Differentiation between papillary renal cell carcinoma and fat-poor angiomyolipoma: a preliminary study assessing detection of intratumoral hemorrhage with chemical shift MRI and T2*-weighted gradient echo

Abstract

Background

Recent literature suggests that intratumoral hemorrhage detection may be helpful in differentiating papillary renal cell carcinoma (pRCC) from fat-poor angiomyolipoma (fpAML).

Purpose

To determine whether intratumoral hemorrhage detected using chemical shift magnetic resonance imaging (MRI) and T2*-weighted (T2*W) gradient echo (GRE) can be used to differentiate pRCC from fpAML.

Material and Methods

This retrospective study included 42 patients with pRCC (n = 28) and fpAML (n = 14) who underwent MRI followed by surgery. Two blinded radiologists independently assessed the presence of intratumoral hemorrhage using chemical shift MRI (decrease in signal intensity from opposed- to in-phase) and T2*W GRE (“blooming”). Consensus reading was determined for discrepant cases. MRI findings were compared using Chi-square test. Inter-observer agreement was assessed using kappa statistics.

Results

Inter-observer agreement was substantial for both sequences (k = 0.622 and 0.793, P < 0.001). For chemical shift MRI, the prevalence of intratumoral hemorrhage was significantly greater in pRCC than in fpAML (71.4% versus 28.6%, P = 0.019 for reader 1; 64.3% versus 14.3%, P = 0.003 for reader 2; and 75% versus 21.4%, P = 0.002 for the consensus). T2*W GRE showed a similar tendency (46.4% versus 14.3%, P = 0.049 for both readers; and 50% versus 14.3%, P = 0.042 for the consensus). Using the consensus reading, sensitivity and specificity of determining pRCC were 75% and 78.6% for chemical shift MRI and 50% and 85.7% for T2*W GRE.

Conclusion

The prevalence of intratumoral hemorrhage identified from chemical shift MRI or T2*W GRE was significantly different between pRCC and fpAML. These hemorrhage-sensitive MRI sequences may be used as an adjunctive tool for discriminating between the two entities.

Keywords

Fat-poor angiomyolipoma papillary renal cell carcinoma magnetic resonance imaging (MRI)hemosiderin hemorrhage

Get full access to this article

View all access options for this article.

References

Bissler

Kingswood

. Renal angiomyolipomata. Kidney Int 2004; 66: 924–934.

Jinzaki

Silverman

Akita

et al.

Renal angiomyolipoma: a radiological classification and update on recent developments in diagnosis and management. Abdom Imaging 2014; 39: 588–604.

Woo

Cho

Kim

et al.

Angiomyolipoma with minimal fat and non-clear cell renal cell carcinoma: differentiation on MDCT using classification and regression tree analysis-based algorithm. Acta Radiol 2014; 55: 1258–1269.

Sasiwimonphan

Takahashi

Leibovich

et al.

Small (<4 cm) renal mass: differentiation of angiomyolipoma without visible fat from renal cell carcinoma utilizing MR imaging. Radiology 2012; 263: 160–168.

Schieda

Dilauro

Moosavi

et al.

MRI evaluation of small (<4 cm) solid renal masses: multivariate modeling improves diagnostic accuracy for angiomyolipoma without visible fat compared to univariate analysis. Eur Radiol 2016; 26: 2242–2251.

Hindman

Ngo

Genega

et al.

Angiomyolipoma with minimal fat: can it be differentiated from clear cell renal cell carcinoma by using standard MR techniques?

Radiology 2012; 265: 468–477.

Amin

Corless

Renshaw

et al.

Papillary (chromophil) renal cell carcinoma: histomorphologic characteristics and evaluation of conventional pathologic prognostic parameters in 62 cases. Am J Surg Pathol 1997; 21: 621–635.

Hakim

Schieda

Hodgdon

et al.

Angiomyolipoma (AML) without visible fat: Ultrasound, CT and MR imaging features with pathological correlation. Eur Radiol 2016; 26: 592–600.

Yoshimitsu

Kakihara

Irie

et al.

Papillary renal carcinoma: diagnostic approach by chemical shift gradient-echo and echo-planar MR imaging. J Magn Reson Imaging 2006; 23: 339–344.

10.

Childs

Clingan

Zagoria

et al.

In-phase signal intensity loss in solid renal masses on dual-echo gradient-echo MRI: association with malignancy and pathologic classification. Am J Roentgenol 2014; 203: W421–428.

11.

Murray

Quon

McInnes

et al.

Evaluation of T1-weighted MRI to detect intratumoral hemorrhage within papillary renal cell carcinoma as a feature differentiating from angiomyolipoma without visible fat. Am J Roentgenol 2016; 207: 585–591.

12.

Lin

Filippi

Steever

et al.

Detection of intracranial hemorrhage: comparison between gradient-echo images and b(0) images obtained from diffusion-weighted echo-planar sequences. Am J Neuroradiol 2001; 22: 1275–1281.

13.

Hsu

Chan

Siegelman

. Small renal cell carcinomas: correlation of size with tumor stage, nuclear grade, and histologic subtype. Am J Roentgenol 2004; 182: 551–557.

14.

Chavhan

Babyn

Thomas

et al.

Principles, techniques, and applications of T2*-based MR imaging and its special applications. Radiographics 2009; 29: 1433–1449.

15.

Woo

Kim

Lee

et al.

MDCT findings of renal cell carcinoma associated with Xp11.2 translocation and TFE3 gene fusion and papillary renal cell carcinoma. Am J Roentgenol 2015; 204: 542–549.

16.

Woo

Cho

Kim

et al.

Comparison of segmental enhancement inversion on biphasic MDCT between small renal oncocytomas and chromophobe renal cell carcinomas. Am J Roentgenol 2013; 201: 598–604.

17.

Landis

Koch

. The measurement of observer agreement for categorical data. Biometrics 1977; 33: 159–174.

18.

Patterson

Lohr

Briscoe

et al.

Calcified renal masses. Urology 1987; 29: 353–356.

19.

Chen

Tang

et al.

Calcified, minimally fat-contained angiomyolipoma clinically indistinguishable from a renal cell carcinoma. BMC Nephrol 2013; 14: 160–160.

20.

Sun

Xing

et al.

Intratumoral Macroscopic Fat and Hemorrhage Combination Useful in the Differentiation of Benign and Malignant Solid Renal Masses. Medicine 2016; 95: e2960–e2960.

21.

Qiu

Zhang

et al.

Detection of intratumoral susceptibility signals using T2*-weighted gradient echo MRI in patients with clear cell renal cell carcinoma. PLoS ONE 2013; 8: e79597–e79597.

22.

Chen

Ding

Dai

et al.

Assessment of intratumoral micromorphology for patients with clear cell renal cell carcinoma using susceptibility-weighted imaging. PLoS ONE 2013; 8: e65866–e65866.

23.

Chen

Sun

Xing

et al.

Prediction of nuclear grade of clear cell renal cell carcinoma with MRI: intratumoral susceptibility signal intensity versus necrosis. Acta Radiol 2014; 55: 378–384.

24.

Woo

Kim

. Differentiation of small, solid renal masses: a pattern recognition approach. Semin Ultrasound CT MR 2017; 38: 28–36.