Objectives: Computed tomography (CT) is the most commonly used imaging modality when diagnosing chronic pancreatitis (CP). We aimed to evaluate the diagnostic accuracy of CT scores for diagnosing CP.
Methods: One hundred eighteen patients were retrospectively included from an observational cohort study that comprised patients referred because of suspected CP. Patients were categorized as CP or non-CP using a modified Mayo score based on biochemistry, clinical presentation, and findings on endoscopic ultrasound and/or transabdominal ultrasound. The CT scans were scored according to the modified Cambridge classification and the unweighted CT score. Diagnostic performance indices were calculated using the modified Mayo score as reference standard.
Results: Seventy-six of the 118 patients fulfilled the CP diagnostic criteria (Mayo score ≥4). The modified Cambridge classification and the unweighted CT score yielded sensitivities of 63% and 67% and specificities of 91% and 91%, respectively, and similar areas under the receiver operating characteristic curves (95% confidence interval) of 0.79 (0.71-0.88)/0.81 (0.73-0.89), respectively (P, not significant).
Conclusions: Both CT scores had similar, moderate accuracies for diagnosing CP. The limitation in diagnostic accuracy makes CT ineligible as a single method to diagnose CP, supporting that the diagnostic process for CP needs to incorporate other imaging methods and/or markers for better diagnostics.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1097/MPA.0000000000001803 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Cytomorphological diagnosis of sarcoidosis using EBUS-TBNA in a tuberculosis-endemic region.
Rev Esp Patol
January 2025
Department of Pathology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.
Background: Sarcoidosis, a granulomatous inflammatory disease, exhibits diverse clinical manifestations, often affecting multiple organs. Diagnostic challenges arise due to its similarities with tuberculosis, particularly in high-burden areas. Differentiating between the two relies on clinical judgment, laboratory tests, imaging, and invasive procedures.
View Article and Find Full Text PDFLarge Language Model Approach for Zero-Shot Information Extraction and Clustering of Japanese Radiology Reports: Algorithm Development and Validation.
JMIR Cancer
January 2025
Division of Radiology and Biomedical Engineering, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Background: The application of natural language processing in medicine has increased significantly, including tasks such as information extraction and classification. Natural language processing plays a crucial role in structuring free-form radiology reports, facilitating the interpretation of textual content, and enhancing data utility through clustering techniques. Clustering allows for the identification of similar lesions and disease patterns across a broad dataset, making it useful for aggregating information and discovering new insights in medical imaging.
View Article and Find Full Text PDFAccuracy of ChatGPT 3.5, 4.0, 4o and Gemini in diagnosing oral potentially malignant lesions based on clinical case reports and image recognition.
Med Oral Patol Oral Cir Bucal
January 2025
15, Trauma Centre, District Hospital Neemuch Madhya Pradesh - 458441, India
Background: The accurate and timely diagnosis of oral potentially malignant lesions (OPMLs) is crucial for effective management and prevention of oral cancer. Recent advancements in artificial intelligence technologies indicates its potential to assist in clinical decision-making. Hence, this study was carried out with the aim to evaluate and compare the diagnostic accuracy of ChatGPT 3.
View Article and Find Full Text PDFDiagnosis of lung cancer using salivary miRNAs expression and clinical characteristics.
BMC Pulm Med
January 2025
Universal Scientific Education and Research Network (USERN), Tehran, Iran.
Objective: Lung cancer (LC), the primary cause for cancer-related death globally is a diverse illness with various characteristics. Saliva is a readily available biofluid and a rich source of miRNA. It can be collected non-invasively as well as transported and stored easily.
View Article and Find Full Text PDFAge group classification based on optical measurement of brain pulsation using machine learning.
Sci Rep
January 2025
Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!