What’s New in Photon Counting CT?

July 26, 2026 · 8 articles · 10 research themes · covering July 19, 2026 – July 26, 2026

Overview

A clear through-line across this week’s papers is the rapid maturation of photon-counting CT (PCD/PCCT) as a quantitative, dose-efficient alternative to energy-integrating CT (EID-CT). Multiple studies directly compare platforms and reconstruction strategies, showing that PCCT can preserve or improve diagnostic image quality while enabling meaningful reductions in radiation dose in multi-phase abdominopelvic protocols. In abdominal imaging, PCCT also appears competitive for fine anatomic delineation (e.g., hepato-bilio-pancreatic structures), and virtual monoenergetic/virtual non-contrast techniques from PCD-CT can approximate true non-contrast liver CT—supporting more streamlined workflows for hepatic steatosis quantification.

Cardiovascular imaging themes focus on making coronary plaque metrics more reliable and clinically actionable. Work on low-attenuation plaque (LAP) detection indicates that PCD-CT improves detectability relative to EID-CT, but performance depends strongly on plaque composition (calcified arcs and iodinated components) and on reconstruction energy/kernel choices. Complementing this, a reproducibility study in patients undergoing dual-platform coronary CT angiography highlights how reconstruction settings can drive inter-platform variability, and identifies harmonized options to enable consistent plaque-component endpoints—an essential step for multi-center/multi-platform clinical trials.

Beyond CT physics, two papers emphasize “mechanistic” and “precision” imaging. In ARDS, CT-derived regional strain/recruitment combined with computational modeling captures spatial heterogeneity that global measures miss, pointing toward region-specific ventilator management to reduce ventilator-induced lung injury. In heart failure, a review frames imaging as moving from descriptive phenotypes toward AI-enabled, integrated, predictive precision phenotyping—linking imaging pipelines to individualized decision support and future trial design. Finally, a whole-body imaging review for hematologic malignancies underscores practical, scenario-based selection between WBCT and WBMRI, balancing diagnostic performance with feasibility, patient tolerance, and radiation considerations.

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Coronary Plaque Imaging & Quantification (Mixed Plaque, LAP, Harmonization)

Mixed coronary plaque phantom analysis by photon-counting CT: impact of calcium and iodine on low-attenuation plaque detection.

This study used a mixed coronary plaque phantom imaged with photon-counting detector CT (PCD-CT) and compared it with energy-integrating detector CT (EID-CT) to test low-attenuation plaque (LAP) detection, varying calcium and iodine content and reconstructing virtual monoenergetic images (40–130 keV) with soft (Qr40) and sharp (Qr72) kernels. PCD-CT improved LAP detectability relative to EID-CT, with performance strongly influenced by the presence of calcified arcs and iodinated components and by reconstruction energy/kernel settings. These findings support optimizing PCD-CT acquisition and reconstruction to better quantify coronary LAP burden, potentially improving risk stratification in mixed-plaque disease.

Szilveszter B, Kolossváry M, Kubovje A et al. · European heart journal. Imaging methods and practice · (2026) · View on PubMed ↗ · Free PDF ↗

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Coronary CT Reconstruction Parameters & Reproducibility

Coronary plaque quantification on energy-integrating and photon-counting detector CT: reproducibility and power modeling for mixed-platform trials.

This retrospective study evaluated reproducibility of coronary plaque quantification between energy-integrating detector CT (EID-CT) and photon-counting detector CT (PCD-CT) in patients undergoing dual-platform coronary CT angiography within 30 days, using specific reconstruction kernels (EID: Qr40/Bv40; PCD: Bv36/40/44 and Qr36/40/44) and quantum iterative reconstruction strengths (2–4). The key finding was that plaque-component variability differed by reconstruction settings, and the authors identified reconstruction options that minimized inter-platform differences, enabling power/sample-size modeling for mixed-platform trials. Scientifically, this supports harmonizing EID-CT and PCD-CT quantitative plaque endpoints to make multi-center/multi-platform clinical trials feasible.

Vecsey-Nagy M, Hagar MT, Osoria-Velasquez J et al. · European radiology · (2026) · View on PubMed ↗ · Free PDF ↗

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Virtual Monoenergetic / Virtual Non-Contrast Imaging (PCD-CT)

Single-Phase Surrogate for True Non-Contrast Liver CT Using 190-keV Monoenergetic Imaging on Photon-Counting CT: Implications for Hepatic Steatosis Assessment.

This study evaluated whether 190-keV virtual monoenergetic imaging (VMI) from photon-counting detector CT (PCD-CT) can act as a surrogate for true non-contrast (TNC) liver CT in hepatic steatosis quantification, comparing it against virtual non-contrast (VNC) reconstructions. In 49 patients with PCD-CT and MRI-proton density fat fraction (PDFF), 190-keV VMI showed attenuation agreement with TNC (assessed with correlation and Bland–Altman analyses), supporting its use when true non-contrast scans are not available. Scientifically and clinically, this could reduce scan burden by enabling steatosis assessment from a single contrast-phase acquisition using PCCT-derived virtual non-contrast techniques.

