Purpose: To evaluate the use of volumetric multiparametric MRI in differentiating pancreatic intraductal papillary mucinous neoplasms (IPMNs) from serous cystadenomas (SCAs) METHODS: Included patients (123 patients with pancreatic cystic neoplasms (PCNs) measuring ≥ 10 mm) were stratified into two groups based on cyst type. Axial cyst size, region of interest (ROI)-based apparent diffusion coefficient (ADC) and volumetric data, including cyst volume, volumetric apparent diffusion coefficient (vADC), and volumetric venous enhancement (vVE) were extracted and compared between the two groups. Univariate and multiple logistic regression was used to develop models for distinguishing between IPMNs and SCAs.
Results: Volume and size of the cysts, vVE and vADC and ROI-ADC were significantly different between the two groups. Cyst volume was significantly larger in SCAs (median = 14.1cm, IQR 3.5-42.5) than in IPMNs (median = 2.5 cm, IQR 1.1-6) (p < 0.001). IPMNs had a higher volumetric ADC value in comparison to SCAs (2925 ± 294 × 10 mm/s vs 2521 ± 202 × 10 mm/s, p < 0.001). However, IPMNs had lower vVE values compared to SCAs (37 signal intensity (SI) vs 86 SI, p < 0.001). Area under the ROC Curve (AUC) of the model that included vADC and cyst volume had 95% accuracy in distinguishing between the two groups. In comparison, the AUC of the model that included ROI-ADC and axial cyst size had 84% accuracy in distinguishing between the two groups. A threshold of 2615 × 10 mm/s for volumetric ADC resulted in the identification of IPMNs from SCAs with sensitivity and specificity of 90.8% and 73.5%, respectively.
Conclusion: IPMNs had smaller cyst volume, higher volumetric ADC and lower volumetric VE values compared to SCAs. Volumetric multiparametric MRI could be useful in differentiating between the IPMN and SCA groups.
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http://dx.doi.org/10.1007/s00261-020-02792-0 | DOI Listing |
Quant Imaging Med Surg
December 2024
Chongqing Medical University, Chongqing, China.
Background: The value of Liver Imaging Reporting and Data System (LI-RADS) radiological features and tumor three-dimensional volumetric quantification in preoperative magnetic resonance imaging (MRI) for predicting the vessels encapsulating tumor clusters (VETC) pattern of solitary hepatocellular carcinoma (HCC) is unknown. This study aimed to assess the value of these indicators for predicting the VETC pattern of solitary HCC.
Methods: In total, 36 patients with HCC were selected from a cohort containing 126 patients for further data evaluation.
Photoacoustics
December 2024
Department of Convergence IT Engineering, Electrical Engineering, Mechanical Engineering, Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea.
Topical corticosteroids manage inflammatory skin conditions via their action on the immune system. An effect of application of corticosteroids to the skin is skin blanching caused by peripheral vasoconstriction. This has been used to characterize, in some cases relative potency and also as a way to compare skin penetration.
View Article and Find Full Text PDFJ Gastrointest Surg
February 2025
Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD, United States; Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, United States. Electronic address:
Purpose: This study aimed to determine the value of radiomics features derived from baseline computed tomography (CT) scans and volumetric measurements to predict overall survival (OS) in patients with nonsurgical pancreatic ductal adenocarcinoma (PDAC) treated with a chemotherapy combination regimen of 5-fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX).
Methods: In this retrospective single-institution study, 131 patients with nonsurgical PDAC who received FOLFIRINOX neoadjuvant chemotherapy between December 2012 and November 2021 were included. Pretreatment contrast-enhanced CT images were obtained for all patients before inclusion.
Proc SPIE Int Soc Opt Eng
February 2024
Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, United States.
Precise deformable image registration of multi-parametric MRI sequences is necessary for radiologists in order to identify abnormalities and diagnose diseases, such as prostate cancer and lymphoma. Despite recent advances in unsupervised learning-based registration, volumetric medical image registration that requires considering the variety of data distributions is still challenging. To address the problem of multi-parametric MRI sequence data registration, we propose an unsupervised domain-transported registration method, called OTMorph by employing neural optimal transport that learns an optimal transport plan to map different data distributions.
View Article and Find Full Text PDFAbdom Radiol (NY)
September 2024
Dokuz Eylül University, Izmir, Turkey.
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