分享:
分享到微信朋友圈
X
综述
MRI在多发性骨髓瘤预后预测中的研究进展
李娇 王勤 薛华丹 金征宇

LI J, WANG Q, XUE H D, et al. Application progress of MRI in the prognostic prediction of multiple myeloma[J]. Chin J Magn Reson Imaging, 2023, 14(8): 192-196.引用本文:李娇, 王勤, 薛华丹, 等. MRI在多发性骨髓瘤预后预测中的研究进展[J]. 磁共振成像, 2023, 14(8): 192-196. DOI:10.12015/issn.1674-8034.2023.08.034.


[摘要] 多发性骨髓瘤(multiple myeloma, MM)是常见的血液系统恶性肿瘤,患者结局不一,生存率从几个月到十年以上不等,精确的预后评估与危险分层对于MM的精准个体化治疗至关重要。近年来,MRI作为检测MM骨髓浸润最敏感的成像技术被广泛地运用到MM预后预测的研究中,本文就近年来MRI在MM预后预测方面的研究进行综述,并强调了不同MRI技术在MM预后预测方面的研究价值,为以后的研究以及临床工作提供一些参考。
[Abstract] Multiple myeloma (MM) is a common hematologic malignancy with varying outcomes and survival rates ranging from a few months to more than ten years. Accurate prognosis assessment and risk stratification are essential for the individualized treatment of MM. In recent years, MRI, as the most sensitive imaging technique for detecting bone marrow infiltration in MM, has been widely used in the research of MM prognosis prediction. In this paper, the research value of different MRI techniques in predicting the prognosis of MM is emphasized, and some references are provided for future research and clinical work.
[关键词] 多发性骨髓瘤;预后;磁共振成像;全身弥散加权成像;应用进展
[Keywords] multiple myeloma;prognosis;magnetic resonance imaging;whole body diffusion weighted imaging;application progress

李娇    王勤    薛华丹    金征宇 *  

中国医学科学院 北京协和医学院 北京协和医院 协和转化医学中心放射科,北京 100730

通信作者:金征宇,E-mail:jinzy@pumch.cn

作者贡献声明:金征宇设计本研究的方案,对稿件重要内容进行了修改;李娇起草和撰写稿件,获取、分析或解释本研究的数据,对稿件进行了修改;王勤获取、分析或解释本研究的数据,对稿件重要内容进行了修改,获得了中央高校基本科研业务费专项资金项目;薛华丹获取、分析或解释本研究的数据,对稿件重要内容进行了修改,获得了中国医学科学院基金、北京市科技计划项目、北京市自然科学基金项目资助;全体作者都同意发表最后的修改稿,同意对本研究的所有方面负责,确保本研究的准确性和诚信。


基金项目: 中央高校基本科研业务费专项资金项目 3332021014 中国医学科学院基金 2020-I2M-C&T-B-037 北京市自然科学基金 L222099 北京市科技计划项目 Z211100002921067
收稿日期:2023-03-12
接受日期:2023-06-26
中图分类号:R445.2  R733.3 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2023.08.034
引用本文:李娇, 王勤, 薛华丹, 等. MRI在多发性骨髓瘤预后预测中的研究进展[J]. 磁共振成像, 2023, 14(8): 192-196. DOI:10.12015/issn.1674-8034.2023.08.034.

0 前言

       多发性骨髓瘤(multiple myeloma, MM)是第二常见的血液系统恶性肿瘤,发病率约为(4.5~6)/10万[1]。MM是一组生物学行为和临床表现呈显著异质性的疾病,患者结局不一,生存率从几个月到十年以上不等[2]。影响MM预后的因素包括:宿主相关因素(比如年龄,肥胖、身体健康程度等)、肿瘤相关因素[(Durie-Salmon, DS)分期等反映肿瘤负荷与临床进程的风险分层系统等]、遗传学相关因素(是否存在高危细胞遗传学异常等)、治疗反应深度和微小残留病水平以及是否伴有髓外软组织浸润等[3]