Ohtani T, Shimada M, Nishiyama K et al. · Academic radiology · (2026) · View on PubMed ↗

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Abdominal Organ Imaging Quality (Hepato-bilio-pancreatic)

Photon-counting CT for hepato-bilio-pancreatic imaging: a qualitative head-to-head comparison with third-generation dual-source CT: preliminary results.

This retrospective head-to-head study compared photon-counting detector CT (PCCT; Siemens NAEOTOM Alpha pro) with third-generation dual-source energy-integrating CT (EID-CT; Siemens SOMATOM Force) for qualitative image quality of hepato-bilio-pancreatic anatomy in 25 patients. The key finding was that PCCT provided reader-assessed image quality and anatomical detail that were comparable or potentially superior to EID-CT, with differences influenced by reconstruction parameters such as section thickness (0.4–0.6 mm for PCCT vs 1.0 mm for EID-CT). This supports the feasibility of PCCT for abdominal organ imaging where fine anatomical delineation is important for diagnosis and staging.

Foti G, Spoto F, Spezia A et al. · La Radiologia medica · (2026) · View on PubMed ↗

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Abdominopelvic Multi-Phase Imaging & Radiation Dose Reduction

Photon-counting CT vs. energy-integrating detector CT: image quality and radiation dose in multi-phase abdominopelvic imaging.

This prospective study enrolled 94 adults to compare photon-counting CT (PCCT) versus energy-integrating CT (EID-CT) in multi-phase abdominopelvic imaging, assessing objective image quality (hepatic noise, SNR, CNR), subjective reader scores, and radiation dose metrics (CTDIvol, DLP, and nDLP). The key finding was that PCCT significantly reduced radiation dose (CTDIvol by 57%, DLP by 62%, and nDLP by 57%) while maintaining image quality measures comparable to EID-CT. This is clinically significant because it suggests PCCT can lower patient radiation exposure in abdominal multi-phase protocols without sacrificing diagnostic image quality.

Huang YF, Yang JF, Zhao L et al. · Radiation protection dosimetry · (2026) · View on PubMed ↗

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Whole-Body Imaging for Hematologic Malignancies (WBCT vs WBMRI)

Complementary Role of Whole-Body MRI and CT in Hematologic Malignancies and Bone Marrow Disorders.

This clinical review studied how whole-body MRI (WBMRI) and whole-body low-dose CT (WBCT) compare for evaluating hematologic malignancies and bone marrow disorders across diagnosis, staging, response assessment, and surveillance. The key finding was that the choice between WBCT and WBMRI depends on practical factors (scanner access, expertise, patient tolerance, radiation considerations, and cost) and that comparative evidence—particularly in multiple myeloma—can guide scenario-based selection. Clinically, it helps standardize imaging strategy decisions to balance diagnostic performance with feasibility and patient safety.

Ghotbi E, Frick M, Cook J et al. · Journal of computer assisted tomography · (2026) · View on PubMed ↗

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Heart Failure Precision Phenotyping & AI-Enabled Imaging Workflows

The Future of Imaging in Heart Failure: Toward Precision Phenotyping, Integration, and Intelligence.

This review studied current and emerging imaging approaches for heart failure (HF) with the goal of moving from modality-siloed, descriptive imaging toward integrated, predictive, patient-specific “precision phenotyping,” including the role of artificial intelligence (AI) in imaging workflows. The key finding was that AI-enabled automation (e.g., echocardiography) and intelligent acquisition/analysis pipelines are accelerating the shift toward integrated phenotyping and decision support. This is significant because it frames how imaging can directly inform individualized HF management and future clinical trial design.

Hundertmark MJ · Current heart failure reports · (2026) · View on PubMed ↗ · Free PDF ↗

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ARDS Lung Mechanics via CT-Derived Strain/Recruitment & Modeling

Quantitative assessment of lung mechanical properties in ARDS using X-ray computed tomography.

This work studied how X-ray computed tomography (CT), combined with quantitative image processing, deformable image registration, and computational modeling, can characterize regional lung mechanics in patients with acute respiratory distress syndrome (ARDS). The key finding was that CT-derived regional strain/recruitment and model-inferred mechanical stress can capture spatial heterogeneity that global physiologic measures miss, offering a more mechanistic basis for ventilator-induced lung injury (VILI) prevention. Clinically, this provides a pathway toward CT-guided, region-specific ventilatory management rather than relying on averaged bedside parameters.

Gao J, Garberi R, Akor EA et al. · Intensive care medicine experimental · (2026) · View on PubMed ↗ · Free PDF ↗

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Generated automatically on July 26, 2026. Covers PubMed articles published July 19, 2026 – July 26, 2026. Summaries are AI-generated; always consult the original publication for clinical or research decisions.