Literature DB >> 31971819

Diagnostic accuracy of signal loss in in-phase gradient-echo images for differentiation between small renal cell carcinoma and lipid-poor angiomyolipomas.

Francisco V A Lima1, Jorge Elias2, Fernando Chahud3, Rodolfo B Reis4, Valdair F Muglia2.   

Abstract

OBJECTIVES: To assess the diagnostic accuracy of signal loss on in-phase (IP) gradient-echo (GRE) images for differentiation between renal cell carcinomas (RCCs) and lipid-poor angiomyolipomas (lpAMLs).
METHODS: We retrospectively searched our institutional database for histologically proven small RCCs (<5.0 cm) and AMLs without visible macroscopic fat (lpAMLs). Two experienced radiologists assessed MRIs qualitatively, to depict signal loss foci on IP GRE images. A third radiologist drew regions of interest (ROIs) on the same lesions, on IP and out-of-phase (OP) images to calculate the ratio of signal loss. Diagnostic accuracy parameters were calculated for both techniques and the inter-reader agreement for the qualitative analysis was evaluated using the κ test.
RESULTS: 15 (38.4%) RCCs lost their signal on IP images, with a sensitivity of 38.5% (95% CI = 23.4-55.4), a specificity of 100% (71.1-100), a positive predictive value (PPV) of 100% (73.4-100), a negative predictive value (NPV) of 31.4% (26.3-37.0), and an overall accuracy of 52% (37.4-66.3%). In terms of the quantitative analysis, the signal intensity index (SII= [(SIIP - SIOP) / SIOP] x 100) for RCCs was -0.132 ± 0.05, while for AMLs it was -0.031 ± 0.02, p = 0.26. The AUC was 0.414 ± -0.09 (0.237-0.592). Using 19% of signal loss as the threshold, sensitivity was 16% and specificity was 100%. The κappa value for subjective analysis was 0.63.
CONCLUSION: Signal loss in "IP" images, assessed subjectively, was highly specific for distinction between RCCs and lpAMLs, although with low sensitivity. The findings can be used to improve the preoperative diagnostic accuracy of MRI for renal masses. ADVANCES IN KNOWLEDGE: Signal loss on "IP" GRE images is a reliable sign for differentiation between RCC and lpAMLs.

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Year:  2020        PMID: 31971819      PMCID: PMC7362915          DOI: 10.1259/bjr.20190975

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  29 in total

Review 1.  Imaging of small renal masses: a medical success story.

Authors:  R J Zagoria
Journal:  AJR Am J Roentgenol       Date:  2000-10       Impact factor: 3.959

2.  Lipid in renal clear cell carcinoma: detection on opposed-phase gradient-echo MR images.

Authors:  E K Outwater; M Bhatia; E S Siegelman; M A Burke; D G Mitchell
Journal:  Radiology       Date:  1997-10       Impact factor: 11.105

3.  Evaluation of T1-Weighted MRI to Detect Intratumoral Hemorrhage Within Papillary Renal Cell Carcinoma as a Feature Differentiating From Angiomyolipoma Without Visible Fat.

Authors:  Catherine A Murray; Matthew Quon; Matthew D F McInnes; Christian B van der Pol; Shaheed W Hakim; Trevor A Flood; Nicola Schieda
Journal:  AJR Am J Roentgenol       Date:  2016-06-08       Impact factor: 3.959

4.  Fat poor renal angiomyolipoma: patient, computerized tomography and histological findings.

Authors:  John Milner; Brian McNeil; Joe Alioto; Kevin Proud; Tara Rubinas; Maria Picken; Terrence Demos; Thomas Turk; Kent T Perry
Journal:  J Urol       Date:  2006-09       Impact factor: 7.450

5.  Renal cell carcinoma: applicability of the apparent coefficient of the diffusion-weighted estimated by MRI for improving their differential diagnosis, histologic subtyping, and differentiation grade.

Authors:  Yulian Mytsyk; Ihor Dutka; Yuriy Borys; Iryna Komnatska; Iryna Shatynska-Mytsyk; Ammad Ahmad Farooqi; Katarina Gazdikova; Martin Caprnda; Luis Rodrigo; Peter Kruzliak
Journal:  Int Urol Nephrol       Date:  2016-11-16       Impact factor: 2.370

6.  Predictive Value of Chemical-Shift MRI in Distinguishing Clear Cell Renal Cell Carcinoma From Non-Clear Cell Renal Cell Carcinoma and Minimal-Fat Angiomyolipoma.

Authors:  Kartik S Jhaveri; Azadeh Elmi; Hooman Hosseini-Nik; Sandeep Hedgire; Andrew Evans; Michael Jewett; Mukesh Harisinghani
Journal:  AJR Am J Roentgenol       Date:  2015-07       Impact factor: 3.959

7.  Double-echo gradient chemical shift MR imaging fails to differentiate minimal fat renal angiomyolipomas from other homogeneous solid renal tumors.

Authors:  R Ferré; F Cornelis; V Verkarre; D Eiss; J M Correas; N Grenier; O Hélénon
Journal:  Eur J Radiol       Date:  2014-12-15       Impact factor: 3.528

Review 8.  Ten uncommon and unusual variants of renal angiomyolipoma (AML): radiologic-pathologic correlation.

Authors:  N Schieda; A Z Kielar; O Al Dandan; M D F McInnes; T A Flood
Journal:  Clin Radiol       Date:  2014-11-15       Impact factor: 2.350

9.  Renal cell carcinoma: t1 and t2 signal intensity characteristics of papillary and clear cell types correlated with pathology.

Authors:  M Raquel Oliva; Jonathan N Glickman; Kelly H Zou; Sze Y Teo; Koenraad J Mortelé; Manoel S Rocha; Stuart G Silverman
Journal:  AJR Am J Roentgenol       Date:  2009-06       Impact factor: 3.959

10.  MR imaging of renal cortical tumours: qualitative and quantitative chemical shift imaging parameters.

Authors:  Christoph A Karlo; Olivio F Donati; Irene A Burger; Junting Zheng; Chaya S Moskowitz; Hedvig Hricak; Oguz Akin
Journal:  Eur Radiol       Date:  2013-01-10       Impact factor: 5.315

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