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Radiomics-based T-staging of Hollow Organ Cancers

Overview
Journal Front Oncol
Specialty Oncology
Date 2023 Sep 18
PMID 37719013
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Abstract

Cancer growing in hollow organs has become a serious threat to human health. The accurate T-staging of hollow organ cancers is a major concern in the clinic. With the rapid development of medical imaging technologies, radiomics has become a reliable tool of T-staging. Due to similar growth characteristics of hollow organ cancers, radiomics studies of these cancers can be used as a common reference. In radiomics, feature-based and deep learning-based methods are two critical research focuses. Therefore, we review feature-based and deep learning-based T-staging methods in this paper. In conclusion, existing radiomics studies may underestimate the hollow organ wall during segmentation and the depth of invasion in staging. It is expected that this survey could provide promising directions for following research in this realm.

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References
1.
Benson A, Venook A, Al-Hawary M, Cederquist L, Chen Y, Ciombor K . Rectal Cancer, Version 2.2018, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw. 2018; 16(7):874-901. PMC: 10203817. DOI: 10.6004/jnccn.2018.0061. View

2.
Gillies R, Kinahan P, Hricak H . Radiomics: Images Are More than Pictures, They Are Data. Radiology. 2015; 278(2):563-77. PMC: 4734157. DOI: 10.1148/radiol.2015151169. View

3.
Wang Y, Liu W, Yu Y, Liu J, Jiang L, Xue H . Prediction of the Depth of Tumor Invasion in Gastric Cancer: Potential Role of CT Radiomics. Acad Radiol. 2019; 27(8):1077-1084. DOI: 10.1016/j.acra.2019.10.020. View

4.
Gao Y, Zhang Z, Li S, Guo Y, Wu Q, Liu S . Deep neural network-assisted computed tomography diagnosis of metastatic lymph nodes from gastric cancer. Chin Med J (Engl). 2019; 132(23):2804-2811. PMC: 6940067. DOI: 10.1097/CM9.0000000000000532. View

5.
Song Z, Wu Y, Yang J, Yang D, Fang X . Progress in the treatment of advanced gastric cancer. Tumour Biol. 2017; 39(7):1010428317714626. DOI: 10.1177/1010428317714626. View