Salivary gland-sparing other than parotid-sparing in definitive head-and-neck intensity-modulated radiotherapy does not seem to jeopardize local control.

International audienceBACKGROUND: The objective was to analyze locoregional (LR) failure patterns in patients with head-and-neck cancer (HNC) treated using intensity-modulated radiotherapy (IMRT) with whole salivary gland-sparing: parotid (PG), submandibular (SMG), and accessory salivary glands represented by the oral cavity (OC). METHODS: Seventy consecutive patients with Stage I-II (23%) or III/IV (77%) HNC treated by definitive IMRT were included. For all LR failure patients, the FDG-PET and CT scans documenting recurrence were rigidly registered to the initial treatment planning CT. Failure volumes (Vf) were delineated based on clinical, radiological, and histological data. The percentage of Vf covered by 95% of the prescription isodose (Vf-V95) was analyzed. Failures were classified as "in-field" if Vf--V95 >= 95%, "marginal" if 20% < Vf-V95 < 95%, and "out-of-field" if Vf-V95 <=20%. Correlation between Vf-V95 and mean doses (Dmean) in the PG, SMG, and OC was assessed using Spearman's rank-order correlation test. The salivary gland dose impact on the LR recurrence risk was assessed by Cox analysis. RESULTS: The median follow-up was 20 months (6--35). Contralateral and ipsilateral PGs were spared in 98% and 54% of patients, respectively, and contralateral and ipsilateral SMG in 26% and 7%, respectively. The OC was spared to a dose <=40 Gy in 26 patients (37%). The 2-year LR control rate was 76.5%. One recurrence was "marginal", and 12 were "in-field". No recurrence was observed in vicinity of spared structures. Vf-V95 was not significantly correlated with Dmean in PG, SMG, and OC. The LR recurrence risk was not increased by lower Dmean in the salivary glands, but by T (p = 0.04) and N stages (p = 0.03). CONCLUSION: Over 92% of LR failures occurred "in-field" within the high dose region when using IMRT with a whole salivary gland-sparing strategy. Sparing SMG and OC in addition to PG thus appears a safe strategy

