Precursor Epithelial Subtypes of Adenocarcinoma Arising from Intraductal Papillary Mucinous Neoplasms (A-IPMN): Clinicopathological Features, Recurrence and Response to Adjuvant Chemotherapy.

BACKGROUND: The clinico-oncological outcomes of precursor epithelial subtypes of adenocarcinoma arising from intraductal papillary mucinous neoplasms (A-IPMN) are limited to small cohort studies. Differences in recurrence patterns and response to adjuvant chemotherapy between A-IPMN subtypes are unknown. METHODS: Clincopathological features, recurrence patterns and long-term outcomes of patients undergoing pancreatic resection (2010-2020) for A-IPMN were reported from 18 academic pancreatic centres worldwide. Precursor epithelial subtype groups were compared using uni- and multivariate analysis. RESULTS: In total, 297 patients were included (median age, 70 years; male, 78.9%), including 54 (18.2%) gastric, 111 (37.3%) pancreatobiliary, 80 (26.9%) intestinal and 52 (17.5%) mixed subtypes. Gastric, pancreaticobiliary and mixed subtypes had comparable clinicopathological features, yet the outcomes were significantly less favourable than the intestinal subtype. The median time to recurrence in gastric, pancreatobiliary, intestinal and mixed subtypes were 32, 30, 61 and 33 months. Gastric and pancreatobiliary subtypes had worse overall recurrence (p = 0.048 and p = 0.049, respectively) compared with the intestinal subtype but gastric and pancreatobiliary subtypes had comparable outcomes. Adjuvant chemotherapy was associated with improved survival in the pancreatobiliary subtype (p = 0.049) but not gastric (p = 0.992), intestinal (p = 0.852) or mixed subtypes (p = 0.723). In multivariate survival analysis, adjuvant chemotherapy was associated with a lower likelihood of death in pancreatobiliary subtype, albeit with borderline significance [hazard ratio (HR) 0.56; 95% confidence interval (CI) 0.31-1.01; p = 0.058]. CONCLUSIONS: Gastric, pancreatobiliary and mixed subtypes have comparable recurrence and survival outcomes, which are inferior to the more indolent intestinal subtype. Pancreatobiliary subtype may respond to adjuvant chemotherapy and further research is warranted to determine the most appropriate adjuvant chemotherapy regimens for each subtype.

The Society for Cardiovascular Magnetic Resonance Registry at 150,000.

OBJECTIVES: To summarize the status of the SCMR Registry at 150,000 exams. BACKGROUND: Cardiovascular magnetic resonance (CMR) is increasingly utilized to evaluate expanding cardiovascular conditions. The SCMR Registry is a central repository for real-world clinical data to support cardiovascular research, including those relating to outcomes, quality improvement, and machine learning. The SCMR Registry is built on a regulatory-compliant, cloud-based infrastructure that houses searchable content and Digital Imaging and Communications in Medicine (DICOM) images. METHODS: The processes for data security, data submission, and research access are outlined. We interrogated the Registry and present a summary of its contents. RESULTS: Data were compiled from 154,458 CMR scans across 20 United States sites, containing 299,622,066 total images (~100 terabytes of storage). The human subjects had an average age of 58 years (range 1 month to >90 years old), were 44% female, 72% Caucasian, and had a mortality rate of 8%. The most common indication was cardiomyopathy (27%), and most frequently used current procedural terminology (CPT) code was 75561 (35%). Macrocyclic gadolinium-based contrast agents represented 89% of contrast utilization after 2015. Short-axis cines were performed in 99% of scans, short-axis LGE in 66%, and stress perfusion sequences in 30%. Mortality data demonstrated increased mortality in patients with left ventricular ejection fraction (LVEF) < 35%, the presence of wall motion abnormalities, stress perfusion defects, and infarct late gadolinium enhancement (LGE), compared to those without these markers. There were 456,678 patient-years of all-cause mortality follow-up, with a median follow-up time of 3.6 years. CONCLUSIONS: The vision of the SCMR Registry is to promote evidence-based utilization of CMR through a collaborative effort by providing a web mechanism for centers to securely upload de-identified data and images for research, education, and quality control. The Registry quantifies changing practice over time and supports large-scale real-world multicenter observational studies of prognostic utility. CONDENSED ABSTRACT: The SCMR Registry is a central regulatory-compliant cloud-based repository for real-world clinical data and DICOM images for multicenter cardiovascular research, including outcomes-based data. The Registry contains 299,622,066 DICOM images and 456,678 patient-years follow-up. Data compiled from 154,458 CMR scans across 20 US sites demonstrated cardiomyopathy as the most common indication and 89% macrocyclic gadolinium contrast utilization after 2015. There was an overall mortality rate of 8%, with higher rates in those with LVEF<35%, abnormal wall motion, ischemia presence, or infarct LGE. The Registry aims to promote evidence-based CMR utilization through a collaborative effort to positively impact cardiovascular outcomes.

