Multiscale and multimodal imaging for three-dimensional vascular and histomorphological organ structure analysis of the pancreas.

Exocrine and endocrine pancreas are interconnected anatomically and functionally, with vasculature facilitating bidirectional communication. Our understanding of this network remains limited, largely due to two-dimensional histology and missing combination with three-dimensional imaging. In this study, a multiscale 3D-imaging process was used to analyze a porcine pancreas. Clinical computed tomography, digital volume tomography, micro-computed tomography and Synchrotron-based propagation-based imaging were applied consecutively. Fields of view correlated inversely with attainable resolution from a whole organism level down to capillary structures with a voxel edge length of 2.0 µm. Segmented vascular networks from 3D-imaging data were correlated with tissue sections stained by immunohistochemistry and revealed highly vascularized regions to be intra-islet capillaries of islets of Langerhans. Generated 3D-datasets allowed for three-dimensional qualitative and quantitative organ and vessel structure analysis. Beyond this study, the method shows potential for application across a wide range of patho-morphology analyses and might possibly provide microstructural blueprints for biotissue engineering.

Application of artificial intelligence in pancreas endoscopic ultrasound imaging- A systematic review.

The pancreas is a vital organ in digestive system which has significant health implications. It is imperative to evaluate and identify malignant pancreatic lesions promptly in light of the high mortality rate linked to such malignancies. Endoscopic Ultrasound (EUS) is a non-invasive precise technique to detect pancreas disorders, but it is highly operator dependent. Artificial intelligence (AI), including traditional machine learning (ML) and deep learning (DL) techniques can play a pivotal role to enhancing the performance of EUS regardless of operator. AI performs a critical function in the detection, classification, and segmentation of medical images. The utilization of AI-assisted systems has improved the accuracy and productivity of pancreatic analysis, including the detection of diverse pancreatic disorders (e.g., pancreatitis, masses, and cysts) as well as landmarks and parenchyma. This systematic review examines the rapidly developing domain of AI-assisted system in EUS of the pancreas. Its objective is to present a thorough study of the present research status and developments in this area. This paper explores the significant challenges of AI-assisted system in pancreas EUS imaging, highlights the potential of AI techniques in addressing these challenges, and suggests the scope for future research in domain of AI-assisted EUS systems.

Cavitron ultrasonic surgical aspirator (CUSA) compared with conventional pancreatic transection in distal pancreatectomy: study protocol for the randomised controlled CUSA-1 pilot trial.

BACKGROUND: Postoperative pancreatic fistula (POPF) remains the most common and serious complication after distal pancreatectomy. Many attempts at lowering fistula rates have led to unrewarding insignificant results as still up to 30% of the patients suffer from clinically relevant POPF. Therefore, the development of new innovative methods and procedures is still a cornerstone of current surgical research.The cavitron ultrasonic surgical aspirator (CUSA) device is a well-known ultrasound-based parenchyma transection method, often used in liver and neurosurgery which has not yet been thoroughly investigated in pancreatic surgery, but the first results seem very promising. METHODS: The CUSA-1 trial is a randomised controlled pilot trial with two parallel study groups. This single-centre trial is assessor and patient blinded. A total of 60 patients with an indication for open distal pancreatectomy will be intraoperatively randomised after informed consent. The patients will be randomly assigned to either the control group with conventional pancreas transection (scalpel or stapler) or the experimental group, with transection using the CUSA device. The primary safety endpoint of this trial will be postoperative complications ≥grade 3 according to the Clavien-Dindo classification. The primary endpoint to investigate the effect will be the rate of POPF within 30 days postoperatively according to the ISGPS definition. Further perioperative outcomes, including postpancreatectomy haemorrhage, length of hospital stay and mortality will be analysed as secondary endpoints. DISCUSSION: Based on the available literature, CUSA may have a beneficial effect on POPF occurrence after distal pancreatectomy. The rationale of the CUSA-1 pilot trial is to investigate the safety and feasibility of the CUSA device in elective open distal pancreatectomy compared with conventional dissection methods and gather the first data on the effect on POPF occurrence. This data will lay the groundwork for a future confirmatory multicentre randomised controlled trial. ETHICS AND DISSEMINATION: The CUSA-1 trial protocol was approved by the ethics committee of the University of Heidelberg (No. S-098/2022). Results will be published in an international peer-reviewed journal and summaries will be provided in lay language to study participants and their relatives. TRIAL REGISTRATION NUMBER: DRKS00027474.

