Endothelin-axis antagonism enhances tumor perfusion in pancreatic cancer.

Delivery of therapeutic agents in pancreatic cancer (PC) is impaired due to its hypovascular and desmoplastic tumor microenvironment. The Endothelin (ET)-axis is the major regulator of vasomotor tone under physiological conditions and is highly upregulated in multiple cancers. We investigated the effect of dual endothelin receptor antagonist bosentan on perfusion and macromolecular transport in a PC cell-fibroblast co-implantation tumor model using Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI). Following bosentan treatment, the contrast enhancement ratio and wash-in rates in tumors were two- and nine times higher, respectively, compared to the controls, whereas the time to peak was significantly shorter (7.29 ± 1.29 min v/s 22.08 ± 5.88 min; p = 0.04). Importantly, these effects were tumor selective as the magnitudes of change for these parameters were much lower in muscles. Bosentan treatment also reduced desmoplasia and improved intratumoral distribution of high molecular weight FITC-dextran. Overall, these findings support that targeting the ET-axis can serve as a potential strategy to selectively enhance tumor perfusion and improve the delivery of therapeutic agents in pancreatic tumors.

Effects of interobserver and interdisciplinary segmentation variabilities on CT-based radiomics for pancreatic cancer.

Radiomics is a method to mine large numbers of quantitative imaging features and develop predictive models. It has shown exciting promise for improved cancer decision support from early detection to personalized precision treatment, and therefore offers a desirable new direction for pancreatic cancer where the mortality remains high despite the current care and intense research. For radiomics, interobserver segmentation variability and its effect on radiomic feature stability is a crucial consideration. While investigations have been reported for high-contrast cancer sites such as lung cancer, no studies to date have investigated it on CT-based radiomics for pancreatic cancer. With three radiation oncology observers and three radiology observers independently contouring on the contrast CT of 21 pancreatic cancer patients, we conducted the first interobserver segmentation variability study on CT-based radiomics for pancreatic cancer. Moreover, our novel investigation assessed whether there exists an interdisciplinary difference between the two disciplines. For each patient, a consensus tumor volume was generated using the simultaneous truth and performance level expectation algorithm, using the dice similarity coefficient (DSC) to assess each observer's delineation against the consensus volume. Radiation oncology observers showed a higher average DSC of 0.81 ± 0.06 than the radiology observers at 0.69 ± 0.16 (p = 0.002). On a panel of 1277 radiomic features, the intraclass correlation coefficients (ICC) was calculated for all observers and those of each discipline. Large variations of ICCs were observed for different radiomic features, but ICCs were generally higher for the radiation oncology group than for the radiology group. Applying a threshold of ICC > 0.75 for considering a feature as stable, 448 features (35%) were found stable for the radiation oncology group and 214 features (16%) were stable from the radiology group. Among them, 205 features were found stable for both groups. Our results provide information for interobserver segmentation variability and its effect on CT-based radiomics for pancreatic cancer. An interesting interdisciplinary variability found in this study also introduces new considerations for the deployment of radiomics models.

Irreversible and sustained upregulation of endothelin axis during oncogene-associated pancreatic inflammation and cancer.

