Radiologist’s Disease

Herts B.R. Silverman S.G. Hindman N.M. et al.

Management of the Incidental Renal Mass on CT: A White Paper of the ACR Incidental Findings Committee.

J Am Coll Radiol. 15: 264-273Frank I. Blute M.L. Cheville J.C. et al.

Solid renal tumors: an analysis of pathological features related to tumor size.

J Urol. 170: 2217-2220Gill I.S. Aron M. Gervais D.A. et al.

Clinical practice. Small renal mass.

N Engl J Med. 362: 624-634Jewett M.A. Mattar K. Basiuk J. et al.

Active surveillance of small renal masses: progression patterns of early stage kidney cancer.

Eur Urol. 60: 39-44Motzer R.J. Jonasch E. Agarwal N. et al.

Kidney Cancer, Version 3.2022, NCCN Clinical Practice Guidelines in Oncology.

J Natl Compr Canc Netw. 20: 71-90

Image Interpretation: Practical Triage of Benign from Malignant Renal Masses.

Radiol Clin North. 58: 875-884

Wang ZJ, Davenport MS, Silverman SG, et al. (2018) CT renal mass protocols v1.0.Available at: https://c.ymcdn.com/sites/www.abdominalradiology.org/resource/resmgr/education_dfp/RCC/RCC.CTprotocolsfinal-7-15-17.pdf. Accessed February12, 2023.

O'Connor S.D. Silverman S.G. Cochon L.R. et al.

Renal cancer at unenhanced CT: imaging features, detection rates, and outcomes.

Abdom Radiol (NY). 43: 1756-1763Costello J.E. Cecava N.D. Tucker J.E. et al.

CT radiation dose: current controversies and dose reduction strategies.

AJR Am J Roentgenol. 201: 1283-1290

Wang ZJ, Davenport MS, Silverman SG, et al. (2018) MR renal mass protocols v1.0. Available at: https://c.ymcdn.com/sites/www.abdominalradiology.org/resource/resmgr/education_dfp/RCC/RCC.MRIprotocolfinal-7-15-17.pdf. Accessed February 12, 2023.

King K.G. Gulati M. Malhi H. et al.

Quantitative assessment of solid renal masses by contrast-enhanced ultrasound with time-intensity curves: how we do it.

Abdom Imaging. 40: 2461-2471Silverman S.G. Pedrosa I. Ellis J.H. et al.

Bosniak Classification of Cystic Renal Masses, Version 2019: An Update Proposal and Needs Assessment.

Radiology. 292: 475-488Young J.R. Young J.A. Margolis D.J.A. et al.

Sarcomatoid Renal Cell Carcinoma and Collecting Duct Carcinoma: Discrimination From Common Renal Cell Carcinoma Subtypes and Benign RCC Mimics on Multiphasic MDCT.

Acad Radiol. 24: 1226-1232Birnbaum B.A. Jacobs J.E. Ramchandani P.

Multiphasic renal CT: comparison of renal mass enhancement during the corticomedullary and nephrographic phases.

Radiology. 200: 753-758Young J.R. Coy H. Kim H.J. et al.

Performance of Relative Enhancement on Multiphasic MRI for the Differentiation of Clear Cell Renal Cell Carcinoma (RCC) From Papillary and Chromophobe RCC Subtypes and Oncocytoma.

AJR Am J Roentgenol. 208: 812-819Lee-Felker S.A. Felker E.R. Tan N. et al.

Qualitative and quantitative MDCT features for differentiating clear cell renal cell carcinoma from other solid renal cortical masses.

AJR Am J Roentgenol. 203: W516-W524Young J.R. Margolis D. Sauk S. et al.

Clear cell renal cell carcinoma: discrimination from other renal cell carcinoma subtypes and oncocytoma at multiphasic multidetector CT.

Radiology. 267: 444-453Bird V.G. Kanagarajah P. Morillo G. et al.

Differentiation of oncocytoma and renal cell carcinoma in small renal masses (<4 cm): the role of 4-phase computerized tomography.

World J Urol. 29: 787-792Coy H. Young J.R. Douek M.L. et al.

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

Abdom Radiol (NY). 44: 180-189Coy H. Young J.R. Pantuck A.J. et al.

Association of tumor grade, enhancement on multiphasic CT and microvessel density in patients with clear cell renal cell carcinoma.

Abdom Radiol (NY). 45: 3184-3192Sun M.R. Ngo L. Genega E.M. et al.

