Accuracy of iodine density thresholds for the separation of vertebral bone metastases from healthy-appearing trabecular bone in spectral detector computed tomography

  • Jan BorggrefeEmail author
  • Victor-Frederic Neuhaus
  • Markus Le Blanc
  • Nils Grosse Hokamp
  • Volker Maus
  • Anastasios Mpotsaris
  • Simon Lennartz
  • Daniel Pinto dos Santos
  • David Maintz
  • Nuran Abdullayev



To evaluate quantitative iodine density mapping (IDM) with spectral detector computed tomography (SDCT) as a quantitative biomarker for separation of vertebral trabecular bone metastases (BM) from healthy-appearing trabecular bone (HTB).

Materials and methods

IRB-approved retrospective single-center-study of portal venous SDCT datasets acquired between June 2016 and March 2017. Inclusion of 43 consecutive cancer patients with BM and 40 without. Target lesions and non-affected control vertebrae were defined using follow-up imaging, MRI, and/or bone scintigraphy. ID and standard deviation were determined with ROI measures by two readers in (a) bone metastases, (b) HTB of BM patients and controls, and (c) ID of various vessels. Volumetric bone mineral density (vBMD) of the lumbar spine and age were recorded. Multivariate ROC analyses und Wilcoxon test were used to determine thresholds for separation of BM and HTB. p < 0.05 was considered significant.


ID measurements of 40 target lesions and 83 reference measurements of HTB were acquired. Age (p < 0.0001) and vBMD (p < 0.05) affected ID measurements independently in multivariate models. There were significant differences of ID between metastases (n = 43) and HTB ID (n = 124; mean 5.5 ± 0.9 vs. 3.5 ± 0.9; p < 0.0001), however, with considerable overlap. In univariate analysis, increased ID discriminated bone lesions (AUC 0.90) with a maximum combined specificity/sensitivity of 77.5%/90.7% when applying a threshold of 4.5 mg/ml. Multivariate regression models improved significantly when considering vBMD, the noise of ID, and vertebral venous ID (AUC 0.98).


IDM of SDCT yielded a statistical separation of vertebral bone lesions and HTB. Adjustment for confounders such as age and lumbar vBMD as well as for vertebral venous ID and lesion heterogeneity improved discrimination of trabecular lesions.

Key Points

• SDCT iodine density mapping provides the possibility for quantitative analysis of iodine uptake in tissue, which allows to differentiate bone lesions from healthy bone marrow.

• Age and vBMD have a significant impact on iodine density measurements.

• Iodine density measured in SDCT yielded highest sensitivity and specificity for the statistical differentiation of vertebral trabecular metastases and healthy trabecular bone using an iodine density threshold of 4.5 mg/ml (most performant)–5.0 mg/ml (optimized for specificity).


Bone Tomography Iodine Diagnosis Neoplasm metastasis 



Computed tomography


Bone mineral density


Bone metastases


Healthy trabecular bone


Iodine density


Iodine density mapping


Spectral detector computed tomography


Union for International Cancer Control


World Health Organization



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

Compliance with ethical standards


The scientific guarantor of this publication is Jan Borggrefe.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: D.M. and J.B. received honorarium from Philips for scientific lectures. The authors have no conflicts of interest.

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.


• Retrospective

• Cross sectional study

• Performed at one institution

Supplementary material

330_2018_5843_MOESM1_ESM.docx (111 kb)
ESM 1 (DOCX 110 kb)


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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  • Jan Borggrefe
    • 1
    Email author
  • Victor-Frederic Neuhaus
    • 1
  • Markus Le Blanc
    • 1
  • Nils Grosse Hokamp
    • 1
  • Volker Maus
    • 1
  • Anastasios Mpotsaris
    • 1
  • Simon Lennartz
    • 1
  • Daniel Pinto dos Santos
    • 1
  • David Maintz
    • 1
  • Nuran Abdullayev
    • 1
  1. 1.Institut für Diagnostische und Interventionelle RadiologieUniklinik KölnKölnGermany

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