MARS spectral molecular imaging of lamb tissue: data collection and image analysis

Spectral molecular imaging is a new imaging technique able to discriminate and quantify different components of tissue simultaneously at high spatial and high energy resolution. Our MARS scanner is an x-ray based small animal CT system designed to be used in the diagnostic energy range (20 to 140 keV). In this paper, we demonstrate the use of the MARS scanner, equipped with the Medipix3RX spectroscopic photon-processing detector, to discriminate fat, calcium, and water in tissue. We present data collected from a sample of lamb meat including bone as an illustrative example of human tissue imaging. The data is analyzed using our 3D Algebraic Reconstruction Algorithm (MARS-ART) and by material decomposition based on a constrained linear least squares algorithm. The results presented here clearly show the quantification of lipid-like, water-like and bone-like components of tissue. However, it is also clear to us that better algorithms could extract more information of clinical interest from our data. Because we are one of the first to present data from multi-energy photon-processing small animal CT systems, we make the raw, partial and fully processed data available with the intention that others can analyze it using their familiar routines.Spectral molecular imaging is a new imaging technique able to discriminate and quantify different components of tissue simultaneously at high spatial and high energy resolution. Our MARS scanner is an x-ray based small animal CT system designed to be used in the diagnostic energy range (20 to 140 keV). In this paper, we demonstrate the use of the MARS scanner, equipped with the Medipix3RX spectroscopic photon-processing detector, to discriminate fat, calcium, and water in tissue. We present data collected from a sample of lamb meat including bone as an illustrative example of human tissue imaging. The data is analyzed using our 3D Algebraic Reconstruction Algorithm (MARS-ART) and by material decomposition based on a constrained linear least squares algorithm. The results presented here clearly show the quantification of lipid-like, water-like and bone-like components of tissue. However, it is also clear to us that better algorithms could extract more information of clinical interest from our data. Because we are one of the first to present data from multi-energy photon-processing small animal CT systems, we make the raw, partial and fully processed data available with the intention that others can analyze it using their familiar routines.Spectral molecular imaging is a new imaging technique ableto discriminate and quantify different components of tissuesimultaneously at high spatial and high energy resolution. Our MARSscanner is an x-ray based small animal CT system designed to be usedin the diagnostic energy range (20–140 keV). In this paper, wedemonstrate the use of the MARS scanner, equipped with theMedipix3RX spectroscopic photon-processing detector, to discriminatefat, calcium, and water in tissue. We present data collected from asample of lamb meat including bone as an illustrative example ofhuman tissue imaging. The data is analyzed using our 3D AlgebraicReconstruction Algorithm (MARS-ART) and by material decompositionbased on a constrained linear least squares algorithm. The resultspresented here clearly show the quantification of lipid-like,water-like and bone-like components of tissue. However, it is alsoclear to us that better algorithms could extract more information ofclinical interest from our data. Because we are one of the first topresent data from multi-energy photon-processing small animal CTsystems, we make the raw, partial and fully processed data availablewith the intention that others can analyze it using their familiarroutines. The raw, partially processed and fully processed data oflamb tissue along with the phantom calibration data can be found athttp://hdl.handle.net/10092/8531