BACKGROUND:Gadopiclenol is a high-relaxivity contrast agent enabling dose reduction while maintaining image quality. However, comparison with conventional agents remains limited in body MRI. PURPOSE:To intra-individually compare half-dose gadopiclenol and standard-dose gadobenate for image quality and lesion conspicuity in abdominal MRI. STUDY TYPE:Retrospective. POPULATION:One hundred patients (55 men; mean age: 64 ± 14 years) who underwent both abdominal MRI with gadobenate (0.1 mmol/kg) and gadopiclenol (0.05 mmol/kg) on the same scanner within 12 months. FIELD STRENGTH/SEQUENCE:1.5T/3T, dynamic T1-weighted imaging pre-contrast, early arterial (EAP), late arterial (LAP), portal venous (PVP), and equilibrium phases (EP) using 3D fat-suppressed gradient echo sequence. ASSESSMENT:Signal intensity of liver, pancreas, spleen, kidneys, aorta, portal vein, and abdominal lesions was measured on each phase except EAP. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and magnitude of contrast enhancement (ΔE) were calculated for organs. In lesions, lesion-to-background ratio (LBR) and ΔE were calculated. Subjective image quality and lesion conspicuity were assessed by three readers using a 5-point Likert scale. STATISTICAL TESTS:Paired t-test and Wilcoxon test. p < 0.05 indicated statistically significant results. RESULTS:Gadopiclenol yielded significantly higher CNR and SNR for pancreas, portal vein, and kidney in LAP. No significant differences in CNR (p: 0.372-0.858) and SNR (p: 0.433-0.936) were found in PVP. In EP, gadobenate showed higher hepatic CNR, while CNR and SNR of all other organs were comparable (p: 0.103-0.912). Gadopiclenol showed higher pancreatic ΔE in all enhanced phases. LBR and ΔE of 21 evaluated lesions were comparable across all phases (p: 0.100-0.821). No significant differences were observed in readers' perception of lesion enhancement (p: 0.059-0.957). CONCLUSION:Half-dose gadopiclenol provides comparable subjective image quality and lesion conspicuity to standard-dose gadobenate, with superior pancreatic, kidney, and portal vein enhancement in LAP, and similar performance in PVP and EP. LEVEL OF EVIDENCE: 4:

Photon-counting detector computed tomography (PCD-CT) is a breakthrough innovation over conventional single-energy and dual-energy CT equipped with energy-integrating detectors (EID). Because of increased spatial resolution and improved material differentiation, PCD-CT aims at improving the diagnosis of various abdominal conditions. This technology offers several advantages over EID-based CT scanners, including higher spatial and contrast resolution, reduced electronic noise, and low radiation dose exposure. Additionally, because spectral information is generated within the detectors, PCD-CT offers the possibility of routine spectral examinations and refines material decomposition through available multienergy imaging, further enhancing tissue characterization and image contrast. With most scientific literature focused on cardiovascular applications, abdominal imaging is an open field for technical and clinical research in PCD-CT. This review aims to provide a general overview of the technical principles of PCD-CT, its applications in abdominal imaging, and to summarize the main literature findings of its clinical applications in the liver, pancreas, adrenals, genitourinary system, bowel, peritoneum, and abdominal vessels. We will also highlight the pros and cons observed in clinical practice and offer insights into potential future developments of PCD-CT in abdominal imaging.

The efficacy of focal therapy (FT) has improved with the use of multiparametric MRI (mpMRI) for lesion identification, though standardized mpMRI reporting post-FT is lacking. The Prostate Imaging after Focal Ablation (PI-FAB) scoring system was recently introduced to standardize mpMRI interpretation for local recurrence post-FT. This study evaluates the diagnostic performance and inter-reader reliability of PI-FAB following cryoablation and high-intensity focused ultrasound (HIFU) modalities. This retrospective, single-institution study included all patients treated with FT from 2007 to 2023 with available follow-up mpMRI and subsequent prostate biopsy. Three fellowship-trained radiologists scored these images using the PI-FAB system. The primary objective was inter-reader agreeability of PI-FAB scores, and the secondary objective assessed performance metrics, including sensitivity, specificity, positive predictive and negative predictive value. 91 patients with 113 mpMRI exams (95 post-cryotherapy; 18 post-HIFU) were reviewed. There was substantial agreement between the readers (Fleiss’ Kappa (κ): 0.71, p < 0.001; Gwet AC2: 0.70, p < 0.03). A PI-FAB score 3 had a significant ability to rule-in csPCa with high specificity (88

