Pancreatic size and fat content in diabetes: A systematic review and meta-analysis of imaging studies

Changes in Pancreas Volume in Living Donor Liver Transplant Recipients

BACKGROUND

Metabolic factors have a significant role in the morbidity and mortality associated with chronic liver disease. The pancreas has a central role in metabolism and metabolic risk factors but has been largely ignored in liver transplantation. Small pancreas volume has been demonstrated in pathologic conditions such as type 1 and 2 diabetes.

METHODS

This study assessed abdominal imaging before and after liver transplantation to determine if liver transplantation induces changes in pancreas volume in living donor liver transplant recipients. Our secondary outcome is to correlate pancreas volume with demographic, clinical, and outcome data. We conducted a retrospective study of pancreas volume in patients enrolled in the adult-to-adult living donor liver transplantation cohort study. Pancreas volume was manually calculated from 413 MRI or computed tomography images and correlated with imaging and clinical data.

RESULTS

Pancreas volume declined by an average of 24% (87.8 ± 25.2 mL to 66.8 ± 20.4 mL, P  < 0.0001), regardless of liver disease etiology. Pancreas volume correlated with portal blood flow, spleen volume, and liver enzyme levels. We found a correlation between smaller pancreas volume pretransplant and longer intensive care unit (ICU) stay across all patients ( P  < 0.05). Individuals with an ICU stay of <2 d had a larger average pancreas volume pretransplant than those with an ICU stay of 2 d or longer (91.2 versus 82.2 mL, P  < 0.05).

CONCLUSIONS

Pancreas volume is dynamic in liver transplant recipients and may reflect altered metabolism and risk of posttransplantation complications.

Trefoil Factor 2 Expressed by the Murine Pancreatic Acinar Cells Is Required for the Development of Islets and for β-Cell Function During Aging

Exocrine-to-endocrine cross talk in the pancreas is crucial to maintain β-cell function. However, the molecular mechanisms underlying this cross talk are largely undefined. Trefoil factor 2 (Tff2) is a secreted factor known to promote the proliferation of β-cells in vitro, but its physiological role in vivo in the pancreas is unknown. Also, it remains unclear which pancreatic cell type expresses Tff2 protein. We therefore created a mouse model with a conditional knockout of Tff2 in the murine pancreas. We find that the Tff2 protein is preferentially expressed in acinar but not ductal or endocrine cells. Tff2 deficiency in the pancreas reduces β-cell mass on embryonic day 16.5. However, homozygous mutant mice are born without a reduction of β-cells and with acinar Tff3 compensation by day 7. When mice are aged to 1 year, both male and female homozygous and male heterozygous mutants develop impaired glucose tolerance without affected insulin sensitivity. Perifusion analysis reveals that the second phase of glucose-stimulated insulin secretion from islets is reduced in aged homozygous mutant compared with controls. Collectively, these results demonstrate a previously unknown role of Tff2 as an exocrine acinar cell-derived protein required for maintaining functional endocrine β-cells in mice.

ARTICLE HIGHLIGHTS

Imaging abnormalities of the pancreas in diabetes: implications for diagnosis and treatment

PURPOSE OF REVIEW

Radiographic imaging of the pancreas has drawn recent interest as pancreas volume may serve as a biomarker in identifying the likelihood of diabetes development, subtyping diabetes, and identifying prognostic indicators of poor ultimate outcomes. In this review, the role of pancreas imaging is discussed in various forms of diabetes including type 1 diabetes (T1D), type 2 diabetes (T2D), and diabetes of the exocrine pancreas, particularly diabetes following acute or chronic pancreatitis.

RECENT FINDINGS

Recent literature of quantitative pancreatic imaging correlating with various forms of diabetes was reviewed. Imaging-derived pancreas volumes are lower in individuals with diabetes, in particular those with T1D. Additionally, morphologic changes, enhancement characteristics, fat content, and MRI signal changes have been observed in different diabetes subtypes. These characteristics, as well as potential confounding variables, are reviewed. Additionally, future areas of research in MRI, CT radiomics, and pancreatitis-related imaging predictors of diabetes are discussed.

SUMMARY

Increased understanding of pancreas imaging features which predict diabetes and gauge prognosis has the potential to identify at-risk individuals and will become increasingly important in diabetes care. This article reviews the current knowledge of common pancreas imaging features as well as future directions of ongoing research in diabetes imaging.

MAVMET trial: maraviroc and/or metformin for metabolic dysfunction associated fatty liver disease in adults with suppressed HIV

OBJECTIVE

Metabolic dysfunction associated fatty liver disease (MAFLD) is over-represented in people with HIV (PWH). Maraviroc (MVC) and/or metformin (MET) may reduce MAFLD by influencing inflammatory pathways and fatty acid metabolism.

DESIGN

Open-label, 48-week randomized trial with a 2 x 2 factorial design.

SETTING

Multicenter HIV clinics.

PARTICIPANTS

Nondiabetic, virologically suppressed PLWH, aged at least 35 years, with confirmed/suspected MAFLD (≥1 biochemical/anthropometric/radiological/histological features).

INTERVENTION

Adjunctive MVC; MET; MVC+MET vs. antiretroviral therapy (ART) alone.

PRIMARY OUTCOME

Change in liver fat fraction (LFF) between baseline and week-48 using magnetic resonance proton density fat fraction (MR PDFF).

RESULTS

Six sites enrolled 90 participants (93% male; 81% white; median age 52 [interquartile range, IQR 47-57] years) between March 19, 2018, and November 11, 2019. Seventy percent had imaging/biopsy and at least one 1 MAFLD criteria. The analysis included 82/90 with week-0 and week-48 scans. Median baseline MR PDFF was 8.9 (4.6-17.1); 40, 38, 8, and 14% had grade zero, one, two, and three steatosis, respectively. Mean LFF increased slightly between baseline and follow-up scans: 2.22% MVC, 1.26% MET, 0.81% MVC+MET, and 1.39% ART alone. Prolonged intervention exposure (delayed week-48 scans) exhibited greater increases in MR PDFF (estimated difference 4.23% [95% confidence interval, 95% CI 2.97-5.48], P  < 0.001). There were no differences in predicted change for any intervention compared to ART alone: MVC (-0.42% [95% CI -1.53 to 0.68, P  = 0.45]), MET (-0.62 [-1.81 to 0.56, P  = 0.30]), and MVC+MET (-1.04 [-2.74 to 0.65, P  = 0.23]). Steatosis grade remained unchanged in 55% and increased in 24%.

CONCLUSION

Baseline levels of liver fat were lower than predicted. Contrary to our hypothesis, neither MVC, MET, or the combination significantly reduced liver fat as measured by MRPDFF compared to ART alone.

nnU-Net-Based Pancreas Segmentation and Volume Measurement on CT Imaging in Patients with Pancreatic Cancer

RATIONALE AND OBJECTIVES

To develop and validate a deep learning (DL)-based method for pancreas segmentation on CT and automatic measurement of pancreatic volume in pancreatic cancer.

MATERIALS AND METHODS

This retrospective study used 3D nnU-net architecture for fully automated pancreatic segmentation in patients with pancreatic cancer. The study used 851 portal venous phase CT images (499 pancreatic cancer and 352 normal pancreas). This dataset was divided into training (n = 506), internal validation (n = 126), and external test set (n = 219). For the external test set, the pancreas was manually segmented by two abdominal radiologists (R1 and R2) to obtain the ground truth. In addition, the consensus segmentation was obtained using Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm. Segmentation performance was assessed using the Dice similarity coefficient (DSC). Next, the pancreatic volumes determined by automatic segmentation were compared to those determined by manual segmentation by two radiologists.

RESULTS

The DL-based model for pancreatic segmentation showed a mean DSC of 0.764 in the internal validation dataset and DSC of 0.807, 0.805, and 0.803 using R1, R2, and STAPLE as references in the external test dataset. The pancreas parenchymal volume measured by automatic and manual segmentations were similar (DL-based model: 65.5 ± 19.3 cm3 and STAPLE: 65.1 ± 21.4 cm3; p = 0.486). The pancreatic parenchymal volume difference between the DL-based model predictions and the manual segmentation by STAPLE was 0.5 cm3, with correlation coefficients of 0.88.

CONCLUSION

The DL-based model efficiently generates automatic segmentation of the pancreas and measures the pancreatic volume in patients with pancreatic cancer.

