Quantitative MRI of Pancreatic Cystic Lesions: A New Diagnostic Approach.

Bibliographic Details
Title: Quantitative MRI of Pancreatic Cystic Lesions: A New Diagnostic Approach.
Authors: Ștefan, Paul Andrei, Lupean, Roxana Adelina, Lebovici, Andrei, Csutak, Csaba, Crivii, Carmen Bianca, Opincariu, Iulian, Caraiani, Cosmin
Source: Healthcare (2227-9032); Jun2022, Vol. 10 Issue 6, p1039-1039, 17p
Subject Terms: DIFFUSION magnetic resonance imaging, MAGNETIC resonance imaging, FEATURE extraction, RADIOMICS, MAGNETIC resonance, DIFFUSION coefficients
Abstract: The commonly used magnetic resonance (MRI) criteria can be insufficient for discriminating mucinous from non-mucinous pancreatic cystic lesions (PCLs). The histological differences between PCLs' fluid composition may be reflected in MRI images, but cannot be assessed by visual evaluation alone. We investigate whether additional MRI quantitative parameters such as signal intensity measurements (SIMs) and radiomics texture analysis (TA) can aid the differentiation between mucinous and non-mucinous PCLs. Fifty-nine PCLs (mucinous, n = 24; non-mucinous, n = 35) are retrospectively included. The SIMs were performed by two radiologists on T2 and diffusion-weighted images (T2WI and DWI) and apparent diffusion coefficient (ADC) maps. A total of 550 radiomic features were extracted from the T2WI and ADC maps of every lesion. The SIMs and TA features were compared between entities using univariate, receiver-operating, and multivariate analysis. The SIM analysis showed no statistically significant differences between the two groups (p = 0.69, 0.21–0.43, and 0.98 for T2, DWI, and ADC, respectively). Mucinous and non-mucinous PLCs were successfully discriminated by both T2-based (83.2–100% sensitivity and 69.3–96.2% specificity) and ADC-based (40–85% sensitivity and 60–96.67% specificity) radiomic features. SIMs cannot reliably discriminate between PCLs. Radiomics have the potential to augment the common MRI diagnosis of PLCs by providing quantitative and reproducible imaging features, but validation is required by further studies. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
More Details
ISSN:22279032
DOI:10.3390/healthcare10061039
Published in:Healthcare (2227-9032)
Language:English