Intensive Care Unit (ICU) mortality risk is high in rheumatoid arthritis (RA) patients, yet effective prognostic tools remain scarce. To develop and evaluate a machine learning (ML)-based prognostic model for predicting hospital mortality in severe RA patients. This retrospective cohort study utilized data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and the Medical Information Mart for Intensive Care Chest X-ray (MIMIC-CXR) databases, including 1,951 chest X-rays from 984 patients with RA. The primary outcome was all-cause in-hospital mortality. Radiomics features were extracted using PyRadiomics, with 74 features retained after quality control. Key features were selected using the Boruta algorithm and integrated with clinical variables to develop three modeling strategies: clinical-only, radiomics-only, and combined models. Nine ML algorithms were applied using a 60/40 training-test split with 10-fold cross-validation. To address class imbalance (mortality rate: 7.7

Background and Objective:Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid malignancies. Neoadjuvant therapy (NAT) has been routinely used in borderline resectable and locally advanced cases, now it is also gradually expanding to some resectable cases. Post-NAT assessment on computed tomography (CT) is intrinsically challenging, as therapy-induced stromal remodeling, fibrosis, and inflammation may obscure viable tumor, while size-based criteria correlate poorly with pathological response and survival. This narrative review aims to synthesize CT-based quantitative imaging features for PDAC after NAT and to clarify how these imaging biomarkers may support clinically relevant multidisciplinary decision-making. Methods:A narrative review was conducted using a three-layer literature identification strategy. A primary search of PubMed and Web of Science Core Collection was performed on 7 April 2026 to identify English-language articles published from 2013 to 2026. The search focused on PDAC, NAT, CT, and CT-derived quantitative approaches, including radiomics, perfusion CT, dual-energy/spectral CT, and photon-counting CT (PCCT), together with clinically relevant endpoints such as response, resectability, margin status, survival, recurrence, and prognosis. Targeted supplementary retrieval and manual anchor retrieval were additionally used for key reviews, foundational pathology and tumor microenvironment (TME) references, complementary magnetic resonance imaging (MRI) and positron emission tomography (PET) literature, and methodological framework papers. Key Content and Findings:Quantitative CT features after NAT can be organized around four multidisciplinary team (MDT) decisions: assessment of tumor-vessel interface resectability and the probability of margin-negative (R0) resection, NAT stewardship, surgical-window timing, and early recurrence risk stratification. The most informative measurement layers include interpretable morphologic and enhancement-based metrics, longitudinal delta features, perfusion-derived functional parameters, iodine- and material-sensitive metrics from energy-resolved CT, and multi-compartment radiomics or habitat analysis. Conclusions:Building on this evidence, we outline a pragmatic, CT-centric measurement ladder that progresses from interpretable enhancement and iodine metrics to interface focused features and habitat-level heterogeneity, aiming to reduce inter-reader variability and improve multicenter reproducibility, with MRI and PET positioned as complementary modalities for future multimodal validation.

Patients with breast cancer liver metastasis (BCLM) have a low survival rate and poor prognosis; thus, early and precise diagnosis and treatment are important. Here, we developed rutin-encapsulated manganese carbonate nanoparticles (RM NPs) for sensitive magnetic resonance imaging (MRI) diagnosis and effective inhibition of BCLM. RM NPs are nanoclusters consisting of manganese carbonate nanocrystals. They have pH-responsive properties and release Mn2+ following their uptake into cells, generating MRI signals. Using a 4T1 mouse liver metastasis model, we demonstrated different uptake rates of RM NPs between normal liver tissue and metastatic tumors. The 'liver-dark/tumor-bright' (tumor-to-normal liver contrast ratio reached 219%) phenomenon can be produced using a specific T1WI imaging sequence, which enables precise imaging of submillimeter (less than 1 mm) BCLM. In vitro and in vivo experiments confirmed that because of the rutin sugar groups on the surface of RM NPs, they actively target tumor cells with overexpressed glucose transporters (Gluts). After being taken up by tumor cells, RM NPs release rutin, which induces tumor cell apoptosis by upregulating cleaved cysteine protease-3 and thereby inhibiting tumor cell growth and liver metastasis. Overall, RM NPs can serve as an effective and safe theranostic platform for precise MRI and treatment of BCLM.

