Literature DB >> 33011876

Role of computed tomography texture analysis using dual-energy-based bone marrow imaging for multiple myeloma characterization: comparison with histology and established serologic parameters.

Hans Bösmüller1, Marius Horger2, Christian Philipp Reinert3, Eva Krieg2, Michael Esser2, Konstantin Nikolaou2,4,5.   

Abstract

OBJECTIVE: To identify textural features on dual-energy CT (DECT)-based bone marrow images in myeloma which correlate with serum markers of myeloma activity and the degree of medullary involvement.
METHODS: A total of 110 patients (63.0 ± 11.0 years, 51 female) who underwent unenhanced whole-body DECT between September 2015 and February 2019 were retrospectively included, which was approved by our institutional ethics committee with a waiver of the informed consent requirement. All patients had current hematologic laboratory tests. Using DECT post-processing, non-calcium bone marrow images were reconstructed. The vertebral bodies T10-L5 were segmented for quantification of textural features, which were compared with serologic parameters and myeloma stages by the Mann-Whitney U test. In a subgroup of 56/110 patients with current bone marrow biopsies, textural features were correlated with the degree of bone marrow infiltration.
RESULTS: First-order features were higher in patients with advanced stage of myeloma (p < .02), whereas the 2nd-order "gray-level co-occurrence matrix (GLCM) cluster prominence" was lower (p < .04). In patients with elevated serum-free light chains (SFLC) or kappa/lambda SFLC ratio above 1.56, the "entropy" and 2nd-order GLCM features were lower (p < .03). The degree of bone marrow infiltration correlated with 1st-order features (e.g., "uniformity"; rP = 0.49; p < .0001), whereas "entropy" and 2nd-order GLCM features were negatively correlated (e.g., "difference entropy"; rP = - 0.54; p < .0001).
CONCLUSIONS: CT textural features applied on non-calcium bone marrow images correlate well with myeloma-related serologic parameters and histology showing a more uniform tissue structure and higher attenuation with increasing medullary infiltration and could therefore be used as additional imaging biomarkers for non-invasive assessment of medullary involvement. KEY POINTS: • Texture analysis applied on dual-energy reconstructed non-calcium bone marrow images provides information about marrow structure and attenuation. • Myeloma-related serologic parameters and the degree of myeloma cell infiltration correlate with 1st- and 2nd-order features which could be useful as additional imaging biomarkers for non-invasive assessment of medullary involvement.

Entities:  

Keywords:  Biomarkers; Bone marrow; Image processing, Computer-assisted; Multiple myeloma; Tumor burden

Mesh:

Year:  2020        PMID: 33011876      PMCID: PMC7979667          DOI: 10.1007/s00330-020-07320-8

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  5 in total

Review 1.  [Potential of radiomics and artificial intelligence in myeloma imaging : Development of automatic, comprehensive, objective skeletal analyses from whole-body imaging data].

Authors:  Markus Wennmann; Jacob M Murray
Journal:  Radiologe       Date:  2021-12-10       Impact factor: 0.635

Review 2.  Utility of dual energy computed tomography in the evaluation of infiltrative skeletal lesions and metastasis: a literature review.

Authors:  Martin Toby Tan; Thomas Bernard Lloyd
Journal:  Skeletal Radiol       Date:  2022-03-16       Impact factor: 2.128

3.  MRI-Based Bone Marrow Radiomics Nomogram for Prediction of Overall Survival in Patients With Multiple Myeloma.

Authors:  Yang Li; Yang Liu; Ping Yin; Chuanxi Hao; Chao Sun; Lei Chen; Sicong Wang; Nan Hong
Journal:  Front Oncol       Date:  2021-12-01       Impact factor: 6.244

4.  Correlation between whole skeleton dual energy CT calcium-subtracted attenuation and bone marrow infiltration in multiple myeloma.

Authors:  Renyang Gu; Ashik Amlani; Ulrike Haberland; Dan Hodson; Matthew Streetly; Michela Antonelli; Isabel Dregely; Vicky Goh
Journal:  Eur J Radiol       Date:  2022-02-16       Impact factor: 4.531

5.  Texture Features of Computed Tomography Image under the Artificial Intelligence Algorithm and Its Predictive Value for Colorectal Liver Metastasis.

Authors:  Derong Sun; Jianjiang Dong; Yindong Mu; Fangwei Li
Journal:  Contrast Media Mol Imaging       Date:  2022-07-19       Impact factor: 3.009

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.