Chimpanzees are knuckle walkers, with forelimbs contacting the ground by the dorsum of the finger's middle phalanges. As these muscular apes are given to high-velocity motions, the question arises of how the ground reaction forces are buffered so that no damage ensues in the load-bearing fingers. In the literature, it was hypothesized that the finger flexors help buffer impacts because in knuckle stance the metacarpophalangeal joints (MCPJs) are strongly hyperextended, which would elongate the finger flexors. This stretching of the finger flexor muscle-tendon units would absorb impact energy. However, EMG studies did not report significant finger flexor activity in knuckle walking. Although these data by themselves question the finger flexor impact buffering hypothesis, the present study aimed to critically investigate the hypothesis from a biomechanical point of view. Therefore, various aspects of knuckle walking were modeled and the finger flexor tendon displacements in the load-bearing fingers were measured in a chimpanzee cadaver hand, of which also an MRI was taken in knuckle stance. The biomechanics do not support the finger flexor impact buffering hypothesis. In knuckle walking, the finger flexors are not elongated to lengths where passive strain forces would become important. Impact buffering by large flexion moments at the MCPJs from active finger flexors would result in impacts at the knuckles themselves, which is dysfunctional for various biomechanical reasons and does not occur in real knuckle walking. In conclusion, the current biomechanical analysis in accumulation of previous EMG findings suggests that finger flexors play no role in impact buffering in knuckle walking.

Purpose: Diffusion kurtosis imaging (DKI) is an advanced magnetic resonance imaging modality that is known to be sensitive to changes in the underlying microstructure of the brain. Image voxels in diffusion weighted images, however, are typically relatively large making them susceptible to partial volume effects, especially when part of the voxel contains cerebrospinal fluid. In this work, we introduce the “Diffusion Kurtosis Imaging with Free Water Elimination” (DKI-FWE) model that separates the signal contributions of free water and tissue, where the latter is modeled using DKI. Theory and Methods: A theoretical study of the DKI-FWE model, including an optimal experiment design and an evaluation of the relative goodness of fit, is carried out. To stabilize the ill-conditioned estimation process, a Bayesian approach with a shrinkage prior (BSP) is proposed. In subsequent steps, the DKI-FWE model and the BSP estimation approach are evaluated in terms of estimation error, both in simulation and real data experiments. Results: Although it is shown that the DKI-FWE model parameter estimation problem is ill-conditioned, DKI-FWE was found to describe the data significantly better compared to the standard DKI model for a large range of free water fractions. The acquisition protocol was optimized in terms of the maximally attainable precision of the DKI-FWE model parameters. The BSP estimator is shown to provide reliable DKI-FWE model parameter estimates. Conclusion: The combination of the DKI-FWE model with BSP is shown to be a feasible approach to estimate DKI parameters, while simultaneously eliminating free water partial volume effects.