September 2016, VOLUME 207
NUMBER 3

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September 2016, Volume 207, Number 3

Genitourinary Imaging

Original Research

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

+ Affiliations:
1Department of Medical Imaging, The Ottawa Hospital, The University of Ottawa, 1053 Carling Ave, Ottawa, ON K1Y 4E9, Canada.

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

Citation: American Journal of Roentgenology. 2016;207: 585-591. 10.2214/AJR.16.16062

ABSTRACT
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OBJECTIVE. The objective of the present study is to determine whether hemorrhage within papillary renal cell carcinoma (RCC) can be detected using T1-weighted MRI and to ascertain whether it can be used to differentiate papillary RCC from angiomyolipoma (AML) without visible fat.

MATERIALS AND METHODS. A retrospective case-control study compared 11 AMLs without visible fat with 58 papillary RCCs smaller than 5 cm that were evaluated using MRI between 2003 and 2015. Two blinded radiologists subjectively evaluated MR images to identify the presence of intratumoral hemorrhage on the basis of a decrease in signal intensity (SI) on in-phase, compared with opposed-phase, chemical-shift MRI and also on the basis of the SI of the lesion compared with that of the renal cortex on fat-suppressed T1-weighted MRI. A third radiologist established consensus and measured the ratio of the SI of the lesion to that of the renal cortex (hereafter referred to as the “SI ratio”) on T2-weighted MRI; the SI loss index, as calculated using the equation [(SItumorIP − SItumorOP) / SItumorOP] × 100, where IP denotes the in-phase image and OP denotes the opposed-phase image; and the SI ratio on fat-suppressed T1-weighted MRI. Analyses were performed using tests of association and ROCs.

RESULTS. When AMLs without visible fat were compared with papillary RCCs, no statistically significant difference in the T2-weighted SI ratio was noted (p = 0.08). Papillary RCCs had a lower mean (± SD) SI loss index (−3.7% ± 17.3%; range, −51.3% to 31.3%) than did AMLs without visible fat (37.8% ± 76.1%; range, −15.6% to 184.4%) (p < 0.001). A mean SI loss index of less than −16% resulted in an AUC of 0.71 (95% CI, 0.52–0.91), with a sensitivity and specificity of 22.8% and 100%, respectively, for the diagnosis of papillary RCC. After consensus review, none of the AMLs without visible fat and 16 of the 58 papillary RCCs (27.6%) were found to have a decrease in SI on subjective analysis (p = 0.06, κ = 0.60). Between groups, no differences were noted in the SI ratio on fat-suppressed T1-weighted MRI (p = 0.58) or in the SI observed on subjective analysis of fat-suppressed T1-weighted MRI (p = 0.20, κ = 0.48).

CONCLUSION. The presence of intratumoral hemorrhage within papillary RCC is a specific feature that differentiates papillary RCCs from AMLs without visible fat. Subjective analysis may be more clinically appropriate than chemical-shift MRI because of limitations in the quantitative measurement of T2* signal with the use of chemical-shift MRI.

Keywords: angiomyolipoma, hemorrhage, MRI, papillary, renal cell carcinoma

Angiomyolipoma (AML) is a benign renal mesenchymal tumor of the perivascular endothelial cell (i.e., a PEComa) [1, 2]. Classic or triphasic AML shows varying amounts of dysmorphic blood vessels, smooth muscle, and adipose tissue, with the detection of intratumoral macroscopic (i.e., gross) fat required for the definitive diagnosis of AML on the basis of imaging findings [3, 4]. A total of 5% of AMLs do not have sufficient amounts of fat to be detected using conventional CT or MRI [5]. These AMLs are referred to as “AMLs without visible fat” [6]. AMLs without visible fat are commonly resected benign renal neoplasms [7, 8]; therefore, preoperative differentiation of AML without visible fat from renal cell carcinoma (RCC) is desirable.

Numerous CT and MRI findings associated with AML without visible fat have been reported [4, 6, 919]. Of these findings, low T2-weighted signal intensity (SI) is a characteristic finding because of the abundant smooth muscle content of AML without visible fat [5, 6, 17, 20, 21]. Although the T2-weighted SI of AML without visible fat differs significantly from that of clear cell RCC [13, 17, 19, 22] (with clear cell tumors rarely noted as being hypointense on T2-weighted MRI [2326]), low T2-weighted SI is commonly observed in papillary RCC [2528]. Therefore, T2-weighted MRI cannot be used alone to differentiate AML without visible fat from RCC because of substantial overlap with papillary tumors.

