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Diagnostic performance of dual-energy CT and subtraction CT for renal lesion detection and characterization

  • Computed Tomography
  • Published:
European Radiology Aims and scope Submit manuscript

A Correction to this article was published on 11 July 2019

This article has been updated

Abstract

Purpose

To compare the effect of dual-energy CT (DECT) material density datasets on diagnostic performance, readers’ confidence, and interpretation time for renal lesion detection and characterization in comparison to subtraction CT (SCT).

Material and methods

One hundred fourteen patients (69/45 = M/F, mean age = 67 years) who underwent contrast-enhanced DECT between January 2015 and February 2018 for suspected renal mass were included retrospectively. For each patient, three radiologists assessed three image datasets: group A, material density iodine (MDI) + material density water (MDW); group B, SCT only; and group C, SCT + true unenhanced phase + virtual monochromatic images at 65 keV. Readers evaluated image quality (4-point scale), the number of lesions, and likely diagnosis. Reading times were recorded. Quantitatively, iodine concentration (IC from MDI) and delta Hounsfield units (ΔHU) for all lesions were measured. Diagnostic accuracy was compared using the area under the receiver operating characteristic curve (AUC). Image quality and interpretation time were compared with Kruskal-Wallis and t tests.

Results

Study cohort (230 lesions; mean size = 23.63 mm (5–116 mm)) consisted of 60 enhancing, 158 non-enhancing, and 12 lipid-dominant angiomyolipoma lesions. Significantly higher image quality was demonstrated for MDI compared to SCT (mean score = 3.82 vs. 3; p < 0.05). Comparable diagnostic accuracy was observed for group A (AUC = 0.88) and group C (AUC = 0.87) and was higher compared to that for group B (AUC = 0.75). Group A was read faster than group C (41.49 s vs. 71.45 s per exam; p < 0.05). Both IC and ΔHU values had high accuracy (AUC = 0.97) for differentiating enhancing vs. non-enhancing lesions; however, IC enabled differentiation of clear cell renal cell carcinoma from other enhancing lesions with moderate accuracy (AUC = 0.73).

Conclusion

MDI images increase readers’ confidence for renal lesion detection and characterization while providing a more efficient radiologist workflow, irrespective of readers’ experience.

Key Points

• Material density iodine (MDI) images enable faster interpretation due to high image quality and potentially reduced need for quantitation.

• MDI images increase diagnostic confidence of readers, irrespective of radiologists’ experience.

• High accuracy with dual-energy CT (DECT) can potentially reduce healthcare costs by eliminating the need for additional investigations.

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Change history

  • 11 July 2019

    The original version of this article, published on 27 May 2019, unfortunately contained a mistake. The following correction has therefore been made in the original.

Abbreviations

AUC:

Area under the receiver operating characteristic curve

cRCC:

Clear cell renal cell carcinoma

DECT:

Dual-energy CT

dsDECT:

Dual-source dual-energy CT

IC:

Iodine concentration

IQ:

Image quality

MDI:

Material density iodine

MDW:

Material density water

NIC:

Normalized iodine concentration

R-CT:

Multiphasic renal mass protocol with conventional CT

ROC:

Receiver operating characteristic

ROI:

Region of interest

rsDECT:

Rapid kV-switching dual-energy CT

SCT:

Subtraction CT

TS:

Tuberous sclerosis

TUE:

True unenhanced

PACS:

Picture archiving and communication system

RCC:

Renal cell carcinoma

SECT:

Stimulated single-energy CT

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Acknowledgements

This work was conducted with support from the Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, National Institutes of Health Award UL 1TR002541) and financial contributions from Harvard University and its affiliated academic healthcare centers. The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University, and its affiliated academic healthcare centers, or the National Institutes of Health.

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Authors and Affiliations

  1. Department of Radiology, Division of Abdominal Imaging and Intervention, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, White 270, Boston, MA, 02114, USA

    Ali Pourvaziri, Anushri Parakh, Amirkasra Mojtahed & Avinash Kambadakone

  2. Department of Radiology, University of Washington, Box 357115, Seattle, WA, 98195-7115, USA

    Dushyant Vasudeo Sahani

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Correspondence to Dushyant Vasudeo Sahani.

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The scientific guarantor of this publication is Dushyant Vasudeo Sahani.

Conflict of interest

Dushyant Vasudeo Sahani, MD has the following disclosures which are not relevant to this work: research grant support from GE, Philips, and Bayer Healthcare; royalties (Elsevier); and being a consultant of Allena Pharmaceuticals, GE Healthcare. Other authors have no relevant disclosure. The data was handled by an investigator with no conflict of interest.

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Hang Lee, Ph.D. kindly provided the statistical advice for this manuscript. One of the authors has significant statistical expertise.

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The original version of this article was revised: The names of Avinash Kambadakone and Dushyant Vasudeo Sahani were presented incorrectly.

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Pourvaziri, A., Parakh, A., Mojtahed, A. et al. Diagnostic performance of dual-energy CT and subtraction CT for renal lesion detection and characterization. Eur Radiol 29, 6559–6570 (2019). https://doi.org/10.1007/s00330-019-06224-6

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