Cross-sectional imaging of the pancreas in diabetes

Diabetes mellitus presents a global health challenge characterized by dysregulated glucose metabolism and insulin resistance. Pancreas dysfunction contributes to the development and progression of diabetes. Cross-sectional imaging modalities have provided new insight into the structural and functional alterations of the pancreas in individuals with diabetes. This review summarizes MRI and CT studies that characterize pancreas alterations in both type 1 and type 2 diabetes and discusses future applications of these techniques.

Radiomics analysis of pancreas based on dual-energy computed tomography for the detection of type 2 diabetes mellitus

Objective

To utilize radiomics analysis on dual-energy CT images of the pancreas to establish a quantitative imaging biomarker for type 2 diabetes mellitus.

Materials and methods

In this retrospective study, 78 participants (45 with type 2 diabetes mellitus, 33 without) underwent a dual energy CT exam. Pancreas regions were segmented automatically using a deep learning algorithm. From these regions, radiomics features were extracted. Additionally, 24 clinical features were collected for each patient. Both radiomics and clinical features were then selected using the least absolute shrinkage and selection operator (LASSO) technique and then build classifies with random forest (RF), support vector machines (SVM) and Logistic. Three models were built: one using radiomics features, one using clinical features, and a combined model.

Results

Seven radiomic features were selected from the segmented pancreas regions, while eight clinical features were chosen from a pool of 24 using the LASSO method. These features were used to build a combined model, and its performance was evaluated using five-fold cross-validation. The best classifier type is Logistic and the reported area under the curve (AUC) values on the test dataset were 0.887 (0.73-1), 0.881 (0.715-1), and 0.922 (0.804-1) for the respective models.

Conclusion

Radiomics analysis of the pancreas on dual-energy CT images offers potential as a quantitative imaging biomarker in the detection of type 2 diabetes mellitus.

Distinct changes to pancreatic volume rather than pancreatic autoantibody positivity: insights into immune checkpoint inhibitors induced diabetes mellitus

BACKGROUND

Immune checkpoint inhibitors (ICI) are promising treatment options for various cancers. However, their use is associated with immune-related adverse events (irAEs), including ICI-induced diabetes mellitus (ICI-DM). This study aimed to investigate the clinical features of ICI-DM, with a particular focus on alterations to pancreatic volume.

METHODS

We conducted a retrospective review of 2829 patients who received ICI treatment at the Chang Gung Memorial Hospital, Linkou, between January 2014 and December 2021. New-onset diabetes or diabetic ketoacidosis (DKA) was identified in ten patients receiving ICI therapy. Pancreatic volumes were assessed by manual segmentation of computed tomography (CT) images before and after ICI-DM diagnosis.

RESULTS

Among these ten patients, nivolumab was the most commonly used ICI (50.0%), followed by pembrolizumab (30.0%) and atezolizumab (20.0%). One patient received combination therapy with nivolumab and ipilimumab. The median age was 63.01 years (range: 40.1 - 87.8). ICI-DM developed after a median of 13.5 cycles (range: 2 - 42) of ICI treatment or 9.85 months (range:1.5 - 21.3) since ICI initiation. The initial presentation was DKA in 60.0% of patients. All patients had low or undetectable C-peptide levels (range: <0.033 - 0.133 nmol/L) and were negative for most type 1 diabetes mellitus (T1DM)-related autoantibodies; only one patient tested positive for glutamic acid decarboxylase antibodies. CT imaging revealed significant pancreatic atrophy, with a median pancreatic volume decrease of 19.92% (P = 0.038) from baseline and sustained significant decline at last follow-up (median - 37.14%, P = 0.012).

CONCLUSIONS

ICI-DM is often accompanied by pancreatic atrophy and approximately two-thirds of patients initially present with DKA. Although the majority of ICI-DM patients lack T1DM-related autoantibodies, identifying diminished pancreatic volumes through CT imaging provides valuable clues into the subclinical aspects of ICI-DM development, aiding in the prevention of diabetic emergencies.

TRIAL REGISTRATION

Not applicable.

Quantitative Magnetic Resonance Imaging for the Pancreas: Current Status

ABSTRACT

Magnetic resonance imaging (MRI) is important for evaluating pancreatic disorders, and anatomical landmarks play a major role in the interpretation of results. Quantitative MRI is an effective diagnostic modality for various pathologic conditions, as it allows the investigation of various physical parameters. Recent advancements in quantitative MRI techniques have significantly improved the accuracy of pancreatic MRI. Consequently, this method has become an essential tool for the diagnosis, treatment, and monitoring of pancreatic diseases. This comprehensive review article presents the currently available evidence on the clinical utility of quantitative MRI of the pancreas.

Fatty Pancreas Is a Risk Factor for Pancreatic Cancer: A Systematic Review and Meta-Analysis of 2956 Patients

Pancreatic cancer (PC) is one of the most lethal cancers worldwide. Recently, fatty pancreas (FP) has been studied thoroughly, and although its relationship to PC is not fully understood, FP is suspected to contribute to the development of PC. We aimed to assess the association between PC and FP by conducting a systematic review and meta-analysis. We systematically searched three databases, MEDLINE, Embase, and CENTRAL, on 21 October 2022. Case-control and cross-sectional studies reporting on patients where the intra-pancreatic fat deposition was determined by modern radiology or histology were included. As main outcome parameters, FP in patients with and without PC and PC in patients with and without FP were measured. Proportion and odds ratio (OR) with a 95% confidence interval (CI) were used for effect size measure. PC among patients with FP was 32% (OR 1.32; 95% CI 0.42-4.16). However, the probability of having FP among patients with PC was more than six times higher (OR 6.13; 95% CI 2.61-14.42) than in patients without PC, whereas the proportion of FP among patients with PC was 0.62 (95% CI 0.42-0.79). Patients identified with FP are at risk of developing PC. Proper screening and follow-up of patients with FP may be recommended.

Longitudinal MRI Shows Progressive Decline in Pancreas Size and Altered Pancreas Shape in Type 1 Diabetes

CONTEXT

Individuals with type 1 diabetes (T1D) have a smaller pancreas, but longitudinal changes in pancreas size and shape are unclear.

OBJECTIVE

We monitored changes in pancreas size and shape after diagnosis with T1D.

DESIGN

We conducted a prospective cohort study at an academic medical center between 2014 and 2022.

PATIENTS AND HEALTHY CONTROLS

Individuals with T1D (n = 91) or controls (n = 90) underwent magnetic resonance imaging (MRI) of the pancreas, including longitudinal MRI in 53 individuals with new-onset T1D.

INTERVENTION

Interventions included MRI and continuous glucose monitoring (CGM).

MAIN OUTCOME MEASURES

Pancreas size and shape were measured from MRI. For participants who used CGM, measures of glycemic variability were calculated.

RESULTS

On longitudinal imaging, pancreas volume and pancreas volume index normalized for body weight declined during the first year after diagnosis. Pancreas volume index continued to decline through the fifth year after diagnosis. A cross-sectional study of individuals with diabetes duration up to 60 years demonstrated that pancreas size in adults negatively correlated with age and disease duration, whereas pancreas volume and pancreas volume index remained stable in controls. Pancreas volume index correlated inversely with low blood glucose index, a measure of risk for hypoglycemia. Pancreas shape was altered in individuals with T1D and further diverged from controls over the first 5 years after diagnosis. Pancreas size and shape are altered in nondiabetic individuals at genetic risk for T1D. Combined pancreas size and shape analysis better distinguished the pancreas of individuals with T1D from controls than size alone.

CONCLUSIONS

Pancreas size declines most rapidly near the clinical diagnosis of T1D and continues to decline throughout adulthood. Declines in pancreas size are accompanied by changes in pancreas shape.

Association of pancreatic fat on imaging with pediatric metabolic co-morbidities

BACKGROUND

The relationship between pancreatic fat on imaging and metabolic co-morbidities has not been established in pediatrics. We sought to investigate the relationship between pancreatic fat measured by MRI and endocrine/exocrine dysfunctions along with the metabolic co-morbidities in a cohort of children.

OBJECTIVE

To investigate relationships between pancreatic fat quantified by MRI and endocrine and exocrine conditions and metabolic co-morbidities in a cohort of children. MATERIALS AND METHODS: This was a retrospective review of pediatric patients (n = 187) who had a clinically indicated MRI examination between May 2018 and February 2020. After 51 patients without useable imaging data were excluded, the remaining 136 subjects comprised the study sample. Laboratory studies were assessed if collected within 6 months of MRI and patient charts were reviewed for demographic and clinical information. MRI proton density fat fraction (PDFF) sequence had been acquired according to manufacturer's specified parameters at a slice thickness of 3 mm. Two blinded radiologists independently collected PDFF data.