Visual Interpretation of Radiomics Features in Filtered Computed Tomography Images during the Portal Phase of Acute Pancreatitis.

BACKGROUND: Current research on radiomics for diagnosing and prognosing acute pancreatitis predominantly revolves around model development and testing. However, there is a notable absence of ongoing interpretation and analysis regarding the physical significance of these models and features. Additionally, there is a lack of extensive exploration of visual information within the images. This limitation hinders the broad applicability of radiomics findings. This study aims to address this gap by specifically analyzing filtered Computed Tomography (CT) image features of acute pancreatitis to identify meaningful visual markers in the pancreas and peripancreatic area. METHODS: Numerous filtered CT images were obtained through pyradiomics. The window width and window level were fine-tuned to emphasize the pancreas and peripancreatic regions. Subsequently, the LightGBM algorithm was employed to conduct an embedded feature screening, followed by statistical analysis to identify features with statistical significance (p-value < 0.01). Within the purview of the study, for each filtering method, features of high importance to the preceding prediction model were incorporated into the analysis. The image visual markers were then systematically sought in reverse, and their medical interpretation was undertaken to a certain extent. RESULTS: In Laplacian of Gaussian filtered images within the pancreatic region, severe acute pancreatitis (SAP) exhibited fewer small areas with repetitive greyscale patterns. Conversely, in the peripancreatic region, SAP displayed greater irregularity in both area size and the distribution of greyscale levels. In logarithmic images, SAP demonstrated reduced low greyscale connectivity in the pancreatic region, while showcasing a higher average variation in greyscale between two adjacent pixels in the peripancreatic region. Moreover, in gradient images, SAP presented with decreased repetition of two adjacent pixel greyscales within the pancreatic region, juxtaposed with an increased inhomogeneity in the size of the same greyscale region within the δ range in the peripancreatic region. CONCLUSIONS: Various filtered images convey distinct physical significance and properties. The selection of the appropriate filtered image, contingent upon the characteristics of the Region of Interest (ROI), enables a more comprehensive capture of the heterogeneity of the disease.

CBCT-DRRs superior to CT-DRRs for target-tracking applications for pancreatic SBRT.

Objective.In current radiograph-based intra-fraction markerless target-tracking, digitally reconstructed radiographs (DRRs) from planning CTs (CT-DRRs) are often used to train deep learning models that extract information from the intra-fraction radiographs acquired during treatment. Traditional DRR algorithms were designed for patient alignment (i.e.bone matching) and may not replicate the radiographic image quality of intra-fraction radiographs at treatment. Hypothetically, generating DRRs from pre-treatment Cone-Beam CTs (CBCT-DRRs) with DRR algorithms incorporating physical modelling of on-board-imagers (OBIs) could improve the similarity between intra-fraction radiographs and DRRs by eliminating inter-fraction variation and reducing image-quality mismatches between radiographs and DRRs. In this study, we test the two hypotheses that intra-fraction radiographs are more similar to CBCT-DRRs than CT-DRRs, and that intra-fraction radiographs are more similar to DRRs from algorithms incorporating physical models of OBI components than DRRs from algorithms omitting these models.Approach.DRRs were generated from CBCT and CT image sets collected from 20 patients undergoing pancreas stereotactic body radiotherapy. CBCT-DRRs and CT-DRRs were generated replicating the treatment position of patients and the OBI geometry during intra-fraction radiograph acquisition. To investigate whether the modelling of physical OBI components influenced radiograph-DRR similarity, four DRR algorithms were applied for the generation of CBCT-DRRs and CT-DRRs, incorporating and omitting different combinations of OBI component models. The four DRR algorithms were: a traditional DRR algorithm, a DRR algorithm with source-spectrum modelling, a DRR algorithm with source-spectrum and detector modelling, and a DRR algorithm with source-spectrum, detector and patient material modelling. Similarity between radiographs and matched DRRs was quantified using Pearson's correlation and Czekanowski's index, calculated on a per-image basis. Distributions of correlations and indexes were compared to test each of the hypotheses. Distribution differences were determined to be statistically significant when Wilcoxon's signed rank test and the Kolmogorov-Smirnov two sample test returnedp≤ 0.05 for both tests.Main results.Intra-fraction radiographs were more similar to CBCT-DRRs than CT-DRRs for both metrics across all algorithms, with allp≤ 0.007. Source-spectrum modelling improved radiograph-DRR similarity for both metrics, with allp< 10-6. OBI detector modelling and patient material modelling did not influence radiograph-DRR similarity for either metric.Significance.Generating DRRs from pre-treatment CBCT-DRRs is feasible, and incorporating CBCT-DRRs into markerless target-tracking methods may promote improved target-tracking accuracies. Incorporating source-spectrum modelling into a treatment planning system's DRR algorithms may reinforce the safe treatment of cancer patients by aiding in patient alignment.

