The PostStroke-Manager - combining mobile, digital and sensor-based technology with personal assistance: protocol of the feasibility study

INTRODUCTION

Post stroke management has moved into the focus as it represents the only way to secure acute treatment effects in the long term. Due to individual courses, post stroke management appears rather challenging and is hindered by existing barriers between treatment sectors. As a novel concept, the PostStroke-Manager combines digital and sensor-based technology with personal assistance to enable intersectoral cooperation, best possible reduction of stroke-related disability, optimal secondary prevention, and detection of physical and psychological comorbidities.

METHODS

This prospective single-center observational study aims to investigate the feasibility of the PostStroke-Manager concept in an outpatient setting. Ninety patients who have suffered an ischemic or hemorrhagic stroke or transient ischemic attack will be equipped with a tablet and mobile devices recording physical activity, blood pressure, and electrocardiographic signals. Through a server-based platform, patients will be connected with the primary care physician, a stroke pilot and, if necessary, other specialists who will use web-based platforms. Via the tablet, patients will have access to an application with 10 newly designed components including, for instance, a communication tool, medication schedule, medical records platform, and psychometric screenings (e.g., depression, anxiety symptoms, quality of life, adherence, cognitive impairment). During the 1-year follow-up period, clinical visits are scheduled at three-month intervals. In the interim, communication will be secured by an appropriate tool that includes text messenger, audio, and video telephony. As the primary endpoint, feasibility will be measured by a 14-item questionnaire that addresses digital components, technical support, and personal assistance. The PostStroke-Manager will be judged feasible if at least 50% of these aspects are rated positively by at least 75% of patients. Secondary endpoints include feedback from professionals and longitudinal analyses on clinical and psychometric parameters.

PERSPECTIVE

This study will answer the question of whether combined digital and personal support is a feasible approach to post stroke management. Furthermore, the patient perspective gained regarding digital support may help to specify future applications. This study will also provide information regarding the potential use of remote therapies and mobile devices in situations with limited face-to-face contacts.

TRIAL REGISTRATION

German Register for Clinical Trials ( DRKS00023213 .), registered 27 April 2021.

An Automatic Method for the Segmentation and Classification of Imminent Labor Contraction From Electrohysterograms

OBJECTIVE

Preterm birth is the first cause of perinatal morbidity and mortality. Despite continuous clinical routine improvements, the preterm rate remains steady. Moreover, the specificity of the early diagnosis stays poor as many hospitalized women for preterm delivery threat finally deliver at term. In this context, the use of electrohysterograms may increase the sensitivity and the specificity of early diagnosis of preterm labor.

METHODS

This paper proposes a clinical application of electrohysterogram processing for the classification of patients as prone to deliver within a week or later. The approach relies on non-linear correlation analysis for the contraction bursts extraction and uses computation of various features combined with the use of Gaussian mixture models for their classification. The method is tested on a new dataset of 68 records collected on women hospitalized for preterm delivery threat.

RESULTS

This paper presents promising results for the automatic segmentation of the contraction and a classification sensitivity, specificity, and accuracy of, respectively, 80.7%, 76.3%, and 76.2%.

CONCLUSION

These results are in accordance with the gold standards but have the advantage to be non-invasive and could be performed at home.

SIGNIFICANCE

Diagnosis of imminent labor is possible by electrohysterography recording and may help in avoiding over-medication and in providing better cares to at-risk pregnant women.

Realtime Tracking of the Photobleaching Trajectory During Photodynamic Therapy

OBJECTIVE

Photodynamic therapy (PDT) is an alternative treatment for cancer, which involves the administration of a photosensitizing agent that is activated by light at a specific wavelength. This illumination causes after a sequence of photoreactions, the production of reactive oxygen species responsible for the death of the tumor cells but also the degradation of the photosensitizing agent, which then loose the fluorescence properties. The phenomenon is commonly known as the photobleaching process and can be considered as a therapy efficiency indicator.

METHODS

This paper presents the design and validation of a real-time controller able to track a preset photobleaching trajectory by modulating the light impulses width during the treatment sessions.

RESULTS

This innovative solution was validated by in vivo experiments that have shown a significantly improvement of reproducibility of the interindividual photobleaching kinetic.