ABSTRACT:Photon-counting detector computed tomography (PCD-CT) is a breakthrough innovation over conventional single-energy and dual-energy CT equipped with energy-integrating detectors (EID). Because of increased spatial resolution and improved material differentiation, PCD-CT aims at improving the diagnosis of various abdominal conditions. This technology offers several advantages over EID-based CT scanners, including higher spatial and contrast resolution, reduced electronic noise, and low radiation dose exposure. Additionally, because spectral information is generated within the detectors, PCD-CT offers the possibility of routine spectral examinations and refines material decomposition through available multienergy imaging, further enhancing tissue characterization and image contrast. With most scientific literature focused on cardiovascular applications, abdominal imaging is an open field for technical and clinical research in PCD-CT. This review aims to provide a general overview of the technical principles of PCD-CT, its applications in abdominal imaging, and to summarize the main literature findings of its clinical applications in the liver, pancreas, adrenals, genitourinary system, bowel, peritoneum, and abdominal vessels. We will also highlight the pros and cons observed in clinical practice and offer insights into potential future developments of PCD-CT in abdominal imaging.

OBJECTIVE:To evaluate an edge-on-irradiated silicon-based photon-counting detector CT (Deep Si-PCD-CT) prototype for quantification of iodine concentration and stability of HU values, as well as detectability of subtle features in simulated kidney parenchyma. MATERIALS AND METHODS:A phantom, simulating moderately and strongly enhancing kidney parenchyma (at 180 and 240 HU) inside a small, medium, and large patient (23, 30, 37 cm diameter, respectively), was scanned on a Deep Si-PCD-CT. Centered in the kidney parenchyma was a water-equivalent rod at 0 HU and a rod of 0.8 mg/mL iodine concentration to simulate a benign, mildly enhancing cystic renal lesion, as well as a rod with a 2 mm septum and 5 mm mural nodule. Accuracy and stability of HU values were evaluated with repeated ROI measurements across consecutive slices, while the septum and nodule were identified on standard polychromatic clinical images and iodine maps. Images were reconstructed with a soft tissue kernel at 0.417- and 0.625-mm slice-thickness without additional denoising. RESULTS:Deep Si-PCD-CT produced accurate HU value measurements for water, intralesional iodine content, and renal parenchymal enhancement. The HU values were similarly variable from the ground truth values as compared with measurements from a commercial energy-integrating detector CT. The nodule and septum inside the phantom were successfully identified using the new Deep Si-PCD-CT prototype, while they were difficult to identify using the standard EID-CT at clinical window-level settings. The iodine maps created from the photon-counting detector CT displayed both the nodule and the septum well, facilitating quick identification. CONCLUSIONS:Deep Si-PCD-CT is a promising tool for the accurate measurement of HU values, as well as the detection of subtle features of complexity in cystic renal lesions. It has the potential to improve the diagnosis and management of cystic renal lesions.

Photon-counting CT (PCCT) offers new opportunities for abdominal imaging by enabling higher spatial resolution, improved image quality, and reduced radiation exposure compared with conventional energy-integrating detector CT systems. However, standardized PCCT protocols for abdominal imaging are lacking, which limits clinical adoption, comparability across institutions, and multicenter research studies. The Society of Abdominal Radiology (SAR) Photon-Counting Detector CT Emerging Technology Commission created a survey to achieve consensus on common adult abdominal PCCT protocols for FDA-approved PCCT, including portal venous phase CT, multiphase aortic CTA, and multiphase pancreas CT protocols. The survey included the following items for each protocol: scan mode, tube potential, image quality level, primary viewing virtual monoenergetic imaging (VMI) level, reconstruction kernel, additional VMI or other spectral reconstructions sent to PACS, and details of archiving the special spectral imaging dataset. Consensus statements were generated based on the survey and voted on by nine radiologists from nine institutions using the consensus-minus-one method. Consensus was reached for 20 protocol features, including that 70-keV VMI is recommended for primary interpretation of portal venous and multiphase pancreas PCCT and that, for multiphase aortic CTA, low virtual monoenergetic levels should be viewed. This multiinstitutional consensus endorsed by SAR establishes standardized abdominal PCCT protocols.

