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ALS is a neurodegenerative disease characterized by loss of motor neurons, resulting in progressive weakness and wasting of muscles. The average survival time is 2-5 years, mostly due to respiratory failure. Since current therapies can prolong survival time by only a few months, multidisciplinary care remains the cornerstone of the management of ALS. At the ALS Expert Centre of University Hospitals Leuven, a large proportion of Belgian ALS patients are seen for diagnosis and a significant number is also in follow-up with the multidisciplinary team. In this retrospective study, we compared the outcome of incident patients who were in follow-up at our site with patients who were not in follow-up. We included 659 patients of which 557 (84.5%) received specialized care at the ALS Expert Centre. After adjusting for clinically relevant prognostic parameters, multidisciplinary follow-up significantly prolonged survival ( p  = 0.004; HR = 0.683; CI 95% [0.528 - 0.884]). This increase in survival is mainly driven by patients with spinal onset ( p  = 0.035; HR = 0.746; CI 95% [0.568 - 0.980]), since no significant increased survival time was observed in patients with bulbar onset ( p  = 0.28; HR = 0.778; CI 95% [0.495 - 1.223]). These data confirm that multidisciplinary follow-up contributes to a better outcome of patients, emphasizing the importance of multidisciplinary specialized care in ALS.

Objective: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder resulting in upper and lower motor neuron loss. ALS often has a focal onset of weakness, which subsequently spreads to other body regions. Survival is limited to two to five years after disease onset, often due to respiratory failure. Cognitive impairment is present in approximately 30% to 50% of patients and in 10%-15% of patients, the clinical criteria of frontotemporal dementia (FTD) are met., Methods: In this retrospective single-center ALS cohort study, we examined the occurrence of cognitive and behavioral impairment in relation to motor impairment at disease presentation and studied its impact on survival., Results: The degree of lower motor neuron involvement was associated with a worse survival, but there was no effect for upper motor neuron involvement. Patients who were cognitively normal had a significantly better survival compared to patients with cognitive or behavioral impairment and to patients with comorbid FTD. There was no significant difference regarding survival between patients with FTD and patients with cognitive or behavioral impairment., Conclusions: The extent of motor and extramotor involvement in patients with ALS at disease presentation holds complementary prognostic information.

Amyotrophic lateral sclerosis (ALS) is characterized by progressive loss of upper and lower motor neurons. In 10% of patients, the disorder runs in the family. Our aim was to study the impact of ALS-causing gene mutations on cerebral glucose metabolism. Between October 2010 and October 2022, 538 patients underwent genetic testing for mutations with strong evidence of causality for ALS and 18 F-2-fluoro-2-deoxy-D-glucose-PET (FDG PET), at University Hospitals Leuven. We identified 48 C9orf72 -ALS and 22 SOD1 -ALS patients. After propensity score matching, two cohorts of 48 and 21 matched sporadic ALS patients, as well as 20 healthy controls were included. FDG PET images were assessed using a voxel-based and volume-of-interest approach. We observed widespread frontotemporal involvement in all ALS groups, in comparison to healthy controls. The degree of relative glucose metabolism in SOD1 -ALS in motor and extra-motor regions did not differ significantly from matched sporadic ALS patients. In C9orf72 -ALS, we found more pronounced hypometabolism in the peri-rolandic region and thalamus, and hypermetabolism in the medulla extending to the pons, in comparison to matched sporadic ALS patients. Our study revealed C9orf72 -dependent differences in glucose metabolism in the peri-rolandic region, thalamus, and brainstem (i.e., medulla, extending to the pons) in relation to matched sporadic ALS patients.

Apart from well-defined factors in neuronal cells 1 , only a few reports consider that the variability of sporadic amyotrophic lateral sclerosis (ALS) progression can depend on less-defined contributions from glia 2,3 and blood vessels 4 . In this study we use an expression-weighted cell-type enrichment method to infer cell activity in spinal cord samples from patients with sporadic ALS and mouse models of this disease. Here we report that patients with sporadic ALS present cell activity patterns consistent with two mouse models in which enrichments of vascular cell genes preceded microglial response. Notably, during the presymptomatic stage, perivascular fibroblast cells showed the strongest gene enrichments, and their marker proteins SPP1 and COL6A1 accumulated in enlarged perivascular spaces in patients with sporadic ALS. Moreover, in plasma of 574 patients with ALS from four independent cohorts, increased levels of SPP1 at disease diagnosis repeatedly predicted shorter survival with stronger effect than the established risk factors of bulbar onset or neurofilament levels in cerebrospinal fluid. We propose that the activity of the recently discovered perivascular fibroblast can predict survival of patients with ALS and provide a new conceptual framework to re-evaluate definitions of ALS etiology.