Pancreaticoduodenectomy with Anatomical Vascular Variant in Groove Pancreatitis-A Case Report.

Groove pancreatitis represents a chronic focal form of pancreatitis affecting the zone between the pancreatic head and the duodenal "C" loop, known as the groove area. This is a rare condition that affects the pancreatic periampullary part, including the duodenum and the common bile duct, which is usually associated with long-term alcohol and tobacco misuse, and is more frequent in men than in women. The most common clinical symptoms of groove pancreatitis include weight loss, acute abdominal pain, nausea, and jaundice. This report is about a 66-year-old woman with a history of heavy smoking, presenting with weight loss, nausea, and upper abdominal pain. Contrast-enhanced computed tomography revealed the existence of chronic pancreatitis as well as the dilatation of the main pancreatic duct, a cyst of the pancreatic head, and enlargement of the biliary tract. Conservatory treatment was initiated but with no improvement of symptoms. Since endoscopic retrograde cholangiopancreatography was not possible due to the local changes, we decided to perform pancreatoduodenectomy, as surgery appears to be the single effective treatment.

Pancreaticoureteric fistula following penetrating abdominal trauma: A Case Report.

Pancreaticoureteric Fistula (PUF) is a very rare complication secondary to penetrating abdominal trauma involving the ureter and pancreatic parenchyma. Pancreatic injuries carry h igh morbidity due to the involvem ent of surrounding structures and are d ifficult to diagnose due to thei r retroperitoneal location. A case of a patient is reported at Civil Hospital, Hyderabad who presented with a history of firearm injury and missed pancreatic duct involvement on initial exploration that eventually led to the development of Pan creaticoureteric Fistula. He was managed v ia p erc ut aneous nep hrostomy ( PCN ) for the right ureteric injury and pancreatic duct (PD) stenting was done for distal main pancreatic duct injury (MPD).

Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives.

Postoperative pancreatic fistula (POPF) is a frequent complication after pancreatectomy, leading to increased morbidity and mortality. Optimizing prediction models for POPF has emerged as a critical focus in surgical research. Although over sixty models following pancreaticoduodenectomy, predominantly reliant on a variety of clinical, surgical, and radiological parameters, have been documented, their predictive accuracy remains suboptimal in external validation and across diverse populations. As models after distal pancreatectomy continue to be progressively reported, their external validation is eagerly anticipated. Conversely, POPF prediction after central pancreatectomy is in its nascent stage, warranting urgent need for further development and validation. The potential of machine learning and big data analytics offers promising prospects for enhancing the accuracy of prediction models by incorporating an extensive array of variables and optimizing algorithm performance. Moreover, there is potential for the development of personalized prediction models based on patient- or pancreas-specific factors and postoperative serum or drain fluid biomarkers to improve accuracy in identifying individuals at risk of POPF. In the future, prospective multicenter studies and the integration of novel imaging technologies, such as artificial intelligence-based radiomics, may further refine predictive models. Addressing these issues is anticipated to revolutionize risk stratification, clinical decision-making, and postoperative management in patients undergoing pancreatectomy.

IgG4-related autoimmune pancreatitis and sclerosing cholangitis: A case report and literature review.

RATIONALE: Immunoglobulin G4-related disease (IgG4-RD) can involve various organs throughout the body, primarily manifesting as endocrine dysfunction, visual impairment, jaundice, and limited sexual function. IgG4-related autoimmune pancreatitis is triggered by autoimmune reactions and characterized by structural changes in the pancreas and pancreatic ducts. The disease mainly affects middle-aged and elderly males, typically presenting as progressive painless jaundice and misdiagnosed as cholangiocarcinoma or pancreatic cancer. PATIENT CONCERNS: This study reports a 54-year-old male who consulted with different institutions multiple times due to diabetes, pancreatitis, elevated liver enzymes, and jaundice. DIAGNOSES: Magnetic resonance imaging revealed swollen head of the pancreas and atrophic tail. Liver and pancreatic tissue pathology showed IgG4 plasma cell infiltration, while liver biopsy indicated interface hepatitis, liver fibrosis, and pseudolobule formation, with no evidence of bile duct damage. INTERVENTIONS: Following hormone therapy, the patient's serum IgG4 levels and liver enzyme levels returned to normal. OUTCOMES: The disease relapsed 2 years after maintaining hormone therapy, and the patient underwent additional hormone-induced remission therapy combined with azathioprine. LESSONS: The purpose of this research report is to enhance the awareness and understanding of IgG4-RD, emphasizing the necessity for personalized treatment strategies that take into account its recurrence, associations, and imaging features. This report provides valuable insights and guidance for clinicians in managing and diagnosing patients with IgG4-RD.