To develop and validate a machine learning (ML) model based on the modified pancreatitis activity scoring system (mPASS) and imaging features for the early assessment of multiple clinically relevant outcomes in acute pancreatitis (AP). A retrospective cohort of 420 AP patients was analyzed. Of these, 310 patients from the primary center were randomly divided into a training set and an internal validation set at a 3:1 ratio; an additional 110 patients from an external hospital served as the independent testing cohort. The Friedman test was used to compare mPASS scores at various time points. The Jonckheere‑Terpstra test assessed the ordinal trend between mPASS and 2012 Revised Atlanta Classification (RAC). The ML model was developed using the age‑adjusted Charlson Comorbidity Index (aCCI), mPASS and imaging features. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and Brier scores for calibration. No significant difference was found between mPASS scores at admission and 24 h post-admission (P = 1.000), but significant differences were observed at subsequent time points (all P < 0.05). The mPASS score at 72 h post-admission demonstrated the best predictive performance for the majority of clinically relevant outcomes, with only a marginal exception. A significant ordinal relationship existed between mPASS and 2012 RAC (P < 0.001). In the testing dataset, AUCs for the ML model ranged from 0.704 to 0.935, exceeding 0.80 for most outcomes. Calibration was acceptable to excellent for most endpoints, though marginal for hospital stay and limited for time to oral refeeding. Overall, the ML model achieved performance generally comparable to that of mPASS and the 2012 RAC, with a significant improvement for complications. Our ML model supports simultaneous multi-outcome risk assessment at this single time point. While showing promise in supporting individualized clinical decision-making, its performance warrants further refinement and prospective multicenter validation. Not applicable (This study is a retrospective analysis and does not involve any prospective health care intervention on human participants).

The pathogenesis of myocardial ischemia-reperfusion (MI/R) injury is intricately linked to mitochondrial dysfunction occurring during both the ischemic and reperfusion phases. Through single-cell transcriptome analysis, we identified a subpopulation of HEY1-high expressing cardiomyocytes (HEY1+ CMs) characterized by superior mitochondrial homeostasis. To leverage this, we isolated P5CS-type or ATP5B-type functional mitochondria from a ΔΨm-high subpopulation, which was obtained via membrane potential sorting following dual overexpression in HEY1+ CMs, and subsequently encapsulated them within HEY1+ CM-derived exosomes to achieve stable, targeted delivery. We designed a responsive microneedle patch based on local copper/iron ion dynamics to enable the stage-specific release of these mitochondria within the ischemic or reperfusion microenvironments. In a Bama minipig MI/R model, this system significantly ameliorated cardiac function, reduced infarct size, and attenuated cardiomyocyte death. Mechanistically, the therapeutic strategy enhanced mitochondrial structural integrity and energy metabolic function. This study establishes a responsive, stage-specific mitochondrial delivery platform, offering a promising strategy for the precision treatment of ischemic heart disease.

BACKGROUND:To develop and test a nomogram model based on drinking patterns and computed tomography and magnetic resonance imaging (CT/MRI) characteristics for recurrence of acute alcoholic pancreatitis (AAP) following its first onset. METHODS:Patients with initial AAP at the Affiliated Hospital of North Sichuan Medical College were retrospectively enrolled and categorized them into recurrence and non-recurrence groups. They were randomly assigned in a 7:3 ratio to form training and independent test sets, and their clinical and imaging data were collected and analyzed. Nomogram models were established to predict the recurrence of AAP. RESULTS:Among 152 cases of initial AAP, 37 cases were recurrent and 115 were non-recurrent, with a mean (SD) age of 43.84 ± 10.28 years and 91.45% male participants. In the training set, 26 cases were recurrent and 80 were non-recurrent; in the independent test set, 11 cases were recurrent and 35 were non-recurrent. Multivariable logistic regression analysis showed that hyperlipidemia, pre-onset alcohol consumption, alcohol cessation, the Bedside Index for Severity in AP (BISAP) score, extrapancreatic inflammation on CT/MRI (EPIC/EPIM) score, and CT/MRI severity index (CTSI/MRSI) score were independent predictors of recurrence after initial AAP onset. Integrating these factors into a nomogram prediction model resulted in the area under the curve (AUC), sensitivity, and specificity values of 0.924 (95% CI 0.871-0.977), 0.885, and 0.838 for the training set and 0.843 (95% CI 0.714-0.972), 0.727, and 0.857 for the independent test set. The clinical model alone and the imaging model achieved AUCs of 0.799 (95% CI 0.703-0.896) and 0.827 (95% CI 0.742-0.912) in the training set and 0.800 (95% CI 0.646-0.954) and 0.686 (95% CI 0.492-0.880) in the independent test set, respectively. CONCLUSIONS:Nomogram models based on drinking patterns and CT/MRI characteristics can more accurately predict AAP recurrence. The model serves as an effective tool for clinical prediction of AAP and helps clinicians in developing personalized prevention and treatment strategies.

