Hierarchies and shape-space for PET image segmentation

International audiencePositron Emission Tomography (PET) image segmentation is essential for detecting lesions and quantifying their metabolic activity. Due to the spatial and spectral properties of PET images, most methods rely on intensity-based strategies. Recent methods also propose to integrate anatomical priors to improve the segmentation process. In this article, we show how the hierarchical approaches proposed in mathematical morphology can efficiently handle these different strategies. Our contribution is twofold. First, we present the component-tree as a relevant data-structure for developing interactive , real-time, intensity-based segmentation of PET images. Second, we prove that thanks to the recent concept of shaping, we can efficiently involve a priori knowledge for lesion segmentation, while preserving the good properties of component-tree segmenta-tion. Preliminary experiments on synthetic and real PET images of lymphoma demonstrate the relevance of our approach

Role of Imaging in the Staging and Response Assessment of Lymphoma:Consensus of the International Conference on Malignant Lymphomas Imaging Working Group

This article comprises the consensus reached to update guidance on the use of PET-CT for staging and response assessment for 18F FDG-avid lymphomas in clinical practice and late-phase trials

Prognostic value of end-of-induction PET response after first-line immunochemotherapy for follicular lymphoma (GALLIUM): secondary analysis of a randomised, phase 3 trial

Initial results from the ongoing GALLIUM trial have shown that patients with follicular lymphoma have a longer progression-free survival after first-line immunochemotherapy with obinutuzumab than with rituximab. The aim of this secondary analysis was to evaluate the prognostic value of PET-CT responses after first-line immunochemotherapy in the GALLIUM study.GALLIUM is an open-label, parallel-group randomised, phase 3 trial, which recruited previously untreated patients with CD20-positive follicular lymphoma (grades 1-3a; disease stage III/IV, or stage II with largest tumour diameter ≥7 cm) who were aged 18 years or older and met the criteria for needing treatment. Eligible patients were randomly assigned in a 1:1 ratio to receive intravenous administration of obinutuzumab (1000 mg on days 1, 8, and 15 of cycle 1, then day 1 of subsequent cycles) or rituximab (375 mg/m2 on day 1 of each cycle), in six 21-day cycles with cyclophosphamide, doxorubicin, vincristine, and prednisone (known as CHOP; oral administration) followed by two 21-day cycles of antibody alone, or eight 21-day cycles cyclophosphamide, vincristine, and prednisone (known as CVP; oral administration), or six 28-day cycles with bendamustine, followed by maintenance antibody every 2 months for up to 2 years. The primary endpoint of the trial, investigator-assessed progression-free survival, has been reported previously. This secondary analysis reports PET and CT-based responses at end-of-induction therapy and explains their relation with progression-free and overall survival outcomes in patients with available scans. As per protocol, during the trial, PET scans (mandatory in the first 170 patients enrolled at sites with available PET facilities, and optional thereafter), acquired at baseline and end of induction (PET population), were assessed prospectively by investigators and an independent review committee (IRC) applying International Harmonisation Project (IHP) 2007 response criteria, and retrospectively by the IRC only applying current Lugano 2014 response criteria. IRC members (but not study investigators) were masked to treatment and clinical outcome when assessing response. The landmark analyses excluded patients who died or progressed (contrast enhanced CT-based assessment of progressive disease, or started next anti-lymphoma treatment) before or at end of induction. GALLIUM is registered at ClinicalTrials.gov, number NCT01332968.1202 patients were enrolled in GALLIUM between July 6, 2011, and Feb 4, 2014, of whom 595 were included in the PET population; 533 (IHP 2007; prospective analysis), and 508 (Lugano 2014; retrospective analysis) were analysed for progression-free survival (landmark analysis). At end of induction, 390 of 595 patients (65·5% [95% CI 61·6-69·4]) achieved PET complete response according to IHP 2007 criteria, and 450 (75·6% [95% CI 72·0-79·0]) obtained PET complete metabolic response according to Lugano 2014 criteria. With a median of 43·3 months of observation (IQR 36·2-51·8), 2·5-year progression-free survival from end of induction was 87·8% (95% CI 83·9-90·8) in PET complete responders and 72·0% (63·1-79·0) in non-complete responders according to IRC-assessed IHP 2007 criteria (hazard ratio [HR] 0·4, 95% CI 0·3-0·6, p<0·0001). According to Lugano 2014 criteria, 2·5-year progression-free survival in complete metabolic responders was 87·4% (95% CI 83·7-90·2) and in non-complete metabolic responders was 54·9% (40·5-67·3; HR 0·2, 95% CI 0·1-0·3, p<0·0001).Our results suggest that PET is a better imaging modality than contrast-enhanced CT for response assessment after first-line immunochemotherapy in patients with follicular lymphoma. PET assessment according to Lugano 2014 response criteria provides a platform for investigation of response-adapted therapeutic approaches. Additional supportive data are welcomed.F Hoffmann-La Roche

