Literature DB >> 26304585

CT prediction of the Fuhrman grade of clear cell renal cell carcinoma (RCC): towards the development of computer-assisted diagnostic method.

Hannu Huhdanpaa1, Darryl Hwang2, Steven Cen3, Brian Quinn4, Megha Nayyar5, Xuejun Zhang6, Frank Chen7, Bhushan Desai8, Gangning Liang9, Inderbir Gill10, Vinay Duddalwar11.   

Abstract

PURPOSE: There are distinct quantifiable features characterizing renal cell carcinomas on contrast-enhanced CT examinations, such as peak tumor enhancement, tumor heterogeneity, and percent contrast washout. While qualitative visual impressions often suffice for diagnosis, quantitative metrics if developed and validated can add to the information available from standard of care diagnostic imaging. The purpose of this study is to assess the use of quantitative enhancement metrics in predicting the Fuhrman grade of clear cell RCC.
MATERIALS AND METHODS: 65 multiphase CT examinations with clear cell RCCs were utilized, 44 tumors with Fuhrman grades 1 or 2 and 21 tumors with grades 3 or 4. After tumor segmentation, the following data were extracted: histogram analysis of voxel-based whole lesion attenuation in each phase, enhancement and washout using mean, median, skewness, kurtosis, standard deviation, and interquartile range.
RESULTS: Statistically significant difference was observed in 4 measured parameters between grades 1-2 and grades 3-4: interquartile range of nephrographic attenuation values, standard deviation of absolute enhancement, as well as interquartile range and standard deviation of residual nephrographic enhancement. Interquartile range of nephrographic attenuation values was 292.86 HU for grades 1-2 and 241.19 HU for grades 3-4 (p value 0.02). Standard deviation of absolute enhancement was 41.26 HU for grades 1-2 and 34.66 HU for grades 3-4 (p value 0.03). Interquartile range was 297.12 HU for residual nephrographic enhancement for grades 1-2 and 235.57 HU for grades 3-4 (p value 0.02), and standard deviation of the same was 42.45 HU for grades 1-2 and 37.11 for grades 3-4 (p value 0.04).
CONCLUSION: Our results indicate that absolute enhancement is more heterogeneous for lower grade tumors and that attenuation and residual enhancement in nephrographic phase is more heterogeneous for lower grade tumors. This represents an important step in devising a predictive non-invasive model to predict the nucleolar grade.

Entities:  

Keywords:  Computed tomography (CT); Computer-assisted diagnosis; Quantitative imaging; Renal cell carcinoma

Mesh:

Substances:

Year:  2015        PMID: 26304585      PMCID: PMC9022673          DOI: 10.1007/s00261-015-0531-8

Source DB:  PubMed          Journal:  Abdom Imaging        ISSN: 0942-8925


  29 in total

Review 1.  Clinical practice. Small renal mass.

Authors:  Inderbir S Gill; Monish Aron; Debra A Gervais; Michael A S Jewett
Journal:  N Engl J Med       Date:  2010-02-18       Impact factor: 91.245

2.  Differentiation of renal clear cell carcinoma and renal papillary carcinoma using quantitative CT enhancement parameters.

Authors:  Andrea J Ruppert-Kohlmayr; Martin Uggowitzer; Thomas Meissnitzer; Georg Ruppert
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3.  International Society of Urological Pathology (ISUP) consensus conference on renal neoplasia: rationale and organization.

Authors:  Brett Delahunt; Lars Egevad; Rodolfo Montironi; John R Srigley
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4.  Intraobserver and interobserver variability of Fuhrman and modified Fuhrman grading systems for conventional renal cell carcinoma.

Authors:  Sibel Bektas; Burak Bahadir; Nilufer Onak Kandemir; Figen Barut; Aylin Ege Gul; Sukru Oguz Ozdamar
Journal:  Kaohsiung J Med Sci       Date:  2009-11       Impact factor: 2.744

5.  Differentiation of subtypes of renal cell carcinoma on helical CT scans.

Authors:  Jeong Kon Kim; Tae Kyoung Kim; Han Jong Ahn; Chung Soo Kim; Kyu-Rae Kim; Kyoung-Sik Cho
Journal:  AJR Am J Roentgenol       Date:  2002-06       Impact factor: 3.959

6.  Increasing incidence of all stages of kidney cancer in the last 2 decades in the United States: an analysis of surveillance, epidemiology and end results program data.