Neuroinflammation has been implicated in amyotrophic lateral sclerosis (ALS) and can be visualized using translocator protein (TSPO) radioligands. To become a reliable pharmacodynamic biomarker for ALS multicenter trials, TSPO radioligands have some challenges to overcome. We aimed to investigate whether multicenter data pooling of different TSPO tracers ( 11 C-PBR28 and 18 F-DPA714) is feasible, after validation of an established 11 C-PBR28 PET pseudo reference analysis technique for 18 F-DPA714. Methods: Seven ALS patients from Belgium (58.9 ± 6.7 y old, 5 men and 2 women), 8 healthy volunteers from Belgium (52.1 ± 15.2 y old, 3 men and 5 women), 7 ALS patients from the United States (53.4 ± 9.8 y old, 5 men and 2 women), and 7 healthy volunteers from the United States (54.6 ± 9.6 y old, 4 men and 3 women) from a previously published study underwent dynamic 18 F-DPA714 (Leuven, Belgium) or 11 C-PBR28 (Boston, Massachusetts) PET/MRI. For 18 F-DPA714, maps of total volume of distribution (V T ) were compared with SUV ratio (SUVR) images from 40 to 60 min after injection (SUVR 40-60 ) calculated using the pseudo reference regions cerebellum, occipital cortex, and whole brain (WB) without ventricles. For 11 C-PBR28, SUVR images from 60 to 90 min after injection using the WB without ventricles were calculated. Results: In line with previous studies, increased 18 F-DPA714 uptake (17.0% ± 5.6%) in primary motor cortices was observed in ALS subjects, as measured by both V T and SUVR 40-60 approaches. The highest sensitivity was found for SUVR calculated using the WB without ventricles (average cluster, 21.6% ± 0.1%). 18 F-DPA714 V T ratio was highly correlated with the SUVR 40-60 ( r > 0.8, P < 0.001). A similar pattern of increased uptake (average cluster, 20.5% ± 0.5%) in the primary motor cortices was observed in ALS subjects for 11 C-PBR28 SUVR calculated using the WB without ventricles. Analysis of the 18 F-DPA714 and 11 C-PBR28 data together resulted in a more extensive pattern of significantly increased glial activation bilaterally in the primary motor cortices. Conclusion: The same pseudo reference region analysis technique for 11 C-PBR28 PET can be extended toward 18 F-DPA714 PET. Therefore, in ALS, standardized analysis across these 2 tracers enables pooling of TSPO PET data across multiple centers and increases the power of TSPO as a biomarker for future therapeutic trials., (© 2020 by the Society of Nuclear Medicine and Molecular Imaging.)

Purpose: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder with on average a 1-year delay between symptom onset and diagnosis. Studies have demonstrated the value of [ 18 F]-FDG PET as a sensitive diagnostic biomarker, but the discriminatory potential to differentiate ALS from patients with symptoms mimicking ALS has not been investigated. We investigated the combination of brain and spine [ 18 F]-FDG PET-CT for differential diagnosis between ALS and ALS mimics in a real-life clinical diagnostic setting., Methods: Patients with a suspected diagnosis of ALS (n = 98; 64.8 ± 11 years; 61 M) underwent brain and spine [ 18 F]-FDG PET-CT scans. In 62 patients, ALS diagnosis was confirmed (67.8 ± 10 years; 35 M) after longitudinal follow-up (average 18.1 ± 8.4 months). In 23 patients, another disease was diagnosed (ALS mimics, 60.9 ± 12.9 years; 17 M) and 13 had a variant motor neuron disease, primary lateral sclerosis (PLS; n = 4; 53.6 ± 2.5 years; 2 M) and progressive muscular atrophy (PMA; n = 9; 58.4 ± 7.3 years; 7 M). Spine metabolism was determined after manual and automated segmentation. VOI- and voxel-based comparisons were performed. Moreover, a support vector machine (SVM) approach was applied to investigate the discriminative power of regional brain metabolism, spine metabolism and the combination of both., Results: Brain metabolism was very similar between ALS mimics and ALS, whereas cervical and thoracic spine metabolism was significantly different (in standardised uptake values; cervical: ALS 2.1 ± 0.5, ALS mimics 1.9 ± 0.4; thoracic: ALS 1.8 ± 0.3, ALS mimics 1.5 ± 0.3). As both brain and spine metabolisms were very similar between ALS mimics and PLS/PMA, groups were pooled for accuracy analyses. Mean discrimination accuracy was 65.4%, 80.0% and 81.5%, using only brain metabolism, using spine metabolism and using both, respectively., Conclusion: The combination of brain and spine FDG PET-CT with SVM classification is useful as discriminative biomarker between ALS and ALS mimics in a real-life clinical setting.

