Photon-counting detector computed tomography in thoracic oncology: revolutionizing tumor imaging through precision and detail.
Authors
Affiliations (16)
Affiliations (16)
- The University of Osaka Graduate School of Medicine, Department of Diagnostic and Interventional Radiology, Osaka, Japan.
- Nagoya University Graduate School of Medicine, Department of Innovative BioMedical Visualization, Nagoya, Japan.
- Osaka Metropolitan University Graduate School of Medicine, Department of Artificial Intelligence, Osaka, Japan.
- University of Tsukuba Institute of Medicine, Department of Radiology, Tsukuba, Japan.
- The University of Tokyo Graduate School of Medicine, Department of Radiology, Tokyo, Japan.
- Kagoshima University Graduate School of Medical and Dental Sciences, Department of Radiology, Kagoshima, Japan.
- Hokkaido University Faculty of Medicine, Global Center for Biomedical Science and Engineering, Division of Radiation Oncology, Sapporo, Japan.
- National Cancer Center Hospital, Department of Diagnostic Radiology, Tokyo, Japan.
- University of Occupational and Environmental Health, Department of Radiology, Kitakyushu, Japan.
- Kyoto University Hospital, Preemptive Medicine and Lifestyle-Related Disease Research Center, Kyoto, Japan.
- Nagoya University Graduate School of Medicine, Department of Fundamental Development for Advanced Low Invasive Diagnostic Imaging, Nagoya, Japan.
- Nagoya University Graduate School of Medicine, Department of Radiology, Nagoya, Japan.
- Kyoto University Graduate School of Medicine, Department of Diagnostic Imaging and Nuclear Medicine, Kyoto, Japan.
- Kobe University Graduate School of Medicine, Department of Radiology, Kobe, Japan.
- Kumamoto University Faculty of Life Sciences, Department of Diagnostic Radiology, Kumamoto, Japan.
- Hokkaido University Graduate School of Medicine, Department of Diagnostic Imaging, Sapporo, Japan.
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".