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Open AccessArticle

Integrative Radiogenomics Approach for Risk Assessment of Post-Operative Metastasis in Pathological T1 Renal Cell Carcinoma: A Pilot Retrospective Cohort Study

1
Department of Hospital Medicine, Yonsei University College of Medicine, Seoul 03722, Korea
2
Department of Electronic and Computer Engineering, Sungkyunkwan University, Suwon 16149, Korea
3
Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 16149, Korea
4
Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea
5
Departments of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
6
Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea
7
Departments of Health Sciences and Technology, Samsung Advanced Institute of Health Science and Technology, Sungkyunkwan University, Seoul 06351, Korea
8
Department of Neurosurgery, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul 06531, Korea
9
Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon 16419, Korea
10
Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06531, Korea
11
School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon 16149, Korea
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Cancers 2020, 12(4), 866; https://doi.org/10.3390/cancers12040866
Received: 19 March 2020 / Accepted: 28 March 2020 / Published: 2 April 2020
Despite the increasing incidence of pathological stage T1 renal cell carcinoma (pT1 RCC), postoperative distant metastases develop in many surgically treated patients, causing death in certain cases. Therefore, this study aimed to create a radiomics model using imaging features from multiphase computed tomography (CT) to more accurately predict the postoperative metastasis of pT1 RCC and further investigate the possible link between radiomics parameters and gene expression profiles generated by whole transcriptome sequencing (WTS). Four radiomic features, including the minimum value of a histogram feature from inner regions of interest (ROIs) (INNER_Min_hist), the histogram of the energy feature from outer ROIs (OUTER_Energy_Hist), the maximum probability of gray-level co-occurrence matrix (GLCM) feature from inner ROIs (INNER_MaxProb_GLCM), and the ratio of voxels under 80 Hounsfield units (Hus) in the nephrographic phase of postcontrast CT (Under80HURatio), were detected to predict the postsurgical metastasis of patients with pathological stage T1 RCC, and the clinical outcomes of patients could be successfully stratified based on their radiomic risk scores. Furthermore, we identified heterogenous-trait-associated gene signatures correlated with these four radiomic features, which captured clinically relevant molecular pathways, tumor immune microenvironment, and potential treatment strategies. Our results of accurate surrogates using radiogenomics could lead to additional benefit from adjuvant therapy or postsurgical metastases in pT1 RCC. View Full-Text
Keywords: renal cell carcinoma; metastasis; radiogenomics; computed tomography; gene expression profiling; imaging surrogate marker renal cell carcinoma; metastasis; radiogenomics; computed tomography; gene expression profiling; imaging surrogate marker
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Lee, H.W.; Cho, H.-H.; Joung, J.-G.; Jeon, H.G.; Jeong, B.C.; Jeon, S.S.; Lee, H.M.; Nam, D.-H.; Park, W.-Y.; Kim, C.K.; Seo, S.I.; Park, H. Integrative Radiogenomics Approach for Risk Assessment of Post-Operative Metastasis in Pathological T1 Renal Cell Carcinoma: A Pilot Retrospective Cohort Study. Cancers 2020, 12, 866.

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