       近年来快速的药理学和技术发展可大大降低MM早期死亡率和提高生存率,显著改善了MM患者的预后。所以早期识别MM患者并进行精确的风险分层与预后评估对于MM的个性化治疗至关重要[1]。现有MM风险分层系统主要包括DS分期系统[4],修订的国际分期系统(revised international staging system, R-ISS)[5]以及Mayo骨髓瘤分层及风险调整治疗分层系统[6]等。这些分期系统将反映疾病负担的血清学因素、遗传学因素等结合起来对MM患者进行分层,以评估其预后[7]。但这些现有标志物存在全身代表性不足,敏感性低等问题,需结合更多更方便、更敏感、更特异的生物学标志物以对患者进行更精准的分层。

       在MM患者中,约80%患有骨溶解性骨病[7],用影像学评估新诊断或复发MM的骨骼受累程度和结构完整性是极其重要的。MRI是检测MM骨髓浸润最敏感的成像技术[8],且无辐射、无需对比剂[9],可早期发现MM(尤其是隐匿性MM,非分泌MM等)骨髓浸润以及髓外浸润情况,从而实现早发现早治疗。MRI可协助MM进行风险分层,从而实现对不同危险程度的患者进行个性化治疗,延缓疾病进展,延长总生存期,减少药物毒性和医疗保健费用[1]

       近年来MRI被越来越广泛地用于MM的研究中,并发现了很多与MM预后相关的影像学指标。但MRI各序列的应用价值尚不明确,临床上如何选择更高性价比的序列尚不清楚,本文就近年来MRI在MM预后预测方面的研究进行综述,并强调了不同MRI技术在MM预后预测方面的研究价值,为以后的研究以及临床工作提供一些参考。

1 目前用于评估MM预后的MRI技术

       MRI具有多种成像序列、多个成像参数,目前多种MRI技术已被用于MM骨髓受累程度的评估。这些技术包括T1加权成像、T2加权及压脂成像、TI加权钆剂增强成像等常规MRI序列,以及动态对比增强MRI(dynamic contrast-enhanced MRI, DCE-MRI)、全身弥散加权成像(whole body diffusion weighted imaging, WB-DWI)、改良的水脂分离成像(modified DIXON, mDIXON)和体素内不相干运动(intravoxel incoherent motion, IVIM)成像等。MM病灶典型表现为T1加权像低信号,T2加权压脂像高信号,钆增强图像上病灶信号常增强[10, 11, 12]。在WB-DWI图像上,MM病灶弥散受限,呈高信号,可通过表观弥散系数(apparent diffusion coefficient, ADC)对水分子弥散进行定量[13]。mDIXON技术可通过脂肪分数(fat fraction, FF)对骨髓脂肪含量进行定量[14]。IVIM技术则可通过慢弥散系数(Dslow)、灌注分数(f)等对骨髓水分子弥散、灌注进行定量[15]

2 不同MRI序列在MM预后中的应用

2.1 常规MRI序列在MM预后中的应用

       常规用于评估MM骨髓浸润的MRI序列有T1加权,T2加权压脂,TI加权压脂钆增强。这些序列可以清楚地显示MM骨髓浸润模式、局灶数目等。MM骨髓浸润模式分为弥漫浸润型、局灶型、弥漫加灶型、椒盐型、正常型5种[16, 17, 18]。骨髓浸润模式与DS分期相关,有研究表明正常型、椒盐型都处于DSⅠ期,大部分弥漫型都位于Ⅲ期,大部分局灶型、弥漫加灶型位于Ⅱ期或Ⅲ期[19]。骨髓浸润模式与ISS分期相关,有研究表明弥漫浸润型患者多位于ISS Ⅲ期[20]。而且有研究者发现弥漫浸润型MRI模式结合高危细胞遗传学和ISS-Ⅲ期可以识别预后极差的MM患者,这些患者早期接受新型药物治疗可以显著改善生存期[21, 22]。弥漫浸润型患者预后较其他浸润型差基本达成共识,但局灶型预后差异较大,有研究发现MRI检出病灶数量越多,骨质破坏程度越高,超出皮质骨边界的局灶性病变显著影响生存率[23]。MRI上局部浸润灶的存在是无症状MM进展为有症状MM的不良预后因素[24, 25]。在有症状MM中,MRI局灶数目7个以上的患者预后较差,而小于等于7个局灶的患者生存率相似[26]。常规MRI序列除了可以显示MM浸润模式、局灶数目外,还可以对骨髓浸润程度进行半定量。有研究者安排两名放射科专家通过肉眼观察MRI图像对MM骨髓浸润程度进行半定量评估,发现骨髓浸润程度大于10%的患者死亡风险显著高于浸润程度小于10%的患者[27]。此外,近年来随着多学科交叉的兴起,常规MRI图像还可用于放射组学特征的提取以及模型构建,从而预测预后。有研究表明基于T1加权、T2加权压脂双序列的MRI放射组学特征可以较好地区分MM中的高危细胞遗传学患者和非高危细胞遗传学患者[28, 29]。而包含了放射组学特征、临床风险因素的综合模型比单独的放射组学特征模型、临床模型在预测MM总生存期的能力上要更好[30]。综上,常规MRI序列上多个局灶病变的存在以及弥漫型浸润是MM患者预后不良的因素。常规MRI的优势是,可以简单方便地直接显示骨髓浸润的类型,不足是尚无法客观定量,对于弥漫浸润型患者,当骨髓浆细胞增多低于10%时可能与MRI假阴性相关[31]。未来常规MRI序列的研究可以往病灶定量、放射组学方面发展。

