Skip to main content

Advertisement

SpringerLink
Log in

Renal angiomyolipoma without visible fat: Can we make the diagnosis using CT and MRI?

  • Urogenital
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Renal angiomyolipomas without visible fat (AML.wovf) are benign masses that are incidentally discovered mainly in women. AML.wovf are typically homogeneously hyperdense on unenhanced CT without calcification or haemorrhage. Unenhanced CT pixel analysis is not useful for diagnosis. AML.wovf are characteristically homogeneously hypointense on T2-weighted (T2W)-MRI and apparent diffusion coefficient (ADC) maps. Despite early reports, only a minority of AML.wovf show signal intensity drop on chemical-shift MRI due to microscopic fat. AML.wovf most commonly show avid early enhancement with washout kinetics at contrast-enhanced CT and MRI. The combination of homogeneously low T2W and/or ADC signal intensity with avid early enhancement and washout is highly accurate for diagnosis of AML.wovf.

Key Points

• AML.wovf are small incidental benign renal masses occurring mainly in women.

• AML.wovf are homogeneously hyperdense with low signal on T2W-MRI and ADC map.

• AML.wovf typically show avid early enhancement with washout kinetics.

• Combining features on CT/MRI is accurate for diagnosis of AML.wovf.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

ADC:

Apparent diffusion coefficient

AML.wovf:

Angiomyolipoma without visible fat

CM:

Corticomedullary

CT:

Computed tomography

DWI:

Diffusion-weighted imaging

IP:

In phase

MRI:

Magnetic resonance imaging

NG:

Nephrographic

OP:

Opposed phase

RCC:

Renal cell carcinoma

T1W:

T1-weighted

T2W:

T2-weighted

References

  1. Berland LL, Silverman SG, Gore RM et al (2010) Managing incidental findings on abdominal CT: white paper of the ACR incidental findings committee. J Am Coll Radiol 7:754–773

    Article  PubMed  Google Scholar 

  2. Novick AC CS, Belldegrun A, et al. (2009) Guideline for Management of the Clinical Stage 1 Renal Mass. American Urology Association. Available via https://www.auanet.org/education/guidelines/renal-mass.cfm. Accessed August 10 2014

  3. Frank I, Blute ML, Cheville JC, Lohse CM, Weaver AL, Zincke H (2003) Solid renal tumors: an analysis of pathological features related to tumor size. J Urol 170:2217–2220

    Article  PubMed  Google Scholar 

  4. Fujii Y, Komai Y, Saito K et al (2008) Incidence of benign pathologic lesions at partial nephrectomy for presumed RCC renal masses: Japanese dual-center experience with 176 consecutive patients. Urology 72:598–602

    Article  PubMed  Google Scholar 

  5. Kutikov A, Fossett LK, Ramchandani P et al (2006) Incidence of benign pathologic findings at partial nephrectomy for solitary renal mass presumed to be renal cell carcinoma on preoperative imaging. Urology 68:737–740

    Article  PubMed  Google Scholar 

  6. Eble JN SG, Epstein JI, Sesterhenn IA (2004) World Health Organization classification of tumors: Pathology and genetics of tumors of the urinary system and male genital organs..Lyon, Fr. Available via http://www.iarc.fr/en/publications/pdfs-online/pat-gen/bb7/BB7.pdf2013

  7. D'Angelo PC, Gash JR, Horn AW, Klein FA (2002) Fat in renal cell carcinoma that lacks associated calcifications. AJR Am J Roentgenol 178:931–932

    Article  PubMed  Google Scholar 

  8. Garin JM, Marco I, Salva A, Serrano F, Bondia JM, Pacheco M (2007) CT and MRI in fat-containing papillary renal cell carcinoma. Br J Radiol 80:e193–195

    Article  CAS  PubMed  Google Scholar 

  9. Helenon O, Merran S, Paraf F et al (1997) Unusual fat-containing tumors of the kidney: a diagnostic dilemma. Radiographics 17:129–144

