The MRI clear cell likelihood score predicts the likelihood that a renal mass is clear cell renal cell carcinoma (ccRCC). A CT-based algorithm has not yet been established. The purpose of our study was to develop and evaluate a CT-based algorithm for diagnosing ccRCC among small (≤ 4 cm) solid renal masses. This retrospective study included 148 patients (73 men, 75 women; mean age, 58 ± 12 [SD] years) with 148 small (≤ 4 cm) solid (> 25% enhancing tissue) renal masses that underwent renal mass CT (unenhanced, corticomedullary, and nephrographic phases) before resection between January 2016 and December 2019. Two radiologists independently evaluated CT examinations and recorded calcification, mass attenuation in all phases, mass-to-cortex corticomedullary attenuation ratio, and heterogeneity score (score on a 5-point Likert scale, assessed in corticomedullary phase). Features associated with ccRCC were identified by multivariable logistic regression analysis and then used to create a five-tiered CT score for diagnosing ccRCC. The masses comprised 53% (78/148) ccRCC and 47% (70/148) other histologic diagnoses. The mass-to-cortex corticomedullary attenuation ratio was higher for ccRCC than for other diagnoses (reader 1: 0.84 ± 0.68 vs 0.68 ± 0.65, = .02; reader 2: 0.75 ± 0.29 vs 0.59 ± 0.25, = .02). The heterogeneity score was higher for ccRCC than other diagnoses (reader 1: 4.0 ± 1.1 vs 1.5 ± 1.6, < .001; reader 2: 4.4 ± 0.9 vs 3.3 ± 1.5, < .001). Other features showed no difference. A five-tiered diagnostic algorithm including the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score had interobserver agreement of 0.71 (weighted κ) and achieved an AUC for diagnosing ccRCC of 0.75 (95% CI, 0.68-0.82) for reader 1 and 0.72 (95% CI, 0.66-0.82) for reader 2. A CT score of 4 or greater achieved sensitivity, specificity, and PPV of 71% (95% CI, 59-80%), 79% (95% CI, 67-87%), and 79% (95% CI, 67-87%) for reader 1 and 42% (95% CI, 31-54%), 81% (95% CI, 70-90%), and 72% (95% CI, 56-84%) for reader 2. A CT score of 2 or less had NPV of 85% (95% CI, 69-95%) for reader 1 and 88% (95% CI, 69-97%) for reader 2. A five-tiered renal CT algorithm, including the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score, had substantial interobserver agreement, moderate AUC and PPV, and high NPV for diagnosing ccRCC. The CT algorithm, if validated, may represent a useful clinical tool for diagnosing ccRCC.
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http://dx.doi.org/10.2214/AJR.22.27971 | DOI Listing |
AME Case Rep
January 2025
Department of Oncology, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou, China.
Background: Treatment options for patients with high-risk metastatic clear cell renal cell carcinoma (mccRCC) include immune checkpoint inhibitors and tyrosine kinase inhibitors (TKIs), but clinical manifestations and treatment of these patients are rarely reported because patients with cardiac metastases and abrupt circulatory disorders are very rare and there are no precise guidelines to follow. In this study, we analyzed and discussed the clinical characteristics, related characteristics, pathogenesis and treatment strategies of patients with cardiac metastases of kidney cancer, so as to provide reference for the diagnosis and treatment of cardiac metastatic tumors.
Case Description: The patient was diagnosed with renal cell carcinoma and underwent surgical radical resection, no special treatment was performed after surgery.
Oncol Res
January 2025
Department of Urology, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, China.
Background: Clear cell renal carcinoma (ccRCC), the leading histological subtype of RCC, lacks any targeted therapy options. Although some studies have shown that early growth response factor 1 (EGR1) has a significant role in cancer development and progression, its role and underlying mechanisms in ccRCC remain poorly understood.
Methods: The Cancer Genome Atlas (TCGA) database was utilized to examine the expression of EGR1 in ccRCC.
Sci Rep
January 2025
Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Clear cell renal cell carcinoma is a prevalent urological malignancy, imposing substantial burdens on both patients and society. In our study, we used bioinformatics methods to select four putative target genes associated with EMT and prognosis and developed a nomogram model which could accurately predicting 5-year patient survival rates. We further analyzed proteome and single-cell data and selected PLCG2 and TMEM38A for the following experiments.
View Article and Find Full Text PDFObjective: The objective of this research was to devise and authenticate a predictive model that employs CT radiomics and deep learning methodologies for the accurate prediction of synchronous distant metastasis (SDM) in clear cell renal cell carcinoma (ccRCC).
Methods: A total of 143 ccRCC patients were included in the training cohort, and 62 ccRCC patients were included in the validation cohort. The CT images from all patients were normalized, and the tumor regions were manually segmented via ITK-SNAP software.
Anal Bioanal Chem
January 2025
Department of Gastroenterology and Hepatology, Zhongshan Hospital, Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China.
Urinary exosome metabolite analysis has demonstrated notable advantages in uncovering disease status, yet its potential in decoding the intricacies of clear cell renal cell carcinoma (ccRCC) remains untapped. To address this, a core-shell magnetic titanium organic framework was designed to capture urinary exosomes and assist laser desorption/ionization mass spectrometry (LDI MS) to decipher the exosomal metabolic profile of ccRCC, with high sensitivity, throughput, and speed. A total of 492 urinary exosome metabolite fingerprints (UEMFs) from 176 samples were extracted for exploring the differences between ccRCC and healthy individuals.
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