2.2 DCE-MRI在MM预后中的应用

       DCE-MRI通过注射对比剂进行增强可以提高成像敏感度。并且通过对感兴趣椎体的连续动态成像[18],可以获得信号强度-时间曲线,对信号变化进行客观定量分析。有研究将随访发生骨折与随访未发生骨折的患者基线DCE-MRI信号进行对比,发现基线时DCE-MRI信号强度的最大增加是一种能够预测MM患者腰椎椎体骨折的预后标记物[32]。DCE-MRI信号强度的最大增加反映了骨髓血管生成增加并与MM骨髓浸润程度相关,在阴燃型MM患者中,如果DCE-MRI信号强度的最大增加大于0.89,那么80%的患者将在2年内发展成有症状的MM[33];在进展性或复发性MM患者中,DCE-MRI信号强度的最大增加与较短的无事件生存期相关[34]。此外,DCE-MRI信号强度的最大增加与MM患者骨髓的微血管密度高度相关,信号强度的最大增加较高的患者髓外疾病的发生率明显高于信号强度的最大增加较低的患者[35]。DCE-MRI信号强度的最大增加也是影响MM患者总生存率的独立不良危险因素[36]。DCE-MRI相比于活检测定微血管密度的优势在于,DCE-MRI可无创反映血管生成,且覆盖范围更大,考虑了浆细胞在骨髓中不是均匀分布的事实[37]。而相较于传统MRI,DCE-MRI敏感度更高,对椎体微血管密度实现了量化,可以预测骨折与髓外疾病的发生。DCE-MRI的不足在于,获取时间长、解剖覆盖范围依然有限[38]、需要使用对比剂,而基于钆的对比剂与肾源性系统性纤维化的风险相关[39]。考虑到这些,我们认为有条件的话更推荐探索WB-DWI、IVIM等无需对比剂的骨髓定量序列影像标记物与预后的关系。

2.3 WB-DWI在MM预后中的应用

       WB-DWI是目前为止检测MM骨髓病变最敏感的序列[40],在软组织中也有很高的敏感度[41]。对于常规MRI中微小的或难以发现的病变,WB-DWI增加了病变的显著性并可能比其他检查检测到更多的病变[42]。WB-DWI是一种测量体内水弥散的功能性技术,肿瘤因为细胞密度较高,其水的弥散受到更多的限制[43]。脾脏是腹部水弥散受限最高的器官[44],WB-DWI上脾脏信号丢失被认为与MM肿瘤高负荷以及极差的预后相关[45]。就骨髓浸润而言,有研究表明,骨髓浸润正常型MM患者平均ADC值与健康对照组无显著差别,弥漫浸润型以及局灶型平均ADC值高于正常型[14]。L3~S1以及一侧髂骨作为代表性浸润骨髓的平均ADC值是无进展生存期和总生存的独立危险因素[46]。WB-DWI上总的弥散体积反映了肿瘤体积,总的弥散体积较高与患者较差的预后相关[47]。ADC图的直方图分析是一种很有前途的定量工具,可以通过感知肿瘤的异质性来预测疾病高风险。具有代表性的背景骨髓平均ADC值以及ADC熵可以将R-ISS Ⅲ期患者与R-ISSⅠ/Ⅱ期患者区分开来,R-ISSⅢ期患者平均ADC以及ADC熵值高于R-ISSⅠ/Ⅱ期患者[48]。WB-DWI是比较推荐的用于MM预后预测的序列,其优势在于,与常规MRI序列相比,WB-DWI更敏感,且可通过ADC值来定量;与DCE-MRI相比,无需对比剂、更便捷、解剖覆盖范围更广[49]。WB-DWI在MM预后中的应用尚不够多,且大部分只涉及有代表性的骨髓。有研究表明,在弥漫性浸润患者中单层ADC值测量的观察者间一致性较差[50],但使用全切片分割技术进行弥漫性浸润患者ADC测量时,观察者间一致性有所改善。未来的WB-DWI相关研究可以考虑纳入全身病灶,结合直方图分析等工具,探索其与总生存期、无进展生存期等直接预后指标的关系。