Endothelin-1 (ET-1) and its two receptors, endothelin receptor A (ETAR) and endothelin receptor B (ETBR) exhibit deregulated overexprerssion in pancreatic ductal adenocarcinoma (PDAC) and pancreatitis. We examined the expression pattern of endothelin (ET) axis components in the murine models of chronic and acute inflammation in the presence or absence of oncogenic K-ras. While the expression of endothelin converting enzyme-1 (ECE-1), ET-1, ETAR and ETBR in the normal pancreas is restricted predominantly to the islet cells, progressive increase of ET receptors in ductal cells and stromal compartment is observed in the KC model (Pdx-1 Cre; K-rasG12D) of PDAC. In the murine pancreas harboring K-rasG12D mutation (KC mice), following acute inflammation induced by cerulein, increased ETAR and ETBR expression is observed in the amylase and CK19 double positive cells that represent cells undergoing pancreatic acinar to ductal metaplasia (ADM). As compared to the wild type (WT) mice, cerulein treatment in KC mice resulted in significantly higher levels of ECE-1, ET-1, ETAR and ETBR, transcripts in the pancreas. Similarly, in response to cigarette smoke-induced chronic inflammation, the expression of ET axis components is significantly upregulated in the pancreas of KC mice as compared to the WT mice. In addition to the expression in the precursor pancreatic intraepithelial neoplasm (PanIN lesions) in cigarette smoke-exposure model and metaplastic ducts in cerulein-treatment model, ETAR and ETBR expression is also observed in infiltrating F4/80 positive macrophages and α-SMA positive fibroblasts and high co-localization was seen in the presence of oncogenic K-ras. In conclusion, both chronic and acute pancreatic inflammation in the presence of oncogenic K-ras contribute to sustained upregulation of ET axis components in the ductal and stromal cells suggesting a potential role of ET axis in the initiation and progression of PDAC.

Radiomics in stratification of pancreatic cystic lesions: Machine learning in action.

Pancreatic cystic lesions (PCLs) are well-known precursors of pancreatic cancer. Their diagnosis can be challenging as their behavior varies from benign to malignant disease. Precise and timely management of malignant pancreatic cysts might prevent transformation to pancreatic cancer. However, the current consensus guidelines, which rely on standard imaging features to predict cyst malignancy potential, are conflicting and unclear. This has led to an increased interest in radiomics, a high-throughput extraction of comprehensible data from standard of care images. Radiomics can be used as a diagnostic and prognostic tool in personalized medicine. It utilizes quantitative image analysis to extract features in conjunction with machine learning and artificial intelligence (AI) methods like support vector machines, random forest, and convolutional neural network for feature selection and classification. Selected features can then serve as imaging biomarkers to predict high-risk PCLs. Radiomics studies conducted heretofore on PCLs have shown promising results. This cost-effective approach would help us to differentiate benign PCLs from malignant ones and potentially guide clinical decision-making leading to better utilization of healthcare resources. In this review, we discuss the process of radiomics, its myriad applications such as diagnosis, prognosis, and prediction of therapy response. We also discuss the outcomes of studies involving radiomic analysis of PCLs and pancreatic cancer, and challenges associated with this novel field along with possible solutions. Although these studies highlight the potential benefit of radiomics in the prevention and optimal treatment of pancreatic cancer, further studies are warranted before incorporating radiomics into the clinical decision support system.

Elevating pancreatic cystic lesion stratification: Current and future pancreatic cancer biomarker(s).

Pancreatic ductal adenocarcinoma (PDAC) is an incredibly deadly disease with a 5-year survival rate of 9%. The presence of pancreatic cystic lesions (PCLs) confers an increased likelihood of future pancreatic cancer in patients placing them in a high-risk category. Discerning concurrent malignancy and risk of future PCL progression to cancer must be carefully and accurately determined to improve survival outcomes and avoid unnecessary morbidity of pancreatic resection. Unfortunately, current image-based guidelines are inadequate to distinguish benign from malignant lesions. There continues to be a need for accurate molecular and imaging biomarker(s) capable of identifying malignant PCLs and predicting the malignant potential of PCLs to enable risk stratification and effective intervention management. This review provides an update on the current status of biomarkers from pancreatic cystic fluid, pancreatic juice, and seromic molecular analyses and discusses the potential of radiomics for differentiating PCLs harboring cancer from those that do not.

Radiation protection and standardization.

X - Rays has become integral and indispensable part of health care diagnosis and intervention. Intervention procedures in Orthopedics surgery now mostly performed under image intensifiers (C-Arm) which involve the risks of occupational overexposure of radiation to the patients and health care personnel. The principles of radiation protection are helpful in keeping radiation exposure just adequate for diagnostic and intervention procedures. Regular surveillance of protective apparel is necessary for longevity of safety. It is responsibility of all OT personnel to know and implement radiation safety. Each situation involving X-ray radiation should include justification of the procedure, minimum radiation exposure just adequate for diagnostic and interventional procedures.