Skip to main content

Advertisement

SpringerLink
Log in

Diagnostic performance of single-phase dual-energy CT to differentiate vascular and nonvascular incidental renal lesions on portal venous phase: comparison with CT

  • Urogenital
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To determine whether single-phase dual-energy CT (DECT) differentiates vascular and nonvascular renal lesions in the portal venous phase (PVP). Optimal iodine threshold was determined and compared to Hounsfield unit (HU) measurements.

Methods

We retrospectively included 250 patients (266 renal lesions) who underwent a clinically indicated PVP abdominopelvic CT on a rapid-kilovoltage-switching single-source DECT (rsDECT) or a dual-source DECT (dsDECT) scanner. Iodine concentration and HU measurements were calculated by four experienced readers. Diagnostic accuracy was determined using biopsy results and follow-up imaging as reference standard. Area under the curve (AUC) was calculated for each DECT scanner to differentiate vascular from nonvascular lesions and vascular lesions from hemorrhagic/proteinaceous cysts. Univariable and multivariable logistic regression analyses evaluated the association between variables and the presence of vascular lesions.

Results

A normalized iodine concentration threshold of 0.25 mg/mL yielded high accuracy in differentiating vascular and nonvascular lesions (AUC 0.93, p < 0.001), with comparable performance to HU measurements (AUC 0.93). Both iodine concentration and HU measurements were independently associated with vascular lesions when adjusted for age, gender, body mass index, and lesion size (AUC 0.95 and 0.95, respectively). When combined, diagnostic performance was higher (AUC 0.96). Both absolute and normalized iodine concentrations performed better than HU measurements (AUC 0.92 vs. AUC 0.87) in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

Conclusion

A single-phase (PVP) DECT scan yields high accuracy to differentiate vascular from nonvascular renal lesions. Iodine concentration showed a slightly higher performance than HU measurements in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

Key Points

• A single-phase dual-energy CT scan in the portal venous phase differentiates vascular from nonvascular renal lesions with high accuracy (AUC 0.93).

• When combined, iodine concentration and HU measurements showed the highest diagnostic performance (AUC 0.96) to differentiate vascular from nonvascular renal lesions.

• Compared to HU measurements, iodine concentration showed a slightly higher performance in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

BMI:

Body mass index

CT:

Computed tomography

DECT:

Dual-energy CT

dsDECT:

Dual-source DECT scanner

HU:

Hounsfield unit

keV:

Kiloelectron volt

kVp:

Kilovoltage peak

PACS:

Picture archive and communication system

PVP:

Portal venous phase

ROC:

Receiver operating curves

ROI:

Region of interest

rsDECT:

Rapid-kilovoltage-switching single-source DECT

VIF:

Variance inflation factor

VUE:

Virtual unenhanced images

References

  1. Patel BN, Alexander L, Allen B et al (2017) Dual-energy CT workflow: multi-institutional consensus on standardization of abdominopelvic MDCT protocols. Abdom Radiol (NY) 42:676–687

    Article  Google Scholar 

  2. Marin D, Boll DT, Mileto A, Nelson RC (2014) State of the art: dual-energy CT of the abdomen. Radiology 271:327–342

    Article  Google Scholar 

  3. McCollough CH, Leng S, Yu L, Fletcher JG (2015) Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology 276:637–653

    Article  Google Scholar 

  4. Patel BN, Thomas JV, Lockhart ME, Berland LL, Morgan DE (2013) Single-source dual-energy spectral multidetector CT of pancreatic adenocarcinoma: optimization of energy level viewing significantly increases lesion contrast. Clin Radiol 68:148–154

    Article  CAS  Google Scholar 

  5. Murray N, Darras KE, Walstra FE, Mohammed MF, McLaughlin PD, Nicolaou S (2019) Dual-energy ct in evaluation of the acute abdomen. Radiographics 39:264–286

    Article  Google Scholar 

  6. Marcon J, Graser A, Horst D et al (2020) Papillary vs clear cell renal cell carcinoma. Differentiation and grading by iodine concentration using DECT-correlation with microvascular density. Eur Radiol 30:1–10

    Article  CAS  Google Scholar 

  7. Pourvaziri A, Parakh A, Mojtahed A, Kambadakone A, Sahani DV (2019) Diagnostic performance of dual-energy CT and subtraction CT for renal lesion detection and characterization. Eur Radiol 29:6559–6570

