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Quantitative iodine content threshold for discrimination of renal cell carcinomas using rapid kV-switching dual-energy CT

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Abstract

Purpose

Determine iodine content threshold discriminating papillary renal cell carcinomas (pRCC) from complex cysts (CCs) using rapid kV-switching dual-energy CT (rsDECT).

Materials and methods

IRB-approved retrospective study of 72 consecutive patients with pathologic diagnosis of renal cell carcinoma, who underwent rsDECT from 2011 to 2015. Controls included consecutive patients with CC during same period. Iodine content of each pRCC (n = 27) was measured on rsDECT workstation for arterial (n = 15) or nephrographic phase (n = 12), and compared to iodine content for clear cell renal cell carcinomas (ccRCC, n = 46) and complex cysts (n = 54). An optimal iodine content threshold was estimated using logistic regressions and Youden’s J based on maximum specificity and sensitivity.

Results

Iodine threshold of 1.28 mg/cc was optimal to discriminate between pRCCs and CCs for nephrographic phase (sens 1.0, spec 0.96, PPV 0.92, and NPV 1.0, AUC 0.997, acc 0.97, p < 0.0001). Iodine threshold of 1.22 mg/cc was the optimal cutoff value to discriminate between pRCCs and CCs in the arterial phase (sens 0.67, spec 0.97, PPV 0.91, NPV 0.85, AUC 0.76, and acc 0.84, p = 0.006). The optimal threshold to discriminate between ccRCCs and pRCCs was 1.85 mg/cc in the arterial phase (sens 0.87, spec 0.92, PPV 0.87, NPV 0.92, p < 0001) and 2.71 mg/cc in the nephrographic phase (sens 1.0, spec 1.0, PPV 1.0, NPV 1.0, p < 0.0001).

Conclusions

Quantitative iodine values on rsDECT discriminate between papillary RCC and complex cysts, and between papillary RCC and clear cell RCC, the former addressing an important clinical challenge particularly when an unenhanced series has not been performed. These rsDECT thresholds differ from values derived from dual-source DECT technology.

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References

  1. Israel GM, Bosniak MA (2005) How I do it: evaluating renal masses. Radiology 236(2):441–450

    Article  PubMed  Google Scholar 

  2. Suh M, et al. (2003) Distinction of renal cell carcinomas from high-attenuation renal cysts at portal venous phase contrast-enhanced CT. Radiology 228(2):330–334

    Article  PubMed  Google Scholar 

  3. Feuerlein S, et al. (2012) Iodine quantification using dual-energy multidetector computed tomography imaging: phantom study assessing the impact of iterative reconstruction schemes and patient habitus on accuracy. Invest Radiol 47(11):656–661

    Article  PubMed  Google Scholar 

  4. Neville AM, et al. (2011) Detection of renal lesion enhancement with dual-energy multidetector CT. Radiology 259(1):173–183

    Article  PubMed  Google Scholar 

  5. Chandarana H, et al. (2011) Iodine quantification with dual-energy CT: phantom study and preliminary experience with renal masses. AJR Am J Roentgenol 196(6):W693–W700

    Article  PubMed  Google Scholar 

  6. Morgan DE (2014) Dual-energy CT of the abdomen. Abdom Imaging 39(1):108–134

    Article  PubMed  Google Scholar 

  7. Marin D, et al. (2014) State of the art: dual-energy CT of the abdomen. Radiology 271(2):327–342

    Article  PubMed  Google Scholar 

  8. Kaza RK, et al. (2011) Distinguishing enhancing from nonenhancing renal lesions with fast kilovoltage-switching dual-energy CT. AJR Am J Roentgenol 197(6):1375–1381

    Article  PubMed  Google Scholar 

  9. Mileto A, et al. (2014) Accuracy of contrast-enhanced dual-energy MDCT for the assessment of iodine uptake in renal lesions. AJR Am J Roentgenol 202(5):W466–W474

    Article  PubMed  Google Scholar 

  10. Ascenti G, et al. (2013) Distinguishing enhancing from nonenhancing renal masses with dual-source dual-energy CT: iodine quantification versus standard enhancement measurements. Eur Radiol 23(8):2288–2295

    Article  PubMed  Google Scholar 

  11. Mileto A, et al. (2015) Virtual monochromatic images from dual-energy multidetector CT: variance in CT numbers from the same lesion between single-source projection-based and dual-source image-based implementations. Radiology 279:269–277