Predictors of long-term survival after resection of adenocarcinoma arising from intraductal papillary mucinous neoplasm and derivation of a prognostic model: An international multicenter study (ADENO-IPMN study).

BACKGROUND: Predictors of long-term survival after resection of adenocarcinoma arising from intraductal papillary mucinous neoplasms are unknown. This study determines predictors of long-term (>5 years) disease-free survival and recurrence in adenocarcinoma arising from intraductal papillary mucinous neoplasms and derives a prognostic model for disease-free survival. METHODS: Consecutive patients who underwent pancreatic resection for adenocarcinoma arising from intraductal papillary mucinous neoplasms in 18 academic pancreatic centers in Europe and Asia between 2010 to 2017 with at least 5-year follow-up were identified. Factors associated with disease-free survival were determined using Cox proportional hazards model. Internal validation was performed, and discrimination and calibration indices were assessed. RESULTS: In the study, 288 patients (median age, 70 years; 52% male) were identified; 140 (48%) patients developed recurrence after a median follow-up of 98 months (interquartile range, 78.4-123), 57 patients (19.8%) developed locoregional recurrence, and 109 patients (37.8%) systemic recurrence. At 5 years after resection, the overall and disease-free survival was 46.5% (134/288) and 35.0% (101/288), respectively. On Cox proportional hazards model analysis, multivisceral resection (hazard ratio, 2.20; 95% confidence interval, 1.06-4.60), pancreatic tail location (hazard ratio, 2.34; 95% confidence interval, 1.22-4.50), poor tumor differentiation (hazard ratio, 2.48; 95% confidence interval, 1.10-5.30), lymphovascular invasion (hazard ratio, 1.74; 95% confidence interval, 1.06-2.88), and perineural invasion (hazard ratio, 1.83; 95% confidence interval, 1.09-3.10) were negatively associated with long-term disease-free survival. The final predictive model incorporated 8 predictors and demonstrated good predictive ability for disease-free survival (C-index, 0.74; calibration, slope 1.00). CONCLUSION: A third of patients achieve long-term disease-free survival (>5 years) after pancreatic resection for adenocarcinoma arising from intraductal papillary mucinous neoplasms. The predictive model developed in the current study can be used to estimate the probability of long-term disease-free survival.

Evaluation of left ventricular filling pressure by echocardiography in patients with atrial fibrillation.