RESULTS

The median age at MRI was 12.1 (IQR: 9.0-14.8) years and the majority of patients were Caucasian (79%), followed by African American and Hispanic at 12% and 11% respectively. There was a higher median pancreas fat fraction in patients with exocrine conditions (chronic pancreatitis or exocrine insufficiency) compared to those without (3.5% vs 2.2%, p = 0.03). There was also a higher median fat fraction in the head of pancreas in patients with endocrine insufficient conditions (insulin resistance, pre-diabetes, type 1 and type 2 diabetes) compared to those without endocrine insufficiency when excluding patients with active acute pancreatitis (3.5% vs 2.0%, p = 0.04). Patients with BMI > 85% had higher mean fat fraction compared to patients with BMI ≤ 85% (head: 3.8 vs 2.4%, p = 0.01; body: 3.8 vs 2.5%, p = 0.005; tail: 3.7 vs 2.7%, p = 0.049; overall pancreas fat fraction: 3.8 vs 2.6%, p = 0.002).

CONCLUSION

Pancreas fat is elevated in patients with BMI > 85% and in those with exocrine and endocrine insufficiencies.

Acute Recurrent Pancreatitis in a Child With INS-Related Monogenic Diabetes and a Heterozygous Pathogenic CFTR Mutation

Given the close anatomical and physiological links between the exocrine and endocrine pancreas, diseases of 1 compartment often affect the other through mechanisms that remain poorly understood. Pancreatitis has been associated with both type 1 and type 2 diabetes, but its association with monogenic diabetes is unknown. Patients heterozygous for pathogenic CFTR variants are cystic fibrosis carriers and have been reported to have an increased risk of acute pancreatitis. We describe a 12-year-old patient with monogenic neonatal diabetes due to a pathogenic heterozygous paternally inherited mutation of the insulin gene (INS), c.94 G > A (p.Gly32Ser), who experienced 3 recurrent episodes of acute pancreatitis over 7 months in conjunction with poor glycemic control, despite extensive efforts to improve glycemic control in the past 4 years. Intriguingly, the maternal side of the family has an extensive history of adult-onset pancreatitis consistent with autosomal dominant inheritance and the proband is heterozygous for a maternally inherited, CFTR variant c.3909C > G (p.Asn1303Lys). Paternally inherited monogenic neonatal diabetes may have promoted earlier age-of-onset of pancreatitis in this pediatric patient compared to maternal relatives with adult-onset acute pancreatitis. Further study is needed to clarify how separate pathophysiologies associated with INS and CFTR mutations influence interactions between the endocrine and exocrine pancreas.

An Adapted Deep Convolutional Neural Network for Automatic Measurement of Pancreatic Fat and Pancreatic Volume in Clinical Multi-Protocol Magnetic Resonance Images: A Retrospective Study with Multi-Ethnic External Validation

Pancreatic volume and fat fraction are critical prognoses for metabolic diseases like type 2 diabetes (T2D). Magnetic Resonance Imaging (MRI) is a required non-invasive quantification method for the pancreatic fat fraction. The dramatic development of deep learning has enabled the automatic measurement of MR images. Therefore, based on MRI, we intend to develop a deep convolutional neural network (DCNN) that can accurately segment and measure pancreatic volume and fat fraction. This retrospective study involved abdominal MR images from 148 diabetic patients and 246 healthy normoglycemic participants. We randomly separated them into training and testing sets according to the proportion of 80:20. There were 2364 recognizable pancreas images labeled and pre-treated by an upgraded superpixel algorithm for a discernible pancreatic boundary. We then applied them to the novel DCNN model, mimicking the most accurate and latest manual pancreatic segmentation process. Fat phantom and erosion algorithms were employed to increase the accuracy. The results were evaluated by dice similarity coefficient (DSC). External validation datasets included 240 MR images from 10 additional patients. We assessed the pancreas and pancreatic fat volume using the DCNN and compared them with those of specialists. This DCNN employed the cutting-edge idea of manual pancreas segmentation and achieved the highest DSC (91.2%) compared with any reported models. It is the first framework to measure intra-pancreatic fat volume and fat deposition. Performance validation reflected by regression R² value between manual operation and trained DCNN segmentation on the pancreas and pancreatic fat volume were 0.9764 and 0.9675, respectively. The performance of the novel DCNN enables accurate pancreas segmentation, pancreatic fat volume, fraction measurement, and calculation. It achieves the same segmentation level of experts. With further training, it may well surpass any expert and provide accurate measurements, which may have significant clinical relevance.

Adult-onset autoimmune diabetes

Adult-onset autoimmune (AOA) diabetes pathophysiology starts with immune changes, followed by dysglycaemia and overt disease. AOA diabetes can occur as classic type 1 diabetes when associated with severe loss of insulin secretion. More frequently, it is diagnosed as latent autoimmune diabetes in adults, a slowly progressing form with late onset, a long period not requiring insulin, and it is often misdiagnosed as type 2 diabetes. As its clinical presentation varies remarkably and immune markers often lack specificity, it is challenging to classify each case ad hoc, especially when insulin treatment is not required at diagnosis. Proper care of AOA diabetes aims to prevent complications and to improve quality of life and life expectancy. To achieve these goals, attention should be paid to lifestyle factors, with the aid of pharmacological therapies properly tailored to each individual clinical setting. Given the heterogeneity of the disease, choosing the right therapy for AOA diabetes is challenging. Most of the trials testing disease-modifying therapies for autoimmune diabetes are conducted in people with childhood onset, whereas non-insulin diabetes therapies have mostly been studied in the larger population with type 2 diabetes. More randomized controlled trials of therapeutic agents in AOA diabetes are needed.

Fully Automated Abdominal CT Biomarkers for Type 2 Diabetes Using Deep Learning

Background CT biomarkers both inside and outside the pancreas can potentially be used to diagnose type 2 diabetes mellitus. Previous studies on this topic have shown significant results but were limited by manual methods and small study samples. Purpose To investigate abdominal CT biomarkers for type 2 diabetes mellitus in a large clinical data set using fully automated deep learning. Materials and Methods For external validation, noncontrast abdominal CT images were retrospectively collected from consecutive patients who underwent routine colorectal cancer screening with CT colonography from 2004 to 2016. The pancreas was segmented using a deep learning method that outputs measurements of interest, including CT attenuation, volume, fat content, and pancreas fractal dimension. Additional biomarkers assessed included visceral fat, atherosclerotic plaque, liver and muscle CT attenuation, and muscle volume. Univariable and multivariable analyses were performed, separating patients into groups based on time between type 2 diabetes diagnosis and CT date and including clinical factors such as sex, age, body mass index (BMI), BMI greater than 30 kg/m², and height. The best set of predictors for type 2 diabetes were determined using multinomial logistic regression. Results A total of 8992 patients (mean age, 57 years ± 8 [SD]; 5009 women) were evaluated in the test set, of whom 572 had type 2 diabetes mellitus. The deep learning model had a mean Dice similarity coefficient for the pancreas of 0.69 ± 0.17, similar to the interobserver Dice similarity coefficient of 0.69 ± 0.09 (P = .92). The univariable analysis showed that patients with diabetes had, on average, lower pancreatic CT attenuation (mean, 18.74 HU ± 16.54 vs 29.99 HU ± 13.41; P < .0001) and greater visceral fat volume (mean, 235.0 mL ± 108.6 vs 130.9 mL ± 96.3; P < .0001) than those without diabetes. Patients with diabetes also showed a progressive decrease in pancreatic attenuation with greater duration of disease. The final multivariable model showed pairwise areas under the receiver operating characteristic curve (AUCs) of 0.81 and 0.85 between patients without and patients with diabetes who were diagnosed 0-2499 days before and after undergoing CT, respectively. In the multivariable analysis, adding clinical data did not improve upon CT-based AUC performance (AUC = 0.67 for the CT-only model vs 0.68 for the CT and clinical model). The best predictors of type 2 diabetes mellitus included intrapancreatic fat percentage, pancreatic fractal dimension, plaque severity between the L1 and L4 vertebra levels, average liver CT attenuation, and BMI. Conclusion The diagnosis of type 2 diabetes mellitus was associated with abdominal CT biomarkers, especially measures of pancreatic CT attenuation and visceral fat. © RSNA, 2022 Online supplemental material is available for this article.

