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Annals of Surgical Oncology
Published in: Annals of Surgical Oncology 13/2022

13-09-2022 | NSCLC | ASO Author Reflections

ASO Author Reflections: The Clinical Use of Radiomics with Artificial Intelligence in Patients with Early-Stage Lung Cancer

Author: Yoshihisa Shimada, MD, PhD

Published in: Annals of Surgical Oncology | Issue 13/2022

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Excerpt

Nearly 30% of patients with stage I non-small cell lung cancer (NSCLC) experienced disease recurrence even though complete resection is achieved.1,2 Most recurrences occur within the first 2 years, and the 2-year postrecurrence survival was only 51% in patients with stage I NSCLC.3,4 Radiomics, with reference to genomics, is a quantitative approach in which a large amount of predefined high-throughput computational data is extracted from medical imaging and has great potential to improve diagnosis and patient stratification in lung cancer. Currently, there is no study to identify factors associated with early recurrence (< 2 years after surgery) in early-stage lung cancer using a radiomics approach. …
Literature
1.
Cho S, Song IH, Yang HC, et al. Predictive factors for node metastasis in patients with clinical stage I non-small cell lung cancer. Ann Thorac Surg. 2013;96:239–45.CrossRefPubMed
2.
Kaseda K, Asakura K, Kazama A, et al. Risk factors for predicting occult lymph node metastasis in patients with clinical stage i non-small cell lung cancer staged by integrated fluorodeoxyglucose positron emission tomography/computed tomography. World J Surg. 2016;40:2976–83.CrossRefPubMed
3.
Varlotto JM, Medford-Davis LN, Recht A, et al. Identification of stage I non-small cell lung cancer patients at high risk for local recurrence following sublobar resection. Chest. 2013;143:1365–77.CrossRefPubMed
4.
Shimada Y, Saji H, Yoshida K, et al. Prognostic factors and the significance of treatment after recurrence in completely resected stage I non-small cell lung cancer. Chest. 2013;143:1626–34.CrossRefPubMed
5.
Metadata
Title
ASO Author Reflections: The Clinical Use of Radiomics with Artificial Intelligence in Patients with Early-Stage Lung Cancer
Author
Yoshihisa Shimada, MD, PhD
Publication date
13-09-2022
Publisher
Springer International Publishing
Published in
Annals of Surgical Oncology / Issue 13/2022
Print ISSN: 1068-9265
Electronic ISSN: 1534-4681
DOI
https://doi.org/10.1245/s10434-022-12518-9

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