Photon-counting CT Research Articles

Technical challenges and benefits of photon counting detector computed tomography

X-ray detector is the essential part of a computed tomography (CT) system that controls dose efficiency and image quality. All clinical CT scanners utilized scintillating detectors up until the first clinical photon-counting-detector (PCD) system was approved in 2021. These detectors do not record information about individual photons during the two-step detection process. PCDs, on the other hand, employ a single step process that transforms X-ray radiation straight into an electrical signal. This retains information on individual photons, allowing one to count the quantity of X-rays in various energy ranges. Better spatial resolution, reduced dosages of iodinated contrast material, enhanced iodine signal, enhanced radiation dose efficiency, and the lack of electronic noise are the main benefits of PCDs. PCDs with multiple energy thresholds are able to separate detected photons into two or more energy bins, allowing for the availability of energy-resolved data for each record. In the event of dual-source CT, this permits high pitch or high temporal resolution acquisitions in addition to high spatial resolution for tasks involving material quantification or classification. PCDCT imaging of anatomy, where excellent spatial resolution provides clinical benefit, is one of the most promising uses of the technology. Inner ear, bone, small blood artery, heart, and lung imaging are among them. Photon-counting CT will become the wave of the future for workhorse CT imaging systems. An overview of the PCDCT principle, possible clinical benefits, and limitations of conventional CT is provided in this review paper, along with potential future developments for this CT imaging technology.

Photon counting CT clinical adoption, integration, and workflow.

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.

Robustness of radiomics among photon-counting detector CT and dual-energy CT systems: a texture phantom study.

To evaluate the robustness of radiomics features among photon-counting detector CT (PCD-CT) and dual-energy CT (DECT) systems. A texture phantom consisting of twenty-eight materials was scanned with one PCD-CT and four DECT systems (dual-source, rapid kV-switching, dual-layer, and sequential scanning) at three dose levels twice. Thirty sets of virtual monochromatic images at 70 keV were reconstructed. Regions of interest were delineated for each material with a rigid registration. Ninety-three radiomics were extracted per PyRadiomics. The test-retest repeatability between repeated scans was assessed by Bland-Altman analysis. The intra-system reproducibility between dose levels, and inter-system reproducibility within the same dose level, were evaluated by intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC). Inter-system variability among five scanners was assessed by coefficient of variation (CV) and quartile coefficient of dispersion (QCD). The test-retest repeatability analysis presented that 97.1% of features were repeatable between scan-rescans. The mean ± standard deviation ICC and CCC were 0.945 ± 0.079 and 0.945 ± 0.079 for intra-system reproducibility, respectively, and 86.0% and 85.7% of features were with ICC > 0.90 and CCC > 0.90, respectively, between different dose levels. The mean ± standard deviation ICC and CCC were 0.157 ± 0.174 and 0.157 ± 0.174 for inter-system reproducibility, respectively, and none of the features were with ICC > 0.90 or CCC > 0.90 within the same dose level. The inter-system variability suggested that 6.5% and 12.8% of features were with CV < 10% and QCD < 10%, respectively, among five CT systems. The radiomics features were non-reproducible with significant variability in values among different CT techniques. Radiomics features are non-reproducible with significant variability in values among photon-counting detector CT and dual-energy CT systems, necessitating careful attention to improve the cross-system generalizability of radiomic features before implementation of radiomics analysis in clinical routine. CT radiomics stability should be guaranteed before the implementation in the clinical routine. Radiomics robustness was on a low level among photon-counting detectors and dual-energy CT techniques. Limited inter-system robustness of radiomic features may impact the generalizability of models.

