Research and Development Division, IMG Pharma Biotech, 48160 Derio, Spain.
Department of Pharmacology, Faculty of Medicine and Nursing, University of the Basque Country UPV/EHU, 48940 Leioa, Spain.
Int J Mol Sci. 2023 Feb 7;24(4):3321. doi: 10.3390/ijms24043321.
Neurodegenerative disorders are characterised by progressive neuron loss in specific brain areas. The most common are Alzheimer's disease and Parkinson's disease; in both cases, diagnosis is based on clinical tests with limited capability to discriminate between similar neurodegenerative disorders and detect the early stages of the disease. It is common that by the time a patient is diagnosed with the disease, the level of neurodegeneration is already severe. Thus, it is critical to find new diagnostic methods that allow earlier and more accurate disease detection. This study reviews the methods available for the clinical diagnosis of neurodegenerative diseases and potentially interesting new technologies. Neuroimaging techniques are the most widely used in clinical practice, and new techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) have significantly improved the diagnosis quality. Identifying biomarkers in peripheral samples such as blood or cerebrospinal fluid is a major focus of the current research on neurodegenerative diseases. The discovery of good markers could allow preventive screening to identify early or asymptomatic stages of the neurodegenerative process. These methods, in combination with artificial intelligence, could contribute to the generation of predictive models that will help clinicians in the early diagnosis, stratification, and prognostic assessment of patients, leading to improvements in patient treatment and quality of life.
神经退行性疾病的特征是特定脑区的神经元进行性丧失。最常见的是阿尔茨海默病和帕金森病；在这两种情况下，诊断都是基于临床测试，但这些测试的区分相似神经退行性疾病和检测疾病早期阶段的能力有限。通常情况下，当患者被诊断出患有这种疾病时，神经退化的程度已经很严重了。因此，寻找新的诊断方法以实现更早、更准确的疾病检测至关重要。本研究回顾了神经退行性疾病的临床诊断方法和一些有潜在应用前景的新技术。神经影像学技术是临床实践中应用最广泛的技术，磁共振成像（MRI）和正电子发射断层扫描（PET）等新技术的出现显著提高了诊断质量。在血液或脑脊液等外周样本中识别生物标志物是神经退行性疾病当前研究的重点。发现良好的标志物可以进行预防性筛查，以识别神经退行性过程的早期或无症状阶段。这些方法与人工智能相结合，可以帮助生成预测模型，帮助临床医生对患者进行早期诊断、分层和预后评估，从而改善患者的治疗效果和生活质量。