Multivariate analysis of MRI findings has been reported to improve differentiation of AML without visible fat from papillary RCC [17, 19, 22]. For example, a decrease in SI on opposed-phase T1-weighted chemical-shift MRI noted in combination with hypointensity on T2-weighted MRI is specific for AMLs without visible fat because, although papillary RCCs may also show a decrease in SI on opposed-phase images, these papillary tumors have a prolonged T2 signal [6, 17, 19, 22, 29].

Unfortunately, despite preliminary reports of the usefulness of chemical-shift MRI in the detection of microscopic fat in AMLs without visible fat [10], it is now known that few AMLs without visible fat have sufficient amounts of fat to be detected using chemical-shift MRI [6, 18, 22]. Moreover, although the combination of rapid wash-in enhancement with washout kinetics on gadolinium-enhanced MRI and low T2-weighted SI may differentiate AML without visible fat from papillary RCC (with the latter characteristically showing progressive enhancement) [17, 22], approximately one-quarter of AMLs without visible fat may not show this typical enhancement pattern [6, 30].

Unlike classic AML, which may present with spontaneous hemorrhage (with increased risk of hemorrhage occurring in AMLs > 4 cm) [3133], AMLs without visible fat do not, to our knowledge, present with hemorrhage; are predominantly composed of smooth muscle [5, 6]; and are typically discovered incidentally when sporadic. Conversely, on histopathologic analysis, RCCs commonly show internal hemorrhage, and of the various RCC subtypes, papillary RCC most frequently shows intratumoral hemorrhage [34, 35]. Yoshimitsu et al. [36] first reported the use of chemical-shift MRI (i.e., detection of susceptibility artifact on the longer-TE in-phase image, compared with the shorter-TE opposed-phase image) as a finding associated with RCC and, in particular, with papillary RCC [36]. More recently, this finding was reevaluated by Childs et al. [37], who also concluded that this finding was specific for RCC and that it was more common in papillary tumors, with histologic analysis confirming its association with the presence of intratumoral hemorrhage.

The purpose of the present study is to evaluate whether intratumoral hemorrhage within papillary RCC, as detected using qualitative and quantitative analysis of chemical-shift MRI and T1-weighted fat-suppressed MRI, which is an additional hemorrhage-sensitive sequence [38], can be used to differentiate papillary RCC from AMLs without visible fat. Intratumoral hemorrhage may be an additional discriminating imaging feature to help further characterize solid renal masses with a low T2-weighted SI.

Materials and Methods
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Patients

This retrospective study was approved by the institutional review board at The Ottawa Hospital, The University of Ottawa, which waived the need for informed consent. We searched the pathology department and PACS databases at our institution to identify patients with histologic diagnoses of papillary RCC (on the basis of findings from either surgical resection or 18-gauge core biopsy) who underwent MRI between May 2003 and October 2015. A total of 69 patients with 76 papillary RCCs were identified.

Papillary RCCs included in the study were required to be less than or equal to 5 cm (because tumors > 5 cm are more likely to be malignant and managed surgically [39]) and solid (i.e., not cystic or necrotic). Sixteen of the 69 patients with papillary RCC were excluded from the study; of these 16 patients, 10 had RCCs larger than 5 cm, four had primarily cystic RCCs, one patient had an incomplete MRI examination, and one patient had severe motion artifact on the MR image, which precluded assessment. Three of the 53 remaining patients had multiple tumors, with two RCCs noted in one patient and four RCCs noted in two patients. Each of the two patients with four RCCs had one tumor excluded from evaluation because the tumor was larger than 5 cm. The final cohort with papillary RCC, therefore, included 53 patients with 58 papillary RCCs.

To establish a comparison group of AMLs without visible fat diagnosed during the same period when the 58 papillary RCCs were diagnosed, we added one patient with AML without visible fat who underwent MRI to an existing database of 10 patients with AML without visible fat who underwent MRI. The comparison group therefore included 11 patients with 11 AMLs without visible fat.

Ten of the 11 AMLs without visible fat and all 58 papillary RCCs in our cohort had previously been studied [6, 22, 29]; however, the objective of the present study (i.e., to detect the presence of intratumoral hemorrhage on chemical-shift and fat-suppressed T1-weighted MRI) had not been the focus of the previous investigations. Data on patient age at diagnosis, sex, and the location of the renal lesion were recorded.

Histopathologic diagnoses of both AML and papillary RCC were independently verified by a genitourinary pathologist with 11 years of experience. For four lesions (one AML without visible fat and three papillary RCCs), histopathologic diagnosis was made by analyzing lesion specimens obtained during 18-gauge core needle biopsy. For all other tumors, histopathologic analysis involved evaluation of specimens obtained during partial or total nephrectomy. The lesion characteristics used in the histopathologic diagnosis of papillary RCC and AML have been described elsewhere [6, 4042]. We did not reevaluate the papillary RCCs for the presence of intratumoral hemorrhage at the time of histopathologic analysis because this finding had been validated repeatedly elsewhere [23, 34, 36, 37].

