[PET/CT in radiotherapy : indications and potential applications]. / TEP/TDM en radiothérapie : indications et perspectives.

Functional imaging, including positron emission tomography combined with computed tomography (PET/CT), allows the evaluation of numerous biological properties that could be considered at all steps of the therapeutic management of patients treated with radiotherapy. Indeed, it enables better initial staging of the disease, and some parameters may also be used as predictive biomarkers for treatment response, allowing better selection of patients eligible for radiotherapy. It may also improve the definition of target volumes with the aim of dose escalations by dose-painting. Finally, it could be useful during the follow-up to assess response to treatment. In this review, we report how functional imaging is integrated at the present time during the radiotherapy procedure, and what are its potential future contributions.

L'imagerie fonctionnelle, dont la tomographie par émission de positons couplée à la tomodensitométrie (TEP/TDM), permet l'évaluation de nombreuses propriétés biologiques qui pourraient être prises en compte à toutes les étapes de la prise en charge des patients traités par radiothérapie. En effet, elle permet une meilleure stadification initiale de la maladie, et certains paramètres peuvent également être utilisés comme biomarqueurs prédictifs de la réponse au traitement, permettant ainsi une meilleure sélection des patients éligibles à la radiothérapie. Elle peut également améliorer la définition des volumes cibles dans le but d'escalader la dose par dose-painting. Enfin, elle pourrait être utile lors du suivi pour évaluer la réponse au traitement. Dans cette revue, nous rapportons comment l'imagerie fonctionnelle est intégrée, à l'heure actuelle, au cours d'un traitement par radiothérapie, et nous discutons quelles sont ses futures contributions potentielles dans les principales localisations tumorales où la radiothérapie est recommandée.

Identification of CT radiomic features robust to acquisition and segmentation variations for improved prediction of radiotherapy-treated lung cancer patient recurrence.

The primary objective of the present study was to identify a subset of radiomic features extracted from primary tumor imaged by computed tomography of early-stage non-small cell lung cancer patients, which remain unaffected by variations in segmentation quality and in computed tomography image acquisition protocol. The robustness of these features to segmentation variations was assessed by analyzing the correlation of feature values extracted from lesion volumes delineated by two annotators. The robustness to variations in acquisition protocol was evaluated by examining the correlation of features extracted from high-dose and low-dose computed tomography scans, both of which were acquired for each patient as part of the stereotactic body radiotherapy planning process. Among 106 radiomic features considered, 21 were identified as robust. An analysis including univariate and multivariate assessments was subsequently conducted to estimate the predictive performance of these robust features on the outcome of early-stage non-small cell lung cancer patients treated with stereotactic body radiation therapy. The univariate predictive analysis revealed that robust features demonstrated superior predictive potential compared to non-robust features. The multivariate analysis indicated that linear regression models built with robust features displayed greater generalization capabilities by outperforming other models in predicting the outcomes of an external validation dataset.

Correlation between rCBV Delineation Similarity and Overall Survival in a Prospective Cohort of High-Grade Gliomas Patients: The Hidden Value of Multimodal MRI?

PURPOSE: The accuracy of target delineation in radiation treatment planning of high-grade gliomas (HGGs) is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Magnetic resonance imaging (MRI) represents the standard imaging modality for delineation of gliomas with inherent limitations in accurately determining the microscopic extent of tumors. The purpose of this study was to assess the survival impact of multi-observer delineation variability of multiparametric MRI (mpMRI) and [18F]-FET PET/CT. MATERIALS AND METHODS: Thirty prospectively included patients with histologically confirmed HGGs underwent a PET/CT and mpMRI including diffusion-weighted imaging (DWI: b0, b1000, ADC), contrast-enhanced T1-weighted imaging (T1-Gado), T2-weighted fluid-attenuated inversion recovery (T2Flair), and perfusion-weighted imaging with computation of relative cerebral blood volume (rCBV) and K2 maps. Nine radiation oncologists delineated the PET/CT and MRI sequences. Spatial similarity (Dice similarity coefficient: DSC) was calculated between the readers for each sequence. Impact of the DSC on progression-free survival (PFS) and overall survival (OS) was assessed using Kaplan-Meier curves and the log-rank test. RESULTS: The highest DSC mean values were reached for morphological sequences, ranging from 0.71 +/- 0.18 to 0.84 +/- 0.09 for T2Flair and T1Gado, respectively, while metabolic volumes defined by PET/CT achieved a mean DSC of 0.75 +/- 0.11. rCBV variability (mean DSC0.32 +/- 0.20) significantly impacted PFS (p = 0.02) and OS (p = 0.002). CONCLUSIONS: Our data suggest that the T1-Gado and T2Flair sequences were the most reproducible sequences, followed by PET/CT. Reproducibility for functional sequences was low, but rCBV inter-reader similarity significantly impacted PFS and OS.

