The age of reason for FDG PET image-derived indices.

International audiencen.

Metabolically active volumes automatic delineation methodologies in PET imaging: review and perspectives

International audiencePET imaging is now considered a gold standard tool in clinical oncology, especially for diagnosis purposes. More recent applications such as therapy follow up or tumor targeting in radiotherapy require a fast, accurate and robust metabolically active tumor volumes on emission images, which cannot be obtained through manual contouring. This clinical need has sprung a large number of methodological developments regarding automatic methods to defined tumor volumes on PET images. This paper reviews most of the methodologies that have been recently proposed and discusses their framework and methodological and/or clinical validation. Perspectives regarding the future work to be done are also suggested

Respiratory motion on Functional Imaging in Oncology: a review of the effects and correction methodologies

A number of different parameters inherent in the PET detection process are contributing to a reduction in the quantitative accuracy of PET images. On the other hand, patient motion during imaging has been shown to cause significant artefacts leading to reduced image quality and quantitative accyracy. These effects are particularly important during imaging in thorax and abdomen where physiological motion associated with cardiac, respiratory and GI tract is significant. Respiratory motion effects in emission tomography imaging lead to a loss of sensitivity in the detection of disease as a result of the associated blurring. Furthermore, respiration causes significant changes in the volumes and activity concentrations of tumours predominantly in the lower thorax and upper abdomen, influencing this way the quantitative accuracy of PET images and subsequently its progress in new application domains such as radiotherapy treatment planning and therapy monitoring. Research in the area of respiratory motion detection and correction especially for emission tomography applications has grown significantly over the last few years. Proposed methodologies to correct for the respiratory motion are based on dynamic gated acquisitions. Furthermore image reconstruction algorithms incorporating respiratory motion compensation have been recently developed. The objectives of this paper are to present a review of current techniques in respiratory motion correction and detection for emission tomography, with a particular focus on oncology applications and PET imaging.De nombreux paramètres inhérents à la détection en Tomographie par Emission de Positons (TEP) influent sur la qualité des images. Le mouvement du patient pendant l'examen produit également d'importants artefacts qui réduisent la qualité des images. Ces effets sont particulièrement importants lors de l'imagerie du thorax et de l'abdomen où on ne peut s'affranchir des mouvements physiologiques du coeur et des poumons. Le mouvement respiratoire produit en particulier un bruit qui réduit la sensibilité de détection des lésions. De plus, la respiration modifie les volumes et les concentrations d'activité des tumeurs essentiellement dans le bas du thorax et le haut de l'abdomen, influençant ainsi les données quantitatives des images TEP reconstruites. La recherche dans le domaine de la détection et de la correction des mouvements respiratoires pour des applications en tomographie d'émission est très réactive. Les méthodologies généralement proposées pour corriger le mouvement respiratoire sont basées sur l'utilisation d'acquisitions dynamiques synchronisées sur la respiration. Néanmoins récemment de nouveaux algorithmes de reconstruction permettant de compenser les effets du mouvement respiratoire ont vu le jour. Les objectifs de cette étude sont de faire une revue des méthodologies actuelles dans le domaine de la compensation du mouvement respiratoire en tomographie d'émission, tout en portant un accent particulier sur les applications oncologiques et de l'imagerie TEP

Impact of tumor size and tracer uptake heterogeneity in (18)F-FDG PET and CT non-small cell lung cancer tumor delineation.: 18F-FDG PET and CT tumor delineation in NSCLC