    Article  CAS  PubMed  Google Scholar 

  10. Ramamurthy NK, Moosavi B, McInnes MD, Flood TA, Schieda N (2014) Multiparametric MRI of solid renal masses: pearls and pitfalls. Clin Radiol. S0009-9260(14)00477-2 10.1016/j.crad.2014.10.006

  11. Richmond L, Atri M, Sherman C, Sharir S (2010) Renal cell carcinoma containing macroscopic fat on CT mimics an angiomyolipoma due to bone metaplasia without macroscopic calcification. Br J Radiol 83:e179–181

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Schuster TG, Ferguson MR, Baker DE, Schaldenbrand JD, Solomon MH (2004) Papillary renal cell carcinoma containing fat without calcification mimicking angiomyolipoma on CT. AJR Am J Roentgenol 183:1402–1404

    Article  PubMed  Google Scholar 

  13. Jinzaki M, Silverman SG, Akita H, Nagashima Y, Mikami S, Oya M (2014) Renal angiomyolipoma: a radiological classification and update on recent developments in diagnosis and management. Abdom Imaging. doi:10.1007/s00261-014-0083-3

    PubMed  PubMed Central  Google Scholar 

  14. Schieda N, Kielar AZ, Al Dandan O, McInnes MD, Flood TA (2014) Ten uncommon and unusual variants of renal angiomyolipoma (AML): radiologic-pathologic correlation. Clin Radiol. S0009-9260(14)00472-3 10.1016/j.crad.2014.10.001

  15. Schieda N (2016) Reply to ‘Solid Renal Cell Carcinomas With an Attenuation Similar to That of Water on Unenhanced CT’. AJR Am J Roentgenol 206:W93

    Article  PubMed  Google Scholar 

  16. Jinzaki M, Silverman SG, Akita H, Nagashima Y, Mikami S, Oya M (2014) Renal angiomyolipoma: a radiological classification and update on recent developments in diagnosis and management. Abdom Imaging 39:588–604

    Article  PubMed  PubMed Central  Google Scholar 

  17. Jinzaki M, Tanimoto A, Narimatsu Y et al (1997) Angiomyolipoma: imaging findings in lesions with minimal fat. Radiology 205:497–502

    Article  CAS  PubMed  Google Scholar 

  18. Milner J, McNeil B, Alioto J et al (2006) Fat poor renal angiomyolipoma: patient, computerized tomography and histological findings. J Urol 176:905–909

    Article  PubMed  Google Scholar 

  19. Hakim SW, Schieda N, Hodgdon T, McInnes MD, Dilauro M, Flood TA (2015) Angiomyolipoma (AML) without visible fat: Ultrasound CT and MR imaging features with pathological correlation. Eur Radiol. doi:10.1007/s00330-015-3851-8

    PubMed  Google Scholar 

  20. Armah HB, Parwani AV (2009) Perivascular Epithelioid Cell Tumor. Arch Pathol Lab Med 133:648–654

    PubMed  Google Scholar 

  21. Yang CW, Shen SH, Chang YH et al (2013) Are there useful CT features to differentiate renal cell carcinoma from lipid-poor renal angiomyolipoma? AJR Am J Roentgenol 201:1017–1028

    Article  PubMed  Google Scholar 

  22. Pusiol T, Piscioli I, Morini A (2013) Discordance about the Use of the Term Minimal Fat Angiomyolipoma. Radiology 267:656–657

    Article  PubMed  Google Scholar 

  23. Jeong CJ, Park BK, Park JJ, Kim CK (2016) Unenhanced CT and MRI Parameters That Can Be Used to Reliably Predict Fat-Invisible Angiomyolipoma. AJR Am J Roentgenol 206:340–347

