Multimodality imaging of pancreatic cancer-computed tomography, magnetic resonance imaging, and positron emission tomography. Cancer J. 2012;18:511-522. [PMID: 23187837 DOI: 10.1097/ppo.0b013e318274a461]

Mesopancreas-Anatomical Insights and Its Implications for Diagnosis and Clinical and Surgical Practice

Background: The concept of mesopancreas is frequently discussed in the surgical literature as the neural pathway for metastatic spread in pancreatic head cancer. It generally refers to a retro-pancreatic plane that should be resected to reduce the incidence of regional metastases. However, this concept remains poorly defined, both embryologically and anatomically. Our objective was to establish a clear embryological and anatomical definition of the mesopancreas, making anatomical data more applicable in surgical practice. Methods: We examined seven cadavers (5 males, 2 females, aged 62-71) with no medical or surgical history, preserved in 9% formalin at Carol Davila University's Anatomy Department. Regional dissections were performed in successive planes, highlighting the celiac ganglia and the associated network of neural connections that comprise the mesopancreas. Results: Our study defines the "mesopancreas" as remnants of primordial mesenteries that coalesced into the Treitz fascia. We identified its functional components as nerve fibers linking the celiac ganglia and superior mesenteric plexus to the pancreas, along with vascular structures, lymphatics, and connective and adipose tissue. These components likely contribute to regional metastasis in pancreatic head cancer. While resection of the mesopancreas could help prevent metastasis, its complex anatomy and proximity to major vessels pose significant surgical challenges. Conclusions: Based on our findings, we propose a plausible definition for the term "mesopancreas". It encompasses the structures that originated as part of the primordial mesenteries, which subsequently coalesced, resulting in the formation of the Treitz fascia. In essence, the mesopancreas is the functional content of a former mesentery.

Imaging Techniques and Biochemical Biomarkers: New Insights into Diagnosis of Pancreatic Cancer

Pancreatic cancer (PaC) incidence is increasing, but our current screening and diagnostic strategies are not very effective. However, screening could be helpful in the case of PaC, as recent evidence shows that the disease progresses gradually. Unfortunately, there is no ideal screening method or program for detecting PaC in its early stages. Conventional imaging techniques, such as abdominal ultrasound, CT, MRI, and EUS, have not been successful in detecting early-stage PaC. On the other hand, biomarkers may be a more effective screening tool for PaC and have greater potential for further evaluation compared to imaging. Recent studies on biomarkers and artificial intelligence (AI)-enhanced imaging have shown promising results in the early diagnosis of PaC. In addition to proteins, non-coding RNAs are also being studied as potential biomarkers for PaC. This review consolidates the current literature on PaC screening modalities to provide an organized framework for future studies. While conventional imaging techniques have not been effective in detecting early-stage PaC, biomarkers and AI-enhanced imaging are promising avenues of research. Further studies on the use of biomarkers, particularly non-coding RNAs, in combination with imaging modalities may improve the accuracy of PaC screening and lead to earlier detection of this deadly disease.

Intra-Operative Tumour Detection and Staging in Pancreatic Cancer Surgery: An Integrative Review of Current Standards and Future Directions

BACKGROUND

Surgical resection for pancreatic ductal adenocarcinoma (PDAC) entails the excision of the primary tumour and regional lymphadenectomy. This traditional strategy is challenged by the high rate of early recurrence, suggesting inadequate disease staging. Novel methods of intra-operative staging are needed to allow surgical resection to be tailored to the disease's biology.

METHODS

A search of published articles on the PubMed and Embase databases was performed using the terms 'pancreas' OR 'pancreatic' AND 'intra-operative staging/detection' OR 'guided surgery'. Articles published between January 2000 and June 2023 were included. Technologies that offered intra-operative staging and tailored treatment were curated and summarised in the following integrative review.

RESULTS

lymph node (LN) mapping and radioimmunoguided surgery have shown promising results but lacked practicality to facilitate real-time intra-operative staging for PDAC. Fluorescence-guided surgery (FGS) offers high contrast and sensitivity, enabling the identification of cancerous tissue and positive LNs with improved precision following intravenous administration of a fluorescent agent. The unique properties of optical coherence tomography and ultrasound elastography lend themselves to be platforms for virtual biopsy intra-operatively.

CONCLUSIONS

Accurate intra-operative staging of PDAC, localisation of metastatic LNs, and identification of extra-pancreatic disease remain clinically unmet needs under current detection methods and staging standards. Tumour-specific FGS combined with other diagnostic and therapeutic modalities could improve tumour detection and staging in patients with PDAC.

Data privacy-aware machine learning approach in pancreatic cancer diagnosis

PROBLEM

Pancreatic ductal adenocarcinoma (PDAC) is considered a highly lethal cancer due to its advanced stage diagnosis. The five-year survival rate after diagnosis is less than 10%. However, if diagnosed early, the five-year survival rate can reach up to 70%. Early diagnosis of PDAC can aid treatment and improve survival rates by taking necessary precautions. The challenge is to develop a reliable, data privacy-aware machine learning approach that can accurately diagnose pancreatic cancer with biomarkers.

AIM

The study aims to diagnose a patient's pancreatic cancer while ensuring the confidentiality of patient records. In addition, the study aims to guide researchers and clinicians in developing innovative methods for diagnosing pancreatic cancer.

METHODS

Machine learning, a branch of artificial intelligence, can identify patterns by analyzing large datasets. The study pre-processed a dataset containing urine biomarkers with operations such as filling in missing values, cleaning outliers, and feature selection. The data was encrypted using the Fernet encryption algorithm to ensure confidentiality. Ten separate machine learning models were applied to predict individuals with PDAC. Performance metrics such as F1 score, recall, precision, and accuracy were used in the modeling process.

RESULTS

Among the 590 clinical records analyzed, 199 (33.7%) belonged to patients with pancreatic cancer, 208 (35.3%) to patients with non-cancerous pancreatic disorders (such as benign hepatobiliary disease), and 183 (31%) to healthy individuals. The LGBM algorithm showed the highest efficiency by achieving an accuracy of 98.8%. The accuracy of the other algorithms ranged from 98 to 86%. In order to understand which features are more critical and which data the model is based on, the analysis found that the features "plasma_CA19_9", REG1A, TFF1, and LYVE1 have high importance levels. The LIME analysis also analyzed which features of the model are important in the decision-making process.

CONCLUSIONS

This research outlines a data privacy-aware machine learning tool for predicting PDAC. The results show that a promising approach can be presented for clinical application. Future research should expand the dataset and focus on validation by applying it to various populations.

Cross-sectional imaging after pancreatic surgery: The dialogue between the radiologist and the surgeon

Pancreatic surgery is nowadays considered one of the most complex surgical approaches and not unscathed from complications. After the surgical procedure, cross-sectional imaging is considered the non-invasive reference standard to detect early and late compilations, and consequently to address patients to the best management possible. Contras-enhanced computed tomography (CECT) should be considered the most important and useful imaging technique to evaluate the surgical site. Thanks to its speed, contrast, and spatial resolution, it can help reach the final diagnosis with high accuracy. On the other hand, magnetic resonance imaging (MRI) should be considered as a second-line imaging approach, especially for the evaluation of biliary findings and late complications. In both cases, the radiologist should be aware of protocols and what to look at, to create a robust dialogue with the surgeon and outline a fitted treatment for each patient.

Discrimination of pancreato-biliary cancer and pancreatitis patients by non-invasive liquid biopsy

BACKGROUND

Current diagnostics for the detection of pancreato-biliary cancers (PBCs) need to be optimized. We therefore propose that methylated cell-free DNA (cfDNA) derived from non-invasive liquid biopsies serves as a novel biomarker with the ability to discriminate pancreato-biliary cancers from non-cancer pancreatitis patients.