PET/CT-Based Radiogenomics Supports KEAP1/NFE2L2 Pathway Targeting for Non-Small Cell Lung Cancer Treated with Curative Radiotherapy.

In lung cancer patients, radiotherapy is associated with a increased risk of local relapse (LR) when compared with surgery but with a preferable toxicity profile. The KEAP1/NFE2L2 mutational status (MutKEAP1/NFE2L2) is significantly correlated with LR in patients treated with radiotherapy but is rarely available. Prediction of MutKEAP1/NFE2L2 with noninvasive modalities could help to further personalize each therapeutic strategy. Methods: Based on a public cohort of 770 patients, model RNA (M-RNA) was first developed using continuous gene expression levels to predict MutKEAP1/NFE2L2, resulting in a binary output. The model PET/CT (M-PET/CT) was then built to predict M-RNA binary output using PET/CT-extracted radiomics features. M-PET/CT was validated on an external cohort of 151 patients treated with curative volumetric modulated arc radiotherapy. Each model was built, internally validated, and evaluated on a separate cohort using a multilayer perceptron network approach. Results: The M-RNA resulted in a C statistic of 0.82 in the testing cohort. With a training cohort of 101 patients, the retained M-PET/CT resulted in an area under the curve of 0.90 (P < 0.001). With a probability threshold of 20% applied to the testing cohort, M-PET/CT achieved a C statistic of 0.7. The same radiomics model was validated on the volumetric modulated arc radiotherapy cohort as patients were significantly stratified on the basis of their risk of LR with a hazard ratio of 2.61 (P = 0.02). Conclusion: Our approach enables the prediction of MutKEAP1/NFE2L2 using PET/CT-extracted radiomics features and efficiently classifies patients at risk of LR in an external cohort treated with radiotherapy.

The dosimetric parameters impact on local recurrence in stereotactic radiotherapy for brain metastases.

OBJECTIVES: Stereotactic radiotherapy (SRT) for brain metastases (BM) allows very good local control (LC). However, approximately 20%-30% of these lesions will recur. The objective of this retrospective study was to evaluate the impact of dosimetric parameters on LC in cerebral SRT. METHODS: Patients treated with SRT for 1-3 BM between January 2015 and December 2018 were retrospectively included. A total of 349 patients with 538 lesions were included. The median gross tumour volume (GTV) was 2 cm3 (IQR, 0-7). The median biological effective dose with α/ß = 10 (BED10) was 60 Gy (IQR, 32-82). The median prescription isodose was 71% (IQR, 70-80). Correlations with LC were examined using the Cox regression model. RESULTS: The median follow-up period was 55 months (min-max, 7-85). Median overall survival was 17.8 months (IQR, 15.2-21.9). There were 95 recurrences and LC at 1 and 2 years was 87.1% (95% CI, 84-90) and 78.1% (95% CI, 73.9-82.4), respectively. Univariate analysis showed that systemic treatment, dose to 2% and 50% of the planning target volume (PTV), BED10 > 50 Gy, and low PTV and GTV volume were significantly correlated with better LC. In the multivariate analysis, GTV volume, isodose, and BED10 were significantly associated with LC. CONCLUSION: These results show the importance of a BED10 > 50 Gy associated with a prescription isodose <80% to optimize LC during SRT for BM. ADVANCES IN KNOWLEDGE: Isodose, BED, and GTV volume were significantly associated with LC. A low isodose improves LC without increasing the risk of radionecrosis.

How to contour the different heart subregions for future deep-learning modeling of the heart: A practical pictorial proposal for radiation oncologists.

There are currently no accurate rules for manually delineating the subregions of the heart (cavities, vessels, aortic/mitral valves, Planning organ at Risk Volumes for coronary arteries) with the perspective of deep-learning based modeling. Our objective was to present a practical pictorial view for radiation oncologists, based on the RTOG atlas and anatomical complementary considerations for the cases where the RTOG guidelines are missing.

