Causes of Exocrine Pancreatic Insufficiency Other Than Chronic Pancreatitis

Exocrine pancreatic insufficiency (EPI), an important cause of maldigestion and malnutrition, results from primary pancreatic disease or is secondary to impaired exocrine pancreatic function. Although chronic pancreatitis is the most common cause of EPI, several additional causes exist. These include pancreatic tumors, pancreatic resection procedures, and cystic fibrosis. Other diseases and conditions, such as diabetes mellitus, celiac disease, inflammatory bowel disease, and advanced patient age, have also been shown to be associated with EPI, but the exact etiology of EPI has not been clearly elucidated in these cases. The causes of EPI can be divided into loss of pancreatic parenchyma, inhibition or inactivation of pancreatic secretion, and postcibal pancreatic asynchrony. Pancreatic enzyme replacement therapy (PERT) is indicated for the conditions described above presenting with clinically clear steatorrhea, weight loss, or symptoms related to maldigestion and malabsorption. This review summarizes the current literature concerning those etiologies of EPI less common than chronic pancreatitis, the pathophysiology of the mechanisms of EPI associated with each diagnosis, and treatment recommendations.

Pancreas MRI segmentation into head, body, and tail enables regional quantitative analysis of heterogeneous disease

Pancreatic disease can be spatially inhomogeneous. For this reason, quantitative imaging studies of the pancreas have often targeted the 3 main anatomical pancreatic parts, head, body, and tail, traditionally using a balanced region of interest (ROI) strategy. Existing automated analysis methods have implemented whole-organ segmentation, which provides an overall quantification, but fails to address spatial heterogeneity in disease. A method to automatically refine a whole-organ segmentation of the pancreas into head, body, and tail subregions is presented for abdominal magnetic resonance imaging (MRI). The subsegmentation method is based on diffeomorphic registration to a group average template image, where the parts are manually annotated. For a new whole-pancreas segmentation, the aligned template's part labels are automatically propagated to the segmentation of interest. The method is validated retrospectively on the UK Biobank imaging substudy (scanned using a 2-point Dixon protocol at 1.5 tesla), using a nominally healthy cohort of 100 subjects for template creation, and 50 independent subjects for validation. Pancreas head, body, and tail were annotated by multiple experts on the validation cohort, which served as the benchmark for the automated method's performance. Good intra-rater (Dice overlap mean, Head: 0.982, Body: 0.940, Tail: 0.961, N=30) as well as inter-rater (Dice overlap mean, Head: 0.968, Body: 0.905, Tail: 0.943, N=150) agreement was observed. No significant difference (Wilcoxon rank sum test, DSC, Head: p=0.4358, Body: p=0.0992, Tail: p=0.1080) was observed between the manual annotations and the automated method's predictions. Results on regional pancreatic fat assessment are also presented, by intersecting the 3-D parts segmentation with one 2-D multi-echo gradient-echo slice, available from the same scanning session, that was used to compute MRI proton density fat fraction (MRI-PDFF). Initial application of the method on a type 2 diabetes cohort showed the utility of the method for assessing pancreatic disease heterogeneity.

The role of molecular biology in the diff erential diagnosis of pancreatic cystic neoplasias

Summary: Pancreatic cysts have been detected ever more frequently in recent years due to the advanced and wider use of imaging methods. We find them on CT or MR also in asymptomatic patients who do not have a history of any pancreatic disease. Pancreatic cystic lesions represent a wide range of pathological changes from simple cysts through precancerous lesions to malignant cysts. Accurate dia­gnosis remains difficult despite the combination of clinical status evaluation, imaging findings, and bio­chemical and cytological examination. Molecular bio­logical examination of cyst aspirate obtained by endosonographic examination increases the detection rate of mucinous cysts (KRAS/GNAS/VHL) and cysts with a high risk of malignancy (KRAS/GNAS/p53/PIK3CA/PTEN/CDKN2A/SMAD4) and optimizes therapeutic approach. Larger prospective validation studies are necessary to make this costly and limited method a routine part of clinical practice. Key words: molecular bio­logy – neoplasia – pancreatic cysts

Endoscopic Ultrasound Guided Fine Needle Aspiration and Biopsy for Pancreatic Disease

The endoscopic ultrasound (EUS) is a device with an ultrasound probe on the tip of endoscope. We can observe the surrounding structures outside the alimentary tract by using EUS. It is also possible to get a tissue from the pancreatic lesion for histopathologic diagnosis by using EUS. The development of devices and techniques of EUS guided tissue acquisitions made it the choice of non-operative pathologic test for pancreatic diseases. This paper describes the clinical applications of this procedure in pancreatic lesions from the recent European and Korean guidelines, including how to choose the needle, role of rapid on site evaluation, usage of stylet, suction and fanning technique, how to process acquired specimen, procedure-related complications and educations of this method.