Imaging evaluation of the pancreas in diabetic patients

Diabetes mellitus (DM) is becoming a global epidemic and its diagnosis and monitoring are based on laboratory testing which sometimes have limitations. The pancreas plays a key role in metabolism and is involved in the pathogenesis of DM. It has long been known through cadaver biopsies that pancreas volume is decreased in patients with DM. With the development of different imaging modalities over the last two decades, many studies have attempted to determine whether there other changes occurred in the pancreas of diabetic patients. This review summarizes current knowledge about the use of different imaging approaches (such as CT, MR, and US) and radiomics for exploring pancreatic changes in diabetic patients. Imaging studies are expected to produce reliable information regarding DM, and radiomics could provide increasingly valuable information to identify some undetectable features and help diagnose and predict the occurrence of diabetes through pancreas imaging.

Deep learning-based pancreas volume assessment in individuals with type 1 diabetes

Pancreas volume is reduced in individuals with diabetes and in autoantibody positive individuals at high risk for developing type 1 diabetes (T1D). Studies investigating pancreas volume are underway to assess pancreas volume in large clinical databases and studies, but manual pancreas annotation is time-consuming and subjective, preventing extension to large studies and databases. This study develops deep learning for automated pancreas volume measurement in individuals with diabetes. A convolutional neural network was trained using manual pancreas annotation on 160 abdominal magnetic resonance imaging (MRI) scans from individuals with T1D, controls, or a combination thereof. Models trained using each cohort were then tested on scans of 25 individuals with T1D. Deep learning and manual segmentations of the pancreas displayed high overlap (Dice coefficient = 0.81) and excellent correlation of pancreas volume measurements (R² = 0.94). Correlation was highest when training data included individuals both with and without T1D. The pancreas of individuals with T1D can be automatically segmented to measure pancreas volume. This algorithm can be applied to large imaging datasets to quantify the spectrum of human pancreas volume.

Accuracy of a CT density threshold enhancement in distinguishing pancreas parenchymal necrosis in cases of acute pancreatitis in the first week

PURPOSE

The purpose of this study was to identify attenuation threshold value on computed tomography (CT) that allowed discriminating between interstitial edematous pancreatitis (IEP) and necrotizing pancreatitis (NP) in patients with acute pancreatitis during the first week of the disease and evaluate interobserver reproducibility for the diagnosis of acute pancreatitis category.

MATERIALS AND METHODS

Patients with acute pancreatitis who underwent CT examination of the abdomen between March 2015 and December 2019 were retrospectively included. Actual diagnosis of IEP or NP was based on final clinical report, follow-up evaluation, and complications. Six regions of interest were manually placed in the pancreatic gland and peripancreatic fat, and differences in CT attenuation values before contrast injection and during the portal venous phase of enhancement were computed. Performance in the diagnosis of AP category was evaluated using receiver operating characteristic analysis. Interobserver agreement was estimated by the intraclass correlation coefficient (ICC) and Bland Altman analysis was used to estimate reproducibility between pairs of observers.

RESULTS

Sixty-six patients with NP (46 men, 20 women; mean age, 55 ± 17 [SD] years; age range: 20-89 years) and 70 patients with IEP (39 men, 31 women; mean age, 54 ± 18 [SD] years; age range: 21-87 years) were included. An enhancement value less than 30 Hounsfield units (HU) in the pancreatic gland during the portal phase compared to non-contrast phase, yielded 90.9% sensitivity (60/66; 95% CI: 81.3-96.6), 94.3% specificity (66/70; 95% CI: 86.0-98.4) and an area under curve of 0.958 (95% CI: 0.919-0.996) for the diagnosis of NP versus IEP. Interobserver reproducibility for pancreas enhancement was good using Bland Altman plot and ICC was excellent for pancreatic gland analysis (ICC 0.978; 95% CI: 0.961-0.988) but poor or moderate (ICC ≤0.634) regarding peripancreatic fat necrosis.

CONCLUSION

By using a pancreas enhancement threshold value of 30 HU, CT is accurate and reproducible for the diagnosis of NP during the first week of the disease.

Molecular Mechanisms of Nutrient-Mediated Regulation of MicroRNAs in Pancreatic β-cells

Pancreatic β-cells within the islets of Langerhans respond to rising blood glucose levels by secreting insulin that stimulates glucose uptake by peripheral tissues to maintain whole body energy homeostasis. To different extents, failure of β-cell function and/or β-cell loss contribute to the development of Type 1 and Type 2 diabetes. Chronically elevated glycaemia and high circulating free fatty acids, as often seen in obese diabetics, accelerate β-cell failure and the development of the disease. MiRNAs are essential for endocrine development and for mature pancreatic β-cell function and are dysregulated in diabetes. In this review, we summarize the different molecular mechanisms that control miRNA expression and function, including transcription, stability, posttranscriptional modifications, and interaction with RNA binding proteins and other non-coding RNAs. We also discuss which of these mechanisms are responsible for the nutrient-mediated regulation of the activity of β-cell miRNAs and identify some of the more important knowledge gaps in the field.

The β Cell in Diabetes: Integrating Biomarkers With Functional Measures

The pathogenesis of hyperglycemia observed in most forms of diabetes is intimately tied to the islet β cell. Impairments in propeptide processing and secretory function, along with the loss of these vital cells, is demonstrable not only in those in whom the diagnosis is established but typically also in individuals who are at increased risk of developing the disease. Biomarkers are used to inform on the state of a biological process, pathological condition, or response to an intervention and are increasingly being used for predicting, diagnosing, and prognosticating disease. They are also proving to be of use in the different forms of diabetes in both research and clinical settings. This review focuses on the β cell, addressing the potential utility of genetic markers, circulating molecules, immune cell phenotyping, and imaging approaches as biomarkers of cellular function and loss of this critical cell. Further, we consider how these biomarkers complement the more long-established, dynamic, and often complex measurements of β-cell secretory function that themselves could be considered biomarkers.

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.

Sonographic Evaluation of the Pancreas in Type 1 Diabetes Mellitus: A Case-control Study

BACKGROUND

Pancreas is a vital insulin-producing gland, and it is subjected to various disorders which produce alteration in the morphology and function. Ultrasound (US) of the pancreas is sensitive for evaluating the gland and provides the accurate diagnosis of pancreatic diseases. The aim of this study is to determine whether there were alterations in pancreatic size and echogenicity in type 1 diabetes mellitus (DM).

METHODS

A total of 100 patients with Type-1 DM (insulin dependent) were examined using the ultrasonography. They were compared to 22 healthy controls. Measurements of the pancreas were performed on type 1 diabetic patients and controls.

RESULTS

Pancreatic diameters of the head, body, and tail of the pancreas were reduced in Type 1 DM versus controls (1.78 vs. 1.80 cm, 95% confidence interval [CI]: -0.147 -0.099, P = 0.699 for the head of the pancreas; and 1.093 vs. 1.13 cm: 95% CI: -2.97-1.196, P = 0.484 for the body of the pancreas; 1.12 vs. 1.46 cm, 95% CI: -0.491-0.194, P < 0.001 for the tail of the pancreas). The echogenicity of the pancreas in patients with Type 1 DM increased significantly as the duration of the disease increased (P = 0.015).

CONCLUSION

Individuals with Type 1 DM have reduced pancreatic size in comparison with controls. Patients with Type 1 DM have increased echogenicity of the pancreas as the duration of the disease increased.

Two-stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra-reader and inter-reader reliability at full and reduced radiation dose on an external dataset

PURPOSE

To develop a two-stage three-dimensional (3D) convolutional neural networks (CNNs) for fully automated volumetric segmentation of pancreas on computed tomography (CT) and to further evaluate its performance in the context of intra-reader and inter-reader reliability at full dose and reduced radiation dose CTs on a public dataset.

METHODS

A dataset of 1994 abdomen CT scans (portal venous phase, slice thickness ≤ 3.75-mm, multiple CT vendors) was curated by two radiologists (R1 and R2) to exclude cases with pancreatic pathology, suboptimal image quality, and image artifacts (n = 77). Remaining 1917 CTs were equally allocated between R1 and R2 for volumetric pancreas segmentation [ground truth (GT)]. This internal dataset was randomly divided into training (n = 1380), validation (n = 248), and test (n = 289) sets for the development of a two-stage 3D CNN model based on a modified U-net architecture for automated volumetric pancreas segmentation. Model's performance for pancreas segmentation and the differences in model-predicted pancreatic volumes vs GT volumes were compared on the test set. Subsequently, an external dataset from The Cancer Imaging Archive (TCIA) that had CT scans acquired at standard radiation dose and same scans reconstructed at a simulated 25% radiation dose was curated (n = 41). Volumetric pancreas segmentation was done on this TCIA dataset by R1 and R2 independently on the full dose and then at the reduced radiation dose CT images. Intra-reader and inter-reader reliability, model's segmentation performance, and reliability between model-predicted pancreatic volumes at full vs reduced dose were measured. Finally, model's performance was tested on the benchmarking National Institute of Health (NIH)-Pancreas CT (PCT) dataset.