Predictive clinical and dosimetric parameters for risk of relapse in early-stage non-small cell lung cancer treated by SBRT: A large single institution experience.

Purpose: To evaluate the impact of dosimetric parameters on efficacy of stereotactic body radiation therapy (SBRT) in early-stage non-small cell lung cancer (ES-NSCLC), using Hypofractionated Treatment Effects in the Clinic (HyTEC) reporting standards. Methods: From April 2010 to December 2020, 497 patients who received SBRT for ES-NSCLC at the University Hospital of Liège were retrospectively enrolled. A total dose of 40 to 60 Gy in 3-5 fractions (72-180 Gy biologically effective dose with an α/ß ratio of 10 (BED10)) was prescribed to the 80 % isodose line of the PTV. Potential clinical and dosimetric predictors of recurrence, overall survival (OS) and disease specific survival (DSS) were evaluated using univariate and multivariate analyses. Results: After a median follow-up of 32 months (range 3-143 months), the local control and disease-free survival (DFS) rates at 3 years were 91 % (95 % CI: 90 %-93 %) and 75 % (95 % CI: 73 %-77 %), respectively. The median OS was 41.6 months and the median DSS was not reached. On multivariate analysis, a higher gross tumor volume (GTV) Dmax (BED10) (cut-off 198 Gy) and a larger percent of the GTV receiving ≥110 % of the prescribed dose were predictive of a better local control, only GTV volume was correlated with DSS and no parameter was correlated with OS and regional or distant recurrences. Conclusion: Lung SBRT for ES-NSCLC in 3 to 5 fractions resulted in high local control rates. A higher percent of GTV receiving ≥110 % of the prescribed dose and a higher GTV Dmax (BED10) seem to allow a better local control.

Multicentric development and evaluation of [18F]FDG PET/CT and CT radiomic models to predict regional and/or distant recurrence in early-stage non-small cell lung cancer treated by stereotactic body radiation therapy.

PURPOSE: To develop machine learning models to predict regional and/or distant recurrence in patients with early-stage non-small cell lung cancer (ES-NSCLC) after stereotactic body radiation therapy (SBRT) using [18F]FDG PET/CT and CT radiomics combined with clinical and dosimetric parameters. METHODS: We retrospectively collected 464 patients (60% for training and 40% for testing) from University Hospital of Liège and 63 patients from University Hospital of Brest (external testing set) with ES-NSCLC treated with SBRT between 2010 and 2020 and who had undergone pretreatment [18F]FDG PET/CT and planning CT. Radiomic features were extracted using the PyRadiomics toolbox®. The ComBat harmonization method was applied to reduce the batch effect between centers. Clinical, radiomic, and combined models were trained and tested using a neural network approach to predict regional and/or distant recurrence. RESULTS: In the training (n = 273) and testing sets (n = 191 and n = 63), the clinical model achieved moderate performances to predict regional and/or distant recurrence with C-statistics from 0.53 to 0.59 (95% CI, 0.41, 0.67). The radiomic (original_firstorder_Entropy, original_gldm_LowGrayLevelEmphasis and original_glcm_DifferenceAverage) model achieved higher predictive ability in the training set and kept the same performance in the testing sets, with C-statistics from 0.70 to 0.78 (95% CI, 0.63, 0.88) while the combined model performs moderately well with C-statistics from 0.50 to 0.62 (95% CI, 0.37, 0.69). CONCLUSION: Radiomic features extracted from pre-SBRT analog and digital [18F]FDG PET/CT outperform clinical parameters in the prediction of regional and/or distant recurrence and to discuss an adjuvant systemic treatment in ES-NSCLC. Prospective validation of our models should now be carried out.

Prediction of Acute Radiation-Induced Lung Toxicity After Stereotactic Body Radiation Therapy Using Dose-Volume Parameters From Functional Mapping on Gallium 68 Perfusion Positron Emission Tomography/Computed Tomography.

