Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder, characterized by a degeneration of upper and lower motor neurons leading to a progressive muscular paralysis. Although median survival most often averages 3–4 years, the large variability of its course (Calvo et al., 2017) raises an urgent need to develop biomarkers able to characterize the mechanisms underlying disease progression and to improve the diagnostic yield of clinical and neuro-physiological evaluation. Most studies in this setting focused on cortical response to ALS. Among these approaches, brain PET studies with 18F-fluorodeoxyglucose (FDG) already reported a significant reduction in glucose metabolism (Pagani et al., 2014) in motor and premotor cortex (Kiernan et al., 1994; Abrahams et al., 1996, 2005). By contrast, involvement of the spinal cord has been characterized in relatively lower detail, mostly because of the anatomical features of this structure that limit the standardization of its evaluation. Consequently, a large uncertainty still exists about the mechanisms underlying ALS-induced damage in the spinal cord and its relationship with cortical impairment. We recently reported the potential of the Hough transform in delineating spinal cord structure and metabolic activity in a population of ALS patients subjected to FDG PET/CT (Marini et al., 2016). Specifically, this classical pattern recognition approach for the automatic identification of straight lines in the image has been recently extended to the recognition of more complex shapes. This computational 3D approach enabled the extraction of spinal cord metabolic information from whole body images and per- mitted us to document increased glucose consumption, possibly representing a potential and independent prognostic marker (Marini et al., 2016). In the present study, we simultaneously analysed brain and spinal cord FDG uptake in a series of prospectively recruited patients submitted to brain and wholebody PET/CT.
Interplay between spinal cord and cerebral cortex metabolism in amyotrophic lateral sclerosis
BELLINI, ALESSANDRO
2020-04-24
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder, characterized by a degeneration of upper and lower motor neurons leading to a progressive muscular paralysis. Although median survival most often averages 3–4 years, the large variability of its course (Calvo et al., 2017) raises an urgent need to develop biomarkers able to characterize the mechanisms underlying disease progression and to improve the diagnostic yield of clinical and neuro-physiological evaluation. Most studies in this setting focused on cortical response to ALS. Among these approaches, brain PET studies with 18F-fluorodeoxyglucose (FDG) already reported a significant reduction in glucose metabolism (Pagani et al., 2014) in motor and premotor cortex (Kiernan et al., 1994; Abrahams et al., 1996, 2005). By contrast, involvement of the spinal cord has been characterized in relatively lower detail, mostly because of the anatomical features of this structure that limit the standardization of its evaluation. Consequently, a large uncertainty still exists about the mechanisms underlying ALS-induced damage in the spinal cord and its relationship with cortical impairment. We recently reported the potential of the Hough transform in delineating spinal cord structure and metabolic activity in a population of ALS patients subjected to FDG PET/CT (Marini et al., 2016). Specifically, this classical pattern recognition approach for the automatic identification of straight lines in the image has been recently extended to the recognition of more complex shapes. This computational 3D approach enabled the extraction of spinal cord metabolic information from whole body images and per- mitted us to document increased glucose consumption, possibly representing a potential and independent prognostic marker (Marini et al., 2016). In the present study, we simultaneously analysed brain and spinal cord FDG uptake in a series of prospectively recruited patients submitted to brain and wholebody PET/CT.File | Dimensione | Formato | |
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