Pancreatitis constitutes a serious global health challenge characterized by a multicellular pathogenesis and limited therapeutic options. The recent discovery of different cellular pathogenic mechanisms and the emerging effectiveness of nanotechnology-based, cell-targeted therapies have provided promising therapeutic avenues for pancreatitis. However, the identification of effective cellular targets, the elucidation of nanotherapeutic mechanisms, and the multicellular-coordinated modulation remain fragmented and insufficiently defined. Here, we summarize recent progress in understanding pathogenic mechanisms from the perspective of different cell populations and analyze relevant nanotechnology-based approaches designed to target these cells in detail. By bridging different cellular pathogenesis with advances in nanotherapeutic design, this review offers a clear framework for cell-targeted nanotherapeutics across the disease progression, proposing pathological and methodological insights to guide the future development of multicellular-coordinated nanomedicines for pancreatitis.

Myeloperoxidase (MPO)-mediated oxidative stress drives inflammatory tissue injury, yet converting this enzyme activity into a selective and sustained imaging readout remains chemically challenging. To address this limitation, we report Mn-TyrCDTA, a manganese chelate designed to couple kinetic inertness with MPO-triggered activation and retention mechanism. Replacement of a flexible EDTA backbone with a rigidified CDTA scaffold improved the kinetic inertness 3-fold under a Zn2+ challenge (dissociation t1/2 = 61.7 min). Incorporation of a tyramine-derived phenolic moiety enabled MPO/H2O2-mediated, one-electron oxidation and covalent protein anchoring, resulting in a 3.6-fold relaxivity enhancement and prolonged inflamed tissue retention. In rat models of acute pancreatitis, contrast enhancement correlated with tissue MPO activity (R2 = 0.83), enabling quantitative disease severity stratification. Complementary 68Ga-TyrCDTA PET studies demonstrated enzyme-dependent tracer accumulation, and MPO inhibition reduced the imaging signal by 85% (R2 = 0.98). These findings establish a rational design framework for the quantitative imaging of neutrophil-driven oxidative tissue injury.

Anomalous origin of the left coronary artery from the pulmonary artery is a rare congenital coronary anomaly. This case report describes an adult male with anomalous origin of the left coronary artery from the pulmonary artery, in whom transthoracic echocardiography revealed mitral valve prolapse without apparent anomalies of the coronary ostia. The definitive anatomical diagnosis was established using invasive coronary angiography and coronary computed tomography angiography. This case underscores the indispensable value of multimodality imaging in the diagnosis of anomalous origin of the left coronary artery from the pulmonary artery.

In acute pancreatitis (AP), disease activity is defined as the reversible manifestation of the disease. The aim of this study was to develop a nomogram for predicting disease activity in AP based on multiparametric magnetic resonance imaging (MRI) radiomics. This retrospective study included 310 patients with first-episode AP from two medical centers in China. Patients from the first medical center were randomly divided into a training cohort (n = 122) and an internal validation cohort (n = 123) in a 5:5 ratio. Patients from the second medical center were used as the external independent validation cohort (n = 65). Radiomics features were extracted from multiparametric MRI images based on pancreatic parenchymal regions. The least absolute shrinkage and selection operator (LASSO) was used for feature screening, logistic regression was used to establish radiomic feature, and statistically significant laboratory parameters were incorporated to construct the nomogram. The area under the receiver operator characteristic curve assessed the predictive performance of the nomogram. Furthermore, decision curve analysis (DCA) was used to assess the clinical utility of the nomogram, and the disease activity was validated against follow-up clinical outcomes (e.g., organ failure progression, ICU admission) and imaging-confirmed changes within one-week after MRI. The AUCs of the radiomic signature were 0.808 (training cohort), 0.789 (internal validation cohort), and 0.783 (external validation cohort). Radiomic signature, extrapancreatic inflammation on MRI (EPIM) scores, and WBC count were identified as independent risk factors for the activity of AP and were therefore included in the nomogram. The AUC of the nomogram were 0.881 (training cohort), 0.922 (internal validation cohort) and 0.912 (external validation cohort). Additionally, the nomogram model obtained the greatest net benefit, according to the results of decision curves Based on the follow-up results, we also found that AP patients with higher disease activity were more likely to experience exacerbations. This nomogram can accurately predict the activity of AP patients, thus providing objective monitoring of the patient’s course and potentially improving patient prognosis.

