Ga-DOTATOC PET/MR Imaging and Radiomic Parameters in Predicting Histopathological Prognostic Factors in Patients with Pancreatic Neuroendocrine Well-differentiated Tumours

Overview

Journal Eur J Nucl Med Mol Imaging

Specialties Biophysics
Nuclear Medicine
Radiology

Date 2022 Feb 14

PMID 35156146

Authors

P Mapelli

C Bezzi

D Palumbo

C Canevari

S Ghezzo

A M Samanes Gajate

B Catalfamo

A Messina

L Presotto

A Guarnaccia

V Bettinardi

F Muffatti

V Andreasi

M Schiavo Lena

L Gianolli

S Partelli

M Falconi

P Scifo

F De Cobelli

M Picchio

Affiliations

Soon will be listed here.

Abstract

Purpose: To explore the role of fully hybrid Ga-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 Ga-DOTATOC PET/MRI scans (March 2018-June 2020) performed for gastroenteropancreatic neuroendocrine tumour were retrospectively evaluated; 16/187 patients met the eligibility criteria (Ga-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 Ga-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.

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