Imaging predictors of BRAF mutation in colorectal cancer

Current Status of Cancer Genomics and Imaging Phenotypes: What Radiologists Need to Know

Ongoing discoveries in cancer genomics and epigenomics have revolutionized clinical oncology and precision health care. This knowledge provides unprecedented insights into tumor biology and heterogeneity within a single tumor, among primary and metastatic lesions, and among patients with the same histologic type of cancer. Large-scale genomic sequencing studies also sparked the development of new tumor classifications, biomarkers, and targeted therapies. Because of the central role of imaging in cancer diagnosis and therapy, radiologists need to be familiar with the basic concepts of genomics, which are now becoming the new norm in oncologic clinical practice. By incorporating these concepts into clinical practice, radiologists can make their imaging interpretations more meaningful and specific, facilitate multidisciplinary clinical dialogue and interventions, and provide better patient-centric care. This review article highlights basic concepts of genomics and epigenomics, reviews the most common genetic alterations in cancer, and discusses the implications of these concepts on imaging by organ system in a case-based manner. This information will help stimulate new innovations in imaging research, accelerate the development and validation of new imaging biomarkers, and motivate efforts to bring new molecular and functional imaging methods to clinical radiology. Keywords: Oncology, Cancer Genomics, Epignomics, Radiogenomics, Imaging Markers Supplemental material is available for this article. © RSNA, 2023.

Computed tomography-based radiomics nomogram for the pre-operative prediction of BRAF mutation and clinical outcomes in patients with colorectal cancer: a double-center study

OBJECTIVE

To develop and validate a radiomics nomogram based on CT for the pre-operative prediction of BRAF mutation and clinical outcomes in patients with colorectal cancer (CRC).

METHODS

A total of 451 CRC patients (training cohort = 190; internal validation cohort = 125; external validation cohort = 136) from 2 centers were retrospectively included. Least absolute shrinkage and selection operator regression was used to select radiomics features and the radiomics score (Radscore) was calculated. Nomogram was constructed by combining Radscore and significant clinical predictors. Receiver operating characteristic curve analysis, calibration curve and decision curve analysis were used to evaluate the predictive performance of the nomogram. Kaplan‒Meier survival curves based on the radiomics nomogram were used to assess overall survival (OS) of the entire cohort.

RESULTS

The Radscore consisted of nine radiomics features which were the most relevant to BRAF mutation. The radiomics nomogram integrating Radscore and clinical independent predictors (age, tumor location and cN stage) showed good calibration and discrimination with AUCs of 0.86 (95% CI: 0.80-0.91), 0.82 (95% CI: 0.74-0.90) and 0.82 (95% CI: 0.75-0.90) in the training cohort, internal validation and external validation cohorts, respectively. Furthermore,the performance of nomogram was significantly better than that of the clinical model (p < 0.05). The radiomics nomogram-predicted BRAF mutation high-risk group had a worse OS than the low-risk group (p < 0.0001).

CONCLUSION

The radiomics nomogram showed good performance in predicting BRAF mutation and OS of CRC patients, which could provide valuable information for individualized treatment.

ADVANCES IN KNOWLEDGE

The radiomics nomogram could effectively predict BRAF mutation and OS in patients with CRC. High-risk BRAF mutation group identified by the radiomics nomogram was independently associated with poor OS.

Risk Factors for Synchronous Peritoneal Metastases in Colorectal Cancer: A Systematic Review and Meta-Analysis

Background

Early detection of synchronous colorectal peritoneal metastases (CPMs) is difficult due to the absence of typical symptoms and the low accuracy of imaging examinations. Increasing the knowledge of the risk factors for synchronous CPM may be essential for early diagnosis and improving their management. This study aimed to identify the risk factors for synchronous CPM.

Method

The study was registered at PROSPERO (CRD42020198548). The PubMed, Embase and Cochrane Library databases were searched for studies comparing the clinicopathological and molecular features between patients with or without synchronous CPM. The pooled data were assessed by a random-effects model.

