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The photon-counting detector (PCD) is a new computed tomography detector technology (photon-counting computed tomography, PCCT) that provides substantial benefits for cardiac and coronary artery imaging. Compared with conventional CT, PCCT has multi-energy capability, increased spatial resolution and soft tissue contrast with near-null electronic noise, reduced radiation exposure, and optimization of the use of contrast agents. This new technology promises to overcome several limitations of traditional cardiac and coronary CT angiography (CCT/CCTA) including reduction in blooming artifacts in heavy calcified coronary plaques or beam-hardening artifacts in patients with coronary stents, and a more precise assessment of the degree of stenosis and plaque characteristic thanks to its better spatial resolution. Another potential application of PCCT is the use of a double-contrast agent to characterize myocardial tissue. In this current overview of the existing PCCT literature, we describe the strengths, limitations, recent applications, and promising developments of employing PCCT technology in CCT.

Photon-counting detector (PCD) is a novel computed tomography detector technology (photon-counting computed tomography—PCCT) that presents many advantages in the neurovascular field, such as increased spatial resolution, reduced radiation exposure, and optimization of the use of contrast agents and material decomposition. In this overview of the existing literature on PCCT, we describe the physical principles, the advantages and the disadvantages of conventional energy integrating detectors and PCDs, and finally, we discuss the applications of the PCD, focusing specifically on its implementation in the neurovascular field.

Photon counting CT was recently introduced into clinical practice [Rajendran K, Petersilka M, Henning A, Shanblatt ER, Schmidt B, Flohr TG, Ferrero A, Baffour F, Diehn FE, Yu L, Rajiah P, Fletcher JG, Leng S, McCollough CH. First Clinical Photon-counting Detector CT System: Technical Evaluation. Radiology 2022;303(1):130–138. doi: https://doi.org/10.1148/radiol.212579]. Photon counting detectors (PCD) afford better spatial resolution, radiation dose efficiency, and iodine contrast-to-noise than EID-CT [Leng S, Bruesewitz M, Tao S, Rajendran K, Halaweish AF, Campeau NG, Fletcher JG, McCollough CH. Photon-counting Detector CT: System Design and Clinical Applications of an Emerging Technology. Radiographics 2019;39(3):729–743. doi: https://doi.org/10.1148/rg.2019180115); (Leng S, Rajendran K, Gong H, Zhou W, Halaweish AF, Henning A, Kappler S, Baer M, Fletcher JG, McCollough CH. 150-mum Spatial Resolution Using Photon-Counting Detector Computed Tomography Technology: Technical Performance and First Patient Images. Invest Radiol 2018;53(11):655–662. doi: https://doi.org/10.1097/RLI.0000000000000488)(Booij R, van der Werf NR, Dijkshoorn ML, van der Lugt A, van Straten M. Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data. Diagnostics (Basel) 2022;12(6). doi: https://doi.org/10.3390/diagnostics12061467); (Sawall S, Klein L, Amato C, Wehrse E, Dorn S, Maier J, Heinze S, Schlemmer HP, Ziener CH, Uhrig M, Kachelriess M. Iodine contrast-to-noise ratio improvement at unit dose and contrast media volume reduction in whole-body photon-counting CT. Eur J Radiol 2020;126:108909. doi: https://doi.org/10.1016/j.ejrad.2020.108909] while also maintaining multienergy CT (MECT) capabilities[Flohr T, Petersilka M, Henning A, Ulzheimer S, Ferda J, Schmidt B. Photon-counting CT review. Phys Med 2020;79:126–136. doi: https://doi.org/10.1016/j.ejmp.2020.10.030]. This article will review the clinical adoption of PCD-CT including protocol development, clinical applications, clinical integration and workflow considerations. Protocol development is institution specific and involves collaborative decision-making among radiologists, physicists, and technologists. Key PCD clinical applications include radiation exposure reduction, intravenous contrast volume reduction, and improved lesion conspicuity. Patients who would most benefit from these improvements may preferentially be scanned with PCD CT. With numerous available reconstructions, radiologists should be strategic in the series sent to PACS for interpretation and routinely sending spectral series to PACS can facilitate integration with clinical workflow. The Society of Abdominal Radiology PCD Emerging Technology Commission endorsed this article.

