Contributo in atti di convegno, 2016, ENG

FDG-PET and the sssessment of spinal cord metabolism in amyotrophic lateral sclerosis (ALS)

Massone, A.M.a, Campi, C.b, Beltrametti, M.C.c, Marini, C.d

aCNR, SPIN, via Dodecaneso 33, Genova, 16146, Italy bDipartimento SBAI, Università degli Studi di Roma la Sapienza, via A. Scarpa 14, Roma, 00161, Italy cDipartimento di Matematica, Università degli Studi di Genova, via Dodecaneso 35, Genova, 16146, Italy dCNR, IBFM Sezione di Genova, Via De Toni 5, Genova, 16132, Italy

Synaptic activity in the nervous system consumes glucose. Therefore Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) may in principle provide iconographic representations of glucose utilization impairment in neurodegenerative diseases and, specifically, in Amyotrophic Lateral Sclerosis (ALS). In a previous paper, we developed a computational method that applies a modern generalization of the Hough transform (HT) to identify the spinal canal and the spinal cord in Xray Computed Tomography (CT) images of ALS patients, and combines this information with the functional data provided by FDG-PET to measure the spinal marrow metabolism in detail. In that application, ellipses were used as prototypes for the HTbased recognition of the spinal cord profile and curves with three convexities as prototypes for the HT-based recognition of the spinal canal profile. In the present work, we provide a detailed description of the theoretical and computational tools at the basis of this approach to image integration, giving specific emphasis to the image processing steps necessary to make the structural information contained in the CT data actually determined by means of the HT procedure. Information inferred from the anatomical images have been integrated with functional information from PET images in order to quantitatively evaluate the metabolic activity of the spinal marrow in 30 control subjects and 30 ALS patients

2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor, Strasburgo, Francia, 29/10-06/11/2016

Keywords

Pattern recognition, Terms-Image analysis

CNR authors

Massone Annamaria, Marini Cecilia

CNR institutes

IBFM – Istituto di bioimmagini e fisiologia molecolare, SPIN – Istituto superconduttori, materiali innovativi e dispositivi