Firmino Macedo, Morais Antônio H, Mendoça Roberto M, Dantas Marcel R, Hekis Helio R, Valentim Ricardo
Department of Information and Computer Science, Federal Institute of Rio Grande do Norte (IFRN), Natal, Brazil.
Biomed Eng Online. 2014 Apr 8;13:41. doi: 10.1186/1475-925X-13-41.
The goal of this paper is to present a critical review of major Computer-Aided Detection systems (CADe) for lung cancer in order to identify challenges for future research. CADe systems must meet the following requirements: improve the performance of radiologists providing high sensitivity in the diagnosis, a low number of false positives (FP), have high processing speed, present high level of automation, low cost (of implementation, training, support and maintenance), the ability to detect different types and shapes of nodules, and software security assurance.
The relevant literature related to "CADe for lung cancer" was obtained from PubMed, IEEEXplore and Science Direct database. Articles published from 2009 to 2013, and some articles previously published, were used. A systemic analysis was made on these articles and the results were summarized.
Based on literature search, it was observed that many if not all systems described in this survey have the potential to be important in clinical practice. However, no significant improvement was observed in sensitivity, number of false positives, level of automation and ability to detect different types and shapes of nodules in the studied period. Challenges were presented for future research.
Further research is needed to improve existing systems and propose new solutions. For this, we believe that collaborative efforts through the creation of open source software communities are necessary to develop a CADe system with all the requirements mentioned and with a short development cycle. In addition, future CADe systems should improve the level of automation, through integration with picture archiving and communication systems (PACS) and the electronic record of the patient, decrease the number of false positives, measure the evolution of tumors, evaluate the evolution of the oncological treatment, and its possible prognosis.
本文旨在对主要的肺癌计算机辅助检测系统(CADe)进行批判性综述,以确定未来研究面临的挑战。CADe系统必须满足以下要求:提高放射科医生的诊断性能,提供高灵敏度、低假阳性(FP)数量、具有高处理速度、呈现高水平自动化、低成本(实施、培训、支持和维护)、能够检测不同类型和形状的结节以及具备软件安全保障。
从PubMed、IEEEXplore和Science Direct数据库获取与“肺癌CADe”相关的文献。使用了2009年至2013年发表的文章以及一些先前发表的文章。对这些文章进行了系统分析并总结了结果。
基于文献检索,发现本综述中描述的许多(如果不是全部)系统在临床实践中都有可能发挥重要作用。然而,在研究期间,灵敏度、假阳性数量、自动化水平以及检测不同类型和形状结节的能力方面并未观察到显著改善。提出了未来研究面临的挑战。
需要进一步研究以改进现有系统并提出新的解决方案。为此,我们认为通过创建开源软件社区进行合作努力对于开发满足上述所有要求且开发周期短的CADe系统是必要的。此外,未来的CADe系统应通过与图像存档和通信系统(PACS)以及患者电子记录集成来提高自动化水平,减少假阳性数量,测量肿瘤的演变,评估肿瘤治疗的进展及其可能的预后。