Early-Stage Lung Cancer Diagnostics
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 60
Special Issue Editors
2. Department of Radiology, Sichuan Cancer Hospital & Institute, Chengdu, China
Interests: early-stage lung cancer diagnosis; lung cancer screening; low-dose CT; oncologic imaging; radiomics
Special Issue Information
Dear Colleagues,
Lung cancer remains the leading cause of cancer-related mortality worldwide, and its curability is fundamentally determined by the earliest possible detection and by the precision with which biological aggressiveness can be estimated before treatment. Over the last decade, the integration of advanced tomographic techniques, high-dimensional image analytics, and systems-level biology has transformed radiology from a purely morphologic discipline into a quantitative bioscience that non-invasively interrogates tumor phenotype, microenvironment, and evolutionary trajectories. This paradigm shift has generated a rapidly expanding repertoire of imaging biomarkers that can now rival, complement, or even replace traditional tissue-based metrics for early detection, risk stratification, precision diagnosis, and prognosis prediction of lung cancer.
This Special Issue invites original research articles and evidence-based reviews that accelerate the clinical translation of quantitative imaging biomarkers across the entire spectrum of early-stage lung cancer care. We especially encourage submissions derived from low-dose CT screening. Papers exploring the multi-parametric signatures derived from dual-energy CT, photon-counting CT, and hybrid PET/CT are also welcome. Contributions that leverage artificial intelligence, deep learning, radiomics, and habitat imaging to decode histopathological subtypes, molecular and genetic phenotypes, spatial heterogeneity, and occult recurrent and metastatic potential are of particular interest.
We look forward to receiving your contributions.
Dr. Jieke Liu
Dr. Zhigang Chu
Guest Editors
Manuscript Submission Information
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Keywords
- early-stage lung cancer
- low-dose CT screening
- artificial intelligence
- deep learning
- radiomics
- habitat imaging
- early detection
- precision diagnosis
- risk stratification
- prognosis prediction
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