Background Detection of hepatic metastases at CT is a daily task in radiology departments that influences medical and surgical treatment strategies for oncology patients. Purpose To compare simulated photon-counting CT (PCCT) with energy-integrating detector (EID) CT for the detection of small liver lesions. Materials and Methods In this reader study (July to December 2023), a virtual imaging framework was used with 50 anthropomorphic phantoms and 183 generated liver lesions (one to six lesions per phantom, 0.4-1.5 cm in diameter). Virtual CT platforms simulated PCCT and EID CT scanners. Phantoms were virtually scanned using routine (6 mGy) and low-dose (1.5 mGy) conditions and reconstructed with three kernels. A subset of 300 scans (150 PCCT vs EID CT pairs) were selected. Four radiologists independently reviewed all scans to mark liver lesions, assigned confidence scores for detection, and rated scan quality. Analysis was performed on a per-lesion basis to determine sensitivity for several variables and on a per-scan basis for scan quality. The McNemar test, two-sided paired t tests, and mixed-effects logistic regression models were fitted; P < .05 was considered indicative of statistically significant difference. Results Consensus reader sensitivity in detecting lesions was 82.1% (451 of 549) for PCCT versus 77.6% (426 of 549) for EID CT (P < .001), with a mean sensitivity gain of 4.3 percentage points ± 1.3 (P < .001 to P = .02 per reader). Readers had better subjective confidence for lesions at PCCT (mean score, 61.5 ± 22 vs 56.1 ± 24 [on a 101-point scale]; P < .001). Sensitivity was lower for lesions smaller than 1 cm, with more pronounced difference between PCCT and EID CT (74.0% [271 of 366] vs 67.2% [246 of 366]; P < .001). At the lower dose level, PCCT showed higher sensitivity than EID CT (68.9% [168 of 244] vs 61.1% [149 of 244]; P < .001) for subcentimeter lesions. In a multivariable model, PCCT was independently associated with increased odds of lesion detection (odds ratio, 1.55; P < .001). Image quality was slightly higher for PCCT (mean score, 55.3 vs 50.6 [on a 101-point scale]; P < .001). Conclusion Compared with EID CT, PCCT showed better sensitivity in the detection of small liver lesions. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Menu in this issue.

OBJECTIVE:Different methods can be used to condition imaging systems for clinical use. The purpose of this study was to assess how these methods complement one another in evaluating a system for clinical integration of an emerging technology, photon-counting computed tomography (PCCT), for thoracic imaging. METHODS:Four methods were used to assess a clinical PCCT system (NAEOTOM Alpha; Siemens Healthineers, Forchheim, Germany) across 3 reconstruction kernels (Br40f, Br48f, and Br56f). First, a phantom evaluation was performed using a computed tomography quality control phantom to characterize noise magnitude, spatial resolution, and detectability. Second, clinical images acquired using conventional and PCCT systems were used for a multi-institutional reader study where readers from 2 institutions were asked to rank their preference of images. Third, the clinical images were assessed in terms of in vivo image quality characterization of global noise index and detectability. Fourth, a virtual imaging trial was conducted using a validated simulation platform (DukeSim) that models PCCT and a virtual patient model (XCAT) with embedded lung lesions imaged under differing conditions of respiratory phase and positional displacement. Using known ground truth of the patient model, images were evaluated for quantitative biomarkers of lung intensity histograms and lesion morphology metrics. RESULTS:For the physical phantom study, the Br56f kernel was shown to have the highest resolution despite having the highest noise and lowest detectability. Readers across both institutions preferred the Br56f kernel (71% first rank) with a high interclass correlation (0.990). In vivo assessments found superior detectability for PCCT compared with conventional computed tomography but higher noise and reduced detectability with increased kernel sharpness. For the virtual imaging trial, Br40f was shown to have the best performance for histogram measures, whereas Br56f was shown to have the most precise and accurate morphology metrics. CONCLUSION:The 4 evaluation methods each have their strengths and limitations and bring complementary insight to the evaluation of PCCT. Although no method offers a complete answer, concordant findings between methods offer affirmatory confidence in a decision, whereas discordant ones offer insight for added perspective. Aggregating our findings, we concluded the Br56f kernel best for high-resolution tasks and Br40f for contrast-dependent tasks.

