Presenter of 2 Presentations
LS 1.1 - How to diagnose
Abstract
Learning objectives
To become familiar with standard CT and MR acquisition protocolsTo learn about CT and MR diagnostic performance in tumour detection and staging
To understand the optimal imaging approach for tumour re-staging
Video-on-demand
LS 1.2 - Multidisciplinary panel discussion
Poster Author of 1 e-Poster
SE-090 - CT and MR texture analyses of liver metastases from neuroendocrine tumour(NET): evaluation of the ability to predict the tumour aggressiveness based on PET evaluation (Octreo-PET and fdg-PET) and histological evaluation.
Author of 1 Presentation
SE-090 - CT and MR texture analyses of liver metastases from neuroendocrine tumour(NET): evaluation of the ability to predict the tumour aggressiveness based on PET evaluation (Octreo-PET and fdg-PET) and histological evaluation.
Abstract
Purpose
The aim of the study is to evaluate the capability of texture analysis(TA) metrics calculated for NET liver metastases on CT and MR in discriminating the tumour aggressiveness based on PET-evaluation and on histological tumour grade.
Material and methods
This retrospective study included patients with liver metastases from NET previously investigated with FDG-PET/CT and Octreo-PET/CT. TA metrics were obtained by drawing a ROI including all liver lesion volume using a semi-automated tool(3D slicer) on contrast-enhanced CT or on ADCmaps. Patients inclusion criteria were: 1)NET histologically proven;2) liver metastases(dimension≥2cm) assessed on contrast-enhanced CT or DWI-MR, Octreo-PET/CT and FDG-PET/CT before any treatment. Patients were divided into two groups according to the aggressiveness based on PET-CT (high aggressiveness=positivity on fdg-PET, low aggressiveness=positivity on Octreo-PET and negative on FDG-PET/CVT) and on histological grade (high aggressiveness=G3, low aggressiveness=G1-G2). Association between TA with the tumour aggressiveness measured on PET and on histological grade were assessed using a logistic regression model (software Weka).
Results
Final study population consisted of 50 patients. The CT-TA discriminates the aggressiveness based on PET-CT with a AUC=0,8 and 0,6 and on histological grade with a AUC=0,9 and 0,5 for the less aggressive and more aggressive respectively. The MR-TA discriminates the aggressiveness based on PET-CT with a AUC=0,8 and 0,5 and on histological grade with a AUC=0,8 and 0,5 for the less aggressive and more aggressive respectively.
Conclusion
TA on both CT and MR showed good accuracy to identify less aggressive compared to more aggressive tumours according to the PET- and histological evaluation.
Presenter of 2 Presentations
LS 1.1 - How to diagnose
Abstract
Learning objectives
To become familiar with standard CT and MR acquisition protocolsTo learn about CT and MR diagnostic performance in tumour detection and staging
To understand the optimal imaging approach for tumour re-staging