MRI Technique

Fifty-five of the 64 patients in the groups with papillary RCCs or AMLs without visible fat underwent MRI examination conducted at our institution. MRI was performed using one of three clinical 1.5-T (Magnetom Symphony, Siemens Healthcare) or 3-T systems (Magnetom Trio, Siemens Healthcare; and Discovery 750 W, GE Healthcare) with the use of a torso phased-array coil. For all patients, the following pulse sequences were performed: axial breath-hold in-phase and opposed-phase T1-weighted gradient-recalled echo (GRE), axial respiratory-triggered or breath-hold T2-weighted turbo spin-echo/fast spin-echo (TSE/FSE), and breath-hold fat-suppressed T1-weighted 3D volume-interpolated GRE sequences.

For the T1-weighted dual-echo GRE sequence, imaging was performed as 2D (n = 35 patients) or 3D (n = 20) acquisition. Before 2006, respiratory-triggered T2-weighted TSE sequences were performed (n = 22); however, after 2006, breath-hold single-shot T2-weighted TSE sequences were performed (n = 33). All patients had breath-hold fat-suppressed T1-weighted 3D volume-interpolated GRE sequences performed. The pulse sequence parameters for chemical-shift T1-weighted (both in-phase and opposed-phase) GRE, T2-weighted TSE/FSE, and fat-suppressed T1-weighted volume-interpolated GRE sequences performed on 1.5-T and 3-T MRI systems are shown in Table 1.

TABLE 1: Pulse Sequence Parameters

The remaining nine patients underwent MRI examinations performed at peripheral institutions, with studies available for review through the PACS at our institution. MRI was performed using clinical 1.5-T systems (with Magnetom Avanto [Siemens Healthcare] used for three patients and Achieva [Philips Healthcare] used for six patients.) The MRI technique used was similar to that used at our institution and involved the use of similar sequence parameters, as shown in Table 1. The following sequences were performed for all nine patients: breath-hold 2D T1-weighted dual-echo GRE, breath-hold T2-weighted single-shot TSE, and breath-hold fat-suppressed volume-interpolated 3D T1-weighted GRE.

Subjective Analysis

Two blinded abdominal radiologists with 10 and 16 years of experience in genitourinary imaging evaluated the lesions on chemical-shift and fat-suppressed T1-weighted MRI. Radiologists were provided with information on lesion location only. Studies were reviewed using a PACS workstation (Horizon Medical Imaging, version 11.9; McKesson). Both radiologists were instructed to look for a focal or diffuse decrease in SI on longer-TE in-phase images, compared with opposed-phase images, and to record whether the finding was present or absent as a binary outcome (Fig. 1). Similarly, both radiologists assessed fat-suppressed T1-weighted MR images to determine the subjective SI of the lesion relative to the renal cortex using a 3-point scale, where the lesion could be hypointense, isointense, or hyperintense to the renal cortex. A third abdominal radiologist with 11 years of experience in genitourinary imaging established the consensus diagnosis for cases with discordant diagnoses.

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Fig. 1A —56-year-old man with right anterior interpolar region papillary renal cell carcinoma.

A, Axial T2-weighted single-shot turbo spin-echo (A), in-phase (B), and opposed-phase (C) T1-weighted gradient-recalled echo MR images each show tumor (arrow). Tumor is heterogeneously hypointense to renal cortex on T2-weighted image (arrow, A). Peripheral foci of decrease in signal intensity (arrowheads, B) on in-phase images, compared with opposed-phase images, were identified by both readers. Signal intensity loss index was −8.0%.

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Fig. 1B —56-year-old man with right anterior interpolar region papillary renal cell carcinoma.

B, Axial T2-weighted single-shot turbo spin-echo (A), in-phase (B), and opposed-phase (C) T1-weighted gradient-recalled echo MR images each show tumor (arrow). Tumor is heterogeneously hypointense to renal cortex on T2-weighted image (arrow, A). Peripheral foci of decrease in signal intensity (arrowheads, B) on in-phase images, compared with opposed-phase images, were identified by both readers. Signal intensity loss index was −8.0%.

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Fig. 1C —56-year-old man with right anterior interpolar region papillary renal cell carcinoma.

C, Axial T2-weighted single-shot turbo spin-echo (A), in-phase (B), and opposed-phase (C) T1-weighted gradient-recalled echo MR images each show tumor (arrow). Tumor is heterogeneously hypointense to renal cortex on T2-weighted image (arrow, A). Peripheral foci of decrease in signal intensity (arrowheads, B) on in-phase images, compared with opposed-phase images, were identified by both readers. Signal intensity loss index was −8.0%.