    Article  Google Scholar 

  8. Patel BN, Vernuccio F, Meyer M et al (2019) Dual-energy CT material density iodine quantification for distinguishing vascular from nonvascular renal lesions: normalization reduces intermanufacturer threshold variability. AJR Am J Roentgenol 212:366–376

    Article  Google Scholar 

  9. Meyer M, Nelson RC, Vernuccio F et al (2019) Comparison of iodine quantification and conventional attenuation measurements for differentiating small, truly enhancing renal masses from high-attenuation nonenhancing renal lesions with dual-energy CT. AJR Am J Roentgenol. https://doi.org/10.2214/AJR.18.20547:W1-W11

  10. Zarzour JG, Milner D, Valentin R et al (2017) Quantitative iodine content threshold for discrimination of renal cell carcinomas using rapid kV-switching dual-energy CT. Abdom Radiol (NY) 42:727–734

    Article  Google Scholar 

  11. Marin D, Davis D, Roy Choudhury K et al (2017) Characterization of small focal renal lesions: diagnostic accuracy with single-phase contrast-enhanced dual-energy ct with material attenuation analysis compared with conventional attenuation measurements. Radiology 284:737–747

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  14. Kaza RK, Caoili EM, Cohan RH, Platt JF (2011) Distinguishing enhancing from nonenhancing renal lesions with fast kilovoltage-switching dual-energy CT. AJR Am J Roentgenol 197:1375–1381

    Article  Google Scholar 

  15. Graser A, Becker CR, Staehler M et al (2010) Single-phase dual-energy CT allows for characterization of renal masses as benign or malignant. Investig Radiol 45:399–405

    Article  Google Scholar 

  16. Graser A, Johnson TR, Hecht EM et al (2009) Dual-energy CT in patients suspected of having renal masses: can virtual nonenhanced images replace true nonenhanced images? Radiology 252:433–440

    Article  Google Scholar 

  17. Patel BN, Boltyenkov AT, Martinez MG et al (2020) Cost-effectiveness of dual-energy CT versus multiphasic single-energy CT and MRI for characterization of incidental indeterminate renal lesions. Abdom Radiol (NY) 45:1896–1906

    Article  Google Scholar 

  18. Salameh JP, McInnes MDF, McGrath TA, Salameh G, Schieda N (2019) Diagnostic accuracy of dual-energy CT for evaluation of renal masses: systematic review and meta-analysis. AJR Am J Roentgenol 212:W100–W105

    Article  Google Scholar 

  19. Bellini D, Panvini N, Laghi A et al (2019) Systematic review and meta-analysis investigating the diagnostic yield of dual-energy CT for renal mass assessment. AJR Am J Roentgenol. https://doi.org/10.2214/AJR.18.20625:1-10

  20. Obmann MM, Cosentino A, Cyriac J et al (2020) Quantitative enhancement thresholds and machine learning algorithms for the evaluation of renal lesions using single-phase split-filter dual-energy CT. Abdom Radiol (NY) 45:1922–1928

    Article  Google Scholar 

  21. Sica GT (2006) Bias in research studies. Radiology 238:780–789

    Article  Google Scholar 

  22. Patel BN, Farjat A, Schabel C et al (2018) Energy-specific optimization of attenuation thresholds for low-energy virtual monoenergetic images in renal lesion evaluation. AJR Am J Roentgenol 210:W205–W217

    Article  Google Scholar 

  23. Krauss B, Grant KL, Schmidt BT, Flohr TG (2015) The importance of spectral separation: an assessment of dual-energy spectral separation for quantitative ability and dose efficiency. Investig Radiol 50:114–118

    Article  Google Scholar 

  24. Li X, Meng X, Ye Z (2016) Iodine quantification to characterize primary lesions, metastatic and non-metastatic lymph nodes in lung cancers by dual energy computed tomography: An initial experience. Eur J Radiol 85:1219–1223

    Article  Google Scholar 

  25. Liang P, Ren XC, Gao JB, Chen KS, Xu X (2017) Iodine concentration in spectral CT: assessment of prognostic determinants in patients with gastric adenocarcinoma. AJR Am J Roentgenol 209:1033–1038

    Article  Google Scholar 

  26. Silverman SG, Israel GM, Trinh QD (2015) Incompletely characterized incidental renal masses: emerging data support conservative management. Radiology 275:28–42