2.4 其他MRI技术在MM预后中的应用

       近年来,随着MRI技术的发展,越来越多的新技术应用到MM的预后预测中来。这些新技术包括mDIXON、IVIM等。研究发现,在ISS Ⅰ期、Ⅱ期、Ⅲ期患者中,Dslow逐渐增加,FF逐渐降低,但联合IVIM与mDIXON技术,通过logistic回归分析发现FF是FF、Dslow、Dfast、f等参数中预测MM晚期的唯一显著因子[51]。有研究表明DS、R-ISS Ⅰ/Ⅱ期的患者FF值高于Ⅲ期的患者[52]。但也有研究表明R-ISS Ⅲ期患者的FF值明显低于R-ISS Ⅱ期,而R-ISS Ⅰ期与Ⅲ期、Ⅰ期与Ⅱ期之间的FF值的差异无统计学意义,ISS各期的FF值无显著差异[53]。mDIXON、IVIM等新技术在MM的预后预测研究尚不多,研究结果也存在争议,未来需要更多大样本量、多中心的研究来明确IVIM、mDIXON等新技术的应用价值。不同MRI技术联合在MM预后预测中的作用研究也较少,未来有条件的中心可以做更多这方面的探索。

       总的来说,MRI在MM预后预测中的应用越来越普遍,涉及的序列也越来越多,不同的序列在预后预测中都表现出一定的价值,但研究普遍样本量较小,缺少预后模型,缺少影像指标与临床指标的结合,缺少不同MRI技术的联合应用,更多的研究使用了ISS分期等间接预后指标,缺少纵向随访生存期等直接预后指标的研究。

3 总结与展望

       MRI技术在MM预后预测中的角色一直在丰富,从之前的主要依赖常规T1、T2来定性到如今的用WB-DWI、mDIXON、IVIM等各种技术来定量,MRI在MM预后预测、风险分层方面发挥着越来越重要的作用。每种技术体现了疾病不同的方面,可以互为补充。未来的研究可以考虑多种MRI技术的联合应用以及各种MRI技术影像标记物的比较,探索出临床应用价值较高的技术组合。此外,影响MM预后的因素很多,未来的研究可以结合宿主相关因素、基于MRI影像标记物的肿瘤相关因素以及遗传相关因素等构建综合模型,为MM患者实现更细致的风险分层,提供更精准的预后预测。

