Department of Radiology Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Department of Radiology, Centre hospitalier de l'Université de Montréal (CHUM), 1000 rue Saint- Denis, Montreal, Quebec, H2×0C1, Canada; Research Center, Centre hospitalier de l'Université de Montréal (CHUM), 900 rue Saint-Denis, Montreal, Quebec, H2×0A9, Canada.
Comput Methods Programs Biomed. 2022 Mar;215:106609. doi: 10.1016/j.cmpb.2021.106609. Epub 2021 Dec 27.
Radiomics is a newcomer field that has opened new windows for precision medicine. It is related to extraction of a large number of quantitative features from medical images, which may be difficult to detect visually. Underlying tumor biology can change physical properties of tissues, which affect patterns of image pixels and radiomics features. The main advantage of radiomics is that it can characterize the whole tumor non-invasively, even after a single sampling from an image. Therefore, it can be linked to a "digital biopsy". Physicians need to know about radiomics features to determine how their values correlate with the appearance of lesions and diseases. Indeed, physicians need practical references to conceive of basics and concepts of each radiomics feature without knowing their sophisticated mathematical formulas. In this review, commonly used radiomics features are illustrated with practical examples to help physicians in their routine diagnostic procedures.
放射组学是一个新兴领域，为精准医学开辟了新的窗口。它涉及从医学图像中提取大量定量特征，这些特征可能难以肉眼检测。肿瘤的潜在生物学特性会改变组织的物理特性，从而影响图像像素和放射组学特征的模式。放射组学的主要优势在于它可以非侵入性地对整个肿瘤进行特征描述，即使只对图像进行单次采样也如此。因此，它可以与“数字活检”相关联。医生需要了解放射组学特征，以确定其值与病变和疾病的外观有何关联。实际上，医生需要参考实用的资料来理解每个放射组学特征的基础知识和概念，而无需了解其复杂的数学公式。在这篇综述中，我们将通过实际示例来说明常用的放射组学特征，以帮助医生在日常诊断程序中使用。