Importance: During a time with the potential for novel treatment strategies, early detection of disease manifestations at an individual level in presymptomatic carriers of a hexanucleotide repeat expansion in the C9orf72 gene (preSxC9) is becoming increasingly relevant., Objectives: To evaluate changes in glucose metabolism before symptom onset of amyotrophic lateral sclerosis or frontotemporal dementia in preSxC9 using simultaneous fluorine 18-labeled fluorodeoxyglucose ([18F]FDG positron emission tomographic (PET) and magnetic resonance imaging as well as the mutation's association with clinical and fluid biomarkers., Design, Setting, and Participants: A prospective, case-control study enrolled 46 participants from November 30, 2015, until December 11, 2018. The study was conducted at the neuromuscular reference center of the University Hospitals Leuven, Leuven, Belgium., Main Outcomes and Measures: Neuroimaging data were spatially normalized and analyzed at the voxel level at a height threshold of P < .001, cluster-level familywise error-corrected threshold of P < .05, and statistical significance was set at P < .05 for the volume-of-interest level analysis, using Benjamini-Hochberg correction for multiple correction. W-score maps were computed using the individuals serving as controls as a reference to quantify the degree of [18F]FDG PET abnormality. The threshold for abnormality on the W-score maps was designated as an absolute W-score greater than or equal to 1.96. Neurofilament levels and performance on cognitive and neurologic examinations were determined. All hypothesis tests were 1-sided., Results: Of the 42 included participants, there were 17 with the preSxC9 mutation (12 women [71%]; mean [SD] age, 51 [9] years) and 25 healthy controls (12 women [48%]; mean [SD] age, 47 [10] years). Compared with control participants, significant clusters of relative hypometabolism were found in frontotemporal regions, basal ganglia, and thalami of preSxC9 participants and relative hypermetabolism in the peri-Rolandic region, superior frontal gyrus, and precuneus cortex. W-score frequency maps revealed reduced glucose metabolism with local maxima in the insular cortices, central opercular cortex, and thalami in up to 82% of preSxC9 participants and increased glucose metabolism in the precentral gyrus and precuneus cortex in up to 71% of preSxC9 participants. Other findings in the preSxC9 group were upper motor neuron involvement in 10 participants (59%), cognitive abnormalities in 5 participants (29%), and elevated neurofilament levels in 3 of 16 individuals (19%) who underwent lumbar puncture., Conclusions and Relevance: The results suggest that [18F]FDG PET can identify glucose metabolic changes in preSxC9 at an individual level, preceding significantly elevated neurofilament levels and onset of symptoms.

Neuroinflammation is important in amyotrophic lateral sclerosis (ALS). The P2X7 receptor (P2X7R) is a promising target for neuroinflammation. The objective of this study was to compare 18 F-DPA714, a second-generation translocator protein tracer, with 11 C-JNJ717, a novel P2X7R tracer, in vitro and in vivo in ALS. Methods: For the in vitro portion of the study, autoradiography with 18 F-DPA714 and 11 C-JNJ717 was performed on human ALS brain sections in comparison to immunofluorescence with Iba1 and GFAP. For the in vivo portion, 3 male patients with early-stage ALS (59.3 ± 7.2 y old) and 6 healthy volunteers (48.2 ± 16.5 y old, 2 men and 4 women) underwent dynamic PET/MR scanning with 18 F-DPA714 and 11 C-JNJ717. Volume-of-distribution images were calculated using Logan plots and analyzed on a volume-of-interest basis. Results: Autoradiography showed no difference in 11 C-JNJ717 binding but did show increased 18 F-DPA714 binding in the motor cortex correlating with Iba1 expression (glial cells). Similar findings were observed in vivo, with a 13% increase in 18 F-DPA714 binding in the motor cortex. Conclusion: In symptomatic ALS patients, 18 F-DPA714 showed increased signal whereas 11 C-JNJ717 was not elevated., (© 2020 by the Society of Nuclear Medicine and Molecular Imaging.)

