Relative Bioavailability Study of Midazolam Intramuscularly Administered with the Needle-Free Auto-Injector ZENEO® in Healthy Adults.

INTRODUCTION: Intramuscular (IM) midazolam is indicated for the treatment of status epilepticus. Administration must be efficient to rapidly terminate prolonged seizures and prevent complications. The objective of this study was to compare, in terms of relative bioavailability and bioequivalence, IM midazolam injection by needle-free auto-injector, in different settings, to IM midazolam injection by a conventional syringe and needle. METHODS: In this open-label, randomized, four-period crossover study, healthy adults received single doses of midazolam (10 mg) under fasting conditions. The reference treatment (conventional syringe) was administered once, on bare skin in the thigh. The tested treatment (the needle-free auto-injector ZENEO®) was administered three times: on bare skin in the thigh, on bare skin in the ventrogluteal area, and through clothing in the thigh. Repeated plasma samples were collected to obtain 36-h pharmacokinetic (PK) profiles. Primary PK parameters were area under the plasma concentration-time curve, from time zero to the last measurable time point (AUC0-t) and from time zero to infinity (AUC0-∞), and the maximum observed plasma concentration (Cmax). RESULTS: Forty adults were enrolled and included in the PK analysis set. In all comparisons, the 90% confidence interval (CI) of the least-squares geometric mean ratios for AUC0-t and AUC0-∞ were within the bioequivalence range of 80-125%, with low intra-individual coefficients of variation (< 20.5% for all parameters in all comparisons). Bioequivalence was also met for Cmax in all comparisons except when comparing the tested treatment through clothing versus the reference treatment, where the 90% CI lower limit was slightly outside the bioequivalence range (78.8%). With all tested treatments Cmax was slightly lower, but early mean plasma concentrations (first 10 min post-dosing) were higher when compared to the reference treatment. In general, all treatments were well tolerated, with maximum sedation 0.5-1 h post-injection. DISCUSSION/CONCLUSION: This study establishes that IM midazolam injection on bare skin in the thigh with the ZENEO® is bioequivalent to IM midazolam injection with a syringe and needle. An acceptable relative bioavailability, compatible with emergency practice, was also shown in multiple settings. Higher mean concentrations within the first 10 min with the ZENEO® device, and quicker two-step injection suggest a faster onset of action, and thereby an earlier seizure termination, thus preventing the occurrence of prolonged seizure and neurological complications. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov identifier: NCT05026567. Registration first posted August 30, 2021, first patient enrolled May 9, 2022.

Seizures require urgent treatment when they last longer than 5 min. Indeed, when prolonged, seizures can lead to damage to the brain, coma, and ultimately death. Midazolam injected in the muscle (i.e., intramuscular (IM) injection) has become the first-line treatment of choice for long-lasting seizures and is usually administered with a syringe and 30-mm needle. The ZENEO^® needle-free auto-injector is an innovative, pre-filled, single-dose, disposable, ready-to-use, two-step device that could become an alternative method for midazolam IM administration. This study therefore compared midazolam IM injections with the ZENEO^® auto-injector versus IM injections with a conventional syringe and needle. The ZENEO^® auto-injector was tested in different conditions (on bare skin, through clothing, in the thigh, and in the hip) in healthy volunteers. The study showed, with a pharmacokinetic analysis (how much and how fast a drug is taken in the bloodstream), that midazolam absorption was similar in all tested conditions, indicating that the ZENEO^® auto-injector is a suitable method for midazolam administration. In addition, the study showed that in the first 10 min of the injection, the amount of midazolam in the blood seemed to be higher when injections were performed with the ZENEO^® auto-injector, suggesting that seizure treatment may start working sooner if injected with the device. This is particularly important and relevant in emergency situations and prehospital settings in order to prevent long-lasting seizures and irreversible damage to the brain (which can occur when a crisis lasts for 30 min) and ultimately improve the patient's outcome.

Deformable image registration with deep network priors: a study on longitudinal PET images.

Objective.This paper proposes a novel approach for the longitudinal registration of PET imaging acquired for the monitoring of patients with metastatic breast cancer. Unlike with other image analysis tasks, the use of deep learning (DL) has not significantly improved the performance of image registration. With this work, we propose a new registration approach to bridge the performance gap between conventional and DL-based methods: medical image registration method regularized by architecture (MIRRBA).Approach.MIRRBAis a subject-specific deformable registration method which relies on a deep pyramidal architecture to parametrize the deformation field. Diverging from the usual deep-learning paradigms,MIRRBAdoes not require a learning database, but only a pair of images to be registered that is used to optimize the network's parameters. We appliedMIRRBAon a private dataset of 110 whole-body PET images of patients with metastatic breast cancer. We used different architecture configurations to produce the deformation field and studied the results obtained. We also compared our method to several standard registration approaches: two conventional iterative registration methods (ANTs and Elastix) and two supervised DL-based models (LapIRN and Voxelmorph). Registration accuracy was evaluated using the Dice score, the target registration error, the average Hausdorff distance and the detection rate, while the realism of the registration obtained was evaluated using Jacobian's determinant. The ability of the different methods to shrink disappearing lesions was also computed with the disappearing rate.Main results.MIRRBA significantly improved all metrics when compared to DL-based approaches. The organ and lesion Dice scores of Voxelmorph improved by 6% and 52% respectively, while the ones of LapIRN increased by 5% and 65%. Regarding conventional approaches, MIRRBA presented comparable results showing the feasibility of our method.Significance.In this paper, we also demonstrate the regularizing power of deep architectures and present new elements to understand the role of the architecture in DL methods used for registration.

Automatic Segmentation of Metastatic Breast Cancer Lesions on 18F-FDG PET/CT Longitudinal Acquisitions for Treatment Response Assessment.

Metastatic breast cancer patients receive lifelong medication and are regularly monitored for disease progression. The aim of this work was to (1) propose networks to segment breast cancer metastatic lesions on longitudinal whole-body PET/CT and (2) extract imaging biomarkers from the segmentations and evaluate their potential to determine treatment response. Baseline and follow-up PET/CT images of 60 patients from the EPICUREseinmeta study were used to train two deep-learning models to segment breast cancer metastatic lesions: One for baseline images and one for follow-up images. From the automatic segmentations, four imaging biomarkers were computed and evaluated: SULpeak, Total Lesion Glycolysis (TLG), PET Bone Index (PBI) and PET Liver Index (PLI). The first network obtained a mean Dice score of 0.66 on baseline acquisitions. The second network obtained a mean Dice score of 0.58 on follow-up acquisitions. SULpeak, with a 32% decrease between baseline and follow-up, was the biomarker best able to assess patients' response (sensitivity 87%, specificity 87%), followed by TLG (43% decrease, sensitivity 73%, specificity 81%) and PBI (8% decrease, sensitivity 69%, specificity 69%). Our networks constitute promising tools for the automatic segmentation of lesions in patients with metastatic breast cancer allowing treatment response assessment with several biomarkers.