Literature DB >> 24706394

Appearance of monoclonal plasma cell diseases in whole-body magnetic resonance imaging and correlation with parameters of disease activity.

Jost K Kloth1, Jens Hillengass, Karin Listl, Kerstin Kilk, Thomas Hielscher, Ola Landgren, Stefan Delorme, Hartmut Goldschmidt, Hans-Ulrich Kauczor, Marc-André Weber.   

Abstract

The aim of our study was to assess in which way different infiltration patterns of monoclonal plasma cell diseases in whole-body (wb) magnetic resonance imaging (MRI) are associated with clinical stages, plasma cell content in bone marrow samples and established serum markers of disease activity. Institutional review board approval was obtained. We performed wb-MRI in 547 consecutive, unselected and untreated patients with monoclonal gammopathy of undetermined significance (MGUS, n=138), smoldering myeloma (SMM, n=157) and multiple myeloma (MM, n=252) on two 1.5 T MRI-scanners with body array coils. The studies were evaluated in consensus by two experienced radiologists blinded to the diagnosis. We observed focal lesions in 23.9% (MGUS), 34.4% (SMM) and 81.3% (MM), respectively. A diffuse infiltration pattern was detected in 38.4%, 45.9% and 71%, respectively. The differences between all infiltration patterns were significant (p<0.0001). The presence of focal lesions and the presence of a diffuse bone marrow infiltration was associated with an increased plasma cell percentage in bone marrow samples (median 22% vs. 14%, 26% vs. 10%, both p<0.0001) and monoclonal protein concentration (median 18 g/dl vs. 13 g/dl, p=0.003, 20 g/dl vs. 11 g/dl, p<0.0001). Further categorization of the diffuse infiltration patterns in wb-MRI into "salt-and-pepper," moderate and severe identified significant associations with M-protein (median g/dl for S+P/moderate/severe 23/18/25, p=0.04), plasma cell percentage in the bone marrow (median 25%/24%/40%, p=0.02), and age (median years 67/60/57, p<0.0001). Bone marrow infiltration in wb-MRI is significantly different between the various stages of plasma cell disease and correlates well with established markers of disease activity.
© 2014 UICC.

Entities:  

Keywords:  correlation analysis; disease activity; magnetic resonance imaging; monoclonal plasma cell disease; multiple myeloma

Mesh:

Substances:

Year:  2014        PMID: 24706394     DOI: 10.1002/ijc.28877

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  6 in total

1.  Application of diffusion-weighted whole-body MRI for response monitoring in multiple myeloma after chemotherapy: a systematic review and meta-analysis.

Authors:  Kaiwen Wang; Elsa Lee; Shedrack Kenis; Simon Hallam; Athar Haroon; Simon Wan; Neil Rabin; Antonio Rojas-Garcia; Anwar Padhani; Sola Adeleke
Journal:  Eur Radiol       Date:  2022-01-14       Impact factor: 7.034

Review 2.  Imaging in myeloma with focus on advanced imaging techniques.

Authors:  Tara Barwick; Laure Bretsztajn; Kathryn Wallitt; Dimitri Amiras; Andrea Rockall; Christina Messiou
Journal:  Br J Radiol       Date:  2019-01-03       Impact factor: 3.039

3.  [Focal lesions in whole-body MRI in multiple myeloma : Quantification of tumor mass and correlation with disease-related parameters and prognosis].

Authors:  S C Brandelik; J Krzykalla; T Hielscher; J Hillengass; J K Kloth; H U Kauczor; M A Weber
Journal:  Radiologe       Date:  2018-01       Impact factor: 0.635

4.  Association between magnetic resonance imaging patterns and baseline disease features in multiple myeloma: analyzing surrogates of tumour mass and biology.

Authors:  Elias K Mai; Thomas Hielscher; Jost K Kloth; Maximilian Merz; Sofia Shah; Michaela Hillengass; Barbara Wagner; Dirk Hose; M S Raab; Anna Jauch; Stefan Delorme; Hartmut Goldschmidt; Marc-André Weber; Jens Hillengass
Journal:  Eur Radiol       Date:  2016-01-15       Impact factor: 5.315

5.  Quantitative whole-body MR imaging for assessment of tumor burden in patients with multiple myeloma: correlation with prognostic biomarkers.

Authors:  Mengtian Sun; Jingliang Cheng; Cuiping Ren; Yong Zhang; Yinhua Li; Ying Li; Suping Zhang
Journal:  Quant Imaging Med Surg       Date:  2021-08

6.  Volumetry based biomarker speed of growth: Quantifying the change of total tumor volume in whole-body magnetic resonance imaging over time improves risk stratification of smoldering multiple myeloma patients.

Authors:  Markus Wennmann; Laurent Kintzelé; Marie Piraud; Bjoern H Menze; Thomas Hielscher; Johannes Hofmanninger; Barbara Wagner; Hans-Ulrich Kauczor; Maximilian Merz; Jens Hillengass; Georg Langs; Marc-André Weber
Journal:  Oncotarget       Date:  2018-05-18
  6 in total

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