Investigation of abdominal artery delineation by photon-counting detector CT

ObjectivesTo evaluate the ability of 50-keV virtual monoenergetic images (VMI) to depict abdominal arteries in abdominal CT angiography (CTA) compared with 70-keV VMI with photon-counting detector CT (PCD-CT).MethodsFifty consecutive patients who underwent multiphase abdominal scans between March and April 2023 were included. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were quantitatively assessed for the abdominal aorta (AA), celiac artery (CeA), superior mesenteric artery (SMA), renal artery (RA), and right hepatic artery (RHA) at both 50- and 70-keV VMI. In addition, 3D images from CTA were analyzed to measure arterial lengths and evaluate the visualization of distal branches.ResultsSignificantly higher SNR and CNR were observed at 50-keV compared to 70-keV VMI for all arteries: AA (36.54 and 48.28 vs. 25.70 and 28.46), CeA (22.39 and 48.38 vs. 19.09 and 29.15), SMA (23.34 and 49.34 vs. 19.67 and 29.71), RA (22.88 and 48.84 vs. 20.15 and 29.41), and RHA (14.38 and 44.41 vs. 13.45 and 27.18), all p < 0.05. Arterial lengths were also significantly longer at 50-keV: RHA (192.6 vs. 180.3 mm), SMA (230.9 vs. 216.5 mm), and RA (95.9 vs. 92.0 mm), all p < 0.001.ConclusionIn abdominal CTA with PCD-CT, 50-keV VMI demonstrated superior quantitative image quality compared to 70-keV VMI. In addition, 50-keV VMI 3D CTA allowed better visualization of abdominal artery branches, highlighting its potential clinical advantage for improved imaging and detailed assessment of abdominal arteries.

Comparison of automated kidney stone size measurement and volumetry in photon counting CT compared to 3rd generation dual energy CT and physically measurements - an ex vivo study.

This ex vivo study aimed to compare a newly developed dual-source photon-counting CT (PCCT) with a 3rd generation dual-source dual-energy CT (DECT) for the detection and measurement (stone lengths and volumetrics) of urinary stones. 143 urinary stones with a known geometry were physically measured and defined as reference values. Next, urinary stones were placed in an anthropomorphic abdomen-model and were scanned with DECT and PCCT. Images were read by two experienced examiners and automatically evaluated using a specific software. DECT and PCCT showed a high sensitivity for manual stone detection of 97.9% and 94.4%, and for automatic detection of 93.0% and 87.4%, respectively. Compared to that uric acid and xanthine stones were recognized slightly worse by DECT and PCCT with manual stone detection (93.3% and 82.2%), and with automatic detection (77.8% and 60.0%). All other stone entities were completely recognized. By comparing the maximum diameter of the reference value and DECT, Pearson-correlation was 0.96 (p < 0.001) for manual and 0.97 (p < 0.001) for automatic measurement, and for PCCT it was 0.94 (p < 0.001) for manual and 0.97 (p < 0.001) for automatic measurements. DECT and PCCT can also reliably determine volume manually and automatically with a Pearson-correlation of 0.99 (p < 0.001), respectively. Both CTs showed comparable results in stone detection, length measurement and volumetry compared to the reference values. Automatic measurement tends to underestimate the maximum diameter. DECT proved to be slightly superior in the recognition of xanthine and uric acid stones.

Establishing a Foundation for the In Vivo Visualization of Intravascular Blood with Photon-Counting Technology in Spectral Imaging in Cranial CT.

Advances in computed tomography (CT) technology, particularly photon-counting CT (PCCT), are reshaping the possibilities for medical imaging. PCCT in spectral imaging enables the high-resolution visualization of tissues with material-specific accuracy. This study aims to establish a foundational approach for the in vivo visualization of intracranial blood using PCCT, focusing on non-enhanced imaging techniques and spectral imaging capabilities. We employed photon-counting detector within a spectral CT framework to differentiate between venous and arterial intracranial blood. Our analysis included not only monoenergetic +67 keV reconstructions, but also images from virtual non-contrast and iodine phases, enabling detailed assessments of blood's characteristics without the use of contrast agents. Our findings demonstrate the ability of PCCT to provide clear and distinct visualizations of intracranial vascular structures. We quantified the signal-to-noise ratio across different imaging phases and found consistent enhancements in image clarity, particularly in the detection and differentiation of arterial and venous blood. PCCT offers a robust platform for the non-invasive and detailed visualization of intravascular intracranial blood. With its superior resolution and specific imaging capabilities, PCCT lays the groundwork for advancing clinical applications and research, notably in the diagnosis and management of intracranial disorders. This technology promises to improve diagnostic accuracy by enabling more precise imaging assessments.

Detection of myeloma-associated osteolytic bone lesions with energy-integrating and photon-counting detector CT.