PURPOSE: The aim of this work was to compare anatomic and functional dose-volume parameters as predictors of acute radiation-induced lung toxicity (RILT) in patients with lung tumors treated with stereotactic body radiation therapy. METHODS AND MATERIALS: Fifty-nine patients treated with stereotactic body radiation therapy were prospectively included. All patients underwent gallium 68 lung perfusion positron emission tomography (PET)/computed tomography (CT) imaging before treatment. Mean lung dose (MLD) and volumes receiving x Gy (VxGy, 5-30 Gy) were calculated in 5 lung volumes: the conventional anatomic volume (AV) delineated on CT images, 3 lung functional volumes (FVs) defined on lung perfusion PET imaging (FV50%, FV70%, and FV90%; ie, the minimal volume containing 50%, 70%, and 90% of the total activity within the AV), and a low FV (LFV; LFV = AV - FV90%). The primary endpoint of this analysis was grade ≥2 acute RILT at 3 months as assessed with National Cancer Institute Common Terminology Criteria for Adverse Events version 5. Dose-volume parameters in patients with and without acute RILT were compared. Receiver operating characteristic curves assessing the ability of dose-volume parameters to discriminate between patients with and without acute RILT were generated, and area under the curve (AUC) values were calculated. RESULTS: Of the 59 patients, 10 (17%) had grade ≥2 acute RILT. The MLD and the VxGy in the AV and LFV were not statistically different between patients with and without acute RILT (P > .05). All functional parameters were significantly higher in acute RILT patients (P < .05). AUC values (95% CI) for MLD AV, LFV, FV50%, FV70%, and FV90% were 0.66 (0.46-0.85), 0.60 (0.39-0.80), 0.77 (0.63-0.91), 0.77 (0.64-0.91), and 0.75 (0.58-0.91), respectively. AUC values for V20Gy AV, LFV, FV50%, FV70%, and FV90% were 0.65 (0.44-0.87), 0.64 (0.46-0.83), 0.82 (0.69-0.95), 0.81 (0.67-0.96), and 0.75 (0.57-0.94), respectively. CONCLUSIONS: The predictive value of PET perfusion-based functional parameters outperforms the standard CT-based dose-volume parameters for the risk of grade ≥2 acute RILT. Functional parameters could be useful for guiding radiation therapy planning and reducing the risk of acute RILT.

The abscopal effect of immune-radiation therapy in recurrent and metastatic cervical cancer: a narrative review.

Despite human papillomavirus vaccination and screening, in about 5% of cases, cervical cancer (CC) is discovered at an initial metastatic stage. Moreover, nearly one-third of patients with locally advanced CC (LACC) will have a recurrence of their disease during follow-up. At the stage of recurrent or metastatic CC, there are very few treatment options. They are considered incurable with a very poor prognosis. For many years, the standard of care was the combination of platinum-based drug and paclitaxel with the possible addition of bevacizumab. The most recent years have seen the development of the use of immune checkpoint inhibitors (ICIs) (pembrolizumab, cemiplimab and others) in patients with CC. They have shown long term responses with improved overall survival of patients in 1st line (in addition to chemotherapy) or 2nd line (as monotherapy) treatment. Another emerging drug is tisotumab vedotin, an antibody-drug conjugate targeting tissue factor. Radiation therapy (RT) often has a limited palliative indication in metastatic cancers. However, it has been observed that RT can induce tumor shrinkage both in distant metastatic tumors beyond the radiation field and in primary irradiated tumors. This is a rarely observed phenomenon, called abscopal effect, which is thought to be related to the immune system and allows a tumor response throughout the body. It would be the activation of the immune system induced by the irradiation of cancer cells that would lead to a specific type of apoptosis, the immunogenic cell death. Today, there is a growing consensus that combining RT with ICIs may boost abscopal response or cure rates for various cancers. Here we will review the potential abscopal effect of immune-radiation therapy in metastatic cervical cancer.

New Automated Method for Lung Functional Volumes Delineation with Lung Perfusion PET/CT Imaging.

