Initial Evaluation of Computer-Assisted Radiologic Assessment for Renal Mass Edge Detection as an Indication of Tumor Roughness to Predict Renal Cancer Subtypes

Autor: Rahul Rajendran, Kevan Iffrig, Deepak K Pruthi, Allison Wheeler, Brian Neuman, Dharam Kaushik, Ahmed M Mansour, Karen Panetta, Sos Agaian, Michael A. Liss
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Advances in Urology, Vol 2019 (2019)
Druh dokumentu: article
ISSN: 1687-6369
1687-6377
DOI: 10.1155/2019/3590623
Popis: Objective. To develop software to assess the potential aggressiveness of an incidentally detected renal mass using images. Methods. Thirty randomly selected patients who underwent nephrectomy for renal cell carcinoma (RCC) had their images independently reviewed by engineers. Tumor “Roughness” was based on image algorithm of tumor topographic features visualized on computed tomography (CT) scans. Univariant and multivariant statistical analyses are utilized for analysis. Results. We investigated 30 subjects that underwent partial or radical nephrectomy. After excluding poor image-rendered images, 27 patients remained (benign cyst = 1, oncocytoma = 2, clear cell RCC = 15, papillary RCC = 7, and chromophobe RCC = 2). The mean roughness score for each mass is 1.18, 1.16, 1.27, 1.52, and 1.56 units, respectively (p
Databáze: Directory of Open Access Journals
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