    Article  PubMed  Google Scholar 

  24. Kang SK, Huang WC, Pandharipande PV, Chandarana H (2014) Solid renal masses: what the numbers tell us. AJR Am J Roentgenol 202:1196–1206

    Article  PubMed  PubMed Central  Google Scholar 

  25. Maya ID, Allon M (2009) Percutaneous renal biopsy: outpatient observation without hospitalization is safe. Semin Dial 22:458–461

    Article  PubMed  PubMed Central  Google Scholar 

  26. Silverman SG, Gan YU, Mortele KJ, Tuncali K, Cibas ES (2006) Renal Masses in the Adult Patient: The Role of Percutaneous Biopsy. Radiology 240:6–22

    Article  PubMed  Google Scholar 

  27. Caoili EM, Davenport MS (2014) Role of percutaneous needle biopsy for renal masses. Semin Interv Radiol 31:20–26

    Article  Google Scholar 

  28. Flum AS, Hamoui N, Said MA et al (2016) Update on the Diagnosis and Management of Renal Angiomyolipoma. J Urol 195:834–846

    Article  PubMed  Google Scholar 

  29. Silverman SG, Israel GM, Herts BR, Richie JP (2008) Management of the incidental renal mass. Radiology 249:16–31

    Article  PubMed  Google Scholar 

  30. Chawla SN, Crispen PL, Hanlon AL, Greenberg RE, Chen DYT, Uzzo RG (2006) The Natural History of Observed Enhancing Renal Masses: Meta-Analysis and Review of the World Literature. J Urol 175:425–431

    Article  PubMed  Google Scholar 

  31. Kunkle DA, Egleston BL, Uzzo RG (2008) Excise, ablate or observe: the small renal mass dilemma--a meta-analysis and review. J Urol 179:1227–1233, discussion 1233–1224

    Article  PubMed  Google Scholar 

  32. Jewett MA, Mattar K, Basiuk J et al (2011) Active surveillance of small renal masses: progression patterns of early stage kidney cancer. Eur Urol 60:39–44

    Article  PubMed  Google Scholar 

  33. Van Poppel H, Joniau S (2007) Is Surveillance an Option for the Treatment of Small Renal Masses? Eur Urol 52:1323–1330

    Article  PubMed  Google Scholar 

  34. Campbell SC, Novick AC, Belldegrun A et al Guideline for Management of the Clinical T1 Renal Mass. The Journal of Urology 182:1271–1279

  35. Steiner MS, Goldman SM, Fishman EK, Marshall FF (1993) The natural history of renal angiomyolipoma. J Urol 150:1782–1786

    Article  CAS  PubMed  Google Scholar 

  36. Takahashi N, Leng S, Kitajima K et al (2015) Small (< 4 cm) Renal Masses: Differentiation of Angiomyolipoma Without Visible Fat From Renal Cell Carcinoma Using Unenhanced and Contrast-Enhanced CT. AJR Am J Roentgenol 205:1194–1202

    Article  PubMed  Google Scholar 

  37. Lane BR, Aydin H, Danforth TL et al (2008) Clinical correlates of renal angiomyolipoma subtypes in 209 patients: classic, fat poor, tuberous sclerosis associated and epithelioid. J Urol 180:836–843

    Article  PubMed  Google Scholar 

  38. Park SY, Jeon SS, Lee SY et al (2011) Incidence and predictive factors of benign renal lesions in Korean patients with preoperative imaging diagnoses of renal cell carcinoma. J Korean Med Sci 26:360–364

    Article  PubMed  PubMed Central  Google Scholar 

  39. Hindman N, Ngo L, Genega EM et al (2012) Angiomyolipoma with minimal fat: can it be differentiated from clear cell renal cell carcinoma by using standard MR techniques? Radiology 265:468–477

    Article  PubMed  PubMed Central  Google Scholar 

  40. Murray CA, Quon M, McInnes MD et al (2016) Evaluation of T1-Weighted MRI to Detect Intratumoral Hemorrhage Within Papillary Renal Cell Carcinoma as a Feature Differentiating From Angiomyolipoma Without Visible Fat. AJR Am J Roentgenol 207:585–591