BACKGROUND: Gallium-68 lung perfusion PET/CT is an emerging imaging modality for the assessment of regional lung function, especially to optimise radiotherapy (RT) planning. A key step of lung functional avoidance RT is the delineation of lung functional volumes (LFVs) to be integrated into radiation plans. However, there is currently no consistent and reproducible delineation method for LFVs. The aim of this study was to develop and evaluate an automated delineation threshold method based on total lung function for LFVs delineation with Gallium-68 MAA lung PET/CT imaging. MATERIAL AND METHOD: Patients prospectively enrolled in the PEGASUS trial-a pilot study assessing the feasibility of lung functional avoidance using perfusion PET/CT imaging for lung stereotactic body radiotherapy (SBRT) of primary or secondary lesion-were analysed. Patients underwent lung perfusion MAA-68Ga PET/CT imaging and pulmonary function tests (PFTs) as part of pre-treatment evaluation. LFVs were delineated using two methods: the commonly used relative to the maximal pixel value threshold method (pmax threshold method, X%pmax volumes) and a new approach based on a relative to whole lung function threshold method (WLF threshold method, FVX% volumes) using a dedicated iterative algorithm. For both methods, LFVs were expressed in terms of % of the anatomical lung volume (AV) and of % of the total lung activity. Functional volumes were compared for patients with normal PFTs and pre-existing airway disease. RESULTS: 60 patients were analysed. Among the 48 patients who had PFTs, 31 (65%) had pre-existing lung disease. The pmax and WLF threshold methods clearly provided different functional volumes with a wide range of relative lung function for a given pmax volume, and conversely, a wide range of corresponding pmax values for a given WLF volume. The WLF threshold method provided more reliable and consistent volumes with much lower dispersion of LFVs as compared to the pmax method, especially in patients with normal PFTs. CONCLUSIONS: We developed a relative to whole lung function threshold segmentation method to delineate lung functional volumes on perfusion PET/CT imaging. The automated algorithm allows for reproducible contouring. This new approach, relatively unaffected by the presence of hot spots, provides reliable and consistent functional volumes, and is clinically meaningful for clinicians.

Pembrolizumab plus pemetrexed-carboplatin combination in first-line treatment of advanced non-squamous non-small cell lung cancer: a multicenter real-life study (CAP29).

Background: Pembrolizumab combined with chemotherapy is now first-line standard of care in advanced non-small cell lung cancer. This real-life study aimed to assess efficacy and safety of carboplatin-pemetrexed plus pembrolizumab in advanced non-squamous non-small cell lung cancer. Methods: CAP29 is a retrospective, observational, multicenter real-life study conducted in 6 French centers. We evaluated efficacy of first-line setting chemotherapy plus pembrolizumab (November 2019 to September 2020) in advanced (stage III-IV) non-squamous non-small cell lung cancer patients without targetable alterations. Primary endpoint was progression-free survival. Secondary endpoints were overall survival, objective response rate and safety. Results: With a median follow-up of 4.5 months (0 to 22 months), a total of 121 patients were included. Baseline characteristics were: median age of 59.8 years with 7.4% ≥75 years, 58.7% of males, 91.8% PS 0-1, 87.6% of stage IV with ≥3 metastatic sites in 62% of cases. Patients had brain and liver metastases in 24% and 15.7% of cases, respectively. PD-L1 was <1% (44.6%), 1-49% (28.1%) and ≥50% (21.5%). Median progression-free survival and overall survival achieved 9 and 20.6 months, respectively. Objective response rate was 63.7% with 7 prolonged complete responses. Survival benefit seemed to be correlated with PD-L1 expression. Brain and liver metastases were not statistically associated with decreased overall survival. Most common adverse events were asthenia (76%), anemia (61.2%), nausea (53.7%), decreased appetite (37.2%) and liver cytolysis (34.7%). Renal and hepatic disorders were the main causes of pemetrexed discontinuation. Grade 3-4 adverse events concerned 17.5% of patients. Two treatment-related deaths were reported. Conclusions: First-line pembrolizumab plus chemotherapy confirmed real-life efficacy for patients with advanced non-squamous non-small cell lung cancer. With median progression-free survival and overall survival of 9.0 and 20.6 months, respectively and no new safety signal, our real-life data are very close to results provided by clinical trials, confirming the benefit and the manageable toxicity profile of this combination.

A Feasibility Study of Functional Lung Volume Preservation during Stereotactic Body Radiotherapy Guided by Gallium-68 Perfusion PET/CT.