Purpose:Photon-counting computed tomography (PCCT) has the potential to provide superior image quality to energy-integrating CT (EICT). We objectively compare PCCT to EICT for liver lesion detection. Approach:Fifty anthropomorphic, computational phantoms with inserted liver lesions were generated. Contrast-enhanced scans of each phantom were simulated at the portal venous phase. The acquisitions were done using DukeSim, a validated CT simulation platform. Scans were simulated at two dose levels ( CTDI vol 1.5 to 6.0 mGy) modeling PCCT (NAEOTOM Alpha, Siemens, Erlangen, Germany) and EICT (SOMATOM Flash, Siemens). Images were reconstructed with varying levels of kernel sharpness (soft, medium, sharp). To provide a quantitative estimate of image quality, the modulation transfer function (MTF), frequency at 50% of the MTF ( f 50 ), noise magnitude, contrast-to-noise ratio (CNR, per lesion), and detectability index ( d ' , per lesion) were measured. Results:Across all studied conditions, the best detection performance, measured by d ' , was for PCCT images with the highest dose level and softest kernel. With soft kernel reconstruction, PCCT demonstrated improved lesion CNR and d ' compared with EICT, with a mean increase in CNR of 35.0% ( p < 0.001 ) and 21% ( p < 0.001 ) and a mean increase in d ' of 41.0% ( p < 0.001 ) and 23.3% ( p = 0.007 ) for the 1.5 and 6.0 mGy acquisitions, respectively. The improvements were greatest for larger phantoms, low-contrast lesions, and low-dose scans. Conclusions:PCCT demonstrated objective improvement in liver lesion detection and image quality metrics compared with EICT. These advances may lead to earlier and more accurate liver lesion detection, thus improving patient care.

BACKGROUND:Risk-versus-benefit optimization required a quantitative comparison of the two. The latter, directly related to effective diagnosis, can be associated to clinical risk. While many strategies have been developed to ascertain radiation risk, there has been a paucity of studies assessing clinical risk, thus limiting the optimization reach to achieve a minimum total risk to patients undergoing imaging examinations. In this study, we developed a mathematical framework for an imaging procedure total risk index considering both radiation and clinical risks based on specific tasks and investigated diseases. METHODS:The proposed model characterized total risk as the sum of radiation and clinical risks defined as functions of radiation burden, disease prevalence, false-positive rate, expected life-expectancy loss for misdiagnosis, and radiologist interpretative performance (i.e., AUC). The proposed total risk model was applied to a population of one million cases simulating a liver cancer scenario. RESULTS:For all demographics, the clinical risk outweighs radiation risk by at least 400%. The optimization application indicates that optimizing typical abdominal CT exams should involve a radiation dose increase in over 90% of the cases, with the highest risk optimization potential in Asian population (24% total risk reduction; 306% C T D I v o l increase) and lowest in Hispanic population (5% total risk reduction; 89% C T D I v o l increase). CONCLUSIONS:Framing risk-to-benefit assessment as a risk-versus-risk question, calculating both clinical and radiation risk using comparable units, allows a quantitative optimization of total risks in CT. The results highlight the dominance of clinical risk at typical CT examination dose levels, and that exaggerated dose reductions can even harm patients.

The purpose of this study was to determine if dual-energy CT (DECT) vital iodine tumor burden (ViTB), a direct assessment of tumor vascularity, allows reliable response assessment in patients with GIST compared to established CT criteria such as RECIST1.1 and modified Choi (mChoi). From 03/2014 to 12/2019, 138 patients (64 years [32-94 years]) with biopsy proven GIST were entered in this prospective, multi-center trial. All patients were treated with tyrosine kinase inhibitors (TKI) and underwent pre-treatment and follow-up DECT examinations for a minimum of 24 months. Response assessment was performed according to RECIST1.1, mChoi, vascular tumor burden (VTB) and DECT ViTB. A change in therapy management could be because of imaging (RECIST1.1 or mChoi) and/or clinical progression. The DECT ViTB criteria had the highest discrimination ability for progression-free survival (PFS) of all criteria in both first line and second line and thereafter treatment, and was significantly superior to RECIST1.1 and mChoi (p < .034). Both, the mChoi and DECT ViTB criteria demonstrated a significantly early median time-to-progression (both delta 2.5 months; both p < .036). Multivariable analysis revealed 6 variables associated with shorter overall survival: secondary mutation (HR = 4.62), polymetastatic disease (HR = 3.02), metastatic second line and thereafter treatment (HR = 2.33), shorter PFS determined by the DECT ViTB criteria (HR = 1.72), multiple organ metastases (HR = 1.51) and lower age (HR = 1.04). DECT ViTB is a reliable response criteria and provides additional value for assessing TKI treatment in GIST patients. A significant superior response discrimination ability for median PFS was observed, including non-responders at first follow-up and patients developing resistance while on therapy.