Radiothérapie adaptative morphologique et métabolique des cancers ORL

Objectifs: The aims of this work were (i) to evaluate the dosimetric benefit and to predict the clinical benefit of adaptive radiotherapy for head and neck cancer, regarding both toxicities and local control, (ii) to identify patients whose good candidate for an adaptive strategy, and (iii) to identify the best adaptive strategy to spare the parotid glands. Materials and methods: The dosimetric benefit was assessed using data from a phase III study evaluating the clinical benefit of an adaptive radiotherapy. Cumulated dose with and without adaptive was estimated using deformable image registration. Different methods of deformable image registration were evaluated regarding both spatial and dose estimation accuracy. Predictive model of the risk of parotid gland overdose was computed using generalized linear mixed model and cross validation by leave‐one‐out. The dosimetric benefit of numerous replanning strategies, defined by various numbers and timing of replanning, with regard to parotid gland sparing, was quantified. We performed a systematic review to evaluate the predictive value of quantitative PET parameters. The predictive value of PET intensity parameters was assessed using two independent cohorts of patients. Résultats: Without adaptive radiotherapy, 65% of the patients had a PG overdose of more than 2 Gy and 50% of the patients had a tumor underdose of more than 1 Gy. Adaptive radiotherapy allows to correct both parotid gland overdose and tumor underdose. Based on parameters calculated at the planning and at the first week of treatment, predictive models of PG overdose and tumor underdose were computed. PET parameters correlated with overall survival were identified. Using two independent cohorts of patients, a nomogram to predict survival was build and externally validated. Conclusion: Our studies showed the benefit of adaptive radiotherapy to spare the parotid glands while increasing tumor coverage. These benefits should allow to decrease the toxicities while increasing local control. Early anatomical and dosimetric parameters allow identifying patients at risk of tumor underdose or parotid gland overdose. PET performed before the treatment allows identifying patients with a high‐risk of locoregional failure and death, potentially candidates for treatment. These results justify further studies on a larger cohort of patients, ideally in phase III clinical trials.Objectifs : Notre travail avait pour objectifs (i) d’évaluer le bénéfice dosimétrique et de prédire le bénéfice clinique d’une radiothérapie adaptative pour des cancers des voies aéro‐digestives supérieures, à la fois en termes de toxicité et de contrôle local, (ii) d’identifier les patients bons candidats à une stratégie de radiothérapie adaptative, et (iii) d’identifier le meilleur schéma de radiothérapie adaptative pour épargner les parotides. Matériels et méthodes : Le bénéfice dosimétrique a été évalué en utilisant les données de patients inclus dans une étude de phase III évaluant le bénéfice clinique d’une radiothérapie adaptative. La dose cumulée sans et avec radiothérapie adaptative a été estimée par des méthodes de recalage élastique. Une évaluation des différents algorithmes de recalage a été faite à la fois en termes de précision spatiale et d’impact sur la dose estimée. Des modèles de prédiction du risque de surdosage ont été développés en utilisant des modèles linéaires généralisées mixtes et une validation croisée par leave‐one‐out. L’évaluation de différents schémas de radiothérapie adaptative (en termes de fréquence et de nombre) a été réalisée en se basant sur l’épargne des parotides. La valeur prédictive de paramètres quantitatifs issus de la TEP a été évaluée à travers une revue systématique de la littérature. La valeur prédictive de paramètres intensité issue de la TEP a été analysée dans 2 cohortes indépendantes. Résultats : Nos travaux ont confirmé qu’en l’absence de radiothérapie adaptative pour des cancers des VADS, il existe un risque de surdosage des parotides de plus de 2 Gy pour les 2/3 des patients. Il s’y associe un risque de sous dosage de la tumeur de plus de 1 Gy pour 50 % des patients. Une radiothérapie adaptative permet de corriger à la fois le surdosage des parotides (bénéfice clinique estimée de 10 % de diminution du risque de xérostomie) et le sous dosage de la tumeur. Basés sur des paramètres issus de la planification et de la première semaine de traitement, des modèles de prédiction du risque de sur dosage des parotides ou de sous dosage de la tumeur ont été développés. Les paramètres TEP prédictifs du risque de récidive ont été identifiés. Un nomogramme a pu être développé et validé dans une 2nd cohorte de patients. Conclusion : Nos travaux confirment le bénéfice d’une radiothérapie adaptative pour épargner les parotides et maintenir la couverture tumorale. Ce bénéfice dosimétrique devrait permettre une diminution de la toxicité et une amélioration du contrôle local. Des paramètres anatomiques et dosimétriques simples permettent l’identification des patients à risque de surdosage des parotides ou de sous dosage de la tumeur. L’utilisation de la TEP permet d’identifier précocement les patients à haut risque de récidive, candidats potentiels à une intensification thérapeutique. Ces résultats justifient la poursuite des travaux sur une cohorte de patients plus importante, idéalement dans le cadre d’études cliniques de phase III

