Michele Scipioni

Michele Scipioni
Massachusetts General Hospital | MGH

Ph.D.

About

21
Publications
966
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109
Citations
Additional affiliations
January 2017 - July 2017
Massachusetts General Hospital
Position
  • Research Assistant
May 2015 - October 2015
Fondazione Toscana Gabriele Monasterio
Position
  • Intern
Education
November 2015 - October 2018
Università di Pisa
Field of study
  • Biomedical Engineering
October 2012 - April 2015
Università di Pisa
Field of study
  • Biomedical Engineering
October 2008 - December 2011
Università Politecnica delle Marche
Field of study
  • Biomedical Engineering

Publications

Publications (21)
Article
Full-text available
A technical comparison is described between two SPECT systems, one dedicated to cardiovascular studies and one general-purpose, to evaluate the advantages and disadvantages of their use in an organ-specific clinical setting. The comparison was made between a dedicated cardiac SPECT (Alcyone, Discovery NM 530c, GE Healthcare) scanner and a general-p...
Article
Full-text available
The objective of the present work was to evaluate the potential of deep learning tools for characterizing the presence of cardiac amyloidosis from early acquired PET images, i.e. 15 min after [18F]-Florbetaben tracer injection. 47 subjects were included in the study: 13 patients with transthyretin-related amyloidosis cardiac amyloidosis (ATTR-CA),...
Article
Objective To evaluate the feasibility of kinetic modeling-based approaches from [18F]-Flobetaben dynamic PET images as a non-invasive diagnostic method for cardiac amyloidosis (CA) and to identify the two AL- and ATTR-subtypes.Methods and ResultsTwenty-one patients with diagnoses of CA (11 patients with AL-subtype and 10 patients with ATTR-subtype...
Article
The idea that performing a proper succession of imaging tests and techniques allows an accurate and early diagnosis of cardiac amyloidosis, avoiding the need to perform the myocardial biopsy, is becoming increasingly popular. Furthermore, being imaging techniques non-invasive, it is possible to perform the follow-up of the pathology through repeate...
Article
Full-text available
Objectives This study aimed to test the diagnostic value of fludeoxyglucose F 18 ([18F])–florbetaben positron emission tomography (PET) in patients with suspicion of CA. Background Diagnosis of cardiac involvement in immunoglobulin light-chain–derived amyloidosis (AL) and transthyretin-related amyloidosis (ATTR), which holds major importance in ri...
Article
Objective To determine one or more indexes able to detect the presence of cardiac amyloidosis (CA) from planar scintigraphy images after injection of 99mTc-HMDP tracer and to identify the earliest acquisition time able to ensure an accurate diagnosis of amyloid transthyretin CA.Methods and ResultsA total of 38 patients were included: 18 subjects wi...
Article
Purpose: Positron emission tomography (PET) image reconstruction is usually performed using maximum likelihood (ML) iterative reconstruction methods, under the assumption of Poisson distributed data. Pre-correcting raw measured counts, this assumption is no longer realistic. The goal of this work is to develop a reconstruction algorithm based on t...
Conference Paper
Dynamic positron emission tomography (dPET) is known for its ability to extract spatiotemporal information of a radio tracer in living tissue. In this paper, a novel direct reconstruction framework is presented, which include concurrent clustering as a potential aid in addressing high levels of noise typical of voxel-wise kinetic modeling. Core ass...
Article
In the context of dynamic emission tomography, the conventional processing pipeline consists of independent image reconstruction of single time frames, followed by the application of a suitable kinetic model to time-activity curves (TACs) at the voxel or region-of-interest level. Direct 4D PET reconstruction, by contrast, seeks to move beyond this...
Article
Full-text available
Purpose: To compare the clinical performance of upper abdominal PET/DCE-MRI with and without concurrent respiratory motion correction (MoCo). Methods: MoCo PET/DCE-MRI of the upper abdomen was acquired in 44 consecutive oncologic patients and compared with non-MoCo PET/MRI. SUVmax and MTV of FDG-avid upper abdominal malignant lesions were assess...
Preprint
Full-text available
In the context of dynamic emission tomography, the conventional processing pipeline consists of independent image reconstruction of single time frames, followed by the application of a suitable kinetic model to time activity curves (TACs) at the voxel or region-of-interest level. The relatively new field of 4D PET direct reconstruction, by contrast...
Article
Full-text available
We propose and test a novel approach for direct parametric image reconstruction of dynamic PET data. We present a theoretical description of the problem of PET direct parametric maps estimation as an inference problem, from a probabilistic point of view, and we derive a simple iterative algorithm, based on the Iterated Conditional Mode (ICM) framew...
Article
In this work, we propose and test a new approach for non-linear kinetic parameters' estimation from dynamic PET data. A technique is discussed, to derive an analytical closed-form expression of the compartmental model used for kinetic parameters' evaluation, using an auxiliary parameter set, with the aim of reducing the computational burden and spe...
Article
Full-text available
Purpose: We present an approach for concurrent reconstruction of respiratory motion compensated abdominal DCE-MRI and PET data in an integrated PET/MR scanner. The MR and PET reconstructions share the same motion vector fields (MVFs) derived from radial MR data; the approach is robust to changes in respiratory pattern and do not increase the total...
Preprint
Full-text available
Parametric images provide insight into the spatial distribution of physiological parameters, but they are often extremely noisy, due to low SNR of tomographic data. Direct estimation from projections allows accurate noise modeling, improving the results of post-reconstruction fitting. We propose a method, which we name kinetic compressive sensing (...
Conference Paper
Full-text available
Parametric images provide insight into the spatial distribution of physiological parameters, but they are often extremely noisy, due to low SNR of tomographic data. Direct estimation from projections allows accurate noise modeling, improving the results of post-reconstruction fitting. We propose a method, which we name kinetic compressive sensing (...
Article
Background: Among the novelties in the field of cardiovascular imaging, the construction of quantitative maps in a fast and efficient way is one of the most interesting aspects of the clinical research. Quantitative parametric maps are typically obtained by post processing dynamic images, that is, sets of images usually acquired in different tempo...
Article
Positron emission tomography (PET) in medicine exploits the properties of positron-emitting unstable nuclei. The pairs of γ- rays emitted after annihilation are revealed by coincidence detectors and stored as projections in a sinogram. It is well known that radioactive decay follows a Poisson distribution; however, deviation from Poisson statistics...
Conference Paper
In the present work a study is carried out in order to assess the efficiency of the direct reconstruction algorithms on noisy dynamic PET data. The study is performed via Monte Carlo simulations of a uniform cylindrical phantom whose emission values change in time according to a kinetic law. After generating the relevant projection data and properl...
Poster
Full-text available
Introduction Dynamic positron emission tomography (PET) studies allow to quantify tissue-specific biochemical properties. Conventional pharmacokinetic analysis requires the voxel-wise time activity curve fitting performed on a sequence of independently reconstructed PET images. Direct parametric reconstruction methods combine emission image reconst...

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Projects (2)
Project
Development of mathematical methods and algorithms to generate parametric maps from dynamic PET dataset