    Article  Google Scholar 

  27. Silverman SG, Pedrosa I, Ellis JH et al (2019) Bosniak Classification of cystic renal masses, Version 2019: an update proposal and needs assessment. Radiology 292:475–488

    Article  Google Scholar 

  28. Corwin MT, Altinmakas E, Asch D et al (2020) Clinical importance of incidental homogeneous renal masses 10-40 mm and 21-39 Hounsfield Units at portal venous-phase CT: A 12-institution retrospective cohort study. AJR Am J Roentgenol. https://doi.org/10.2214/AJR.20.24245

  29. Hu EM, Ellis JH, Silverman SG, Cohan RH, Caoili EM, Davenport MS (2018) Expanding the definition of a benign renal cyst on contrast-enhanced CT: can incidental homogeneous renal masses measuring 21-39 HU be safely ignored? Acad Radiol 25:209–212

    Article  Google Scholar 

  30. Silverman SG, Israel GM, Herts BR, Richie JP (2008) Management of the incidental renal mass. Radiology 249:16–31

    Article  Google Scholar 

  31. Corwin MT, Hansra SS, Loehfelm TW, Lamba R, Fananapazir G (2018) Prevalence of solid tumors in incidentally detected homogeneous renal masses measuring > 20 HU on portal venous phase CT. AJR Am J Roentgenol 211:W173–W177

    Article  Google Scholar 

  32. Silverman SG, Gan YU, Mortele KJ, Tuncali K, Cibas ES (2006) Renal masses in the adult patient: the role of percutaneous biopsy. Radiology 240:6–22

    Article  Google Scholar 

  33. Lin YM, Chiou YY, Wu MH, Huang SS, Shen SH (2018) Attenuation values of renal parenchyma in virtual noncontrast images acquired from multiphase renal dual-energy CT: Comparison with standard noncontrast CT. Eur J Radiol 101:103–110

    Article  Google Scholar 

Download references

Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

  1. Department of Radiology, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA, 94305, USA

    Domenico Mastrodicasa, Martin J. Willemink, Nikhil Madhuripan, Ranjit Singh Chima & Amanzo A. Ho

  2. Department of Radiology, University of Colorado, 12401 East 17th Avenue, Aurora, CO, 80045, USA

    Nikhil Madhuripan

  3. Department of Radiology, Duke University Medical Center, 2301 Erwin Rd, Durham, NC, 27710, USA

    Yuqin Ding & Daniele Marin

  4. Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai Institute of Medical Imaging, Shanghai, 200032, People’s Republic of China

    Yuqin Ding

  5. Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ, 85259, USA

    Bhavik N Patel

Authors
  1. Domenico Mastrodicasa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Martin J. Willemink
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nikhil Madhuripan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ranjit Singh Chima
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Amanzo A. Ho
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yuqin Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Daniele Marin
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Bhavik N Patel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bhavik N Patel.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Bhavik Patel, MD, MBA.

Conflict of interest

The authors of this manuscript declare relationships with the following companies:

DoMa activities related to the present article: none. Activities not related to the present article: research grant from the National Institute of Biomedical Imaging and Bioengineering (5T32EB009035). Shareholder of Segmed, Inc. Consultant for Segmed, Inc. Other relationships: no relevant relationships.

MW activities related to the present article: none. Activities not related to the present article: research grants from American Heart Association (18POST34030192), Philips Healthcare, and Stanford University, consulting for Arterys, Inc, and co-founder/shareholder of Segmed, Inc. Other relationships: no relevant relationships.

BP has research support from General Electric through an institutional grant outside of the submitted work.

The other authors have no conflict of interest to disclose.

Statistics and biometry

One of the authors has significant statistical expertise.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• Retrospective

• Experimental

• Performed at one institution

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Table 6

– Univariable and multivariable logistic regression models evaluating the associations between variables and the presence of vascular lesions compared to non-vascular lesions. Table 7 – Univariable and multivariable logistic regression models evaluating the associations between variables and the presence of vascular lesions compared to hemorrhagic/proteinaceous cysts. (DOCX 29 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mastrodicasa, D., Willemink, M.J., Madhuripan, N. et al. Diagnostic performance of single-phase dual-energy CT to differentiate vascular and nonvascular incidental renal lesions on portal venous phase: comparison with CT. Eur Radiol 31, 9600–9611 (2021). https://doi.org/10.1007/s00330-021-08097-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-021-08097-0

Keywords

Search

Navigation