BACKGROUND: Echocardiography is widely used to evaluate left ventricular (LV) diastolic function in patients suspected of heart failure. For patients in sinus rhythm, a combination of several echocardiographic parameters can differentiate between normal and elevated LV filling pressure with good accuracy. However, there is no established echocardiographic approach for the evaluation of LV filling pressure in patients with atrial fibrillation. The objective of the present study was to determine if a combination of several echocardiographic and clinical parameters may be used to evaluate LV filling pressure in patients with atrial fibrillation. RESULTS: In a multicentre study of 148 atrial fibrillation patients, several echocardiographic parameters were tested against invasively measured LV filling pressure as the reference method. No single parameter had sufficiently strong association with LV filling pressure to be recommended for clinical use. Based on univariate regression analysis in the present study, and evidence from existing literature, we developed a two-step algorithm for differentiation between normal and elevated LV filling pressure, defining values ≥ 15 mmHg as elevated. The parameters in the first step included the ratio between mitral early flow velocity and septal mitral annular velocity (septal E/e'), mitral E velocity, deceleration time of E, and peak tricuspid regurgitation velocity. Patients who could not be classified in the first step were tested in a second step by applying supplementary parameters, which included left atrial reservoir strain, pulmonary venous systolic/diastolic velocity ratio, and body mass index. This two-step algorithm classified patients as having either normal or elevated LV filling pressure with 75% accuracy and with 85% feasibility. Accuracy in EF ≥ 50% and EF < 50% was similar (75% and 76%). CONCLUSIONS: In patients with atrial fibrillation, no single echocardiographic parameter was sufficiently reliable to be used clinically to identify elevated LV filling pressure. An algorithm that combined several echocardiographic parameters and body mass index, however, was able to classify patients as having normal or elevated LV filling pressure with moderate accuracy and high feasibility.

Evaluation of Deep Learning Estimation of Whole Heart Anatomy from Automated Cardiovascular Magnetic Resonance Short- and Long-Axis Analyses in UK Biobank.

AIMS: Standard methods of heart chamber volume estimation in cardiovascular magnetic resonance (CMR) typically utilize simple geometric formulae based on a limited number of slices. We aimed to evaluate whether an automated deep learning neural network prediction of 3D anatomy of all four chambers would show stronger associations with cardiovascular risk factors and disease than standard volume estimation methods in the UK Biobank. METHODS: A deep learning network was adapted to predict 3D segmentations of left and right ventricles (LV, RV) and atria (LA, RA) at ∼1mm isotropic resolution from CMR short and long axis 2D segmentations obtained from a fully automated machine learning pipeline in 4723 individuals with cardiovascular disease (CVD) and 5733 without in the UK Biobank. Relationships between volumes at end-diastole (ED) and end-systole (ES) and risk/disease factors were quantified using univariate, multivariate and logistic regression analyses. Strength of association between deep learning volumes and standard volumes was compared using the area under the receiving operator characteristic curve (AUC). RESULTS: Univariate and multivariate associations between deep learning volumes and most risk and disease factors were stronger than for standard volumes (higher R2 and more significant P values), particularly for sex, age, and body mass index. AUC for all logistic regressions were higher for deep learning volumes than standard volumes (p<0.001 for all four chambers at ED and ES). CONCLUSIONS: Neural network reconstructions of whole heart volumes had significantly stronger associations with cardiovascular disease and risk factors than standard volume estimation methods in an automatic processing pipeline.

A three-dimensional left atrial motion estimation from retrospective gated computed tomography: application in heart failure patients with atrial fibrillation.

