Title: Review of an initial experience with an experimental spectral photon-counting computed tomography system

Spectral photon-counting CT (SPCCT) is an emerging X-ray imaging technology that extends the scope of available diagnostic imaging tools. The main advantage of photon-counting CT technology is better sampling of the spectral information from the transmitted spectrum in order to benefit from additional physical information being produced during matter interaction, including photo-electric and Compton effects, and the K-edge effect. The K-edge, which is specific for a given element, is the increase in X-ray absorption of the element above the binding energy between its inner electronic shell and the nucleus. Hence, the spectral information contributes to better characterization of tissues and materials of interest, explaining the excitement surrounding this area of X-ray imaging. Other improvements of SPCCT compared with conventional CT, such as higher spatial resolution, lower radiation exposure and lower noise are also expected to provide benefits for diagnostic imaging. In this review, we describe multienergy CT imaging, from dual energy to photon counting technology, and our initial experience results using a clinical-scale spectral photon counting CT (SPCCT) prototype system in vitro and in vivo. In addition, possible clinical applications are introduced. Keywords: Spectral photon-counting computed tomography, gold nanoparticles, K-edge imaging, contrast agent, dual contrast imaging, clinical applications. Abbreviations ASIC: application specific integrated circuit CNR: contrast-to-noise ratio CT: Computed tomography DECT: Dual energy computed tomography EID: energy integrating detector HU: Hounsfield units MRI: magnetic resonance imaging SPCCT: spectral photon-counting computed tomography PET: positron emission tomography PCD: photon-counting detectors 1. Introduction Computed tomography (CT) is currently one of the key imaging modalities in clinical use. The number of CT scans performed worldwide per year is now numbered in the hundreds of millions (1). It is available in standard and emergency settings nearly everywhere in the world, with applications in the diagnosis of many different conditions and injuries. It provides threedimensional images of the linear attenuation coefficient distribution within a patient, accurately delineating organs and tissue. However, there are five major limitations to current CT technologies with current contrast agents: 1) Spatial resolution (around 0.5 mm), even if better than other non-invasive technologies such as MRI or PET, is still a limitation for assessment of small structures such as the lumens of coronary arteries and atherosclerotic plaques. 2) Contrast between different tissues or materials is often insufficient, especially for soft tissue, because CT images are not tissue-type specific. Indeed different tissue types often have similar attenuation values. 3) X-ray attenuation measured by CT and expressed in Hounsfield Units (HU) does not allow an absolute quantification of the contrast agent injected, e.g. iodine, since it combines the attenuation of the contrast material to be quantified and the attenuation of the underlying tissue. Furthermore, the attenuation of a material depends on the energy of the X-rays spectrum used. 4) CT scanning is a relatively high radiation-dose procedure. In general, its use is therefore mostly for diagnostic imaging and is limited for screening of large populations or repeated examinations in the presence of a chronic disease. 5) Iodine-based contrast agents currently in use are not specific and thus do not detect or monitor pathologic processes in patients in a targeted fashion. These limitations impair the diagnostic performance of CT in all medical fields where CT is applied. A recent, notable development in the field of CT is the analysis of spectral information of the X-rays that have passed through the subject. Although this concept has been discussed since CT was invented (2–4), the technology to accurately record this information has only become available over the past decade. Conventional CT scanners integrate all the signals from the detected transmitted X-ray photons into a single attenuation signal without recording any information on their individual energies (Fig 1A). A variety of systems that are given the term dual-energy CT (DECT) and use energy-integrating detectors (EIDs) have been introduced clinically that begin to exploit the benefits of spectral detection by acquiring two energetically distinct datasets (Fig 1B,C). Nevertheless, DECT systems do not typically have improved spatial resolution compared to single energy CT scanners, which is still limited by the scintillators used to convert photons into light that spread the signal spatially, and by the noise resulting from the signal integration process and the associated detection electronics. Furthermore, DECT systems only perform a two-point analysis of the X-ray attenuation, which improves tissue characterization and allows quite precise iodine quantification, but is insufficient to accurately discriminate between iodine and calcium, especially at low radiation dose. In addition, many DECT systems expose the patient to two energy beams that can result in potentially high radiation exposure, and motion can create issues for aligning the two datasets. Finally, no specific contrast agent has been developed for DECT due to the lack of sensitivity of such systems for specific material imaging (5). Figure 1. Representation of the information provided by the energy integrating detectors in single energy CT systems (A), dual source DECT systems (B) and dual-layer detector based DECT systems (C), compared to SPCCT systems that allow several datasets to be derived from a transmitted spectrum (D). Recently, systems based on photon counting detectors (PCDs), termed spectral photoncounting detectors CT (SPCCT) or multicolor SPCCT (6), have been introduced in the field of CT imaging (Fig. 1D). These PCDs are the subject of ongoing research and development in CT systems (5,7–10). They have the capability of energy discrimination based on analysis of the pulse height of each detected photon of the transmitted x-ray spectrum and the count of their number above different energy thresholds or in multiple energy windows (7). The number of energy bins (windows) depends on the design of the detection chain of the PCDs, and the energy thresholds can be selected depending on the chosen application. Hence, the transmitted spectrum is divided into several energy bins leading to better sampling of the X-ray spectrum than DECT. This characteristic allows detection of K-edges within certain energy windows and to distinguish simultaneously between different attenuation profiles, for instance those specific to different contrast agents, allowing multi-contrast agent imaging (6). In addition, due to their architecture and detection mechanism, PCDs can provide improved spatial resolution and reduced radiation dose compared to conventional CT (11). Although all these advantages have the potential to improve the five intrinsic limitations of the conventional CT imaging described above, SPCCT systems face technical challenges such as handling the high photon flux used in CT (approximately 10 counts/sec/mm) (5). SPCCT systems are being investigated for CT applications as the next step to derive more information from transmitted X-ray photons. In this review, we describe the field of clinical imaging using DECT systems and experimental spectral photon counting technology and the results of our initial experience using a pre-clinical spectral photon counting CT (SPCCT) in vitro and in vivo. In addition, possible SPCCT clinical applications are introduced. 2. Multi-energy CT imaging With single energy CT imaging systems, tissues and materials can have the same attenuation values (i.e. Hounsfield unit values) despite having different compositions, based on their mass density (12), leading to a potential misclassification of pathologies, e.g. in differentiation between hemorrhage and tissue in a kidney cyst, or in separating calcified plaques from the lumen of vessels filled with iodine. Pitfalls such as these have encouraged the development of multi-energy CT imaging techniques, based on acquiring more than one dataset from energetically distinct Xray spectra. The first technology based on a multi-energy approach that has been translated to clinical use is DECT imaging. SPCCT is a next generation, multi-energy technology that is being seriously considered for clinical translation, with the first report of SPCCT scans of patients being recently published (13). 2.1. DECT systems This term is typically used for techniques making use of two datasets that are derived from energetically distinct X-ray spectra in order to differentiate between different materials. Wellknown implementations include emission based dual energy CT: dual-source CT (14–16), various implementations of kVp-switching from view-to-view during the CT acquisition (17–19), and detection based dual energy CT: i.e. dual-layer detector CT (20). All these forms of DECT use EIDs. DECT enables two-material basis set decomposition techniques and a number of applications inaccessible to conventional CT. New image types that are often available from DECT systems include basis material images of iodine and water, soft-tissue and bone-images, and virtual mono-energy (MonoE) images (Fig 2) (12,21,22).