Skachat Rusty Survival Na Pk
Pancreatic ductal adenocarcinoma (PDAC) is the third most common cause of cancer-related death in the US with an extremely poor prognosis. Over the past four decades, the 5-year survival rate has only marginally increased from 3% to 8.5%1. As the only definitive treatment, about 20% of PDAC cases are eligible for surgical resection2 with these patients having a 5-year survival of 19%3.
skachat rusty survival na pk
The most common clinicopathologic factors significantly associated with 5-year survival are lymph node status, tumour size, margin status at surgery, histological tumour grade, and receipt of adjuvant chemotherapy3,4,5,6.
As an evolving paradigm in cancer biomarker discovery and validation, radiomics has shown early promise in exploiting the latent information in medical images and establishing links between quantitative imaging biomarkers, and patient outcome and response to systemic chemotherapy and radiation7,8,9. Radiomics refers to the extraction and analysis of a large amount of quantitative features from medical images10,11. These quantitative imaging features can be used to build prognostic models to risk-stratify patients based on different clinical outcomes such as survival. The ability to capture the entirety of a tumour gives radiomics the capability of assessing one of the key features of cancer, heterogeneity. Radiomic parameters related to heterogeneity have been shown to be a prognostic factor for patient outcome in other cancer sites such as lung12.
In PDAC, computed tomography (CT) is the main diagnostic tool for assessment of local extent of disease and surgical planning16. As a standard-of-care imaging modality, CT images can be used to extract radiomic features with no extra image acquisition cost to the healthcare system, thus providing comprehensive information on the phenotypic and textural structure of the tumour. Neoadjuvant therapy has been shown to improve the survival of patients with resectable PDAC17. If radiomic features can identify patients with more aggressive disease, it might help select patients most in need of neoadjuvant treatment.
Figure 3 shows the Kaplan-Meier plots for OS using the radiomics signature in the validation cohort for the two readers. Figure 4 shows two typical examples from the validation cohort contoured for tumour by both Reader 1 and 2 with specific survival time and radiomic signature values.
PDAC has a very low survival rate33. Better treatment options, fundamental understanding of the disease and earlier detection methods are needed. In this exploratory study, we evaluated the potential of radiomic features in PDAC on CT as part of early validation. We have demonstrated the potential of a radiomic signature as a prognostic biomarker in PDAC that can be used across different CT scanners and readers. Although radiomic features have been found to be prognostic of patient outcome in different cancer sites such as lung7,18, kidney19,20, and colorectal cancer21, there is limited work on PDAC9,22,23. These studies are all single institution exploring a limited number of radiomic features. In addition, only one reader contour has been used for the analysis, and standard radiomic libraries are not used in most of these studies. By using an open source code library (PyRadiomics24), there is an opportunity for other centres to validate the findings presented in this study. If further validated, this signature could be used to help select patients that may benefit from neoadjuvant treatment.
Limitations of this work was the relatively small sample, and outcome was limited to overall survival. We hope to extend this work to larger cohorts and multicentre studies with more clinical outcome and genomics data soon. Moreover, CA19-9 and carcinoembryonic antigen (CEA) which have been shown to be associated with the OS of PDAC37 were not available for all patients. In future studies, the added prognostic value of radiomic signature to these preoperative biomarkers will be investigated using the full cohorts. Nevertheless, when these biomarkers are obtained, which is after diagnosis, radiomic features are readily available with no extra cost. Thus, a reliable radiomic signature with prognostic power is of significant value independent of other preoperative biomarkers. 041b061a72