Background: A reduced left atrial (LA) strain correlates with the presence of atrial fibrillation (AF). Conventional atrial strain analysis uses two-dimensional (2D) imaging, which is, however, limited by atrial foreshortening and an underestimation of through-plane motion. Retrospective gated computed tomography (RGCT) produces high-fidelity three-dimensional (3D) images of the cardiac anatomy throughout the cardiac cycle that can be used for estimating 3D mechanics. Its feasibility for LA strain measurement, however, is understudied. Aim: The aim of this study is to develop and apply a novel workflow to estimate 3D LA motion and calculate the strain from RGCT imaging. The utility of global and regional strains to separate heart failure in patients with reduced ejection fraction (HFrEF) with and without AF is investigated. Methods: A cohort of 30 HFrEF patients with (n = 9) and without (n = 21) AF underwent RGCT prior to cardiac resynchronisation therapy. The temporal sparse free form deformation image registration method was optimised for LA feature tracking in RGCT images and used to estimate 3D LA endocardial motion. The area and fibre reservoir strains were calculated over the LA body. Universal atrial coordinates and a human atrial fibre atlas enabled the regional strain calculation and the fibre strain calculation along the local myofibre orientation, respectively. Results: It was found that global reservoir strains were significantly reduced in the HFrEF + AF group patients compared with the HFrEF-only group patients (area strain: 11.2 ± 4.8% vs. 25.3 ± 12.6%, P = 0.001; fibre strain: 4.5 ± 2.0% vs. 15.2 ± 8.8%, P = 0.001), with HFrEF + AF patients having a greater regional reservoir strain dyssynchrony. All regional reservoir strains were reduced in the HFrEF + AF patient group, in whom the inferior wall strains exhibited the most significant differences. The global reservoir fibre strain and LA volume + posterior wall reservoir fibre strain exceeded LA volume alone and 2D global longitudinal strain (GLS) for AF classification (area-under-the-curve: global reservoir fibre strain: 0.94 ± 0.02, LA volume + posterior wall reservoir fibre strain: 0.95 ± 0.02, LA volume: 0.89 ± 0.03, 2D GLS: 0.90 ± 0.03). Conclusion: RGCT enables 3D LA motion estimation and strain calculation that outperforms 2D strain metrics and LA enlargement for AF classification. Differences in regional LA strain could reflect regional myocardial properties such as atrial fibrosis burden.

Adjuvant chemotherapy for adenocarcinoma arising from intraductal papillary mucinous neoplasia: multicentre ADENO-IPMN study.

BACKGROUND: The clinical impact of adjuvant chemotherapy after resection for adenocarcinoma arising from intraductal papillary mucinous neoplasia is unclear. The aim of this study was to identify factors related to receipt of adjuvant chemotherapy and its impact on recurrence and survival. METHODS: This was a multicentre retrospective study of patients undergoing pancreatic resection for adenocarcinoma arising from intraductal papillary mucinous neoplasia between January 2010 and December 2020 at 18 centres. Recurrence and survival outcomes for patients who did and did not receive adjuvant chemotherapy were compared using propensity score matching. RESULTS: Of 459 patients who underwent pancreatic resection, 275 (59.9%) received adjuvant chemotherapy (gemcitabine 51.3%, gemcitabine-capecitabine 21.8%, FOLFIRINOX 8.0%, other 18.9%). Median follow-up was 78 months. The overall recurrence rate was 45.5% and the median time to recurrence was 33 months. In univariable analysis in the matched cohort, adjuvant chemotherapy was not associated with reduced overall (P = 0.713), locoregional (P = 0.283) or systemic (P = 0.592) recurrence, disease-free survival (P = 0.284) or overall survival (P = 0.455). Adjuvant chemotherapy was not associated with reduced site-specific recurrence. In multivariable analysis, there was no association between adjuvant chemotherapy and overall recurrence (HR 0.89, 95% c.i. 0.57 to 1.40), disease-free survival (HR 0.86, 0.59 to 1.30) or overall survival (HR 0.77, 0.50 to 1.20). Adjuvant chemotherapy was not associated with reduced recurrence in any high-risk subgroup (for example, lymph node-positive, higher AJCC stage, poor differentiation). No particular chemotherapy regimen resulted in superior outcomes. CONCLUSION: Chemotherapy following resection of adenocarcinoma arising from intraductal papillary mucinous neoplasia does not appear to influence recurrence rates, recurrence patterns or survival.

Hybrid artificial intelligence outcome prediction using features extraction from stress perfusion cardiac magnetic resonance images and electronic health records.

