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

작성자
kaistsoftware
작성일
2020-06-09 10:27
조회
6767
  • 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.
전체 121
번호 제목 작성자 작성일 추천 조회
공지사항
2024년 봄학기 콜로퀴엄 일정 안내
kaistsoftware | 2024.02.21 | 추천 1 | 조회 3360
kaistsoftware 2024.02.21 1 3360
120
5/7 지향성 프로그램 분석 (허기홍 교수/KAIST 전산학부)
kaistsoftware | 2024.04.23 | 추천 0 | 조회 31
kaistsoftware 2024.04.23 0 31
119
4/23 사모투자의 이해 (최원호 교수/KAIST 전산학부)
kaistsoftware | 2024.04.18 | 추천 0 | 조회 119
kaistsoftware 2024.04.18 0 119
118
4/2 LLM 기반 소프트웨어 공학의 현재와 전망 (유신 교수/KAIST 전산학부)
kaistsoftware | 2024.03.25 | 추천 0 | 조회 338
kaistsoftware 2024.03.25 0 338
117
3/26 하드웨어도 소프트웨어처럼 짜야한다 (강지훈 교수/KAIST 전산학부)
kaistsoftware | 2024.03.21 | 추천 0 | 조회 367
kaistsoftware 2024.03.21 0 367
116
3/19 자율주행과 안전 (배홍상 교수/KAIST 전산학부)
kaistsoftware | 2024.03.11 | 추천 0 | 조회 528
kaistsoftware 2024.03.11 0 528
115
3/12 에너지 효율적인 인공지능 학습 시스템 (권영진 교수/KAIST 전산학부)
kaistsoftware | 2024.03.05 | 추천 0 | 조회 692
kaistsoftware 2024.03.05 0 692
114
2/27 멀티-디바이스 모바일 플랫폼 (신인식 교수/KAIST 전산학부)
kaistsoftware | 2024.02.27 | 추천 0 | 조회 1250
kaistsoftware 2024.02.27 0 1250
113
11/20 Where is Autonomous Driving going? Boss, Traffic Jam Pilot, and the Future (배홍상 교수/KAIST 전산학부, Zeta Mobility)
kaistsoftware | 2023.11.16 | 추천 1 | 조회 2619
kaistsoftware 2023.11.16 1 2619
112
11/14 데이터 품질 문제에 견고한 AI 기술 (이재길 교수/KAIST 전산학부)
kaistsoftware | 2023.11.16 | 추천 1 | 조회 1807
kaistsoftware 2023.11.16 1 1807
111
11/6 인터랙션 중심 AI (김주호 교수/KAIST 전산학부)
kaistsoftware | 2023.11.01 | 추천 0 | 조회 1866
kaistsoftware 2023.11.01 0 1866