The aim of this study was to assess the feasibility of sparing functional lung areas by integration of pulmonary functional mapping guided by 68Ga-perfusion PET/CT imaging in lung SBRT planification. Sixty patients that planned to receive SBRT for primary or secondary lung tumors were prospectively enrolled. Lung functional volumes were defined as the minimal volume containing 50% (FV50%), 70% (FV70%) and 90% (FV90%) of the total activity within the anatomical volume. All patients had a treatment planning carried out in 2 stages: an anatomical planning blinded to the PET results and then a functional planning respecting the standard constraints but also incorporating "lung functional volume" constraints. The mean lung dose (MLD) in functional volumes and the percentage of lung volumes receiving xGy (VxGy) within the lung functional volumes using both plans were calculated and compared. SBRT planning optimized to spare lung functional regions led to a significant reduction (p < 0.0001) of the MLD and V5 to V20 Gy in all functional volumes. Median relative difference of the MLD in the FV50%, FV70% and FV90% was -8.0% (-43.0 to 1.2%), -7.1% (-34.3 to 1.2%) and -5.7% (-22.3 to 4.4%), respectively. Median relative differences for VxGy ranged from -12.5% to -9.2% in the FV50%, -11.3% to -7.2% in the FV70% and -8.0% to -5.3% in the FV90%. This study shows the feasibility of significantly decreasing the doses delivered to the lung functional volumes using 68Ga-perfusion PET/CT while still respecting target volume coverage and doses to other organs at risk.

Multicentric development and evaluation of 18F-FDG PET/CT and MRI radiomics models to predict para-aortic lymph node involvement in locally advanced cervical cancer.

PURPOSE: To develop machine learning models to predict para-aortic lymph node (PALN) involvement in patients with locally advanced cervical cancer (LACC) before chemoradiotherapy (CRT) using 18F-FDG PET/CT and MRI radiomics combined with clinical parameters. METHODS: We retrospectively collected 178 patients (60% for training and 40% for testing) in 2 centers and 61 patients corresponding to 2 further external testing cohorts with LACC between 2010 to 2022 and who had undergone pretreatment analog or digital 18F-FDG PET/CT, pelvic MRI and surgical PALN staging. Only primary tumor volumes were delineated. Radiomics features were extracted using the Radiomics toolbox®. The ComBat harmonization method was applied to reduce the batch effect between centers. Different prediction models were trained using a neural network approach with either clinical, radiomics or combined models. They were then evaluated on the testing and external validation sets and compared. RESULTS: In the training set (n = 102), the clinical model achieved a good prediction of the risk of PALN involvement with a C-statistic of 0.80 (95% CI 0.71, 0.87). However, it performed in the testing (n = 76) and external testing sets (n = 30 and n = 31) with C-statistics of only 0.57 to 0.67 (95% CI 0.36, 0.83). The ComBat-radiomic (GLDZM_HISDE_PET_FBN64 and Shape_maxDiameter2D3_PET_FBW0.25) and ComBat-combined (FIGO 2018 and same radiomics features) models achieved very high predictive ability in the training set and both models kept the same performance in the testing sets, with C-statistics from 0.88 to 0.96 (95% CI 0.76, 1.00) and 0.85 to 0.92 (95% CI 0.75, 0.99), respectively. CONCLUSIONS: Radiomic features extracted from pre-CRT analog and digital 18F-FDG PET/CT outperform clinical parameters in the decision to perform a para-aortic node staging or an extended field irradiation to PALN. Prospective validation of our models should now be carried out.

Re-Irradiation by Stereotactic Radiotherapy of Brain Metastases in the Case of Local Recurrence.

PURPOSE: To evaluate the efficacy and safety of a second course of stereotactic radiotherapy (SRT2) treatment for a local recurrence of brain metastases previously treated with SRT (SRT1), using the Hypofractionated Treatment Effects in the Clinic (HyTEC) reporting standards and the European Society for Radiotherapy and Oncology guidelines. METHODS: From December 2014 to May 2021, 32 patients with 34 brain metastases received salvage SRT2 after failed SRT1. A total dose of 21 to 27 Gy in 3 fractions or 30 Gy in 5 fractions was prescribed to the periphery of the PTV (99% of the prescribed dose covering 99% of the PTV). After SRT2, multiparametric MRI, sometimes combined with 18F-DOPA PET-CT, was performed every 3 months to determine local control (LC) and radionecrosis (RN). RESULTS: After a median follow-up of 12 months (range: 1-37 months), the crude LC and RN rates were 68% and 12%, respectively, and the median overall survival was 25 months. In a multivariate analysis, the performance of surgery was predictive of a significantly better LC (p = 0.002) and survival benefit (p = 0.04). The volume of a normal brain receiving 5 Gy during SRT2 (p = 0.04), a dose delivered to the PTV in SRT1 (p = 0.003), and concomitant systemic therapy (p = 0.04) were associated with an increased risk of RN. CONCLUSION: SRT2 is an effective approach for the local recurrence of BM after initial SRT treatment and is a potential salvage therapy option for well-selected people with a good performance status. Surgery was associated with a higher LC.

