Treb, Kevin J

Abstract Background Photon counting detector CT (PCD‐CT) has the potential to sort detected x‐ray photons into more than two energy bins to perform multi‐material decomposition using K‐edge materials without additional mathematical constraints/assumptions. The availability of multiple energy thresholds in PCD‐CT opens the possibility for unique clinical applications such as simultaneous multi‐contrast‐agent imaging. Purpose To evaluate the technical performance of a PCD‐CT system with four energy thresholds for conducting multi‐material decomposition of iodine, gadolinium, and water after a comprehensive system calibration procedure. Methods Experiments were performed on a commercial PCD‐CT scanner (NAEOTOM Alpha, Siemens Healthineers) using a research mode with four energy thresholds. Material calibration was performed by scanning contrast materials with known concentration placed in various sizes of cylindrical water‐equivalent phantoms at various tube currents and positions. From these data, per‐voxel contrast models were derived for each material by multiple linear regressions up to second order, where the predictor variables were combinations of tube current, phantom diameter, and distance to isocenter. After calibration, small (20 cm diameter) and large (30 cm × 40 cm) uniform multi‐energy CT phantoms and an anthropomorphic thorax phantom (31 cm × 39 cm), each containing bone, soft tissue, and several quantitative inserts of iodine (0.2–5.0 mg/ml), gadolinium (0.3–5.0 mg/ml), and a mixture of both (5.0 mg/ml each) were scanned using the four‐energy threshold mode at 140 kV with energy thresholds set at 20, 52, 75, and 82 keV. Images for each energy threshold were reconstructed with a filtered back‐projection algorithm and a quantitative kernel (Qr44). Subsequent image‐based material decomposition was performed on individual voxels of the energy threshold images using the models derived from the calibration process to generate water, iodine, and gadolinium basis images. Quantitative material concentrations and image noise magnitudes, and noise power spectra (NPS) were measured. Results Iodine and gadolinium concentrations above 1.25 mg/ml were visible in the material basis images in all phantoms. Averaged quantitative accuracy for iodine and gadolinium in the small, large, and thorax phantoms were 0.39 ± 0.30 mg/ml, 0.96 ± 0.53 mg/ml, and 0.53 ± 0.35 mg/ml, respectively. In the water basis images, accuracy was within 24 HU in all phantoms. Noise magnitudes in iodine and gadolinium basis images were 2.91 and 3.52 times that of the lowest energy threshold image for the small phantom, and were 6.92 and 7.17 times that of the lowest threshold image for the large phantom. Noise texture did not change between the energy threshold and material basis images for either size phantom as measured by the NPS. Conclusions After a comprehensive system calibration, a commercial PCD‐CT with four energy thresholds performed multiple material decomposition of iodine, gadolinium, and water for concentrations above 1.25 mg/ml in human‐sized phantoms. Noise amplification and quantitative accuracy from the decomposition greatly depended on object size.

Abstract Quantitative computed tomography (CT) enables the measurement of biophysical processes characterized by morphology, composition, flow, and/or motion to aid in clinical diagnosis and intervention. Since its initial application for determining bone mineral density for skeletal fragility assessment, quantitative CT has continued to evolve alongside CT’s technological advancements. A key challenge facing quantitative CT is the lack of standardization pertinent to image acquisition, reconstruction, and image analysis. With the introduction of spectral CT involving dual-energy approaches and photon-counting detectors (PCD), we are now able to obtain detailed information regarding mass densities of endogenous and exogeneous materials. Furthermore, energy-resolved CT yields spectral image types (eg, virtual monoenergetic image) that are, in principle, independent of tube potential and patient size. This paves the way for workflow standardization and helps improve the consistency and reproducibility of CT-derived measurements. In this article, we review clinical applications of quantitative CT, discuss key challenges associated with quantitative CT and its adoption into routine practice, and outline the unique benefits ushered by new CT technologies such as PCD-CT towards improving quantitative imaging.