Tharmaseelan Hishan, Hertel Alexander, Rennebaum Shereen, Nörenberg Dominik, Haselmann Verena, Schoenberg Stefan O, Froelich Matthias F
Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim of the University of Heidelberg, 68167 Mannheim, Germany.
Institute of Clinical Chemistry, University Medical Center Mannheim, Medical Faculty Mannheim of the University of Heidelberg, 68167 Mannheim, Germany.
Cancers (Basel). 2022 Jul 9;14(14):3349. doi: 10.3390/cancers14143349.
Similar to the transformation towards personalized oncology treatment, emerging techniques for evaluating oncologic imaging are fostering a transition from traditional response assessment towards more comprehensive cancer characterization via imaging. This development can be seen as key to the achievement of truly personalized and optimized cancer diagnosis and treatment. This review gives a methodological introduction for clinicians interested in the potential of quantitative imaging biomarkers, treating of radiomics models, texture visualization, convolutional neural networks and automated segmentation, in particular. Based on an introduction to these methods, clinical evidence for the corresponding imaging biomarkers-(i) dignity and etiology assessment; (ii) tumoral heterogeneity; (iii) aggressiveness and response; and (iv) targeting for biopsy and therapy-is summarized. Further requirements for the clinical implementation of these imaging biomarkers and the synergistic potential of personalized molecular cancer diagnostics and liquid profiling are discussed.
与向个性化肿瘤治疗的转变类似，新兴的肿瘤影像学评估技术正在推动从传统的反应评估向通过影像学进行更全面的癌症特征描述的转变。这一发展可被视为实现真正个性化和优化癌症诊断与治疗的关键。本综述为对定量成像生物标志物、放射组学模型、纹理可视化、卷积神经网络和自动分割潜力感兴趣的临床医生提供了方法学介绍。基于对这些方法的介绍，总结了相应成像生物标志物的临床证据——（i）尊严和病因评估；（ii）肿瘤异质性；（iii）侵袭性和反应；以及（iv）活检和治疗靶点。还讨论了这些成像生物标志物临床应用的进一步要求以及个性化分子癌症诊断和液体分析的协同潜力。