Lung Stereotactic Body Radiation Therapy in a Patient with Severe Lung Function Impairment Allowed by Gallium-68 Perfusion PET/CT Imaging: A Case Report.

Lung stereotactic body radiotherapy (SBRT) is increasingly proposed, especially for patients with poor lung function who are not eligible for surgery. However, radiation-induced lung injury remains a significant treatment-related adverse event in these patients. Moreover, for patients with very severe COPD, we have very few data about the safety of SBRT for lung cancer. We present the case of a female with very severe chronic obstructive pulmonary disease (COPD) with a forced expiratory volume in one second (FEV1) of 0.23 L (11%), for whom a localized lung tumor was found. Lung SBRT was the only possible treatment. It was allowed and safely performed, based on a pre-therapeutic evaluation of regional lung function with Gallium-68 perfusion lung positron emission tomography combined with computed tomography (PET/CT). This is the first case report to highlight the potential use of a Gallium-68 perfusion PET/CT in order to safely select patients with very severe COPD who can benefit from SBRT.

Combination of Radiomics Features and Functional Radiosensitivity Enhances Prediction of Acute Pulmonary Toxicity in a Prospective Validation Cohort of Patients with a Locally Advanced Lung Cancer Treated with VMAT-Radiotherapy.

INTRODUCTION: The standard of care for people with locally advanced lung cancer (LALC) who cannot be operated on is (chemo)-radiation. Despite the application of dose constraints, acute pulmonary toxicity (APT) still often occurs. Prediction of APT is of paramount importance for the development of innovative therapeutic combinations. The two models were previously individually created. With success, the Rad-model incorporated six radiomics functions. After additional validation in prospective cohorts, a Pmap-model was created by identifying a specific region of the right posterior lung and incorporating several clinical and dosimetric parameters. To create and test a novel model to forecast the risk of APT in two cohorts receiving volumetric arctherapy radiotherapy (VMAT), we aimed to include all the variables in this study. METHODS: In the training cohort, we retrospectively included all patients treated by VMAT for LALC at one institution between 2015 and 2018. APT was assessed according to the CTCAE v4.0 scale. Usual clinical and dosimetric features, as well as the mean dose to the pre-defined Pmap zone (DMeanPmap), were processed using a neural network approach and subsequently validated on an observational prospective cohort. The model was evaluated using the area under the curve (AUC) and balanced accuracy (Bacc). RESULTS: 165 and 42 patients were enrolled in the training and test cohorts, with APT rates of 22.4 and 19.1%, respectively. The AUCs for the Rad and Pmap models in the validation cohort were 0.83 and 0.81, respectively, whereas the AUC for the combined model (Comb-model) was 0.90. The Bacc for the Rad, Pmap, and Comb models in the validation cohort were respectively 78.7, 82.4, and 89.7%. CONCLUSION: The accuracy of prediction models were increased by combining radiomics, DMeanPmap, and common clinical and dosimetric features. The use of this model may improve the evaluation of APT risk and provide access to novel therapeutic alternatives, such as dose escalation or creative therapy combinations.

Abscopal Response in Metastatic Melanoma: Real-World Data of a Retrospective, Multicenter Study.

Objective: To evaluate the incidence of the abscopal response (AR) in patients with metastatic melanoma requiring palliative radiotherapy (RT). Patients and methods: Patients treated for metastatic melanoma between January 1998 and February 2020 in four oncology departments were screened. Patients with progression under immune checkpoint inhibitors or without ongoing systemic treatment, and requiring palliative RT were considered. The AR was defined as an objective response according to RECIST and/or iRECIST for at least one non-irradiated metastasis at distance (≥10 cm) from the irradiated lesion. Primary endpoint was the rate of AR. Secondary endpoints were overall survival (OS), progression-free survival (PFS), local control (LC) of the irradiated lesion, and toxicity as assessed by CTCAE v5. Results: Over the period considered, 118 patients were included and analyzed. Fifteen patients (12.7%) had an AR. With a median follow-up of 7.7 months (range, 0.2−242.2), median OS and PFS after RT were significantly longer in patients with an AR compared to those without: 28 vs. 6.6 months (p < 0.01) and not reached vs. 3.2 months, respectively. No grade ≥2 toxicity was reported. Patients who developed an AR were more likely to be treated with immunotherapy (93.3% vs. 55.9%, p = 0.02). In multivariate analysis, they had a higher number of irradiated metastases treated concomitantly (HR = 16.9, p < 0.01) and a higher rate of mild infections during RT (HR = 403.5, p < 0.01). Conclusions: AR in metastatic melanoma seems to be highly prognostic of overall survival, although it is a rare phenomenon. It may be promoted by multiple concomitant treatments with RT and immunotherapy and by acute inflammatory events such as infection.

