Evidence map›Paper›PMID 40100399›Full record

ArticleEuropean radiology2025

The value of multiparametric functional MRI histogram features in assessing multiple myeloma activity.

Ying Lin, Hongjie Huang, Zebin Xiao, Shufang Shi, Qiang Weng, Zhanhai Tu

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Article in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Ying LinDepartment of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Hongjie HuangDepartment of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Zebin XiaoDepartment of Biomedical Sciences, University of Pennsylvania, Philadelphia, PA, USA.
Shufang ShiDepartment of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Qiang WengDepartment of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Zhanhai TuDepartment of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China. tuzhanhai@163.com.ORCID http://orcid.org/0000-0002-6746-477X

Funding

Natural Science Foundation of Fujian Province 2020J0112
6 · The paper itself

Abstract

objectiveTo investigate the application of histogram features of apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), mean kurtosis (MK), and fat fraction (FF) for assessing multiple myeloma (MM) activity. MATERIALS AND

methodsFrom April 2023 to December 2023, 24 multiple myeloma patients who underwent zonally oblique multi-slice diffusion-weighted imaging (ZOOM-DWI), zonally oblique multi-slice diffusion kurtosis imaging (ZOOM-DKI), and modified Dixon quantification imaging (mDixon-Quant) were enrolled in this retrospective study. Histogram features of ADC, MD, MK, and FF were analyzed. Significant variables were selected for multivariate logistic regression analysis using a backward stepwise selection method. The diagnostic efficacies of individual histogram features and combined models were evaluated by the receiver operating characteristic curve (ROC) and the area under the curve (AUC).

resultsA total of 24 participants were enrolled in this study, 12 males and 12 females, with an age range of 39-73 (57.88 ± 8.55) years. The ADC and MD histogram features did not correlate with the disease status in multiple myeloma, whereas the MK and FF histogram features were significantly associated with the disease status (p < 0.05). MK_InterquartileRange and FF_Median had the highest AUC values in multiple myeloma activity assessment. The differences in diagnostic efficacies between MK_InterquartileRange and FF_Median, MK_InterquartileRange and the MK model, FF_Median and the FF model, the MK model and the FF model were not statistically different (p = 0.70, 0.54, 0.09 and 0.09, respectively).

conclusionHistogram features of MK and FF are valuable in assessing disease activity in multiple myeloma patients. KEY POINTS: Question Accurate assessment of the disease status of multiple myeloma is crucial for enhancing individualized treatment, yet current non-invasive tools remain inadequate. Findings Mean kurtosis (MK) and fat fraction (FF) histogram features are associated with disease activity of multiple myeloma, providing rich and accurate parameters for assessing the disease status. Clinical relevance The MK and FF histogram features facilitate non-invasive assessment of multiple myeloma activity, potentially guiding the development of personalized treatment strategies.

Indexed as

Diffusion Magnetic Resonance ImagingMultiparametric Magnetic Resonance ImagingMultiple MyelomaAdultAgedFemaleHumansMaleMiddle AgedRetrospective StudiesDiffusion kurtosis imagingDiffusion-weighted imagingFat fractionHistogram featuresMultiple myeloma

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.