Personalised 3D knee compliance from clinically viable knee laxity measurements: A proof of concept ex vivo experiment.

Personalised information of knee mechanics is increasingly used for guiding knee reconstruction surgery. We explored use of uniaxial knee laxity tests mimicking Lachman and Pivot-shift tests for quantifying 3D knee compliance in healthy and injured knees. Two healthy knee specimens (males, 60 and 88 years of age) were tested. Six-degree-of-freedom tibiofemoral displacements were applied to each specimen at 5 intermediate angles between 0° and 90° knee flexion. The force response was recorded. Six-degree-of-freedom and uniaxial tests were repeated after sequential resection of the anterior cruciate, posterior cruciate and lateral collateral ligament. 3D knee compliance (C6DOF) was calculated using the six-degrees-of-freedom measurements for both the healthy and ligament-deficient knees and validated using a leave-one-out cross-validation. 3D knee compliance (CCT) was also calculated using uniaxial measurements for Lachman and Pivot-shift tests both conjointly and separately. C6DOF and CCT matrices were compared component-by-component and using principal axes decomposition. Bland-Altman plots, median and 40-60th percentile range were used as measurements of bias and dispersion. The error on tibiofemoral displacements predicted using C6DOF was < 9.6% for every loading direction and after release of each ligament. Overall, there was good agreement between C6DOF and CCT components for both the component-by-component and principal component comparison. The dispersion of principal components (compliance coefficients, positions and pitches) based on both uniaxial tests was lower than that based on single uniaxial tests. Uniaxial tests may provide personalised information of 3D knee compliance

Wearable sensors can reliably quantify gait alterations associated with disability in people with progressive multiple sclerosis in a clinical setting

Gait disability in people with progressive multiple sclerosis (MS) is difficult to quantify using existing clinical tools. This study aims to identify reliable and objective gait-based biomarkers to monitor progressive multiple sclerosis (MS) in clinical settings. During routine clinical visits, 57 people with secondary progressive MS and 24 healthy controls walked for 6 minutes wearing three inertial motion sensors. Fifteen gait measures were computed from the sensor data and tested for between-session reliability, for differences between controls and people with moderate and severe MS disability, and for correlation with Expanded Disability Status Scale (EDSS) scores. The majority of gait measures showed good to excellent between-session reliability when assessed in a subgroup of 23 healthy controls and 25 people with MS. These measures showed that people with MS walked with significantly longer step and stride durations, reduced step and stride regularity, and experienced difficulties in controlling and maintaining a stable walk when compared to controls. These abnormalities significantly increased in people with a higher level of disability and correlated with their EDSS scores. Reliable and objective gait-based biomarkers using wearable sensors have been identified. These biomarkers may allow clinicians to quantify clinically relevant alterations in gait in people with progressive MS within the context of regular clinical visits

Is a wearable sensor-based characterisation of gait robust enough to overcome differences between measurement protocols? A multi-centric pragmatic study in patients with multiple sclerosis

Inertial measurement units (IMUs) allow accurate quantification of gait impairment of people with multiple sclerosis (pwMS). Nonetheless, it is not clear how IMU-based metrics might be influenced by pragmatic aspects associated with clinical translation of this approach, such as data collection settings and gait protocols. In this study, we hypothesised that these aspects do not significantly alter those characteristics of gait that are more related to quality and energetic efficiency and are quantifiable via acceleration related metrics, such as intensity, smoothness, stability, symmetry, and regularity. To test this hypothesis, we compared 33 IMU-based metrics extracted from data, retrospectively collected by two independent centres on two matched cohorts of pwMS. As a worst-case scenario, a walking test was performed in the two centres at a different speed along corridors of different lengths, using different IMU systems, which were also positioned differently. The results showed that the majority of the temporal metrics (9 out of 12) exhibited significant between-centre differences. Conversely, the between-centre differences in the gait quality metrics were small and comparable to those associated with a test-retest analysis under equivalent conditions. Therefore, the gait quality metrics are promising candidates for reliable multi-centric studies aiming at assessing rehabilitation interventions within a routine clinical context

A quality control check to ensure comparability of stereophotogrammetric data between session and systems

Optoelectronic stereophotogrammetric (SP) systems are widely used in human movement research for clinical diagnostics, interventional applications, and as a reference system for validating alternative technologies. Regardless of the application, SP systems exhibit different random and systematic errors depending on camera specifications, system setup and laboratory environment, which hinders comparing SP data between sessions and across different systems. While many methods have been proposed to quantify and report the errors of SP systems, they are rarely utilized due to their complexity and need for additional equipment. In response, an easy-to-use quality control (QC) check has been designed that can be completed immediately prior to a data collection. This QC check requires minimal training for the operator and no additional equipment. In addition, a custom graphical user interface ensures automatic processing of the errors in an easy-to-read format for immediate interpretation. On initial deployment in a multicentric study, the check (i) proved to be feasible to perform in a short timeframe with minimal burden to the operator, and (ii) quantified the level of random and systematic errors between sessions and systems, ensuring comparability of data in a variety of protocol setups, including repeated measures, longitudinal studies and multicentric studies