[1]
VAN DE DONK N W C J, PAWLYN C, YONG K L. Multiple myeloma[J]. Lancet, 2021, 397(10272): 410-427. DOI: 10.1016/s0140-6736(21)00135-5.
[2]
MARCON C, SIMEON V, DEIAS P, et al. Experts' consensus on the definition and management of high risk multiple myeloma[J/OL]. Front Oncol, 2022, 12: 1096852 [2023-05-17]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9899889. DOI: 10.3389/fonc.2022.1096852.
[3]
马柯娃, 孙超, 李建勇, 等. 多发性骨髓瘤预后因素的研究进展[J]. 中国实验血液学杂志, 2021, 29(4): 1346-1350. DOI: 10.19746/j.cnki.issn1009-2137.2021.04.053.
MA K W, SUN C, LI J Y, et al. Research progress on prognostic factors of multiple myeloma—review[J]. J Exp Hematol, 2021, 29(4): 1346-1350. DOI: 10.19746/j.cnki.issn1009-2137.2021.04.053.
[4]
DURIE B G M, SALMON S E. A clinical staging system for multiple myeloma correlation of measured myeloma cell mass with presenting clinical features, response to treatment, and survival[J]. Cancer, 1975, 36(3): 842-854. DOI: 10.1002/1097-0142(197509)36:3<842:aid-cncr2820360303>3.0.co;2-u.
[5]
PALUMBO A, AVET-LOISEAU H, OLIVA S, et al. Revised international staging system for multiple myeloma: a report from international myeloma working group[J]. J Clin Oncol, 2015, 33(26): 2863-2869. DOI: 10.1200/JCO.2015.61.2267.
[6]
RAJKUMAR S V. Multiple myeloma: 2022 update on diagnosis, risk stratification, and management[J]. Am J Hematol, 2022, 97(8): 1086-1107. DOI: 10.1002/ajh.26590.
[7]
COWAN A J, GREEN D J, KWOK M, et al. Diagnosis and management of multiple myeloma: a review[J]. JAMA, 2022, 327(5): 464-477. DOI: 10.1001/jama.2022.0003.
[8]
HILLENGASS J, USMANI S, RAJKUMAR S V, et al. International myeloma working group consensus recommendations on imaging in monoclonal plasma cell disorders[J/OL]. Lancet Oncol, 2019, 20(6): e302-e312 [2022-11-18]. https://www.sciencedirect.com/science/article/pii/S1470204519303092?via%3Dihub. DOI: 10.1016/S1470-2045(19)30309-2.
[9]
HEIDEMEIER A, SCHLOETELBURG W, THURNER A, et al. Multi-parametric whole-body MRI evaluation discerns vital from non-vital multiple myeloma lesions as validated by 18F-FDG and 11C-methionine PET/CT[J/OL]. Eur J Radiol, 2022, 155: 110493 [2023-05-21]. https://www.sciencedirect.com/science/article/pii/S0720048X22003436?via%3Dihub. DOI: 10.1016/j.ejrad.2022.110493.
[10]
LIBSHITZ H I, MALTHOUSE S R, CUNNINGHAM D, et al. Multiple myeloma: appearance at MR imaging[J]. Radiology, 1992, 182(3): 833-837. DOI: 10.1148/radiology.182.3.1535904.
[11]
WEININGER M, LAUTERBACH B, KNOP S, et al. Whole-body MRI of multiple myeloma: comparison of different MRI sequences in assessment of different growth patterns[J]. Eur J Radiol, 2009, 69(2): 339-345. DOI: 10.1016/j.ejrad.2007.10.025.
[12]
SUN M T, CHENG J L, REN C P, et al. Differentiation of diffuse infiltration pattern in multiple myeloma from hyperplastic hematopoietic bone marrow: qualitative and quantitative analysis using whole-body MRI[J]. J Magn Reson Imaging, 2022, 55(4): 1213-1225. DOI: 10.1002/jmri.27934.
[13]
JI X D, HUANG W Y, DONG H Z, et al. Evaluation of bone marrow infiltration in multiple myeloma using whole-body diffusion-weighted imaging and T1-weighted water-fat separation Dixon[J]. Quant Imaging Med Surg, 2021, 11(2): 641-651. DOI: 10.21037/qims-20-289.
[14]
BERARDO S, SUKHOVEI L, ANDORNO S, et al. Quantitative bone marrow magnetic resonance imaging through apparent diffusion coefficient and fat fraction in multiple myeloma patients[J]. Radiol Med, 2021, 126(3): 445-452. DOI: 10.1007/s11547-020-01258-z.
[15]
