Lin Ying, Huang Hongjie, Xiao Zebin, Shi Shufang, Weng Qiang, Tu Zhanhai
Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Eur Radiol. 2025 Mar 18. doi: 10.1007/s00330-025-11507-2.
To 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.
From 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).
A 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).
Histogram features of MK and FF are valuable in assessing disease activity in multiple myeloma patients.
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.
探讨表观扩散系数（ADC）、平均扩散系数（MD）、平均峰度（MK）和脂肪分数（FF）的直方图特征在评估多发性骨髓瘤（MM）活动中的应用。
2023年4月至2023年12月，本回顾性研究纳入了24例接受区域斜向多层扩散加权成像（ZOOM-DWI）、区域斜向多层扩散峰度成像（ZOOM-DKI）和改良Dixon定量成像（mDixon-Quant）的多发性骨髓瘤患者。分析了ADC、MD、MK和FF的直方图特征。采用向后逐步选择法选择显著变量进行多因素逻辑回归分析。通过受试者工作特征曲线（ROC）和曲线下面积（AUC）评估单个直方图特征和联合模型的诊断效能。
本研究共纳入24名参与者，男性12名，女性12名，年龄范围为39-73岁（57.88±8.55岁）。ADC和MD直方图特征与多发性骨髓瘤的疾病状态无关，而MK和FF直方图特征与疾病状态显著相关（p<0.05）。MK_四分位间距和FF_中位数在多发性骨髓瘤活动评估中具有最高的AUC值。MK_四分位间距与FF_中位数、MK_四分位间距与MK模型、FF_中位数与FF模型、MK模型与FF模型之间的诊断效能差异无统计学意义（p分别为0.70、0.54、0.09和0.09）。
MK和FF的直方图特征在评估多发性骨髓瘤患者的疾病活动中具有重要价值。
问题准确评估多发性骨髓瘤的疾病状态对于加强个体化治疗至关重要，但目前的非侵入性工具仍不充分。发现平均峰度（MK）和脂肪分数（FF）直方图特征与多发性骨髓瘤的疾病活动相关，为评估疾病状态提供了丰富而准确的参数。临床意义MK和FF直方图特征有助于对多发性骨髓瘤活动进行非侵入性评估，可能指导个性化治疗策略的制定。