Background: Prediction of clinical outcomes in coronary artery disease (CAD) has been conventionally achieved using clinical risk factors. The relationship between imaging features and outcome is still not well understood. This study aims to use artificial intelligence to link image features with mortality outcome. Methods: A retrospective study was performed on patients who had stress perfusion cardiac magnetic resonance (SP-CMR) between 2011 and 2021. The endpoint was all-cause mortality. Convolutional neural network (CNN) was used to extract features from stress perfusion images, and multilayer perceptron (MLP) to extract features from electronic health records (EHRs), both networks were concatenated in a hybrid neural network (HNN) to predict study endpoint. Image CNN was trained to predict study endpoint directly from images. HNN and image CNN were compared with a linear clinical model using area under the curve (AUC), F1 scores, and McNemar's test. Results: Total of 1,286 cases were identified, with 201 death events (16%). The clinical model had good performance (AUC =80%, F1 score =37%). Best Image CNN model showed AUC =72% and F1 score =38%. HNN outperformed the other two models (AUC =82%, F1 score =43%). McNemar's test showed statistical difference between image CNN and both clinical model (P<0.01) and HNN (P<0.01). There was no significant difference between HNN and clinical model (P=0.15). Conclusions: Death in patients with suspected or known CAD can be predicted directly from stress perfusion images without clinical knowledge. Prediction can be improved by HNN that combines clinical and SP-CMR images.

Long-term Outcomes following Resection of Adenocarcinoma Arising from Intraductal Papillary Mucinous Neoplasm (A-IPMN) versus Pancreatic Ductal Adenocarcinoma (PDAC): A Propensity-score Matched Analysis.

OBJECTIVE: The aim of the present study was to compare long-term post-resection oncological outcomes between A-IPMN and PDAC. SUMMARY BACKGROUND DATA: Knowledge of long term oncological outcomes (e.g recurrence and survival data) comparing between adenocarcinoma arising from intraductal papillary mucinous neoplasms (A-IPMN) and pancreatic ductal adenocarcinoma (PDAC) is scarce. METHODS: Patients undergoing pancreatic resection (2010-2020) for A-IPMN were identified retrospectively from 18 academic pancreatic centres and compared with PDAC patients from the same time-period. Propensity-score matching (PSM) was performed and survival and recurrence were compared between A-IPMN and PDAC. RESULTS: 459 A-IPMN patients (median age,70; M:F,250:209) were compared with 476 PDAC patients (median age,69; M:F,262:214). A-IPMN patients had lower T-stage, lymphovascular invasion (51.4%vs. 75.6%), perineural invasion (55.8%vs. 71.2%), lymph node positivity (47.3vs. 72.3%) and R1 resection (38.6%vs. 56.3%) compared to PDAC(P<0.001). The median survival and time-to-recurrence for A-IPMN versus PDAC were 39.0 versus19.5months (P<0.001) and 33.1 versus 14.8months (P<0.001), respectively (median follow-up,78 vs.73 months). Ten-year overall survival for A-IPMN was 34.6%(27/78) and PDAC was 9%(6/67). A-IPMN had higher rates of peritoneal (23.0 vs. 9.1%, P<0.001) and lung recurrence (27.8% vs. 15.6%, P<0.001) but lower rates of locoregional recurrence (39.7% vs. 57.8%; P<0.001). Matched analysis demonstrated inferior overall survival (P=0.005), inferior disease-free survival (P=0.003) and higher locoregional recurrence (P<0.001) in PDAC compared to A-IPMN but no significant difference in systemic recurrence rates (P=0.695). CONCLUSIONS: PDACs have inferior survival and higher recurrence rates compared to A-IPMN in matched cohorts. Locoregional recurrence is higher in PDAC but systemic recurrence rates are comparable and constituted by their own distinctive site-specific recurrence patterns.

A universal biventricular coordinate system incorporating valve annuli: Validation in congenital heart disease.

