Department of Health Sciences (DISSAL), University of Genoa, 16129 Genoa, Italy.
IRCCS Ospedale Policlinico San Martino, 16129 Genoa, Italy.
Medicina (Kaunas). 2021 Jan 21;57(2):94. doi: 10.3390/medicina57020094.
Multiple Myeloma (MM) is the second most common type of hematological disease and, although it is rare among patients under 40 years of age, its incidence rises in elderly subjects. MM manifestations are usually identified through hyperCalcemia, Renal failure, Anaemia, and lytic Bone lesions (CRAB). In particular, the extent of the bone disease is negatively related to a decreased quality of life in patients and, in general, bone disease in MM increases both morbidity and mortality. The detection of lytic bone lesions on imaging, especially computerized tomography (CT) and Magnetic Resonance Imaging (MRI), is becoming crucial from the clinical viewpoint to separate asymptomatic from symptomatic MM patients and the detection of focal lytic lesions in these imaging data is becoming relevant even when no clinical symptoms are present. Therefore, radiology is pivotal in the staging and accurate management of patients with MM even in early phases of the disease. In this review, we describe the opportunities offered by quantitative imaging and radiomics in multiple myeloma. At the present time there is still high variability in the choice between various imaging methods to study MM patients and high variability in image interpretation with suboptimal agreement among readers even in tertiary centers. Therefore, the potential of medical imaging for patients affected by MM is still to be completely unveiled. In the coming years, new insights to study MM with medical imaging will derive from artificial intelligence (AI) and radiomics usage in different bone lesions and from the wide implementations of quantitative methods to report CT and MRI. Eventually, medical imaging data can be integrated with the patient's outcomes with the purpose of finding radiological biomarkers for predicting the prognostic flow and therapeutic response of the disease.
多发性骨髓瘤(MM)是第二大常见的血液系统疾病,虽然在 40 岁以下患者中较为罕见,但在老年患者中发病率上升。MM 的表现通常通过高钙血症、肾功能衰竭、贫血和溶骨性骨病变(CRAB)来识别。特别是,骨病的严重程度与患者生活质量的降低呈负相关,而且一般来说,多发性骨髓瘤的骨病会增加发病率和死亡率。在影像学上,特别是计算机断层扫描(CT)和磁共振成像(MRI)上检测到溶骨性骨病变,从临床角度来看对于区分无症状和有症状的 MM 患者变得至关重要,而且即使没有临床症状,这些影像学数据中局灶性溶骨性病变的检测也变得相关。因此,放射学在 MM 患者的分期和准确治疗中至关重要,即使在疾病的早期阶段也是如此。在这篇综述中,我们描述了定量成像和放射组学在多发性骨髓瘤中的应用机会。目前,在选择各种成像方法来研究 MM 患者时仍然存在很大的变异性,即使在三级中心,图像解释也存在很大的变异性,并且读者之间的一致性也不理想。因此,医学影像学在 MM 患者中的应用潜力仍有待完全揭示。在未来几年,人工智能(AI)和放射组学在不同骨病变中的应用以及定量方法的广泛实施将为研究 MM 提供新的见解,这些方法可以报告 CT 和 MRI。最终,可以将医学影像学数据与患者的结果进行整合,以寻找预测疾病预后和治疗反应的放射学生物标志物。