CONCLUSION

We believe that this approach could lead to personalized PDT modalities.

SIGNIFICANCE

This work may open new perspectives in the control and optimization of photodynamic treatments.

A new algorithm for a better characterization and timing of the anti-VEGF vascular effect named "normalization"

Antiangiogenics are widely used in cancer treatment in combination with chemotherapy and radiotherapy for their vascular effects. Antiangiogenics are supposed to induce morphological and functional changes in the chaotic tumor vasculature that would help enhance the therapeutic efficacy of chemotherapy and radiotherapy through the amelioration of the drug delivery or the oxygenation in the tumor, respectively. However, finding the best treatment sequence is not an easy task to achieve and no consensus has yet been established because of the lack of knowledge regarding when and for how long the vascular network is ameliorated. The aim of this work was to develop a dedicated image processing algorithm able to analyze the vascular structures on optical microscopy images of the vascular network and to follow its fine modifications in vivo, over time. We applied this algorithm to follow the evolution of the vascular parameters (vascularized tissue surface, branches, sprouts and length), in response or not to anti-VEGF therapy (10 mg/kg/day) and determine precisely whether there is really a vascular "normalization" with anti-VEGF therapy in comparison with the parameters extracted from healthy vascular networks. We found that for this determination, the choice of region of interest to analyze is critical as it is important to compare only microcirculation areas and avoid areas with arteriole-venule-capillary hierarchy. The algorithm analysis allowed us to define a vascular "normalization" in treated tumors, between 8 and 12 days of bevacizumab treatment that was confirmed by standard immunohistochemical analysis, microvascular permeability assessment and immunohistological blood perfusion assessment.

Comparison of three light doses in the photodynamic treatment of actinic keratosis using mathematical modeling

Photodynamic therapy (PDT) is an emerging treatment modality for various diseases, especially for cancer therapy. Although high efficacy is demonstrated for PDT using standardized protocols in nonhyperkeratotic actinic keratoses, alternative light doses expected to increase efficiency, to reduce adverse effects or to expand the use of PDT, are still being evaluated and refined. We propose a comparison of the three most common light doses in the treatment of actinic keratosis with 5-aminolevulinic acid PDT through mathematical modeling. The proposed model is based on an iterative procedure that involves determination of the local fluence rate, updating of the local optical properties, and estimation of the local damage induced by the therapy. This model was applied on a simplified skin sample model including an actinic keratosis lesion, with three different light doses (red light dose, 37 J∕cm2, 75 mW∕cm2, 500 s; blue light dose, 10 J∕cm2, 10 mW∕cm2, 1000 s; and daylight dose, 9000 s). Results analysis shows that the three studied light doses, although all efficient, lead to variable local damage. Defining reference damage enables the nonoptimal parameters for the current light doses to be refined and the treatment to be more suitable.

A Model-Based Pharmacokinetics Characterization Method of Engineered Nanoparticles for Pilot Studies

Recent developments on engineered multifunctional nanomaterials have opened new perspectives in oncology. But assessment of both quality and safety in nanomedicine requires new methods for their biological characterization. This paper proposes a new model-based approach for the pre-characterization of multifunctional nanomaterials pharmacokinetics in small scale in vivo studies. Two multifunctional nanoparticules, with and without active targeting, designed for photodynamic therapy guided by magnetic resonance imaging are used to exemplify the presented method. It allows to the experimenter to rapidly test and select the most relevant PK model structure planned to be used in the subsequent explanatory studies. We also show that the model parameters estimated from the in vivo responses provide relevant preliminary information about the tumor uptake, the elimination rate and the residual storage. For some parameters, the accuracy of the estimates is accurate enough to compare and draw significant pre-conclusions. A third advantage of this approach is the possibility to optimally refine the in vivo protocol for the subsequent explanatory and confirmatory studies complying with the 3Rs (reduction, refinement, replacement) ethical recommendations. More precisely, we show that the identified model may be used to select the appropriate duration of the MR imaging sessions planned for the subsequent studies. The proposed methodology integrates MRI image processing, continuous-time system identification algorithms and statistical analysis. Except, the choice of the model parameters to be compared and interpreted, most of the processing procedure may be automated to speed up the PK characterization process at an early stage of experimentation.