A [68Ga]Ga-DOTANOC PET/CT Radiomic Model for Non-Invasive Prediction of Tumour Grade in Pancreatic Neuroendocrine Tumours

Predicting grade 1 (G1) and 2 (G2) primary pancreatic neuroendocrine tumour (panNET) is crucial to foresee panNET clinical behaviour. Fifty-one patients with G1-G2 primary panNET demonstrated by pre-surgical [68Ga]Ga-DOTANOC PET/CT and diagnostic conventional imaging were grouped according to the tu...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Alessandro Bevilacqua, Diletta Calabrò, Silvia Malavasi, Claudio Ricci, Riccardo Casadei, Davide Campana, Serena Baiocco, Stefano Fanti, Valentina Ambrosini
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2021-05-01
Sarja:	Diagnostics
Aiheet:	[68Ga]Ga-DOTANOC pancreatic neuroendocrine tumour machine learning biomarker standardized uptake value
Linkit:	https://www.mdpi.com/2075-4418/11/5/870
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