LA VIE ET L'OEUVRE DE PHILIPPE IGNACE SEMMELWEIS OU COMMENT LOUIS DESTOUCHES ANNONCE CELINE

PARIS12-CRETEIL BU Médecine (940282101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Apport de la normalisation spatiale des tomoscintigraphies à un modèle de référence pour la mesure quantitative de la contraction et de la perfusion myocardiques

La possibilité de mesurer simultanément la contraction et la perfusion myocardiques en tomoscintigraphie synchronisée constitue une avancée majeure pour la prise en charge de l'insuffisance coronaire, tant diagnostique que pronostique. De nombreuses approches en traitement d'image ont été proposées depuis les années 1990 pour quantifier au mieux ces variables. Dans ce travail, nous avons d'abord analysé les performances et les limites des principales approches publiées dans la littérature. Nous avons ensuite proposé une approche alternative, reposant sur une normalisation spatiale des images à un modèle cardiaque de référence, développée au cours d'une collaboration de notre institution avec la société Quantificare. L'intérêt de la normalisation spatiale est double : 1) améliorer la segmentation du myocarde grâce à une référence anatomique a priori fournie par une population normale moyennée (pour l'analyse de la fraction d'éjection du ventricule gauche), et 2) mieux caractériser la distribution de la perfusion en effectuant une comparaison voxel-par-voxel avec la population normale moyennée (pour l'analyse de la taille et de la sévérité des hypoperfusions). Nous avons enfin validé cette approche sur des populations de patients adaptées, en termes de précision, exactitude et pertinence clinique. Nous présentons le texte original de quatre articles publiés dans des revues internationales dans le cadre de ce travail. Nous concluons que la normalisation spatiale permet non seulement d'obtenir des mesures reproductibles et exactes de la fraction d'éjection du ventricule gauche mais se prête par ailleurs à une analyse de l'évolution temporelle des pathologies ischémiques.The ability for gated SPECT to measure simultaneously myocardial contraction and perfusion constitutes a major step forward in the management of coronary artery disease, such diagnostically than prognostically. Numerous image processing approaches have been proposed since the 1990's to quantify as best as possible these variables. In the present work, we first have analyzed the performances and limitations of the main approaches proposed in the literature. Then, we have proposed an alternative approach, based on the spatial normalization of images to a reference heart template, which has been developed during a collaboration between our institution and the Quantificare company. The interest of spatial normalization is twofold : 1) to improve myocardial segmentation with help of an a priori anatomical reference provided by an averaged normal population (for the assessment of left ventricular ejection fraction), and 2) to better characterize perfusion distribution by performing a voxel-by-voxel comparison with the averaged normal population (for the assessment of extent and severity of hypoperfusions). Finally, we have validated this approach on appropriate patient populations, in terms of precision, accuracy and clinical pertinence. We provide the text of four original articles published in international journals in the scope of the present work. We conclude that spatial normalization not only allows to obtain reproducible and accurate measurements of left ventricular ejection fraction but also is adapted to monitor serial changes of ischemic pathologies.PARIS12-CRETEIL BU Multidisc. (940282102) / SudocSudocFranceF

Automated 3D lymphoma lesion segmentation from PET/CT characteristics

International audiencePositron Emission Tomography (PET) using 18 F-FDG is recognized as the modality of choice for lymphoma, due to its high sensitivity and specificity. Its wider use for the detection of lesions, quantifica-tion of their metabolic activity and evaluation of response to treatment demands the development of accurate and reproducible quantitative image interpretation tools. An accurate tumour delineation remains a challenge in PET, due to the limitations the modality suffers from, despite being essential for quantifying reliable changes in tumour tissues. Due to the spatial and spectral properties of PET images , most methods rely on intensity-based strategies. Recent methods also propose to integrate anatomical priors to improve the seg-mentation process. However, the current routinely-used approach remains a local relative thresholding and requires important user interaction , leading to a process that is not only user-dependent but very laborious in the case of lymphomas. In this paper, we propose to rely on hierarchical image models embedding multimodality PET/CT de-scriptors for a fully automated PET lesion detection / segmenta-tion, performed via a machine learning process. More precisely, we propose to perform random forest classification within the mixed spatial-spectral space of component-trees modeling PET/CT mages. This new approach, combining the strengths of machine learning and morphological hierarchy models leads to intelligent thresholding based on high-level PET/CT knowledge. We evaluate our approach on a database of multi-centric PET/CT images of patients treated for lymphoma, delineated by an expert. Our method provides good efficiency, with the detection of 92% of all lesions, and accurate seg-mentation results with mean sensitivity and specificity of 0.73 and 0.99 respectively, without any user interaction