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

  • Ali Pourvaziri
  • Anushri Parakh
  • Amirkasra Mojtahed
  • Avinash Kambadakone
  • Dushyant Vasudeo SahaniEmail author
Computed Tomography



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.


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).


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.


Kidney X-ray computed tomography Workflow Neoplasms Radiologist 



Area under the receiver operating characteristic curve


Clear cell renal cell carcinoma


Dual-energy CT


Dual-source dual-energy CT


Iodine concentration


Image quality


Material density iodine


Material density water


Normalized iodine concentration


Multiphasic renal mass protocol with conventional CT


Receiver operating characteristic


Region of interest


Rapid kV-switching dual-energy CT


Subtraction CT


Tuberous sclerosis


True unenhanced


Picture archiving and communication system


Renal cell carcinoma


Stimulated single-energy CT



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.


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

Compliance with ethical standards


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.

Statistics and biometry

Hang Lee, Ph.D. kindly provided the statistical advice for this manuscript. 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.


• Retrospective

• diagnostic study

• performed in one institution


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Copyright information

© European Society of Radiology 2019
corrected publication 2019

Authors and Affiliations

  • Ali Pourvaziri
    • 1
  • Anushri Parakh
    • 1
  • Amirkasra Mojtahed
    • 1
  • Avinash Kambadakone
    • 1
  • Dushyant Vasudeo Sahani
    • 2
    Email author
  1. 1.Department of Radiology, Division of Abdominal Imaging and Intervention, Massachusetts General HospitalHarvard Medical SchoolBostonUSA
  2. 2.Department of RadiologyUniversity of WashingtonSeattleUSA

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