METHODS

Differentially methylated regions (DMRs) from plasma cfDNA between PBCs, pancreatitis and clinical control samples conditions were identified by next-generation sequencing after enrichment using methyl-binding domains and database searches to generate a discriminatory panel for a hybridization and capture assay with subsequent targeted high throughput sequencing.

RESULTS

The hybridization and capture panel, covering around 74 kb in total, was applied to sequence a cohort of 25 PBCs, 25 pancreatitis patients, 25 clinical controls, and seven cases of Intraductal Papillary Mucinous Neoplasia (IPMN). An unbiased machine learning approach identified the 50 most discriminatory methylation markers for the discrimination of PBC from pancreatitis and controls resulting in an AUROC of 0.85 and 0.88 for a training (n = 45) and a validation (n = 37) data set, respectively. The panel was also able to distinguish high grade from low grade IPMN samples.

CONCLUSIONS

We present a proof of concept for a methylation biomarker panel with better performance and improved discriminatory power than the current clinical marker CA19-9 for the discrimination of pancreato-biliary cancers from non-cancerous pancreatitis patients and clinical controls. This workflow might be used in future diagnostics for the detection of precancerous lesions, e.g. the identification of high grade IPMNs vs. low grade IPMNs.

Computed tomography and guidelines-based human-machine fusion model for predicting resectability of the pancreatic cancer

BACKGROUND AND AIM

The study aims to develop a hybrid machine learning model for predicting resectability of the pancreatic cancer, which is based on computed tomography (CT) and National Comprehensive Cancer Network (NCCN) guidelines.

METHOD

We retrospectively studied 349 patients. One hundred seventy-one cases from Center 1 and 92 cases from Center 2 were used as the primary training cohort, and 66 cases from Center 3 and 20 cases from Center 4 were used as the independent test dataset. Semi-automatic module of ITK-SNAP software was used to assist CT image segmentation to obtain three-dimensional (3D) imaging region of interest (ROI). There were 788 handcrafted features extracted for 3D ROI using PyRadiomics. The optimal feature subset consists of three features screened by three feature selection methods as the input of the SVM to construct the conventional radiomics-based predictive model (cRad). 3D ROI was used to unify the resolution by 3D spline interpolation method for constructing the 3D tumor imaging tensor. Using 3D tumor image tensor as input, 3D kernelled support tensor machine-based predictive model (KSTM), and 3D ResNet-based deep learning predictive model (ResNet) were constructed. Multi-classifier fusion ML model is constructed by fusing cRad, KSTM, and ResNet using multi-classifier fusion strategy. Two experts with more than 10 years of clinical experience were invited to reevaluate each patient based on their CECT following the NCCN guidelines to obtain resectable, unresectable, and borderline resectable diagnoses. The three results were converted into probability values of 0.25, 0.75, and 0.50, respectively, according to the traditional empirical method. Then it is used as an independent classifier and integrated with multi-classifier fusion machine learning (ML) model to obtain the human-machine fusion ML model (HMfML).

RESULTS

Multi-classifier fusion ML model's area under receiver operating characteristic curve (AUC; 0.8610), predictive accuracy (ACC: 80.23%), sensitivity (SEN: 78.95%), and specificity (SPE: 80.60%) is better than cRad, KSTM, and ResNet-based single-classifier models and their two-classifier fusion models. This means that three different models have mined complementary CECT feature expression from different perspectives and can be integrated through CFS-ER, so that the fusion model has better performance. HMfML's AUC (0.8845), ACC (82.56%), SEN (84.21%), SPE (82.09%). This means that ML models might learn extra information from CECT that experts cannot distinguish, thus complementing expert experience and improving the performance of hybrid ML models.

CONCLUSION

HMfML can predict PC resectability with high accuracy.

18F-FAPI-04 Outperforms 18F-FDG PET/CT in Clinical Assessments of Patients with Pancreatic Adenocarcinoma

Accurate diagnosis and staging are crucial for selecting treatment for patients with pancreatic ductal adenocarcinoma (PDAC). The desmoplastic responses associated with PDAC are often characterized by hypometabolism. Here, we investigated 18F-fibroblast activation protein inhibitor (FAPI)-04 PET/CT in evaluation of PDAC and compared the findings with those obtained using 18F-FDG. Methods: Sixty-two PDAC patients underwent 18F-FAPI-04 PET/CT and 18F-FDG PET/CT. Identification of primary lesions, lymph node (LN) metastasis, and distant metastasis (DM) by these methods was evaluated, and TNM staging was performed. Correlation between SUVmax of the primary lesion and treatment response was explored in patients who received systemic therapy. Results: 18F-FAPI-04 PET/CT identified all patients with PDAC; 18F-FDG PET/CT missed 1 patient. Tracer uptake was higher in 18F-FAPI-04 PET/CT than in 18F-FDG PET/CT in primary tumors (10.63 vs. 2.87, P < 0.0001), LN metastasis (2.90 vs. 1.43, P < 0.0001), and DM (liver, 6.11 vs. 3.10, P = 0.002; peritoneal, 4.70 vs. 2.08, P = 0.015). The methods showed no significant difference in the T staging category, but the N and M values were significantly higher for 18F-FAPI-04 PET/CT than for 18F-FDG PET/CT (P = 0.002 and 0.008, respectively). Thus, 14 patients were upgraded, and only 1 patient was downgraded, by 18F-FAPI-04 PET/CT compared with 18F-FDG PET/CT. A high SUVmax of the primary tumor did not correlate with treatment response for either 18F-FAPI-04 or 18F-FDG. Conclusion: 18F-FAPI-04 PET/CT performed better than 18F-FDG PET/CT in identification of primary tumors, LN metastasis, and DM and in TNM staging of PDAC.

Role of artificial intelligence in the characterization of indeterminate pancreatic head mass and its usefulness in preoperative diagnosis

Artificial intelligence (AI) has been used in various fields of day-to-day life and its role in medicine is immense. Understanding of oncology has been improved with the introduction of AI which helps in diagnosis, treatment planning, management, prognosis, and follow-up. It also helps to identify high-risk groups who can be subjected to timely screening for early detection of malignant conditions. It is more important in pancreatic cancer as it is one of the major causes of cancer-related deaths worldwide and there are no specific early features (clinical and radiological) for diagnosis. With improvement in imaging modalities (computed tomography, magnetic resonance imaging, endoscopic ultrasound), most often clinicians were being challenged with lesions that were difficult to diagnose with human competence. AI has been used in various other branches of medicine to differentiate such indeterminate lesions including the thyroid gland, breast, lungs, liver, adrenal gland, kidney, etc. In the case of pancreatic cancer, the role of AI has been explored and is still ongoing. This review article will focus on how AI can be used to diagnose pancreatic cancer early or differentiate it from benign pancreatic lesions, therefore, management can be planned at an earlier stage.

Ethical Considerations of Biopsies in Early-Stage Pancreatic Cancer

PURPOSE

The standard of care in resectable and borderline resectable pancreatic ductal adenocarcinoma (PDAC) has evolved to include neoadjuvant treatment before surgical resection. Current guidelines call for obtaining histologic tissue diagnosis via endoscopic ultrasound fine-needle aspiration before administration of neoadjuvant therapy, which differ from guidelines discouraging delay in surgical resection for a biopsy.

MATERIALS AND METHODS

Whether to proceed with treatment before a biopsy confirms that malignancy is a nuanced decision and includes considerations of physical and psychological risks entailed in both pursuing and forgoing a biopsy.

