In this study, we test the feasibility of free-breathing quantitative T2 measurement in the pancreas and we correlate T2-values with demographical and clinical parameters in 88 patients whom were subject to a liver MRI. We found that using a 10-fold accelerated multi-echo-spin-echo MRI prototype sequence at 3T, we were able to measure pancreatic T2-values in a short acquisition time, with low variability and a good inter-reader agreement. We found significant differences in T2-values depending on age, measurement location, main pancreatic duct dilatation and diffuse pancreatic disease.
Unlike conventional MR sequences, which evaluate morphological alterations, T2 mapping, or T2 relaxometry, enables the quantification of the transverse relaxation time of the underlying tissues1. This quantitative evaluation is assumed to be more sensitive and reproducible than the visual assessment of T2 weighted MR images for the identification of small contrast changes (e.g. tissue edema)2. Moreover, due to the comparability of the absolute quantitative measures, it is possible to establish normative value ranges for different organsT2 mapping has already been introduced in clinical practice for various organs, e.g. brain3–5, heart6 and cartilage7–9.
The application of T2 mapping in the abdomen has been proven more difficult because of the physiological movement of the abdominal organs with the respiratory cycle, as well as bowel peristalsis, which may result in motion artifacts. However, the technique has already been successfully applied in the liver for diffuse liver disease, such as iron overload10.
Although pancreatic T2 mapping has been successfully performed in a few volunteers at 1.5 and 3T11–13, the technique has not yet been investigated in patients. Furthermore, since motion artifacts are invariably associated with the long acquisition times of quantitative imaging, T2 mapping in abdominal organs has not been widely performed. However, recent work validated the use of a novel quantitative MRI sequence for T2 mapping in the brain, that drastically shortened the acquisition time compared to previously used methods14. A similar strategy may enable reproducible T2 mapping in moving abdominal organs as well. The aim of our study was to test the feasibility of free-breathing quantitative T2 measurement in the pancreas and correlate T2-values with age, body mass index, measurement location, main pancreatic duct dilatation and underlying pathology.
This retrospective single center pilot study included 88 consecutive adult patients (M/F: 42/46, mean age 57 yo) who underwent a dedicated liver magnetic resonance imaging (MRI) protocol including a prototype T2-mapping sequence using an accelerated multi-echo-spin-echo sampling with respiratory trigger. Patients in whom the identification of the pancreas parenchyma on the MR images was impossible were excluded (n=5). Quantitative maps were reconstructed by employing a combination of GeneRalized Auto-calibrating Partially Parallel Acquisition (GRAPPA) and Model-based Accelerated RelaxomeTry by Iterative Non-linear Inversion (MARTINI), dubbed “GRAPPATINI”. The technique also allowed multiple synthetic reconstructions of T2 weighted images at different TE times (at 40, 100 and 150ms).
Two radiologists independently delineated three regions of interest inside the head, body and tail of the pancreas for each acquisition. The mean and standard deviation of T2-values within these regions were measured for all patients (Fig. 1). Variation of T2-values with demographic data, intraparenchymal location, presence of pancreatic duct dilation and underlying pancreatic disease was assessed. The electronic patient charts were then reviewed in order to collect demographic and clinical data: sex, age, BMI, and any possible diffuse/focal pancreatic disease. Inter-reader reliability was determined by calculating the interclass coefficient. T2-values were compared intra-patient between different pancreatic locations (ANOVA). Inter-patient correlations between T2-values and demographical, clinical and radiological data were calculated (ANOVA).
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