An improvement method for pancreas CT segmentation using superpixel-based active contour.

Objective.Pancreas is one of the most challenging organs for Computed Tomograph (CT) image automatic segmentation due to its complex shapes and fuzzy edges. It is simple and universal to use the traditional segmentation method as a post-processor of deep learning method for segmentation accuracy improvement. As the most suitable traditional segmentation method for pancreatic segmentation, the active contour model (ACM), still suffers from the problems of weak boundary leakage and slow contour evolution speed. Therefore, a convenient post-processor for any deep learning methods using superpixel-based active contour model (SbACM) is proposed to improve the segmentation accuracy.Approach.Firstly, the superpixels with strong adhesion to edges are used to guide the design of narrowband and energy function. A multi-scale evolution strategy is also proposed to reduce the weak boundary leakage and comprehensively improve the evolution speed. Secondly, using the original image and the coarse segmentation results obtained from deep learning methods as inputs, the proposed SbACM method is used as a post-processor for fine segmentation. Finally, the pancreatic segmentation public dataset TCIA from the National Institutes of Health(NIH, USA) is used for evaluation, and the Wilcoxon Test confirmed that the improvement of proposed method is statistically significant.Main results.(1) the superpixel-based narrowband shape and dynamic edge energy of the proposed SbACM work for boundary leakage reduction, as well as the multi-scale evolution strategy and dynamic narrowband width for the evolution speed improvement; (2) as a post-processor, SbACM can increase the Dice similarity coefficients (DSC) of five typical UNet-based models, including UNet, SS-UNet, PBR UNet, ResDSN, and nnUNet, 2.35% in average and 9.04% in maximum. (3) Based on the best backbone nnUNet, the proposed post-processor performs better than either adding edge awareness or adding edge loss in segmentation enhancement without increasing the complexity and training time of deep learning models.Significance.The proposed SbACM can improve segmentation accuracy with the lowest cost, especially in cases of squeezed fuzzy edges with similar neighborhood , and complex edges.

Deep causal learning for pancreatic cancer segmentation in CT sequences.

Segmenting the irregular pancreas and inconspicuous tumor simultaneously is an essential but challenging step in diagnosing pancreatic cancer. Current deep-learning (DL) methods usually segment the pancreas or tumor independently using mixed image features, which are disrupted by surrounding complex and low-contrast background tissues. Here, we proposed a deep causal learning framework named CausegNet for pancreas and tumor co-segmentation in 3D CT sequences. Specifically, a causality-aware module and a counterfactual loss are employed to enhance the DL network's comprehension of the anatomical causal relationship between the foreground elements (pancreas and tumor) and the background. By integrating causality into CausegNet, the network focuses solely on extracting intrinsic foreground causal features while effectively learning the potential causality between the pancreas and the tumor. Then based on the extracted causal features, CausegNet applies a counterfactual inference to significantly reduce the background interference and sequentially search for pancreas and tumor from the foreground. Consequently, our approach can handle deformable pancreas and obscure tumors, resulting in superior co-segmentation performance in both public and real clinical datasets, achieving the highest pancreas/tumor Dice coefficients of 86.67%/84.28%. The visualized features and anti-noise experiments further demonstrate the causal interpretability and stability of our method. Furthermore, our approach improves the accuracy and sensitivity of downstream pancreatic cancer risk assessment task by 12.50% and 50.00%, respectively, compared to experienced clinicians, indicating promising clinical applications.

Pancreatic neuroendocrine tumour resection in circumportal pancreas: a rare anatomical anomaly with important surgical implications.

