Prediction of pancreatic neuroendocrine tumour grade with MR imaging features: added value of diffusion-weighted imaging.
In: European Radiology, Jg. 27 (2017-04-01), Heft 4, S. 1748-1759
Online
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Zugriff:
Objectives: To evaluate the value of MR imaging including diffusion-weighted imaging (DWI) for the grading of pancreatic neuroendocrine tumours (pNET). Material and Methods: Between 2006 and 2014, all resected pNETs with preoperative MR imaging including DWI were included. Tumour grading was based on the 2010 WHO classification. MR imaging features included size, T1-w, and T2-w signal intensity, enhancement pattern, apparent (ADC) and true diffusion (D) coefficients. Results: One hundred and eight pNETs (mean 40 ± 33 mm) were evaluated in 94 patients (48 women, 51 %, mean age 52 ± 12). Fifty-five (51 %), 42 (39 %), and 11 (10 %) tumours were given the following grades (G): G1, G2, and G3. Mean ADC and D values were significantly lower as grade increased (ADC: 2.13 ± 0.70, 1.78 ± 0.72, and 0.86 ± 0.22 10-3 mm2/s, and D: 1.92 ± 0.70, 1.75 ± 0.74, and 0.82 ± 0.19 10-3 mm2/s G1, G2, and G3, all p < 0.001). A higher grade was associated with larger sized tumours (p < 0.001). The AUROC of ADC and D to differentiate G3 and G1-2 were 0.96 ± 0.02 and 0.95 ± 0.02. Optimal cut-off values for the identification of G3 were 1.19 10-3 mm2/s for ADC (sensitivity 100 %, specificity 92 %) and 1.04 10-3 mm2/s for D (sensitivity 82 %, specificity 92 %). Conclusion: Morphological/functional MRI features of pNETS depend on tumour grade. DWI is useful for the identification of high-grade tumours. Key Points: • Morphological and functional MRI features of pNETs depend on tumour grade. • Their combination has a high predictive value for grade. • All pNETs should be explored by MR imaging including DWI. • DWI is helpful for identification of high-grade and poorly-differentiated tumours. [ABSTRACT FROM AUTHOR]
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Prediction of pancreatic neuroendocrine tumour grade with MR imaging features: added value of diffusion-weighted imaging.
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Autor/in / Beteiligte Person: | Lotfalizadeh, Emad ; Ronot, Maxime ; Wagner, Mathilde ; Cros, Jérôme ; Couvelard, Anne ; Vullierme, Marie-Pierre ; Allaham, Wassim ; Hentic, Olivia ; Ruzniewski, Philippe ; Vilgrain, Valérie |
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Zeitschrift: | European Radiology, Jg. 27 (2017-04-01), Heft 4, S. 1748-1759 |
Veröffentlichung: | 2017 |
Medientyp: | academicJournal |
ISSN: | 0938-7994 (print) |
DOI: | 10.1007/s00330-016-4539-4 |
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