Abstract

The maturation of photon-counting detector (PCD) technology promises to enhance routine CT imaging applications with high-fidelity spectral information. In this paper, we demonstrate the power of this synergy and our complementary reconstruction techniques, performing 4D, cardiac PCD-CT data acquisition and reconstruction in a mouse model of atherosclerosis, including calcified plaque. Specifically, in vivo cardiac micro-CT scans were performed in four ApoE knockout mice, following their development of calcified plaques. The scans were performed with a prototype PCD (DECTRIS, Ltd.) with 4 energy thresholds. Projections were sampled every 10 ms with a 10 ms exposure, allowing the reconstruction of 10 cardiac phases at each of 4 energies (40 total 3D volumes per mouse scan). Reconstruction was performed iteratively using the split Bregman method with constraints on spectral rank and spatio-temporal gradient sparsity. The reconstructed images represent the first in vivo, 4D PCD-CT data in a mouse model of atherosclerosis. Robust regularization during iterative reconstruction yields high-fidelity results: an 8-fold reduction in noise standard deviation for the highest energy threshold (relative to unregularized algebraic reconstruction), while absolute spectral bias measurements remain below 13 Hounsfield units across all energy thresholds and scans. Qualitatively, image domain material decomposition results show clear separation of iodinated contrast and soft tissue from calcified plaque in the in vivo data. Quantitatively, spatial, spectral, and temporal fidelity are verified through a water phantom scan and a realistic MOBY phantom simulation experiment: spatial resolution is robustly preserved by iterative reconstruction (10% MTF: 2.8–3.0 lp/mm), left-ventricle, cardiac functional metrics can be measured from iodine map segmentations with ~1% error, and small calcifications (615 μm) can be detected during slow moving phases of the cardiac cycle. Given these preliminary results, we believe that PCD technology will enhance dynamic CT imaging applications with high-fidelity spectral and material information.

Highlights

  • Dual-energy (DE) spectral imaging methods enhance the diagnostic capabilities of x-ray CT through quantitative material discrimination [1] and the ability to synthesize virtual nonenhanced [2, 3] and monochromatic images [4]

  • Because the ground truth reconstruction is known in this simulation experiment (C), root-meansquare error (RMSE; Hounsfield units, HU) measurements can be computed over the entire reconstruction and over only the portion of the reconstruction which changes in time

  • We demonstrated the superiority of our photon-counting detector (PCD)-based micro-CT system over our similar energy-integrating detectors (EIDs)-based micro-CT system for sarcoma tumor imaging in mice [26]

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Summary

Introduction

Dual-energy (DE) spectral imaging methods enhance the diagnostic capabilities of x-ray CT through quantitative material discrimination [1] and the ability to synthesize virtual nonenhanced [2, 3] and monochromatic images [4]. DE-CT scanners are available from several vendors: Siemens Healthineers (Erlangen, Germany; dual-source, split filter), GE Healthcare (Chicago, IL; fast kVp switching), Koninklijke Philips There are no patents, products in development, or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials. Dual-layer), and Canon Medical Systems (Otawara, Tochigi Prefecture, Japan; slow kVp switching). These DE scanners are associated with several routine imaging applications, including plaque differentiation, myocardial perfusion, and kidney stone characterization [5]. Spectral CT has been utilized in several additional applications, including differential imaging of vasculature and vascular permeability in sarcoma [6] and lung [7] tumors, and with several preclinical contrast agents based on iodine [8], barium [9], gadolinium [10], and gold [6]

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