Authors:  Lynette M Hock; James Lynch; K C Balaji
Journal:  J Urol       Date:  2002-01       Impact factor: 7.450

Review 7.  Epidemiology of renal cell cancer.

Authors:  Eunyoung Cho; Hans-Olov Adami; Per Lindblad
Journal:  Hematol Oncol Clin North Am       Date:  2011-08       Impact factor: 3.722

8.  Histologic coagulative tumor necrosis as a prognostic indicator of renal cell carcinoma aggressiveness.

Authors:  Shomik Sengupta; Christine M Lohse; Bradley C Leibovich; Igor Frank; R Houston Thompson; W Scott Webster; Horst Zincke; Michael L Blute; John C Cheville; Eugene D Kwon
Journal:  Cancer       Date:  2005-08-01       Impact factor: 6.860

9.  A novel grading system for clear cell renal cell carcinoma incorporating tumor necrosis.

Authors:  Brett Delahunt; Jesse K McKenney; Christine M Lohse; Bradley C Leibovich; Robert Houston Thompson; Stephen A Boorjian; John C Cheville
Journal:  Am J Surg Pathol       Date:  2013-03       Impact factor: 6.394

10.  Contemporary incidence and mortality rates of kidney cancer in the United States.

Authors:  Giorgio Gandaglia; Praful Ravi; Firas Abdollah; Abd-El-Rahman M Abd-El-Barr; Andreas Becker; Ioana Popa; Alberto Briganti; Pierre I Karakiewicz; Quoc-Dien Trinh; Michael A Jewett; Maxine Sun
Journal:  Can Urol Assoc J       Date:  2014-07       Impact factor: 1.862

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  12 in total

1.  Differentiating solid, non-macroscopic fat containing, enhancing renal masses using fast Fourier transform analysis of multiphase CT.

Authors:  Bino A Varghese; Frank Chen; Darryl H Hwang; Steven Y Cen; Inderbir S Gill; Vinay A Duddalwar
Journal:  Br J Radiol       Date:  2018-06-21       Impact factor: 3.039

2.  Whole-tumor 3D volumetric MRI-based radiomics approach for distinguishing between benign and malignant soft tissue tumors.

Authors:  Brandon K K Fields; Natalie L Demirjian; Darryl H Hwang; Bino A Varghese; Steven Y Cen; Xiaomeng Lei; Bhushan Desai; Vinay Duddalwar; George R Matcuk
Journal:  Eur Radiol       Date:  2021-04-23       Impact factor: 5.315

3.  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

4.  CT-based radiomics stratification of tumor grade and TNM stage of clear cell renal cell carcinoma.

Authors:  Natalie L Demirjian; Bino A Varghese; Steven Y Cen; Darryl H Hwang; Manju Aron; Imran Siddiqui; Brandon K K Fields; Xiaomeng Lei; Felix Y Yap; Marielena Rivas; Sharath S Reddy; Haris Zahoor; Derek H Liu; Mihir Desai; Suhn K Rhie; Inderbir S Gill; Vinay Duddalwar
Journal:  Eur Radiol       Date:  2021-11-10       Impact factor: 5.315

5.  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

6.  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

7.  Predictive models composed by radiomic features extracted from multi-detector computed tomography images for predicting low- and high- grade clear cell renal cell carcinoma: A STARD-compliant article.

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Journal:  Medicine (Baltimore)       Date:  2019-01       Impact factor: 1.889

8.  Preoperative Predicting the WHO/ISUP Nuclear Grade of Clear Cell Renal Cell Carcinoma by Computed Tomography-Based Radiomics Features.

Authors:  Claudia-Gabriela Moldovanu; Bianca Boca; Andrei Lebovici; Attila Tamas-Szora; Diana Sorina Feier; Nicolae Crisan; Iulia Andras; Mircea Marian Buruian
Journal:  J Pers Med       Date:  2020-12-23

9.  New Preoperative Nomogram Using the Centrality Index to Predict High Nuclear Grade Clear Cell Renal Carcinoma.

Authors:  Zhan Feng; Shuangshuang Lou; Lixia Zhang; Liang Zhang; Wenting Lan; Minhong Wang; Qijun Shen; Zhengyu Hu; Feng Chen
Journal:  Cancer Manag Res       Date:  2019-12-31       Impact factor: 3.989

10.  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

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