Photon counting detector CT (PCD-CT) is the newest major development in CT technology and has been commercially available since 2021. It offers major technological advantages over current standard-of-care energy integrating detector CT (EID-CT) including improved spatial resolution, improved iodine contrast to noise ratio, multi-energy imaging, and reduced noise. This article serves as a foundational basis to the technical approaches and concepts of PCD-CT technology with primary emphasis on detector technology in direct comparison to EID-CT. The article also addresses current technological challenges to PCD-CT with particular attention to cross talk and its causes (e.g., Compton scattering, fluorescence, charge sharing, K-escape) as well as pile-up.

OBJECTIVE:Patient characteristics, iodine injection, and scanning parameters can impact the quality and consistency of contrast enhancement of hepatic parenchyma in CT imaging. Improving the consistency and adequacy of contrast enhancement can enhance diagnostic accuracy and reduce clinical practice variability, with added positive implications for safety and cost-effectiveness in the use of contrast medium. We developed a clinical tool that uses patient attributes (height, weight, sex, age) to predict hepatic enhancement and suggest alternative injection/scanning parameters to optimize the procedure. METHODS:The tool was based on a previously validated neural network prediction model that suggested adjustments for patients with predicted insufficient enhancement. We conducted a prospective clinical study in which we tested this tool in 24 patients aiming for a target portal-venous parenchyma CT number of 110 HU ± 10 HU. RESULTS:Out of the 24 patients, 15 received adjustments to their iodine contrast injection parameters, resulting in median reductions of 8.8% in volume and 9.1% in injection rate. The scan delays were reduced by an average of 42.6%. We compared the results with the patients' previous scans and found that the tool improved consistency and reduced the number of underenhanced patients. The median enhancement remained relatively unchanged, but the number of underenhanced patients was reduced by half, and all previously overenhanced patients received enhancement reductions. CONCLUSIONS:Our study showed that the proposed patient-informed clinical framework can predict optimal contrast enhancement and suggest empiric injection/scanning parameters to achieve consistent and sufficient contrast enhancement of hepatic parenchyma. The described GUI-based tool can prospectively inform clinical decision-making predicting optimal patient's hepatic parenchyma contrast enhancement. This reduces instances of nondiagnostic/insufficient enhancement in patients.

PURPOSE:Photon-counting detector CT (PCD CT) is a promising technology for abdominal imaging due to its ability to provide high spatial and contrast resolution images with reduced patient radiation exposure. However, there is currently no consensus regarding the optimal imaging protocols for PCD CT. This article aims to present the PCD CT abdominal imaging protocols used by two tertiary care academic centers in the United States.METHODS:A review of PCD CT abdominal imaging protocols was conducted by two abdominal radiologists at different academic institutions. Protocols were compared in terms of acquisition parameters and reconstruction settings. Both imaging centers independently selected similar protocols for PCD CT abdominal imaging, using QuantumPlus mode.RESULTS:There were some differences in the use of reconstruction kernels and iterative reconstruction levels, however the individual combination at each site resulted in similar image impressions. Overall, the imaging protocols used by both centers provide high-quality images with low radiation exposure.CONCLUSION:These findings provide valuable insights into the development of standardized protocols for PCD CT abdominal imaging, which can help to ensure consistent as well as high-quality imaging across different institutions and allow for future multicenter research collaborations.

To determine whether image reconstruction with a higher matrix size improves image quality for lower extremity CTA studies. Raw data from 50 consecutive lower extremity CTA studies acquired on two MDCT scanners (SOMATOM Flash, Force) in patients evaluated for peripheral arterial disease (PAD) were retrospectively collected and reconstructed with standard (512 × 512) and higher resolution (768 × 768, 1024 × 1024) matrix sizes. Five blinded readers reviewed representative transverse images in randomized order (150 total). Readers graded image quality (0 (worst)–100 (best)) for vascular wall definition, image noise, and confidence in stenosis grading. Ten patients’ stenosis scores on CTA images were compared to invasive angiography. Scores were compared using mixed effects linear regression. Reconstructions with 1024 × 1024 matrix were ranked significantly better for wall definition (mean score 72, 95