Quantitative Analysis

The third radiologist also evaluated the lesions quantitatively by performing ROI analyses on T2-weighted chemical-shift MR images and fat-suppressed T1-weighted MR images. An ROI was placed in the midpoint of the lesion, encompassing up to two-thirds of the tumor on all sequences at the same level. A fixed-diameter (5 mm) ROI was also placed in the ipsilateral renal cortex when SI ratios were calculated, as described elsewhere [17]. The SI ratios on T2-weighted and fat-suppressed T1-weighted MR images were calculated using the following equation: SItumor / SIcortex [17]. For chemical-shift MRI, the SI loss index was calculated as described elsewhere [37], with the use of the following equation: [(SItumorIP − SItumorOP) / SItumorOP] × 100, where IP denotes the in-phase image and OP denotes the opposed-phase image. The greater the decrease in SI on in-phase images versus opposed-phase images, the more negative the value of the SI loss index was likely to be. The expected loss of SI related to the longer TE of the in-phase sequence was considered negligible in the present study, as has been reported in previously published studies [36, 37]. Standardized ROI placement was used, rather than measurement of areas of a visible decrease in SI, to determine whether there is any additional benefit of quantitative versus subjective analysis.

Statistical Analysis

Parametric data, presented as mean (± SD) values, were compared using independent t tests, and subjective data were compared using the chi-square test of proportions, with interobserver agreement assessed using the Cohen kappa statistic. A Bonferroni correction was applied to correct for familywise error. To determine the diagnostic accuracy of each MRI finding for papillary RCCs and AMLs without visible fat, ROC curves were generated for statistically significant variables and the AUC was calculated. The optimal sensitivity and specificity were recorded using the Youden J statistic. The threshold value p < 0.05 (unless Bonferroni correction was applied) indicated a statistically significant difference. Statistical analysis was performed using Stata data analysis and statistical software (version 13, StataCorp).

Results
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No difference in mean patient age was noted when AMLs without visible fat and papillary RCCs were compared (57.3 ± 4.9 vs 62.2 ± 10.9 years; p = 0.20). More women had AMLs without visible fat (90.9%; 10/11 patients) than papillary RCCs (33.9%; 18/53 patients) (p = 0.001). The mean size of AMLs without visible fat was smaller than that of papillary RCCs 12.8 ± 4.4 vs 25.3 ± 9.7 mm; p < 0.001).

Findings of quantitative imaging analysis are presented in Table 2. No statistically significant difference in the T2-weighted SI ratio was noted when AML without visible fat was compared with papillary RCC (p = 0.08). Papillary RCCs had a lower mean SI loss index (−3.7% ± 17.3%; range, −51.3% to 31.3%) than did AMLs without visible fat (37.8% ± 76.1%; range, −15.6% to 184.4%) (p < 0.001) (Fig. 2). No AMLs without visible fat had an SI loss index lower than −16%; however, this degree of SI loss was only present in 20.7% of papillary RCCs (12/58). For the diagnosis of papillary RCC, an SI loss index of less than −16% had an AUC of 0.71 (95% CI, 0.52–0.91), sensitivity of 22.8%, and specificity of 100% (Fig. 3).

TABLE 2: Quantitative MRI Parameters of Angiomyolipoma (AML) Without Visible Fat and Papillary Renal Cell Carcinoma (RCC)
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Fig. 2 —Box-and-whisker plots comparing quantitative signal intensity loss index associated with renal lesions. Mean signal intensity loss index was lower in papillary renal cell carcinoma (RCC) than in angiomyolipoma without visible fat (p < 0.001), indicating greater signal intensity loss. Threshold signal intensity loss index of less than −16% (dotted line) was specific for papillary RCC. Horizontal lines within boxes denote mean values, vertical lines and whiskers denote 95% CIs, and black circles denote outliers.

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Fig. 3 —ROC curve analysis for diagnosis of papillary renal cell carcinoma, compared with angiomyolipoma without visible fat, using signal intensity loss index threshold of less than −16%. Gray line denotes mean.