    Article  PubMed  Google Scholar 

  41. Umeoka S, Koyama T, Miki Y, Akai M, Tsutsui K, Togashi K (2008) Pictorial Review of Tuberous Sclerosis in Various Organs. RadioGraphics 28, e32

    Article  PubMed  Google Scholar 

  42. Crino PB, Nathanson KL, Henske EP (2006) The Tuberous Sclerosis Complex. N Engl J Med 355:1345–1356

    Article  CAS  PubMed  Google Scholar 

  43. Schieda N, Hodgdon T, El-Khodary M, Flood TA, McInnes MD (2014) Unenhanced CT for the diagnosis of minimal-fat renal angiomyolipoma. AJR Am J Roentgenol 203:1236–1241

    Article  PubMed  Google Scholar 

  44. Kim JK, Park SY, Shon JH, Cho KS (2004) Angiomyolipoma with minimal fat: differentiation from renal cell carcinoma at biphasic helical CT. Radiology 230:677–684

    Article  PubMed  Google Scholar 

  45. Woo S, Cho JY, Kim SH, Kim SY (2013) Angiomyolipoma with minimal fat and non-clear cell renal cell carcinoma: differentiation on MDCT using classification and regression tree analysis-based algorithm. Acta Radiol. doi:10.1177/0284185113513887

    Google Scholar 

  46. Zhang YY, Luo S, Liu Y, Xu RT (2013) Angiomyolipoma with minimal fat: differentiation from papillary renal cell carcinoma by helical CT. Clin Radiol 68:365–370

    Article  PubMed  Google Scholar 

  47. Hafron J, Fogarty JD, Hoenig DM, Li M, Berkenblit R, Ghavamian R (2005) Imaging characteristics of minimal fat renal angiomyolipoma with histologic correlations. Urology 66:1155–1159

    Article  PubMed  Google Scholar 

  48. Sahni VA, Silverman SG (2009) Biopsy of renal masses: when and why. Cancer Imaging 9:44–55

    Article  PubMed  PubMed Central  Google Scholar 

  49. Yan L, Liu Z, Wang G et al (2015) Angiomyolipoma with Minimal Fat: Differentiation From Clear Cell Renal Cell Carcinoma and Papillary Renal Cell Carcinoma by Texture Analysis on CT Images. Acad Radiol 22:1115–1121

    Article  PubMed  Google Scholar 

  50. Farrell C, Noyes SL, Tourojman M, Lane BR (2015) Renal Angiomyolipoma: Preoperative Identification of Atypical Fat-Poor AML. Curr Urol Rep 16:12

    Article  PubMed  Google Scholar 

  51. Verma SK, Mitchell DG, Yang R et al (2010) Exophytic renal masses: angular interface with renal parenchyma for distinguishing benign from malignant lesions at MR imaging. Radiology 255:501–507

    Article  PubMed  Google Scholar 

  52. Kim KH, Yun BH, Jung SI et al (2013) Usefulness of the ice-cream cone pattern in computed tomography for prediction of angiomyolipoma in patients with a small renal mass. Korean J Urol 54:504–509

    Article  PubMed  PubMed Central  Google Scholar 

  53. Kim JY, Kim JK, Kim N, Cho KS (2008) CT histogram analysis: differentiation of angiomyolipoma without visible fat from renal cell carcinoma at CT imaging. Radiology 246:472–479

    Article  PubMed  Google Scholar 

  54. Catalano OA, Samir AE, Sahani DV, Hahn PF (2008) Pixel distribution analysis: can it be used to distinguish clear cell carcinomas from angiomyolipomas with minimal fat? Radiology 247:738–746