Various congenital anomalies of the pancreas have been reported due to its complex embryological development involving the fusion of two separate buds. Circumportal pancreas is a rare anatomical anomaly where the pancreatic head and uncinate process fuse abnormally with the pancreatic body, encasing the portal vein and/or superior mesenteric vein completely. This anomaly poses several challenges to hepatobiliary surgeons, as the encasement of the portal vein by the abnormal pancreatic tissue makes an additional parenchymal transection necessary. Vascular variants have also been reported with circumportal pancreas, which, if not recognised preoperatively, can be catastrophic. Therefore, careful preoperative evaluation and planning are essential, to ensure safe pancreatic resection and recovery in a patient with circumportal pancreas. We present a case of a successful subtotal pancreatectomy and splenectomy in a patient with circumportal pancreas, for a suspected pancreatic duct adenocarcinoma. The aim of this case report is to contribute valuable insights that can aid hepatobiliary surgeons in enhancing their preoperative planning when encountered with patients with similar anatomical variances.

Sutton-Kadir Syndrome can be treated safely with endovascular embolisation alone.

INTRODUCTION: Sutton-Kadir Syndrome (SKS) describes true inferior pancreaticoduodenal artery (IPDA) aneurysms in the setting of coeliac artery (CA) stenosis or occlusion. Although rare, SKS aneurysms can rupture and cause morbidity. Due to its rarity and lack of controlled treatment data, correct treatment for the CA lesion is currently unknown. Our aim was to assess if endovascular embolisation alone was safe and effective in treatment of SKS aneurysms, in emergent and elective settings. Secondary objectives were to describe presentation and imaging findings. METHODS: A retrospective cohort study of patients treated at Sir Charles Gairdner Hospital between January 2014 and December 2021 was done. Data on presentation, diagnostics, aneurysm characteristics, CA lesion aetiology, treatment and outcomes were extracted from chart review. RESULTS: Twenty-four aneurysms in 14 patients were identified. Rupture was seen in 7/15 patients. Most aneurysms (22/24) were in the IPDA or one of its anterior or posterior branches. Median arcuate ligament (MAL) compression was identified in all. There was no difference in median (IQR) maximal transverse diameter between ruptured and non-ruptured aneurysms (6 mm (9), 12 mm (6), P = 0.18). Of ruptures, 6/7 had successful endovascular embolisation and 1/7 open surgical ligation. Of non-ruptures, 6/7 had successful endovascular embolisation, 1/7 open MAL division then endovascular CA stenting and aneurysm embolisation. No recurrences or new aneurysms were detected with computed tomography or magnetic resonance angiography over a median (IQR) follow-up period of 30 (10) months in 12 patients. CONCLUSION: Endovascular embolisation of SKS aneurysms without treatment of MAL compression is safe and effective in both the emergent and elective settings.

Effect of X-ray tube on image quality and pancreatic ductal adenocarcinoma conspicuity in pancreatic protocol dual-energy CT.

AIM: To compare the radiation dose, image quality, and conspicuity of pancreatic ductal adenocarcinoma (PDAC) in pancreatic protocol dual-energy computed tomography (CT) between two X-ray tubes mounted in the same CT machine. MATERIAL AND METHODS: This retrospective study comprised 80 patients (median age, 73 years; 45 men) who underwent pancreatic protocol dual-energy CT from January 2019 to March 2022 using either old (Group A, n=41) or new (Group B, n=39) X-ray tubes mounted in the same CT machine. The imaging parameters were completely matched between the two groups, and CT data were reconstructed at 70 and 40 keV. The CT dose-index volume (CTDIvol); CT attenuation of the abdominal aorta, pancreas, and PDAC; background noise; and qualitative scores for the image noise, overall image quality, and PDAC conspicuity were compared between the two groups. RESULTS: The CTDIvol was lower in Group B than Group A (7.9 versus 9.2 mGy; p<0.001). The CT attenuation of all anatomical structures at 70 and 40 keV was comparable between the two groups (p=0.06-0.78). The background noise was lower in Group B than Group A (12 versus 14 HU at 70 keV, p=0.046; and 26 versus 30 HU at 40 keV, p<0.001). Qualitative scores for image noise and overall image quality at 70 and 40 keV and PDAC conspicuity at 40 keV were higher in Group B than Group A (p<0.001-0.045). CONCLUSION: The latest X-ray tube could reduce the radiation dose and improve image quality in pancreatic protocol dual-energy CT.

Intra-pancreatic fat is associated with continuous glucose monitoring metrics.