Morphological and metabolic adaptive radiotherapy for head and neck cancers

Objectifs : Notre travail avait pour objectifs (i) d’évaluer le bénéfice dosimétrique et de prédire le bénéfice clinique d’une radiothérapie adaptative pour des cancers des voies aéro‐digestives supérieures, à la fois en termes de toxicité et de contrôle local, (ii) d’identifier les patients bons candidats à une stratégie de radiothérapie adaptative, et (iii) d’identifier le meilleur schéma de radiothérapie adaptative pour épargner les parotides. Matériels et méthodes : Le bénéfice dosimétrique a été évalué en utilisant les données de patients inclus dans une étude de phase III évaluant le bénéfice clinique d’une radiothérapie adaptative. La dose cumulée sans et avec radiothérapie adaptative a été estimée par des méthodes de recalage élastique. Une évaluation des différents algorithmes de recalage a été faite à la fois en termes de précision spatiale et d’impact sur la dose estimée. Des modèles de prédiction du risque de surdosage ont été développés en utilisant des modèles linéaires généralisées mixtes et une validation croisée par leave‐one‐out. L’évaluation de différents schémas de radiothérapie adaptative (en termes de fréquence et de nombre) a été réalisée en se basant sur l’épargne des parotides. La valeur prédictive de paramètres quantitatifs issus de la TEP a été évaluée à travers une revue systématique de la littérature. La valeur prédictive de paramètres intensité issue de la TEP a été analysée dans 2 cohortes indépendantes. Résultats : Nos travaux ont confirmé qu’en l’absence de radiothérapie adaptative pour des cancers des VADS, il existe un risque de surdosage des parotides de plus de 2 Gy pour les 2/3 des patients. Il s’y associe un risque de sous dosage de la tumeur de plus de 1 Gy pour 50 % des patients. Une radiothérapie adaptative permet de corriger à la fois le surdosage des parotides (bénéfice clinique estimée de 10 % de diminution du risque de xérostomie) et le sous dosage de la tumeur. Basés sur des paramètres issus de la planification et de la première semaine de traitement, des modèles de prédiction du risque de sur dosage des parotides ou de sous dosage de la tumeur ont été développés. Les paramètres TEP prédictifs du risque de récidive ont été identifiés. Un nomogramme a pu être développé et validé dans une 2nd cohorte de patients. Conclusion : Nos travaux confirment le bénéfice d’une radiothérapie adaptative pour épargner les parotides et maintenir la couverture tumorale. Ce bénéfice dosimétrique devrait permettre une diminution de la toxicité et une amélioration du contrôle local. Des paramètres anatomiques et dosimétriques simples permettent l’identification des patients à risque de surdosage des parotides ou de sous dosage de la tumeur. L’utilisation de la TEP permet d’identifier précocement les patients à haut risque de récidive, candidats potentiels à une intensification thérapeutique. Ces résultats justifient la poursuite des travaux sur une cohorte de patients plus importante, idéalement dans le cadre d’études cliniques de phase III.Objectifs: The aims of this work were (i) to evaluate the dosimetric benefit and to predict the clinical benefit of adaptive radiotherapy for head and neck cancer, regarding both toxicities and local control, (ii) to identify patients whose good candidate for an adaptive strategy, and (iii) to identify the best adaptive strategy to spare the parotid glands. Materials and methods: The dosimetric benefit was assessed using data from a phase III study evaluating the clinical benefit of an adaptive radiotherapy. Cumulated dose with and without adaptive was estimated using deformable image registration. Different methods of deformable image registration were evaluated regarding both spatial and dose estimation accuracy. Predictive model of the risk of parotid gland overdose was computed using generalized linear mixed model and cross validation by leave‐one‐out. The dosimetric benefit of numerous replanning strategies, defined by various numbers and timing of replanning, with regard to parotid gland sparing, was quantified. We performed a systematic review to evaluate the predictive value of quantitative PET parameters. The predictive value of PET intensity parameters was assessed using two independent cohorts of patients. Résultats: Without adaptive radiotherapy, 65% of the patients had a PG overdose of more than 2 Gy and 50% of the patients had a tumor underdose of more than 1 Gy. Adaptive radiotherapy allows to correct both parotid gland overdose and tumor underdose. Based on parameters calculated at the planning and at the first week of treatment, predictive models of PG overdose and tumor underdose were computed. PET parameters correlated with overall survival were identified. Using two independent cohorts of patients, a nomogram to predict survival was build and externally validated. Conclusion: Our studies showed the benefit of adaptive radiotherapy to spare the parotid glands while increasing tumor coverage. These benefits should allow to decrease the toxicities while increasing local control. Early anatomical and dosimetric parameters allow identifying patients at risk of tumor underdose or parotid gland overdose. PET performed before the treatment allows identifying patients with a high‐risk of locoregional failure and death, potentially candidates for treatment. These results justify further studies on a larger cohort of patients, ideally in phase III clinical trials

Indications et résultats de la radiothérapie stéréotaxique robotisée par le Cyberknife de Nice (étude prospective 2007)

NICE-BU Médecine Odontologie (060882102) / SudocSudocFranceF

A PET-based nomogram for oropharyngeal cancers

Purpose In the context of locally advanced oropharyngeal cancer (LAOC) treated with definitive radiotherapy (RT) (combined with chemotherapy or cetuximab), the aims of this study were: (1) to identify PET-FDG parameters correlated with overall survival (OS) from a first cohort of patients; then (2) to compute a prognostic score; and (3) finally to validate this scoring system in a second independent cohort of patients. Materials and methods A total of 76 consecutive patients (training cohort from Rennes) treated with chemoradiotherapy or RT with cetuximab for LAOC were used to build a predictive model of locoregional control (LRC) and OS based on PET-FDG parameters. After internal calibration and validation of this model, a nomogram and a scoring system were developed and tested in a validation cohort of 46 consecutive patients treated with definitive RT for LAOC in Lausanne. Results In multivariate analysis, the metabolic tumour volume (MTV) of the primary tumour and the lymph nodes were independent predictive factors for LRC and OS. Internal calibration showed a very good adjustment between the predicted OS and the observed OS at 24 months. Using the predictive score, two risk groups were identified (median OS 42 versus 14 months, p < 0.001) and confirmed in the validation cohort from Lausanne (median OS not reached versus 26 months, p = 0.008). Conclusions This is the first report of a PET-based nomogram in oropharyngeal cancer. Interestingly, it appeared stronger than the classical prognostic factors and was validated in independent cohorts markedly diverging in many aspects, which suggest that the observed signal was robust