The detection of peaks shifts in Raman spectroscopy enables a fingerprint reconstruction to discriminate among molecules with neither labelling nor sample preparation. Time-resolved Raman spectroscopy is an effective technique to reject the strong fluorescence background that profits from the time scale difference in the two responses: Raman photons are scattered almost instantaneously while fluorescence shows a nanoseconds time constant decay. The combination of short laser pulses with time-gated detectors enables the collection of only those photons synchronous with the pulse, thus rejecting fluorescent ones. This review addresses time-gating issues from the sensor standpoint and identifies single photon avalanche diode (SPAD) arrays as the most suitable single-photon detectors to be rapidly and precisely time-gated without bulky, complex, or expensive setups. At first, we discuss the requirements for ideal Raman SPAD arrays, particularly focusing on the design guidelines for optimized on-chip processing electronics. Then we present some existing SPAD-based architectures, featuring specific operation modes which can be usefully exploited for Raman spectroscopy. Finally, we highlight key aspects for future ultrafast Raman platforms and highly integrated sensors capable of undistorted identification of Raman peaks across many pixels.

Detecting submerged targets in shallow waters from satellite platforms remains a challenge, as the optical spectral information of targets is significantly distorted by the absorption and scattering effects of the water column. In this study, we propose a new framework as the bathymetry‐informed target extraction, which integrates the spaceborne lidar data and multispectral imagery. By using lidar assisted Satellite‐Derived Bathymetry model, we convert the complex multispectral information into relative depth data. Through this transformation, the challenging issue of distorted color domain image segmentation is converted into the task of depth anomaly detection. The method is validated on submerged artificial stone weirs and breakwaters in typical open ocean and coastal waters, which indicates significant improvements in target detection rate and reliability compared to direct color‐based methods. This approach promises large‐scale surveys of submerged targets in shallow waters, offering an alternative solution to on‐site surveys such as shipborne sonars.

Accurately detecting defect-induced photon emissions enables early defect detection and characterization. To address this, a defect evolution state recognition model based on phase-resolved photon counting and dimensionality reduction calculations is proposed under alternating current (AC) excitation. Initially, photon information from protruding metal defects simulated using needle–plane electrodes during partial discharge (PD) evolution is analyzed in SF6. Subsequently, phase-resolved photon counting (PRPC) techniques and statistical analysis are employed to extract feature parameters for quantitative characterization of defect-induced photon responses. Finally, a t-distributed stochastic neighbor embedding (t-SNE) dimensionality reduction analysis is utilized to establish criteria for categorizing defect evolution states. The findings reveal that metal-particle-triggered optical PRPC maintains the obvious polarity effect, and the entire evolution of the discharge can be divided into three processes. These research findings are expected to advance the accurate assessment of operational risks in gas-insulated systems.

Photon-counting computed tomography (PCCT) is a new advanced imaging technique that is going to transform the standard clinical use of computed tomography (CT) imaging. Photon-counting detectors resolve the number of photons and the incident X-ray energy spectrum into multiple energy bins. Compared with conventional CT technology, PCCT offers the advantages of improved spatial and contrast resolution, reduction of image noise and artifacts, reduced radiation exposure, and multi-energy/multi-parametric imaging based on the atomic properties of tissues, with the consequent possibility to use different contrast agents and improve quantitative imaging. This narrative review first briefly describes the technical principles and the benefits of photon-counting CT and then provides a synthetic outline of the current literature on its use for vascular imaging.