The first reader identified one AML without visible fat for which a subjectively assessed decrease in SI was noted on in-phase versus opposed-phase images, whereas the second reader was unable to identify any AMLs without visible fat that showed a subjective decrease in SI on in-phase images, compared with opposed-phase images. After consensus review, zero of 11 AMLs without visible fat and 16 of 58 papillary RCCs (27.6%) showed a decrease in SI on in-phase images compared with opposed-phase images, with moderate interobserver agreement (κ = 0.60). Subjective analysis of chemical-shift MRI identified an additional 10 papillary tumors with a decrease in SI that did not show a quantitative SI loss index of less than −16% (Fig. 1). Conversely, quantitative analysis identified six papillary RCCs that had an SI loss index of less than −16% and that were not subjectively considered to show a decrease in SI on visual analysis. Combining a subjective decrease in SI and a quantitative (i.e., less than −16%) loss in SI improved the sensitivity for the diagnosis of papillary RCC, resulting in a sensitivity of 37.9% (95% CI, 25.5–51.6%) and a specificity of 100% (95% CI, 71.5–100%). Of the 58 papillary RCCs evaluated, a total of 37.9% (n = 22) showed a decrease in SI on in-phase chemical shift MRI, 10.3% (n = 6) showed a decrease in SI on subjective and quantitative analysis, 10.3% (n = 6) showed a decrease in SI on quantitative analysis only, and 17.2% (n = 10) showed a decrease in SI on visual analysis only.

No statistically significant difference in the SI ratio on fat-suppressed T1-weighted MRI was noted when AML without visible fat was compared with papillary RCC (p = 0.58). In addition, no statistically significant difference in subjective SI assessment on fat-suppressed T1-weighted MRI was noted by either reader when AML without visible fat was compared with papillary RCC, and interobserver agreement was weak (p = 0.20, κ = 0.48); however, neither reader considered any AML without visible fat to be hyperintense on T1-weighted MRI.

Discussion
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The present study confirms that intratumoral hemorrhage within papillary RCC can be detected using chemical-shift MRI and illustrates that this imaging finding may be used as an additional feature with which to further characterize solid T2-hypointense renal masses and differentiate papillary RCC from AMLs without visible fat. In our study, a qualitative or quantitative decrease in SI on in-phase versus opposed-phase chemical-shift MRI was specific for the diagnosis of papillary RCC but was not noted in AMLs without visible fat. These results are important because when a small enhancing T2-hypointense renal mass is seen in clinical practice, differentiating between papillary RCC and AML without visible fat is often challenging, and additional discriminating features, such as microscopic fat and an enhancement pattern, are not always observed.

In the present study, no difference in T2-weighted SI was noted when papillary RCC was compared with AML without visible fat, which confirms findings reported elsewhere [5, 6, 17, 20, 21, 2528]. AMLs without visible fat have an intrinsically low T2 signal because of their smooth muscle content [7]. Unlike clear cell RCC (which is rarely T2 hypointense [23]), papillary RCC characteristically shows shortened T2 values that are thought to be related to papillary architecture and intratumoral hemorrhage [23, 36]. Therefore, the main differential diagnosis for an enhancing T2-hypointense renal lesion is papillary RCC and AML without visible fat. The use of multivariate analysis of additional MRI findings (e.g., intratumoral lipid, enhancement pattern, and homogeneity [6, 43]) must be relied on for potential differentiation. These additional findings can be limited because approximately one-quarter of AMLs without visible fat may show gradual progressive enhancement [6, 30], and few AMLs without visible fat have sufficient amounts of microscopic fat to be detected using chemical-shift MRI [6, 18, 22]. Assessment of tumor homogeneity is limited by the subjective nature of the finding and, to our knowledge, has not been quantitatively evaluated with MRI.

The present study confirmed that intratumoral hemorrhage can be detected in papillary tumors by observing a decrease in SI on the longer-TE in-phase image, compared with the shorter-TE opposed-phase images. The rate of the decrease in the SI observed in papillary RCCs in the present study compares favorably with the rates described by Yoshimitsu et al. [36] and Childs et al. [37], with approximately 40% of papillary tumors showing the finding. In our study, an SI loss index of less than −16% was specific for papillary RCC and identified an additional six tumors that did not show a visual decrease in SI on subjective analysis. This finding compares favorably to the results from the study by Yoshimitsu et al. The use of quantitative MRI analysis of dual-echo chemical-shift MRI to measure T2* effects in renal masses should be interpreted and applied cautiously because of differences that can be expected in relation to various factors, including primarily field strength, TR, and TE [44].

Although the quantitative results of our study using the previously described SI loss index are concordant with those previously published by Yoshimitsu et al. [36] and Childs et al. [37], if quantitative measurement of T2* in renal masses is to be applied in clinical practice, it may be better performed using a dedicated T2* GRE sequence with the use of a body coil at specified field strengths, to control for differences that would be expected because of hardware and pulse sequence acquisition parameters as well as because of confounding effects related to T1 signal and the presence of microscopic fat or intracellular lipid [45, 46]. Nevertheless, the subjective evaluation of dual-echo chemical-shift MRI for susceptibility effects in renal masses can be readily applied in clinical practice, and more sensitive techniques for the detection of internal hemorrhage, such as susceptibility weighted MRI, may be of additional benefit [47, 48]. Further analysis is required.