RESULTS

Three-dimensional CNN had mean (SD) Dice similarity coefficient (DSC): 0.91 (0.03) and average Hausdorff distance of 0.15 (0.09) mm on the test set. Model's performance was equivalent between males and females (P = 0.08) and across different CT slice thicknesses (P > 0.05) based on noninferiority statistical testing. There was no difference in model-predicted and GT pancreatic volumes [mean predicted volume 99 cc (31cc); GT volume 101 cc (33 cc), P = 0.33]. Mean pancreatic volume difference was -2.7 cc (percent difference: -2.4% of GT volume) with excellent correlation between model-predicted and GT volumes [concordance correlation coefficient (CCC)=0.97]. In the external TCIA dataset, the model had higher reliability than R1 and R2 on full vs reduced dose CT scans [model mean (SD) DSC: 0.96 (0.02), CCC = 0.995 vs R1 DSC: 0.83 (0.07), CCC = 0.89, and R2 DSC:0.87 (0.04), CCC = 0.97]. The DSC and volume concordance correlations for R1 vs R2 (inter-reader reliability) were 0.85 (0.07), CCC = 0.90 at full dose and 0.83 (0.07), CCC = 0.96 at reduced dose datasets. There was good reliability between model and R1 at both full and reduced dose CT [full dose: DSC: 0.81 (0.07), CCC = 0.83 and reduced dose DSC:0.81 (0.08), CCC = 0.87]. Likewise, there was good reliability between model and R2 at both full and reduced dose CT [full dose: DSC: 0.84 (0.05), CCC = 0.89 and reduced dose DSC:0.83(0.06), CCC = 0.89]. There was no difference in model-predicted and GT pancreatic volume in TCIA dataset (mean predicted volume 96 cc (33); GT pancreatic volume 89 cc (30), p = 0.31). Model had mean (SD) DSC: 0.89 (0.04) (minimum-maximum DSC: 0.79 -0.96) on the NIH-PCT dataset.

CONCLUSION

A 3D CNN developed on the largest dataset of CTs is accurate for fully automated volumetric pancreas segmentation and is generalizable across a wide range of CT slice thicknesses, radiation dose, and patient gender. This 3D CNN offers a scalable tool to leverage biomarkers from pancreas morphometrics and radiomics for pancreatic diseases including for early pancreatic cancer detection.

Amelioration of pancreatic fat accumulation in Japanese type 2 diabetes patients treated with sodium-glucose cotransporter 2 inhibitors: a retrospective study

Background

Prior reports have suggested that pancreatic fat is related to type 2 diabetes. Sodium‐glucose co‐transporter‐2 (SGLT‐2) inhibitors are expected to reduce ectopic fat accumulation.

Aim

This study assessed the effect of SGLT‐2 inhibitors on pancreatic and liver fat accumulations in patients with type 2 diabetes.

Materials and Methods

Retrospective analyses of indices of pancreatic and liver fat accumulations were conducted in 22 type 2 diabetes outpatients who were receiving SGLT‐2 inhibitors for more than 12 weeks. The differences between the pancreatic (P) or liver (L) and splenic (S) computed tomography values were evaluated.

Results

Fatty pancreas was defined as P−S < −8 Hounsfield Unit (HU), and the number of patients with fatty pancreas was 11 (50%). Fatty pancreas significantly improved after SGLT‐2 inhibitor use (median, −20.8; IQR, −34.8 to −14.3 HU vs. median, −14.6; IQR, −29.5 to −7.8 HU; p = 0.041). Fatty liver was defined as L−S ≤ 3.9 HU, and the number of patients with fatty liver was 11 (50%). Fatty liver significantly improved after SGLT‐2 inhibitor use (median, −4.3; IQR, −23.0 to 3.0 HU vs. median, −0.7; IQR, −5.2 to 6.3 HU; p = 0.016).

Conclusion

Pancreatic fat and liver fat accumulations might be reduced after treatment with SGLT‐2 inhibitors in type 2 diabetes patients with intense cumulative fat depositions in these organs.

Severity of hyperechoic pancreas on ultrasonography as a risk factor for glycemic progression

Purpose

The aim of this study was to evaluate the association between the severity of hyperechoic pancreas (HP) on ultrasonography (US) and glycemic progression.

Methods

In total, 1,386 participants who underwent abdominal US as part of health examinations between December 2008 and May 2014 were included in this retrospective study. We classified pancreatic echogenicity on a 4-point scale, and compared it using two distinct criteria: fatty pancreas (FP) 1 criterion (normal vs. ≥mild HP) and FP2 criterion (normal/mild HP vs. ≥moderate HP). According to the presence of nonalcoholic fatty liver disease (NAFLD), participants were subdivided into four groups: non-NAFLD and non-HP, isolated NAFLD, isolated HP, and HP with NAFLD. Glycemic progression was defined as progression from normoglycemia to prediabetes or diabetes or progression from prediabetes to diabetes.

Results

During the follow-up (median, 5.9 years), 262 of the 1,386 participants developed glycemic progression. Using FP2, the probability of glycemic progression across the four subgroups showed cumulative aggravation for NAFLD and HP (all P<0.05). Isolated HP showed a higher probability of glycemic progression than isolated NAFLD according to FP2 (P<0.001). The highest probability of glycemic progression was observed in patients with both NAFLD and HP (P<0.001). The hazard ratio for glycemic progression increased with the severity of HP.

Conclusion

Increasing severity of HP on US was found to be significantly correlated with glycemic progression. Moreover, isolated HP of moderate or greater severity predicted glycemic progression independent of NAFLD.

Pancreas Optical Clearing and 3-D Microscopy in Health and Diabetes

Although first described over a hundred years ago, tissue optical clearing is undergoing renewed interest due to numerous advances in optical clearing methods, microscopy systems, and three-dimensional (3-D) image analysis programs. These advances are advantageous for intact mouse tissues or pieces of human tissues because samples sized several millimeters can be studied. Optical clearing methods are particularly useful for studies of the neuroanatomy of the central and peripheral nervous systems and tissue vasculature or lymphatic system. Using examples from solvent- and aqueous-based optical clearing methods, the mouse and human pancreatic structures and networks will be reviewed in 3-D for neuro-insular complexes, parasympathetic ganglia, and adipocyte infiltration as well as lymphatics in diabetes. Optical clearing with multiplex immunofluorescence microscopy provides new opportunities to examine the role of the nervous and circulatory systems in pancreatic and islet functions by defining their neurovascular anatomy in health and diabetes.

Immune Checkpoint Inhibitor-Associated Diabetes: A Single-Institution Experience

OBJECTIVE

To characterize immune checkpoint inhibitor-associated diabetes mellitus (ICI-DM) in a single-institution case series.

RESEARCH DESIGN AND METHODS

Retrospective chart review of 18 patients with new-onset ICI-DM following anti-programmed cell death protein 1 (PD-1)/anti-programmed cell death protein ligand 1 (PD-L1) therapy for advanced carcinomas.

RESULTS

Of 18 patients, 9 had diabetic ketoacidosis (median glucose 27.92 mmol/L; median glucose before presentation 6.35 mmol/L). Median C-peptide at ICI-DM diagnosis was low, and it declined during follow-up. Median anti-PD-1/anti-PD-L1 duration before ICI-DM was 3.65 months (range 0.56-12.23 months). Time to ICI-DM onset was a median 1.4 months/3 ICI cycles and 6 months/10 cycles in those patients who were positive and negative for GAD65 autoantibodies, respectively. Time to ICI-DM onset was a median 2.5 months/3 ICI cycles and 4.8 months/8 cycles after anti-PD-L1 or anti-PD-1 therapy, respectively. Significant pancreatic atrophy was seen radiographically.

CONCLUSIONS

ICI-DM presents abruptly, appears irreversible, is characterized by pancreatic atrophy, and may occur both earlier following PD-L1 blockade compared with PD-1 inhibition and in those who have positive GAD65 autoantibodies.

Pancreatic Tissue Proteomics Unveils Key Proteins, Pathways, and Networks Associated with Type 1 Diabetes

PURPOSE

Type 1 diabetes (T1D) is characterized by autoimmune mediated self-destruction of the pancreatic islet beta cells and the resultant insulin deficiency. However, little is known about the underlying molecular pathogenesis at the pancreatic tissue level given the limited availability of clinical specimens.