RESULTS

Accuracy of imaging and biopsy results, the presence of contributing clinical signs/symptoms, and the existing precedents of considering biopsies as waivable such as in scenarios with high clinical suspicion and primary surgical resection.

CONCLUSION

When considering the aspects of ethical medical practice including beneficence (doing good), nonmaleficence (avoiding harm), autonomy (allowing patients to make decisions about their care), and utilitarianism (doing the most good for the most people), analysis of whether guidelines guiding biopsies should continue to differ between resection and neoadjuvant treatments in PDAC is prudent.

Pancreatic Cancer and Detection Methods

The pancreas is a vital organ with exocrine and endocrine functions. Pancreatitis is an inflammation of the pancreas caused by alcohol consumption and gallstones. This condition can heighten the risk of pancreatic cancer (PC), a challenging disease with a high mortality rate. Genetic and epigenetic factors contribute significantly to PC development, along with other risk factors. Early detection is crucial for improving PC outcomes. Diagnostic methods, including imagining modalities and tissue biopsy, aid in the detection and analysis of PC. In contrast, liquid biopsy (LB) shows promise in early tumor detection by assessing biomarkers in bodily fluids. Understanding the function of the pancreas, associated diseases, risk factors, and available diagnostic methods is essential for effective management and early PC detection. The current clinical examination of PC is challenging due to its asymptomatic early stages and limitations of highly precise diagnostics. Screening is recommended for high-risk populations and individuals with potential benign tumors. Among various PC screening methods, the N-NOSE plus pancreas test stands out with its high AUC of 0.865. Compared to other commercial products, the N-NOSE plus pancreas test offers a cost-effective solution for early detection. However, additional diagnostic tests are required for confirmation. Further research, validation, and the development of non-invasive screening methods and standardized scoring systems are crucial to enhance PC detection and improve patient outcomes. This review outlines the context of pancreatic cancer and the challenges for early detection.

Computer-Aided Detection for Pancreatic Cancer Diagnosis: Radiological Challenges and Future Directions

Radiological imaging plays a crucial role in the detection and treatment of pancreatic ductal adenocarcinoma (PDAC). However, there are several challenges associated with the use of these techniques in daily clinical practice. Determination of the presence or absence of cancer using radiological imaging is difficult and requires specific expertise, especially after neoadjuvant therapy. Early detection and characterization of tumors would potentially increase the number of patients who are eligible for curative treatment. Over the last decades, artificial intelligence (AI)-based computer-aided detection (CAD) has rapidly evolved as a means for improving the radiological detection of cancer and the assessment of the extent of disease. Although the results of AI applications seem promising, widespread adoption in clinical practice has not taken place. This narrative review provides an overview of current radiological CAD systems in pancreatic cancer, highlights challenges that are pertinent to clinical practice, and discusses potential solutions for these challenges.

Pancreatic cancer, autoimmune or chronic pancreatitis, beyond tissue diagnosis: Collateral imaging and clinical characteristics may differentiate them

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies and is developing into the 2nd leading cause of cancer-related death. Often, the clinical and radiological presentation of PDAC may be mirrored by other inflammatory pancreatic masses, such as autoimmune pancreatitis (AIP) and mass-forming chronic pancreatitis (MFCP), making its diagnosis challenging. Differentiating AIP and MFCP from PDAC is vital due to significant therapeutic and prognostic implications. Current diagnostic criteria and tools allow the precise differentiation of benign from malignant masses; however, the diagnostic accuracy is imperfect. Major pancreatic resections have been performed in AIP cases under initial suspicion of PDAC after a diagnostic approach failed to provide an accurate diagnosis. It is not unusual that after a thorough diagnostic evaluation, the clinician is confronted with a pancreatic mass with uncertain diagnosis. In those cases, a re-evaluation must be entertained, preferably by an experienced multispecialty team including radiologists, pathologists, gastroenterologists, and surgeons, looking for disease-specific clinical, imaging, and histological hallmarks or collateral evidence that could favor a specific diagnosis. Our aim is to describe current diagnostic limitations that hinder our ability to reach an accurate diagnosis among AIP, PDAC, and MFCP and to highlight those disease-specific clinical, radiological, serological, and histological characteristics that could support the presence of any of these three disorders when facing a pancreatic mass with uncertain diagnosis after an initial diagnostic approach has been unsuccessful.

Innovative Imaging Techniques Used to Evaluate Borderline-Resectable Pancreatic Adenocarcinoma

A diagnosis of pancreatic cancer carries a 5-y survival rate of less than 10%. Furthermore, the detection of pancreatic cancer occurs most often in later stages of the disease due to its location in the retroperitoneum and lack of symptoms (in most cases) until tumors become more advanced. Once diagnosed, cross-sectional imaging techniques are heavily utilized to determine the tumor stage and the potential for surgical resection. However, a major determinant of resectability is the extent of local vascular involvement of the mesenteric vessels and critical tributaries; current imaging techniques have limited capacity to accurately determine vascular involvement. Surrounding inflammation and fibrosis can be difficult to discriminate from viable tumor, making determination of the degree of vascular involvement unreliable. New innovations in fluorescence and optoacoustic imaging techniques may overcome these limitations and make determination of resectability more accurate. These imaging modalities are able to more clearly discern between viable tumor tissue and non-neoplastic inflammation or desmoplasia, allowing clinicians to more reliably characterize vascular involvement and develop individualized treatment plans for patients. This review will discuss the current imaging techniques used to diagnose pancreatic cancer, the barriers that current techniques raise to accurate staging, and novel fluorescence and optoacoustic imaging techniques that may provide more accurate clinical staging of pancreatic cancer.

Pancreatic Tumorigenesis: Precursors, Genetic Risk Factors and Screening

Pancreatic cancer (PC) is a highly malignant and aggressive tumor. Despite medical advancement, the silent nature of PC results in only 20% of all cases considered resectable at the time of diagnosis. It is projected to become the second leading cause in 2030. Most pancreatic cancer cases are diagnosed in the advanced stages. Such cases are typically unresectable and are associated with a 5-year survival of less than 10%. Although there is no guideline consensus regarding recommendations for screening for pancreatic cancer, early detection has been associated with better outcomes. In addition to continued utilization of imaging and conventional tumor markers, clinicians should be aware of novel testing modalities that may be effective for early detection of pancreatic cancer in individuals with high-risk factors. The pathogenesis of PC is not well understood; however, various modifiable and non-modifiable factors have been implicated in pancreatic oncogenesis. PC detection in the earlier stages is associated with better outcomes; nevertheless, most oncological societies do not recommend universal screening as it may result in a high false-positive rate. Therefore, targeted screening for high-risk individuals represents a reasonable option. In this review, we aimed to summarize the pathogenesis, genetic risk factors, high-risk population, and screening modalities for PC.

Artificial Intelligence-Driven Diagnosis of Pancreatic Cancer

Pancreatic cancer is among the most challenging forms of cancer to treat, owing to its late diagnosis and aggressive nature that reduces the survival rate drastically. Pancreatic cancer diagnosis has been primarily based on imaging, but the current state-of-the-art imaging provides a poor prognosis, thus limiting clinicians' treatment options. The advancement of a cancer diagnosis has been enhanced through the integration of artificial intelligence and imaging modalities to make better clinical decisions. In this review, we examine how AI models can improve the diagnosis of pancreatic cancer using different imaging modalities along with a discussion on the emerging trends in an AI-driven diagnosis, based on cytopathology and serological markers. Ethical concerns regarding the use of these tools have also been discussed.