    Article  PubMed  Google Scholar 

  55. Chaudhry HS, Davenport MS, Nieman CM, Ho LM, Neville AM (2012) Histogram analysis of small solid renal masses: differentiating minimal fat angiomyolipoma from renal cell carcinoma. AJR Am J Roentgenol 198:377–383

    Article  PubMed  Google Scholar 

  56. Hodgdon T, McInnes MD, Schieda N, Flood TA, Lamb L, Thornhill RE (2015) Can Quantitative CT Texture Analysis be Used to Differentiate Fat-poor Renal Angiomyolipoma from Renal Cell Carcinoma on Unenhanced CT Images? Radiology. doi:10.1148/radiol.2015142215:142215

    PubMed  Google Scholar 

  57. Zhang J, Lefkowitz RA, Ishill NM et al (2007) Solid Renal Cortical Tumors: Differentiation with CT. Radiology 244:494–504

    Article  PubMed  Google Scholar 

  58. Low G, Huang G, Fu W, Moloo Z, Girgis S (2016) Review of renal cell carcinoma and its common subtypes in radiology. World J Radiol 8:484–500

    Article  PubMed  PubMed Central  Google Scholar 

  59. Roy C, Sauer B, Lindner V, Lang H, Saussine C, Jacqmin D (2007) MR Imaging of papillary renal neoplasms: potential application for characterisation of small renal masses. Eur Radiol 17:193–200

    Article  PubMed  Google Scholar 

  60. Lee-Felker SA, Felker ER, Tan N et al (2014) Qualitative and quantitative MDCT features for differentiating clear cell renal cell carcinoma from other solid renal cortical masses. AJR Am J Roentgenol 203:W516–524

    Article  PubMed  Google Scholar 

  61. Cornelis F, Tricaud E, Lasserre AS et al (2014) Routinely performed multiparametric magnetic resonance imaging helps to differentiate common subtypes of renal tumours. Eur Radiol 24:1068–1080

    Article  CAS  PubMed  Google Scholar 

  62. Pedrosa I, Sun MR, Spencer M et al (2008) MR Imaging of Renal Masses: Correlation with Findings at Surgery and Pathologic Analysis. RadioGraphics 28:985–1003

    Article  PubMed  Google Scholar 

  63. Chung MS, Choi HJ, Kim MH, Cho KS (2014) Comparison of T2-weighted MRI with and without fat suppression for differentiating renal angiomyolipomas without visible fat from other renal tumors. AJR Am J Roentgenol 202:765–771

    Article  PubMed  Google Scholar 

  64. Schieda N, Avruch L, Flood TA (2014) Small (<1 cm) incidental echogenic renal cortical nodules: chemical shift MRI outperforms CT for confirmatory diagnosis of angiomyolipoma (AML). Insights Imaging. doi:10.1007/s13244-014-0323-7

    PubMed Central  Google Scholar 

  65. Schieda N, Dilauro M, Moosavi B et al (2015) MRI evaluation of small (<4cm) solid renal masses: multivariate modeling improves diagnostic accuracy for angiomyolipoma without visible fat compared to univariate analysis. Eur Radiol. doi:10.1007/s00330-015-4039-y

    Google Scholar 

  66. Sasiwimonphan K, Takahashi N, Leibovich BC, Carter RE, Atwell TD, Kawashima A (2012) Small (<4 cm) renal mass: differentiation of angiomyolipoma without visible fat from renal cell carcinoma utilizing MR imaging. Radiology 263:160–168

    Article  PubMed  Google Scholar 

  67. Oliva MR, Glickman JN, Zou KH et al (2009) Renal cell carcinoma: t1 and t2 signal intensity characteristics of papillary and clear cell types correlated with pathology. AJR Am J Roentgenol 192:1524–1530

    Article  PubMed  Google Scholar 

  68. Campbell N, Rosenkrantz AB, Pedrosa I (2014) MRI phenotype in renal cancer: is it clinically relevant? Top Magn Reson Imaging 23:95–115