Radiolabeled superparamagnetic iron oxide nanoparticles (SPIONs) have gained significant attention for their potential in dual-modality imaging, combining positron emission tomography (PET) and magnetic resonance imaging (MRI). The integration provides clinicians with enhanced and complementary imaging information, improving the accuracy of disease diagnosis. However, the complexity of ligand synthesis for functionalization and stable radiolabeling and the difficulty in achieving controlled large-scale production with consistent nano- particle quality, both of which limit their potential in clinical applications. To overcome these limitations, we report a novel method for preparing SPIONs utilized a simple dual-chelation functional ligand and a continuous synthesis approach to facilitate their clinical translation. The functionalized SPIONs were successfully synthesized by using a flow synthesis technique and the dual-chelation functional ligand (PAsp-g-DA/EA). Compared with traditional synthesis methods, this approach enabled mass production with high reproducibility. The obtained SPIONs showed ultra-small sizes (5.1 +/- 0.1 nm), good monodispersity, excellent relaxivity, and superior biocompatibility. The dual-chelation functional ligand enabled direct and efficient radiolabeling of SPIONs with [64Cu]Cu2+ achieving over 80 % efficiency and outstanding labeling stability. After intravenous injection into rats, high-quality PET and MRI images were obtained. Furthermore, both PET and MRI demonstrated significant nanoprobe accumulation in tumor-bearing mice. In this study, a dual-chelation functional ligand was employed to facilitate the batch and reproducible synthesis of directly radiolabelable SPIONs, thereby addressing key challenges associated with the clinical translation of PET/MRI dual-modality nanoprobes. The nano-probes developed demonstrate excellent biocompatibility, superior imaging efficacy in both PET and MRI, making them potential candidates for medical PET/MRI dual-modality probes.

In recent years, the incidence of acute pancreatitis (AP) in the older people has been increasing. Some reports indicate that AP in the older people, is clinically more severe and systemic complications more frequent, leading to higher mortality compared to younger individuals. The clinical and CT/MRI features of senile AP are insufficient and the results are inconsistent. The purpose of this study was to investigate the clinical features, CT/MRI imaging characteristics, and prognosis of AP in older people based on age stratification. We collected clinical and imaging (CT/MRI) data from 449 older people with AP and categorized them into three age groups: aged 65 74 (young old, group 1), 75 84 (middle old, group 2), and ≥ 85 years (oldest old, group 3). Their clinical presentation, imaging characteristics, and clinical outcome endpoints were identified and compared. The average age was 73 (69,78) years, with 259 (57.7

OBJECTIVE:This study aimed to compare computed tomography (CT)/magnetic resonance imaging (MRI) characteristics of acute pancreatitis (AP) between patients with cholecystectomy and non-cholecystectomy and to validate the effect of prior cholecystectomy on the severity of subsequent pancreatitis. METHODS:This retrospective study included 384 inpatients with AP at our hospital from January 1, 2020 to December 31, 2023. Based on their history of cholecystectomy, the patients were split into cholecystectomy and non-cholecystectomy groups. propensity score matching was applied, considering age and sex, in a 1:3 ratio. Demographic, clinical, laboratory, and CT/MRI parameters of each group were analyzed. RESULTS:There were 200 (52.1%) males and 184 (47.9%) females, with a mean age of 53.55 ± 13.86 years (range: 18-98 y). Ninety-six patients were in the cholecystectomy group that had previously undergone cholecystectomy, and 288 in the non-cholecystectomy group. Creatinine and C-reactive protein levels were lower in the patients with cholecystectomy than in patients with non-cholecystectomy ( P 1 = 0.001, P 2 = 0.049). In the prevalence of biliary pancreatitis, the cholecystectomy patients are 27.1%, whereas the non-cholecystectomy patients are 45.8% ( P = 0.005). The non-cholecystectomy patients had a significantly higher mean CT/MRI severity index score (3.57 ± 1.72 points) than the cholecystectomy group (3.00 ± 1.58 points; P < 0.001). Regarding local complications, In the groups that underwent cholecystectomy and those that did not, the prevalence of acute peripancreatic fluid collection was 40.4% and 21.9%, respectively. ( P < 0.001). CONCLUSIONS:AP following cholecystectomy exhibits unique imaging characteristics. Cholecystectomy reduces the severity and acute peripancreatic fluid collection rate of subsequent pancreatitis on CT/MRI.

