P Mapelli1,2, C Bezzi1,2, D Palumbo1,3, C Canevari2, S Ghezzo1,2, A M Samanes Gajate2, B Catalfamo4, A Messina1,3, L Presotto2, A Guarnaccia1, V Bettinardi2, F Muffatti5, V Andreasi1,5, M Schiavo Lena6, L Gianolli2, S Partelli1,5, M Falconi1,5, P Scifo2, F De Cobelli1,3, M Picchio7,8. 1. Vita-Salute San Raffaele University, Via Olgettina 58, 20132, Milan, Italy. 2. Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. 3. Department of Radiology, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. 4. Department of Biomedical and Dental Sciences and of Morpho-Functional Imaging, Nuclear Medicine Unit, University of Messina, Piazza Pugliatti 1, 98125, Messina, Italy. 5. Pancreatic Surgery Unit, Pancreas Translational & Clinical Research Centre, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. 6. Pathology Department, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. 7. Vita-Salute San Raffaele University, Via Olgettina 58, 20132, Milan, Italy. picchio.maria@hsr.it. 8. Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. picchio.maria@hsr.it.
Abstract
PURPOSE: To explore the role of fully hybrid 68Ga-DOTATOC PET/MR imaging and radiomic parameters in predicting histopathological prognostic factors in patients with pancreatic neuroendocrine tumours (PanNETs) undergoing surgery. METHODS: One hundred eighty-seven consecutive 68Ga-DOTATOC PET/MRI scans (March 2018-June 2020) performed for gastroenteropancreatic neuroendocrine tumour were retrospectively evaluated; 16/187 patients met the eligibility criteria (68Ga-DOTATOC PET/MRI for preoperative staging of PanNET and availability of histological data). PET/MR scans were qualitatively and quantitatively interpreted, and the following imaging parameters were derived: PET-derived SUVmax, SUVmean, somatostatin receptor density (SRD), total lesion somatostatin receptor density (TLSRD), and MRI-derived apparent diffusion coefficient (ADC), arterial and late enhancement, necrosis, cystic degeneration, and maximum diameter. Additionally, first-, second-, and higher-order radiomic parameters were extracted from both PET and MRI scans. Correlations with several PanNETs' histopathological prognostic factors were evaluated using Spearman's coefficient, while the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate parameters' predictive performance. RESULTS: Primary tumour was detected in all 16 patients (15/16 by 68Ga-DOTATOC PET and 16/16 by MRI). SUVmax and SUVmean resulted good predictors of lymphnodal (LN) involvement (AUC of 0.850 and 0.783, respectively). Second-order radiomic parameters GrayLevelVariance and HighGrayLevelZoneEmphasis extracted from T2 MRI demonstrated significant correlations with LN involvement (adjusted p = 0.009), also showing good predictive performance (AUC = 0.992). CONCLUSION: This study demonstrates the role of the fully hybrid PET/MRI tool for the synergic function of imaging parameters extracted by the two modalities and highlights the potentiality of imaging and radiomic parameters in assessing histopathological features of PanNET aggressiveness.
PURPOSE: To explore the role of fully hybrid 68Ga-DOTATOC PET/MR imaging and radiomic parameters in predicting histopathological prognostic factors in patients with pancreatic neuroendocrine tumours (PanNETs) undergoing surgery. METHODS: One hundred eighty-seven consecutive 68Ga-DOTATOC PET/MRI scans (March 2018-June 2020) performed for gastroenteropancreatic neuroendocrine tumour were retrospectively evaluated; 16/187 patients met the eligibility criteria (68Ga-DOTATOC PET/MRI for preoperative staging of PanNET and availability of histological data). PET/MR scans were qualitatively and quantitatively interpreted, and the following imaging parameters were derived: PET-derived SUVmax, SUVmean, somatostatin receptor density (SRD), total lesion somatostatin receptor density (TLSRD), and MRI-derived apparent diffusion coefficient (ADC), arterial and late enhancement, necrosis, cystic degeneration, and maximum diameter. Additionally, first-, second-, and higher-order radiomic parameters were extracted from both PET and MRI scans. Correlations with several PanNETs' histopathological prognostic factors were evaluated using Spearman's coefficient, while the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate parameters' predictive performance. RESULTS: Primary tumour was detected in all 16 patients (15/16 by 68Ga-DOTATOC PET and 16/16 by MRI). SUVmax and SUVmean resulted good predictors of lymphnodal (LN) involvement (AUC of 0.850 and 0.783, respectively). Second-order radiomic parameters GrayLevelVariance and HighGrayLevelZoneEmphasis extracted from T2 MRI demonstrated significant correlations with LN involvement (adjusted p = 0.009), also showing good predictive performance (AUC = 0.992). CONCLUSION: This study demonstrates the role of the fully hybrid PET/MRI tool for the synergic function of imaging parameters extracted by the two modalities and highlights the potentiality of imaging and radiomic parameters in assessing histopathological features of PanNET aggressiveness.
Authors: Thomas A Hope; Miguel Hernandez Pampaloni; Eric Nakakura; Henry VanBrocklin; James Slater; Salma Jivan; Carina Mari Aparici; Judy Yee; Emily Bergsland Journal: Abdom Imaging Date: 2015-08
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