Tracking Usage Patterns of a Mobile Application for Dementia Risk Assessment in Elderly Individuals.

Among elderly individuals, dementia stands as a prominent contributor to disability. However, multidomain lifestyle interventions have emerged as a promising approach for enhancing cognition. Taking a progressive step, integrating digital elements such as a mobile intervention application for elderly participants becomes crucial. Hence, it's crucial to identify the usage patterns of intervention features. Our aim was to implement a usage tracking mechanism and analyze usage trends and feature preferences over the initial six months of a clinical trial across various clinical sites, comparing intervention and control groups. Our findings reveal the differences in usage between the groups and highlight the most used features.

Integrating AI-Generated Summaries of Medication Leaflets into a Mobile Application for Medication Management.

Effective medication management poses significant challenges, particularly when navigating multiple medications with intricate dosages and schedules. This paper presents a prototype mobile application to streamline information retrieval from dense medication leaflets. By utilizing automated information extraction based on large language models, the application seamlessly retrieves pertinent details from the Austrian medicinal product index upon scanning the medication package. This extracted information is organized and displayed within the app, ensuring clarity and accessibility for users. In addition to this core functionality, the application offers a suite of features tailored to facilitate effective medication management. By integrating comprehensive medication information with practical medication management tools, the application empowers users to navigate complex medication regimes with confidence and ease.

LETHE: A Digital Intervention for Cognitive Decline.

Dementia is the main cause of disability in elderly populations. It has been shown that the risk factors of dementia are a mixture of pathological, lifestyle and heritable factors, with some of those being provably modifiable. Early diagnosis of dementia and approaches to slow down its evolution are currently the most prominent management methodologies due to lack of a cure. For that reason, a plethora of home-based assistive technologies for dementia management do exist, with most of them focusing on the improvement of memory and thinking. The main objective of LETHE is prevention in the whole spectrum of cognitive decline in the elderly population at risk reaching from asymptomatic to subjective or mild cognitive impairment to prodromal Dementia. LETHE will provide a Big Data collection platform and analysis system, that will allow prevention, personalized risk detection and intervention on cognitive decline. Through the subsequent 2-year clinical trial, the LETHE system, as well as the respective knowledge gained will be evaluated and validated. The scope of the current paper is to introduce the LETHE study and its respective novel platform as a holistic approach to multidomain lifestyle intervention trial studies. The present work depicts the architectural perspective and extends beyond state-of-the-art guidelines and approaches to health management systems and cloud platform development.Clinical Relevance - Patient Management Systems as well as lifestyle management platforms have significant clinical relevance as they allow for remote and continuous monitoring of patients' health status. LETHE aims to improve patient outcomes by providing predictive models for cognitive decline and patient adherence to the multimodal lifestyle intervention, enabling prompt and appropriate medical decisions.

Joint multi-field T1 quantification for fast field-cycling MRI.

PURPOSE: Recent developments in hardware design enable the use of fast field-cycling (FFC) techniques in MRI to exploit the different relaxation rates at very low field strength, achieving novel contrast. The method opens new avenues for in vivo characterizations of pathologies but at the expense of longer acquisition times. To mitigate this, we propose a model-based reconstruction method that fully exploits the high information redundancy offered by FFC methods. METHODS: The proposed model-based approach uses joint spatial information from all fields by means of a Frobenius - total generalized variation regularization. The algorithm was tested on brain stroke images, both simulated and acquired from FFC patients scans using an FFC spin echo sequences. The results are compared to three non-linear least squares fits with progressively increasing complexity. RESULTS: The proposed method shows excellent abilities to remove noise while maintaining sharp image features with large signal-to-noise ratio gains at low-field images, clearly outperforming the reference approach. Especially patient data show huge improvements in visual appearance over all fields. CONCLUSION: The proposed reconstruction technique largely improves FFC image quality, further pushing this new technology toward clinical standards.

High-Field Detection of Biomarkers with Fast Field-Cycling MRI: The Example of Zinc Sensing.

Many smart magnetic resonance imaging (MRI) probes provide response to a biomarker based on modulation of their rotational correlation time. The magnitude of such MRI signal changes is highly dependent on the magnetic field and the response decreases dramatically at high fields (>2 T). To overcome the loss of efficiency of responsive probes at high field, with fast-field cycling magnetic resonance imaging (FFC-MRI) we exploit field-dependent information rather than the absolute difference in the relaxation rate measured in the absence and in the presence of the biomarker at a given imaging field. We report here the application of fast field-cycling techniques combined with the use of a molecular probe for the detection of Zn2+ to achieve 166 % MRI signal enhancement at 3 T, whereas the same agent provides no detectable response using conventional MRI. This approach can be generalized to any biomarker provided the detection is based on variation of the rotational motion of the probe.

R1 dispersion contrast at high field with fast field-cycling MRI.

Contrast agents with a strong R1 dispersion have been shown to be effective in generating target-specific contrast in MRI. The utilization of this R1 field dependence requires the adaptation of an MRI scanner for fast field-cycling (FFC). Here, we present the first implementation and validation of FFC-MRI at a clinical field strength of 3 T. A field-cycling range of ±100 mT around the nominal B0 field was realized by inserting an additional insert coil into an otherwise conventional MRI system. System validation was successfully performed with selected iron oxide magnetic nanoparticles and comparison to FFC-NMR relaxometry measurements. Furthermore, we show proof-of-principle R1 dispersion imaging and demonstrate the capability of generating R1 dispersion contrast at high field with suppressed background signal. With the presented ready-to-use hardware setup it is possible to investigate MRI contrast agents with a strong R1 dispersion at a field strength of 3 T.

A cryostatic, fast scanning, wideband NQR spectrometer for the VHF range.

In the search for a novel MRI contrast agent which relies on T1 shortening due to quadrupolar interaction between Bi nuclei and protons, a fast scanning wideband system for zero-field nuclear quadrupole resonance (NQR) spectroscopy is required. Established NQR probeheads with motor-driven tune/match stages are usually bulky and slow, which can be prohibitive if it comes to Bi compounds with low SNR (excessive averaging) and long quadrupolar T1 times. Moreover many experiments yield better results at low temperatures such as 77 K (liquid nitrogen, LN) thus requiring easy to use cryo-probeheads. In this paper we present electronically tuned wideband probeheads for bands in the frequency range 20-120 MHz which can be immersed in LN and which enable very fast explorative scans over the whole range. To this end we apply an interleaved subspectrum sampling strategy (ISS) which relies on the electronic tuning capability. The superiority of the new concept is demonstrated with an experimental scan of triphenylbismuth from 24 to 116 MHz, both at room temperature and in LN. Especially for the first transition which exhibits extremely long T1 times (64 ms) the and low signal the new approach allows an acceleration factor by more than 100 when compared to classical methods.