Universal coordinate systems have been proposed to facilitate anatomic registration between three-dimensional images, data and models of the ventricles of the heart. However, current universal ventricular coordinate systems do not account for the outflow tracts and valve annuli where the anatomy is complex. Here we propose an extension to the 'Cobiveco' biventricular coordinate system that also accounts for the intervalvular bridges of the base and provides a tool for anatomically consistent registration between widely varying biventricular shapes. CobivecoX uses a novel algorithm to separate intervalvular bridges and assign new coordinates, including an inflow-outflow coordinate, to describe local positions in these regions uniquely and consistently. Anatomic consistency of registration was validated using curated three-dimensional biventricular shape models derived from cardiac MRI measurements in normal hearts and hearts from patients with congenital heart diseases. This new method allows the advantages of universal cardiac coordinates to be used for three-dimensional ventricular imaging data and models that include the left and right ventricular outflow tracts and valve annuli.

A Deep Learning-Based Integrated Framework for Quality-Aware Undersampled Cine Cardiac MRI Reconstruction and Analysis.

Cine cardiac magnetic resonance (CMR) imaging is considered the gold standard for cardiac function evaluation. However, cine CMR acquisition is inherently slow and in recent decades considerable effort has been put into accelerating scan times without compromising image quality or the accuracy of derived results. In this article, we present a fully-automated, quality-controlled integrated framework for reconstruction, segmentation and downstream analysis of undersampled cine CMR data. The framework produces high quality reconstructions and segmentations, leading to undersampling factors that are optimised on a scan-by-scan basis. This results in reduced scan times and automated analysis, enabling robust and accurate estimation of functional biomarkers. To demonstrate the feasibility of the proposed approach, we perform simulations of radial k-space acquisitions using in-vivo cine CMR data from 270 subjects from the UK Biobank (with synthetic phase) and in-vivo cine CMR data from 16 healthy subjects (with real phase). The results demonstrate that the optimal undersampling factor varies for different subjects by approximately 1 to 2 seconds per slice. We show that our method can produce quality-controlled images in a mean scan time reduced from 12 to 4 seconds per slice, and that image quality is sufficient to allow clinically relevant parameters to be automatically estimated to lie within 5% mean absolute difference.

Developing Cardiac Digital Twins at Scale: Insights from Personalised Myocardial Conduction Velocity.

Large-cohort studies using cardiovascular imaging and diagnostic datasets have assessed cardiac anatomy, function, and outcomes, but typically do not reveal underlying biological mechanisms. Cardiac digital twins (CDTs) provide personalized physics- and physiology-constrained in-silico representations, enabling inference of multi-scale properties tied to these mechanisms. We constructed 3464 anatomically-accurate CDTs using cardiac magnetic resonance images from UK biobank and personalised their myocardial conduction velocities (CVs) from electrocardiograms (ECG), through an automated framework. We found well-known sex-specific differences in QRS duration were fully explained by myocardial anatomy, as CV remained consistent across sexes. Conversely, significant associations of CV with ageing and increased BMI suggest myocardial tissue remodelling. Novel associations were observed with left ventricular ejection fraction and mental-health phenotypes, through a phenome-wide association study, and CV was also linked with adverse clinical outcomes. Our study highlights the utility of population-based CDTs in assessing intersubject variability and uncovering strong links with mental health.

lGeneralized super-resolution 4D Flow MRI-using ensemble learning to extend across the cardiovascular system.

4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of quantifying blood flow across the cardiovascular system. While practical use is limited by spatial resolution and image noise, incorporation of trained super-resolution (SR) networks has potential to enhance image quality post-scan. However, these efforts have predominantly been restricted to narrowly defined cardiovascular domains, with limited exploration of how SR performance extends across the cardiovascular system; a task aggravated by contrasting hemodynamic conditions apparent across the cardiovasculature. The aim of our study was to explore the generalizability of SR 4D Flow MRI using a combination of heterogeneous training sets and dedicated ensemble learning. With synthetic training data generated across three disparate domains (cardiac, aortic, cerebrovascular), varying convolutional base and ensemble learners were evaluated as a function of domain and architecture, quantifying performance on both in-silico and acquired in-vivo data from the same three domains. Results show that both bagging and stacking ensembling enhance SR performance across domains, accurately predicting high-resolution velocities from low-resolution input data in-silico. Likewise, optimized networks successfully recover native resolution velocities from downsampled in-vivo data, as well as show qualitative potential in generating denoised SR-images from clinicallevel input data. In conclusion, our work presents a viable approach for generalized SR 4D Flow MRI, with ensemble learning extending utility across various clinical areas of interest.

