Donatienne Van Weehaeghe1,2, Martijn Devrome3, Michel Koole3, Koen Van Laere3,4, Georg Schramm3, Joke De Vocht5, Wies Deckers4, Kristof Baete3,4, Philip Van Damme5,6. 1. Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium. donatienne.vanweehaeghe@uzleuven.be. 2. Division of Nuclear Medicine, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium. donatienne.vanweehaeghe@uzleuven.be. 3. Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium. 4. Division of Nuclear Medicine, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium. 5. Department of Neurology, University Hospital Leuven, Leuven, Belgium. 6. Laboratory of Neurobiology, Center for Brain & Disease Research, VIB and KU Leuven, Leuven, Belgium.
Abstract
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 [18F]-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 [18F]-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 [18F]-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.
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 [18F]-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 [18F]-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 [18F]-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.
Entities:
Keywords:
ALS mimics; Amyotrophic lateral sclerosis; Automated spinal cord segmentation; Brain and spinal [18F]-FDG PET-CT; Convolutional neural network; Support vector machine
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