The synergistic effect of radiotherapy and immunotherapy: A promising but not simple partnership

International audienceRadiotherapy (RT) is one of the main components in the treatment of cancer. The better understanding of the immune mechanisms associated with tumor establishment and how RT affects inflammation and immunity has led to the development of novel treatment strategies. Several preclinical studies support the use of RT in combination with immunotherapy obtaining better local and systemic tumor control. Current ongoing studies will provide information about the optimal RT approach, but the development of reliable predictors of the response from the preclinical and the early phases of clinical studies is necessary to avoid discarding treatment strategies with significant clinical benefit. This review summarize the current concepts of the synergism between RT and immunotherapy, the molecular effects of RT in the tumor microenvironment, their impact on immune activation and its potential clinical applications in trials exploring this important therapeutic opportunity. Finally, the potential predictors of clinical response are discussed

FDG PET in Diffuse Spinal Carcinomatous Meningitis

International audienc

Deep Learning-Based Segmentation of Head and Neck Organs-at-Risk with Clinical Partially Labeled Data

International audienceRadiotherapy is one of the main treatments for localized head and neck (HN) cancer. To design a personalized treatment with reduced radio-induced toxicity, accurate delineation of organs at risk (OAR) is a crucial step. Manual delineation is time- and labor-consuming, as well as observer-dependent. Deep learning (DL) based segmentation has proven to overcome some of these limitations, but requires large databases of homogeneously contoured image sets for robust training. However, these are not easily obtained from the standard clinical protocols as the OARs delineated may vary depending on the patient’s tumor site and specific treatment plan. This results in incomplete or partially labeled data. This paper presents a solution to train a robust DL-based automated segmentation tool exploiting a clinical partially labeled dataset. We propose a two-step workflow for OAR segmentation: first, we developed longitudinal OAR-specific 3D segmentation models for pseudo-contour generation, completing the missing contours for some patients; with all OAR available, we trained a multi-class 3D convolutional neural network (nnU-Net) for final OAR segmentation. Results obtained in 44 independent datasets showed superior performance of the proposed methodology for the segmentation of fifteen OARs, with an average Dice score coefficient and surface Dice similarity coefficient of 80.59% and 88.74%. We demonstrated that the model can be straightforwardly integrated into the clinical workflow for standard and adaptive radiotherapy

Segmentation and classification of head and neck nodal metastases and primary tumors in PET/CT

The prediction of cancer characteristics, treatment planning and patient outcome from medical images generally requires tumor delineation. In Head and Neck cancer (H&N), the automatic segmentation and differentiation of primary Gross Tumor Volumes (GTVt) and malignant lymph nodes (GTVn) is a necessary step for large-scale radiomics studies to predict patient outcome such as Progression Free Survival (PFS). Detecting malignant lymph nodes is also a crucial step for Tumor-Node-Metastases (TNM) staging and to support the decision to resect the nodes. In turn, automatic TNM staging and patient outcome prediction can greatly benefit patient care by helping clinicians to find the best personalized treatment. We propose the first model to automatically individually segment GTVt and GTVn in PET/CT images. A bi-modal 3D U-Net model is trained for multi-class and multi-components segmentation on the multi-centric HECKTOR 2020 dataset containing 254 cases. The dataset has been specifically re-annotated by experts to obtain ground truth GTVn contours. The results show promising segmentation performance for the automation of radiomics pipelines and their validation on large-scale studies for which manual annotations are not available. An average test Dice Similarity Coefficients (DSC) of 0.717 is obtained for the segmentation of GTVt. The GTVn segmentation is evaluated with an aggregated DSC to account for the cases without GTVn, which is estimated at 0.729 on the test set