-lesional tissue (-28.2%, P < 0.001), and pre-lesional tissue was already lower than baseline NAWM (-7.8%, P < 0.001). In CIS at baseline, higher NAGM T1-w/T2-w was associated with multiple sclerosis diagnosis, and longitudinal decreases in NAGM and NAWM T1-w/T2-w were associated with disease activity. In established multiple sclerosis, T1-w/T2-w was inversely correlated with clinical disability and disease duration. Conclusion A decrease in T1-w/T2-w ratio precedes lesion formation. In CIS, higher T1-w/T2-w was associated with multiple sclerosis diagnosis. In established multiple sclerosis, lower T1-w/T2-w values were associated with clinical disability. The possible differential impact of chronic inflammation, iron deposition and demyelination should be considered to interpret these findings.This project was developed as a part of Mateus Boaventura ECTRIMS Clinical Training Fellowship Programme 2018–2019. This study was partially supported by the Project PI18/00823, from the Fondo de Investigación Sanitaria (FIS), Instituto de Salud Carlos III

Characterizing 1-year development of cervical cord atrophy across different MS phenotypes: A voxel-wise, multicentre analysis

Background: Spatio-temporal evolution of cord atrophy in multiple sclerosis (MS) has not been investigated yet. Objective: To evaluate voxel-wise distribution and 1-year changes of cervical cord atrophy in a multicentre MS cohort. Methods: Baseline and 1-year 3D T1-weighted cervical cord scans and clinical evaluations of 54 healthy controls (HC) and 113 MS patients (14 clinically isolated syndromes (CIS), 77 relapsing-remitting (RR), 22 progressive (P)) were used to investigate voxel-wise cord volume loss in patients versus HC, 1-year volume changes and clinical correlations (SPM12). Results: MS patients exhibited baseline cord atrophy versus HC at anterior and posterior/lateral C1/C2 and C4–C6 (p < 0.05, corrected). While CIS patients showed baseline volume increase at C4 versus HC (p < 0.001, uncorrected), RRMS exhibited posterior/lateral C1/C2 atrophy versus CIS, and PMS showed widespread cord atrophy versus RRMS (p < 0.05, corrected). At 1 year, 13 patients had clinically worsened. Cord atrophy progressed in MS, driven by RRMS, at posterior/lateral C2 and C3–C6 (p < 0.05, corrected). CIS patients showed no volume changes, while PMS showed circumscribed atrophy progression. Baseline cord atrophy at posterior/lateral C1/C2 and C3–C6 correlated with concomitant and 1-year disability (r = −0.40/–0.62, p < 0.05, corrected). Conclusions: Voxel-wise analysis characterized spinal cord neurodegeneration over 1 year across MS phenotypes and helped to explain baseline and 1-year disability

Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study

Atrofia; IRM; Esclerosis múltipleAtròfia; IRM; Esclerosi múltipleAtrophy; MRI; Multiple SclerosisBackground and rationale Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. Methods Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. Results In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values < 0.001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0.23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings. Conclusion Automated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings.The study was funded by the Nauta fonds through a travel grant. The MS Center Amsteram is supported by the Dutch MS Research Foundation through a program grant (current grant 18-358f). D.B. is supported by project PI18/00823 from the “Fondo de Investigación Sanitaria Carlos III”. F.B. and O.C. are supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. The acquisition of data in London was funded by supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. A sincere thank you to Tom Verhoeven for his editing of the figures

Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis : A multicenter study

Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ ρ =(-0.42)-(-0.76); p- values < 0.001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0.23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings. Automated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings

Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study

Background and rationale: Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. Methods: Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. Results: In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values < 0.001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0.23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings. Conclusion: Automated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings

Agreement of MSmetrix with established methods for measuring cross-sectional and longitudinal brain atrophy

Introduction Despite the recognized importance of atrophy in multiple sclerosis (MS), methods for its quantification have been mostly restricted to the research domain. Recently, a CE labelled and FDA approved MS-specific atrophy quantification method, MSmetrix, has become commercially available. Here we perform a validation of MSmetrix against established methods in simulated and in vivo MRI data. Methods Whole-brain and gray matter (GM) volume were measured with the cross-sectional pipeline of MSmetrix and compared to the outcomes of FreeSurfer (cross-sectional pipeline), SIENAX and SPM. For this comparison we investigated 20 simulated brain images, as well as in vivo data from 100 MS patients and 20 matched healthy controls. In fifty of the MS patients a second time point was available. In this subgroup, we additionally analyzed the whole-brain and GM volume change using the longitudinal pipeline of MSmetrix and compared the results with those of FreeSurfer (longitudinal pipeline) and SIENA. Results In the simulated data, SIENAX displayed the smallest average deviation compared with the reference whole-brain volume (+ 19.56 ± 10.34 mL), followed by MSmetrix (− 38.15 ± 17.77 mL), SPM (− 42.99 ± 17.12 mL) and FreeSurfer (− 78.51 ± 12.68 mL). A similar pattern was seen in vivo. Among the cross-sectional methods, Deming regression analyses revealed proportional errors particularly in MSmetrix and SPM. The mean difference percentage brain volume change (PBVC) was lowest between longitudinal MSmetrix and SIENA (+ 0.16 ± 0.91%). A strong proportional error was present between longitudinal percentage gray matter volume change (PGVC) measures of MSmetrix and FreeSurfer (slope = 2.48). All longitudinal methods were sensitive to the MRI hardware upgrade that occurred during the time of the study. Conclusion MSmetrix, FreeSurfer, FSL and SPM show differences in atrophy measurements, even at the whole-brain level, that are large compared to typical atrophy rates observed in MS. Especially striking are the proportional errors between methods. Cross-sectional MSmetrix behaved similarly to SPM, both in terms of mean volume difference as well as proportional error. Longitudinal MSmetrix behaved most similar to SIENA. Our results indicate that brain volume measurement and normalization from T1-weighted images remains an unsolved problem that requires much more attention

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

Automated detection of lupus white matter lesions in MRI

Brain magnetic resonance imaging provides detailed information which can be used to detect and segment white matter lesions (WML). In this work we propose an approach to automatically segment WML in Lupus patients by using T1w and fluid-attenuated inversion recovery (FLAIR) images. Lupus WML appear as small focal abnormal tissue observed as hyperintensities in the FLAIR images. The quantification of these WML is a key factor for the stratification of lupus patients and therefore both lesion detection and segmentation play an important role. In our approach, the T1w image is first used to classify the three main tissues of the brain, white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF), while the FLAIR image is then used to detect focal WML as outliers of its GM intensity distribution. A set of post-processing steps based on lesion size, tissue neighborhood, and location are used to refine the lesion candidates. The proposal is evaluated on 20 patients, presenting qualitative, and quantitative results in terms of precision and sensitivity of lesion detection [True Positive Rate (62%) and Positive Prediction Value (80%), respectively] as well as segmentation accuracy [Dice Similarity Coefficient (72%)]. Obtained results illustrate the validity of the approach to automatically detect and segment lupus lesions. Besides, our approach is publicly available as a SPM8/12 toolbox extension with a simple parameter configuration