Previous studies have confirmed that alcohol can increase the sensitivity of the pancreas to stressors and exacerbate the severity of pancreatitis when excessive alcohol intake is combined with other causes. In the current work, this study attempted to explore how does alcohol regulate cerulein-induced acute pancreatitis, especially before inflammation occurs. Proteomics was performed to analyze the differentially expressed proteins in pancreatic tissues from a rat model of pancreatitis. The metabolite levels in the pancreatic tissue, serum of rats and serum of persons with a history of alcohol consumption were detected by LC‒MS/MS. In the present study the impact of etomoxir (a carnitine palmitoyl-transferase 1A-specific inhibitor) treatment on AR42J cells treated with alcohol and the effect of etomoxir injection on the inflammatory response in an alcohol + cerulein-induced AAP rat model was evaluated. When treated with the same amount of cerulein, the rats that ingested alcohol presented with more severe pancreatitis. The proteomics results revealed that the fatty acid degradation pathway was closely related to the development of alcoholic acute pancreatitis, and CPT1A exhibited the greatest increase (approximately twofold increase). The products (acylcarnitines) of CPT1A were changed in the serum of persons with a history of alcohol consumption. Etomoxir treatment mitigates the influence of alcohol stimulation on the aberrant expression of proteins associated with oxidative stress, increased ROS production, mitochondrial ultrastructural alterations and mitochondrial dysfunction in AR42J cells. Etomoxir injection reduced the inflammatory response in the AAP rat model. Alcohol upregulates CPT1A protein expression in pancreatic tissue, resulting in abnormal lipid metabolism. The products of lipid metabolism, ROS, contribute to mitochondrial ultrastructural alterations and mitochondrial dysfunction. These changes act as sentinel events that regulate acute pancreatitis.

Acute pancreatitis (AP) is a rapidly progressing and life-threatening inflammatory disease. Traditional medications have limitations such as a short half-life, low bioavailability, monofunctionality, and notable side effects, making it difficult to inhibit the progression of AP. We developed a biomimetic nanomedicine (MDU@Mn) that is responsive to and targets the pancreatic inflammatory microenvironment; the medicine consists of polydopamine nanoparticles coloaded with ulinastatin (U) and manganese ions and encapsulated with macrophage membranes. MDU@Mn evades immune system clearance, promotes nanoparticle enrichment at sites of inflammation, and exhibits improved bioavailability and a relatively long half-life. In addition, it specifically releases U and manganese ions in regions of the pancreas with low pH and high Reactive Oxygen Species (ROS) levels for image-guided therapy with fewer side effects. In vitro and in vivo studies demonstrated that MDU@Mn has excellent therapeutic and magnetic resonance imaging capabilities and can significantly reduce the levels of relevant indicators of inflammation in the pancreatic microenvironment (ROS, inflammatory cells, enzymes, etc.), preventing further expansion of inflammation. This study provides a new strategy for constructing a responsive multifunctional diagnostic and therapeutic platform for inflammatory microenvironments.