Arecent innovation in computed tomography (CT) imaging has been the introduction of photon-counting detector CT (PCD-CT) systems, which are able to register the number and the energy level of incoming x‑ray photons and have smaller detector elements compared with conventional CT scanners that operate with energy-integrating detectors (EID-CT). The study aimed to evaluate the potential benefits of anovel, non-CE certified PCD-CT in detecting myeloma-associated osteolytic bone lesions (OL) compared with astate-of-the-art EID-CT. Nine patients with multiple myeloma stageIII (according to Durie and Salmon) underwent magnetic resonance imaging (MRI), EID-CT, and PCD-CT of the lower lumbar spine and pelvis. The PCD-CT and EID-CT images of all myeloma lesions that were visible in clinical MRI scans were reviewed by three radiologists for corresponding OL. Additionally, the visualization of destructions to cancellous or cortical bone, and trabecular structures, was compared between PCD-CT and EID-CT. Readers detected 21% more OL in PCD-CT than in EID-CT images (138 vs. 109; p < 0.0001). The sensitivity advantage of PCD-CT in lesion detection increased with decreasing lesion size. The visualization quality of cancellous and cortical destructions as well as of trabecular structures was rated higher by all three readers in PCD-CT images (mean image quality improvements for PCD-CT over EID-CT were +0.45 for cancellous and +0.13 for cortical destructions). For myeloma-associated OL, PCD-CT demonstrated significantly higher sensitivity, especially with small size. Visualization of bone tissue and lesions was considered significantly better in PCD-CT than in EID-CT. This implies that PCD-CT scanners could potentially be used in the early detection of myeloma-associated bone lesions.

Comprehensive Review of Inner Ear Anatomy on Photon Counting CT.

The inner ear contains many fissures and canals which can mimic pathology. Photon counting CT allows greater spatial and contrast resolution of these structures over traditional energy integrating CT detectors. Small channels containing nerves, arteries, and normal anatomy such as the cochlear cleft, cochlear and vestibular aqueducts are commonly encountered on temporal bone imaging. The improved visualization of these structures poses challenges for radiologists who are new photon counting CT. This manuscript updates the existing temporal bone anatomy literature with a detailed anatomical review of the inner ear and major nerves frequently encountered when reviewing temporal bone imaging.ABBREVIATIONS: EID = energy-integrating detector; PCT = photon-counting computed tomography, CPA = cerebellopontine angle; IAC = internal auditory canal.

Self-supervised tomographic image noise suppression via residual image prior network

Computed tomography (CT) denoising is a challenging task in medical imaging that has garnered considerable attention. Supervised networks require a lot of noisy-clean image pairs, which are always unavailable in clinical settings. Existing self-supervised algorithms for suppressing noise with paired noisy images have limitations, such as ignoring the residual between similar image pairs during training and insufficiently learning the spectrum information of images. In this study, we propose a Residual Image Prior Network (RIP-Net) to sufficiently model the residual between the paired similar noisy images. Our approach offers new insights into the field by addressing the limitations of existing methods. We first establish a mathematical theorem clarifying the non-equivalence between similar-image-based self-supervised learning and supervised learning. It helps us better understand the strengths and limitations of self-supervised learning. Secondly, we introduce a novel regularization term to model a low-frequency residual image prior. This can improve the accuracy and robustness of our model. Finally, we design a well-structured denoising network capable of exploring spectrum information while simultaneously sensing context messages. The network has dual paths for modeling high and low-frequency compositions in the raw noisy image. Additionally, context perception modules capture local and global interactions to produce high-quality images. The comprehensive experiments on preclinical photon-counting CT, clinical brain CT, and low-dose CT datasets, demonstrate that our RIP-Net is superior to other unsupervised denoising methods.

Technical note: Can photon-counting CT improve PET/CT's quantitative accuracy?

Linear attenuation coefficients (LACs) in positron emission tomography combined with computed tomography (PET/CT) are derived from CT scans that utilize energy-integrating detectors (EID-CT). These LACs are inaccurate when iodine contrast has been injected. Photon counting detector CT (PCD-CT) may be able to improve the accuracy. To investigate whether PCD-CT can improve PET/CT quantitative accuracy. Two experiments were performed: one with CT only and one that combined PET and CT. The first experiment used an electron density phantom whose inserts were imaged with EID-CT and PCD-CT. The inserts simulated normal human tissues, including bone and iodinated blood. In the case of PCD-CT, virtual-monoenergetic images at 190keV were created. LACs were derived in each case and compared against known values. For inserts with iodine, more accurate LACs were expected with PCD-CT. The second experiment involved a custom PET phantom with various materials simulating human tissues (blood, iodinated blood, and bone) and 18F radioactivity. Data were first acquired with an EID-CT-based PET/CT system and then separately in a PCD-CT system without PET. PET images were reconstructed using LAC from EID-CT and PCD-CT. PET image values were compared against known activity values using recovery coefficients (RC). In the first experiment, LAC based on EID-CT were in error by as much as 18%, whereas the corresponding PCD-CT based measurements were within 3%. In the second experiment, minimum, maximum, and mean RC were (96.1%, 115.4%, and 103.8%) for the EID-CT method, and (95.8%, 105.5%, and 101.0%) for the PCD-CT method. The consistency of PET images in body and head orientations was improved. PCD-CT can acquire the information needed for accurate LAC for PET reconstruction in a single spiral acquisition.

