Literature DB >> 29023154

Diagnostic Performance of DWI for Differentiating High- From Low-Grade Clear Cell Renal Cell Carcinoma: A Systematic Review and Meta-Analysis.

Sungmin Woo, Chong Hyun Suh1,2, Sang Youn Kim, Jeong Yeon Cho3,4, Seung Hyup Kim3,4.   

Abstract

OBJECTIVE: The purpose of our study was to review the diagnostic performance of DWI for differentiating high- from low-grade clear cell renal cell carcinoma (RCC).
MATERIALS AND METHODS: MEDLINE, EMBASE, and Cochrane library databases were searched up to March 15, 2017. We included diagnostic accuracy studies that used DWI for differentiating high- from low-grade clear cell RCC compared with histopathologic results of Fuhrman grade based on nephrectomy or biopsy specimens in original research articles. Two independent reviewers assessed methodologic quality using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Sensitivity and specificity of the included studies were pooled and graphically presented using a hierarchic summary ROC plot. For heterogeneity exploration, we assessed the presence of a threshold effect and performed meta-regression analyses.
RESULTS: Eight retrospective studies (394 patients with 397 clear cell RCCs) were included. Pooled sensitivity was 0.78 (95% CI, 0.68-0.85) with a specificity of 0.86 (95% CI, 0.70-0.94). A considerable threshold effect was observed with a correlation coefficient of 0.811 (95% CI, 0.248-0.964) between the sensitivity and false-positive rate. At meta-regression analysis, apparent diffusion coefficient (× 10 mm2/s) cutoff value (< 1.57 vs ≥ 1.57; p = 0.03) and location of ROI (solid portion vs whole tumor; p = 0.04) were significant factors affecting heterogeneity. Other factors with regard to patients and tumors, study, and MRI characteristics were not significant (p = 0.17-0.91).
CONCLUSION: DWI shows moderate diagnostic performance for differentiating high-from low-grade clear cell RCC. Substantial heterogeneity was observed because of a threshold effect. Further prospective studies may be needed; all included studies were retrospective.

Entities:  

Keywords:  DWI; Fuhrman grade; MRI; clear cell renal cell carcinoma; meta-analysis

Mesh:

Year:  2017        PMID: 29023154     DOI: 10.2214/AJR.17.18283

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  8 in total

1.  Association between nuclear grade of renal cell carcinoma and the aorta-lesion-attenuation-difference.

Authors:  Joseph R Grajo; Nikhil V Batra; Shahab Bozorgmehri; Laura L Magnelli; Padraic O'Malley; Russell Terry; Li-Ming Su; Paul L Crispen
Journal:  Abdom Radiol (NY)       Date:  2021-08-31

2.  Comparison of Various Parameters of DWI in Distinguishing Solitary Pulmonary Nodules.

Authors:  Han-Xiong Guan; Yue-Ying Pan; Yu-Jin Wang; Da-Zong Tang; Shu-Chang Zhou; Li-Ming Xia
Journal:  Curr Med Sci       Date:  2018-10-20

3.  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

4.  Clear Cell Renal Cell Carcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis for Prediction of Fuhrman Nuclear Grade.

Authors:  Ceyda Turan Bektas; Burak Kocak; Aytul Hande Yardimci; Mehmet Hamza Turkcanoglu; Ugur Yucetas; Sevim Baykal Koca; Cagri Erdim; Ozgur Kilickesmez
Journal:  Eur Radiol       Date:  2018-08-30       Impact factor: 5.315

5.  Renal cell carcinoma: preoperative evaluate the grade of histological malignancy using volumetric histogram analysis derived from magnetic resonance diffusion kurtosis imaging.

Authors:  Ke Wang; Jingyun Cheng; Yan Wang; Guangyao Wu
Journal:  Quant Imaging Med Surg       Date:  2019-04

6.  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

7.  Application of diffusion kurtosis tensor MR imaging in characterization of renal cell carcinomas with different pathological types and grades.

Authors:  Jie Zhu; Xiaojie Luo; Jiayin Gao; Saying Li; Chunmei Li; Min Chen
Journal:  Cancer Imaging       Date:  2021-03-16       Impact factor: 3.909

8.  Diagnostic Performance of Diffusion-Weighted Imaging for Differentiating Malignant From Benign Intraductal Papillary Mucinous Neoplasms of the Pancreas: A Systematic Review and Meta-Analysis.

Authors:  Fan Xu; Yingying Liang; Wei Guo; Zhiping Liang; Liqi Li; Yuchao Xiong; Guoxi Ye; Xuwen Zeng
Journal:  Front Oncol       Date:  2021-07-05       Impact factor: 6.244

  8 in total

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