Background:Patients with acute pancreatitis (AP) have different sites of pancreatic involvement. The aim of this study was to investigate the differences in magnetic resonance imaging (MRI) findings and clinical features of different sites of involvement (subtypes) in AP, with a view to complement and complete the classification of AP based on anatomical imaging features. Methods:We consecutively collected data from inpatients with AP from January 2018 to October 2022 at a tertiary care hospital. The patients with AP were classified into three subtypes by MRI: type I mainly involved the head of the pancreas; type II mainly involved the body and tail of the pancreas; and type III involved the entire pancreas (head, body, and tail simultaneously). We examined the MRI findings and clinical features of the three subtypes, including their prevalence, gender, etiology, age, assessment of severity, prevalence of hypertension, diabetes mellitus, coronary artery disease, laboratory markers, prognosis, necrosis, and the incidence of complications. The three subgroups were analyzed using one-way analysis of variance (ANOVA), Kruskal-Wallis H-test, Chi-squared test or Fisher's exact probability method depending on the data distribution, and logistic regression and linear regression were used to determine the risk factors for poor short-term prognosis of AP and the number of days in hospital. Results were considered statistically significant at P<0.05. Results:Among the 240 patients recruited, the mean age was 51±15 years (range, 12-89 years); 146 (60.83%) were male and 94 (39.17%) were female. Biliary pancreatitis accounted for 45.00% (108/240), hyperlipidemic pancreatitis for 33.75% (81/240), alcoholic pancreatitis for 8.75% (21/240), and unknown etiology for 12.5% (30/240). Some 81.25% (195/240) of the cases were edematous pancreatitis, whereas 18.75% (45/240) were necrotizing pancreatitis. Overall, 75 patients (31.25%) had type I AP, 108 patients (45.00%) had type II AP, and 57 patients (23.75%) had type III AP. These three subtypes were significantly different in terms of etiology, incidence of diabetes, C-reactive protein (CRP), severity, incidence of necrosis, local complications, clinical and imaging severity scores, and prognosis (P<0.05). Total pancreatic involvement (Type III) was the most severe subtype, with hyperlipidemia as the main cause. Regression analysis revealed that subtype classification is an important risk factor for prognosis. Conclusions:We classified AP into three subtypes based on different sites of involvement and revealed the MRI features and clinical characteristics of each subtype of AP. The subtype classification helps to characterize AP from the imaging dimension and predict the prognosis. The results of this study could be a target for future studies to adopt new classification methods.

ObjectiveTo develop a model that integrates radiomics features and clinical factors to predict upper gastrointestinal bleeding (UGIB) in patients with decompensated cirrhosis.Methods104 decompensated cirrhosis patients with UGIB and 104 decompensated cirrhosis patients without UGIB were randomized according to a 7:3 ratio into a training cohort (n = 145) and a validation cohort (n = 63). Radiomics features of the abdominal skeletal muscle area (SMA) were extracted from the cross-sectional image at the largest level of the third lumbar vertebrae (L3) on the abdominal unenhanced multi-detector computer tomography (MDCT) images. Clinical-radiomics nomogram were constructed by combining a radiomics signature (Rad score) with clinical independent risk factors associated with UGIB. Nomogram performance was evaluated in calibration, discrimination, and clinical utility.ResultsThe radiomics signature was built using 11 features. Plasma prothrombin time (PT), sarcopenia, and Rad score were independent predictors of the risk of UGIB in patients with decompensated cirrhosis. The clinical-radiomics nomogram performed well in both the training cohort (AUC, 0.902; 95% CI, 0.850–0.954) and the validation cohort (AUC, 0.858; 95% CI, 0.762–0.953) compared with the clinical factor model and the radiomics model and displayed excellent calibration in the training cohort. Decision curve analysis (DCA) demonstrated that the predictive efficacy of the clinical-radiomics nomogram model was superior to that of the clinical and radiomics model.ConclusionClinical-radiomics nomogram that combines clinical factors and radiomics features has demonstrated favorable predictive effects in predicting the occurrence of UGIB in patients with decompensated cirrhosis. This helps in early diagnosis and treatment of the disease, warranting further exploration and research.