EXPERIMENTAL DESIGN

Quantitative proteomic studies is performed on age-matched T1D and healthy cadaveric pancreatic tissues (n = 18 each) using TMT 10plex-based isobaric labeling and BoxCar-based label-free LC-MS/MS approaches. ELISA is used to validate the differentially expressed proteins (DEPs).

RESULTS

Overall, the two quantitative proteomics approaches identified 8824 proteins, of which 261 are DEPs. KEGG pathway and functional network analyses of the DEPs reveal dysregulations to pancreatic exocrine function, complement coagulation cascades, and extracellular matrix receptor interaction pathways in T1D. A selected list of the DEPs associated with pathways, subnetworks, and plasma proteome of T1D are validated using ELISA.

CONCLUSIONS AND CLINICAL RELEVANCE

Integrating labeling and label-free approaches improve the confidence in quantitative profiling of pancreatic tissue proteome, which furthers the understanding of the dysregulated pathways and functional subnetworks associated with T1D pathogenesis and may aid to develop diagnostic and therapeutic strategies for T1D.

Organisation of the human pancreas in health and in diabetes

For much of the last century, our knowledge regarding the pancreas in type 1 and type 2 diabetes was largely derived from autopsy studies of individuals with these disorders or investigations utilising rodent models of either disease. While many important insights emanated from these efforts, the mode for investigation has increasingly seen change due to the availability of transplant-quality organ-donor tissues, improvements in pancreatic imaging, advances in metabolic assessments of living patients, genetic analyses, technological advances for laboratory investigation and more. As a result, many long-standing notions regarding the role for and the changes that occur in the pancreas in individuals with these disorders have come under question, while, at the same time, new issues (e.g., beta cell persistence, disease heterogeneity, exocrine contributions) have arisen. In this article, we will consider the vital role of the pancreas in human health and physiology, including discussion of its anatomical features and dual (exocrine and endocrine) functions. Specifically, we convey changes that occur in the pancreas of those with either type 1 or type 2 diabetes, with careful attention to the facets that may contribute to the pathogenesis of either disorder. Finally, we discuss the emerging unknowns with the belief that understanding the role of the pancreas in type 1 and type 2 diabetes will lead to improvements in disease diagnosis, understanding of disease heterogeneity and optimisation of treatments at a personalised level. Graphical abstract.

Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records

Type II diabetes mellitus (T2DM) is a significant public health concern with multiple known risk factors (e.g., body mass index (BMI), body fat distribution, glucose levels). Improved prediction or prognosis would enable earlier intervention before possibly irreversible damage has occurred. Meanwhile, abdominal computed tomography (CT) is a relatively common imaging technique. Herein, we explore secondary use of the CT imaging data to refine the risk profile of future diagnosis of T2DM. In this work, we delineate quantitative information and imaging slices of patient history to predict onset T2DM retrieved from ICD-9 codes at least one year in the future. Furthermore, we investigate the role of five different types of electronic medical records (EMR), specifically 1) demographics; 2) pancreas volume; 3) visceral/subcutaneous fat volumes in L2 region of interest; 4) abdominal body fat distribution and 5) glucose lab tests in prediction. Next, we build a deep neural network to predict onset T2DM with pancreas imaging slices. Finally, motivated by multi-modal machine learning, we construct a merged framework to combine CT imaging slices with EMR information to refine the prediction. We empirically demonstrate our proposed joint analysis involving images and EMR leads to 4.25% and 6.93% AUC increase in predicting T2DM compared with only using images or EMR. In this study, we used case-control dataset of 997 subjects with CT scans and contextual EMR scores. To the best of our knowledge, this is the first work to show the ability to prognose T2DM using the patients' contextual and imaging history. We believe this study has promising potential for heterogeneous data analysis and multi-modal medical applications.

Patients with type 2 diabetes present with multiple anomalies of the pancreatic arterial tree on abdominal computed tomography: comparison between patients with type 2 diabetes and a matched control group

Background

Studies suggest that cardio-vascular risk factors could foster the development of type 2 diabetes (T2D). This could partly be mediated by pancreatic atherosclerosis resulting in pancreatic ischemia. We hypothesized that patients with T2D present with more severe atherosclerosis of pancreas-bound arteries than control patients without T2D.

Methods

We performed a retrospective study comparing the abdominal computed tomography of patients with T2D and of control subjects matched for gender and for age. We performed a multivariate logistic regression with adjustment for age, gender, BMI and the presence or absence of hypertension.

Results

Forty-eight patients with T2D and 48 control subjects were included. A calcification score of the splenic artery was defined (from 0: no calcification to 3: continuous linear calcifications). Seventeen percent of the patients with T2D presented with a high calcification score (i.e. 2 or 3), versus only 2% of the control subjects (p = 0.04). The mean number of pancreas-bound branches among the greater pancreatic artery, dorsal pancreatic artery and inferior pancreatic artery (from 0 to 3) was lower in patients with T2D than in control subjects (1.1 vs 1.7, p = 0.003). The mean number of visible intrapancreatic arterial subdivisions (from 0 to 2) was lower in patients with T2D than in control subjects (0.7 vs 1.3, p = 0.0017). All these differences hold true using multivariate logistic regression. None of these differences correlated with the duration of diabetes. The relationship between pancreas volume and BMI seen in control subjects was not confirmed in patients with T2D. Conversely, in patients with T2D but not in control subjects, the splenic artery diameter correlated with the pancreas volume.

Conclusions

Patients with T2D present with more calcifications of the splenic artery and with a less dense pancreatic arterial tree than control subjects.

Improving the slice interaction of 2.5D CNN for automatic pancreas segmentation

PURPOSE

Volumetric pancreas segmentation can be used in the diagnosis of pancreatic diseases, the research about diabetes and surgical planning. Since manual delineation is time-consuming and laborious, we develop a deep learning-based framework for automatic pancreas segmentation in three dimensional (3D) medical images.

METHODS

A two-stage framework is designed for automatic pancreas delineation. In the localization stage, a Square Root Dice loss is developed to handle the trade-off between sensitivity and specificity. In refinement stage, a novel 2.5D slice interaction network with slice correlation module is proposed to capture the non-local cross-slice information at multiple feature levels. Also a self-supervised learning-based pre-training method, slice shuffle, is designed to encourage the inter-slice communication. To further improve the accuracy and robustness, ensemble learning and a recurrent refinement process are adopted in the segmentation flow.

RESULTS

The segmentation technique is validated in a public dataset (NIH Pancreas-CT) with 82 abdominal contrast-enhanced 3D CT scans. Fourfold cross-validation is performed to assess the capability and robustness of our method. The dice similarity coefficient, sensitivity, and specificity of our results are 86.21 ± 4.37%, 87.49 ± 6.38% and 85.11 ± 6.49% respectively, which is the state-of-the-art performance in this dataset.

CONCLUSIONS

We proposed an automatic pancreas segmentation framework and validate in an open dataset. It is found that 2.5D network benefits from multi-level slice interaction and suitable self-supervised learning method for pre-training can boost the performance of neural network. This technique could provide new image findings for the routine diagnosis of pancreatic disease.

Adipose Tissue Composition in Obesity and After Bariatric Surgery

The adipose tissue is a complex organ that regulates food intake and energy expenditure as well as induces low-grade inflammation. This review deals with changes in the composition and activity of the adipose organ after bariatric surgery, focusing on epicardial and ectopic fat and on relationships between white and brown adipose tissues. Postoperative improvements of ectopic fat and epicardial fat size and composition account for the metabolic recovery and the decreased cardiovascular risk. Following Roux-en-Y gastric bypass or biliopancreatic diversion, a proportional increase in the size and activity of the metabolically active brown adipose tissue was observed, most likely related to the postoperative rearrangement of the entero-hormonal pattern with an increase of GLP-1 production: this aspect would promote the postoperative weight loss and maintenance of post-surgery benefits.

From immunohistological to anatomical alterations of human pancreas in type 1 diabetes: New concepts on the stage

The histological analysis of human pancreatic samples in type 1 diabetes (T1D) has been proven essential to move forward in the evaluation of in situ events characterizing T1D. Increasing availability of pancreatic tissues collected from diabetic multiorgan donors by centralized biorepositories, which have shared tissues among researchers in the field, has allowed a deeper understanding of T1D pathophysiology, using novel immunohistological and high-throughput methods. In this review, we provide a comprehensive update of the main recent advancements in the characterization of cellular and molecular events involving endocrine and exocrine pancreas as well as the immune system in the onset and progression of T1D. Additionally, we underline novel elements, which provide evidence that T1D pathological changes affect not only islet β-cells but also the entire pancreas.

