Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis.

Objective: Developing an integrative approach to early treatment response classification using survival modeling and bioinformatics with various biomarkers for early assessment of filgrastim (granulocyte colony stimulating factor) treatment effects in amyotrophic lateral sclerosis (ALS) patients. Filgrastim, a hematopoietic growth factor with excellent safety, routinely applied in oncology and stem cell mobilization, had shown preliminary efficacy in ALS. Methods: We conducted individualized long-term filgrastim treatment in 36 ALS patients. The PRO-ACT database, with outcome data from 23 international clinical ALS trials, served as historical control and mathematical reference for survival modeling. Imaging data as well as cytokine and cellular data from stem cell analysis were processed as biomarkers in a non-linear principal component analysis (NLPCA) to identify individual response. Results: Cox proportional hazard and matched-pair analyses revealed a significant survival benefit for filgrastim-treated patients over PRO-ACT comparators. We generated a model for survival estimation based on patients in the PRO-ACT database and then applied the model to filgrastim-treated patients. Model-identified filgrastim responders displayed less functional decline and impressively longer survival than non-responders. Multimodal biomarkers were then analyzed by PCA in the context of model-defined treatment response, allowing identification of subsequent treatment response as early as within 3 months of therapy. Strong treatment response with a median survival of 3.8 years after start of therapy was associated with younger age, increased hematopoietic stem cell mobilization, less aggressive inflammatory cytokine plasma profiles, and preserved pattern of fractional anisotropy as determined by magnetic resonance diffusion tensor imaging (DTI-MRI). Conclusion: Long-term filgrastim is safe, is well-tolerated, and has significant positive effects on disease progression and survival in a small cohort of ALS patients. Developing and applying a model-based biomarker response classification allows use of multimodal biomarker patterns in full potential. This can identify strong individual treatment responders (here: filgrastim) at a very early stage of therapy and may pave the way to an effective individualized treatment option.

Value of fluid-attenuated inversion recovery MRI data analyzed by the lesion segmentation toolbox in amyotrophic lateral sclerosis.

BACKGROUND: MRI fluid-attenuated inversion recovery (FLAIR) studies reported hyperintensity in the corticospinal tract and corpus callosum of patients with amyotrophic lateral sclerosis (ALS). PURPOSE: To evaluate the lesion segmentation toolbox (LST) for the objective quantification of FLAIR lesions in ALS patients. STUDY TYPE: Retrospective. POPULATION: Twenty-eight ALS patients (eight females, mean age: 50 range: 24-73, mean ALSFRS-R sum score: 36) were compared with 31 age-matched healthy controls (12 females, mean age: 45, range: 25-67). ALS patients were treated with riluzole and additional G-CSF (granulocyte-colony stimulating factor) on a named patient basis. FIELD STRENGTH/SEQUENCE: 1.5 T, FLAIR, T1 -weighted MRI. ASSESSMENT: The lesion prediction algorithm (LPA) of the LST enabled the extraction of individual binary lesion maps, total lesion volume (TLV), and number (TLN). Location and overlap of FLAIR lesions across patients were investigated by registration to FLAIR average space and an atlas. ALS-specific functional rating scale revised (ALSFRS-R), disease progression, and survival since diagnosis served as clinical correlates. STATISTICAL TESTS: Univariate analysis of variance (ANOVA), repeated-measures ANOVA, t-test, Bravais-Pearson correlation, Chi-square test of independence, Kaplan-Meier analysis, Cox-regression analysis. RESULTS: Both ALS patients and healthy controls exhibited FLAIR alterations. TLN significantly depended on age (F(1,54) = 24.659, P < 0.001) and sex (F(1,54) = 5.720, P = 0.020). ALS patients showed higher TLN than healthy controls depending on sex (F(1, 54) = 5.076, P = 0.028). FLAIR lesions were small and most pronounced in male ALS patients. FLAIR alterations were predominantly detected in the superior and posterior corona radiata, anterior capsula interna, and posterior thalamic radiation. Patients with pyramidal tract (PT) lesions exhibited significantly inferior survival than patients without PT lesions (P = 0.013). Covariate age exhibited strong prognostic value for survival (P = 0.015). DATA CONCLUSION: LST enables the objective quantification of FLAIR alterations and is a potential prognostic biomarker for ALS. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:552-559.

