6/11 Image-driven precision oncology for malignant gliomas: beyond cliché (최승원 교수/삼성서울병원 신경외과)

작성자
kaistsoftware
작성일
2020-06-09 10:27
조회
6544
  • 강사 : 최승원 교수 (삼성서울병원 신경외과) 
  • 일시 : 2020. 6. 11 (목) 17:00~18:30
Malignant gliomas are most common primary brain malignancy in adults. Despite some success stories of other solid tumors, the cure for these tumors is still pessimistic. One of major hurdles to conquer these tumors is their rarity, and another concern is their peculiar anatomic location which may hinder adequate sampling. Given enormous intra-tumor heterogeneity, molecular biomarkers are limited to fully represent the biologic activities of the entire tumor as they are usually derived from a single confined sub-region of the tumor. During past decades, genomic research much helped to comprehend tumor biology of malignant gliomas, however, failed to improve the clinical outcome regarding precision oncology. In other words, genomic information alone could not recapitulate the tumor evolution underneath the clinical progression, which implying the necessity of integrating multi-omics data.
In the light of clinical application, medical images are powerful tools and potentially represent underlying biologic activity of tumors. Imaging biomarkers are more versatile than molecular biomarkers considering several key challenges against malignant gliomas; they are non-invasive and free from sampling bias, thus reflecting the characteristics of the whole tumor. However, they also have some inherent weakness; data reproducibility and objectivity are main concerns accompanied by radiographic assessment. Radiomics, by converting medical images into high-dimensional data, has enabled us to transform the descriptive imaging features into the format of quantitative and objective data, thus contributing the evolution of image-driven data science. Another unsolved issue is their translational ability in terms of biological activity. Many have attempted to annotate the imaging phenotype with understandable molecular correlates, still robust association has not been elucidated.
Herein we present the basic principles of radiomics and introduce several key radiomic studies in the field of neuro-oncology. Future perspectives of radiomics study will be also discussed in this session.
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