VMAT-Based Planning Allows Sparing of a Spatial Dose Pattern Associated with Radiation Pneumonitis in Patients Treated with Radiotherapy for a Locally Advanced Lung Cancer.

Introduction: In patients treated with radiotherapy for locally advanced lung cancer, respect for dose constraints to organs at risk (OAR) insufficiently protects patients from acute pulmonary toxicity (APT), such toxicities being associated with a potential impact on the treatment's completion and the patient's quality of life. Dosimetric planning does not take into account regional lung functionality. An APT prediction model combining usual dosimetry features with the mean dose (DMeanPmap) received by a voxel-based volume (Pmap) localized in the posterior right lung has been previously developed. A DMeanPmap of ≥30.3 Gy or a predicted APT probability (ProbAPT) of ≥8% were associated with a higher risk of APT. In the present study, the authors aim to demonstrate the possibility of decreasing the DMeanPmap via a volumetric arctherapy (VMAT)-based adapted planning and evaluate the impact on the risk of APT. Methods: Among the 207 patients included in the initial study, only patients who presented with APT of ≥grade 2 and with a probability of APT ≥ 8% based on the prediction model were included. Dosimetry planning was optimized with a new constraint (DMeanPmap < 30.3 Gy) added to the usual constraints. The initial and optimized treatment plans were compared using the t-test for the independent variables and the non-parametric Mann−Whitney U test otherwise, regarding both doses to the OARs and PTV (Planning Target Volume) coverage. Conformity and heterogeneity indexes were also compared. The risk of APT was recalculated using the new dosimetric features and the APT prediction model. Results: Dosimetric optimization was considered successful for 27 out of the 44 included patients (61.4%), meaning the dosimetric constraint on the Pmap region was achieved without compromising the PTV coverage (p = 0.61). The optimization significantly decreased the median DMeanPmap from 28.8 Gy (CI95% 24.2−33.4) to 22.1 Gy (CI95% 18.3−26.0). When recomputing the risk of APT using the new dosimetric features, the optimization significantly reduced the risk of APT (p < 0.0001) by reclassifying 43.2% (19/44) of the patients. Conclusion: Our approach appears to be both easily implementable on a daily basis and efficient at reducing the risk of APT. Regional radiosensitivity should be considered in usual lung dose constraints, opening the possibility of new treatment strategies, such as dose escalation or innovative treatment associations.

Multi-Omics Approaches for the Prediction of Clinical Endpoints after Immunotherapy in Non-Small Cell Lung Cancer: A Comprehensive Review.

Immune checkpoint inhibitors (ICI) have revolutionized the management of locally advanced and advanced non-small lung cancer (NSCLC). With an improvement in the overall survival (OS) as both first- and second-line treatments, ICIs, and especially programmed-death 1 (PD-1) and programmed-death ligands 1 (PD-L1), changed the landscape of thoracic oncology. The PD-L1 level of expression is commonly accepted as the most used biomarker, with both prognostic and predictive values. However, even in a low expression level of PD-L1, response rates remain significant while a significant number of patients will experience hyperprogression or adverse events. The dentification of such subtypes is thus of paramount importance. While several studies focused mainly on the prediction of the PD-L1 expression status, others aimed directly at the development of prediction/prognostic models. The response to ICIs depends on a complex physiopathological cascade, intricating multiple mechanisms from the molecular to the macroscopic level. With the high-throughput extraction of features, omics approaches aim for the most comprehensive assessment of each patient. In this article, we will review the place of the different biomarkers (clinical, biological, genomics, transcriptomics, proteomics and radiomics), their clinical implementation and discuss the most recent trends projecting on the future steps in prediction modeling in NSCLC patients treated with ICI.