Background: Recently, four neuropathological stages of amyotrophic lateral sclerosis (ALS) with spreading of transactive response DNA-binding protein-43 pathology were described. Although 18F-FDG PET has been useful in diagnosis and prognosis of ALS patients, in-vivo disease staging using glucose metabolic patterns across the different ALS stages has not been attempted so far. In this study, we investigated whether the discriminant brain regions of the neuropathological stage model can be translated to metabolic patterns for in-vivo staging of ALS. Furthermore, we examined the correlation of these metabolic patterns with disease duration, the Revised ALS Functional Rating Scale (ALSFRS-R) and the forced vital capacity (FVC)., Methods: A total of 146 ALS patients (age 66.0±11.0 years; 86 male, 60 female) were divided into four metabolic stages depending on glucose metabolism in discriminant regions of neuropathological stages. 18F-FDG data were analysed voxel-based to compare local metabolic patterns between different stages. Additionally, correlation analyses were performed between pathologic stage and clinical parameters., Results: Relative hypometabolism was present in regions known to be affected from the post-mortem pathological spread model, but relative hypermetabolism was also observed across the different ALS stages. In particular, stage 4 reflected a different frontotemporal pattern discordant with mere progression of stage 1-3, which may point to a potential different subgroup in ALS. Furthermore, metabolic stage correlated with disease duration (Spearman's ρ=-0.21, P=0.01) and FVC (Spearman's ρ=-0.24, P=0.04)., Conclusions: The neuropathological ALS stages correspond to discriminative regional brain glucose metabolism patterns correlating with disease duration and forced vital capacity. Furthermore, metabolic stage 4 may represents a separate group of ALS progression towards frontotemporal dementia.

Background: The Edinburgh cognitive and behavioral ALS screen (ECAS) was developed specifically to detect cognitive and behavioral changes in patients with amyotrophic lateral sclerosis (ALS). Differences with regard to normative data of different (language) versions of neuropsychological tests such as the ECAS exist., Objective: To derive norms for the Dutch version of the ECAS., Methods: Normative data were derived from a large sample of 690 control subjects and cognitive profiles were compared between a matched sample of 428 patients with ALS and 428 control subjects., Results: Age, level of education, and sex were significantly associated with performance on the ECAS in the normative sample. ECAS data were not normally distributed and therefore normative data were expressed as percentile ranks. The comparison of ECAS scores between patients and control subjects demonstrated that patients obtained significantly lower scores for language, executive function, verbal fluency, and memory, which is in line with the established cognitive profile of ALS., Conclusion: For an accurate interpretation of ECAS results, it is important to derive normative data in large samples with nonparametric methods. The present normative data provide healthcare professionals with an accurate estimate of how common or uncommon patients' ECAS scores are and provide a useful supplement to existing cut-off scores.

Objective: 18 F-Fluorodeoxyglucose ( 18 F-FDG) positron emission tomography (PET) single-center studies using support vector machine (SVM) approach to differentiate amyotrophic lateral sclerosis (ALS) from controls have shown high overall accuracy on an individual patient basis using local a priori defined classifiers. The aim of the study was to validate the SVM accuracy on a multicentric level., Methods: A previously defined Belgian (BE) group of 175 ALS patients (61.9 ± 12.2 years, 120M/55F) and 20 screened healthy controls (62.4 ± 6.4 years, 12M/8F) was used to classify another large dataset from Italy (IT), consisting of 195 patients (63.2 ± 11.6 years, 117M/78F) and 40 controls (62 ± 14.4 years; 29M/11F) free of any neurological and psychiatric disorder who underwent whole-body 18 F-FDG PET-CT for lung cancer without any evidence of paraneoplastic symptoms. 18 F-FDG within-center group comparisons based on statistical parametric mapping (SPM) were performed and SVM classifiers based on the local training sets were applied to differentiate ALS from controls from the other centers., Results: SPM group analysis showed only minor differences between both ALS groups, indicating pattern consistency. SVM using BE data set as training, classified 183/193 ALS-IT correctly (accuracy of 94.8%). However, 35/40 CON-IT were misclassified as ALS (accuracy 12.5%). Furthermore, using IT data as training, ALS-BE could not be distinguished from CON-BE. Within-center SPM group analysis confirmed prefrontal hypometabolism in CON-IT versus CON-BE, indicating subclinical brain changes in patients undergoing oncological scanning., Conclusion: This multicenter study confirms that the 18 F-FDG ALS pattern is stable across centers. Furthermore, it highlights the importance of carefully selected controls, as subclinical frontal changes might be present in patients in an oncological setting.