Genome-edited zebrafish model of ABCC8 loss-of-function disease

KATP channel gain- (GOF) and loss-of-function (LOF) mutations underlie human neonatal diabetes mellitus (NDM) and hyperinsulinism (HI), respectively. Genetically modified mice with transgenic overexpression of GOF mutations recapitulate many features of human NDM but, importantly, there are currently no gene knock-in mouse models of GOF mutations. Moreover, while transgenic mice expressing incomplete KATP LOF do reiterate mild hyperinsulinism, KATP knockout animals do not exhibit persistent hyperinsulinism. We have shown that islet excitability and glucose homeostasis are regulated by identical KATP channels in zebrafish. SUR1 truncation mutation (K499X) was introduced into the abcc8 gene to explore the possibility of using zebrafish for modeling human NDM and HI. Patch-clamp analysis confirmed complete absence of channel activity in β-cells from K499X (SUR1-/-) fish. No difference in random blood glucose was detected in heterozygous SUR1+/- fish, nor in homozygous SUR1-/- fish, mimicking findings in SUR1 knockout mice. Mutant fish did however, demonstrate impaired glucose tolerance, similar to partial LOF mouse models. In paralleling features of mammalian diabetes and hyperinsulinism resulting from equivalent gain- or loss-of-function mutations, these gene-edited animals provide valid zebrafish models of KATP LOF driven-dependent pancreatic disease.

SP3.1.2 The influence of frailty on outcomes for older adults admitted to hospital with benign biliary and pancreatic disease

Aims To study the prevalence and complications of biliary disease with increasing age. We describe the prevalence of frailty in older patients hospitalised with benign biliary and pancreatic disease and establish its association with mortality and duration of hospital stay. Methods Prospective observational cohort study of patients aged 75 years and over admitted with acute biliary disease between 17/09/2014 and 20/03/2017. Clinical Frailty Scale (CFS) score was recorded on admission. Results 200 patients with a median age of 82 (75-99), 60% females, 154 (77%) were independent for personal and 99 (49.5%) for instrumental activities of daily living. Acute cholecystitis was the most common diagnosis (43%), acute cholangitis (36%) and acute pancreatitis (21%). 99 patients were non-frail (NF = CFS 1-4) and 101 were frail (F= CFS ≥5). 104 patients received medical treatment only. Surgery was more common in non-frail (F 2% vs. NF 11%), percutaneous drainage more frequently carried out in frail patients (15% vs. NF 5%) and endoscopic cholangiopancreatography (ERCP) was similar in both groups (F 32%vs. NF 31%). Frailty was associated with worse clinical outcomes. F vs. NF: functional deconditioning (34% vs. 11%), increased care level (19% vs 3%), length of stay (12 vs. 7 days), 90-day (8% vs. 3%) and 1 year-mortality (48% vs. 24%). Conclusions : Higher frailty scoring is associated with increased mortality in acute biliary disease. Individuals living with frailty were less likely to undergo surgical treatment, spent longer in hospital and were less likely to remain alive at 12 months after hospital discharge.

CGAT: Cell Graph ATtention Network for Grading of Pancreatic Disease Histology Images

Early detection of Pancreatic Ductal Adenocarcinoma (PDAC), one of the most aggressive malignancies of the pancreas, is crucial to avoid metastatic spread to other body regions. Detection of pancreatic cancer is typically carried out by assessing the distribution and arrangement of tumor and immune cells in histology images. This is further complicated due to morphological similarities with chronic pancreatitis (CP), and the co-occurrence of precursor lesions in the same tissue. Most of the current automated methods for grading pancreatic cancers rely on extensive feature engineering involving accurate identification of cell features or utilising single number spatially informed indices for grading purposes. Moreover, sophisticated methods involving black-box approaches, such as neural networks, do not offer insights into the model’s ability to accurately identify the correct disease grade. In this paper, we develop a novel cell-graph based Cell-Graph Attention (CGAT) network for the precise classification of pancreatic cancer and its precursors from multiplexed immunofluorescence histology images into the six different types of pancreatic diseases. The issue of class imbalance is addressed through bootstrapping multiple CGAT-nets, while the self-attention mechanism facilitates visualization of cell-cell features that are likely responsible for the predictive capabilities of the model. It is also shown that the model significantly outperforms the decision tree classifiers built using spatially informed metric, such as the Morisita-Horn (MH) indices.