Integrated US-OCT-NIRF Tri-Modality Endoscopic Imaging System for Pancreaticobiliary Duct Imaging

Pancreaticobiliary carcinomas is a highly malignant gastrointestinal tumor. Most pancreaticobiliary cancers arise from epithelial proliferation within the pancreaticobiliary ducts, referred to as pancreatic intraepithelial neoplasias (PanINs). Some PanINs are benign metaplasia, while others progress to invasive duct adenocarcinoma (IDAC). However, there is no standard program to diagnose the progression from PanINs to IDAC. In this study, we present a tri-modality imaging system, which integrates ultrasound (US), optical coherence tomography (OCT), and near-infrared fluorescence (NIRF) for pancreaticobiliary duct imaging. This system can obtain OCT, US, and NIRF images in real-time with a frame rate of 30 frames per second. For the endoscopy probe with an outer diameter of 0.9 mm, the US transducer and fiber ball lens were placed back to back. In vivo experiments were performed on the rectums of Sprague-Dawley rats to demonstrate the imaging performance of US, OCT, and fluorescence angiography. An ex vivo experiment on a human pancreatic duct was performed for a more accurate assessment of the pancreaticobiliary duct. The tomography images of rat rectums and human pancreatic ducts were correlated with hematoxylin and eosin (H&E) histology to check the measurement accuracy. The integrated tri-modality system has great clinical potential in mechanism studies, early diagnosis, and prognosis evaluation of malignant pancreaticobiliary carcinomas.

Advanced Imaging of the Biliary System and Pancreas

Despite advances in noninvasive techniques for imaging the pancreaticobiliary system, several disease processes including indeterminate biliary strictures as well as neuroendocrine tumors, inflammatory pseudotumors, and complex cysts of the pancreas remain difficult to characterize. New endoscopic imaging technologies have emerged to address these challenges. Cholangioscopy and intraductal ultrasound (IDUS) are powerful tools to characterize subtle biliary concretions and strictures. Confocal Laser Endomicroscopy (CLE) and Optical Coherence Tomography (OCT) are emerging approaches for the most difficult biliary lesions. Contrast harmonic endoscopic ultrasound (CH-EUS), elastography, and 3D-EUS are improving the approach to subtle pancreatic lesions, particularly in the context of indeterminate tissue sampling. Pancreatoscopy, pancreatic IDUS, and intracystic CLE hold promise to further improve the assessment of pancreatic cysts. We aim to comprehensively review the emerging clinical evidence for these innovative endoscopic imaging techniques.

Chronic Pancreatitis Is a Risk Factor for Pancreatic Cancer, and Incidence Increases With Duration of Disease: A Systematic Review and Meta-analysis

INTRODUCTION

Observational studies have suggested an increased risk of pancreatic ductal adenocarcinoma (PDAC) in patients with acute and chronic pancreatitis. We conducted a systematic review and meta-analysis to evaluate the magnitude of this association and summarize the published epidemiological evidence.

METHODS

We searched electronic databases (MEDLINE, Embase, Web of Science, Cochrane, and Scopus) and reference lists until January 18, 2021. Studies reporting quantitative association between pancreatitis and PDAC were included and assessed for eligibility, data abstraction, and risk of bias. Standardized incidence ratios (SIRs) were pooled using the random-effects model.

RESULTS

Twenty-five cohort and case-control studies met inclusion criteria. Meta-analysis of 12 chronic pancreatitis (CP) studies demonstrated an increased risk of PDAC in patients with CP (SIR: 22.61, 95% confidence interval [CI]: 14.42-35.44). This elevated risk persisted in subgroup analysis of studies that excluded patients diagnosed with PDAC within 2 years of CP diagnosis (SIR: 21.77, 95% CI: 14.43-32.720). The risk was higher in hereditary pancreatitis (SIR: 63.36, 95% CI: 45.39-88.46). The cumulative incidence rates of PDAC in CP increased with follow-up duration. Limited evidence in acute pancreatitis indicates higher PDAC risk in the subset of patients eventually diagnosed with CP. PDAC seems to be uncommon in patients with autoimmune pancreatitis, with 8 reported cases in 358 patients with autoimmune pancreatitis across 4 studies.

DISCUSSION

There is an increased risk of PDAC in patients with CP, and incidence rates increase with CP disease duration. Our results indicate that PDAC surveillance may be considered in individuals with long-standing CP.

The Role of Endoscopic Ultrasonography in the Diagnosis and Staging of Pancreatic Cancer

Pancreatic cancer is the fourth leading cause of cancer-related death and the second gastrointestinal cancer-related death in the United States. Early detection and accurate diagnosis and staging of pancreatic cancer are paramount in guiding treatment plans, as surgical resection can provide the only potential cure for this disease. The overall prognosis of pancreatic cancer is poor even in patients with resectable disease. The 5-year survival after surgical resection is ~10% in node-positive disease compared to ~30% in node-negative disease. The advancement of imaging studies and the multidisciplinary approach involving radiologists, gastroenterologists, advanced endoscopists, medical, radiation, and surgical oncologists have a major impact on the management of pancreatic cancer. Endoscopic ultrasonography is essential in the diagnosis by obtaining tissue (FNA or FNB) and in the loco-regional staging of the disease. The advancement in EUS techniques has made this modality a critical adjunct in the management process of pancreatic cancer. In this review article, we provide an overall description of the role of endoscopic ultrasonography in the diagnosis and staging of pancreatic cancer.

High-Resolution, High b-Value Computed Diffusion-Weighted Imaging Improves Detection of Pancreatic Ductal Adenocarcinoma

Background: Our purpose was to investigate the potential of high-resolution, high b-value computed DWI (cDWI) in pancreatic ductal adenocarcinoma (PDAC) detection. Materials and Methods: We retrospectively enrolled 44 patients with confirmed PDAC. Respiratory-triggered, diffusion-weighted, single-shot echo-planar imaging (ss-EPI) with both conventional (i.e., full field-of-view, 3 × 3 × 4 mm voxel size, b = 0, 50, 300, 600 s/mm2) and high-resolution (i.e., reduced field-of-view, 2.5 × 2.5 × 3 mm voxel size, b = 0, 50, 300, 600, 1000 s/mm2) imaging was performed for suspected PDAC. cDWI datasets at b = 1000 s/mm2 were generated for the conventional and high-resolution datasets. Three radiologists were asked to subjectively rate (on a Likert scale of 1–4) the following metrics: image quality, lesion detection and delineation, and lesion-to-pancreas intensity relation. Furthermore, the following quantitative image parameters were assessed: apparent signal-to-noise ratio (aSNR), contrast-to-noise ratio (aCNR), and lesion-to-pancreas contrast ratio (CR). Results: High-resolution, high b-value computed DWI (r-cDWI1000) enabled significant improvement in lesion detection and a higher incidence of a high lesion-to-pancreas intensity relation (type 1, clear hyperintense) compared to conventional high b-value computed and high-resolution high b-value acquired DWI (f-cDWI1000 and r-aDWI1000, respectively). Image quality was rated inferior in the r-cDWI1000 datasets compared to r-aDWI1000. Furthermore, the aCNR and CR were higher in the r-cDWI1000 datasets than in f-cDWI1000 and r-aDWI1000. Conclusion: High-resolution, high b-value computed DWI provides significantly better visualization of PDAC compared to the conventional high b-value computed and high-resolution high b-value images acquired by DWI.