    Article  PubMed  PubMed Central  Google Scholar 

  69. Young JR, Margolis D, Sauk S, Pantuck AJ, Sayre J, Raman SS (2013) Clear cell renal cell carcinoma: discrimination from other renal cell carcinoma subtypes and oncocytoma at multiphasic multidetector CT. Radiology 267:444–453

    Article  PubMed  Google Scholar 

  70. Amin MB, Corless CL, Renshaw AA, Tickoo SK, Kubus J, Schultz DS (1997) Papillary (chromophil) renal cell carcinoma: histomorphologic characteristics and evaluation of conventional pathologic prognostic parameters in 62 cases. Am J Surg Pathol 21:621–635

    Article  CAS  PubMed  Google Scholar 

  71. Yoshimitsu K, Kakihara D, Irie H et al (2006) Papillary renal carcinoma: diagnostic approach by chemical shift gradient-echo and echo-planar MR imaging. J Magn Reson Imaging 23:339–344

    Article  PubMed  Google Scholar 

  72. Childs DD, Clingan MJ, Zagoria RJ et al (2014) In-phase signal intensity loss in solid renal masses on dual-echo gradient-echo MRI: association with malignancy and pathologic classification. AJR Am J Roentgenol 203:W421–428

    Article  PubMed  Google Scholar 

  73. Kim JK, Kim SH, Jang YJ et al (2006) Renal angiomyolipoma with minimal fat: differentiation from other neoplasms at double-echo chemical shift FLASH MR imaging. Radiology 239:174–180

    Article  PubMed  Google Scholar 

  74. Outwater EK, Bhatia M, Siegelman ES, Burke MA, Mitchell DG (1997) Lipid in renal clear cell carcinoma: detection on opposed-phase gradient-echo MR images. Radiology 205:103–107

    Article  CAS  PubMed  Google Scholar 

  75. Karlo CA, Donati OF, Burger IA et al (2013) MR imaging of renal cortical tumours: qualitative and quantitative chemical shift imaging parameters. Eur Radiol 23:1738–1744

    Article  PubMed  Google Scholar 

  76. Jhaveri KS, Elmi A, Hosseini-Nik H et al (2015) Predictive Value of Chemical-Shift MRI in Distinguishing Clear Cell Renal Cell Carcinoma From Non-Clear Cell Renal Cell Carcinoma and Minimal-Fat Angiomyolipoma. AJR Am J Roentgenol 205:W79–86

    Article  PubMed  Google Scholar 

  77. Schieda N, van der Pol CB, Moosavi B, McInnes MD, Mai KT, Flood TA (2015) Intracellular lipid in papillary renal cell carcinoma (pRCC): T2 weighted (T2W) MRI and pathologic correlation. Eur Radiol. doi:10.1007/s00330-015-3610-x

    Google Scholar 

  78. Ferre R, Cornelis F, Verkarre V et al (2014) Double-echo gradient chemical shift MR imaging fails to differentiate minimal fat renal angiomyolipomas from other homogeneous solid renal tumors. Eur J Radiol. S0720-048X(14)00568-3 10.1016/j.ejrad.2014.11.040

  79. Agnello F, Roy C, Bazille G et al (2013) Small solid renal masses: characterisation by diffusion-weighted MRI at 3 T. Clin Radiol 68:e301–308

    Article  CAS  PubMed  Google Scholar 

  80. Sandrasegaran K, Sundaram CP, Ramaswamy R et al (2010) Usefulness of diffusion-weighted imaging in the evaluation of renal masses. AJR Am J Roentgenol 194:438–445

    Article  PubMed  Google Scholar 

  81. Squillaci E, Manenti G, Di Stefano F, Miano R, Strigari L, Simonetti G (2004) Diffusion-weighted MR imaging in the evaluation of renal tumours. J Exp Clin Cancer Res 23:39–45

