医学
免疫疗法
免疫系统
免疫检查点
癌症
肿瘤微环境
分子成像
不利影响
疾病
模式
生物信息学
体内
病理
免疫学
内科学
社会科学
生物技术
社会学
生物
作者
Larissa Bastos Costa,Marcelo A. Queiroz,Felipe de Galiza Barbosa,Rafael Fernandes Nunes,Elaine C. Zaniboni,Mariana Mazo Ruiz,Denis L. Jardim,José Flávio Gomes Marin,Giovanni Guido Cerri,Carlos Alberto Buchpiguel
出处
期刊:Radiographics
[Radiological Society of North America]
日期:2020-12-04
卷期号:41 (1): 120-143
被引量:34
标识
DOI:10.1148/rg.2021200093
摘要
Cancer demands precise evaluation and accurate and timely assessment of response to treatment. Imaging must be performed early during therapy to allow adjustments to the course of treatment. For decades, cross-sectional imaging provided these answers, showing responses to the treatment through changes in tumor size. However, with the emergence of immune checkpoint inhibitors, complex immune response patterns were revealed that have quickly highlighted the limitations of this approach. Patterns of response beyond tumor size have been recognized and include cystic degeneration, necrosis, hemorrhage, and cavitation. Furthermore, new unique patterns of response have surfaced, like pseudoprogression and hyperprogression, while other patterns were shown to be deceptive, such as unconfirmed progressive disease. This evolution led to new therapeutic evaluation criteria adapted specifically for immunotherapy. Moreover, inflammatory adverse effects of the immune checkpoint blockade were identified, many of which were life threatening and requiring prompt intervention. Given complex concepts like tumor microenvironment and novel therapeutic modalities in the era of personalized medicine, increasingly sophisticated imaging techniques are required to address the intricate patterns of behavior of different neoplasms. Fluorine 18–fluorodeoxyglucose PET/CT has rapidly emerged as one such technique that spans both molecular biology and immunology. This imaging technique is potentially capable of identifying and tracking prognostic biomarkers owing to its combined use of anatomic and metabolic imaging, which enables it to characterize biologic processes in vivo. This tailored approach may provide whole-body quantification of the metabolic burden of disease, providing enhanced prediction of treatment response and improved detection of adverse events. ©RSNA, 2020
科研通智能强力驱动
Strongly Powered by AbleSci AI