European Radiology

, Volume 27, Issue 7, pp 2969–2977 | Cite as

Improved MDCT monitoring of pelvic myeloma bone disease through the use of a novel longitudinal bone subtraction post-processing algorithm

  • Marius Horger
  • Wolfgang M. Thaiss
  • Hendrik Ditt
  • Katja Weisel
  • Jan Fritz
  • Konstantin Nikolaou
  • Shu Liao
  • Christopher Kloth
Computed Tomography



To evaluate the diagnostic performance of a novel CT post-processing software that generates subtraction maps of baseline and follow-up CT examinations in the course of myeloma bone lesions.

Materials and methods

This study included 61 consecutive myeloma patients who underwent repeated whole-body reduced-dose MDCT at our institution between November 2013 and June 2015. CT subtraction maps classified a progressive disease (PD) vs. stable disease (SD)/remission. Bone subtraction maps (BSMs) only and in combination with 1-mm (BSM+) source images were compared with 5-mm axial/MPR scans.


Haematological response categories at follow-up were: complete remission (n = 9), very good partial remission (n = 2), partial remission (n = 17) and SDh (n = 19) vs. PDh (n = 14). Five-millimetre CT scan yielded PD (n = 14) and SD/remission (n = 47) whereas bone subtraction + 1-mm axial scans (BSM+) reading resulted in PD (n = 18) and SD/remission (n = 43). Sensitivity/ specificity/accuracy for 5-mm/1-mm/BSM(alone)/BSM + in "lesion-by-lesion" reading was 89.4 %/98.9 %/98.3 %/ 99.5 %; 69.1 %/96.9 %/72 %/92.1 % and 83.8 %/98.4 %/92.1 %/98.3 %, respectively. The use of BSM+ resulted in a change of response classification in 9.8 % patients (n = 6) from SD to PD.


BSM reading is more accurate for monitoring myeloma compared to axial scans whereas BSM+ yields similar results with 1-mm reading (gold standard) but by significantly reduced reading time.

Key points

CT evaluation of myeloma bone disease using a longitudinal bone subtraction post-processing algorithm.

Bone subtraction post-processing algorithm is more accurate for assessment of therapy.

Bone subtraction allowed improved and more efficient detection of myeloma bone lesions.

Post-processing tool demonstrating a change in response classification in 9.8 % patients (all showing PD).

Reading time could be substantially shortened as compared to regular CT assessment.


Multiple myeloma Lytic bone lesions Pelvic bones CT imaging Bone subtraction maps 



We thank Claudia Kroll (medical technician) for the best support in carrying out this study.

The scientific guarantor of this publication is Prof. Dr. Marius Horger. The authors of this manuscript declare relationships with the following companies: Two of the authors (H.D. and S.L.) are Siemens AG staff members. One author (H.M.) has contributed conceptually to the development of this post-processing software but has no financial interest to disclose. Jan Fritz received institutional research funds and speaker's honorarium from Siemens Healthcare USA and is a scientific advisor of Siemens Healthcare USA and Alexion Pharmaceuticals, Inc. One of the authors has significant statistical expertise (CK). Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. No study subjects or cohorts have been previously reported.

Methodology: retrospective, diagnostic or prognostic study, performed at one institution.


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Copyright information

© European Society of Radiology 2016

Authors and Affiliations

  • Marius Horger
    • 1
  • Wolfgang M. Thaiss
    • 1
  • Hendrik Ditt
    • 2
  • Katja Weisel
    • 3
  • Jan Fritz
    • 4
  • Konstantin Nikolaou
    • 1
  • Shu Liao
    • 5
  • Christopher Kloth
    • 1
  1. 1.Department of Diagnostic and Interventional RadiologyEberhard-Karls-University TübingenTuebingenGermany
  2. 2.Siemens AG HealthcareSector Imaging and Interventional RadiologyForchheimGermany
  3. 3.Department of Internal Medicine IIEberhard-Karls-University TübingenTübingenGermany
  4. 4.Russell H. Morgan Department of Radiology and Radiological ScienceJohns Hopkins University School of MedcineBaltimoreUSA
  5. 5.Siemens Medical SolutionsMalvernUSA

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