Riccardo De Robertis1, Bogdan Maris2, Nicolò Cardobi3, Paolo Tinazzi Martini3, Stefano Gobbo4, Paola Capelli5, Silvia Ortolani6, Sara Cingarlini7, Salvatore Paiella8, Luca Landoni8, Giovanni Butturini9, Paolo Regi9, Aldo Scarpa5, Giampaolo Tortora7, Mirko D'Onofrio10. 1. Department of Radiology, P. Pederzoli Hospital, Via Monte Baldo 24, 37019, Peschiera del Garda, Italy. riccardo.derobertis@hotmail.it. 2. Department of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy. 3. Department of Radiology, P. Pederzoli Hospital, Via Monte Baldo 24, 37019, Peschiera del Garda, Italy. 4. Department of Pathology, P. Pederzoli Hospital, Via Monte Baldo 24, 37019, Peschiera del Garda, Italy. 5. Department of Pathology, G.B. Rossi Hospital - University of Verona, Piazzale L.A. Scuro 10, 37134, Verona, Italy. 6. Department of Oncology, P. Pederzoli Hospital, Via Monte Baldo 24, 37019, Peschiera del Garda, Italy. 7. Department of Oncology, G.B. Rossi Hospital - University of Verona, Piazzale L.A. Scuro 10, 37134, Verona, Italy. 8. Department of Pancreatic Surgery, G.B. Rossi Hospital - University of Verona, Piazzale L.A. Scuro 10, 37134, Verona, Italy. 9. Department of Pancreatic Surgery, P. Pederzoli Hospital, Via Monte Baldo 24, 37019, Peschiera del Garda, Italy. 10. Department of Radiology, G.B. Rossi Hospital - University of Verona, Piazzale L.A. Scuro 10, 37134, Verona, Italy.
Abstract
OBJECTIVES: To evaluate MRI derived whole-tumour histogram analysis parameters in predicting pancreatic neuroendocrine neoplasm (panNEN) grade and aggressiveness. METHODS: Pre-operative MR of 42 consecutive patients with panNEN >1 cm were retrospectively analysed. T1-/T2-weighted images and ADC maps were analysed. Histogram-derived parameters were compared to histopathological features using the Mann-Whitney U test. Diagnostic accuracy was assessed by ROC-AUC analysis; sensitivity and specificity were assessed for each histogram parameter. RESULTS: ADCentropy was significantly higher in G2-3 tumours with ROC-AUC 0.757; sensitivity and specificity were 83.3 % (95 % CI: 61.2-94.5) and 61.1 % (95 % CI: 36.1-81.7). ADCkurtosis was higher in panNENs with vascular involvement, nodal and hepatic metastases (p= .008, .021 and .008; ROC-AUC= 0.820, 0.709 and 0.820); sensitivity and specificity were: 85.7/74.3 % (95 % CI: 42-99.2 /56.4-86.9), 36.8/96.5 % (95 % CI: 17.2-61.4 /76-99.8) and 100/62.8 % (95 % CI: 56.1-100/44.9-78.1). No significant differences between groups were found for other histogram-derived parameters (p >.05). CONCLUSIONS: Whole-tumour histogram analysis of ADC maps may be helpful in predicting tumour grade, vascular involvement, nodal and liver metastases in panNENs. ADCentropy and ADCkurtosis are the most accurate parameters for identification of panNENs with malignant behaviour. KEY POINTS: • Whole-tumour ADC histogram analysis can predict aggressiveness in pancreatic neuroendocrine neoplasms. • ADC entropy and kurtosis are higher in aggressive tumours. • ADC histogram analysis can quantify tumour diffusion heterogeneity. • Non-invasive quantification of tumour heterogeneity can provide adjunctive information for prognostication.
OBJECTIVES: To evaluate MRI derived whole-tumour histogram analysis parameters in predicting pancreatic neuroendocrine neoplasm (panNEN) grade and aggressiveness. METHODS: Pre-operative MR of 42 consecutive patients with panNEN >1 cm were retrospectively analysed. T1-/T2-weighted images and ADC maps were analysed. Histogram-derived parameters were compared to histopathological features using the Mann-Whitney U test. Diagnostic accuracy was assessed by ROC-AUC analysis; sensitivity and specificity were assessed for each histogram parameter. RESULTS: ADCentropy was significantly higher in G2-3 tumours with ROC-AUC 0.757; sensitivity and specificity were 83.3 % (95 % CI: 61.2-94.5) and 61.1 % (95 % CI: 36.1-81.7). ADCkurtosis was higher in panNENs with vascular involvement, nodal and hepatic metastases (p= .008, .021 and .008; ROC-AUC= 0.820, 0.709 and 0.820); sensitivity and specificity were: 85.7/74.3 % (95 % CI: 42-99.2 /56.4-86.9), 36.8/96.5 % (95 % CI: 17.2-61.4 /76-99.8) and 100/62.8 % (95 % CI: 56.1-100/44.9-78.1). No significant differences between groups were found for other histogram-derived parameters (p >.05). CONCLUSIONS: Whole-tumour histogram analysis of ADC maps may be helpful in predicting tumour grade, vascular involvement, nodal and liver metastases in panNENs. ADCentropy and ADCkurtosis are the most accurate parameters for identification of panNENs with malignant behaviour. KEY POINTS: • Whole-tumour ADC histogram analysis can predict aggressiveness in pancreatic neuroendocrine neoplasms. • ADC entropy and kurtosis are higher in aggressive tumours. • ADC histogram analysis can quantify tumour diffusion heterogeneity. • Non-invasive quantification of tumour heterogeneity can provide adjunctive information for prognostication.
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