In the present study, fat-suppressed T1-weighted imaging was not useful in differentiating papillary RCC from AML without visible fat. This may be related to the nature of the intratumoral hemorrhage within papillary tumors, which usually is in the form of hemosiderin [34, 35]. Hemosiderin would be expected to show low T1-weighted SI, whereas deoxyhemoglobin is typically hyperintense on T1-weighted MRI [49]. In the present study, no AML without visible fat was considered hyperintense on T1-weighted MRI, which is a finding that is concordant with results of a previous study by Hindman et al. [13], which compared AML without visible fat with clear cell RCC and which found that no AML without visible fat showed internal hemorrhage on fat-suppressed T1-weighted MRI.

There are limitations to the present study. To maximize our sample size, we used a long study period, which resulted in heterogeneity in MRI protocols; however, our study design and the MRI techniques used are comparable to what has been previously reported. Despite the long study period, the number of AMLs without visible fat remained relatively small, and our results require validation in future studies. Including patients with multiple lesions in the group with papillary RCC introduces cluster bias into our study; however, we think that this is a minor limitation because only three patients had multiple RCCs. We did not assess the use of chemical-shift MRI for the detection of intratumoral lipid in AMLs without visible fat or papillary RCC tumors because this has been previously reported elsewhere [22, 29]. Similarly, we did not assess other MRI features that may differentiate papillary RCC from AML without visible fat (e.g., contrast enhancement characteristics, DWI, or heterogeneity) because these features have also been previously reported [22, 29, 43, 50] and were not the intended focus of the study.

In conclusion, intratumoral hemorrhage within papillary RCC can be detected using qualitative or quantitative analysis of chemical-shift MRI, by noting a decrease in SI when longer-TE in-phase images are compared with shorter-TE opposed-phase images. Although sensitivity was low, this imaging finding was not observed in AMLs without visible fat, showing high specificity for papillary tumors. Our results suggest that intratumoral hemorrhage, when detected using chemical-shift MRI, can be used as an additional discriminating imaging feature in the characterization of solid T2-hypointense renal masses. The subjective evaluation of dual-echo chemical-shift MRI for the detection of T2* effects within renal tumors is more clinically appropriate because of technical differences that can be expected with the use of quantitative analysis, and further analysis of dedicated T2* GRE sequences are required if quantitative metrics are to be applied in clinical practice.