Renal cell carcinoma: dynamic contrast-enhanced MR imaging for differentiation of tumor subtypes--correlation with pathologic findings.

Radiology. 250: 793-802Young J.R. Coy H. Douek M. et al.

Clear cell renal cell carcinoma: identifying the gain of chromosome 12 on multiphasic MDCT.

Abdom Radiol (NY). 42: 236-241Young J.R. Coy H. Douek M. et al.

Type 1 papillary renal cell carcinoma: differentiation from Type 2 papillary RCC on multiphasic MDCT.

Abdom Radiol (NY). 42: 1911-1918Young J.R. Coy H. Kim H.J. et al.

Clear cell renal cell carcinoma: identifying PTEN expression on multiphasic MDCT.

Abdom Radiol (NY). 43: 3410-3417Young J.R. Coy H. Douek M. et al.

Clear Cell Renal Cell Carcinoma: Identifying the Loss of the Y Chromosome on Multiphasic MDCT.

AJR Am J Roentgenol. 209: 333-338Young J.R. Young J.A. Margolis D.J. et al.

Clear cell renal cell carcinoma: identifying the gain of chromosome 20 on multiphasic MDCT.

Abdom Radiol (NY). 41: 2175-2181Young J.R. Coy H. Kim H.J. et al.

Utility of multiphasic multidetector computed tomography in discriminating between clear cell renal cell carcinomas with high and low carbonic anhydrase-IX expression.

Abdom Radiol (NY). 43: 2734-2742

How We Do It: Managing the Indeterminate Renal Mass with the MRI Clear Cell Likelihood Score.

Radiology. 302: 256-269Steinberg R.L. Rasmussen R.G. Johnson B.A. et al.

Prospective performance of clear cell likelihood scores (ccLS) in renal masses evaluated with multiparametric magnetic resonance imaging.

Eur Radiol. 31: 314-324Schieda N. Davenport M.S. Silverman S.G. et al.

Multicenter Evaluation of Multiparametric MRI Clear Cell Likelihood Scores in Solid Indeterminate Small Renal Masses.

Radiology. 303: 590-599Johnson B.A. Kim S. Steinberg R.L. et al.

Diagnostic performance of prospectively assigned clear cell Likelihood scores (ccLS) in small renal masses at multiparametric magnetic resonance imaging.

Urol Oncol. 37: 941-946Rasmussen R.G. Xi Y. Sibley R.C. et al.

Association of Clear Cell Likelihood Score on MRI and Growth Kinetics of Small Solid Renal Masses on Active Surveillance.

AJR Am J Roentgenol. 218: 101-110

Surawech C, Miao Q, Suvannarerg V. Differentiation Clear Cell Renal Cell Carcinoma from Other Common Renal Masses on Multiphasic MRI: A Likert Based Multireader Analysis.

Cornelis F. Tricaud E. Lasserre A.S. et al.

Multiparametric magnetic resonance imaging for the differentiation of low and high grade clear cell renal carcinoma.

Eur Radiol. 25: 24-31

Tubtawee T. Multireader Diagnostic Accuracy of the Renal Mass CT Score (with Clear Cell RCC Likelihood Score) to Characterize Solid Renal Masses on Multiphasic MDCT.

García-Figueiras R. Goh V.J. Padhani A.R. et al.

CT perfusion in oncologic imaging: a useful tool?.

AJR Am J Roentgenol. 200: 8-19Mazzei F.G. Mazzei M.A. Cioffi Squitieri N. et al.

CT perfusion in the characterisation of renal lesions: an added value to multiphasic CT.

BioMed Res Int. 2014: 135013

Chung A. Quantitative flow Parameters Differentiating Oncocytoma and Papillary Renal Cancer from Clear Cell Renal Cancer on Perfusion MD CT.

Jamshidi N. Jonasch E. Zapala M. et al.

The Radiogenomic Risk Score: Construction of a Prognostic Quantitative, Noninvasive Image-based Molecular Assay for Renal Cell Carcinoma.

Radiology. 277: 114-123Johnson N.B. Johnson M.M. Selig M.K. et al.

Use of electron microscopy in core biopsy diagnosis of oncocytic renal tumors.

Ultrastruct Pathol. 34: 189-194Wilson M.P. Katlariwala P. Abele J. et al.

A review of 99mTc-sestamibi SPECT/CT for renal oncocytomas: A modified diagnostic algorithm.