Multivariate signal-to-noise ratio as a metric for characterizing spectral computed tomography

Objective. With the introduction of spectral CT techniques into the clinic, the imaging capacities of CT were expanded to multiple energy levels. Due to a variety of factors, the acquired signal in spectral CT datasets is shared between these images. Conventional image quality metrics assume independence between images which is not preserved within spectral CT datasets, limiting their utility for characterizing energy selective images. The purpose of this work was to develop a metrology to characterize energy selective images by incorporating the shared information between images within a spectral CT dataset. Approach. The signal-to-noise ratio (SNR) was extended into a multivariate space where each image within a spectral CT dataset was treated as a separate information channel. The general definition was applied to the specific case of contrast to define a multivariate contrast-to-noise ratio (CNR). The matrix contained two types of terms: a conventional CNR term which characterized image quality within each image in the spectral CT dataset and covariance weighted CNR (Covar-CNR) which characterized the contrast in each image relative to the covariance between images. Experimental data from an investigational photon-counting CT scanner was used to demonstrate the insight of this metrology. A cylindrical water phantom containing vials of iodine and gadolinium (2, 4, and 8 mg ml−1) was imaged under conditions of variable tube current, tube voltage, and energy threshold. Two image series (threshold and bin images) containing two images each were defined based upon the contribution of photons to reconstructed images. Analysis of variance (ANOVA) was calculated between CNR terms and image acquisition variables. A multivariate regression was then fitted to experimental data. Main Results. Image type had a major difference on how Covar-CNR values were distributed. Bin images had a slightly higher mean and wider standard deviation (Covar-CNRlo: 3.38 ±17.25, Covar-CNRhi: 5.77 ± 30.64) compared to threshold images (Covar-CNRlo: 2.08 ±1.89, Covar-CNRhi: 3.45 ± 2.49) across all conditions. ANOVA found that each acquisition variable had a significant relationship with both Covar-CNR terms. The multivariate regression model suggested that material concentration had the largest impact on all CNR terms. Signficance. In this work, we described a theoretical framework to extend the SNR to a multivariate form that is able to characterize images independently and also provide insight regarding the relationship between images. Experimental data was used to demonstrate the insight that this metrology provides about image formation factors in spectral CT.

CT in musculoskeletal imaging: still helpful and for what?

Computed tomography (CT) is a common modality employed for musculoskeletal imaging. Conventional CT techniques are useful for the assessment of trauma in detection, characterization and surgical planning of complex fractures. CT arthrography can depict internal derangement lesions and impact medical decision making of orthopedic providers. In oncology, CT can have a role in the characterization of bone tumors and may elucidate soft tissue mineralization patterns. Several advances in CT technology have led to a variety of acquisition techniques with distinct clinical applications. These include four-dimensional CT, which allows examination of joints during motion; cone-beam CT, which allows examination during physiological weight-bearing conditions; dual-energy CT, which allows material decomposition useful in musculoskeletal deposition disorders (e.g., gout) and bone marrow edema detection; and photon-counting CT, which provides increased spatial resolution, decreased radiation, and material decomposition compared to standard multi-detector CT systems due to its ability to directly translate X-ray photon energies into electrical signals. Advanced acquisition techniques provide higher spatial resolution scans capable of enhanced bony microarchitecture and bone mineral density assessment. Together, these CT acquisition techniques will continue to play a substantial role in the practices of orthopedics, rheumatology, metabolic bone, oncology, and interventional radiology.

