Search Results (8)

Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) prediction in high-risk individuals is essential for early detection and improved outcome. While prior studies have utilized pancreatic radiomics for PDAC prediction, the added value of main pancreatic duct (MPD) features remains unclear. This study aims to assess the additional value of features of the main pancreatic duct (MPD) for predicting PDAC occurrence across different timeframes in advance. Methods: In total, 321 contrast-enhanced CT scans of the MPD and pancreas carried out across control, pre-diagnostic, and diagnostic cohorts were segmented, and radiomics were extracted. A support vector machine (SVM) classifier was used to classify the control and pre-diagnostic cohorts, with model performance assessed using area under the receiver operating characteristic (ROC) curves (AUCs) Results: The MPD diameter and volume significantly increased from the control to the pre-diagnostic and diagnostic CT scans (p < 0.05). The addition of features of the MPD to the pancreas improved the PDAC prediction AUC from 0.83 to 0.96 for subjects 6 months to 3 years in advance, from 0.81 to 0.94 for 3–6 years in advance, and 0.75 to 0.84 for 6–10 years in advance of diagnosis. Additionally, integrating MPD radiomics with diameter and volume significantly improved the AUC from 0.81 to 0.88 for subjects 6 months to 3 years in advance. Conclusions: Radiomic features from abdominal CT scans allow PDAC prediction up to 10 years in advance. Integrating MPD features, including diameter and volume, significantly improves PDAC prediction compared to using radiomics of the pancreas alone. Full article

Elastography is a non-invasive imaging modality that has been developed for the evaluation of the stiffness of various organs. It is categorized into two main types: strain elastography and shear wave elastography. While strain elastography offers valuable information on the mechanical properties of the organ being studied, it is limited by the qualitative nature of its measurements and its reliance on operator skills. On the other hand, shear wave elastography overcomes these limitations as it provides a quantitative assessment of tissue stiffness, offers more reproducibility, and is less operator-dependent. Endoscopic ultrasound-guided shear wave elastography (EUS-SWE) is an emerging technique that overcomes the limitations of transabdominal ultrasound in the evaluation of the pancreas. A growing body of literature has demonstrated its safety and feasibility in the evaluation of pancreatic parenchyma. This article provides a comprehensive review of the current state of the literature on EUS-SWE, including its technical aspects, clinical applications in the evaluation of various pancreatic conditions, technological limitations, and future directions. Full article

Background: Esophageal self-expandable metal stents (SEMS) are an important endoscopic tool. These stents have now been adapted successfully to manage post-bariatric surgery complications such as anastomotic leaks and strictures. In centers of expertise, this has become the primary standard-of-care treatment given its minimally invasive nature, and that it results in early oral feeding, decreased hospitalization, and overall favorable outcomes. Self-expandable metal stents (SEMS) fractures are a rare complication of unknown etiology. We aimed to investigate possible causes of SEMS fractures and highlight a unique endoscopic approach utilized to manage a fractured and impaled SEMS. Methods: This is a retrospective study of consecutive patients who underwent esophageal SEMS placement between 2015–2021 at a tertiary referral center to identify fractured SEMS. Patient demographics, stent characteristics, and possible etiologies of fractured SEMS were identified. A comprehensive literature review was also conducted to evaluate all prior cases of fractured SEMS and to hypothesize fracture theories. Results: There were seven fractured esophageal SEMS, of which six were used to manage post-bariatric surgery complications. Five SEMS were deployed with their distal ends in the gastric antrum and proximal ends in the distal esophagus. All stents fractured within 9 weeks of deployment. Most stents (5/7) were at least 10 cm in length with fractures commonly occurring in the distal third of the stents (6/7). The wires of a fractured SEMS were embedded within the esophagogastric junction in one case, prompting the use of an overtube that was synchronously advanced while steadily extracting the stent. Discussion: We suggest the following four etiologies of SEMS fractures: anatomical, physiological, mechanical, and chemical. Stent curvature at the stomach incisura can lead to strain- and stress-related fatigue due to mechanical bending with exacerbation from respiratory movements. Physiologic factors (gastric body contractions) can result in repetitive squeezing of the stent, adding to metal fatigue. Intrinsic properties (long length and low axial force) may be contributing factors. Lastly, the stomach acidic environment may cause nitinol-induced chemical weakness. Despite the aforementioned theories, SEMS fracture etiology remains unclear. Until more data become available, it may be advisable to remove these stents within 6 weeks. Full article

In previous studies, a significant increase in the incidence of pancreatic cancer among younger women compared to men in the United States was noted. However, the specific histopathologic characteristics were not delineated. This population-based study aimed to assess whether this disproportionate rise in pancreatic cancer in younger women was contributed by pancreatic ductal adenocarcinoma (PDAC) or pancreatic neuroendocrine tumors (PanNET). The United States Cancer Statistics (USCS) database was used to identify patients with pancreatic cancer between 2001 and 2018. The results showed that, in younger adults, the incidence of PDAC has increased in women [average annual percentage change (AAPC) = 0.62%], while it has remained stable in men (AAPC = −0.09%). The PDAC incidence rate among women increased at a greater rate compared to men with a statistically significant difference in AAPC (p < 0.001), with neither identical nor parallel trends. In contrast, cases of PanNET did not demonstrate a statistically significant sex-specific AAPC difference. In conclusion, this study demonstrated that the dramatic increase in the incidence rate of PDAC explains the disproportionate rise in pancreatic cancer incidence in younger women. This prompts further prospective studies to investigate the underlying reasons for these sex-specific disparities in PDAC. Full article