Repeatability and Reproducibility of Pancreas Volume Measurements Using MRI

Reduced pancreas volume, as measured by non-contrast magnetic resonance imaging (MRI), is observed in individuals with newly-diagnosed type 1 diabetes (T1D) and declines over the first year after diagnosis. In this study, we determined the repeatability and inter-reader reproducibility of pancreas volume measurements by MRI. Test-retest scans in individuals with or without T1D (n = 16) had an intraclass correlation coefficient (ICC) of 0.985 (95% CI 0.961 to 0.995) for pancreas volume. Independent pancreas outlines by two board-certified radiologists (n = 30) yielded an ICC of 0.945 (95% CI 0.889 to 0.973). The mean Dice coefficient, a measurement of the degree of overlap between pancreas regions of interest between the two readers, was 0.77. Prandial state did not influence pancreatic measurements, as stomach volume did not correlate with pancreas volume. These data demonstrate that MRI measurements of pancreas volume between two readers are repeatable and reproducible with ICCs that correspond to excellent clinical significance (ICC > 0.9), are not related to changes in stomach volume, and could be a useful tool for clinical investigation of diabetes and other pancreas pathologies.

Quantitative Magnetic Resonance Imaging of the Pancreas of Individuals With Diabetes

Magnetic resonance imaging (MRI) has the potential to improve our understanding of diabetes and improve both diagnosis and monitoring of the disease. Although the spatial resolution of MRI is insufficient to directly image the endocrine pancreas in people, the increasing awareness that the exocrine pancreas is also involved in diabetes pathogenesis has spurred new MRI applications. These techniques build upon studies of exocrine pancreatic diseases, for which MRI has already developed into a routine clinical tool for diagnosis and monitoring of pancreatic cancer and pancreatitis. By adjusting the imaging contrast and carefully controlling image acquisition and processing, MRI can quantify a variety of tissue pathologies. This review introduces a number of quantitative MRI techniques that have been applied to study the diabetic pancreas, summarizes progress in validating and standardizing each technique, and discusses the need for image analyses that account for spatial heterogeneity in the pancreas.

Glucose dysregulation in patients with iron overload: is there a relationship with quantitative pancreas and liver iron and fat content measured by MRI?

OBJECTIVES

The aim was to investigate the relationship between pancreatic and hepatic iron and fat to glucose metabolism in patients with iron overload and address conflicting results in literature as regards the relationship between pancreas iron and glucose dysregulation.

METHODS

We retrospectively evaluated pancreatic and hepatic R2*, fat fraction (FF), liver iron concentration (LIC), and glucose metabolism in 105 patients with iron overload obtained with a multi-echo gradient echo R2* technique and assessed the correlation between pancreatic R2* and FF to glucose dysregulation.

RESULTS

There were no significant differences in pancreatic R2*, liver R2*, and FF in patients with iron overload and glucose dysregulation compared to those with normoglycemia (p = 0.435, p = 0.674, and p = 0.976), whereas pancreatic FF was significantly higher, 23.5% vs 16.7% respectively (p = 0.011). Pancreatic FF and R2* demonstrated an area under the curve of 0.666 and 0.571 for discriminating glucose dysregulation. Pancreatic FF of 26.2% yielded specificity and sensitivity of 80% and 45% for prediction of glucose dysregulation. Pancreatic R2* weakly correlated with pancreatic FF, r = 0.388 (p < 0.001), and liver R2*, r = 0.201 (p = 0.033), and showed no correlation with hepatic FF r = -0.013 (p = 0.892) or LIC categories (p = 0.493).

CONCLUSION

Pancreatic FF but not pancreatic R2* was associated with glucose dysregulation in patients with iron overload. Prior studies reporting correlation of pancreatic R2* to glucose dysregulation likely relate from inadequate MRI technique or analysis employed, which unlike our study did not perform simultaneous measurements of fat and iron essential to avoid their confounding effects during quantitative analysis.

KEY POINTS

• Pancreatic fat fraction, unlike iron, is associated with glucose dysregulation in iron overload. • Simultaneous measurement of pancreatic iron and fat content with MRI is essential to avoid confounding effects of one another during quantitative analysis. • Pancreatic fat fraction could be utilized to predict glucose dysregulation in iron overload states.

No acute pancreatitis but reduced exocrine pancreatic function at diagnosis of type 1 diabetes in children

BACKGROUND

Insulitis in type 1 diabetes (T1D) seems to be both mild and rather rare, and immune cells are found also in the exocrine pancreas, which often is small. We wanted to see whether clinical pancreatitis at diagnosis of T1D in children is a commonly missed diagnosis.

METHODS

Clinical symptoms suggesting pancreatitis were investigated in a retrospective case-control study in 191 newly diagnosed T1D patients (105 boys, 86 girls) with age at onset 0.2 to 18 (mean = 10.05, SD = 4.71, median = 10.36) years, 23/191 (12%) with ketoacidosis at diagnosis. Blood samples were taken on day 4 and stored at -20°C until analyses for P-amylase and C-reactive protein (CRP), and compared with 100 age-matched healthy control children with plasma stored at -80°C, and 46 with plasma stored at -20°C.

RESULTS

At diagnosis, 23/191 (12%) patients had mild transient abdominal pain, 2/23 with obstipation, and 5/23 also transient mild diarrhea. Five of 23 patients with abdominal pain had pH < 7.30. None had clinical acute pancreatitis. One diabetic patient had P-amylase 1.3 μkat/L (normal range = 0.15-1.1 μkat/L), while 62/191 (32.4%) diabetic children had P-amylase below the normal range. None (0/100) of the -80-controls and only 1/46 (0.14 μkat/L) of the -20-controls had the P-amylase level in the normal range. Five diabetic children, but no controls, had increased CRP, but not related to P-amylase or to gastrointestinal symptoms.

CONCLUSIONS

Acute pancreatitis seems to be very rare at diagnosis of T1D, but decreased exocrine function quite common, which supports that T1D sometimes is part of a more generalized pancreatic disorder.

Metabolomic Characteristics of Fatty Pancreas

Objective Pancreatic steatosis is associated with impaired beta cell function in patients with prediabetes. The pathomechanisms underlying this association still remain to be elucidated. Recent data show that adipocytes are situated within the pancreatic parenchyma and therefore give raise to hypothesize that pancreatic fat together with known and unknown metabolites such as hepatokines affect insulin secretion. Applying a targeted metabolomic approach we investigated possible circulating markers of pancreatic fat in order to better understand its role in the pathophysiology of impaired beta cell function.

Methods We included 361 Caucasians, at increased risk of type 2 diabetes, from the Tübingen Family Study. All participants underwent a frequently sampled oral glucose tolerance test to assess insulin secretion and a magnetic resonance imaging to quantify pancreatic fat content, total body fat and visceral fat. Among the 152 subjects with prediabetes (IFG and/or IGT), two groups each with 20 individuals, having the lowest and highest pancreatic fat content were selected. The groups were matched for sex, age, BMI, total fat content, visceral fat content, liver fat content and insulin sensitivity. Metabolites were analyzed using the AbsoluteIDQ® p400 HR Kit by Biocrates.

Results Pancreatic fat content of all 152 subjects with prediabetes was negatively associated with insulin secretion represented by AUCC-peptide 0–120/AUCGlucose 0–120 (p=0.04; β=− 3.24). Furthermore, pancreatic fat content was positively associated with BMI, total body and visceral fat (all p<0.005). Levels of aminoacids, biogenic amines and monosaccharides were similar between the groups with high/low pancreatic fat content (p>0.90). Also, levels of polar lipids such as lysophosphatidylcholines, phosphatidylcholines, sphingomyelins and ceramides did not differ significantly between the groups (p>0.90). Investigating the levels of neutral lipids such as aclycarnitines, diglycerides, triglycerides and cholesteryl esters also revealed no differences between the groups (p>0.90).

Conclusion The amount of pancreatic fat is not associated with the metabolomic pattern in individuals with prediabetes. This might be due to the relatively low pancreatic fat content compared to the total amount of fat stored in other depots. The impact of pancreatic steatosis on insulin secretion might be mediated by paracrine effects which cannot be detected in the circulation.

