Literature DB >> 31041495

Can MRI be used to diagnose histologic grade in T1a (< 4 cm) clear cell renal cell carcinomas?

Kevin Moran1, Jorge Abreu-Gomez2, Satheesh Krishna3, Trevor A Flood2, Daniel Walker1, Matthew D F McInnes1, Nicola Schieda4,5.   

Abstract

OBJECTIVE: To assess whether MRI can differentiate low-grade from high-grade T1a cc-RCC.
MATERIALS AND METHODS: With IRB approval, 49 consecutive solid < 4 cm cc-RCC (low grade [Grade 1 or 2] N = 38, high grade [Grade 3] N = 11) with pre-operative MRI before nephrectomy were identified between 2013 and 2018. Tumor size, apparent diffusion coefficient (ADC) histogram analysis, enhancement wash-in and wash-out rates, and chemical shift signal intensity index (SI index) were assessed by a blinded radiologist. Subjectively, two blinded Radiologists also assessed for (1) microscopic fat, (2) homogeneity (5-point Likert scale), and (3) ADC signal (relative to renal cortex); discrepancies were resolved by consensus. Outcomes were studied using Chi square, multivariate analysis, logistic regression modeling, and ROC. Inter-observer agreement was assessed using Cohen's kappa.
RESULTS: Tumor size was 24 ± 7 (13-39) mm with no association to grade (p = 0.45). Among quantitative features studied, corticomedullary phase wash-in index (p = 0.015), SI index (p = 0.137), and tenth-centile ADC (p = 0.049) were higher in low-grade tumors. 36.8% (14/38) low-grade tumors versus zero high-grade tumors demonstrated microscopic fat (p = 0.015; Kappa = 0.67). Microscopic fat was specific for low-grade disease (100.0% [71.5-100.0]) with low sensitivity (36.8% [21.8-54.6]). Other subjective features did not differ between groups (p > 0.05). A logistic regression model combining microscopic fat + wash-in index + tenth-centile-ADC yielded area under ROC curve 0.98 (Confidence Intervals 0.94-1.0) with sensitivity/specificity 87.5%/100%.
CONCLUSION: The combination of microscopic fat, higher corticomedullary phase wash-in and higher tenth-centile ADC is highly accurate for diagnosis of low-grade disease among T1a clear cell RCC.

Entities:  

Keywords:  Clear cell; Fuhrman Nuclear Grade; Grade; Magnetic Resonance Imaging; Renal cell carcinoma

Year:  2019        PMID: 31041495     DOI: 10.1007/s00261-019-02018-y

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  4 in total

1.  Diagnostic test accuracy of ADC values for identification of clear cell renal cell carcinoma: systematic review and meta-analysis.

Authors:  Mickael Tordjman; Rahul Mali; Guillaume Madelin; Vinay Prabhu; Stella K Kang
Journal:  Eur Radiol       Date:  2020-03-06       Impact factor: 5.315

2.  Identification of sarcomatoid differentiation in renal cell carcinoma by machine learning on multiparametric MRI.

Authors:  Asim Mazin; Samuel H Hawkins; Olya Stringfield; Jasreman Dhillon; Brandon J Manley; Daniel K Jeong; Natarajan Raghunand
Journal:  Sci Rep       Date:  2021-02-15       Impact factor: 4.379

3.  A CT-Based Radiomics Nomogram Integrated With Clinic-Radiological Features for Preoperatively Predicting WHO/ISUP Grade of Clear Cell Renal Cell Carcinoma.

Authors:  Yingjie Xv; Fajin Lv; Haoming Guo; Zhaojun Liu; Di Luo; Jing Liu; Xin Gou; Weiyang He; Mingzhao Xiao; Yineng Zheng
Journal:  Front Oncol       Date:  2021-12-03       Impact factor: 6.244

4.  A CT-Based Radiomics Approach for the Differential Diagnosis of Sarcomatoid and Clear Cell Renal Cell Carcinoma.

Authors:  Xiaoli Meng; Jun Shu; Yuwei Xia; Ruwu Yang
Journal:  Biomed Res Int       Date:  2020-07-24       Impact factor: 3.411

  4 in total

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