The purpose of this study is to determine clinical impact of EUS-guided microbiopsy procedure and supplementary molecular analyses compared to standard diagnostic workup of pancreatic cysts. The hypothesis is that a combination of previously mentioned modalities may change the management of some pancreatic cystic lesions, increase the diagnostic accuracy and optimize the discrimination between high- and low-risk pancreatic cysts.
Pancreatic ductal adenocarcinoma (PDAC) accounts for 6% of all cancer related deaths in Denmark, and the 5-year survival rate is only 8%. PDAC develops from precursor lesions with pancreatic intraepithelial neoplasia (panIN) being the most common, and cystic lesions as a second precursor. Unlike panINs, which are too small for detection with current imaging modalities, cystic lesions of the pancreas are increasingly diagnosed due to the extended use of cross-sectional imaging. Pancreatic cystic lesions may be observed in up to 13.5% of all MRI scans and 3% of all CT scans. There are several types of pancreatic cysts and each of them requires individual management, ranging from no treatment over watchful waiting to surgical resection according to their malignant potential. Standard diagnostic workup includes cross-sectional imaging of the cystic lesions and, in selected cases endoscopic ultrasound (EUS) with aspiration of cyst fluid by fine needle aspiration (FNA), followed by cyst fluid cytology and tumor marker analysis. The diagnostic algorithm is based on International consensus guidelines established in 2006, and revised in 2012 and 2017, integrating clinical features with EUS-findings. The level of evidence in these guidelines is unfortunately low. A recent meta-analysis concluded that EUS and cyst fluid cytology have low sensitivity (54-63%), whereas the specificity is acceptable (88-92%) for detection of mucinous cysts. Low sensitivity is mainly due to absence of sufficient cellular material in the cyst fluid for definite diagnosis. Tumor marker analysis of cyst fluid, such as carcinoembryonic antigen (CEA), CA 72.4, CA 125, CA 19.9, and CA 15.3, have been studied extensively with CEA being the most accurate marker. A cut-off value of 192 ng/mL for CEA distinguishes mucinous from non-mucinous cysts with a good, albeit imperfect, accuracy of 80%. However, the value will not differentiate between IPMN and MCN, and more importantly, it does not correlate with the level of dysplasia or malignancy. EUS-guided through-the-needle microbiopsy using the Moray™ forceps is a novel adjunctive. The device can be inserted through a EUS-FNA needle and used to obtain microbiopsies from different tissues in relationship to the gastrointestinal system. This instrument can be used in combination with EUS-FNA to subsequently obtain microbiopsies from the pancreatic cyst wall. Microbiopsies seem to represent a break-through in pre-operative classification of pancreatic cysts, as they provide histological material for examination of tissue architecture not readily accessible in FNA material. However, very little experience has been obtained hitherto. Even though this technique is currently described only in a few studies, it seems feasible and theoretically offers a higher quality of material than what can be obtained by EUS-FNA alone.
Use of EUS-guided through-the-needle microbiopsy forceps for obtainment of tissue from the wall of the cystic lesion
Prevalence of genetic mutations in known cancer-associated genes in the microbiopsy tissue examined using the Ion AmpliSeq Cancer Hotspot Panel v2 (Life Technologies, Carlsbad, USA). The multigene panel explores selected regions of 50 cancer-associated genes, among others KRAS, GNAS, CDKN2A and SMAD4 genes.
Gastro Unit, Division of Endoscopy
Herlev, Danmark, Denmark
Clinical impact of EUS-guided microbiopsies in patients with pancreatic cystic lesions
All patients are evaluated at a multidisciplinary conference prior to microbiopsy procedure. A primary decision is made based on available imaging modalities and/or cyst fluid analysis (operation, follow-up or discontinuation from follow-up). Subsequently, each patient is once again evaluated at a multidisciplinary conference, and a possible change in management is noted. Clinical impact is defined as a proportion of the patients where a change in clinical management is observed.
Time frame: 3 weeks
Technical success of EUS-guided microbiopsy procedure
Technical success is defined as a proportion of patients where a pancreatic cystic lesion is successfully punctured by a 19G FNA needle, and where at least one microbiopsy is obtained with the microbiopsy forceps.
Time frame: 3 weeks
Adverse events following EUS-guided microbiopsy procedure
Adverse events are defined in concordance with ASGE guidelines (Cotton PB, Eisen GM, Aabakken L et al. A lexicon for endoscopic adverse events: report of an ASGE workshop. Gastrointest Endosc 2010; 71: 446-454). All patients are contacted by telephone on day 3 following the procedure. Adverse event rate is an overall proportion of the patients where an adverse event is observed.
Time frame: 3 weeks
Diagnostic yield of EUS-guided microbiopsies
Diagnostic yield is defined as a proportion of the patients included where a definite histopathological diagnosis could be made on microbiopsy material.
Time frame: 3 weeks
Diagnostic performance of EUS-guided microbiopsies in the surgical subcohort
Sensitivity, specificity as well as positive and negative predictive values are calculated by comparing microbiopsy diagnosis with gold standard (resected specimens).
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Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
101
Time frame: 2 years
Diagnostic values of gene mutations (NGS analyses) in microbiopsy material in the surgical subcohort
Sensitivity, specificity as well as positive and negative predictive values are calculated by correlating different mutations with final diagnosis in patients that undergo surgery. NGS analysis is performed using the Ion AmpliSeq Cancer Hotspot Panel v2 (Life Technologies, Carlsbad, USA). The multigene panel explores selected regions of 50 cancer-associated genes, among others KRAS, GNAS, CDKN2A and SMAD4 genes.
Time frame: 2 years