Connecting pancreatic islet lipid metabolism with insulin secretion and the development of type 2 diabetes

Obesity is the major contributing factor for the increased prevalence of type 2 diabetes (T2D) in recent years. Sustained positive influx of lipids is considered to be a precipitating factor for beta cell dysfunction and serves as a connection between obesity and T2D. Importantly, fatty acids (FA), a key building block of lipids, are a double-edged sword for beta cells. FA acutely increase glucose-stimulated insulin secretion through cell-surface receptor and intracellular pathways. However, chronic exposure to FA, combined with elevated glucose, impair the viability and function of beta cells in vitro and in animal models of obesity (glucolipotoxicity), providing an experimental basis for the propensity of beta cell demise under obesity in humans. To better understand the two-sided relationship between lipids and beta cells, we present a current view of acute and chronic handling of lipids by beta cells and implications for beta cell function and health. We also discuss an emerging role for lipid droplets (LD) in the dynamic regulation of lipid metabolism in beta cells and insulin secretion, along with a potential role for LD under nutritional stress in beta cells, and incorporate recent advancement in the field of lipid droplet biology.

A free-choice high-fat, high-sucrose diet induces hyperphagia, obesity, and cardiovascular dysfunction in female cycling and pregnant rats

The main objective of these studies was to characterize metabolic, body composition, and cardiovascular responses to a free-choice high-fat, high-sucrose diet in female cycling and pregnant rats. In the nonpregnant state, female Sprague-Dawley rats offered a 3-wk free-choice high-fat, high-sucrose diet had greater energy intake, adiposity, serum leptin, and triglyceride concentrations compared with rats fed with standard chow and developed glucose intolerance. In addition, choice-diet-fed rats had larger cardiac ventricular weights, smaller kidney and pancreas weights, and higher blood pressure than chow-fed rats, but they did not exhibit resistance artery endothelial dysfunction. When the free-choice diet continued throughout pregnancy, rats remained hyperphagic, hyperleptinemic, and obese. Choice pregnant rats exhibited uterine artery endothelial dysfunction and had smaller fetuses compared with chow pregnant rats. Pregnancy normalized mean arterial blood pressure and pancreas weights in choice rats. These studies are the first to provide a comprehensive evaluation of free-choice high-fat, high-sucrose diet on metabolic and cardiovascular functions in female rats, extending the previous studies in males to female cycling and pregnant rodents. Free-choice diet may provide a new model of preconceptual maternal obesity to study the role of increased energy intake, individual food components, and preexisting maternal obesity on maternal and offspring physiological responses during pregnancy and after birth.

Relative Pancreas Volume Is Reduced in First-Degree Relatives of Patients With Type 1 Diabetes

OBJECTIVE

Pancreas size is reduced in patients at type 1 diabetes onset and in autoantibody (AAB)-positive donors without diabetes. We sought to determine whether pancreas volume (PV) imaging could improve understanding of the loss of pancreas size in first-degree relatives (FDRs) of patients with type 1 diabetes. We also examined relationships among PV, AAB status, and endocrine and exocrine functions.

RESEARCH DESIGN AND METHODS

We conducted a cross-sectional study that included five groups: AAB^- control subjects (no diabetes and no first- or second-degree relatives with type 1 diabetes) (N = 49), AAB^- FDRs (N = 61), AAB⁺ FDRs (N = 67 total: n = 31 with a single positive AAB [AAB⁺ single] and n = 36 with multiple positive AABs [AAB⁺ multiple]), and patients with recent-onset type 1 diabetes (<1 year) (N = 52). Fasting subjects underwent 1.5T pancreatic MRI, and PV and relative PV (RPV) (PV-to-BMI ratio) were analyzed between groups and for correlations with HbA_1c, C-peptide, glucose, and trypsinogen.

RESULTS

All FDR groups had significantly lower RPV adjusted for BMI (RPV_BMI) than control subjects (all P < 0.05). Patients with type 1 diabetes had lower RPV_BMI than AAB^- FDR (P < 0.0001) and AAB⁺ multiple (P ≤ 0.013) subjects. Transformed data indicated that trypsinogen levels were lowest in patients with type 1 diabetes.

CONCLUSIONS

This study demonstrates, for the first time, all FDRs having significantly smaller RPV_BMI compared with AAB^- control subjects. Furthermore, RPV_BMI was significantly lower in patients with recent-onset type 1 diabetes than in the AAB^- FDR and AAB⁺ multiple groups. As such, RPV_BMI may be a novel noninvasive biomarker for predicting progression through stages of type 1 diabetes risk. This study highlights the potential paracrine relationships between the exocrine and endocrine pancreas in progression to type 1 diabetes in subjects at risk.

Pancreas Volume Declines During the First Year After Diagnosis of Type 1 Diabetes and Exhibits Altered Diffusion at Disease Onset

OBJECTIVE

This study investigated the temporal dynamics of pancreas volume and microstructure in children and adolescents with recent-onset type 1 diabetes (T1D) and individuals without diabetes, including a subset expressing autoantibodies associated with the early stages of T1D.

RESEARCH DESIGN AND METHODS

MRI was performed in individuals with recent-onset stage 3 T1D (n = 51; median age 13 years) within 100 days after diagnosis (mean 67 days), 6 months, and 1 year postdiagnosis. Longitudinal MRI measurements were also made in similarly aged control participants (n = 57) and in autoantibody-positive individuals without diabetes (n = 20). The MRI protocol consisted of anatomical imaging to determine pancreas volume and quantitative MRI protocols interrogating tissue microstructure and composition.

RESULTS

Within 100 days of diabetes onset, individuals with T1D had a smaller pancreas (median volume 28.6 mL) than control participants (median volume 48.4 mL; P < 0.001), including when normalized by individual weight (P < 0.001). Longitudinal measurements of pancreas volume increased in control participants over the year, consistent with adolescent growth, but pancreas volume declined over the first year after T1D diagnosis (P < 0.001). In multiple autoantibody-positive individuals, the pancreas volume was significantly larger than that of the T1D cohort (P = 0.017) but smaller than that of the control cohort (P = 0.04). Diffusion-weighted MRI showed that individuals with recent-onset T1D had a higher apparent diffusion coefficient (P = 0.012), suggesting a loss of cellular structural integrity, with heterogeneous pancreatic distribution.

CONCLUSIONS

These results indicate that pancreas volume is decreased in stages 1, 2, and 3 of T1D and decreases during the first year after diabetes onset and that this loss of pancreatic volume is accompanied by microstructural changes.

Detection and quantification of beta cells by PET imaging: why clinical implementation has never been closer

In this issue of Diabetologia, Alavi and Werner ( https://doi.org/10.1007/s00125-018-4676-1 ) criticise the attempts to use positron emission tomography (PET) for in vivo imaging of pancreatic beta cells, which they consider as 'futile'. In support of this strong statement, they point out the limitations of PET imaging, which they believe render beta cell mass impossible to estimate using this method. In our view, the Alavi and Werner presentation of the technical limitations of PET imaging does not reflect the current state of the art, which leads them to questionable conclusions towards the feasibility of beta cell imaging using this approach. Here, we put forward arguments in favour of continuing the development of innovative technologies enabling in vivo imaging of pancreatic beta cells and concisely present the current state of the art regarding putative technical limitations of PET imaging. Indeed, far from being a 'futile' effort, we demonstrate that beta cell imaging is now closer than ever to becoming a long-awaited clinical reality.

Comparison of pancreatic volume and fat amount linked with glucose homeostasis between healthy Caucasians and Koreans

AIM

To compare pancreatic volume and fat amount, and their associations with glucose homeostasis, in a Korean and a white population.

MATERIALS AND METHODS

In 43 healthy Korean and 43 healthy white people, matched for age (±3 years) and body mass index (BMI; ±1 kg/m² ), we measured pancreatic volume and fat amount in the pancreas and abdomen using computed tomography. Pancreatic β-cell function and insulin resistance were estimated according to biochemical characteristics and a 75-g oral glucose tolerance test. Body composition and resting energy expenditure (REE) were examined using bioimpedance and indirect calorimetry, respectively.

RESULTS

The mean ±SD age of the participants was 29.9 ± 5.9 years and 30.0 ± 5.2 years, and BMI was 24.0 ±3.7 and 24.1 ±3.2 kg/m² in the white participants and the Korean participants, respectively. Pancreatic volume in the white participants was greater than that in Korean participants (77.8 ±11.6 vs 68.2 ±12.1 cm³ ; P < .001). Pancreatic fat content in Korean participants was 22.8% higher than in white participants (P = .051). Insulinogenic index, disposition index, muscle mass and REE were significantly lower in Korean participants. Pancreatic volume was positively associated with indices linked to β-cell function; fat content in the pancreas was negatively associated with such indices, and positively with insulin resistance after adjusting for relevant variables including REE.

CONCLUSIONS

A smaller pancreas and higher fat deposition might be crucial determinants of vulnerability to diabetes in Korean people compared with white people with similar BMI and body fat levels.