Literature DB >> 25472466

Multiparametric MRI of solid renal masses: pearls and pitfalls.

N K Ramamurthy1, B Moosavi1, M D F McInnes1, T A Flood2, N Schieda3.   

Abstract

Functional imaging [diffusion-weighted imaging (DWI) and dynamic contrast enhancement (DCE)] techniques combined with T2-weighted (T2W) and chemical-shift imaging (CSI), with or without urography, constitutes a comprehensive multiparametric (MP) MRI protocol of the kidneys. MP-MRI of the kidneys can be performed in a time-efficient manner. Breath-hold sequences and parallel imaging should be used to reduce examination time and improve image quality. Increased T2 signal intensity (SI) in a solid renal nodule is specific for renal cell carcinoma (RCC); whereas, low T2 SI can be seen in RCC, angiomyolipoma (AML), and haemorrhagic cysts. Low b-value DWI can replace conventional fat-suppressed T2W. DWI can be performed free-breathing (FB) with two b-values to reduce acquisition time without compromising imaging quality. RCC demonstrates restricted diffusion; however, restricted diffusion is commonly seen in AML and in chronic haemorrhage. CSI must be performed using the correct echo combination at 3 T or T2* effects can mimic intra-lesional fat. Two-dimensional (2D)-CSI has better image quality compared to three-dimensional (3D)-CSI, but volume averaging in small lesions can simulate intra-lesional fat using 2D techniques. SI decrease on CSI is present in both AML and clear cell RCC. Verification of internal enhancement with MRI can be challenging and is improved with image subtraction. Subtraction imaging is prone to errors related to spatial misregistration, which is ameliorated with expiratory phase imaging. SI ratios can be used to confirm subtle internal enhancement and enhancement curves are predictive of RCC subtype. MR urography using conventional extracellular gadolinium must account for T2* effects; however, gadoxetic acid enhanced urography is an alternative. The purpose of this review it to highlight important technical and interpretive pearls and pitfalls encountered with MP-MRI of solid renal masses.
Copyright © 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

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Year:  2014        PMID: 25472466     DOI: 10.1016/j.crad.2014.10.006

Source DB:  PubMed          Journal:  Clin Radiol        ISSN: 0009-9260            Impact factor:   2.350


  40 in total

1.  MRI evaluation of small (<4cm) solid renal masses: multivariate modeling improves diagnostic accuracy for angiomyolipoma without visible fat compared to univariate analysis.

Authors:  Nicola Schieda; Marc Dilauro; Bardia Moosavi; Taryn Hodgdon; Gregory O Cron; Matthew D F McInnes; Trevor A Flood
Journal:  Eur Radiol       Date:  2015-10-20       Impact factor: 5.315

2.  Angiomyolipoma (AML) without visible fat: Ultrasound, CT and MR imaging features with pathological correlation.

Authors:  Shaheed W Hakim; Nicola Schieda; Taryn Hodgdon; Matthew D F McInnes; Marc Dilauro; Trevor A Flood
Journal:  Eur Radiol       Date:  2015-06-03       Impact factor: 5.315

Review 3.  Imaging of ureter: a primer for the emergency radiologist.

Authors:  Mohd Zahid; Pankaj Nepal; Arpit Nagar; Prem P Batchala; Devendra Kumar; Vijayanadh Ojili
Journal:  Emerg Radiol       Date:  2021-04-13

Review 4.  Imaging features of solid renal masses.

Authors:  Massimo Galia; Domenico Albano; Alberto Bruno; Antonino Agrusa; Giorgio Romano; Giuseppe Di Buono; Francesco Agnello; Giuseppe Salvaggio; Ludovico La Grutta; Massimo Midiri; Roberto Lagalla
Journal:  Br J Radiol       Date:  2017-07-13       Impact factor: 3.039

Review 5.  Imaging Protocols for Active Surveillance in Renal Cell Carcinoma.

Authors:  Christine W Liaw; Jared S Winoker; Reza Mehrazin
Journal:  Curr Urol Rep       Date:  2018-08-13       Impact factor: 3.092

Review 6.  Review of renal cell carcinoma and its common subtypes in radiology.

Authors:  Gavin Low; Guan Huang; Winnie Fu; Zaahir Moloo; Safwat Girgis
Journal:  World J Radiol       Date:  2016-05-28

7.  Predicting common solid renal tumors using machine learning models of classification of radiologist-assessed magnetic resonance characteristics.

Authors:  Camila Lopes Vendrami; Robert J McCarthy; Carolina Parada Villavicencio; Frank H Miller
Journal:  Abdom Radiol (NY)       Date:  2020-07-14

Review 8.  Thoracoabdominal imaging of tuberous sclerosis.

Authors:  Cara E Morin; Nicholas P Morin; David N Franz; Darcy A Krueger; Andrew T Trout; Alexander J Towbin
Journal:  Pediatr Radiol       Date:  2018-08-04

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

Authors:  Brett A Johnson; Sandy Kim; Ryan L Steinberg; Alberto Diaz de Leon; Ivan Pedrosa; Jeffrey A Cadeddu
Journal:  Urol Oncol       Date:  2019-09-17       Impact factor: 3.498

Review 10.  Role of Multiparametric MR Imaging in Malignancies of the Urogenital Tract.

Authors:  Alberto Diaz de Leon; Daniel Costa; Ivan Pedrosa
Journal:  Magn Reson Imaging Clin N Am       Date:  2016-02       Impact factor: 2.266

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