Abstract Photon-counting computed tomography (PCCT) imaging uses a new detector technology to provide added information beyond what can already be obtained with current CT and MR technologies. This review provides an overview of PCCT of the abdomen and focuses specifically on applications that benefit the most from this new imaging technique. We describe the requirements for a successful abdominal PCCT acquisition and the challenges for clinical translation. The review highlights work done within the last year with an emphasis on new protocols that have been tested in clinical practice. Applications of PCCT include imaging of cystic lesions, sources of bleeding, and cancers. Photon-counting CT is positioned to move beyond detection of disease to better quantitative staging of disease and measurement of treatment response.

PURPOSE:To compare liver fat quantification between MRI and photon-counting CT (PCCT). METHOD:A cylindrical phantom with inserts containing six concentrations of oil (0, 10, 20, 30, 50 and 100%) and oil-iodine mixtures (0, 10, 20, 30 and 50% fat +3 mg/mL iodine) was imaged with a PCCT (NAEOTOM Alpha) and a 1.5 T MRI system (MR 450w, IDEAL-IQ sequence), using clinical parameters. An IRB-approved prospective clinical evaluation included 12 obese adult patients with known fatty liver disease (seven women, mean age: 61.5 ± 13 years, mean BMI: 30.3 ± 4.7 kg/m2). Patients underwent a same-day clinical MRI and PCCT of the abdomen. Liver fat fractions were calculated for four segments (I, II, IVa and VII) using in- and opposed-phase on MRI ((Meanin - Meanopp)/2*Meanin) and iodine-fat, tissue decomposition analysis in PCCT (Syngo.Via VB60A). CT and MRI Fat fractions were compared using two-sample t-tests with equal variance. Statistical analysis was performed using RStudio (Version1.4.1717). RESULTS:Phantom results showed no significant differences between the known fat fractions (P = 0.32) or iodine (P = 0.6) in comparison to PCCT-measured concentrations, and no statistically significant difference between known and MRI-measured fat fractions (P = 0.363). In patients, the mean fat signal fraction measured on MRI and PCCT was 13.1 ± 9.9% and 12.0 ± 9.0%, respectively, with an average difference of 1.1 ± 1.9% between the modalities (P = 0.138). CONCLUSION:First experience shows promising accuracy of liver fat fraction quantification for PCCT in obese patients. This method may improve opportunistic screening for CT in the future.

Evaluate a novel algorithm for noise reduction in obese patients using dual-source dual-energy (DE) CT imaging. Seventy-nine patients with contrast-enhanced abdominal imaging (54 women; age: 58 ± 14 years; BMI: 39 ± 5 kg/m2, range: 35–62 kg/m2) from seven DECT (SOMATOM Flash or Force) were retrospectively included (01/2019–12/2020). Image domain data were reconstructed with the standard clinical algorithm (ADMIRE/SAFIRE 2), and denoised with a comparison (ME-NLM) and a test algorithm (rank-sparse kernel regression). Contrast-to-noise ratio (CNR) was calculated. Four blinded readers evaluated the same original and denoised images (0 (worst)–100 (best)) in randomized order for perceived image noise, quality, and their comfort making a diagnosis from a table of 80 options. Comparisons between algorithms were performed using paired t-tests and mixed-effects linear modeling. Average CNR was 5.0 ± 1.9 (original), 31.1 ± 10.3 (comparison; p < 0.001), and 8.9 ± 2.9 (test; p < 0.001). Readers were in good to moderate agreement over perceived image noise (ICC: 0.83), image quality (ICC: 0.71), and diagnostic comfort (ICC: 0.6). Diagnostic accuracy was low across algorithms (accuracy: 66, 63, and 67

Computed tomography (CT) has seen remarkable developments in the past several decades, radically transforming the role of imaging in day-to-day clinical practice. Dual-energy CT (DECT), an exciting innovation introduced in the early part of this century, has widened the scope of CT, opening new opportunities due to its ability to provide superior tissue characterization. The introduction of photon-counting CT (PCCT) heralds a paradigm shift in CT scanner technology representing another significant milestone in CT innovation. PCCT offers several advantages over DECT, such as improved spectral resolution, enhanced tissue characterization, reduced image artifacts, and improved image quality.