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Circularity Index on Contrast-Enhanced Computed Tomography Helps Distinguish Fat-Poor Angiomyolipoma from Renal Cell Carcinoma: Retrospective Analyses of Histologically Proven 257 Small Renal Tumors Less Than 4 cm

  • Hye Seon Kang (Department of Radiology, Chungnam National University Hospital) ;
  • Jung Jae Park (Department of Radiology, Chungnam National University Hospital)
  • Received : 2020.07.02
  • Accepted : 2020.10.08
  • Published : 2021.05.01

Abstract

Objective: To evaluate circularity as a quantitative shape factor of small renal tumor on computed tomography (CT) in differentiating fat-poor angiomyolipoma (AML) from renal cell carcinoma (RCC). Materials and Methods: In 257 consecutive patients, 257 pathologically confirmed renal tumors (either AML or RCC less than 4 cm), which did not include visible fat on unenhanced CT, were retrospectively evaluated. A radiologist drew the tumor margin to measure the perimeter and area in all the contrast-enhanced axial CT images. In each image, a quantitative shape factor, circularity, was calculated using the following equation: 4 x π x (area ÷ perimeter2). The median circularity (circularity index) was adopted as a representative value in each tumor. The circularity index was compared between fat-poor AML and RCC, and the receiver operating characteristic (ROC) curve analysis was performed. Univariable and multivariable binary logistic regression analysis was performed to determine the independent predictor of fat-poor AML. Results: Of the 257 tumors, 26 were AMLs and 231 were RCCs (184 clear cell RCCs, 25 papillary RCCs, and 22 chromophobe RCCs). The mean circularity index of AML was significantly lower than that of RCC (0.86 ± 0.04 vs. 0.93 ± 0.02, p < 0.001). The mean circularity index was not different between the subtypes of RCCs (0.93 ± 0.02, 0.92 ± 0.02, and 0.92 ± 0.02 for clear cell, papillary, and chromophobe RCCs, respectively, p = 0.210). The area under the ROC curve of circularity index was 0.924 for differentiating fat-poor AML from RCC. The sensitivity and specificity were 88.5% and 90.9%, respectively (cut-off, 0.90). Lower circularity index (≤ 0.9) was an independent predictor (odds ratio, 41.0; p < 0.001) for predicting fat-poor AML on multivariable logistic regression analysis. Conclusion: Circularity is a useful quantitative shape factor of small renal tumor for differentiating fat-poor AML from RCC.