Objectives To predict liver injury in acute pancreatitis (AP) patients by establishing a radiomics model based on contrast-enhanced computed tomography (CECT). Methods A total of 1223 radiomic features were extracted from late arterial-phase pancreatic CECT images of 209 AP patients (146 in the training cohort and 63 in the test cohort), and the optimal radiomic features retained after dimensionality reduction by least absolute shrinkage and selection operator (LASSO) were used to construct a radiomic model through logistic regression analysis. In addition, clinical features were collected to develop a clinical model, and a joint model was established by combining the best radiomic features and clinical features to evaluate the practicality and application value of the radiomic models, clinical model and combined model. Results Four potential features were selected from the pancreatic parenchyma to construct the radiomic model, and the area under the receiver operating characteristic curve (AUC) of the radiomic model was significantly greater than that of the clinical model for both the training cohort (0.993 vs. 0.653, p = 0.000) and test cohort (0.910 vs. 0.574, p = 0.000). The joint model had a greater AUC than the radiomics model for both the training cohort (0.997 vs. 0.993, p = 0.357) and test cohort (0.925 vs. 0.910, p = 0.302). Conclusions The radiomic model based on CECT has good performance in predicting liver injury in AP patients and can guide clinical decision-making and improve the prognosis of patients with AP.

PURPOSE:This study aimed to evaluate the Pharmacovigilance (PV) and severity of hypersensitivity reactions induced by non-ionic Iodinated Contrast Media (ICM) in the radiology diagnosis reported to the United States Food and Drug Administration Adverse Event Reporting System (FAERS). METHODS:We retrospectively reviewed the reports of ICM-induced hypersensitivity reactions submitted to the FAERS database between January 2015 and January 2023 and conducted a disproportionality analysis. The seven most common non-ionic ICM, including iohexol, iopamidol, ioversol, iopromide, iomeprol, iobitridol, and iodixanol, were chiefly analyzed. Our primary endpoint was the PV of non-ionic ICM-induced total hypersensitivity events. STATA 17.0 MP was used for statistical analysis. RESULTS:In total, 35357 reports of adverse reaction events in radiology diagnosis were retrieved from the FAERS database. Among them, 6181 reports were on hypersensitivity reaction events (mean age: 57.1 ± 17.8 years). The hypersensitivity reaction-related PV signal was detected for iohexol, ioversol, iopromide, iomeprol, iobitridol, and iodixanol, but not for iopamidol. The proportion of iomeprol-induced hypersensitivity reactions and the probability of ioversol-induced severe hypersensitivity reactions have been found to be significantly increased. CONCLUSION:The probability and severity of hypersensitivity reaction events in non-ionic ICM are different. Iohexol, ioversol, iopromide, iomeprol, iobitridol, and iodixanol have higher risks compared to iopamidol. In addition, the constituent ratio of hypersensitivity reactions induced by iomeprol is significantly increased, and the associated probability induced by ioversol is significantly increased.

Abstract Background The modified pancreatitis activity scoring system (mPASS) was proposed to assess the activity of acute pancreatitis (AP) while it doesn’t include indicators that directly reflect pathophysiology processes and imaging characteristics. Objectives To determine the threshold of admission mPASS and investigate radiomics and laboratory parameters to construct a model to predict the activity of AP. Methods AP inpatients at institution 1 were randomly divided into training and validation groups based on a 5:5 ratio. AP inpatients at Institution 2 were served as test group. The cutoff value of admission mPASS scores in predicting severe AP was selected to divide patients into high and low level of disease activity group. LASSO was used in screening features. Multivariable logistic regression was used to develop radiomics model. Meaningful laboratory parameters were used to construct combined model. Results There were 234 (48 years ± 10, 155 men) and 101 (48 years ± 11, 69 men) patients in two institutions. The threshold of admission mPASS score was 112.5 in severe AP prediction. The AUC of the radiomics model was 0.79, 0.72, and 0.76 and that of the combined model incorporating rad-score and white blood cell were 0.84, 0.77, and 0.80 in three groups for activity prediction. The AUC of the combined model in predicting disease without remission was 0.74. Conclusions The threshold of admission mPASS was 112.5 in predicting severe AP. The model based on CECT radiomics has the ability to predict AP activity. Its ability to predict disease without remission is comparable to mPASS. Critical relevance statement This work is the first attempt to assess the activity of acute pancreatitis using contrast-enhanced CT radiomics and laboratory parameters. The model provides a new method to predict the activity and prognosis of AP, which could contribute to further management. Key Points Radiomics features and laboratory parameters are associated with the activity of acute pancreatitis. The combined model provides a new method to predict the activity and prognosis of AP. The ability of the combined model is comparable to the modified Pancreatitis Activity Scoring System. Graphical Abstract