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Utility of magnetic resonance imaging in pancreatic ductal adenocarcinoma evaluation

任 海楠 東北大学

2022.03.25

概要

Background: The prognosis of pancreatic ductal adenocarcinoma (PDAC) is extremely poor because most patients are diagnosed at advanced stages and unresectable. PDAC sometimes shares similar radiological features with mass-forming autoimmune pancreatitis (AIP). Magnetic resonance imaging (MRI) plays an important role in the diagnosis of PDAC for its superior soft-tissue contrast. The most used non-contrast pancreatic MRI sequences include T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) with quantitative apparent diffusion coefficient (ADC) map, and magnetic resonance cholangiopancreatography (MRCP). To our knowledge, no study has proposed an interpretation model using Boolean logistic operators “OR” or “AND” based on combinations of findings on these sequences to help making clinical judgement for small PDAC screening. Neither no study has evaluated the diagnostic performance of multiple ADC parameters by region of interest (ROI) methods in differentiating PDAC from mass-forming AIP. The purpose of this study was to propose an appropriate interpretation model for small PDAC screening (Part Ⅰ) and to identify effective quantitative ADC parameters for differential diagnosis between PDAC and mass-forming AIP (Part Ⅱ).

Materials and methods: In Part Ⅰ, thirty consecutive patients with surgery confirmed small PDAC (≤20 mm) and 302 patients without pancreatic abnormality were enrolled. I evaluated the presence of pancreatic masses on T1WI, T2WI, and DWI, and the abnormality of the main pancreatic duct (MPD) on T2WI and MRCP. Multivariate logistic regression analysis was performed to select significant sequences for discriminating the small PDAC and control groups. Boolean operators “OR” or “AND” were used to construct combinations of findings. Diagnostic performances of these sequences and combinations were evaluated by X2 tests. In Part Ⅱ, one hundred and fortyfour patients with PDAC and 23 patients with mass-forming AIP underwent diffusionweighted imaging with b-values of 0 s/mm2 and 800 s/mm2 . The minimum, maximum, and mean ADC values obtained by placing ROIs within lesions and percentile ADC values (10th, 25th, 50th, 75th, and 90th) from entire-lesion histogram analysis were compared between the two groups using Mann–Whitney U tests. The diagnostic performance was evaluated by receiver operating characteristic (ROC) curve analysis.

Results: In Part Ⅰ, multivariate logistic regression analysis showed that T1WI and DWI for detecting the presence of masses and MRCP for evaluating MPD abnormality were significantly associated with differentiation between the two groups (p = 0.0002, p = 0.0484 and p < 0.0001, respectively). The combination of findings on “T1WI or DWI or MRCP” achieved the highest sensitivity of 96.7% and negative predictive value of 99.6%. In Part Ⅱ, the ROC curve analysis showed that the maximum ADC value had the highest diagnostic performance (0.92), while the minimum ADC value had the lowest diagnostic performance (0.72). The AUC was lowest in 10th percentile ADC value and highest in 90th percentile value. The AUC of percentile ADC values increased along with the increase of percentile values.

Conclusions: The interpretation model “T1WI or DWI or MRCP” might be effective in small PDAC screening. When a mass was identified in the pancreas, quantitative ADC parameters might be helpful in differential diagnosis.

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