Combined conventional factors and the radiomics signature of coronary plaque texture could improve cardiac risk prediction

ObjectivesThis study aims to investigate how radiomics analysis can help understand the association between plaque texture, epicardial adipose tissue (EAT), and cardiovascular risk. Working with a Photon-counting CT, which exhibits enhanced feature stability, offers the potential to advance radiomics analysis and enable its integration into clinical routines.MethodsCoronary plaques were manually segmented in this retrospective, single-centre study and radiomic features were extracted using pyradiomics. The study population was divided into groups according to the presence of high-risk plaques (HRP), plaques with at least 50% stenosis, plaques with at least 70% stenosis, or triple-vessel disease. A combined group with patients exhibiting at least one of these risk factors was formed. Random forest feature selection identified differentiating features for the groups. EAT thickness and density were measured and compared with feature selection results.ResultsA total number of 306 plaques from 61 patients (mean age 61 years +/− 8.85 [standard deviation], 13 female) were analysed. Plaques of patients with HRP features or relevant stenosis demonstrated a higher presence of texture heterogeneity through various radiomics features compared to patients with only an intermediate stenosis degree. While EAT thickness did not significantly differ, affected patients showed significantly higher mean densities in the 50%, HRP, and combined groups, and insignificantly higher densities in the 70% and triple-vessel groups.ConclusionThe combination of a higher EAT density and a more heterogeneous plaque texture might offer an additional tool in identifying patients with an elevated risk of cardiovascular events.Clinical relevance statementCardiovascular disease is the leading cause of mortality globally. Plaque composition and changes in the EAT are connected to cardiac risk. A better understanding of the interrelation of these risk indicators can lead to improved cardiac risk prediction.Key PointsCardiac plaque composition and changes in the EAT are connected to cardiac risk.Higher EAT density and more heterogeneous plaque texture are related to traditional risk indicators.Radiomics texture analysis conducted on PCCT scans can help identify patients with elevated cardiac risk.Graphical

Prospective ECG-gated High-Pitch Photon-Counting CT Angiography: Evaluation of measurement accuracy for aortic annulus sizing in TAVR planning

PurposeIn planning transcatheter aortic valve replacement (TAVR), retrospective cardiac spiral-CT is recommended to measure aortic annulus with subsequent CT-angiography (CTA) to evaluate access routes. Photon-counting detector (PCD)-CT enables to assess the aortic annulus in desired cardiac phases, using prospective ECG-gated high-pitch CTA. The aim of this study was to evaluate the measurement accuracy of aortic annulus using prospective ECG-gated high-pitch CTA against retrospective spiral-CT reference. MethodThirty patients underwent cardiac spiral-CT and prospective ECG-gated (30% R-R on aortic valve level) high-pitch CTA. Using propensity score matching, another 30 patients were identified whose CTA was performed using high-pitch mode without ECG-synchronization. Two investigators measured annular diameter, perimeter, and area on cardiac spiral-CT and high-pitch CTA. ResultsThe aortic valve was imaged in systole in 90 % of prospective ECG-gated CTA cases but only 50 % of non-ECG-gated CTA cases (p = 0.002). There was a strong correlation (r ≥ 0.94) without significant differences (p ≥ 0.09) between cardiac spiral-CT and prospective ECG-gated high-pitch CTA for all annulus measurements. In contrast, significant differences were found in annular short-axis diameter and area between cardiac spiral-CT and non-ECG-gated high-pitch CTA (p ≤ 0.03). Furthermore, prospective ECG-gated high-pitch CTA showed significantly reduced radiation exposure compared with cardiac spiral-CT (CTDI 4.52 vs. 24.10 mGy; p < 0.001). ConclusionPCD-CT-based prospective ECG-gated high-pitch scans with targeted systolic acquisition at the level of the aortic valve can simultaneously visualize TAVR access routes and accurately measure systolic annulus size. This approach could aid in optimizing protocols to achieve lower radiation doses in the growing population of younger, low-risk TAVR patients.

A minireview of four-dimensional CT and joint biomechanics

Since its introduction, four dimensional computed tomography (4D CT) has improved the precision of a variety of diagnostic challenges such as radiation therapy in oncology and has also been expanded into cardiovascular assessments as well. Its use in musculoskeletal imaging marks a breakthrough in peripheral joint imaging, enabling detailed analysis of joint biomechanics and stability across various joints such as the knee, wrist, shoulder, and ankle. Studies employing 4D CT have offered new insights into normative and altered joint biomechanics, contributing to the diagnosis of joint pathologies and aiding in surgical planning. Looking ahead, artificial intelligence and photon-counting CT systems are poised to further refine 4D CT's capabilities, potentially leading to personalized diagnostic and therapeutic approaches based on individualized biomechanical characteristics. This review delves into the transformative role of four-dimensional computed tomography in musculoskeletal imaging, particularly its applications in understanding joint biomechanics.