    Article  PubMed  Google Scholar 

  12. Coleman BG, et al. (1984) Hyperdense renal masses: a computed tomographic dilemma. AJR Am J Roentgenol 143(2):291–294

    Article  CAS  PubMed  Google Scholar 

  13. Jonisch AI, et al. (2007) Can high-attenuation renal cysts be differentiated from renal cell carcinoma at unenhanced CT? Radiology 243(2):445–450

    Article  PubMed  Google Scholar 

  14. Birnbaum BA, et al. (2002) Renal cyst pseudoenhancement: evaluation with an anthropomorphic body CT phantom. Radiology 225(1):83–90

    Article  PubMed  Google Scholar 

  15. Silverman SG, et al. (2007) Hyperattenuating renal masses: etiologies, pathogenesis, and imaging evaluation. Radiographics 27(4):1131–1143

    Article  PubMed  Google Scholar 

  16. Ruopp MD, et al. (2008) Youden Index and optimal cut-point estimated from observations affected by a lower limit of detection. Biom J 50(3):419–430

    Article  PubMed  PubMed Central  Google Scholar 

  17. Amin MB, et al. (1997) Papillary (chromophil) renal cell carcinoma: histomorphologic characteristics and evaluation of conventional pathologic prognostic parameters in 62 cases. Am J Surg Pathol 21(6):621–635

    Article  CAS  PubMed  Google Scholar 

  18. Delahunt B, Eble JN (1997) Papillary renal cell carcinoma: a clinicopathologic and immunohistochemical study of 105 tumors. Mod Pathol 10(6):537–544

    CAS  PubMed  Google Scholar 

  19. Silverman SG, et al. (2008) Management of the incidental renal mass. Radiology 249(1):16–31

    Article  PubMed  Google Scholar 

  20. Kim JK, et al. (2002) Differentiation of subtypes of renal cell carcinoma on helical CT scans. AJR Am J Roentgenol 178(6):1499–1506

    Article  PubMed  Google Scholar 

  21. Teloken PE, et al. (2009) Prognostic impact of histological subtype on surgically treated localized renal cell carcinoma. J Urol 182(5):2132–2136

    Article  PubMed  PubMed Central  Google Scholar 

  22. Leibovich BC, et al. (2010) Histological subtype is an independent predictor of outcome for patients with renal cell carcinoma. J Urol 183(4):1309–1315

    Article  PubMed  Google Scholar 

  23. Zhang J, et al. (2007) Solid renal cortical tumors: differentiation with CT. Radiology 244(2):494–504

    Article  PubMed  Google Scholar 

  24. Mileto A, et al. (2014) Iodine quantification to distinguish clear cell from papillary renal cell carcinoma at dual-energy multidetector CT: a multireader diagnostic performance study. Radiology 273(3):813–820

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Radiology, University of Alabama at Birmingham, 619 19th Street South, JTN 357, Birmingham, AL, 35294, USA

    Jessica G. Zarzour, Desmin Milner, Roberto Valentin, Soroush Rais-Bahrami & Desiree E. Morgan

  2. Department of Preventative Medicine, University of Alabama at Birmingham, Birmingham, AL, USA

    Bradford E. Jackson

  3. Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, USA

    Jennifer Gordetsky

  4. Department of Urology, University of Alabama at Birmingham, Birmingham, AL, USA

    Jennifer Gordetsky & Soroush Rais-Bahrami

  5. School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA

    Janelle West

Authors
  1. Jessica G. Zarzour
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  2. Desmin Milner
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  3. Roberto Valentin
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  4. Bradford E. Jackson
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  5. Jennifer Gordetsky
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  7. Soroush Rais-Bahrami
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  8. Desiree E. Morgan
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Corresponding author

Correspondence to Jessica G. Zarzour.

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Funding

No funding was received for this study.

Conflict of interest

Desiree E. Morgan has received research support from GE Healthcare and was a one-time consultant for educational materials for DECT. The other authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Zarzour, J.G., Milner, D., Valentin, R. et al. Quantitative iodine content threshold for discrimination of renal cell carcinomas using rapid kV-switching dual-energy CT. Abdom Radiol 42, 727–734 (2017). https://doi.org/10.1007/s00261-016-0967-5

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  • DOI: https://doi.org/10.1007/s00261-016-0967-5

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