International audienceUNLABELLED: The objectives of this study were to investigate the relationship between CT- and (18)F-FDG PET-based tumor volumes in non-small cell lung cancer (NSCLC) and the impact of tumor size and uptake heterogeneity on various approaches to delineating uptake on PET images. METHODS: Twenty-five NSCLC cancer patients with (18)F-FDG PET/CT were considered. Seventeen underwent surgical resection of their tumor, and the maximum diameter was measured. Two observers manually delineated the tumors on the CT images and the tumor uptake on the corresponding PET images, using a fixed threshold at 50% of the maximum (T(50)), an adaptive threshold methodology, and the fuzzy locally adaptive Bayesian (FLAB) algorithm. Maximum diameters of the delineated volumes were compared with the histopathology reference when available. The volumes of the tumors were compared, and correlations between the anatomic volume and PET uptake heterogeneity and the differences between delineations were investigated. RESULTS: All maximum diameters measured on PET and CT images significantly correlated with the histopathology reference (r > 0.89, P < 0.0001). Significant differences were observed among the approaches: CT delineation resulted in large overestimation (+32% ± 37%), whereas all delineations on PET images resulted in underestimation (from -15% ± 17% for T(50) to -4% ± 8% for FLAB) except manual delineation (+8% ± 17%). Overall, CT volumes were significantly larger than PET volumes (55 ± 74 cm(3) for CT vs. from 18 ± 25 to 47 ± 76 cm(3) for PET). A significant correlation was found between anatomic tumor size and heterogeneity (larger lesions were more heterogeneous). Finally, the more heterogeneous the tumor uptake, the larger was the underestimation of PET volumes by threshold-based techniques. CONCLUSION: Volumes based on CT images were larger than those based on PET images. Tumor size and tracer uptake heterogeneity have an impact on threshold-based methods, which should not be used for the delineation of cases of large heterogeneous NSCLC, as these methods tend to largely underestimate the spatial extent of the functional tumor in such cases. For an accurate delineation of PET volumes in NSCLC, advanced image segmentation algorithms able to deal with tracer uptake heterogeneity should be preferred

Comparison Between 18F-FDG PET Image-Derived Indices for Early Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer.

International audienceThe goal of this study was to determine the best predictive factor among image-derived parameters extracted from sequential F-FDG PET scans for early tumor response prediction after 2 cycles of neoadjuvant chemotherapy in breast cancer. METHODS: 51 breast cancer patients were included. Responder and nonresponder status was determined by histopathologic examination according to the tumor and node Sataloff scale. PET indices (maximum and mean standardized uptake value [SUV], metabolically active tumor volume, and total lesion glycolysis [TLG]), at baseline and their variation (Δ) after 2 cycles of neoadjuvant chemotherapy were extracted from the PET images. Their predictive value was investigated using Mann-Whitney U tests and receiver-operating-characteristic analysis. Subgroup analysis was also performed by considering estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative, triple-negative, and HER2-positive tumors separately. The impact of partial-volume correction was also investigated using an iterative deconvolution algorithm. RESULTS: There were 24 pathologic nonresponders and 27 responders. None of the baseline PET parameters was correlated with response. After 2 neoadjuvant chemotherapy cycles, the reduction of each parameter was significantly associated with response, the best prediction of response being obtained with ΔTLG (96% sensitivity, 92% specificity, and 94% accuracy), which had a significantly higher area under the curve (0.91 vs. 0.82, P = 0.01) than did ΔSUV (63% sensitivity, 92% specificity, and 77% accuracy). Subgroup analysis confirmed a significantly higher accuracy for ΔTLG than ΔSUV for ER-positive/HER-negative but not for triple-negative and HER2-positive tumors. Partial-volume correction had no impact on the predictive value of any of the PET image-derived parameters despite significant changes in their absolute values. CONCLUSION: Our results suggest that the reduction after 2 neoadjuvant chemotherapy cycles of the metabolically active volume of primary tumor measurements such as ΔTLG predicts histopathologic tumor response with higher accuracy than does ΔSUV measurements, especially for ER-positive/HER2-negative breast cancer. These results should be confirmed in a larger group of patients as they may potentially increase the clinical value and efficiency of F-FDG PET for early prediction of response to neoadjuvant chemotherapy

FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi-cancer site patient cohort.: FDG-PET heterogeneity and volume