On the use of wearable sensors as mobility biomarkers in the marketing authorization of new drugs: a regulatory perspective

The loss of mobility is a common trait in multiple health conditions (e.g., Parkinson's disease) and is associated with reduced quality of life. In this context, being able to monitor mobility in the real world, is important. Until recently, the technology was not mature enough for this; but today, miniaturized sensors and novel algorithms promise to monitor mobility accurately and continuously in the real world, also in pathological populations. However, before any such methodology can be employed to support the development and testing of new drugs in clinical trials, they need to be qualified by the competent regulatory agencies (e.g., European Medicines Agency). Nonetheless, to date, only very narrow scoped requests for regulatory qualification were successful. In this work, the Mobilise-D Consortium shares its positive experience with the European regulator, summarizing the two requests for Qualification Advice for the Mobilise-D methodologies submitted in October 2019 and June 2020, as well as the feedback received, which resulted in two Letters of Support publicly available for consultation on the website of the European Medicines Agency. Leveraging on this experience, we hereby propose a refined qualification strategy for the use of digital mobility outcome (DMO) measures as monitoring biomarkers for mobility in drug trials

A double‐blind, randomized, placebo‐controlled trial of ursodeoxycholic acid (UDCA) in Parkinson's disease

Background Rescue of mitochondrial function is a promising neuroprotective strategy for Parkinson's disease (PD). Ursodeoxycholic acid (UDCA) has shown considerable promise as a mitochondrial rescue agent across a range of preclinical in vitro and in vivo models of PD. Objectives To investigate the safety and tolerability of high-dose UDCA in PD and determine midbrain target engagement. Methods The UP (UDCA in PD) study was a phase II, randomized, double-blind, placebo-controlled trial of UDCA (30 mg/kg daily, 2:1 randomization UDCA vs. placebo) in 30 participants with PD for 48 weeks. The primary outcome was safety and tolerability. Secondary outcomes included 31-phosphorus magnetic resonance spectroscopy (31P-MRS) to explore target engagement of UDCA in PD midbrain and assessment of motor progression, applying both the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS-III) and objective, motion sensor-based quantification of gait impairment. Results UDCA was safe and well tolerated, and only mild transient gastrointestinal adverse events were more frequent in the UDCA treatment group. Midbrain 31P-MRS demonstrated an increase in both Gibbs free energy and inorganic phosphate levels in the UDCA treatment group compared to placebo, reflecting improved ATP hydrolysis. Sensor-based gait analysis indicated a possible improvement of cadence (steps per minute) and other gait parameters in the UDCA group compared to placebo. In contrast, subjective assessment applying the MDS-UPDRS-III failed to detect a difference between treatment groups. Conclusions High-dose UDCA is safe and well tolerated in early PD. Larger trials are needed to further evaluate the disease-modifying effect of UDCA in PD

Mobilise-D Insights To Estimate Real-World Walking Speed in Multiple Conditions With a Wearable Device

This study aimed to validate a wearable device\u27s walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson\u27s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and - 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application.Trial registration: ISRCTN - 12246987

On the use of wearable sensors as mobility biomarkers in the marketing authorization of new drugs: a regulatory perspective

The loss of mobility is a common trait in multiple health conditions (e.g., Parkinson's disease) and is associated with reduced quality of life. In this context, being able to monitor mobility in the real world, is important. Until recently, the technology was not mature enough for this; but today, miniaturized sensors and novel algorithms promise to monitor mobility accurately and continuously in the real world, also in pathological populations. However, before any such methodology can be employed to support the development and testing of new drugs in clinical trials, they need to be qualified by the competent regulatory agencies (e.g., European Medicines Agency). Nonetheless, to date, only very narrow scoped requests for regulatory qualification were successful. In this work, the Mobilise-D Consortium shares its positive experience with the European regulator, summarizing the two requests for Qualification Advice for the Mobilise-D methodologies submitted in October 2019 and June 2020, as well as the feedback received, which resulted in two Letters of Support publicly available for consultation on the website of the European Medicines Agency. Leveraging on this experience, we hereby propose a refined qualification strategy for the use of digital mobility outcome (DMO) measures as monitoring biomarkers for mobility in drug trials