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Differentiation between fat-poor angiomyolipoma and clear cell renal cell carcinoma: qualitative and quantitative analysis using arterial spin labeling MR imaging

  • Jing Ye
  • Qing XuEmail author
  • Shou-An Wang
  • Jin Zheng
  • Qing-Qiang Zhu
  • Wei-Qiang Dou
Kidneys, Ureters, Bladder, Retroperitoneum

Abstract

Purpose

To assess the diagnostic effectiveness of arterial spin labeling (ASL) MR imaging in differentiating fat-poor AML from clear cell renal cell carcinoma (ccRCC).

Methods

In this prospective study, 29 ccRCC patients and 9 fat-poor AML patients underwent routine anatomical MRI and ASL at 3T before surgery after signing written informed consent form. For each tumor, tumor blood flow (TBF) was measured in a region of interest (ROI) which was positioned to outline the edge of the target lesions on ASL perfusion maps. Additionally, the mean TBF values were obtained by standardizing the TBF using a blood flow measurement in the reference ROI. Moreover, a cluster containing more than 10 voxels was chosen from the renal cortex and medulla area in normal contralateral kidney as a reference ROI to calculate tumor-to-cortex ratio and tumor-to-medulla ratio. Independent sample t test was used to examine the alteration among the groups of fat-poor AML and ccRCC. ASL images were together analyzed by two radiologists to assess the following characteristics of the renal mass: predominant SI in the tumor on ASL images was lower than, as same as, or higher than SI of the cortex. For qualitative variables, Fisher’s exact test was employed to compare the proportions of these two groups. The sensitivity, specificity ,and accuracy required for discrimination of fat-poor AML from ccRCC were quantified using receiver operating characteristic (ROC) curve. The corresponding optimal cutoff value was obtained for each parameter as well.

Results

The TBF value was significantly higher in ccRCC group than that in fat-poor AML (270.49 ± 78.88 ml/100 g/min vs. 146.68 ± 47.21 ml/100 g/min; P < 0.01). Both tumor-to-cortex and tumor-to-medulla ratios were notably higher in ccRCC group compared with those in fat-poor AML group (1.22 ± 0.26 vs. 0.74 ± 0.14, 3.13 ± 0.94 vs. 1.77 ± 0.55; P < 0.05). The values of area under the ROC curve (AUC) for TBF, tumor-to-cortex ratio, and tumor-to-medulla ratio were 0.931, 0.964, and 0.900, respectively. No significant difference in AUC values among these three measurements was observed. For qualitative variables, the SI of fat-poor AML was equal to or slightly lower than that of renal medulla and the SI of ccRCC was found to be higher than renal cortex in ASL.

Conclusion

ASL MRI performs well in differentiating fat-poor AML from ccRCC in both qualitative and quantitative analyses.

Keywords

Fat-poor angiomyolipoma Clear cell renal cell carcinoma Magnetic resonance imaging Arterial spin labeling 

Notes

Author contributions

Ye J is the guarantor of integrity of the entire study; all authors contributed to the approval of final version of submitted manuscript and agree to ensure that any questions related to the work are appropriately resolved; Zheng J contributed to clinical case studies; Wang SA contributed to statistical analysis. All authors contributed to manuscript editing.

Funding

National Natural Science Foundation of China, 81401384. Social Develop Foundation of Yangzhou, 2017066. Yangzhou City Science and Education Strengthening Leading Talents Project, LJRC201810. Yangzhou City Science and Education Strengthening Key Talents Project, ZDRC201873. Jiangsu Province “Six First Project” for High-Level Health Professionals, LGY2019032.

Compliance with ethical standards

Conflicts of interest

All authors declare that they have no any conflict of interest.

Informed consent

Informed consent was obtained from the patient included in the study.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Medical Imaging, Clinic Medical School, Northern Jiangsu Province HospitalYangzhou UniversityYangzhouChina
  2. 2.MR Research, GE HealthcareBeijingChina

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