Spectral CT, using the Medipix3 detector and silicon sensor layer, can quantify certain sets of up to three materials using the proposed method of constrained least squares. The system has some ability to independently distinguish calcium, fat, and water, and these have been quantified within phantom equivalents of fatty liver and atheroma. In this configuration, spectral CT cannot distinguish iron from calcium within soft tissues.

The MARS research group has created a new version of their scanner for taking improved spectral CT datasets. This version of the scanner (MARS-CT-3) has taken the first Medipix3 CT images of a phantom. MARS-CT-3 incorporates a new gantry, new x-ray sources and the new MARS readout board, as well as the ability to connect gas lines to the specimen.The new gantry has improved mechanical rigidity and can perform scans faster. Magnification can be controlled by moving the detector and the x-ray source independently. The brighter x-ray source means images can be taken six times faster. Gas lines allow the user to control various environmental factors inside the scanner, such as temperature, or deliver oxygen and anaesthetics, providing the ability to do a full spectroscopic CT scan of a live sedated biological specimen, such as a mouse. The new MARS readout is able to read from all current chips from the Medipix family, has faster image downloading, and the use of up to six Medipix detectors in parallel on the same chip carrier. The use of Medipix3 chips allows for compensation of charge sharing via Charge Summing Mode.

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 -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 photonprocessing 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. The raw, partially processed and fully processed data of lamb tissue along with the phantom calibration data can be found at [http://hdl.handle.net/10092/8531].

Spectral computed tomography offers new insights into tissue characterisation. Components of vulnerable atherosclerotic plaque are spectrally distinct with intrinsic contrast. Spectral CT of excised atherosclerotic plaques can display iron, calcium and lipid. Calcium deposits are larger than iron deposits in atheroma. Spectral CT may help in the non-invasive detection of vulnerable plaques.

• Spectral computed tomography uses K-edge and slope effects to identify element signatures. • New visualisation tools will be required to efficiently display spectral CT information. • This paper demonstrates HU variation with keV using the Medipix3 chip. • HU ( keV ) is a suggested format when stating spectral HU measurements.