Combining generative modelling and semi-supervised domain adaptation for whole heart cardiovascular magnetic resonance angiography segmentation.

BACKGROUND: Quantification of three-dimensional (3D) cardiac anatomy is important for the evaluation of cardiovascular diseases. Changes in anatomy are indicative of remodeling processes as the heart tissue adapts to disease. Although robust segmentation methods exist for computed tomography angiography (CTA), few methods exist for whole-heart cardiovascular magnetic resonance angiograms (CMRA) which are more challenging due to variable contrast, lower signal to noise ratio and a limited amount of labeled data. METHODS: Two state-of-the-art unsupervised generative deep learning domain adaptation architectures, generative adversarial networks and variational auto-encoders, were applied to 3D whole heart segmentation of both conventional (n = 20) and high-resolution (n = 45) CMRA (target) images, given segmented CTA (source) images for training. An additional supervised loss function was implemented to improve performance given 10%, 20% and 30% segmented CMRA cases. A fully supervised nn-UNet trained on the given CMRA segmentations was used as the benchmark. RESULTS: The addition of a small number of segmented CMRA training cases substantially improved performance in both generative architectures in both standard and high-resolution datasets. Compared with the nn-UNet benchmark, the generative methods showed substantially better performance in the case of limited labelled cases. On the standard CMRA dataset, an average 12% (adversarial method) and 10% (variational method) improvement in Dice score was obtained. CONCLUSIONS: Unsupervised domain-adaptation methods for CMRA segmentation can be boosted by the addition of a small number of supervised target training cases. When only few labelled cases are available, semi-supervised generative modelling is superior to supervised methods.

Risk of Recurrence after Surgical Resection for Adenocarcinoma Arising from Intraductal Papillary Mucinous Neoplasia (IPMN) with Patterns of Distribution and Treatment: An International, Multicentre, Observational Study.

OBJECTIVE: This international multicentre cohort study aims to identify recurrence patterns and treatment of first and second recurrence in a large cohort of patients after pancreatic resection for adenocarcinoma arising from IPMN. SUMMARY BACKGROUND DATA: Recurrence patterns and treatment of recurrence post resection of adenocarcinoma arising from IPMN are poorly explored. METHOD: Patients undergoing pancreatic resection for adenocarcinoma from IPMN between January 2010 to December 2020 at 18 pancreatic centres were identified. Survival analysis was performed by the Kaplan-Meier log rank test and multivariable logistic regression by Cox-Proportional Hazards modelling. Endpoints were recurrence (time-to, location, and pattern of recurrence) and survival (overall survival and adjusted for treatment provided). RESULTS: Four hundred and fifty-nine patients were included (median, 70 y; IQR, 64-76; male, 54 percent) with a median follow-up of 26.3 months (IQR, 13.0-48.1 mo). Recurrence occurred in 209 patients (45.5 percent; median time to recurrence, 32.8 months, early recurrence [within 1 y], 23.2 percent). Eighty-three (18.1 percent) patients experienced a local regional recurrence and 164 (35.7 percent) patients experienced distant recurrence. Adjuvant chemotherapy was not associated with reduction in recurrence (HR 1.09;P=0.669) One hundred and twenty patients with recurrence received further treatment. The median survival with and without additional treatment was 27.0 and 14.6 months (P<0.001), with no significant difference between treatment modalities. There was no significant difference in survival between location of recurrence (P=0.401). CONCLUSION: Recurrence after pancreatic resection for adenocarcinoma arising from IPMN is frequent with a quarter of patients recurring within 12 months. Treatment of recurrence is associated with improved overall survival and should be considered.

Quality of life after severe acute pancreatitis: systematic review.