Introduction: Although the global incidence of non-cardia gastric cancer (NCGC) is decreasing, there are limited data on sex-specific incidence in the United States. This study aimed to investigate time trends of NCGC from the SEER database to externally validate findings in a SEER-independent national database, and to further assess trends among subpopulations. Methods: Age-adjusted incidence rates of NCGC were obtained from the SEER database from 2000 to 2018. We used joinpoint models to calculate average annual percentage change (AAPC) to determine sex-specific trends among older (≥55 years) and younger adults (15–54 years). Using the same methodology, findings were then externally validated using SEER-independent data from the National Program of Cancer Registries (NPCR). Stratified analyses by race, histopathology, and staging at diagnosis were also conducted in younger adults. Results: Overall, there were 169,828 diagnoses of NCGC from both independent databases during the period 2000–2018. In SEER, among those <55 years, incidence increased at a higher rate in women (AAPC = 3.22%, p < 0.01) than men (AAPC = 1.51%, p = 0.03), with non-parallel trends (p = 0.02), while a decreasing trend was seen in both men (AAPC = −2.16%, p < 0.01) and women (AAPC = −1.37%, p < 0.01) of the ≥55 years group. Validation analysis of the SEER-independent NPCR database from 2001 to 2018 showed similar findings. Further stratified analyses showed that incidence is disproportionately increasing in young non-Hispanic White women [AAPC = 2.28%, p < 0.01] while remaining stable in their counterpart men [AAPC = 0.58%, p = 0.24] with non-parallel trends (p = 0.04). This pattern was not observed in other race groups. Conclusion: NCGC incidence has been increasing at a greater rate in younger women compared to counterpart men. This disproportionate increase was mainly seen in young non-Hispanic White women. Future studies should investigate the etiologies of these trends. Full article

Background and aims: Pancreatic cancer (PC) incidence is increasing at a greater rate in young women compared to young men. We performed a race- and ethnicity-specific evaluation of incidence trends in subgroups stratified by age and sex to investigate the association of race and ethnicity with these trends. Methods: Age-adjusted PC incidence rates (IR) from the years 2000 to 2018 were obtained from the SEER 21 database. Non-Hispanic White (White), Non-Hispanic Black (Black) and Hispanic patients were included. Age categories included older (ages ≥ 55) and younger (ages < 55) adults. Time-trends were described as annual percentage change (APC) and average APC (AAPC). Results: Younger White [AAPC difference = 0.73, p = 0.01)], Black [AAPC difference = 1.96, p = 0.01)] and Hispanic [AAPC difference = 1.55, p = 0.011)] women experienced a greater rate of increase in IR compared to their counterpart men. Younger Hispanic women experienced a greater rate of increase in IR compared to younger Black women [AAPC difference = −1.28, p = 0.028)] and younger White women [AAPC difference = −1.35, p = 0.011)]. Conclusion: Younger women of all races and ethnicities experienced a greater rate of increase in PC IR compared to their counterpart men; however, younger Hispanic and Black women experienced a disproportionately greater increase. Hispanic women experienced a greater rate of increase in IR compared to younger Black and White women. Full article

Upper gastrointestinal (GI) malignancy is a leading cause of cancer-related morbidity and mortality. Upper endoscopy has an established role in diagnosing and staging upper GI cancers, screening for pre-malignant lesions, and providing palliation in cases of advanced malignancy. New advances in endoscopic techniques and technology have improved diagnostic accuracy and increased the therapeutic potential of upper endoscopy. We aim to describe the different types of endoscopic technology used in cancer diagnosis, summarize the current guidelines for endoscopic diagnosis and treatment of malignant and pre-malignant lesions, and explore new potential roles for endoscopy in cancer therapy. Full article

The accurate segmentation of pancreatic subregions (head, body, and tail) in CT images provides an opportunity to examine the local morphological and textural changes in the pancreas. Quantifying such changes aids in understanding the spatial heterogeneity of the pancreas and assists in the diagnosis and treatment planning of pancreatic cancer. Manual outlining of pancreatic subregions is tedious, time-consuming, and prone to subjective inconsistency. This paper presents a multistage anatomy-guided framework for accurate and automatic 3D segmentation of pancreatic subregions in CT images. Using the delineated pancreas, two soft-label maps were estimated for subregional segmentation—one by training a fully supervised naïve Bayes model that considers the length and volumetric proportions of each subregional structure based on their anatomical arrangement, and the other by using the conventional deep learning U-Net architecture for 3D segmentation. The U-Net model then estimates the joint probability of the two maps and performs optimal segmentation of subregions. Model performance was assessed using three datasets of contrast-enhanced abdominal CT scans: one public NIH dataset of the healthy pancreas, and two datasets D₁ and D₂ (one for each of pre-cancerous and cancerous pancreas). The model demonstrated excellent performance during the multifold cross-validation using the NIH dataset, and external validation using D₁ and D₂. To the best of our knowledge, this is the first automated model for the segmentation of pancreatic subregions in CT images. A dataset consisting of reference anatomical labels for subregions in all images of the NIH dataset is also established. Full article