Results

Twenty-five studies were included. A synchronous CPM was positively associated with female sex (OR 1.299; 1.118 to 1.509; P = 0.001), PROK1/PROKR2-positivity (OR 2.244; 1.031 to 4.884; P = 0.042), right-sided colon cancer (OR 2.468; 2.050 to 2.970; P < 0.001), poorly differentiated grade (OR 2.560; 1.537 to 4.265; P < 0.001), BRAF mutation (OR 2.586; 1.674 to 3.994; P < 0.001), mucinous adenocarcinoma (OR 3.565; 2.095 to 6.064; P < 0.001), signet-ring cell carcinoma (OR 4.480; 1.836 to 10.933; P = 0.001), N1-2 (OR 5.665; 3.628 to 8.848; P < 0.001), T4 (OR 12.331; 7.734 to 19.660; P < 0.001) and elevated serum CA19-9 (OR 12.868; 5.196 to 31.867; P < 0.001).

Conclusions

These evidence-based risk factors are indicators that could predict the presence of synchronous CPMs and can improve their management.

Systematic Review Registration

www.crd.york.ac.uk/prospero, identifier: CRD42020198548.

Preoperative Prediction of BRAF Mutation Status in Colorectal Cancer Using a Clinical-radiomics Model

RATIONALE AND OBJECTIVES

This study aimed to develop a clinically practical model to predict V-raf murine sarcoma viral oncogene homolog B1 (BRAF) mutation in colorectal cancer according to radiomic signatures based on computed tomography (CT) and clinical risk factors, and to determine the model's diagnostic accuracy for BRAF mutation status.

MATERIALS AND METHODS

This retrospective study included 140 patients with colorectal cancer. The significant clinical risk factors were used to build the clinical model; the least absolute shrinkage and selection operator algorithm was adopted to construct a radiomics signature according to imaging features of the tumor lesion, and stepwise logistic regression was applied to select the significant variables to develop the clinical-radiomics model. The predictive performance was evaluated by receiver operating characteristic curve analysis, calibration curve analysis, and decision curve analysis.

RESULTS

The radscore, generated by 5 selected radiomics features, demonstrated a favorable ability to predict BRAF mutation in both the training (area under the receiver operating characteristic curve [AUC] 0.93) and validation (AUC 0.87) cohorts. Subsequently, integrating two independent predictors (including the radscore and clinical risk factors) into a nomogram exhibited more favorable discriminatory performance, with the AUC improved to 0.95 and 0.88 in both cohorts. Moreover, the accuracy for predicting BRAF mutations was higher than that of the clinical model, ranging from 0.70 to 0.89.

CONCLUSION

The proposed CT-based radiomics signature is associated with BRAF mutations. The present study also proposes a combined model can potentially be applied in the individual preoperative prediction of BRAF mutation status in colorectal cancer.

ADVANCES IN KNOWLEDGE

CT-based radiomics showed satisfactory diagnostic significance for the BRAF status in colorectal cancer, the clinical-combined model may be applied in the individual preoperative prediction of BRAF mutation.

Overview of serum and tissue markers in colorectal cancer: a primer for radiologists

Serum and tissue tumor markers provide crucial information in the diagnosis, treatment, and follow-up of colorectal cancers. Tissue tumor markers are increasingly used for determination of targeted chemotherapy planning based on genotyping of tumor cells. Recently, plasma-based technique of liquid biopsy is being evaluated for providing tumor biomarkers in the management of colorectal cancer. Tumor markers are commonly used in conjunction with imaging during initial staging, treatment determination, response assessment, and determination of recurrence or metastatic disease. Knowledge of tumor markers and their association with radiological findings is thus crucial for radiologists. Additionally, various novel imaging techniques are being evaluated as potential noninvasive imaging biomarkers to predict tumor genotypes, features, and tumor response. We review and discuss the potential role of these newer imaging techniques.