Review of Immunohistochemistry Biomarkers in Pancreatic Cancer Diagnosis

Pancreatic cancer is one of the cancer types with poor prognosis and high rate of mortality. Diagnostic modalities for early detection of pancreatic cancer have been among the academic concerns. On account of the potential role of immunohistochemistry (IHC) biomarkers in overcoming certain limitations of imaging diagnostic tools in discriminating pancreatic cancer tissues from benign ones, a growing scholarly attention has been given to the diagnostic efficacy of IHC biomarkers for pancreatic cancer. This review will analyze and synthesize published articles to provide an insight into potential IHC biomarkers for pancreatic cancer diagnosis.

The exploration of quantitative intra-tumoral metabolic heterogeneity in dual-time 18F-FDG PET/CT of pancreatic cancer

PURPOSE

We aimed to analyze the change of quantitative intra-tumoral metabolic heterogeneity consisting of texture features and conventional metabolic parameters of pancreatic cancer (PC) in dual-time 2-deoxy-2(18F) fluoro-D-glucose (18F-FDG) positron emission tomography-computed tomography (PET/CT).

METHODS

A retrospective analysis was conducted considering the texture features and conventional metabolic parameters in dual-time 18F-FDG PET/CT scans of PC patients. Features were extracted based on spatial distribution of 18F-FDG uptake in image. Firstly, the texture features and the conventional metabolic parameters of the delayed scan were both compared with that of the early scan. Statistically different data was defined among them. Secondly, the study evaluated the correlations between retention index (RI) of the texture features and the conventional metabolic parameters. Finally, the variation of texture features in dual-time PET/CT of resectable PC patients and unresectable PC patients was calculated separately.

RESULTS

In total, 183 PC patients were analyzed retrospectively in this research. The conventional metabolic parameters were all statistically different between the early and delayed scans except for metabolic tumor volume (MTV). In the radiomics, there were 59 textural features. Nineteen of 59 texture features were statistically different between the early and delayed scans. Features that were more than 10% different during two scans were observed in a substantial percentage of patients. Weak correlations were only found between MTV, TLG (Total lesion glycolysis), SUVpeak and the RI of some texture features in early or delayed scans. There were obviously fewer features with significant difference in resectable PC group than in unresectable PC group. Most features showing the difference in unresectable group while no significant difference in resectable group.

CONCLUSIONS

This study investigated the change and inner correlations of quantitative tumoral metabolic heterogeneity in the dual-time 18F-FDG-PET/CT scan of PC patients. Some features displayed the difference between dual-time scans. Conventional metabolic parameters were weakly related to the change of texture feature. The change of texture feature in resectable PC group was different from that in unresectable PC group. This result is potential to provide more information for the image evaluation of PC.

Development of a standardized MRI protocol for pancreas assessment in humans

Magnetic resonance imaging (MRI) has detected changes in pancreas volume and other characteristics in type 1 and type 2 diabetes. However, differences in MRI technology and approaches across locations currently limit the incorporation of pancreas imaging into multisite trials. The purpose of this study was to develop a standardized MRI protocol for pancreas imaging and to define the reproducibility of these measurements. Calibrated phantoms with known MRI properties were imaged at five sites with differing MRI hardware and software to develop a harmonized MRI imaging protocol. Subsequently, five healthy volunteers underwent MRI at four sites using the harmonized protocol to assess pancreas size, shape, apparent diffusion coefficient (ADC), longitudinal relaxation time (T1), magnetization transfer ratio (MTR), and pancreas and hepatic fat fraction. Following harmonization, pancreas size, surface area to volume ratio, diffusion, and longitudinal relaxation time were reproducible, with coefficients of variation less than 10%. In contrast, non-standardized image processing led to greater variation in MRI measurements. By using a standardized MRI image acquisition and processing protocol, quantitative MRI of the pancreas performed at multiple locations can be incorporated into clinical trials comparing pancreas imaging measures and metabolic state in individuals with type 1 or type 2 diabetes.

Diagnosis of Pancreatic Ductal Adenocarcinoma by Immuno-Positron Emission Tomography

Diagnosis of pancreatic ductal adenocarcinoma (PDAC) by current imaging techniques is useful and widely used in the clinic but presents several limitations and challenges, especially in small lesions that frequently cause radiological tumors infra-staging, false-positive diagnosis of metastatic tumor recurrence, and common occult micro-metastatic disease. The revolution in cancer multi-"omics" and bioinformatics has uncovered clinically relevant alterations in PDAC that still need to be integrated into patients' clinical management, urging the development of non-invasive imaging techniques against principal biomarkers to assess and incorporate this information into the clinical practice. "Immuno-PET" merges the high target selectivity and specificity of antibodies and engineered fragments toward a given tumor cell surface marker with the high spatial resolution, sensitivity, and quantitative capabilities of positron emission tomography (PET) imaging techniques. In this review, we detail and provide examples of the clinical limitations of current imaging techniques for diagnosing PDAC. Furthermore, we define the different components of immuno-PET and summarize the existing applications of this technique in PDAC. The development of novel immuno-PET methods will make it possible to conduct the non-invasive diagnosis and monitoring of patients over time using in vivo, integrated, quantifiable, 3D, whole body immunohistochemistry working like a "virtual biopsy".

Improved detectability of hypoattenuating focal pancreatic lesions by dual-layer computed tomography using virtual monoenergetic images

Background

Multidetector CT is the mainstay for radiologic evaluation of pancreatic pathology. Still, imaging of focal pancreatic lesions using MDCT is faced by a number of challenges that are related to the limited contrast between the lesion and surrounding parenchyma, such as detecting early-stage pancreatic cancer and subtle features of cystic lesions that point to malignancy. Dual-layer CT is the first dual-energy CT machine based on separation of high- and low-energy photons at the detector level. If improved contrast between the lesions and normal pancreatic parenchyma could be achieved on CT images, we may expect enhanced CT detection of pancreatic lesions. The purpose of this study was to evaluate whether virtual monoenergetic reconstructions generated using contrast-enhanced dual-layer CT could improve detectability of hypoattenuating focal pancreatic lesions compared to conventional polyenergetic reconstructions.

Results

Fifty-four lesions were identified and verified by histopathology or follow-up CT, MRCP, and/or EUS along with clinical data. Across the virtual monoenergetic spectrum, 40 KeV images had the highest contrast-to-noise and signal-to-noise ratios (p < 0.001, p < 0.001) and were significantly higher than conventional images (p < 0.001). Subjective scores for lesion visibility at low kiloelectron volt monoenergetic (40 and 50 KeV) images greatly exceeded conventional images (p < 0.001).

Conclusion

Low kiloelectron volt monoenergetic reconstructions of contrast-enhanced dual-layer CT significantly improve detectability of hypoattenuating focal pancreatic lesions compared to conventional polyenergetic reconstructions.

Magnetic resonance fingerprinting of the pancreas at 1.5 T and 3.0 T

Magnetic resonance imaging of the pancreas is increasingly used as an important diagnostic modality for characterisation of pancreatic lesions. Pancreatic MRI protocols are mostly qualitative due to time constraints and motion sensitivity. MR Fingerprinting is an innovative acquisition technique that provides qualitative data and quantitative parameter maps from a single free-breathing acquisition with the potential to reduce exam times. This work investigates the feasibility of MRF parameter mapping for pancreatic imaging in the presence of free-breathing exam. Sixteen healthy participants were prospectively imaged using MRF framework. Regions-of-interest were drawn in multiple solid organs including the pancreas and T1 and T2 values determined. MRF T1 and T2 mapping was performed successfully in all participants (acquisition time:2.4-3.6 min). Mean pancreatic T1 values were 37-43% lower than those of the muscle, spleen, and kidney at both 1.5 and 3.0 T. For these organs, the mean pancreatic T2 values were nearly 40% at 1.5 T and < 12% at 3.0 T. The feasibility of MRF at 1.5 T and 3 T was demonstrated in the pancreas. By enabling fast and free-breathing quantitation, MRF has the potential to add value during the clinical characterisation and grading of pathological conditions, such as pancreatitis or cancer.