The Photon-Counting CT Enters the Field of Cochlear Implantation: Comparison to Angiography DynaCT and Conventional Multislice CT.

Cochlear duct length (CDL) measurement plays a role in the context of individualized cochlear implant (CI) surgery regarding an individualized selection and implantation of the CI electrode carrier and an efficient postoperative anatomy-based fitting process. The level of detail of the preoperative temporal bone CT scan depends on the imaging modality with major impact on CDL measurements and CI electrode contact position determination. The aim of this study was to evaluate the accuracy of perioperative CDL measurements and electrode contact determination in photon-counting CT (PCCT). Ten human fresh-frozen petrous bone specimens were examined with a first-generation PCCT. A clinically applicable radiation dose of 27.1 mGy was used. Scans were acquired before and after CI insertion. Postoperative measurement of the CDL was conducted using an otological planning software and 3D-curved multiplanar reconstruction. Investigation of electrode contact position was performed by two respective observers. Measurements were compared with a conventional multislice CT and to a high-resolution flat-panel volume CT with secondary reconstructions. Pre- and postoperative CDL measurements in PCCT images showed no significant difference to high-resolution flat-panel volume CT. Postoperative CI electrode contact determination was also as precise as the flat-panel CT-based assessment. PCCT and flat-panel volume CT were equivalent concerning interobserver variability. CDL measurement with PCCT was equivalent to flat-panel volume CT with secondary reconstructions. PCCT enabled highly precise postoperative CI electrode contact determination with substantial advantages over conventional multislice CT scanners.

Recent Advances in Fast-Decaying Metal Halide Perovskites Scintillators.

Fast-decaying scintillators show subnanoseconds or nanoseconds lifetime and high time resolution, making them important in nuclear physics, medical diagnostics, scientific research, and other fields. Metal halide perovskites (MHPs) show great potential for scintillator applications owing to their easy synthesis procedure and attractive optical properties. However, MHPs scintillators still need further improvement in decay lifetime. To optimize the decay lifetime, great progress has been achieved recently. In this Perspective, we first summarize the structural characteristics of MHPs in various dimensions, which brings different exciton behaviors. Then, recent advances in designing fast-decaying MHPs according to different exciton behaviors have been concluded, focusing on the photophysical mechanisms to achieve fast-decaying lifetimes. These advancements in decay lifetimes could facilitate the MHPs scintillators in advanced applications, such as time-of-flight positron emission tomography (TOF-PET), photon-counting computed tomography (PCCT), etc. Finally, the challenges and future opportunities are discussed to provide a roadmap for designing novel fast-decaying MHPs scintillators.

Accurate Reconstruction of Multiple Basis Images Directly From Dual Energy CT Data.

We develop optimization-based algorithms to accurately reconstruct multiple ( 2) basis images directly from dual-energy (DE) data in CT. In medical and industrial CT imaging, some basis materials such as bone, metals, and contrast agents of interest are confined often spatially within regions in the image. Exploiting this observation, we develop an optimization-based algorithm to reconstruct, directly from DE data, basis-region images from which multiple ( 2) basis images and virtual monochromatic images (VMIs) can be obtained over the entire image array. We conduct experimental studies using simulated and real DE data in CT, and evaluate basis images and VMIs obtained in terms of visual inspection and quantitative metrics. The study results reveal that the algorithm developed can accurately and robustly reconstruct multiple ( 2) basis images directly from DE data. The developed algorithm can yield accurate multiple ( 2) basis images, VMIs, and physical quantities of interest from DE data in CT. The work may provide insights into the development of practical procedures for reconstructing multiple basis images, VMIs, and physical quantities from DE data in applications. The work can be extended to reconstruct multiple basis images in multi-spectral or photon-counting CT.

Evaluation Of Coronary Stents With Photon-counting CT: Benefits Of High-resolution Imaging And Deep-learning Reconstruction

Evaluation Of Coronary Stents With Photon-counting CT: Benefits Of High-resolution Imaging And Deep-learning Reconstruction

Ultra-high-resolution Photon-counting Detector CT To Detect Coronary In-stent Restenosis: Comparison To Quantitative Invasive Coronary Angiography

Ultra-high-resolution Photon-counting Detector CT To Detect Coronary In-stent Restenosis: Comparison To Quantitative Invasive Coronary Angiography