ESTRO 2022 - Abstract Book

S555

Abstract book

ESTRO 2022

Conclusion NG-IVIM revealed differences in both microvasculature and cellularity between HPV+ and HPV- tumors, in addition to the difference in ADC obtained from conventional DWI. So, NG-IVIM is capable of providing a much more detailed picture of the tumor micro-environment and could aid in the understanding of differences between HPV+ and HPV- tumors.

Proffered Papers: Application of functional & quantitative imaging

OC-0626 Is pre-radiotherapy metabolic heterogeneity of Glioblastoma predictive of progression free survival?

F. TENSAOUTI 1,2 , F. Desmoulin 2 , J. Gilhodes 3 , S. Ken 4 , J. Lotterie 5 , G. Noël 6 , G. Truc 7 , M. Sunyach 8 , M.C. Charissoux 9 , N. Magné 10 , V. Lubrano 2 , P. Péran 2 , E.C. Moyal 11,12 , A. Laprie 13,2 1 Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse – Oncopôle , Radiation oncology, Toulouse, France; 2 ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Research, Toulouse, France; 3 Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse – Oncopôle , Biostatistics, Toulouse, France; 4 Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse – Oncopôle , Engineering and Medical Physics, Toulouse, France; 5 CHU Toulouse, Nuclear Medicine, Toulouse, France; 6 Institut de cancérologie Strasbourg Europe, Radiation Oncology, Strasbourg, France; 7 Centre Georges-François Leclerc, Radiation Oncology , Dijon, France; 8 Centre Léon-Bérard , Radiation oncology, Lyon, France; 9 Institut du Cancer de Montpellier, Radiation Oncology, Montpellier, France; 10 Institut de Cancérologie de la Loire Lucien Neuwirth, Radiation Oncology, Saint-Priest-en-Jarez, France; 11 Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse – Oncopôle, Radiation oncology, Toulouse, France; 12 Inserm U1037- Centre de Recherches contre le Cancer de Toulouse, Research, Toulouse, France; 13 Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse – Oncopôle , Radiation oncology, Toulouse, France Purpose or Objective Worse outcome of patients with glioblastoma (GBM) can be attributed to the heterogeneity of the tumor. Recent research has revealed that all GBM subtypes share the hallmark feature of aggressive invasion into the surrounding tissue that are not considered in the target volume. Then, identification of the different components of the tumor is of great importance to ensure an effective treatment. 1H MRI spectroscopic imaging (MRSI) is a non-invasive technique to obtain metabolic information. It is used for diagnosis, monitoring of response to treatment, dose escalation and for detection of mutated IDH gene status in gliomas. Every tissue can be classified based on its metabolic state. MRSI is able to identify the pathologic tissue with high accuracy where Choline (Cho), Creatine (Cr), N-acetylaspartate (NAA) and lactates (Lac) are the main altered metabolites. The aim of this work is to 1) identify clusters of metabolic heterogeneity in GBM using large MRSI data and 2) investigate which clusters can predict the progression free survival (PFS). Materials and Methods MRSI data from 173 patients included in the prospective SPECTRO-GLIO Trial (Laprie et al, 2019 and 2021) were analysed. A total of 42 699 good quality spectra were acquired in pre-radiotherapy examination. Automatic post-processing of data was carried out with syngo.MR Spectro (VB40A; Siemens). Eight features were extracted: Cho/NAA, NAA/Cr, Cho/Cr, Lac/NAA and (%Cho, %NAA, %Cr, %Lac (ratio of each metabolite to the sum of all)). The clustering was obtained via a mini-batch k-means algorithm, subsets of the input data are randomly sampled in each training iteration. Each mini-batch contains 1000 random spectra. The silhouette analysis was used to define the optimal