TORKIAN P, AZADBAKHT J, ANDREA BONAFFINI P, et al. Advanced imaging in multiple myeloma: new frontiers for MRI[J/OL]. Diagnostics (Basel), 2022, 12(9): 2182 [2023-03-14] . https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497462. DOI: 10.3390/diagnostics12092182.
[16]
MOULOPOULOS L A, VARMA D G, DIMOPOULOS M A, et al. Multiple myeloma: spinal MR imaging in patients with untreated newly diagnosed disease[J]. Radiology, 1992, 185(3): 833-840. DOI: 10.1148/radiology.185.3.1438772.
[17]
VANDE BERG B C, KIRCHGESNER T, ACID S, et al. Diffuse vertebral marrow changes at MRI: multiple myeloma or normal?[J]. Skeletal Radiol, 2022, 51(1): 89-99. DOI: 10.1007/s00256-021-03886-6.
[18]
VAN DEN BERGHE T, VERSTRAETE K L, LECOUVET F E, et al. Review of diffusion-weighted imaging and dynamic contrast-enhanced MRI for multiple myeloma and its precursors (monoclonal gammopathy of undetermined significance and smouldering myeloma)[J]. Skeletal Radiol, 2022, 51(1): 101-122. DOI: 10.1007/s00256-021-03903-8.
[19]
STÄBLER A, BAUR A, BARTL R, et al. Contrast enhancement and quantitative signal analysis in MR imaging of multiple myeloma: assessment of focal and diffuse growth patterns in marrow correlated with biopsies and survival rates[J]. AJR Am J Roentgenol, 1996, 167(4): 1029-1036. DOI: 10.2214/ajr.167.4.8819407.
[20]
SONG M K, CHUNG J S, LEE J J, et al. Magnetic resonance imaging pattern of bone marrow involvement as a new predictive parameter of disease progression in newly diagnosed patients with multiple myeloma eligible for autologous stem cell transplantation[J]. Br J Haematol, 2014, 165(6): 777-785. DOI: 10.1111/bjh.12820.
[21]
MOULOPOULOS L A, DIMOPOULOS M A, KASTRITIS E, et al. Diffuse pattern of bone marrow involvement on magnetic resonance imaging is associated with high risk cytogenetics and poor outcome in newly diagnosed, symptomatic patients with multiple myeloma: a single center experience on 228 patients[J]. Am J Hematol, 2012, 87(9): 861-864. DOI: 10.1002/ajh.23258.
[22]
SONG M K, CHUNG J S, LEE J J, et al. Risk stratification model in elderly patients with multiple myeloma: clinical role of magnetic resonance imaging combined with international staging system and cytogenetic abnormalities[J]. Acta Haematol, 2015, 134(1): 7-16. DOI: 10.1159/000370235.
[23]
MAI E K, HIELSCHER T, KLOTH J K, et al. Association between magnetic resonance imaging patterns and baseline disease features in multiple myeloma: analyzing surrogates of tumour mass and biology[J]. Eur Radiol, 2016, 26(11): 3939-3948. DOI: 10.1007/s00330-015-4195-0.
[24]
HILLENGASS J, FECHTNER K, WEBER M A, et al. Prognostic significance of focal lesions in whole-body magnetic resonance imaging in patients with asymptomatic multiple myeloma[J]. J Clin Oncol, 2010, 28(9): 1606-1610. DOI: 10.1200/JCO.2009.25.5356.
[25]
KASTRITIS E, MOULOPOULOS L A, TERPOS E, et al. The prognostic importance of the presence of more than one focal lesion in spine MRI of patients with asymptomatic (smoldering) multiple myeloma[J]. Leukemia, 2014, 28(12): 2402-2403. DOI: 10.1038/leu.2014.230.
[26]
WALKER R, BARLOGIE B, HAESSLER J, et al. Magnetic resonance imaging in multiple myeloma: diagnostic and clinical implications[J]. J Clin Oncol, 2007, 25(9): 1121-1128. DOI: 10.1200/jco.2006.08.5803.
[27]
AILAWADHI S, ABDELHALIM A N, DERBY L, et al. Extent of disease burden determined with magnetic resonance imaging of the bone marrow is predictive of survival outcome in patients with multiple myeloma[J]. Cancer, 2010, 116(1): 84-92. DOI: 10.1002/cncr.24704.
[28]
