METASTRA: CoMputer-aided EffecTive frActure risk STRAtification of patients with vertebral metastases for personalised treatment through robust computational models validated in clinical settings

在欧洲，预后阳性的癌症患者(270万)暴露于继发性肿瘤的高发病率(˜为100万)。30-70%的病例骨转移到脊柱，30%的病例降低了椎体的承载能力并引发骨折。临床医生只有两个选择：要么手术稳定脊柱，要么让患者暴露在高骨折风险之下。这一决定具有高度的主观性，可能会导致不必要的手术，或者导致严重影响生活质量和癌症治疗的骨折。对脊椎转移瘤患者进行分类的标准是基于放射学图像的评分系统，很少考虑局部生物力学。目前的评分系统无法在大约60%的病例中建立手术指征。因此，有一个尚未得到满足的需求，即准确和及时地量化骨折的风险，以改善患者分层并确定最佳的个性化治疗。这个跨学科的项目将开发基于人工智能(AI)和基于生理学(VPH)的生物力学计算模型，以对有高骨折风险的脊柱转移患者进行分层，并确定最佳的个性化手术治疗。在使用临床(2000个回顾病例)和生物力学(120个体外标本)数据进行严格的模型训练之后，新方法将在多中心前瞻性观察研究(200名患者)中进行测试。这些模型将被组合在一个决策支持系统(DSS)中，使临床医生能够成功地对转移患者进行分层。这些模型和决策支持系统的设计将符合监管要求和未来的开发。METASTRA将为转移性患者的分层和管理提出新的指南。METASTRA方法有望将不确定诊断从目前的60%降至20%。这将减少患者的痛苦，并允许每年削减24亿欧元的支出。

Cancer patients (2.7M in Europe) with a positive prognosis are exposed to a high incidence of secondary tumours (˜1M). Bone metastases spread to the spine in 30-70% cases, reducing the load bearing capacity of the vertebrae and triggering fracture in 30% cases. Clinicians have only two options: either operate to stabilise the spine, or leave the patient exposed to a high fracture risk. The decision is highly subjective and can either lead to unnecessary surgery, or a fracture significantly affecting the quality of life and cancer treatment. The standard-of-care to classify patients with vertebral metastasis are scoring systems based on radiographic images, with little consideration of the local biomechanics. Current scoring systems are unable to establish an indication for surgery in around 60% of cases. Thus, there is an unmet need to accurately and timely quantify the risk of fracture to improve patient stratification and identify the best personalised treatment. This interdisciplinary project will develop Artificial Intelligence (AI)- and Physiology-based (VPH) biomechanical computational models to stratify patients with spine metastasis who are at high risk of fracture and to identify the best personalised surgical treatment. After rigorous model training with clinical (2000 retrospective cases) and biomechanical (120 ex vivo specimens) data, the new approach will be tested in a multicentric prospective observational study (200 patients). The models will be combined in a decision support system (DSS) enabling clinicians to successfully stratify metastatic patients. The models and the DSS will be designed so as to be suitable for regulatory requirements and future exploitation. METASTRA will propose new guidelines for the stratification and management of metastatic patients. METASTRA approach is expected to cut the uncertain diagnoses from the current 60% down to 20% of cases. This will reduce patient suffering, and allow cutting expenditure by 2.4B€/year.