Baseline [18F]FDG PET features are associated with survival and toxicity in patients treated with CAR T cells for large B cell lymphoma.

PURPOSE: Chimeric antigen receptor (CAR) T cells have established themselves as an effective treatment for refractory or relapsed large B cell lymphoma (LBCL). Recently, the sDmax, which corresponds to the distance separating the two farthest lesions standardized by the patient's body surface area, has appeared as a prognostic factor in LBCL. This study aimed to identify [18F]FDG-PET biomarkers associated with prognosis and predictive of adverse events in patients treated with CAR T cells. METHODS: Patients were retrospectively included from two different university hospitals. They were being treated with CAR T cells for LBCL and underwent [18F]FDG-PET just before CAR T cell infusion. Lesions were segmented semi-automatically with a threshold of 41% of the maximal uptake. In addition to clinico-biological features, sDmax, total metabolic tumor volume (TMTV), SUVmax, and uptake intensity of healthy lymphoid organs and liver were collected. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method. The occurrence of adverse events, such as cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), was reported. RESULTS: Fifty-six patients were included. The median follow-up was 9.7 months. Multivariate analysis showed that TMTV (cut-off of 36 mL) was an independent prognostic factor for PFS (p < 0.001) and that sDmax (cut-off of 0.15 m-1) was an independent prognostic factor for OS (p = 0.008). Concerning the occurrence of adverse events, a C-reactive protein level > 35 mg/L (p = 0.006) and a liver SUVmean > 2.5 (p = 0.027) before CAR T cells were associated with grade 2 to 4 CRS and a spleen SUVmean > 1.9 with grade 2 to 4 ICANS. CONCLUSION: TMTV and sDmax had independent prognostic values, respectively, on PFS and OS. Regarding adverse events, the mean liver and spleen uptakes were associated with the occurrence of grade 2 to 4 CRS and ICANS, respectively. Integrating these biomarkers into the clinical workflow could be useful for early adaptation of patients management.

Head and neck cancers volume reduction: should we reduce our prophylactic node radiation to spare the antitumor immune response?

Radiotherapy for locally advanced head and neck cancer classically include large prophylactic node volume. However, the use of these large volumes can be responsible for significant toxicity. Furthermore, the disappointing results of radioimmunotherapy combinations in head and neck tumors raise concerns about radiotherapy's potential negative impact on the immune response when large lymph node volumes are treated. Besides, in other tumor locations, such as lung cancers, the volumes of elective irradiation have been considerably reduced, with the same local control as before. This opinion piece reviews the current state of radiation volumes in head and neck cancers, the rationale for these volumes, the potential impact of radiotherapy on immune response, and the volume changes that would improve the efficacy of radioimmunotherapy combinations.

Voxel-based identification of local recurrence sub-regions from pre-treatment PET/CT for locally advanced head and neck cancers.

BACKGROUND: Overall, 40% of patients with a locally advanced head and neck cancer (LAHNC) treated by chemoradiotherapy (CRT) present local recurrence within 2 years after the treatment. The aims of this study were to characterize voxel-wise the sub-regions where tumor recurrence appear and to predict their location from pre-treatment 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) images. MATERIALS AND METHODS: Twenty-six patients with local failure after treatment were included in this study. Local recurrence volume was identified by co-registering pre-treatment and recurrent PET/CT images using a customized rigid registration algorithm. A large set of voxel-wise features were extracted from pre-treatment PET to train a random forest model allowing to predict local recurrence at the voxel level. RESULTS: Out of 26 expert-assessed registrations, 15 provided enough accuracy to identify recurrence volumes and were included for further analysis. Recurrence volume represented on average 23% of the initial tumor volume. The MTV with a threshold of 50% of SUVmax plus a 3D margin of 10 mm covered on average 89.8% of the recurrence and 96.9% of the initial tumor. SUV and MTV alone were not sufficient to identify the area of recurrence. Using a random forest model, 15 parameters, combining radiomics and spatial location, were identified, allowing to predict the recurrence sub-regions with a median area under the receiver operating curve of 0.71 (range 0.14-0.91). CONCLUSION: As opposed to regional comparisons which do not bring enough evidence for accurate prediction of recurrence volume, a voxel-wise analysis of FDG-uptake features suggested a potential to predict recurrence with enough accuracy to consider tailoring CRT by dose escalation within likely radioresistant regions.