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Potential of Higher Resolution Synchrotron Radiation Tomography Using Crystal Analyzer-Based Imaging Techniques for Differential Diagnosis of Human Lung Cancers
by
, ,
Eunjue Yi
1,†
,
Naoki Sunaguchi
2,†,
Jeong Hyeon Lee
3,
Miyoung Woo
1,
Youngjin Kang
3,
Seung-Jun Seo
4,
Daisuke Shimao
5 and
Sungho Lee
1,* 1
Department of Thoracic and Cardiovascular Surgery, Korea University Anam Hospital, Seoul 02841, Republic of Korea
2
Photon Factory, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801, Japan
3
Department of Pathology, Korea University Anam Hospital, Seoul 02841, Republic of Korea
4
Department of Experimental Animal Facility, Daegu Catholic University Medical Center, Daegu 42472, Republic of Korea
5
Department of Radiological Sciences, School of Health Sciences, International University of Health and Welfare, Otawara, 324-8501, Japan
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Cancers 2026, 18(1), 82; https://doi.org/10.3390/cancers18010082 (registering DOI)
Submission received: 21 November 2025
/
Revised: 21 December 2025
/
Accepted: 22 December 2025
/
Published: 26 December 2025
(This article belongs to the Section Cancer Causes, Screening and Diagnosis)
Simple Summary
The subtle deterioration in alveolar structures that occurs in the course of lung cancer development is often hard to detect using conventional imaging methods. We explored the application of X-ray methods using synchrotron radiation to reveal subtype-specific features with high clarity, including invasive fronts, necrotic foci, fibrotic bands, and deformation of alveolar microstructures, enabling non-destructive three-dimensional virtual histology. The resulting detail and contrast are comparable to those achieved with light microscopy, and the specimen is kept intact for standard evaluation. The purpose of this study is to investigate a rapid, non-destructive imaging method that complements pathology, helps clinicians distinguish between lung cancer subtypes, and improves confidence in early diagnosis. If clinically adopted, it will improve early diagnosis, guide treatment planning, and facilitate new research on how tumors spread along air spaces.
Abstract
Background: Conventional absorption-based computed tomography has a limited ability to resolve lung microarchitectures that are critical for histological subtype discrimination. This study evaluated the potential of X-ray Dark-Field Imaging Computed Tomography (XDFI CT) using synchrotron radiation for non-destructive, three-dimensional visualization of human lung cancer microstructures. Methods: Surgically resected human lung cancer specimens (n = 4) were examined, including acinar-predominant adenocarcinoma (n = 1), adenocarcinoma after concurrent chemoradiation therapy (n = 1), keratinizing squamous cell carcinoma (n = 1), and metastatic hepatocellular carcinoma in the lung (n = 1). Image acquisition was performed at beamline BL-14B of the Photon Factory (Tsukuba, Japan), using a monochromatic 19.8 keV synchrotron X-ray beam and a crystal analyzer-based refraction-contrast optical system. Imaging findings were qualitatively correlated with corresponding histopathological sections. Results: Synchrotron radiation XDFI CT enabled clear visualization of normal distal lung microanatomy, including alveolar walls and associated vascular structures, which served as internal references adjacent to tumor regions. Distinct microstructural features—such as invasive growth patterns, fibrotic or keratinized stroma, necrosis, and treatment-related remodeling—were identifiable and varied according to histological subtype. Tumor–normal tissue transitional zones were consistently delineated in all specimens. Conclusions: Synchrotron radiation XDFI CT provides high-resolution, non-destructive volumetric imaging of lung cancer tissues and reveals subtype-associated microarchitectural features. This technique may complement conventional histopathology by enabling three-dimensional virtual histologic assessment of lung cancer specimens.