Prediction of tumour grade and survival outcome using pre-treatment PET- and MRI-derived imaging features in patients with resectable pancreatic ductal adenocarcinoma

OBJECTIVES

To perform a correlation analysis between histopathology and imaging in patients with previously untreated pancreatic ductal adenocarcinoma (PDAC) and to determine the prognostic values of clinical, histological, and imaging parameters regarding overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS).

METHODS

This single-centre study prospectively included 61 patients (32 males; median age, 68.0 years [IQR, 63.0-75.0 years]) with histologically confirmed PDAC and following surgical resection who preoperatively underwent ¹⁸F-FDG PET/CT and DW-MRI. On whole lesions, we measured, using a 42% SUV_max threshold volume of interest (VOI), the following quantitative parameters: mean and maximum standardised uptake values (SUV_mean and SUV_max), total lesion glycolysis (TLG), metabolic tumour volume (MTV), mean and minimum apparent diffusion coefficient (ADC_mean and ADC_min), diffusion total volume (DTV), and MTV/ADC_min ratio. Spearman's correlation analysis was performed to assess relationships between these markers and histopathological findings from surgical specimens (stage; grade; resection quality; and vascular, perineural, and lymphatic invasion). Kaplan-Meier and Cox hazard ratio methods were used to evaluate the impacts of imaging parameters on OS (n = 41), DSS (n = 36), and PFS (n = 41).

RESULTS

Inverse correlations between ADC_min and SUV_max (rho = - 0.34; p = 0.0071), and between SUV_mean and ADC_mean (rho = - 0.29; p = 0.026) were identified. ADC_min was inversely correlated with tumour grade (rho = - 0.40; p = 0.0015). MTV was an independent predictive factor for OS and DSS, while DTV was an independent predictive factor for PFS.

CONCLUSION

In previously untreated PDAC, ADC and SUV values are correlated. Combining PET-MRI metrics may help predict PDAC grade and patients' survival.

KEY POINTS

• Minimum apparent diffusion coefficient derived from DW-MRI inversely correlates with tumour grade in pancreatic ductal adenocarcinoma. • In pancreatic ductal adenocarcinoma, metabolic tumour volume has been confirmed as a predictive factor for patients' overall survival and disease-specific survival. • Combining PET and MRI metrics may help predict grade and patients' survival in pancreatic ductal adenocarcinoma.

Imaging diagnosis and staging of pancreatic ductal adenocarcinoma: a comprehensive review

Pancreatic ductal adenocarcinoma (PDAC) has continued to have a poor prognosis for the last few decades in spite of recent advances in different imaging modalities mainly due to difficulty in early diagnosis and aggressive biological behavior. Early PDAC can be missed on CT due to similar attenuation relative to the normal pancreas, small size, or hidden location in the uncinate process. Tumor resectability and its contingency on the vascular invasion most commonly assessed with multi-phasic thin-slice CT is a continuously changing concept, particularly in the era of frequent neoadjuvant therapy. Coexistent celiac artery stenosis may affect the surgical plan in patients undergoing pancreaticoduodenectomy. In this review, we discuss the challenges related to the imaging of PDAC. These include radiological and clinical subtleties of the tumor, evolving imaging criteria for tumor resectability, preoperative diagnosis of accompanying celiac artery stenosis, and post-neoadjuvant therapy imaging. For each category, the key imaging features and potential pitfalls on cross-sectional imaging will be discussed. Also, we will describe the imaging discriminators of potential mimickers of PDAC.

Pancreas Solid Tumors

Solid tumors of the pancreas encompass a variety of diagnoses with treatments ranging from observation to major abdominal surgery. Pancreatic ductal adenocarcinoma remains one of the most common and most lethal of these differential of diagnoses and requires a multimodality approach through a multidisciplinary team of specialists. This article reviews the classification, clinical presentation, and workup in differentiating solid tumors of the pancreas and serves as an additional tool for general surgeons faced with such a clinical finding, from a surgical oncology perspective.

Pancreatic Adenocarcinoma: Epidemiology, Role of EUS in Diagnosis, Role of ERCP, Endoscopic Palliation

Pancreatic cancer is the seventh leading cause of cancer deaths worldwide and is associated with a poor survival rate. The vast majority of pancreatic cancers are inoperable at the time of diagnosis. In the absence of metastatic disease, operability depends on the extent of local disease; in particular, the presence or absence of vascular and lymph node involvement. Adequate staging is vital in deciding an appropriate treatment plan. Cross sectional imaging including CT, MRI and PET-CT are commonly used for staging. However, EUS is a useful adjunct for accurate loco-regional staging in addition to allowing diagnostic tissue samples to be obtained. Emerging EUS-guided therapeutic techniques have opened up new horizons in the management of pancreatic malignancy. EUS guidance can be used for coeliac plexus neurolysis in patients with intractable pain and fiducial placement in directing stereotactic radiotherapy. The majority of patients with cancer of the pancreatic head present with biliary obstruction. ERCP can be used to drain the obstructed biliary system with plastic or metal stents and offers an opportunity to confirm the diagnosis by obtaining brush cytology and forceps biopsy specimens. EUS-guided choledocho-duodenostomy or hepatico-gastrostomy is increasingly being employed for draining the biliary system if ERCP is unsuccessful.

Pitfalls in the MDCT of pancreatic cancer: strategies for minimizing errors

Multidetector computed tomography (MDCT) is a widely used cross-sectional imaging modality for initial evaluation of patients with suspected pancreatic ductal adenocarcinoma (PDAC). However, diagnosis of PDAC can be challenging due to numerous pitfalls associated with image acquisition and interpretation, including technical factors, imaging features, and cognitive errors. Accurate diagnosis requires familiarity with these pitfalls, as these can be minimized using systematic strategies. Suboptimal acquisition protocols and other technical errors such as motion artifacts and incomplete anatomical coverage increase the risk of misdiagnosis. Interpretation of images can be challenging due to intrinsic tumor features (including small and isoenhancing masses, exophytic masses, subtle pancreatic duct irregularities, and diffuse tumor infiltration), presence of coexisting pathology (including chronic pancreatitis and intraductal papillary mucinous neoplasm), mimickers of PDAC (including focal fatty infiltration and focal pancreatitis), distracting findings, and satisfaction of search. Awareness of pitfalls associated with the diagnosis of PDAC along with the strategies to avoid them will help radiologists to minimize technical and interpretation errors. Cognizance and mitigation of these errors can lead to earlier PDAC diagnosis and ultimately improve patient prognosis.

Chronic Pancreatitis or Pancreatic Tumor? A Problem-solving Approach

Certain inflammatory pancreatic abnormalities may mimic pancreatic ductal adenocarcinoma at imaging, which precludes accurate preoperative diagnosis and may lead to unnecessary surgery. Inflammatory conditions that may appear masslike include mass-forming chronic pancreatitis, focal autoimmune pancreatitis, and paraduodenal pancreatitis or "groove pancreatitis." In addition, obstructive chronic pancreatitis can mimic an obstructing ampullary mass or main duct intraductal papillary mucinous neoplasm. Secondary imaging features such as the duct-penetrating sign, biliary or main pancreatic duct skip strictures, a capsulelike rim, the pancreatic duct-to-parenchyma ratio, displaced calcifications in patients with chronic calcific pancreatitis, the "double duct" sign, and vessel encasement or displacement can help to suggest the possibility of an inflammatory mass or a neoplastic process. An awareness of the secondary signs that favor a diagnosis of malignant or inflammatory lesions in the pancreas can help the radiologist to perform the differential diagnosis and determine the degree of suspicion for malignancy. Repeat biopsy or surgical resection may be necessary to achieve an accurate diagnosis and prevent unnecessary surgery for inflammatory conditions. Online supplemental material and DICOM image stacks are available for this article. ^©RSNA, 2019.