AIM: To investigate the relationship of fat in the pancreas with time spent in different glycaemic ranges. METHODS: Abdominal magnetic resonance imaging at 3.0 Tesla was used to quantify fat in the pancreas as both continuous [i.e. intra-pancreatic fat deposition (IPFD)] and binary (i.e. fatty change of the pancreas vs. normal pancreas) variables. Dexcom G6 devices were used to collect continuous glucose monitoring data every 5 min over a continuous 7-day period. Time above range (TAR), time in range (TIR) and time below range were computed. Statistical models were built to adjust for age, sex, body composition, and other covariates in linear regression analysis and analysis of covariance. RESULTS: In total, 38 individuals were studied. IPFD was significantly associated with TAR (p = .036) and TIR (p = .042) after adjustment for covariates. For every 1% increase in IPFD, there was a 0.3 unit increase in TAR and a decrease in TIR. Individuals with fatty change of the pancreas, when compared with those with normal pancreas, had significantly higher TAR (p = .034) and lower TIR (p = .047) after adjustment for covariates. Neither IPFD (p = .805) nor fatty change of the pancreas (p = .555) was associated with time below range after adjustment for covariates. CONCLUSION: Increased fat in the pancreas is associated with excessive glycaemic variability. Fatty change of the pancreas may contribute to heightening the risk of cardiovascular diseases.

Development of a CT-based radiomics-clinical model to diagnose acute pancreatitis on nonobvious findings on CT in children with pancreaticobiliary maljunction.

OBJECTIVES: Since neither abdominal pain nor pancreatic enzyme elevation is specific for acute pancreatitis (AP), the diagnosis of AP in patients with pancreaticobiliary maljunction (PBM) may be challenging when the pancreas appears normal or nonobvious on CT. This study aimed to develop a quantitative radiomics-based nomogram of pancreatic CT for identifying AP in children with PBM who have nonobvious findings on CT. METHODS: PBM patients with a diagnosis of AP evaluated at the Children's Hospital of Soochow University from June 2015 to October 2022 were retrospectively reviewed. The radiological features and clinical factors associated with AP were evaluated. Based on the selected variables, multivariate logistic regression was used to construct clinical, radiomics, and combined models. RESULTS: Two clinical parameters and 6 radiomics characteristics were chosen based on their significant association with AP, as demonstrated in the training (area under curve [AUC]: 0.767, 0.892) and validation (AUC: 0.757, 0.836) datasets. The radiomics-clinical nomogram demonstrated superior performance in both the training (AUC, 0.938) and validation (AUC, 0.864) datasets, exhibiting satisfactory calibration (P > .05). CONCLUSIONS: Our radiomics-based nomogram is an accurate, noninvasive diagnostic technique that can identify AP in children with PBM even when CT presentation is not obvious. ADVANCES IN KNOWLEDGE: This study extracted imaging features of nonobvious pancreatitis. Then it developed and evaluated a combined model with these features.

Pancreatic Paragonimiasis in Children: A Case Report.

ABSTRACT: A few pediatric cases of abdominal paragonimiasis have been described. Here we describe a case of pulmonary and abdominal paragonimiasis with involvement of the pancreas in a 9-year-old boy. The aim of this study was to analyze the clinical and radiological features of pancreatic paragonimiasis in children and raise the awareness of this disease.

The Signal Intensity Ratio of Pancreas to Spleen in Magnetic Resonance Imaging Can Predict Nonalcoholic Fatty Liver Disease After Pancreaticoduodenectomy.

OBJECTIVES: Signal intensity ratio of pancreas to spleen (SI ratio p/s ) on fat-suppressed T1-weighted images of magnetic resonance imaging has been associated with pancreatic exocrine function. We here investigated the predictive value of the SI ratio p/s for the development of nonalcoholic fatty liver disease (NAFLD) after pancreaticoduodenectomy (PD). MATERIALS AND METHODS: This study comprised 208 patients who underwent PD. NAFLD was defined as a liver-to-spleen attenuation ratio of <0.9 calculated by a computed tomography 1 year after surgery. SI ratio p/s was calculated by dividing the average pancreas SI by the spleen SI. We retrospectively investigated the association of clinical variables including the SI ratio p/s and NAFLD by univariate and multivariate analyses. RESULTS: NAFLD after 1 year was developed in 27 patients (13%). In multivariate analysis, the SI ratio p/s < 1 ( P < 0.001) was an independent predictor of incidence of NAFLD. The SI ratio p/s < 1 was associated with low amylase level of the pancreatic juice ( P < 0.001) and progressed pancreatic fibrosis ( P = 0.017). According to the receiver operating characteristics curve, the SI ratio p/s had better prognostic ability of NAFLD than the remnant pancreas volume. CONCLUSIONS: The SI ratio p/s is useful to predict NAFLD development after PD. Moreover, the SI ratio p/s can be a surrogate marker, which represents exocrine function of the pancreas.