LIU J F, ZENG P E, GUO W, et al. Prediction of high-risk cytogenetic status in multiple myeloma based on magnetic resonance imaging: utility of radiomics and comparison of machine learning methods[J]. J Magn Reson Imaging, 2021, 54(4): 1303-1311. DOI: 10.1002/jmri.27637.
[29]
LIU J F, WANG C J, GUO W, et al. A preliminary study using spinal MRI-based radiomics to predict high-risk cytogenetic abnormalities in multiple myeloma[J]. Radiol Med, 2021, 126(9): 1226-1235. DOI: 10.1007/s11547-021-01388-y.
[30]
LI Y, LIU Y, YIN P, et al. MRI-based bone marrow radiomics nomogram for prediction of overall survival in patients with multiple myeloma[J/OL]. Front Oncol, 2021, 11: 709813 [2023-03-16]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8671997. DOI: 10.3389/fonc.2021.709813.
[31]
MOULOPOULOS L A, GIKA D, ANAGNOSTOPOULOS A, et al. Prognostic significance of magnetic resonance imaging of bone marrow in previously untreated patients with multiple myeloma[J]. Ann Oncol, 2005, 16(11): 1824-1828. DOI: 10.1093/annonc/mdi362.
[32]
SCHERER A, WITTSACK H J, STRUPP C, et al. Vertebral fractures in multiple myeloma: first results of assessment of fracture risk using dynamic contrast-enhanced magnetic resonance imaging[J]. Ann Hematol, 2002, 81(9): 517-521. DOI: 10.1007/s00277-002-0532-x.
[33]
HILLENGASS J, RITSCH J, MERZ M, et al. Increased microcirculation detected by dynamic contrast-enhanced magnetic resonance imaging is of prognostic significance in asymptomatic myeloma[J]. Br J Haematol, 2016, 174(1): 127-135. DOI: 10.1111/bjh.14038.
[34]
HILLENGASS J, WASSER K, DELORME S, et al. Lumbar bone marrow microcirculation measurements from dynamic contrast-enhanced magnetic resonance imaging is a predictor of event-free survival in progressive multiple myeloma[J]. Clin Cancer Res, 2007, 13(2Pt 1): 475-481. DOI: 10.1158/1078-0432.CCR-06-0061.
[35]
HUANG S Y, CHEN B B, LU H Y, et al. Correlation among DCE-MRI measurements of bone marrow angiogenesis, microvessel density, and extramedullary disease in patients with multiple myeloma[J]. Am J Hematol, 2012, 87(8): 837-839. DOI: 10.1002/ajh.23256.
[36]
MERZ M, MOEHLER T M, RITSCH J, et al. Prognostic significance of increased bone marrow microcirculation in newly diagnosed multiple myeloma: results of a prospective DCE-MRI study[J]. Eur Radiol, 2016, 26(5): 1404-1411. DOI: 10.1007/s00330-015-3928-4.
[37]
ANDRULIS M, BÄUERLE T, GOLDSCHMIDT H, et al. Infiltration patterns in monoclonal plasma cell disorders: correlation of magnetic resonance imaging with matched bone marrow histology[J]. Eur J Radiol, 2014, 83(6): 970-974. DOI: 10.1016/j.ejrad.2014.03.005.
[38]
WU F B, BERNARD S, FAYAD L M, et al. Updates and ongoing challenges in imaging of multiple myeloma: AJR expert panel narrative review[J]. Am J Roentgenol, 2021, 217(4): 775-785. DOI: 10.2214/ajr.21.25878.
[39]
BRIOLI A, MORGAN G J, DURIE B, et al. The utility of newer imaging techniques as predictors of clinical outcomes in multiple myeloma[J]. Expert Rev Hematol, 2014, 7(1): 13-16. DOI: 10.1586/17474086.2014.873347.
[40]
HAMEED M, SANDHU A, SONEJI N, et al. Pictorial review of whole body MRI in myeloma: emphasis on diffusion-weighted imaging[J/OL]. Br J Radiol, 2020, 93(1115): 20200312 [2023-05-17]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519646. DOI: 10.1259/bjr.20200312.
[41]
GUIRGUIS M, SHARAN G, WANG J, et al. Diffusion-weighted MR imaging of musculoskeletal tissues: incremental role over conventional MR imaging in bone, soft tissue, and nerve lesions[J/OL]. BJR Open, 2022, 4(1): 20210077 [2023-05-17]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667480. DOI: 10.1259/bjro.20210077.
