Regge Daniele, Mazzetti Simone, Giannini Valentina, Bracco Christian, Stasi Michele
Department of Surgical Sciences, University of Torino, A.O.U. Città della Salute e della Scienza, via Genova 3, 10126, Turin, Italy.
Department of Radiology, Candiolo Cancer Institute-FPO, IRCCS, Strada Provinciale 142, km 3.95, Candiolo, 10060, Turin, Italy.
Radiol Med. 2017 Jun;122(6):458-463. doi: 10.1007/s11547-016-0687-5. Epub 2016 Sep 13.
Cancer is a complex disease and unfortunately understanding how the components of the cancer system work does not help understand the behavior of the system as a whole. In the words of the Greek philosopher Aristotle "the whole is greater than the sum of parts." To date, thanks to improved information technology infrastructures, it is possible to store data from each single cancer patient, including clinical data, medical images, laboratory tests, and pathological and genomic information. Indeed, medical archive storage constitutes approximately one-third of total global storage demand and a large part of the data are in the form of medical images. The opportunity is now to draw insight on the whole to the benefit of each individual patient. In the oncologic patient, big data analysis is at the beginning but several useful applications can be envisaged including development of imaging biomarkers to predict disease outcome, assessing the risk of X-ray dose exposure or of renal damage following the administration of contrast agents, and tracking and optimizing patient workflow. The aim of this review is to present current evidence of how big data derived from medical images may impact on the diagnostic pathway of the oncologic patient.
癌症是一种复杂的疾病，不幸的是，了解癌症系统的各个组成部分如何运作并不能帮助我们理解整个系统的行为。用希腊哲学家亚里士多德的话来说，“整体大于部分之和”。迄今为止，由于信息技术基础设施的改进，存储每位癌症患者的数据成为可能，这些数据包括临床数据、医学图像、实验室检查以及病理和基因组信息。事实上，医疗档案存储约占全球总存储需求的三分之一，并且大部分数据是以医学图像的形式存在。现在的机会是从整体上获取见解，以造福每一位患者。在肿瘤患者中，大数据分析尚处于起步阶段，但可以设想一些有用的应用，包括开发成像生物标志物以预测疾病转归、评估使用造影剂后X射线剂量暴露或肾损伤的风险，以及跟踪和优化患者就医流程。本综述的目的是展示来自医学图像的大数据如何影响肿瘤患者诊断途径的当前证据。
