MR Imaging for Early Extrapancreatic Necrosis in Acute Pancreatitis

Acute pancreatitis: A review of diagnosis, severity prediction and prognosis assessment from imaging technology, scoring system and artificial intelligence

Acute pancreatitis (AP) is a potentially life-threatening inflammatory disease of the pancreas, with clinical management determined by the severity of the disease. Diagnosis, severity prediction, and prognosis assessment of AP typically involve the use of imaging technologies, such as computed tomography, magnetic resonance imaging, and ultrasound, and scoring systems, including Ranson, Acute Physiology and Chronic Health Evaluation II, and Bedside Index for Severity in AP scores. Computed tomography is considered the gold standard imaging modality for AP due to its high sensitivity and specificity, while magnetic resonance imaging and ultrasound can provide additional information on biliary obstruction and vascular complications. Scoring systems utilize clinical and laboratory parameters to classify AP patients into mild, moderate, or severe categories, guiding treatment decisions, such as intensive care unit admission, early enteral feeding, and antibiotic use. Despite the central role of imaging technologies and scoring systems in AP management, these methods have limitations in terms of accuracy, reproducibility, practicality and economics. Recent advancements of artificial intelligence (AI) provide new opportunities to enhance their performance by analyzing vast amounts of clinical and imaging data. AI algorithms can analyze large amounts of clinical and imaging data, identify scoring system patterns, and predict the clinical course of disease. AI-based models have shown promising results in predicting the severity and mortality of AP, but further validation and standardization are required before widespread clinical application. In addition, understanding the correlation between these three technologies will aid in developing new methods that can accurately, sensitively, and specifically be used in the diagnosis, severity prediction, and prognosis assessment of AP through complementary advantages.

Radiomics analysis of contrast-enhanced T1W MRI: predicting the recurrence of acute pancreatitis

To investigate the predictive value of radiomics based on T1-weighted contrast-enhanced MRI (CE-MRI) in forecasting the recurrence of acute pancreatitis (AP). A total of 201 patients with first-episode of acute pancreatitis were enrolled retrospectively (140 in the training cohort and 61 in the testing cohort), with 69 and 30 patients who experienced recurrence in each cohort, respectively. Quantitative image feature extraction was obtained from MR contrast-enhanced late arterial-phase images. The optimal radiomics features retained after dimensionality reduction were used to construct the radiomics model through logistic regression analysis, and the clinical characteristics were collected to construct the clinical model. The nomogram model was established by linearly integrating the clinically independent risk factor with the optimal radiomics signature. The five best radiomics features were determined by dimensionality reduction. The radiomics model had a higher area under the receiver operating characteristic curve (AUC) than the clinical model for estimating the recurrence of acute pancreatitis for both the training cohort (0.915 vs. 0.811, p = 0.020) and testing cohort (0.917 vs. 0.681, p = 0.002). The nomogram model showed good performance, with an AUC of 0.943 in the training cohort and 0.906 in the testing cohort. The radiomics model based on CE-MRI showed good performance for optimizing the individualized prediction of recurrent acute pancreatitis, which provides a reference for the prevention and treatment of recurrent pancreatitis.

Ranson score to stratify severity in Acute Pancreatitis remains valid - Old is gold

Introduction: Acute pancreatitis (AP) is a common gastrointestinal disease with a wide spectrum of severity and morbidity. Developed in 1974, the Ranson score was the first scoring system to prognosticate AP. Over the past decades, while the Ranson score remains widely used, it was identified to have certain limitations, such as having low predictive power. It has also been criticized for its 48-hour requirement for computation of the final score, which has been argued to potentially delay management. With advancements in our understanding of AP, is the Ranson score still relevant as an effective prognostication system for AP?Areas covered: This review summarizes the available evidence comparing Ranson score with other conventional and novel scoring systems, in terms of prognostic accuracy, benefits, limitations and clinical applicability. It also evaluates the effectiveness of Ranson score with regard to the Revised Atlanta Classification.Expert opinion: The Ranson score consistently exhibits comparable prognostic accuracy to other newer scoring systems, and the 48-hour timeframe for computing the full Ranson score is an inherent strength, not a weakness. These aspects, coupled with relative ease of use, practicality and universality of the score, advocate for the continued relevance of the Ranson score in modern clinical practice.