The letter published in the European Journal of Nuclear Medicine & Molecular Imaging in 2024 addresses a correction and additional validation study related to the differentiation between ALS patients and ALS mimics using FDG PET scans of the brain and spinal cord. The study initially reported significant differences in spinal metabolism between ALS patients and ALS mimics, but a validation study in 2023 revealed that these differences were due to improper implementation of a correction factor in the 2020 study. The corrected analysis showed no significant differences in spine metabolism between the two groups, indicating that spine metabolism does not improve the accuracy of distinguishing between ALS and ALS mimics when combined with brain FDG PET scans. [Extracted from the article]

Objective: 18F-Fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) single-center studies using support vector machine (SVM) approach to differentiate amyotrophic lateral sclerosis (ALS) from controls have shown high overall accuracy on an individual patient basis using local a priori defined classifiers. The aim of the study was to validate the SVM accuracy on a multicentric level. Methods: A previously defined Belgian (BE) group of 175 ALS patients (61.9 ± 12.2 years, 120M/55F) and 20 screened healthy controls (62.4 ± 6.4 years, 12M/8F) was used to classify another large dataset from Italy (IT), consisting of 195 patients (63.2 ± 11.6 years, 117M/78F) and 40 controls (62 ± 14.4 years; 29M/11F) free of any neurological and psychiatric disorder who underwent whole-body 18F-FDG PET-CT for lung cancer without any evidence of paraneoplastic symptoms. 18F-FDG within-center group comparisons based on statistical parametric mapping (SPM) were performed and SVM classifiers based on the local training sets were applied to differentiate ALS from controls from the other centers. Results: SPM group analysis showed only minor differences between both ALS groups, indicating pattern consistency. SVM using BE data set as training, classified 183/193 ALS-IT correctly (accuracy of 94.8%). However, 35/40 CON-IT were misclassified as ALS (accuracy 12.5%). Furthermore, using IT data as training, ALS-BE could not be distinguished from CON-BE. Within-center SPM group analysis confirmed prefrontal hypometabolism in CON-IT versus CON-BE, indicating subclinical brain changes in patients undergoing oncological scanning. Conclusion: This multicenter study confirms that the 18F-FDG ALS pattern is stable across centers. Furthermore, it highlights the importance of carefully selected controls, as subclinical frontal changes might be present in patients in an oncological setting. [ABSTRACT FROM AUTHOR]

Background: 18F-FDG brain PET measures metabolic changes in neurodegenerative disorders and may discriminate between different diseases even at an early stage. The objective of this study was to classify patients with amyotrophic lateral sclerosis (ALS) and Parkinson plus syndromes (PP). To this end, different approaches were evaluated using generalized linear models and corresponding glucose metabolic brain patterns. Besides direct classification, healthy controls were also included to generate disease-specific metabolic brain patterns and to perform a classification using disease expression scores.Methods: ALS patients (n = 70) and PP patients (n = 33: 20 PSP, 3 CBD, and 10 MSA) were available from an existing database of patients with neuromuscular and movement disorders while age-matched healthy controls (n = 29) were selected from a prospective study. To generate both disease-discriminative (direct classification) and disease-specific (classification versus controls) metabolic brain patterns, data were spatially normalized and a principal component analysis (PCA) was performed prior to classification using either logistic regression (PCA-LR) or a support vector machine (PCA-SVM). Furthermore, a direct SVM approach was considered. To compare the three different approaches, Pearson correlations (r) between pattern expression scores and metabolic brain patterns were evaluated, while pairs of ALS- and PP-specific pattern expression scores were compared using the RV coefficient.Results: Classification between ALS and PP resulted in a sensitivity and specificity ≥ 0.82 for both direct classification and classification according to disease-specific pattern expression scores. PCA-LR, PCA-SVM, and SVM generated very similar metabolic brain patterns with voxelwise correlations ≥ 0.66, while all patterns allowed straightforward identification of ALS- and PP-specific brain regions of hyper- and hypometabolism. Moreover, pattern expression scores were highly correlated among different classifiers with a mean r of 0.94 while a RV coefficient ≥ 0.91 was found between pairs of ALS- and PP-specific pattern expression scores.Conclusion: We demonstrated that a classification between ALS and PP using expression scores of an ALS and PP metabolic brain pattern leads to a similar and high prediction accuracy as direct classification between ALS and PP. Classification performance and disease-specific metabolic patterns, which could support visual reading and improve insight in brain pathology, were very related for different classifiers. [ABSTRACT FROM AUTHOR]