References
Previous sectionNext section
1. Eble JN, Sauter G, Epstein JI, Sesterhenn IA, eds. World Health Organization classification of tumors: pathology and genetics—tumours of the urinary system and male genital organs. Lyon, France: IARC Press, 2004 [Google Scholar]
2. Bissler JJ, Kingswood JC. Renal angiomyolipomata. Kidney Int 2004; 66:924–934 [Google Scholar]
3. Schieda N, Avruch L, Flood TA. Small (<1 cm) incidental echogenic renal cortical nodules: chemical shift MRI outperforms CT for confirmatory diagnosis of angiomyolipoma (AML). Insights Imaging 2014; 5:295–299 [Google Scholar]
4. Schieda N, Hodgdon T, El-Khodary M, Flood TA, McInnes MD. Unenhanced CT for the diagnosis of minimal-fat renal angiomyolipoma. AJR 2014; 203:1236–1241 [Abstract] [Google Scholar]
5. Jinzaki M, Silverman SG, Akita H, Nagashima Y, Mikami S, Oya M. Renal angiomyolipoma: a radiological classification and update on recent developments in diagnosis and management. Abdom Imaging 2014; 39:588–604 [Google Scholar]
6. Hakim SW, Schieda N, Hodgdon T, McInnes MD, Dilauro M, Flood TA. Angiomyolipoma (AML) without visible fat: ultrasound, CT and MR imaging features with pathological correlation. Eur Radiol 2016; 26:592–600 [Google Scholar]
7. Remzi M, Ozsoy M, Klingler HC, et al. Are small renal tumors harmless? Analysis of histopathological features according to tumors 4 cm or less in diameter. J Urol 2006; 176:896–899 [Google Scholar]
8. Violette P, Abourbih S, Szymanski KM, et al. Solitary solid renal mass: can we predict malignancy? BJU Int 2012; 110:E548–E552 [Google Scholar]
9. Simpfendorfer C, Herts BR, Motta-Ramirez GA, et al. Angiomyolipoma with minimal fat on MDCT: can counts of negative-attenuation pixels aid diagnosis? AJR 2009; 192:438–443 [Abstract] [Google Scholar]
10. Kim JK, Kim SH, Jang YJ, et al. Renal angiomyolipoma with minimal fat: differentiation from other neoplasms at double-echo chemical shift FLASH MR imaging. Radiology 2006; 239:174–180 [Google Scholar]
11. Kim JK, Park SY, Shon JH, Cho KS. Angiomyolipoma with minimal fat: differentiation from renal cell carcinoma at biphasic helical CT. Radiology 2004; 230:677–684 [Google Scholar]
12. Kim JY, Kim JK, Kim N, Cho KS. CT histogram analysis: differentiation of angiomyolipoma without visible fat from renal cell carcinoma at CT imaging. Radiology 2008; 246:472–479 [Google Scholar]
13. Hindman N, Ngo L, Genega EM, 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 [Google Scholar]
14. Zhang YY, Luo S, Liu Y, Xu RT. Angiomyolipoma with minimal fat: differentiation from papillary renal cell carcinoma by helical CT. Clin Radiol 2013; 68:365–370 [Google Scholar]
15. Chaudhry HS, Davenport MS, Nieman CM, Ho LM, Neville AM. Histogram analysis of small solid renal masses: differentiating minimal fat angiomyolipoma from renal cell carcinoma. AJR 2012; 198:377–383 [Abstract] [Google Scholar]
16. Jinzaki M, Tanimoto A, Narimatsu Y, et al. Angiomyolipoma: imaging findings in lesions with minimal fat. Radiology 1997; 205:497–502 [Google Scholar]
17. Sasiwimonphan K, Takahashi N, Leibovich BC, Carter RE, Atwell TD, Kawashima A. Small (<4 cm) renal mass: differentiation of angiomyolipoma without visible fat from renal cell carcinoma utilizing MR imaging. Radiology 2012; 263:160–168 [Google Scholar]
18. Ferré R, Cornelis F, Verkarre V, et al. Double-echo gradient chemical shift MR imaging fails to differentiate minimal fat renal angiomyolipomas from other homogeneous solid renal tumors. Eur J Radiol 2015; 84:360–365 [Google Scholar]
19. Cornelis F, Tricaud E, Lasserre AS, et al. Routinely performed multiparametric magnetic resonance imaging helps to differentiate common subtypes of renal tumours. Eur Radiol 2014; 24:1068–1080 [Google Scholar]
20. Schieda N, Kielar AZ, Al Dandan O, McInnes MD, Flood TA. Ten uncommon and unusual variants of renal angiomyolipoma (AML): radiologic-pathologic correlation. Clin Radiol 2015; 70:206–220 [Google Scholar]
21. Choi HJ, Kim JK, Ahn H, Kim CS, Kim MH, Cho KS. Value of T2-weighted MR imaging in differentiating low-fat renal angiomyolipomas from other renal tumors. Acta Radiol 2011; 52:349–353 [Google Scholar]
22. Schieda N, Dilauro M, Moosavi B, et al. MRI evaluation of small (<4cm) solid renal masses: multivariate modeling improves diagnostic accuracy for angiomyolipoma without visible fat compared to univariate analysis. Eur Radiol 2015 Oct 20 [Epub ahead of print] [Google Scholar]
23. Oliva MR, Glickman JN, Zou KH, et al. Renal cell carcinoma: T1 and T2 signal intensity characteristics of papillary and clear cell types correlated with pathology. AJR 2009; 192:1524–1530 [Abstract] [Google Scholar]
24. Chung MS, Choi HJ, Kim MH, Cho KS. Comparison of T2-weighted MRI with and without fat suppression for differentiating renal angiomyolipomas without visible fat from other renal tumors. AJR 2014; 202:765–771 [Abstract] [Google Scholar]
