Multi-contrast CT imaging using a high energy resolution CdTe detector and a CZT photon-counting detector

Abstract

Computed tomography (CT) imaging with high energy resolution detectors shows great promise in material decomposition and multi-contrast imaging. Multi-contrast imaging was studied by imaging a phantom with iodine (I), gadolinium (Gd), and gold (Au) solutions, and mixtures of the three using a cadmium telluride (CdTe) spectrometer with an energy resolution of 1% as well as with a cadmium zinc telluride (CZT) detector with an energy resolution of 13%. The phantom was imaged at 120 kVp and 1.1 mA with 7 mm of aluminum filtration. For the CdTe data collection, the phantom was imaged using a 0.2 mm diameter x-ray beam with 96 ten-second data acquisitions across the phantom at 45 rotation angles. For the CZT detector, we had 720 projections using a cone beam, and the six detector energy thresholds were set to 23, 33, 50, 64, 81, and 120 keV so that three thresholds corresponded to the K-edges of the contrast agents. Contrast agent isolation methods were then examined. K-edge subtraction and novel spectrometric algebraic image reconstruction (SAIR) were used for the CdTe data. K-edge subtraction alone was used for the CZT data. Linearity plots produced similar R 2 values and slopes for all three reconstruction methods. Comparing CdTe methods, SAIR offered less noise than CdTe K-edge subtraction and better geometric accuracy at low contrast concentrations. CdTe contrast agent images of I, Gd, and Au offered less noise and greater contrast than the CZT images, highlighting the benefits of high energy resolution CdTe detectors for possible use in pre-clinical or clinical CT imaging.

Material decomposition with a prototype photon-counting detector CT system: expanding a stoichiometric dual-energy CT method via energy bin optimization and K-edge imaging

“…In practice, the electronic cross sections for each of the elements that appear in the tissue-equivalent material compositions were obtained from the XCOM photon cross section database (Berger et al 1998). Beam spectra were generated in SpekPy (Poludniowski et al 2021), previously validated for our x-ray source (Clements et al 2022). Separately, each element's electronic cross section was averaged over the photon spectrum or energy bin spectrum in question, weighted by the relative number of photons of each energy.…”

Joint estimation of interaction position and energy deposition in semiconductor SPECT imaging sensors using fully connected neural network

“…Pixelated CdTe/CZT detectors have achieved excellent energy and spatial resolution and show great advantages for brain SPECT imaging [1], MRI compatible SPECT systems [2], clinical SPECT imaging [3], high spatial resolution PET imaging [4], and CT systems with multi-contrast imaging [5]. In nuclear medicine and molecular imaging applications, the imaging system performance is intrinsically determined by the accurate location and energy of single-photon interactions within the CdTe/CZT sensors.…”