Aging is a multifaceted and intricate physiological process characterized by a gradual decline in functional capacity, leading to increased susceptibility to diseases and mortality. While chronological age serves as a strong risk factor for age-related health conditions, considerable heterogeneity exists in the aging trajectories of individuals, suggesting that biological age may provide a more nuanced understanding of the aging process. However, the concept of biological age lacks a clear operationalization, leading to the development of various biological age predictors without a solid statistical foundation. This paper addresses these limitations by proposing a comprehensive operationalization of biological age, introducing the “AccelerAge” framework for predicting biological age, and introducing previously underutilized evaluation measures for assessing the performance of biological age predictors. The AccelerAge framework, based on Accelerated Failure Time (AFT) models, directly models the effect of candidate predictors of aging on an individual’s survival time, aligning with the prevalent metaphor of aging as a clock. We compare predictors based on the AccelerAge framework to a predictor based on the GrimAge predictor, which is considered one of the best-performing biological age predictors, using simulated data as well as data from the UK Biobank and the Leiden Longevity Study. Our approach seeks to establish a robust statistical foundation for biological age clocks, enabling a more accurate and interpretable assessment of an individual’s aging status.

Mechanical stress influences scarring of a surgical wound. Several lines have been proposed for the best excision direction. It is unknown if these lines still apply when the body posture changes. The objective is to measure the skin reaction force in four directions and determine the direction of least force. Secondary objective is to determine if the reaction force varies in a different body posture. Skin reaction force was measured with the compressiometer in 30 participants on four different locations (forearm/upper arm/shoulder blade/lower back) in four directions (0°–45°–90°–135°) and two body postures. The direction of least skin reaction force changed with a different body posture and was significant for the forearm (p < 0.01) and shoulder blade (p = 0.05) The skin reaction force in all four direction changed significantly in a different body posture, except the 45° line in the upper arm and shoulder blade. Our results demonstrate that the skin reaction force in four directions in four locations varies with change in body posture. Focus should therefore not only lay on choosing the right direction, but also on managing skin tension postoperatively.

Purpose: To assess errors associated with EPI-accelerated intracardiac 4D flow MRI (4DEPI) with EPI factor 5, compared with non-EPI gradient echo (4DGRE). Methods: Three 3T MRI experiments were performed comparing 4DEPI to 4DGRE: steady flow through straight tubes, pulsatile flow in a left-ventricle phantom, and intracardiac flow in 10 healthy volunteers. For each experiment, 4DEPI was repeated with readout and blip phase-encoding gradient in different orientations, parallel or perpendicular to the flow direction. In vitro flow rates were compared with timed volumetric collection. In the left-ventricle phantom and in vivo, voxel-based speed and spatio-temporal median speed were compared between sequences, as well as mitral and aortic transvalvular net forward volume. Results: In steady-flow phantoms, the flow rate error was largest (12%) for high velocity (>2 m/s) with 4DEPI readout gradient parallel to the flow. Voxel-based speed and median speed in the left-ventricle phantom were ≤5.5% different between sequences. In vivo, mean net forward volume inconsistency was largest (6.4 ± 8.5%) for 4DEPI with nonblip phase-encoding gradient parallel to the main flow. The difference in median speed for 4DEPI versus 4DGRE was largest (9%) when the 4DEPI readout gradient was parallel to the flow. Conclusions: Velocity and flow rate are inaccurate for 4DEPI with EPI factor 5 when flow is parallel to the readout or blip phase-encoding gradient. However, mean differences in flow rate, voxel-based speed, and spatio-temporal median speed were acceptable (≤10%) when comparing 4DEPI to 4DGRE for intracardiac flow in healthy volunteers.