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A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
[Advances in the Growth Risk Assessment and Precision Management of Pulmonary Subsolid Nodules]
Shulei Cui1, Linlin Qi1, Jianwei Wang1
1Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
None:
Pulmonary subsolid nodules (SSNs) exhibit heterogeneous growth patterns. Most SSNs remain stable or grow only slowly during long-term follow-up, whereas a small subset grows rapidly over a relatively short period. Some of these lesions may ultimately progress to invasive adenocarcinoma (IAC). Growth is an important imaging manifestation of evolving biological behavior in SSNs. It also serves as a key determinant of surveillance strategies and the timing of intervention. Accordingly, accurate assessment of growth risk has become a major focus of current research. Starting from the natural history of SSNs and the challenges associated with their clinical surveillance and management, this review systematically examines advances in SSNs growth risk assessment across imaging, radiomics, and deep learning. It also summarizes relevant molecular biological evidence to inform accurate growth risk assessment and the development of individualized management strategies for SSNs. .
