Department of Magnetic Resonance, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Department of Hematology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
J Magn Reson Imaging. 2024 Jun;59(6):2035-2045. doi: 10.1002/jmri.28962. Epub 2023 Sep 7.
Accurate identification of high-risk multiple myeloma (HRMM) is important for prognostication. The degree of diffuse infiltration patterns on magnetic resonance imaging (MRI) is associated with patient prognosis in multiple myeloma. However, objective indexes to determine the degree of diffuse infiltration patterns are unavailable.
To investigate whether qualitative and quantitative evaluations of diffuse infiltration patterns on MRI could identify HRMM.
Retrospective.
Totally, 180 patients (79 HRMM and 101 standard-risk MM) were assessed. The presence of del(17p), t(4;14), t(14;16), t(14;20), gain 1q, and/or p53 mutations was considered to indicate HRMM.
FIELD STRENGTH/SEQUENCE: 3.0 T/diffusion-weighted whole-body imaging with background body signal suppression (DWIBS), modified Dixon chemical-shift imaging Quant (mDIXON Quant), and short TI inversion recovery (STIR).
Qualitative analysis involved assessing the degree of diffuse marrow infiltration (mild, moderate, or severe), and quantitative analysis involved evaluating apparent diffusion coefficient (ADC), fat fraction (FF), and T2* values. Clinical data such as sex, age, hemoglobin, serum albumin, serum calcium, serum creatinine, serum lactate dehydrogenase, β2-microglobulin, and bone marrow plasma cells (BMPCs) were also included.
Univariate and multivariate analyses, receiver operating characteristic (ROC) curve. P < 0.05 was considered statistically significant.
The high-risk group had significantly higher ADC and T2* and lower FF compared with the standard-risk group. Multivariate analysis indicated BMPCs as a significant independent risk factor for HRMM (odds ratio (OR) = 1.019, 95% CI 1.004-1.033), while FF was a significant independent protective factor associated with HRMM (OR = 0.972, 95% CI 0.946-0.999). The combination of BMPCs and FF achieved the highest areas under the curve (AUC) of 0.732, with sensitivity and specificity of 70.9% and 68.3%, respectively.
Compared with qualitative analysis, FF value was independently associated with HRMM. The quantitative features of diffuse marrow infiltration on MRI scans are more effective in detecting HRMM.
3 TECHNICAL EFFICACY: Stage 2.
准确识别高危多发性骨髓瘤（HRMM）对于预后判断很重要。磁共振成像（MRI）上弥漫浸润模式的程度与多发性骨髓瘤患者的预后相关。然而，目前还没有确定弥漫浸润模式程度的客观指标。
探讨 MRI 上弥漫浸润模式的定性和定量评估是否可用于识别 HRMM。
回顾性。
共评估了 180 名患者（79 名 HRMM 和 101 名标准风险 MM）。存在 del（17p）、t（4；14）、t（14；16）、t（14；20）、1q 增益和/或 p53 突变被认为是 HRMM。
磁场强度/序列：3.0T/全身弥散加权成像（DWIBS）、改良的狄克逊化学位移成像定量（mDIXON Quant）和短 TI 反转恢复（STIR）。
定性分析包括评估弥漫性骨髓浸润程度（轻度、中度或重度），定量分析包括评估表观扩散系数（ADC）、脂肪分数（FF）和 T2* 值。还包括临床数据，如性别、年龄、血红蛋白、血清白蛋白、血清钙、血清肌酐、血清乳酸脱氢酶、β2-微球蛋白和骨髓浆细胞（BMPCs）。
单变量和多变量分析，受试者工作特征（ROC）曲线。P＜0.05 被认为具有统计学意义。
高危组的 ADC 和 T2* 值显著高于标准风险组，FF 值显著低于标准风险组。多变量分析表明，BMPCs 是 HRMM 的显著独立危险因素（比值比（OR）=1.019，95%置信区间 1.004-1.033），而 FF 是与 HRMM 相关的显著独立保护因素（OR=0.972，95%置信区间 0.946-0.999）。BMPCs 和 FF 的联合应用获得了最高的曲线下面积（AUC）为 0.732，灵敏度和特异性分别为 70.9%和 68.3%。
与定性分析相比，FF 值与 HRMM 独立相关。MRI 扫描弥漫性骨髓浸润的定量特征在检测 HRMM 方面更有效。
3 级技术疗效：2 级。