Design of an immunohistochemistry biomarker panel for diagnosis of pancreatic adenocarcinoma

BACKGROUND

Challenges still exist in differentiating pancreatic adenocarcinoma from benign disease. The use of adjuvant testing of tissue biopsies has demonstrated potential diagnostic value. We designed a proof of concept study to first validate four individual immunohistochemistry biomarkers and then combine them into a panel to boost overall diagnostic sensitivity.

METHODS

Malignant and benign pancreas from 27 pancreaticoduodenectomy specimens underwent immunohistochemistry staining with VHL, IMP3, S100A4, S100P. Using ROC curve analysis, threshold criteria for number of cells staining were chosen for each biomarker. Biomarkers were then evaluated as a panel for their ability to discriminate malignant from benign specimens.

RESULTS

Diagnostic sensitivity of VHL, IMP3, S100A4, and S100P were 75.0%, 79.2%, 45.8%, and 0%. When VHL, IMP3, and S100A4 were grouped into a panel, they were able to distinguish cancer from normal tissue with a sensitivity of 100% and a specificity of 96%.

CONCLUSIONS

The high diagnostic value of an IHC panel consisting of VHL, IMP3, and S100A4 on surgical specimens suggests the need for future prospective studies of these biomarkers on biopsy specimens.

Measurement of T1 and T2 relaxation times of the pancreas at 7 T using a multi-transmit system

Objective

To determine T₁ and T₂ relaxation times of healthy pancreas parenchyma at 7 T using a multi-transmit system.

Materials and methods

Twenty-six healthy subjects were scanned with a 7 T MR system using eight parallel transceiver antennas, each with two additional receive loops. A Look-Locker sequence was used to obtain images for T₁ determination, while T₂ was obtained from spin-echo images and magnetic resonance spectroscopy measurements with different echo times. T₁ and T₂ times were calculated using a mono-exponential fit of the average magnitude signal from a region of interest in the pancreas and were tested for correlation with age.

Results

The age range of the included subjects was 21–72 years. Average T₁ and T₂ relaxation times in healthy pancreas were 896 ± 149 ms, and 26.7 ± 5.3 ms, respectively. No correlation with age was found.

Conclusion

T₁ and T₂ relaxation times of the healthy pancreas were reported for 7 T, which can be used for image acquisition optimization. No significant correlations were found between age and T₁ or T₂ relaxation times of the pancreas. Considering their low standard deviation and no observable age dependence, these values may be used as a baseline to study potentially pancreatic tissue affected by disease.

CT response of primary tumor and CA19-9 predict resectability of metastasized pancreatic cancer after FOLFIRINOX

BACKGROUND

Effective chemotherapy protocols are currently changing the treatment options for metastasized pancreatic cancer. Survival benefits after synchronous metastasectomy have been reported for selected patients. We set out to assess predictive factors of resectability for synchronous metastases after FOLFIRINOX.

METHODS

Consecutive patients with metastatic pancreatic cancer undergoing surgery after FOLFIRINOX between 2011 and 2017 were identified from a prospectively collected database. Surgery following chemotherapy was indicated in patients with no more than six metastatic lesions, no progression detected on CT, and technically resectable disease. Patients who received synchronous metastasectomy were compared with patients who received explorative laparotomy or palliative surgery in terms of predictors of resectability and overall survival. In patients undergoing resection, prognostic factors were examined.

RESULTS

Of 101 patients scheduled for surgery after FOLFIRINOX, synchronous metastasectomy was performed in 43 cases (43%) and non-resection surgery in 58 cases (57%). The shrinkage rate of the primary tumor on CT (P = 0.04) and the postchemotherapy serum CA19-9 concentration (P = 0.02) were associated with resectability. The median overall survival of the patients undergoing metastasectomy was longer than that of the patients without resection (21.9 months vs 16.4 months, P = 0.006). Postchemotherapy serum CA19-9 value (P = 0.04) and lymph node ratio (P = 0.01) were prognostic factors in the patients undergoing metastasectomy.

CONCLUSIONS

In selected patients who satisfied our surgical criteria, shrinkage rate of primary tumor and postchemotherapy serum CA19-9 level, which predict resectability of metastasized pancreatic cancer, should be considered in decision making to avoid unnecessary surgery.

Incidence and risk factors for abdominal occult metastatic disease in patients with pancreatic adenocarcinoma

BACKGROUND

The incidence of occult metastatic disease (OMD) in pancreatic ductal adenocarcinoma (PDAC) and associated risk factors are largely unknown.

METHODS

We identified all patients with PDAC, who had an aborted oncologic operation due to OMD within a 10-year period. The cases were matched to a cohort of resected PDAC patients on a 1:3 ratio, based on age and sex, for comparison of preoperative clinical characteristics and potential risk factors for OMD.

RESULTS

In the studied period, 117 patients with OMD were identified in 1423 pancreatectomies performed for PDAC (8%). Liver metastases were the most common finding (79%) followed by peritoneal implants (16%). When compared with non-OMD cases, patients with OMD presented more often with abdominal pain (P < 0.001), and higher preoperative carbohydrate antigen 19-9 (CA 19-9) values ( P = 0.007). Additionally, indeterminate liver lesions on preoperative computed tomography (CT) were identified in 40% of OMD versus 17% of non-OMD patients ( P < 0.001). Multivariable analysis distinguished four independent predictors for OMD: indeterminate lesions on preoperative CT, tumor size > 30 mm, abdominal pain, and preoperative CA 19-9 > 192 U/mL.

CONCLUSIONS

Occurrence of OMD in PDAC accounts for 8% of cases. Preoperative CA 19-9 > 192 U/mL, primary tumor size > 30 mm, and identification of indeterminate lesions in preoperative CT may indicate the need for diagnostic laparoscopy.

Advances in Diagnostic and Intraoperative Molecular Imaging of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis. To improve outcomes, there is a critical need for improved tools for detection, accurate staging, and resectability assessment. This could improve patient stratification for the most optimal primary treatment modality. Molecular imaging, used in combination with tumor-specific imaging agents, can improve established imaging methods for PDAC. These novel, tumor-specific imaging agents developed to target specific biomarkers have the potential to specifically differentiate between malignant and benign diseases, such as pancreatitis. When these agents are coupled to various types of labels, this type of molecular imaging can provide integrated diagnostic, noninvasive imaging of PDAC as well as image-guided pancreatic surgery. This review provides a detailed overview of the current clinical imaging applications, upcoming molecular imaging strategies for PDAC, and potential targets for imaging, with an emphasis on intraoperative imaging applications.

Does Second Reader Opinion Affect Patient Management in Pancreatic Ductal Adenocarcinoma?

RATIONALE AND OBJECTIVES

To determine the impact of second-opinion assessment on cancer staging and patient management in patients with pancreatic ductal adenocarcinoma.

