AI4RA: AI-powered visual technology to diagnose rheumatoid arthritis activity

AI4RA项目将使Wan Rusli博士从帝国理工学院借调到Arthronica。借调的目的是利用Rusli博士在生物力学和计算建模方面的技能来评估Arthronica为类风湿性关节炎（RA）患者提供远程监测和确定疾病活动状态的能力。类风湿性关节炎是一种慢性、致残的自身免疫性疾病，在这种疾病中，身体会攻击关节周围的细胞，使关节肿胀、僵硬和疼痛；随着时间的推移，这也会损害软骨和附近的骨骼。国家审计署估计，英国目前约有58万成年人患有这种疾病，每年还会新增2.6万例病例。越来越多的证据表明，12周内的治疗与改善的治疗反应和患者预后有关。一些研究进一步支持了这一点，这些研究表明，通过治疗到目标的方法可以获得最佳临床结果。这要求患者接受至少两个月的随访，以确定他们的疾病是否活跃或治疗是否成功地抑制了疾病活动。评估RA疾病活动性的主要指标是28个关节的疾病活动性评分（DAS-28）。DAS-28是类风湿性关节炎患者就诊时的常规测量指标。它涉及四个领域：临床医生报告的肿胀关节计数，临床医生报告的疼痛关节计数，患者整体症状测量，以及血液测试中的炎症生物标志物。在冠状病毒大流行的时代，很明显，我们需要创新的解决方案，能够远程测量疾病活动，但仍然可靠。生物标志物水平可以获得，因为家庭检测试剂盒是可用的。患者症状严重程度评分很容易获得。关节压痛可通过患者自我评估学习。需要的是一种远程记录关节状态的机制，包括肿胀和活动范围。为了满足这些需求，Arthronica正在与国王学院医院的风湿病学系进行一项横断面诊断准确性研究，以记录和测量肿胀关节的图像。然而，该公司在生物力学建模方面缺乏深入的专业知识。Rusli博士在计算建模和肌肉骨骼生物力学方面拥有丰富的经验，将支持Arthronica研究人员验证类风湿性关节炎生物力学模型，以提高远程评估类风湿性关节炎疾病活动性的技术准备。

The AI4RA project will enable the secondment of Dr Wan Rusli from Imperial College to Arthronica. The objective of the secondment is to employ Dr Rusli's skills in biomechanics and computational modelling to evaluate Arthronica's ability to provide remote monitoring and determine disease activity status for patients with rheumatoid arthritis (RA).RA is a chronic, disabling autoimmune condition in which the body attacks the cells that line the joints, making the joints swollen, stiff and painful; over time this can also damage the cartilage and nearby bone. The National Audit Office estimates that approximately 580,000 adults in England currently have the disease, with a further 26,000 new cases diagnosed each year. There is growing evidence to suggest that treatment within 12 weeks is associated with improved response to treatment and patient outcomes. This is further supported by a number of studies that have shown that the best clinical outcomes are achieved through a treat-to-target approach. This requires that patients receive at least bi-monthly follow-ups in order to determine if their disease is active or the treatment has successfully dampened disease activity.The leading metric to assess disease activity in RA is the Disease Activity Score using 28 joints (DAS-28). The DAS-28 is routinely measured in clinic visits for patients with RA. It involves four domains: a clinician-reported swollen joint count, a clinician-reported tender joint count, a patient global measure of symptoms, and a biomarker of inflammation from a blood test. In the era of the coronavirus pandemic, it is overtly apparent that we need innovative solutions that enable measurement of disease activity remotely, but still reliably. Biomarker levels can be obtained, as home testing kits are available. Patient symptom severity scores are easily captured. Joint tenderness can be learnt through patient self-assessment. What is needed is a mechanism for remotely recording the status of the joints, including swelling and range of motion.To address these needs, Arthronica is engaged in a cross-sectional diagnostic accuracy study with the Rheumatology Department at King's College Hospital to record images of and measure the swollen joints. However, the company is lacking in-depth expertise in biomechanical modelling. Dr Rusli has extensive experience in computational modelling and musculoskeletal biomechanics and will support Arthronica researchers in the validation of the RA biomechanical model to increase the technology readiness for remotely assessing RA disease activity.