Combinatory Biomarker Use of Cortical Thickness, MUNIX, and ALSFRS-R at Baseline and in Longitudinal Courses of Individual Patients With Amyotrophic Lateral Sclerosis.

Objective: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative process affecting upper and lower motor neurons as well as non-motor systems. In this study, precentral and postcentral cortical thinning detected by structural magnetic resonance imaging (MRI) were combined with clinical (ALS-specific functional rating scale revised, ALSFRS-R) and neurophysiological (motor unit number index, MUNIX) biomarkers in both cross-sectional and longitudinal analyses. Methods: The unicenter sample included 20 limb-onset classical ALS patients compared to 30 age-related healthy controls. ALS patients were treated with standard Riluzole and additional long-term G-CSF (Filgrastim) on a named patient basis after written informed consent. Combinatory biomarker use included cortical thickness of atlas-based dorsal and ventral subdivisions of the precentral and postcentral cortex, ALSFRS-R, and MUNIX for the musculus abductor digiti minimi (ADM) bilaterally. Individual cross-sectional analysis investigated individual cortical thinning in ALS patients compared to age-related healthy controls in the context of state of disease at initial MRI scan. Beyond correlation analysis of biomarkers at cross-sectional group level (n = 20), longitudinal monitoring in a subset of slow progressive ALS patients (n = 4) explored within-subject temporal dynamics of repeatedly assessed biomarkers in time courses over at least 18 months. Results: Cross-sectional analysis demonstrated individually variable states of cortical thinning, which was most pronounced in the ventral section of the precentral cortex. Correlations of ALSFRS-R with cortical thickness and MUNIX were detected. Individual longitudinal biomarker monitoring in four slow progressive ALS patients revealed evident differences in individual disease courses and temporal dynamics of the biomarkers. Conclusion: A combinatory use of structural MRI, neurophysiological and clinical biomarkers allows for an appropriate and detailed assessment of clinical state and course of disease of ALS.

White Matter Connectivity of the Visual-Vestibular Cortex Examined by Diffusion-Weighted Imaging.

The parieto-insular vestibular cortex (PIVC) and the posterior insular cortex (PIC) are key regions of the cortical vestibular network, both located in the midposterior section of the lateral sulcus. Little is known about the structural connectivity pattern of these areas. We used probabilistic fiber tracking based on diffusion-weighted magnetic resonance imaging (MRI) and compared the ipsilateral connectivity of PIVC and PIC. Seed areas for the tracking algorithm were identified in each brain by functional MRI activity during caloric and visual motion stimulation, respectively. Cortical track terminations were investigated by a surface-based approach. Both PIVC and PIC shared ipsilateral connections to the insular/lateral sulcus, superior temporal cortex, and inferior frontal gyrus. However, PIVC showed significantly more connections than PIC with the anterior insula and Heschl's gyrus in both hemispheres and with the precuneus, intraparietal sulcus, and posterior callosum of the right hemisphere. In contrast, PIC connectivity was more pronounced with the supramarginal gyrus and superior temporal sulcus. Subcortical tracks were examined by a region-of-interest-based approach, which was validated on cortico-thalamic motor tracts. Both PIVC and PIC were connected with lateral nuclei of the thalamus and the basal ganglia (primarily putamen). PIVC tracks but not PIC tracks showed a right-hemispheric lateralization in cortical and subcortical connectivity. Overall, these results suggest that human PIVC and PIC share cortical and even subcortical connections. Nevertheless, they also differ in their primary connectivity pattern: PIVC is linked with posterior parietal and inferior frontal cortex, whereas PIC is linked with superior temporal and inferior parietal cortex.