PreprintArticleVersion 2This version is not peer-reviewed
Radiogenomics Pilot Study: Association Between Radiomics and SNP-Based Microarray Copy Number Variation in Diagnosing Renal Oncocytoma and Chromophobe Renal Cell Carcinoma
Version 1
: Received: 21 October 2024 / Approved: 21 October 2024 / Online: 22 October 2024 (09:15:44 CEST)
Version 2
: Received: 24 October 2024 / Approved: 24 October 2024 / Online: 25 October 2024 (10:24:10 CEST)
How to cite:
Alhussaini, A. J.; Veluchamy, A.; Kernohan, N.; Palmer, C. N. A.; Steele, J. D.; Nabi, G. Radiogenomics Pilot Study: Association Between Radiomics and SNP-Based Microarray Copy Number Variation in Diagnosing Renal Oncocytoma and Chromophobe Renal Cell Carcinoma. Preprints2024, 2024101596. https://doi.org/10.20944/preprints202410.1596.v2
Alhussaini, A. J.; Veluchamy, A.; Kernohan, N.; Palmer, C. N. A.; Steele, J. D.; Nabi, G. Radiogenomics Pilot Study: Association Between Radiomics and SNP-Based Microarray Copy Number Variation in Diagnosing Renal Oncocytoma and Chromophobe Renal Cell Carcinoma. Preprints 2024, 2024101596. https://doi.org/10.20944/preprints202410.1596.v2
Alhussaini, A. J.; Veluchamy, A.; Kernohan, N.; Palmer, C. N. A.; Steele, J. D.; Nabi, G. Radiogenomics Pilot Study: Association Between Radiomics and SNP-Based Microarray Copy Number Variation in Diagnosing Renal Oncocytoma and Chromophobe Renal Cell Carcinoma. Preprints2024, 2024101596. https://doi.org/10.20944/preprints202410.1596.v2
APA Style
Alhussaini, A. J., Veluchamy, A., Kernohan, N., Palmer, C. N. A., Steele, J. D., & Nabi, G. (2024). Radiogenomics Pilot Study: Association Between Radiomics and SNP-Based Microarray Copy Number Variation in Diagnosing Renal Oncocytoma and Chromophobe Renal Cell Carcinoma. Preprints. https://doi.org/10.20944/preprints202410.1596.v2
Chicago/Turabian Style
Alhussaini, A. J., J. Douglas Steele and Ghulam Nabi. 2024 "Radiogenomics Pilot Study: Association Between Radiomics and SNP-Based Microarray Copy Number Variation in Diagnosing Renal Oncocytoma and Chromophobe Renal Cell Carcinoma" Preprints. https://doi.org/10.20944/preprints202410.1596.v2
Abstract
Background: RO and ChRCC are kidney tumours with overlapping characteristics, making differentiation between them challenging. Objectives: The objective of this research is to create a radiogenomics map by correlating radiomic features to molecular phenotypes in ChRCC and RO, using resection as the gold standard. Methods: Fourteen patients (6 RO and 8 ChRCC) were included in the study. A total of 1,875 radiomic features were extracted from CT scans, alongside 632 cytobands containing 16,303 genes from the genomic data. Results: Feature selection algorithms applied to the radiomic features resulted in 13 key features. From the genomic data, 24 cytobands highly correlated with histology were selected and cross-correlated with the radiomic features. The analysis identified four radiomic features that were strongly associated with seven genomic features. Conclusion: These findings demonstrate the potential of integrating radiomic and genomic data to enhance the differential diagnosis of RO and ChRCC, paving the way for more precise and non-invasive diagnostic tools in clinical practice.
Medicine and Pharmacology, Oncology and Oncogenics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.