Giulia Benedetti1,2, Martina Mori3, Marta Maria Panzeri1, Maurizio Barbera1, Diego Palumbo1, Carla Sini3, Francesca Muffatti4, Valentina Andreasi4, Stephanie Steidler1, Claudio Doglioni5,6, Stefano Partelli4,6, Marco Manzoni7, Massimo Falconi4,6, Claudio Fiorino3,6, Francesco De Cobelli8,9,10. 1. Department of Radiology, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. 2. Radiology, Guys and St Thomas' NHS Foundation Trust, London, UK. 3. Medical Physics, IRCCS San Raffaele Scientific Institute, Milan, Italy. 4. Pancreatic Surgery Unit, Pancreas Translational & Clinical Research Center, IRCCS San Raffaele Scientific Institute, Milan, Italy. 5. Department of Pathology, IRCCS San Raffaele Scientific Institute, Milan, Italy. 6. Vita-Salute University, Milan, Italy. 7. Endocrinology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy. 8. Department of Radiology, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. decobelli.francesco@hsr.it. 9. Vita-Salute University, Milan, Italy. decobelli.francesco@hsr.it. 10. Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. decobelli.francesco@hsr.it.
Abstract
PURPOSE: To assess the ability of radiomic features (RF) extracted from contrast-enhanced CT images (ceCT) and non-contrast-enhanced (non-ceCT) in discriminating histopathologic characteristics of pancreatic neuroendocrine tumors (panNET). METHODS: panNET contours were delineated on pre-surgical ceCT and non-ceCT. First- second- and higher-order RF (adjusted to eliminate redundancy) were extracted and correlated with histological panNET grade (G1 vs G2/G3), metastasis, lymph node invasion, microscopic vascular infiltration. Mann-Whitney with Bonferroni corrected p values assessed differences. Discriminative power of significant RF was calculated for each of the end-points. The performance of conventional-imaged-based-parameters was also compared to RF. RESULTS: Thirty-nine patients were included (mean age 55-years-old; 24 male). Mean diameters of the lesions were 24 × 27 mm. Sixty-nine RF were considered. Sphericity could discriminate high grade tumors (AUC = 0.79, p = 0.002). Tumor volume (AUC = 0.79, p = 0.003) and several non-ceCT and ceCT RF were able to identify microscopic vascular infiltration: voxel-alignment, neighborhood intensity-difference and intensity-size-zone families (AUC ≥ 0.75, p < 0.001); voxel-alignment, intensity-size-zone and co-occurrence families (AUC ≥ 0.78, p ≤ 0.002), respectively). Non-ceCT neighborhood-intensity-difference (AUC = 0.75, p = 0.009) and ceCT intensity-size-zone (AUC = 0.73, p = 0.014) identified lymph nodal invasion; several non-ceCT and ceCT voxel-alignment family features were discriminative for metastasis (p < 0.01, AUC = 0.80-0.85). Conventional CT 'necrosis' could discriminate for microscopic vascular invasion (AUC = 0.76, p = 0.004) and 'arterial vascular invasion' for microscopic metastasis (AUC = 0.86, p = 0.001). No conventional-imaged-based-parameter was significantly associated with grade and lymph node invasion. CONCLUSIONS: Radiomic features can discriminate histopathology of panNET, suggesting a role of radiomics as a non-invasive tool for tumor characterization. TRIAL REGISTRATION NUMBER: NCT03967951, 30/05/2019.
PURPOSE: To assess the ability of radiomic features (RF) extracted from contrast-enhanced CT images (ceCT) and non-contrast-enhanced (non-ceCT) in discriminating histopathologic characteristics of pancreatic neuroendocrine tumors (panNET). METHODS: panNET contours were delineated on pre-surgical ceCT and non-ceCT. First- second- and higher-order RF (adjusted to eliminate redundancy) were extracted and correlated with histological panNET grade (G1 vs G2/G3), metastasis, lymph node invasion, microscopic vascular infiltration. Mann-Whitney with Bonferroni corrected p values assessed differences. Discriminative power of significant RF was calculated for each of the end-points. The performance of conventional-imaged-based-parameters was also compared to RF. RESULTS: Thirty-nine patients were included (mean age 55-years-old; 24 male). Mean diameters of the lesions were 24 × 27 mm. Sixty-nine RF were considered. Sphericity could discriminate high grade tumors (AUC = 0.79, p = 0.002). Tumor volume (AUC = 0.79, p = 0.003) and several non-ceCT and ceCT RF were able to identify microscopic vascular infiltration: voxel-alignment, neighborhood intensity-difference and intensity-size-zone families (AUC ≥ 0.75, p < 0.001); voxel-alignment, intensity-size-zone and co-occurrence families (AUC ≥ 0.78, p ≤ 0.002), respectively). Non-ceCT neighborhood-intensity-difference (AUC = 0.75, p = 0.009) and ceCT intensity-size-zone (AUC = 0.73, p = 0.014) identified lymph nodal invasion; several non-ceCT and ceCT voxel-alignment family features were discriminative for metastasis (p < 0.01, AUC = 0.80-0.85). Conventional CT 'necrosis' could discriminate for microscopic vascular invasion (AUC = 0.76, p = 0.004) and 'arterial vascular invasion' for microscopic metastasis (AUC = 0.86, p = 0.001). No conventional-imaged-based-parameter was significantly associated with grade and lymph node invasion. CONCLUSIONS: Radiomic features can discriminate histopathology of panNET, suggesting a role of radiomics as a non-invasive tool for tumor characterization. TRIAL REGISTRATION NUMBER: NCT03967951, 30/05/2019.
Entities:
Keywords:
Area under the curve (AUC); Computed tomography; Neuroendocrine tumors; Pancreatic neoplasms; Radiomic features
Authors: Francesco Giganti; Paolo Marra; Alessandro Ambrosi; Annalaura Salerno; Sofia Antunes; Damiano Chiari; Elena Orsenigo; Antonio Esposito; Elena Mazza; Luca Albarello; Roberto Nicoletti; Carlo Staudacher; Alessandro Del Maschio; Francesco De Cobelli Journal: Eur J Radiol Date: 2017-03-01 Impact factor: 3.528
Authors: G Rindi; G Klöppel; H Alhman; M Caplin; A Couvelard; W W de Herder; B Erikssson; A Falchetti; M Falconi; P Komminoth; M Körner; J M Lopes; A-M McNicol; O Nilsson; A Perren; A Scarpa; J-Y Scoazec; B Wiedenmann Journal: Virchows Arch Date: 2006-09-12 Impact factor: 4.064