Keywords

References

  1. Fujii Y, Ajima J, Oka K, Tosaka A, Takehara Y. Benign renal tumors detected among healthy adults by abdominal ultrasonography. Eur Urol 1995;27:124-127 https://doi.org/10.1159/000475142
  2. Kutikov A, Fossett LK, Ramchandani P, Tomaszewski JE, Siegelman ES, Banner MP, et al. Incidence of benign pathologic findings at partial nephrectomy for solitary renal mass presumed to be renal cell carcinoma on preoperative imaging. Urology 2006;68:737-740 https://doi.org/10.1016/j.urology.2006.04.011
  3. Bosniak MA, Megibow AJ, Hulnick DH, Horii S, Raghavendra BN. CT diagnosis of renal angiomyolipoma: the importance of detecting small amounts of fat. AJR Am J Roentgenol 1988;151:497-501 https://doi.org/10.2214/ajr.151.3.497
  4. Takahashi K, Honda M, Okubo RS, Hyodo H, Takakusaki H, Yokoyama H, et al. CT pixel mapping in the diagnosis of small angiomyolipomas of the kidneys. J Comput Assist Tomogr 1993;17:98-101 https://doi.org/10.1097/00004728-199301000-00018
  5. Jinzaki M, Tanimoto A, Narimatsu Y, Ohkuma K, Kurata T, Shinmoto H, et al. Angiomyolipoma: imaging findings in lesions with minimal fat. Radiology 1997;205:497-502 https://doi.org/10.1148/radiology.205.2.9356635
  6. 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 https://doi.org/10.1148/radiol.2303030003
  7. Silverman SG, Israel GM, Herts BR, Richie JP. Management of the incidental renal mass. Radiology 2008;249:16-31 https://doi.org/10.1148/radiol.2491070783
  8. Fittschen A, Wendlik I, Oeztuerk S, Kratzer W, Akinli AS, Haenle MM, et al. Prevalence of sporadic renal angiomyolipoma: a retrospective analysis of 61,389 in- and out-patients. Abdom Imaging 2014;39:1009-1013 https://doi.org/10.1007/s00261-014-0129-6
  9. Prasad SR, Humphrey PA, Catena JR, Narra VR, Srigley JR, Cortez AD, et al. Common and uncommon histologic subtypes of renal cell carcinoma: imaging spectrum with pathologic correlation. Radiographics 2006;26:1795-1806; discussion 1806-1810 https://doi.org/10.1148/rg.266065010
  10. Jinzaki M, Tanimoto A, Mukai M, Ikeda E, Kobayashi S, Yuasa Y, et al. Double-phase helical CT of small renal parenchymal neoplasms: correlation with pathologic findings and tumor angiogenesis. J Comput Assist Tomogr 2000;24:835-842 https://doi.org/10.1097/00004728-200011000-00002
  11. Alshumrani G, O'Malley M, Ghai S, Metser U, Kachura J, Finelli A, et al. Small (< or = 4 cm) cortical renal tumors: characterization with multidetector CT. Abdom Imaging 2010;35:488-493 https://doi.org/10.1007/s00261-009-9546-3
  12. Sung CK, Kim SH, Woo S, Moon MH, Kim SY, Kim SH, et al. Angiomyolipoma with minimal fat: differentiation of morphological and enhancement features from renal cell carcinoma at CT imaging. Acta Radiol 2016;57:1114-1122 https://doi.org/10.1177/0284185115618547
  13. Verma SK, Mitchell DG, Yang R, Roth CG, O'Kane P, Verma M, et al. Exophytic renal masses: angular interface with renal parenchyma for distinguishing benign from malignant lesions at MR imaging. Radiology 2010;255:501-507 https://doi.org/10.1148/radiol.09091109
  14. Kim KH, Yun BH, Jung SI, Hwang IS, Hwang EC, Kang TW, et al. Usefulness of the ice-cream cone pattern in computed tomography for prediction of angiomyolipoma in patients with a small renal mass. Korean J Urol 2013;54:504-509 https://doi.org/10.4111/kju.2013.54.8.504
  15. Kim YH, Han K, Oh YT, Jung DC, Cho NH, Park SY. Morphologic analysis with computed tomography may help differentiate fat-poor angiomyolipoma from renal cell carcinoma: a retrospective study with 602 patients. Abdom Radiol (NY) 2018;43:647-654 https://doi.org/10.1007/s00261-017-1244-y
  16. Takashimizu Y, Iiyoshi M. New parameter of roundness R: circularity corrected by aspect ratio. Prog in Earth and Planet 2016;3:2
  17. Choi HJ, Choi HK. Grading of renal cell carcinoma by 3D morphological analysis of cell nuclei. Comput Biol Med 2007;37:1334-1341 https://doi.org/10.1016/j.compbiomed.2006.12.008
  18. Schochlin M, Weissinger SE, Brandes AR, Herrmann M, Moller P, Lennerz JK. A nuclear circularity-based classifier for diagnostic distinction of desmoplastic from spindle cell melanoma in digitized histological images. J Pathol Inform 2014;5:40
  19. Murphy GF, Partin AW, Maygarden SJ, Mohler JL. Nuclear shape analysis for assessment of prognosis in renal cell carcinoma. J Urol 1990;143:1103-1107 https://doi.org/10.1016/S0022-5347(17)40198-4
  20. Nanes BA. Slide set: reproducible image analysis and batch processing with ImageJ. Biotechniques 2015;59:269-278 https://doi.org/10.2144/000114351
  21. Kim MH, Lee J, Cho G, Cho KS, Kim J, Kim JK. MDCT-based scoring system for differentiating angiomyolipoma with minimal fat from renal cell carcinoma. Acta Radiol 2013;54:1201-1209 https://doi.org/10.1177/0284185113491087
  22. Takahashi N, Leng S, Kitajima K, Gomez-Cardona D, Thapa P, Carter RE, et al. Small (< 4 cm) Small (< 4 cm) renal masses: differentiation of angiomyolipoma without visible fat from renal cell carcinoma using unenhanced and contrast-enhanced CT. AJR Am J Roentgenol 2015;205:1194-1202 https://doi.org/10.2214/AJR.14.14183
  23. Park JJ, Kim CK. Small (< 4 cm) renal tumors with predominantly low signal intensity on T2-weighted images: differentiation of minimal-fat angiomyolipoma from renal cell carcinoma. AJR Am J Roentgenol 2017;208:124-130 https://doi.org/10.2214/AJR.16.16102
  24. Dyer R, DiSantis DJ, McClennan BL. Simplified imaging approach for evaluation of the solid renal mass in adults. Radiology 2008;247:331-343 https://doi.org/10.1148/radiol.2472061846
  25. Tan S, Ozcan MF, Tezcan F, Balci S, Karaoglanoglu M, Huddam B, et al. Real-time elastography for distinguishing angiomyolipoma from renal cell carcinoma: preliminary observations. AJR Am J Roentgenol 2013;200:W369-W375 https://doi.org/10.2214/AJR.12.9139