METHODS AND MATERIALS

This retrospective study was approved by our institutional review board with a waiver of informed consent. Second-opinion reports between January 1, 2009 and December 31, 2013, alongside outside reports for 65 consecutive cases of biopsy-proven pancreatic adenocarcinomas, were presented in random order to two experienced abdominal surgeons who independently reviewed them blinded to the origin of the report, images of the examinations, and patient identifier. Each surgeon filled in a questionnaire for each report recommending cancer staging and patient management. Recommended patient management and staging were evaluated against reference standards (actual patient management at 6 months following second-opinion assessment, and pathology or other clinical and imaging reference standards at 6 months or longer, respectively) using Cohen kappa.

RESULTS

Cancer staging differed in 13% (9 of 65) of cases for surgeon 1 and in 18.4% (12 of 65) for surgeon 2. Patient management changed in 38.4% (25 of 65) of cases for surgeon 1 and in 20% (13 of 65) for surgeon 2. When compared to the pathologic staging gold standard, second opinion was correct in 85.7% (six of seven) of the time for both surgeons. Recommended patient management from second-opinion reports showed good agreement with the reference standard (weighted k = 0.6467 [0.4014-0.892] and weighted k = 0.6262 [0.3954-0.857] for surgeon 2).

CONCLUSION

Second-opinion review by subspecialized oncologic radiologists can impact patient care, specifically in terms of management decision.

Glycoprotein biomarkers for the detection of pancreatic ductal adenocarcinoma

Pancreatic cancer (PaC) shows a clear tendency to increase in the next years and therefore represents an important health and social challenge. Currently, there is an important need to find biomarkers for PaC early detection because the existing ones are not useful for that purpose. Recent studies have indicated that there is a large window of time for PaC early detection, which opens the possibility to find early biomarkers that could greatly improve the dismal prognosis of this tumor. The present manuscript reviews the state of the art of the existing PaC biomarkers. It focuses on the anomalous glycosylation process and its role in PaC. Glycan structures of glycoconjugates such as glycoproteins are modified in tumors and these modifications can be detected in biological fluids of the cancer patients. Several studies have found serum glycoproteins with altered glycan chains in PaC patients, but they have not shown enough specificity for PaC. To find more specific cancer glycoproteins we propose to analyze the glycan moieties of a battery of glycoproteins that have been reported to increase in PaC tissues and that can also be found in serum. The combination of these new candidate glycoproteins with their aberrant glycosylation together with the existing biomarkers could result in a panel, which would expect to give better results as a new tool for early diagnosis of PaC and to monitor the disease.

Challenges in diagnosis of pancreatic cancer

Pancreatic cancer is a growing source of cancer related death, yet has poor survival rates which have not improved in the last few decades. Its high mortality rate is attributed to pancreatic cancer biology, difficulty in early diagnosis and the lack of standardised international guidelines in assessing suspicious pancreatic masses. This review aims to provide an update in the current state of play in pancreatic cancer diagnosis and to evaluate the benefits and limitations of available diagnostic technology. The main modalities discussed are imaging with computed tomography, magnetic resonance imaging, endoscopic ultrasound and positron emission tomography and tissue acquisition with fine needle aspiration. We also review the improvements in the techniques used for tissue acquisition and the opportunity for personalised cancer medicine. Screening of high risk individuals, promising biomarkers and common mimickers of pancreatic cancer are also explored, as well as suggestions for future research directions to allow for earlier detection of pancreatic cancer. Timely and accurate diagnosis of pancreatic cancer can lead to improvements in the current poor outcome of this disease.

Incremental Role of Pancreatic Magnetic Resonance Imaging after Staging Computed Tomography to Evaluate Patients with Pancreatic Ductal Adenocarcinoma

Purpose

The purpose of this study was to investigate the impact of contrast enhanced pancreatic magnetic resonance imaging (MRI) in resectability and prognosis evaluation after staging computed tomography (CT) in patients with pancreatic ductal adenocarcinoma (PDA).

Materials and Methods

From January 2005 to December 2012, 298 patients were diagnosed to have potentially resectable stage PDA on CT. Patients were divided into CT+MR (patients underwent both CT and MRI; n=216) and CT only groups (n=82). Changes in resectability staging in the CT+MR group were evaluated. The overall survival was compared between the two groups. The recurrence-free survival and median time to liver metastasis after curative surgery were compared between the two groups.

Results

Staging was changed from resectable on CT to unresectable state on MRI in 14.4% of (31 of 216 patients) patients of the CT+MR group. The overall survival and recurrence-free survival rates were not significantly different between the two groups (p=0.162 and p=0.721, respectively). The median time to liver metastases after curative surgery in the CT+MR group (9.9 months) was significantly longer than that in the CT group (4.2 months) (p=0.011).

Conclusion

Additional MRI resulted in changes of resectability and treatment modifications in a significant proportion of patients who have potentially resectable state at CT and in prolonged time to liver metastases in patients after curative surgery. Additional MRI to standard staging CT can be recommended for surgical candidates of PDA.

Characterizing indeterminate liver lesions in patients with localized pancreatic cancer at the time of diagnosis

BACKGROUND

In patients with newly diagnosed pancreatic cancer, the classification of indeterminate liver lesions is an unanswered clinical dilemma as misclassification of these lesions can impact the assignment of clinical stage and subsequent treatment planning. Our objective was to design a standardized classification system to more accurately define the risk of malignancy in indeterminate liver lesions.

METHODS

In this retrospective study, patients with localized, non-metastatic pancreatic cancer were identified and pre-treatment computed tomography (CT) scans were evaluated for the presence or absence of liver lesions. Liver lesions were defined as definitely benign (1) or indeterminate (2). Indeterminate lesions were further sub-classified as either indeterminate probably benign (2B) or indeterminate possibly malignant (2M). The index liver lesion was evaluated on follow-up imaging for stability or unequivocal disease progression.

RESULTS

From 2008 to 2015, 304 patients with localized, non-metastatic pancreatic cancer were identified and 125 (41%) patients had liver lesions. Of the 125 patients, the liver lesions in 35 (28%) were classified as definitely benign and in 90 (72%) patients they were classified as indeterminate. The 90 patients with indeterminate lesions included 80 (89%) classified as indeterminate probably benign (2B) and 10 (11%) classified as indeterminate possibly malignant (2M). After a median follow-up of 56 weeks, no patient with a definitely benign lesion had metastatic disease progression of the index lesion. Of the 90 patients with indeterminate liver lesions, the index lesion progressed to unequivocal liver metastasis in 8 (9%) patients; 5 (6%) of the 80 lesions classified as indeterminate probably benign (2B), and 3 (30%) of the ten lesions classified as indeterminate possibly malignant (2M). The sensitivity of the classification system was 38% and the specificity was 91%. The positive predictive value was 30% and the negative predictive value was 94%.

CONCLUSIONS

A significant proportion of patients with localized pancreatic cancer will have liver lesions identified at the time of diagnosis and most of these lesions will have indeterminate characteristics. A classification system which further stratifies indeterminate liver lesions by malignant potential can assist clinicians in determining optimal treatment plan and is associated with a high negative predictive value.

Neoadjuvant treatment for borderline and resectable pancreatic ductal adenocarcinoma

Nowadays and given the improvement in response rate with the new schemes of treatment with chemotherapy, the interest in neoadjuvant treatment for pancreatic ductal adenocarcinoma, allowing the early application of systemic therapies, has also increased. However, treatment selection fundamentally depends on decisions taken by multidisciplinary committees due to the absence of randomized trials on this indication and because the available evidence is based primarily on small studies. The present manuscript tries to establish recommendations based on the available evidence and expert opinion to correctly select the indication, the type of treatment, as well as its duration and how to correctly follow-up patients during treatment with chemotherapy.