Intractable Rare Dis Res. 11: 46-51Sheikhbahaei S. Jones C.S. Porter K.K. et al.

Defining the Added Value of 99mTc-MIBI SPECT/CT to Conventional Cross-Sectional Imaging in the Characterization of Enhancing Solid Renal Masses.

Clin Nucl Med. 42: e188-e193Coy H. Young J.R. Douek M.L. et al.

Quantitative computer-aided diagnostic algorithm for automated detection of peak lesion attenuation in differentiating clear cell from papillary and chromophobe renal cell carcinoma, oncocytoma, and fat-poor angiomyolipoma on multiphasic multidetector computed tomography.

Abdom Radiol (NY). 42: 1919-1928Suarez-Ibarrola R. Basulto-Martinez M. Heinze A. et al.

Radiomics Applications in Renal Tumor Assessment: A Comprehensive Review of the Literature.

Cancers. 12https://doi.org/10.3390/cancers12061387Yan L. Liu Z. Wang G. et al.

Angiomyolipoma with minimal fat: differentiation from clear cell renal cell carcinoma and papillary renal cell carcinoma by texture analysis on CT images.

Acad Radiol. 22: 1115-1121Feng Z. Rong P. Cao P. et al.

Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma.

Eur Radiol. 28: 1625-1633Cui E.M. Lin F. Li Q. et al.

Differentiation of renal angiomyolipoma without visible fat from renal cell carcinoma by machine learning based on whole-tumor computed tomography texture features.

Acta Radiol. 60: 1543-1552Yu H. Scalera J. Khalid M. et al.

Texture analysis as a radiomic marker for differentiating renal tumors.

Abdom Radiol (NY). 42: 2470-2478Meng X. Shu J. Xia Y. et al.

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

BioMed Res Int. 2020: 7103647Coy H. Hsieh K. Wu W. et al.

Deep learning and radiomics: the utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT.

Abdom Radiol (NY). 44: 2009-2020Bektas C.T. Kocak B. Yardimci A.H. et al.

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

Eur Radiol. 29: 1153-1163Holdbrook D.A. Singh M. Choudhury Y. et al.

Automated Renal Cancer Grading Using Nuclear Pleomorphic Patterns.

JCO Clin Cancer Inform. 2: 1-12Ding J. Xing Z. Jiang Z. et al.

CT-based radiomic model predicts high grade of clear cell renal cell carcinoma.

Eur J Radiol. 103: 51-56Kocak B. Yardimci A.H. Bektas C.T. et al.

Textural differences between renal cell carcinoma subtypes: Machine learning-based quantitative computed tomography texture analysis with independent external validation.

Eur J Radiol. 107: 149-157Lin F. Cui E.M. Lei Y. et al.

CT-based machine learning model to predict the Fuhrman nuclear grade of clear cell renal cell carcinoma.

Abdom Radiol (NY). 44: 2528-2534Sun X. Liu L. Xu K. et al.

Prediction of ISUP grading of clear cell renal cell carcinoma using support vector machine model based on CT images.

Medicine (Baltim). 98: e15022Shu J. Tang Y. Cui J. et al.

Clear cell renal cell carcinoma: CT-based radiomics features for the prediction of Fuhrman grade.

Eur J Radiol. 109: 8-12Demirjian N.L. Varghese B.A. Cen S.Y. et al.

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

Eur Radiol. 32: 2552-2563Li P. Ren H. Zhang Y. et al.

Fifteen-gene expression based model predicts the survival of clear cell renal cell carcinoma.

Medicine (Baltim). 97: e11839Kocak B. Durmaz E.S. Ates E. et al.

Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning-Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation Status.

AJR Am J Roentgenol. 212: W55-W63Mühlbauer J. Egen L. Kowalewski K.F. et al.

Radiomics in Renal Cell Carcinoma-A Systematic Review and Meta-Analysis.

Cancers. 13https://doi.org/10.3390/cancers13061348Marconi L. Dabestani S. Lam T.B. Hofmann F. Stewart F. Norrie J. Bex A. Bensalah K. Canfield S.E. Hora M. Kuczyk M.A. Merseburger A.S. Mulders P.F.A. Powles T. Staehler M. Ljungberg B. Volpe A.

Systematic Review and Meta-analysis of Diagnostic Accuracy of Percutaneous Renal Tumour Biopsy.

Eur Urol. 69 (): 660-673https://doi.org/10.1016/j.eururo.2015.07.072

Comments (0)

No login
gif