Comparison of magnetic resonance imaging and computed tomography in the diagnosis of acute pancreatitis: a systematic review and meta-analysis of diagnostic test accuracy studies

Sun, Hui; Jian, Sha; Peng, Bo; Hou, Jiancheng

doi:10.21037/atm-22-812

Cited by 6 publications

(5 citation statements)

References 21 publications

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“…The findings are consistent with the study by Irshad et al, 22 and Banday et al, also suggested mCTSI to be a simple and accurate scoring tool as compared to Balthazr CT severity index and mCTSI to have a significant correlation with clinical outcomes in terms of duration of hospitalization, development of complications, and overall mortality. 6 However a systematic and meta-analysis of diagnostic accuracy studies have concluded magnetic resonance imaging (MRI) to be more specific, sensitive and accurate as compared to CT. 23 MRI has higher recognition ability for diagnosis of pancreatic injury in terms of peripancreatic effusion, pancreatic contour, and vascular proliferation at site of lesion. 24,25 Despite advances in diagnosis and management, CRP and mCTSI scores have their predictive value in risk stratification and aid in management.…”

Section: Discussionmentioning

confidence: 99%

C-reactive protein and modified computed tomography severity index in assessing severity of acute pancreatitis

Lahan¹,

Sonowal²,

Teli³

et al. 2023

Asian J Med Sci

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Background: The mortality and morbidity associated with acute pancreatitis (AP) demands timely management and prediction of disease progression and clinical outcome. Multifactorial scoring systems shall facilitate risk stratification and prognostic assessment in AP. Aims and Objectives: The aim of the study was (i) to assess C-reactive protein (CRP) levels and modified computed tomography severity index (mCTSI) in AP patients and their association with the clinical outcome and (ii) to determine the correlation between CRP levels and mCTSI scores in AP. Materials and Methods: This cross-sectional, hospital-based study comprised 90 patients diagnosed with AP. Data collection included sociodemographic information, clinical presentation, and CRP estimation. The mCTSI score was estimated by axial slices contrast-enhanced computed tomography of abdomen and was used to assess the severity of AP. Categorical data were analyzed by Chi-square test and Pearson’s coefficient was estimated to determine the correlation between CRP levels and mCTSI score. P<0.05 was adopted as level of significance. Results: The study comprised 81 males (90%) and 9 females (10%). The mean age of the patients was 36.94±9.19 years, with majority in age group of 31–40 years (40%). Alcohol consumption (>50 g/day) was the commonest risk factor in 82.22% (n=74) patients, followed by hypertriglyceridemia in 13.33% (n=12) patients. Pain in abdomen was the most common presentation in 96.67% (n=87) patients, followed by vomiting 57.78% (n=52) patients. Majority of patients [82.22% (n=74)] had CRP levels of 10–21 mg/dL. Mild, moderate, and severe mCTSI scores were obtained in 17.78%, 66.67%, and 15.55% patients, respectively. There is a significant positive correlation between CRP values and mCTSI scores with r=0.3008 (P=0.003). Conclusion: CRP level had significant positive correlation with mCTSI scores in AP. Higher values of CRP and severe mCTSI scores had worse clinical outcome in AP.

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Section: Discussionmentioning

confidence: 99%

C-reactive protein and modified computed tomography severity index in assessing severity of acute pancreatitis

Lahan¹,

Sonowal²,

Teli³

et al. 2023

Asian J Med Sci

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“…Our previous research has also confirmed this point demonstrating the EPIM score to be more helpful in evaluating the severity of AP than either the MRSI and MMRSI in the early stage of AP ( 7 , 20 ). Another possible reason may be that MRI is more sensitive than CT in detecting slight changes of mild inflammation and effusion ( 28 , 29 ).…”

Section: Discussionmentioning

confidence: 99%

A new logistic regression model for early prediction of severity of acute pancreatitis using magnetic resonance imaging and Acute Physiology and Chronic Health Evaluation II scoring systems

Tang¹,

Zhou²,

Ma³

et al. 2022

Quant Imaging Med Surg

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Background: The aim of this study was to develop a new model constructed by logistic regression for the early prediction of the severity of acute pancreatitis (AP) using magnetic resonance imaging (MRI) and the Acute Physiology and Chronic Health Evaluation II (APACHE II) scoring system.Methods: This retrospective study included 363 patients with AP. The severity of AP was evaluated by MRI and the APACHE II scoring system, and some subgroups of AP severity were constructed based on a combination of these two scoring systems. The length of stay and occurrence of organ dysfunction were used as clinical outcome indicators and were compared across the different subgroups. We combined the MRI and APACHE II scoring system to construct the regression equations and evaluated the diagnostic efficacy of these models.Results: In the 363 patients, 144 (39.67%) had systemic inflammatory response syndrome (SIRS), 58 (15.98%) had organ failure, and 17 (4.68%) had severe AP. The AP subgroup with a high MRI score and a simultaneously high APACHE II score was more likely to develop SIRS and had a longer hospitalization.The model, which predicted the severity AP by combining extrapancreatic inflammation on magnetic resonance (EPIM) and APACHE II, was successful, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.912, which was higher than that of any single parameter. Other models that predicted SIRS complications by combining MRI parameters and APACHE II scores were also successful (all P<0.05), and these models based on EPIM and APACHE II scores were superior to other models in predicting outcome. Conclusions:The combination of MRI and clinical scoring systems to assess the severity of AP is feasible, and these models may help to develop personalized treatment and management.

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Section: Imaging Technologymentioning

confidence: 99%

“…In a meta-analysis encompassing a total of 566 patients, MRI demonstrated superior accuracy and sensitivity compared to CT for diagnosing AP[ 89 ]. While no study has yet shown that MRI can decrease AP mortality or enhance prognosis, MRI serves as an invaluable diagnostic tool for distinguishing individuals with suspected AP and is regarded as the premier imaging choice for the clinical diagnosis of AP[ 89 ]. Tang et al [ 82 ], utilizing MRI and APACHE II, devised a novel model through logistic regression for the early prediction of AP severity and ascertained that the combined model of extrapancreatic inflammation on MRI (EPIM) and APACHE II excelled in predicting AP severity, surpassing individual parameters.…”

Section: Imaging Technologymentioning

confidence: 99%

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

Hu,

Zhao,

Wang

et al. 2023

World J Gastroenterol

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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.

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Comparison of magnetic resonance imaging and computed tomography in the diagnosis of acute pancreatitis: a systematic review and meta-analysis of diagnostic test accuracy studies

Cited by 6 publications

References 21 publications

C-reactive protein and modified computed tomography severity index in assessing severity of acute pancreatitis

C-reactive protein and modified computed tomography severity index in assessing severity of acute pancreatitis

A new logistic regression model for early prediction of severity of acute pancreatitis using magnetic resonance imaging and Acute Physiology and Chronic Health Evaluation II scoring systems

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

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