    CAS  PubMed  Google Scholar 

  82. Lassel EA, Rao R, Schwenke C, Schoenberg SO, Michaely HJ (2014) Diffusion-weighted imaging of focal renal lesions: a meta-analysis. Eur Radiol 24:241–249

    Article  CAS  PubMed  Google Scholar 

  83. Connolly MJMM, McGrath T, Schieda N (2016) Diagnostic Accuracy of Virtual Non-Contrast Enhanced Dual-Energy CT for Diagnosis of Adrenal Adenoma: A Systematic Review and Meta-AnalysisRadiological Society of North America. RSNA, Chicago Il USA

    Google Scholar 

  84. Park JJ, Kim CK (2016) Small (< 4 cm) Renal Tumors With Predominantly Low Signal Intensity on T2-Weighted Images: Differentiation of Minimal-Fat Angiomyolipoma From Renal Cell Carcinoma. AJR Am J Roentgenol. doi:10.2214/AJR.16.16102:1-7

    Google Scholar 

  85. Villavicencio CP VC, Lewis V, McCarthy R, Oberlin DT, Casalino DD, Miller FH. (2016) Can MR Differentiate Subtypes of Renal Cell Carcinoma and Distinguish Subtypes from Oncocytoma or Angiomyolipoma: Multiparametric Feature Analysis. In: RSNA, (ed) Radiological Society of North America, Chicago Il, USA

  86. Habibollahi P, Chauhan A, Sultan LR, Jones LP, Sehgal CM (2017) Can ‘Tumor-to-Cortex Echogenicity Ratio’ Differentiate Angiomyolipomas from Other Hyper-echoic Renal Masses. Ultrasound Med Biol. doi:10.1016/j.ultrasmedbio.2017.02.015

    PubMed  Google Scholar 

  87. Marin D, Davis D, Roy Choudhury K et al (2017) Characterisation of Small Focal Renal Lesions: Diagnostic Accuracy with Single-Phase Contrast-enhanced Dual-Energy CT with Material Attenuation Analysis Compared with Conventional Attenuation Measurements. Radiology. doi:10.1148/radiol.2017161872:161872

    PubMed Central  Google Scholar 

  88. Mileto A, Nelson RC, Marin D, Roy Choudhury K, Ho LM (2015) Dual-energy multidetector CT for the characterisation of incidental adrenal nodules: diagnostic performance of contrast-enhanced material density analysis. Radiology 274:445–454

    Article  PubMed  Google Scholar 

  89. Lin CY, Chen HY, Ding HJ, Yen KY, Kao CH (2013) FDG PET or PET/CT in evaluation of renal angiomyolipoma. Korean J Radiol 14:337–342

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Medical Imaging, The Ottawa Hospital, The University of Ottawa, Ottawa, Ontario, Canada

    Robert S. Lim, Matthew D. F. McInnes & Nicola Schieda

  2. Department of Anatomical Pathology, The Ottawa Hospital, The University of Ottawa, Ottawa, Ontario, Canada

    Trevor A. Flood

  3. Department of Surgery, Division of Urology, The Ottawa Hospital, The University of Ottawa, Ottawa, Ontario, Canada

    Luke T. Lavallee

Authors
  1. Robert S. Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Trevor A. Flood
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Matthew D. F. McInnes
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Luke T. Lavallee
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nicola Schieda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nicola Schieda.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Nicola Schieda MD FRCP(C).

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Funding

The authors state that this work has not received any funding.

Statistics and biometry

No statistical experience was required (review article).

Ethical approval

Institutional Review Board approval was not required (review article).

Methodology

• Review article

• Performed at one institution

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lim, R.S., Flood, T.A., McInnes, M.D.F. et al. Renal angiomyolipoma without visible fat: Can we make the diagnosis using CT and MRI?. Eur Radiol 28, 542–553 (2018). https://doi.org/10.1007/s00330-017-4988-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-017-4988-4

Keywords

Search

Navigation