BACKGROUND: Severe acute pancreatitis, the most severe form of acute pancreatitis, can alter pancreatic morphology, physiology, and function resulting in long-term morbidity, even after a single episode. This review assesses long-term outcomes and quality of life of severe acute pancreatitis. METHODS: A comprehensive literature review was conducted across MEDLINE, Embase, Scopus, and PubMed electronic databases on 18 January 2021 and updated on 26 April 2022 to ensure no new literature had been omitted. All studies were prospective or retrospective, included adult patients (>18 years) presenting with acute pancreatitis for whom data on long-term outcomes specifically after severe acute pancreatitis were reported. Quantitative and qualitative data extraction and synthesis were carried out and no meta-analysis was performed. Outcome measures included aetiology and mortality of severe acute pancreatitis, length of stay, endocrine and exocrine pancreatic insufficiency, chronic symptoms, and quality of life compared with healthy controls as assessed by validated questionnaires. RESULTS: Fourteen retrospective cohort studies were included, for a total of 779 patients, using quality of life questionnaires. The most common aetiology of severe acute pancreatitis was biliary (36 per cent) followed by alcoholic (29 per cent). Mortality rate ranged from 5 to 35 per cent and length of stay ranged from 2 to 367 days. Quality of life was somewhat lower in patients with exocrine insufficiency, but unaffected by endocrine insufficiency or chronic symptoms. Quality of life was more likely to be reduced in the first 4 years but normalize thereafter and was more likely to be negatively affected where alcohol was the aetiology. In four studies, the relationship between disease severity and lower quality of life was investigated, and a significant correlation was found. CONCLUSION: The review shows how a single episode of severe acute pancreatitis can have a variable effect on long-term quality of life, which is different to previous studies showing a strong reduction in quality of life. This could indicate that in current times treatment modalities are more effective.

Quinapril treatment curtails decline of global longitudinal strain and mechanical function in hypertensive rats.

BACKGROUND: Left ventricular (LV) global longitudinal strain (GLS) has been proposed as an early imaging biomarker of cardiac mechanical dysfunction. OBJECTIVE: To assess the impact of angiotensin-converting enzyme (ACE) inhibitor treatment of hypertensive heart disease on LV GLS and mechanical function. METHODS: The spontaneously hypertensive rat (SHR) model of hypertensive heart disease ( n  = 38) was studied. A subset of SHRs received quinapril (TSHR, n  = 16) from 3 months (mo). Wistar Kyoto rats (WKY, n  = 13) were used as controls. Tagged cardiac MRI was performed using a 4.7 T Varian preclinical scanner. RESULTS: The SHRs had significantly lower LV ejection fraction (EF) than the WKYs at 3 mo (53.0 ±â€Š1.7% vs. 69.6 ±â€Š2.1%, P  < 0.05), 14 mo (57.0 ±â€Š2.5% vs. 74.4 ±â€Š2.9%, P  < 0.05) and 24 mo (50.1 ±â€Š2.4% vs. 67.0 ±â€Š2.0%, P  < 0.01). At 24 mo, ACE inhibitor treatment was associated with significantly greater LV EF in TSHRs compared to untreated SHRs (64.2 ±â€Š3.4% vs. 50.1 ±â€Š2.4%, P  < 0.01). Peak GLS magnitude was significantly lower in SHRs compared with WKYs at 14 months (7.5% ±â€Š0.4% vs. 9.9 ±â€Š0.8%, P  < 0.05). At 24 months, Peak GLS magnitude was significantly lower in SHRs compared with both WKYs (6.5 ±â€Š0.4% vs. 9.7 ±â€Š1.0%, P  < 0.01) and TSHRs (6.5 ±â€Š0.4% vs. 9.6 ±â€Š0.6%, P  < 0.05). CONCLUSIONS: ACE inhibitor treatment curtails the decline in global longitudinal strain in hypertensive rats, with the treatment group exhibiting significantly greater LV EF and GLS magnitude at 24 mo compared with untreated SHRs.