Senior Research Career Scientist

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PROJECT SUMMARY/ABSTRACT Dr. Ledoux’s current research program aims to reduce both functional and anatomical limb loss by: exploring the disease processes that lead to aberrant limb function; quantifying the effects of conservative and surgical treatment options; and developing novel, state-of-the-art technologies for studying the foot. His research focuses on two Veteran populations: those with musculoskeletal impairment at the foot and ankle, where pain and limitations in mobility are the key issues (i.e., functional limb loss); and those at risk of lower limb amputation due to diabetes, where loss of the foot is a major concern (i.e., anatomical limb loss). The overarching goals of his research include: (1) insight into the pathomechanics of: diabetic foot ulceration, ankle and great toe arthritis, and severe foot deformities; (2) quantitative comparison of different treatment options for foot pathologies that can lead to improved limb function or prevention of amputation; and (3) the development of novel research tools. Dr. Ledoux is working on several projects related to hallux rigidus, or arthritis of the first metatarsophalangeal joint (MTPJ1). Various designs for MTPJ1 arthroplasties have been proposed, but none have been particularly successful. Development of new implants aimed at addressing these problems has been limited by insufficient quantitative data on the MTPJ1 mechanical environment. Similarly, due to previous technological limitations, no precise 3D data are available on either the kinematics of this disease. CLiMB is engaged in novel research to identify the kinematic envelope of normal MTPJ1 function required during activities of daily living (RX0032590). We will build on our initial successes generating novel, evidence-based implant concepts that emphasize strong initial component fixation to improve MTPJ1 implant technology through computational modeling and robotic gait simulation of human cadavers (R01AR076475). These better-performing implants will ultimately lead to improved patient outcomes. It is our working hypothesis that a successful MTPJ1 implant will exhibit both strong initial component fixation and physiologically normative joint biomechanics. Additionally, Dr. Ledoux is collaborating with Dr. Sangeorzan on a multisite hallux rigidus study comparing motion sparing procedures (joint replacement or bone shaping) to arthrodesis (fusion). This study will determine factors associated with treatment success. Developing improved treatment options requires a better fundamental understanding of diabetic disease pathomechanics. Despite growing agreement that aberrant pressures and shear stresses are linked to ulceration, the specific causative mechanism of ulceration remains poorly understood. From a structural perspective—in which tissues of different material properties and different geometries interact to create a bulk response—most studies have been 2D and limited in the number of locations considered. Given the complex structure and functional motion of the foot, it should be investigated in 3D across the entire plantar surface. However, many techniques that afford volumetric inquiry have other concerns: dissection is disruptive, finite element models rely on assumptions and simplifications, CT has poor soft tissue resolution, and MRI is computationally and fiscally expensive. Ultrasound has good soft tissue resolution, but most commercial systems create planar images or are limited to small, angularly swept volumes. Ultrasound can also be difficult to read for the naïve user. In order to overcome these barriers, we propose these specific aims: 1) Develop a mechanical system and the necessary software to generate a 3D scan of the entire plantar soft tissue, using B-mode ultrasound for structural information and shear wave elastography for tissue properties. 2) Collect plantar soft tissue scans for 7 diabetic non-neuropathic subjects and 7 non-diabetic subjects. 3) Analyze these scans using segmentation and strain information calculated with digital volume correlation as well as an interpretable classification neural network. The successful completion of this NIH funded pilot study (5U24DK115255-04, subaward 32307-94) will demonstrate the utility of the proposed methods and support a larger grant application.