Abstract 1833
Background
Although the personalized medicine has always focused on the genomic or proteomic characterization of tumor, medical imaging is still one of the major factors to guide therapy and to monitor the progression of the tumor. Radiomics is an emerging field that converts the medical image data into the mineable quantitative features via the automatically algorithms, and can server as a bridge between medical image, genomics and clinical-parameters. Serval studies have demonstrated that the radiomic-based model can predict outcome of RCC, but the correlation between radiomic features and histological subtypes of RCC is still unknown. The aim of this letter is to focus on the ability of radiomics to identify the histological subtypes and metastasis of RCC.
Methods
This study included Forty-four patients diagnosed with renal tumor. For each renal lesion, The CT images of volume of interest (VOI) were obtained semi-automatically by two experienced nuclear medicine physician, 85 texture features were extracted from each VOI using the first-order statistics features, Shape Based Features, Gray Level Neighboring Gray Level Dependence Matrix and Neighboring Gray Tone Difference Matrix.
Results
To investigate the value of radiomic features to capture phenotypic differences of RCC, we performed Unsupervised Clustering of patients with similar radiomic expression patterns. We analyzed the two main clusters of patients with clinical parameters, and found that the tumor clusters were statistically and significantly associated with primary tumor stage (P < 0.001), M-stage (P = 0.049) and benign (P = 0.037), wherein high T-stages, M-stage and tumor group showed in cluster II. RCC histology and N-stage (lymph-node) did not reach statistical significance for their association with the radiomic expression patterns (P = 0.165, 0.361, respectively). In addition, we analyzed the overall survival (OS) of the each radiomic features, and showed that P25, IMC1 and IMC2 were associated with OS (P = 0.002, 0.002, 0.016, respectively, log-rank test).
Conclusions
The radiomic features from medical images could be helpful in deciphering T-stages, metastasis and benign of RCC and may have potential as imaging biomarker for prediction of RCC overall survival.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Zhejiang Cancer Hospital.
Funding
National Natural Science Foundation of China (No 81402117, 81671775), Natural Science Foundation of Zhejiang Province (No LY17H160043) and Qianjiang talent plan of Zhejiang Province (No QJD1602025).
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
2171 - CCND1 Amplification Contributes to Immunosuppression in Head and Neck Squamous Cell Carcinoma and the Association with a Poor Response to Immune Checkpoint Inhibitors
Presenter: Chloe Huang
Session: Poster Display session 3
Resources:
Abstract
2624 - Efficacy of PD-1/PD-L1 inhibitors in the treatment of non-small cell lung cancer patients with sensitive genes mutation
Presenter: Hui-Juan Cui
Session: Poster Display session 3
Resources:
Abstract
3494 - Neutrophil to Lymphocyte Ratio (NLR) kinetics as predictors of outcomes in metastatic renal cell carcinoma (mRCC) and non-small cell lung cancer (NSCLC) patients treated with nivolumab (N).
Presenter: Audrey Simonaggio
Session: Poster Display session 3
Resources:
Abstract
3964 - Predictive markers of checkpoint inhibitor activity in adult metastatic solid tumours
Presenter: Alexandra Pender
Session: Poster Display session 3
Resources:
Abstract
3041 - Blood-based TMB (bTMB) correlates with tissue-based TMB (tTMB) in a multi-cancer Phase I IO Cohort
Presenter: Daniel Araujo
Session: Poster Display session 3
Resources:
Abstract
3910 - Analysis of Molecular Profile Complexities for Immunotherapy Decision Support
Presenter: Robert Dóczi
Session: Poster Display session 3
Resources:
Abstract
4836 - The Role of Tumor Neoantigens in the Differential Response to Immunotherapy (IO) in EGFR and BRAF Mutated Lung Cancers - Quantity or Quality?
Presenter: Katrina Case
Session: Poster Display session 3
Resources:
Abstract
1929 - Impact of previous corticosteroid (CS) exposure on efficacy of Programmed Cell Death-(Ligand) 1 blockade in patients with advanced Non-Small-Cell Lung Cancer (NSCLC): a single Center retrospective analysis
Presenter: Fabrizio Nelli
Session: Poster Display session 3
Resources:
Abstract
2601 - Comparison 18F-FDG-PET/CT criteria for prediction of therapy response and clinical outcome in patients with metastatic melanoma treated with Ipilimumab and PD-1 inhibitors
Presenter: Sabrina Vari
Session: Poster Display session 3
Resources:
Abstract
3628 - Predictive model for survival in advanced non-small-cell lung cancer (NSCLC) treated with frontline pembrolizumab
Presenter: Xabier Mielgo Rubio
Session: Poster Display session 3
Resources:
Abstract