25. Pedrosa I, Sun MR, Spencer M, et al. MR imaging of renal masses: correlation with findings at surgery and pathologic analysis. RadioGraphics 2008; 28:985–1003 [Google Scholar]
26. Campbell N, Rosenkrantz AB, Pedrosa I. MRI phenotype in renal cancer: is it clinically relevant? Top Magn Reson Imaging 2014; 23:95–115 [Google Scholar]
27. Prasad SR, Humphrey PA, Catena JR, et al. Common and uncommon histologic subtypes of renal cell carcinoma: imaging spectrum with pathologic correlation. RadioGraphics 2006; 26:1795–1806; discussion, 1806–1810 [Google Scholar]
28. Ramamurthy NK, Moosavi B, McInnes MD, Flood TA, Schieda N. Multiparametric MRI of solid renal masses: pearls and pitfalls. Clin Radiol 2015; 70:304–316 [Google Scholar]
29. Schieda N, van der Pol CB, Moosavi B, McInnes MD, Mai KT, Flood TA. Intracellular lipid in papillary renal cell carcinoma (pRCC): T2 weighted (T2W) MRI and pathologic correlation. Eur Radiol 2015; 25:2134–2142 [Google Scholar]
30. Lee-Felker SA, Felker ER, Tan N, et al. Qualitative and quantitative MDCT features for differentiating clear cell renal cell carcinoma from other solid renal cortical masses. AJR 2014; 203:[web] W516–W524 [Abstract] [Google Scholar]
31. Kuusk T, Biancari F, Lane B, et al. Treatment of renal angiomyolipoma: pooled analysis of individual patient data. BMC Urol 2015; 15:123 [Google Scholar]
32. Yamakado K, Tanaka N, Nakagawa T, Kobayashi S, Yanagawa M, Takeda K. Renal angiomyolipoma: relationships between tumor size, aneurysm formation, and rupture. Radiology 2002; 225:78–82 [Google Scholar]
33. Muttarak M, Pattamapaspong N, Lojanapiwat B, Chaiwun B. Renal angiomyolipoma with bleeding. Biomed Imaging Interv J 2007; 3:e8 [Google Scholar]
34. Amin MB, Corless CL, Renshaw AA, Tickoo SK, Kubus J, Schultz DS. 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 [Google Scholar]
35. Granter SR, Perez-Atayde AR, Renshaw AA. Cytologic analysis of papillary renal cell carcinoma. Cancer 1998; 84:303–308 [Google Scholar]
36. Yoshimitsu K, Kakihara D, Irie H, 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 [Google Scholar]
37. Childs DD, Clingan MJ, Zagoria RJ, et al. In-phase signal intensity loss in solid renal masses on dual-echo gradient-echo MRI: association with malignancy and pathologic classification. AJR 2014; 203:[web]W421–W428 [Abstract] [Google Scholar]
38. Siegelman ES. Body MRI. Philadelphia, PA: Elsevier Saunders, 2004 [Google Scholar]
39. Hsu RM, Chan DY, Siegelman SS. Small renal cell carcinomas: correlation of size with tumor stage, nuclear grade, and histologic subtype. AJR 2004; 182:551–557 [Abstract] [Google Scholar]
40. Delahunt B, Eble JN. Papillary renal cell carcinoma: a clinicopathologic and immunohistochemical study of 105 tumors. Mod Pathol 1997; 10:537–544 [Google Scholar]
41. Lefèvre M, Couturier J, Sibony M, et al. Adult papillary renal tumor with oncocytic cells: clinicopathologic, immunohistochemical, and cytogenetic features of 10 cases. Am J Surg Pathol 2005; 29:1576–1581 [Google Scholar]
42. Renshaw AA, Corless CL. Papillary renal cell carcinoma: histology and immunohistochemistry. Am J Surg Pathol 1995; 19:842–849 [Google Scholar]
43. Hodgdon T, McInnes MD, Schieda N, Flood TA, Lamb L, Thornhill RE. Can quantitative CT texture analysis be used to differentiate fat-poor renal angiomyolipoma from renal cell carcinoma on unenhanced CT images? Radiology 2015; 276:787–796 [Google Scholar]
44. Chavhan GB, Babyn PS, Thomas B, Shroff MM, Haacke EM. Principles, techniques, and applications of T2*-based MR imaging and its special applications. RadioGraphics 2009; 29:1433–1449 [Google Scholar]
45. Gandon Y, Olivie D, Guyader D, et al. Non-invasive assessment of hepatic iron stores by MRI. Lancet 2004; 363:357–362 [Google Scholar]
46. Schieda N, Ramanathan S, Ryan J, Khanna M, Virmani V, Avruch L. Diagnostic accuracy of dual-echo (in- and opposed-phase) T1-weighted gradient recalled echo for detection and grading of hepatic iron using quantitative and visual assessment. Eur Radiol 2014; 24:1437–1445 [Google Scholar]
47. Xing W, He X, Kassir MA, et al. Evaluating hemorrhage in renal cell carcinoma using susceptibility weighted imaging. PLoS One 2013; 8:e57691 [Google Scholar]
48. Chen J, Sun J, Xing W, 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 [Google Scholar]
49. Helms CA, Major NM, Anderson MW, Kaplan P, Dussault R. Musculoskeletal MRI. Philadelphia, PA: Saunders, 2008 [Google Scholar]
50. Tanaka H, Yoshida S, Fujii Y, et al. Diffusion-weighted magnetic resonance imaging in the differentiation of angiomyolipoma with minimal fat from clear cell renal cell carcinoma. Int J Urol 2011; 18:727–730 [Google Scholar]
Address correspondence to N. Schieda ().

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