Count‐loss characteristics of photon‐counting 2D detectors are demonstrated for eight bunch‐modes at SPring‐8 through Monte Carlo simulations. As an indicator, the effective maximum count rate was introduced to signify the X‐ray intensity that the detector can count with a linearity of 1% or better after applying a count‐loss correction in each bunch‐mode. The effective maximum count rate is revealed to vary depending on the bunch‐mode and the intrinsic dead time of the detectors, ranging from 0.012 to 0.916 Mcps (megacounts per second) for a 120 ns dead time, 0.009 to 0.807 Mcps for a 0.5 µs dead time and 0.020 to 0.273 Mcps for a 3 µs intrinsic detector dead time. Even with equal‐interval bunch‐modes at SPring‐8, the effective maximum count rate does not exceed 1 Mcps pixel−1. In other words, to obtain data with a linearity better than 1%, the maximum intensity of X‐rays entering the detector should be reduced to 1 Mcps pixel−1 or less, and, in some cases, even lower, depending on the bunch‐mode. When applying count‐loss correction using optimized dead times tailored to each bunch‐mode, the effective maximum count rate exceeds the values above. However, differences in the effective maximum count rate due to bunch‐modes persist. Users of photon‐counting 2D detectors are encouraged to familiarize themselves with the count‐loss characteristics dependent on bunch‐mode, and to conduct experiments accordingly. In addition, when designing the time structure of bunch‐modes at synchrotron radiation facilities, it is essential to take into account the impact on experiments using photon‐counting 2D detectors. The effects of SPring‐8 bunch‐modes on the count‐loss features of photon‐counting detectors and effective maximum count rates are discussed.

This experimental phantom study investigates current standard of care protocols in cone beam computed tomography (CBCT), energy-integrating-detector (EID) CT, and photon-counting-detector (PCD) CT regarding their potential in delineation of dental root canals. Artificial accessory canals (diameters: 1000, 600, 400, 300 and 200 μm) were drilled into three bovine teeth mounted on a bovine rib as a jaw substitute. The phantom was scanned in two dental CBCTs, two EID-CTs and a PCD-CT using standard clinical protocols. Scans from a micro-CT served as reference standard. Spatial resolution was evaluated via line profiles through the canals, whereby visibility compared to surrounding noise and compared to the ground truth were assessed. PCD-CT was able to delineate all artificial canals down to 200 μm diameter. In CBCT and EID-CT canals could only be reliably detected down to 300 μm. Also, PCD-CT showed a considerably smaller width-divergence from the ground trough with 4.4% at 1000 μm and 35.1% at 300 μm compared to CBCT (13.5 and 72.9%) and EID-CT (10.1 and 115.7%). PCD-CT provided superior resolution, accurate size measurement, and enhanced detection of small dental root canals, thereby offering improvements in diagnostic capabilities compared to CBCT and EID-CT systems.

Accurate visualization of dental structures in root-filled teeth is critical for endodontic assessment but challenging due to artifacts from root canal (RC) fillings. This study compares photon-counting-detector CT (PCD-CT) and cone-beam CT (CBCT) for detecting small accessory canals in the presence of RC fillings. A phantom model with four bovine teeth containing RC fillings and five artificial accessory canals (1000–200 μm) per tooth was embedded in a bovine rib. The phantom was scanned with clinical PCD-CT (ultra-high-resolution protocol) and dental CBCT (endodontic protocol). Canal visibility was evaluated using signal-to-noise criteria, and canal diameters were compared with micro-CT measurements, serving as the reference. Blooming artifacts from RC fillings were quantified using the full width at half maximum (FWHM) of attenuation profiles. PCD-CT detected all canals down to 400 μm and 81.5% at 200 μm, while CBCT reliably detected canals ≥ 800 μm, with detection dropping to 47.2% at 400 μm and none at 200 μm. Measurement errors for canal diameters were lower with PCD-CT. Artifact widths varied between modalities, with no clear superiority. PCD-CT provided higher detectability and measurement fidelity for small accessory canals in root-filled teeth compared to a dental CBCT, with similar filling-related blooming, supporting the potential of PCD-CT in post-treatment endodontic imaging.