Literature DB >> 29987358

Association of qualitative and quantitative imaging features on multiphasic multidetector CT with tumor grade in clear cell renal cell carcinoma.

Heidi Coy1, Jonathan R Young2, Michael L Douek3, Alan Pantuck4, Matthew S Brown3, James Sayre5, Steven S Raman6.   

Abstract

PURPOSE: The purpose of the study was to determine if enhancement features and qualitative imaging features on multiphasic multidetector computed tomography (MDCT) were associated with tumor grade in patients with clear cell renal cell carcinoma (ccRCC).
METHODS: In this retrospective, IRB approved, HIPAA-compliant, institutional review board-approved study with waiver of informed consent, 127 consecutive patients with 89 low grade (LG) and 43 high grade (HG) ccRCCs underwent preoperative four-phase MDCT in unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases. Previously published quantitative (absolute peak lesion enhancement, absolute peak lesion enhancement relative to normal enhancing renal cortex, 3D whole lesion enhancement and the wash-in/wash-out of enhancement within the 3D whole lesion ROI) and qualitative (enhancement pattern; presence of necrosis; pattern of; tumor margin; tumor-parenchymal interface, tumor-parenchymal interaction; intratumoral vascularity; collecting system infiltration; renal vein invasion; and calcification) assessments were obtained for each lesion independently by two fellowship-trained genitourinary radiologists. Comparisons between variables included χ2, ANOVA, and student t test. p values less than 0.05 were considered to be significant. Inter-reader agreement was obtained with the Gwet agreement coefficient (AC1) and standard error (SE) was reported.
RESULTS: No significant differences were observed between the LG and HG ccRCC cohorts with respect to absolute peak lesion enhancement and relative lesion enhancement ratio. There was a significant inverse correlation between low and high grade ccRCC and tumor enhancement the NP (71 HU vs. 54 HU, p < 0.001) and EX (52 HU vs. 39 HU, p < 0.001) phases using the 3D whole lesion ROI method. The percent wash-in of 3D enhancement from the UN to the CM phase was also significantly different between LG and HG ccRCCs (352% vs. 255%, p = 0.003). HG lesions showed significantly more calcification, necrosis, collecting system infiltration and ill-defined tumor margins (p < 0.05). Overall agreement between the two readers had a mean AC1 of 0.8172 (SE 0.0235).
CONCLUSIONS: Quantitatively, high grade ccRCC had significantly lower whole lesion enhancement in the NP and EX phases on MDCT. Qualitatively, high grade ccRCC were significantly more likely to be associated with calcifications, necrosis, collecting system infiltration, and an ill-defined tumor margin.

Entities:  

Keywords:  Clear cell renal cell carcinoma; Fuhrman nuclear grade; Kidney; Neoplasm grading; Renal computed tomography; Tumor heterogenity

Mesh:

Year:  2019        PMID: 29987358     DOI: 10.1007/s00261-018-1688-8

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  9 in total

1.  Prediction models for clear cell renal cell carcinoma ISUP/WHO grade: comparison between CT radiomics and conventional contrast-enhanced CT.

Authors:  Dong Han; Yong Yu; Nan Yu; Shan Dang; Hongpei Wu; Ren Jialiang; Taiping He
Journal:  Br J Radiol       Date:  2020-08-12       Impact factor: 3.039

2.  Quantification of contrast-uptake as imaging biomarker for disease progression of renal cell carcinoma after tumor ablation.

Authors:  Bruno R Tegel; Steffen Huber; Lynn J Savic; MingDe Lin; Bernhard Gebauer; Jeffrey Pollak; Julius Chapiro
Journal:  Acta Radiol       Date:  2020-03-26       Impact factor: 1.990

3.  Multiphase Contrast-Enhanced CT-Based Machine Learning Models to Predict the Fuhrman Nuclear Grade of Clear Cell Renal Cell Carcinoma.

Authors:  Shengsheng Lai; Lei Sun; Jialiang Wu; Ruili Wei; Shiwei Luo; Wenshuang Ding; Xilong Liu; Ruimeng Yang; Xin Zhen
Journal:  Cancer Manag Res       Date:  2021-02-04       Impact factor: 3.989

4.  CT texture analysis: a potential tool for predicting the Fuhrman grade of clear-cell renal carcinoma.

Authors:  Zhan Feng; Qijun Shen; Ying Li; Zhengyu Hu
Journal:  Cancer Imaging       Date:  2019-02-06       Impact factor: 3.909

5.  FORCE dual-energy CT in pathological grading of clear cell renal cell carcinoma.

Authors:  Chunling Zhang; Ning Wang; Xinyou Su; Kun Li; Dexin Yu; Aimei Ouyang
Journal:  Oncol Lett       Date:  2019-10-30       Impact factor: 2.967

6.  Clinicopathological and radiological significance of the collateral vessels of renal cell carcinoma on preoperative computed tomography.

Authors:  Xueling Suo; Junru Chen; Yijun Zhao; Qidun Tang; Xibiao Yang; Yuan Yuan; Ling Nie; Ni Chen; Hao Zeng; Jin Yao
Journal:  Sci Rep       Date:  2021-03-04       Impact factor: 4.379

7.  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

8.  CT-based transformer model for non-invasively predicting the Fuhrman nuclear grade of clear cell renal cell carcinoma.

Authors:  Meiyi Yang; Xiaopeng He; Lifeng Xu; Minghui Liu; Jiali Deng; Xuan Cheng; Yi Wei; Qian Li; Shang Wan; Feng Zhang; Lei Wu; Xiaomin Wang; Bin Song; Ming Liu
Journal:  Front Oncol       Date:  2022-09-28       Impact factor: 5.738

9.  Differentiation of Clear Cell Renal Cell Carcinoma from other Renal Cell Carcinoma Subtypes and Benign Oncocytoma Using Quantitative MDCT Enhancement Parameters.

Authors:  Claudia-Gabriela Moldovanu; Bianca Petresc; Andrei Lebovici; Attila Tamas-Szora; Mihai Suciu; Nicolae Crisan; Paul Medan; Mircea Marian Buruian
Journal:  Medicina (Kaunas)       Date:  2020-10-28       Impact factor: 2.430

  9 in total

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