[42]
MESGUICH C, HULIN C, LATRABE V, et al. Prospective comparison of 18-FDG PET/CT and whole-body diffusion-weighted MRI in the assessment of multiple myeloma[J]. Ann Hematol, 2020, 99(12): 2869-2880. DOI: 10.1007/s00277-020-04265-2.
[43]
SUROV A, MEYER H J, WIENKE A. Correlation between minimum apparent diffusion coefficient (ADCmin) and tumor cellularity: a meta-analysis[J]. Anticancer Res, 2017, 37(7): 3807-3810. DOI: 10.21873/anticanres.11758.
[44]
MORANI A C, ELSAYES K M, LIU P S, et al. Abdominal applications of diffusion-weighted magnetic resonance imaging: where do we stand[J]. World J Radiol, 2013, 5(3): 68-80. DOI: 10.4329/wjr.v5.i3.68.
[45]
RASCHE L, KUMAR M, GERSHNER G, et al. Lack of Spleen Signal on Diffusion Weighted MRI is associated with High Tumor Burden and Poor Prognosis in Multiple Myeloma: a Link to Extramedullary Hematopoiesis?[J]. Theranostics, 2019, 9(16): 4756-4763. DOI: 10.7150/thno.33289.
[46]
ZHANG L, WANG Q, WU X, et al. Baseline bone marrow ADC value of diffusion-weighted MRI: a potential independent predictor for progression and death in patients with newly diagnosed multiple myeloma[J]. Eur Radiol, 2021, 31(4): 1843-1852. DOI: 10.1007/s00330-020-07295-6.
[47]
TERAO T, MACHIDA Y, NARITA K, et al. Total diffusion volume in MRI vs. total lesion glycolysis in PET/CT for tumor volume evaluation of multiple myeloma[J]. Eur Radiol, 2021, 31(8): 6136-6144. DOI: 10.1007/s00330-021-07687-2.
[48]
WANG Q, ZHANG L, LI S, et al. Histogram analysis based on apparent diffusion coefficient maps of bone marrow in multiple myeloma: an independent predictor for high-risk patients classified by the revised international staging system[J/OL]. Acad Radiol, 2022, 29(6): e98-e107 [2022-12-21]. https://www.sciencedirect.com/science/article/pii/S1076633221003184?via%3Dihub. DOI: 10.1016/j.acra.2021.07.010.
[49]
PAWLYN C, FOWKES L, OTERO S, et al. Whole-body diffusion-weighted MRI: a new gold standard for assessing disease burden in patients with multiple myeloma?[J]. Leukemia, 2016, 30(6): 1446-1448. DOI: 10.1038/leu.2015.338.
[50]
ELGENDY K, BARWICK T D, AUNER H W, et al. Repeatability and test-retest reproducibility of mean apparent diffusion coefficient measurements of focal and diffuse disease in relapsed multiple myeloma at 3T whole body diffusion-weighted MRI (WB-DW-MRI)[J/OL]. Br J Radiol, 2022, 95(1138): 20220418 [2022-12-21]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815750. DOI: 10.1259/bjr.20220418.
[51]
JO A, JUNG J Y, LEE S Y, et al. Prognosis prediction in initially diagnosed multiple myeloma patients using intravoxel incoherent motion-diffusion weighted imaging and multiecho Dixon imaging[J]. J Magn Reson Imaging, 2021, 53(2): 491-501. DOI: 10.1002/jmri.27321.
[52]
SUN M T, CHENG J L, REN C P, et al. Quantitative whole-body MR imaging for assessment of tumor burden in patients with multiple myeloma: correlation with prognostic biomarkers[J]. Quant Imaging Med Surg, 2021, 11(8): 3767-3780. DOI: 10.21037/qims-20-1361.
[53]
古雅雯, 吴颖, 颜瑞馨, 等. 磁共振成像水脂分离技术在多发性骨髓瘤患者中的应用研究[J]. 中国实验血液学杂志, 2022, 30(1): 183-188. DOI: 10.19746/j.cnki.issn1009-2137.2022.01.030.
GU Y W, WU Y, YAN R X, et al. Application of MRI water-fat separation technology in patients with multiple myeloma[J]. J Exp Hematol, 2022, 30(1): 183-188. DOI: 10.19746/j.cnki.issn1009-2137.2022.01.030.

上一篇 MRI影像组学在早期宫颈癌不良病理因素评估的研究进展
下一篇 超顺磁性氧化铁纳米粒子在肿瘤诊断及治疗方面的应用
  
诚聘英才 | 广告合作 | 免责声明 | 版权声明
联系电话:010-67113815
京ICP备19028836号-2