International audienceIntra-tumor uptake heterogeneity in 18F-FDG PET has been associated with patient treatment outcomes in several cancer types. Textural features (TF) analysis is a promising method for its quantification. An open issue associated with the use of TF for the quantification of intratumoral heterogeneity concerns its added contribution and dependence on the metabolically active tumor volume (MATV), which has already been shown as a significant predictive and prognostic parameter. Our objective was to address this question using a larger cohort of patients covering different cancer types.METHODS:A single database of 555 pre-treatment 18F-FDG PET images (breast, cervix, esophageal, head & neck and lung cancer tumors) was assembled. Four robust and reproducible TF-derived parameters were considered. The issues associated with the calculation of TF using co-occurrence matrices (such as the quantization and spatial directionality relationships) were also investigated. The relationship between these features and MATV, as well as among the features themselves was investigated using Spearman rank coefficients, for different volume ranges. The complementary prognostic value of MATV and TF was assessed through multivariate Cox analysis in the esophageal and NSCLC cohorts.RESULTS:A large range of MATVs was included in the population considered (3-415 cm3, mean = 35, median = 19, SD=50). The correlation between MATV and TF varied greatly depending on the MATVs, with reduced correlation for increasing volumes. These findings were reproducible across the different cancer types. The quantization and the calculation method both had an impact on the correlation. Volume and heterogeneity were independent prognostic factors (P = 0.0053 and 0.0093 respectively) along with stage (P = 0.002) in NSCLC, but in the esophageal tumors, volume and heterogeneity had less complementary value due to smaller overall volumes.CONCLUSION:Our results suggest that heterogeneity quantification and volume may provide valuable complementary information for volumes above 10cm3, although the complementary information increases substantially with larger volumes

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

Valeur pronostique de la TEP-TDM au 18F-FluoroDéoxyGlucose dans les cancers broncho-pulmonaires non à petites cellules non métastatiques (apport de paramètres avancés)

Objectif : La distribution du 18 F-FDG au sein d'une lésion tumorale est un paramètre envisagé depuis peu pour caractériser les lésions en TEP. Plusieurs études ont montré son intérêt pronostique dans différents modèles tumoraux. L'objectif de cette étude est de comparer dans les cancers broncho-pulmonaires non à petites cellules non métastatiques (CBPNPC) la valeur pronostique des facteurs clinico-biologiques usuels et les paramètres dérivés de l'imagerie TEP tels que le volume, l'intensité de fixation et l'hétérogénéité de fixation qu'elle soit appréciée visuellement ou caractérisée avec l'analyse de texture. Matériels et méthodes : 122 patients atteints d'un CBPNPC de stade I à III ont été inclus dans une étude rétrospective de 2008 à 2011 (92 hommes, 30 femmes, âge moyen : 66 ans). Tous les patients avaient bénéficié d'une TEP-TDM au 18F-FDG avant traitement dans le cadre du bilan d'extension. Après le traitement initial, les patients ont été suivis régulièrement de façon usuelle. L'apport pronostique en termes de survie sans progression et de survie globale de 6 paramètres quantitatifs d'hétérogénéité, du SUV max, du volume tumoral métabolique actif (MATV) et du Total Lesion Glycolysis (TLG) a été évalué. L'hétérogénéité a été également appréciée visuellement en aveugle par deux observateurs, en utilisant 3 classes : distribution homogène, intermédiaire et hétérogène. Résultats : L'analyse multi variée montre que le stade TNM (p=0,01) est un facteur prédictif indépendant de la survie globale et sans progression. Certains paramètres d'hétérogénéité quantitative (la déviation standard et l'inhomogénéité) ainsi que le volume tumoral métabolique actif et le TLG sont également prédictifs de la survie et tendent même à être des facteurs pronostiques indépendants. Il existe par ailleurs une bonne concordance inter-observateur pour l'analyse visuelle de l'hétérogénéité tumorale avec une valeur de Kappa pondéré de 0.683. Cette analyse visuelle est également bien corrélée à l'analyse quantitative de la texture des images, mais sa valeur pronostique reste limitée. Conclusion : L'hétérogénéité de la distribution intra tumorale du 18F-FDG en TEP-TDM semble être un facteur pronostique prometteur chez les patients atteints d'un CBPNPC de stade I à III. Son appréciation visuelle semble moins pertinente que l'analyse de texture pour prédire le devenir des patients.POITIERS-BU Médecine pharmacie (861942103) / SudocSudocFranceF

Autocontouring versus manual contouring.

International audiencen.

Caractérisation de l'hétérogénéité intra tumorale en imagerie TEP pour la prédiction de la thérapeutique : impact de la méthode de segmentation et de la correction des effets de volumes partiels

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