早期膀胱肿瘤诊断的现有方法在很大程度上取决于侵入性和耗时的程序。导致住院,出血,膀胱穿孔,患者的感染和其他健康风险。减少当前的风险因素,在保持甚至提高诊断精度的同时,是临床仪器研究的潜在因素。例如,对于有非浸润性膀胱肿瘤病史的患者的临床监测,实时肿瘤诊断可以在门诊使用柔性膀胱镜立即进行激光切除肿瘤.因此,需要新的诊断方式,可以提供实时体内肿瘤诊断。拉曼光谱提供了离体和体内组织样品的生化信息,而无需复杂的样品制备和染色程序。在过去的十年中,在不同器官中诊断和表征早期癌症的应用有所增加。例如头部和颈部,结肠和胃,但也有不同的病理,例如,炎症和动脉粥样硬化斑块。膀胱病理学也得到了研究,但很少关注可能影响诊断的方面,如组织异质性,数据预处理和模型开发。本研究提出了一项关于膀胱活检的临床调查研究,以表征离体肿瘤分级,使用紧凑的基于光纤探针的成像拉曼系统,作为迈向体内拉曼内窥镜的关键一步。此外,这项研究提出了高荧光膀胱组织的组织异质性的评估,以及用于区分非肿瘤组织的多变量统计分析,和低级和高级肿瘤。
Existing approaches for early-stage bladder tumor diagnosis largely depend on invasive and time-consuming procedures, resulting in hospitalization, bleeding, bladder perforation, infection and other health risks for the patient. The reduction of current risk factors, while maintaining or even improving the diagnostic precision, is an underlying factor in clinical instrumentation research. For example, for clinic surveillance of patients with a history of noninvasive bladder tumors real-time tumor diagnosis can enable immediate laser-based removal of tumors using flexible cystoscopes in the outpatient clinic. Therefore, novel diagnostic modalities are required that can provide real-time in vivo tumor diagnosis. Raman spectroscopy provides biochemical information of tissue samples ex vivo and in vivo and without the need for complicated sample preparation and staining procedures. For the past decade there has been a rise in applications to diagnose and characterize early cancer in different organs, such as in head and neck, colon and stomach, but also different pathologies, for example, inflammation and atherosclerotic plaques. Bladder pathology has also been studied but only with little attention to aspects that can influence the diagnosis, such as tissue heterogeneity, data preprocessing and model development. The present study presents a clinical investigative study on bladder biopsies to characterize the tumor grading ex vivo, using a compact fiber probe-based imaging Raman system, as a crucial step towards in vivo Raman endoscopy. Furthermore, this study presents an evaluation of the tissue heterogeneity of highly fluorescent bladder tissues, and the multivariate statistical analysis for discrimination between nontumor tissue, and low- and high-grade tumor.