Photon-counting detector computed tomography in thoracic oncology: revolutionizing tumor imaging through precision and detail

Photon-counting detector computed tomography (PCD-CT) is an emerging imaging technology that promises to overcome the limitations of conventional energy-integrating detector (EID)-CT, particularly in thoracic oncology. This narrative review summarizes technical advances and clinical applications of PCD-CT in the thorax with emphasis on spatial resolution, dose-image-quality balance, and intrinsic spectral imaging, and it outlines practical implications relevant to thoracic oncology. A literature review of PubMed through May 31, 2025, was conducted using combinations of "photon counting," "computed tomography," "thoracic oncology," and "artificial intelligence." We screened the retrieved records and included studies with direct relevance to lung and mediastinal tumors, image quality, radiation dose, spectral/iodine imaging, or artificial intelligence-based reconstruction; case reports, editorials, and animal-only or purely methodological reports were excluded. PCD-CT demonstrated superior spatial resolution compared with EID-CT, enabling clearer visualization of fine pulmonary structures, such as bronchioles and subsolid nodules; slice thicknesses of approximately 0.4 mm and <i>ex vivo</i> resolvable structures approaching 0.11 mm have been reported. Across intraindividual clinical comparisons, radiation-dose reductions of 16%-43% have been achieved while maintaining or improving diagnostic image quality. Intrinsic spectral imaging enables accurate iodine mapping and low-keV virtual monoenergetic images and has shown quantitative advantages versus dual-energy CT in phantoms and early clinical work. Artificial intelligence-based deep-learning reconstruction and super-resolution can complement detector capabilities to reduce noise and stabilize fine-structure depiction without increasing dose. Potential reductions in contrast volume are biologically plausible given improved low-keV contrast-to-noise ratio, although clinical dose-finding data remain limited, and routine K-edge imaging has not yet translated to clinical thoracic practice. In conclusion, PCD-CT provides higher spatial and spectral fidelity at lower or comparable doses, supporting earlier and more precise tumor detection and characterization; future work should prioritize outcome-oriented trials, protocol harmonization, and implementation studies aligned with "Green Radiology".

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Journal
Diagnostic and Interventional Radiology
Published
2025-09-24
DOI
https://doi.org/10.4274/dir.2025.253550
Primary Topic
Advanced X-ray and CT Imaging
Type
article
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article

Photon-counting detector computed tomography in thoracic oncology: revolutionizing tumor imaging through precision and detail

Satoru Ide, Kentaro Nishioka, Ryo Kurokawa, Seitaro Oda et al.
Diagnostic and Interventional Radiology
Advanced X-ray and CT Imaging
article

Photon-counting detector computed tomography in thoracic oncology: revolutionizing tumor imaging through precision and detail

Satoru Ide, Kentaro Nishioka, Ryo Kurokawa, Seitaro Oda, Midori Ueno, Tadashi Watabe, Shinji Naganawa, Rintaro Ito, Maya Honda, Tsukasa Saida, Keitaro Sofue, Koji Takumi, Masahiro Yanagawa, Daiju Ueda, Mami Iima, Shunsuke Sugawara, Akihiko Sakata, Mariko Kawamura, Kenji Hirata
article en

Abstract

Photon-counting detector computed tomography (PCD-CT) is an emerging imaging technology that promises to overcome the limitations of conventional energy-integrating detector (EID)-CT, particularly in thoracic oncology. This narrative review summarizes technical advances and clinical applications of PCD-CT in the thorax with emphasis on spatial resolution, dose-image-quality balance, and intrinsic spectral imaging, and it outlines practical implications relevant to thoracic oncology. A literature review of PubMed through May 31, 2025, was conducted using combinations of "photon counting," "computed tomography," "thoracic oncology," and "artificial intelligence." We screened the retrieved records and included studies with direct relevance to lung and mediastinal tumors, image quality, radiation dose, spectral/iodine imaging, or artificial intelligence-based reconstruction; case reports, editorials, and animal-only or purely methodological reports were excluded. PCD-CT demonstrated superior spatial resolution compared with EID-CT, enabling clearer visualization of fine pulmonary structures, such as bronchioles and subsolid nodules; slice thicknesses of approximately 0.4 mm and <i>ex vivo</i> resolvable structures approaching 0.11 mm have been reported. Across intraindividual clinical comparisons, radiation-dose reductions of 16%-43% have been achieved while maintaining or improving diagnostic image quality. Intrinsic spectral imaging enables accurate iodine mapping and low-keV virtual monoenergetic images and has shown quantitative advantages versus dual-energy CT in phantoms and early clinical work. Artificial intelligence-based deep-learning reconstruction and super-resolution can complement detector capabilities to reduce noise and stabilize fine-structure depiction without increasing dose. Potential reductions in contrast volume are biologically plausible given improved low-keV contrast-to-noise ratio, although clinical dose-finding data remain limited, and routine K-edge imaging has not yet translated to clinical thoracic practice. In conclusion, PCD-CT provides higher spatial and spectral fidelity at lower or comparable doses, supporting earlier and more precise tumor detection and characterization; future work should prioritize outcome-oriented trials, protocol harmonization, and implementation studies aligned with "Green Radiology".

Diagnostic and Interventional Radiology
Hokkaido University of Science (JP), Kagoshima University (JP), University of Tsukuba (JP), University of Occupational and Environmental Health Japan (JP), Hokkaido University (JP), Kyoto University (JP), National Cancer Centre Japan (JP), National Cancer Center (US), University of Tokyo Hospital (JP), National Cancer Center Hospital East (JP), Kyoto University Hospital (JP), Tokyo National Hospital (JP), Nagoya University (JP), Kobe University (JP), Tokyo Metropolitan University (JP), The University of Tokyo (JP), Kumamoto University (JP), The University of Osaka (JP)
Openalex Percentile: Top 75%
Advanced X-ray and CT Imaging
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