Dynamic Susceptibility Contrast (DSC) Perfusion MR in the Prediction of Long-Term Survival of Glioblastomas (GBM): Correlation with MGMT Promoter Methylation and 1p/19q Deletions

PURPOSE: To investigate the surgical, perfusion, and molecular characteristics of glioblastomas which influence long-term survival after treatment, and to explore the association between MR perfusion parameters and the presence of MGMT methylation and 1p/19q deletions. MATERIALS AND METHODS: This retrospective study was approved by our institutional review board. A total 43 patients were included, all with pathologic diagnosis of glioblastoma with known MGMT methylation and 1p/19q deletion statuses. We divided these patients into long-term (≥ 60 months, n = 7) and short-term (< 60 months, n = 36) survivors, then compared surgical extent, molecular status, and rCBV parameters between the two groups using Fisher's exact test or Mann-Whitney test. The rCBV parameters were analyzed according to the presence of MGMT methylation and 1p/19q deletions. We investigated the relationship between the mean rCBV and overall survival using linear correlation. Multivariable linear regression was performed in order to find the variables related to overall survival. RESULTS: Long-term survivors (100% [7 of 7]) demonstrated a greater percentage of gross total or near total resection than short-term survivors (54.5% [18 of 33]). A higher prevalence of 1p/19q deletions was also noted among the long-term survivors (42.9% [3 of 7]) than the short-term survivors (0.0% [0 of 36]). The rCBV parameters did not differ between the long-term and short-term survivors. The rCBV values were marginally lower in patients with MGMT methylation and 1p/19q deletions. Despite no correlation found between overall survival and rCBV in the whole group, the short-term survivor group showed negative correlation (R2 = 0.181, P = 0.025). Multivariable linear regression revealed that surgical extent and 1p/19q deletions, but not rCBV values, were associated with prolonged overall survival. CONCLUSION: While preoperative rCBV and 1p/19q deletion status are related to each other, only surgical extent and the presence of 1p/19q deletion in GBM patients may predict long-term survival.

Towards precision medicine: from quantitative imaging to radiomics / 浙江大学学报（英文版）（B辑：生物医学和生物技术）

Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues. Therefore, interest in the application of radiomics has been growing in recent years as it has the potential to provide significant interpretive and predictive information for decision support. Radiomics is a combination of conventional computer-aided diagnosis, deep learning methods, and human skills, and thus can be used for quantitative characterization of tumour phenotypes. This paper discusses the overview of radiomics workflow, the results of various radiomics-based studies conducted using various radiological images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET), the challenges we are facing, and the potential contribution of radiomics towards precision medicine.

Progress of radiomics and radiogenomics in lung cancer / 国际肿瘤学杂志

Radiomics and radiogenomics are used to provide comprehensive tumor biological characte-ristics and further clinical information by extracting,screening and analyzing the most valuable quantitative ra-diomics features. In recent years,numerous studies have shown that radiomics plays a role in the diagnosis, treatment and predicting efficacy and prognosis of lung cancer. Radiogenomics shows a great value in the pre-diction of lung cancer gene phenotype and individualized precision treatment by combining radiomics features with genomics,proteomics and so on. Radiomics and radiogenomics are non-invasive,quantitative,and repro-ducible,and they can provide multidirectional tumor biological characteristics,which are expected to be widely used in the precise medical treatment of lung cancer in the future.

Progresses of radiogenomics in association between CT features and driver gene mutations of non-small cell lung cancer / 中国医学影像技术

Driver genes of non-small cell lung cancer (NSCLC) include EGFR,KRAS,BRAF,PIK3CA and ALK,etc.Obtaining precise molecular phenotype is the premise of target therapy.However,because of heterogeneity of NSCLC,the genetic mutations of the tumor may not be accurately obtained from small biopsy samples.As a routine modality for NSCLC,CT may comprehensively reflect the underlying pathophysiology and molecular biology of the tumors.Radiogenomics,which is focusing on defining relationships between image features (image phenotypes) and molecular markers (molecular phenotypes),has a broad prospect in the prediction of driver gene mutations of NSCLC.Progresses of radiogenomics in association between CT features and driver gene mutations of NSCLC were reviewed in this article.