FDG-PET Parameters as Prognostic Factor in Esophageal Cancer Patients: A Review

Background:18F-fluorodeoxyglucose positron emission tomography (FDG-PET) has been used extensively to explore whether FDG Uptake can be used to provide prognostic information for esophageal cancer patients. The aim of the present review is to evaluate the literature available to date concerning the potential prognostic value of FDG uptake in esophageal cancer patients, in terms of absolute pretreatment values and of decrease in FDG uptake during or after neoadjuvant therapy. Methods: A computer-aided search of the English language literature concerning esophageal cancer and standardized uptake values was performed. This search focused on clinical studies evaluating the prognostic value of FDG uptake as an absolute value or the decrease in FDG uptake and using overall mortality and/or disease-related mortality as an end point. Results: In total, 31 studies met the predefined criteria. Two main groups were identified based on the tested prognostic parameter: (1) FDG uptake and (2) decrease in FDG uptake. Most studies showed that pretreatment FDG uptake and postneoadjuvant treatment FDG uptake, as absolute values, are predictors for survival in univariate analysis. Moreover, early decrease in FDG uptake during neoadjuvant therapy is predictive for response and survival in most studies described. However, late decrease in FDG uptake after completion of neoadjuvant therapy was predictive for pathological response and survival in only 2 of 6 studies. Conclusions: Measuring decrease in FDG uptake early during neoadjuvant therapy is most appealing, moreover because the observed range of values expressed as relative decrease to discriminate responding from nonresponding patients is very small. At present inter-institutional comparison of results is difficult because several different normalization factors for FDG uptake are in use. Therefore, more research focusing on standardization of protocols and inter-institutional differences should be performed, before a PET-guided algorithm can be universally advocated

A Generic Respiratory Motion Model Based on 4D MRI Imaging and 2D Image Navigators

International audienceRespiratory motion modeling is a key method improving the accuracy of both diagnostic and therapeutic multi-modality imaging applications. Most of the respiratory motion models presented to date are patient specific, based on 4D CT or MRI datasets. They require a 4D anatomical image acquisition for every patient, implying in the case of CT an associated increased dose not justified for all patients or require a 4D MRI acquisition which is associated with a compromise between image quality and longer acquisitions not compatible with clinical practice. The objective of this work was to create a global respiratory motion model based on principal component analysis using 4D T1 MRI volunteer studies covering the thoracic region. This model can then be adapted on a specific patient using only two "breath hold" 3D MRI volumes in addition to 2D MRI images acquired using a 2D image navigator. Our generic model relates these navigators to the internal organ motion described by motion fields. Five volunteers were included in this study. Four of them were used to create the motion model which was subsequently tested on a fifth subject using a leave-one-out strategy. The global model accuracy was assessed by generating 4D MRI series and comparing them to the volunteer specific acquired 4D MRI images. The obtained accuracy and reproducibility results of the proposed generic respiratory motion model may allow robust and accurate respiratory motion correction in PET/MRI imaging without the need for patient specific 4D MRI acquisitions

A Generic Respiratory Motion Model Based on 4D MRI Imaging and 2D Image Navigators

International audienceRespiratory motion modeling is a key method improving the accuracy of both diagnostic and therapeutic multi-modality imaging applications. Most of the respiratory motion models presented to date are patient specific, based on 4D CT or MRI datasets. They require a 4D anatomical image acquisition for every patient, implying in the case of CT an associated increased dose not justified for all patients or require a 4D MRI acquisition which is associated with a compromise between image quality and longer acquisitions not compatible with clinical practice. The objective of this work was to create a global respiratory motion model based on principal component analysis using 4D T1 MRI volunteer studies covering the thoracic region. This model can then be adapted on a specific patient using only two "breath hold" 3D MRI volumes in addition to 2D MRI images acquired using a 2D image navigator. Our generic model relates these navigators to the internal organ motion described by motion fields. Five volunteers were included in this study. Four of them were used to create the motion model which was subsequently tested on a fifth subject using a leave-one-out strategy. The global model accuracy was assessed by generating 4D MRI series and comparing them to the volunteer specific acquired 4D MRI images. The obtained accuracy and reproducibility results of the proposed generic respiratory motion model may allow robust and accurate respiratory motion correction in PET/MRI imaging without the need for patient specific 4D MRI acquisitions

18F-FDG intra tumor uptake heterogeneity quantification form baseline PET images are prognostic factors of disease free survival and predict local recurrence in head and neck cancer

International audienc

18F-FDG intra tumor uptake heterogeneity quantification form baseline PET images are prognostic factors of disease free survival and predict local recurrence in head and neck cancer

International audienc

Prognostic value of head and neck tumor proliferative sphericity from 3’-deoxy-3’-[18F] fluorothymidine positron emission tomography

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Comparison of Timor Uptake Heterogeneity Characterization Between Static and Parametric F-18-FDG PET Images in Non-Small Cell Lung Cancer

Imaging- and therapeutic targets in neoplastic and musculoskeletal inflammatory diseas