Clinical workflow for personalized foot pressure ulcer prevention.

Foot pressure ulcers are a common complication of diabetes because of patient's lack of sensitivity due to neuropathy. Deep pressure ulcers appear internally when pressures applied on the foot create high internal strains nearby bony structures. Monitoring tissue strains in persons with diabetes is therefore important for an efficient prevention. We propose to use personalized biomechanical foot models to assess strains within the foot and to determine the risk of ulcer formation. Our workflow generates a foot model adapted to a patient's morphology by deforming an atlas model to conform it to the contours of segmented medical images of the patient's foot. Our biomechanical model is composed of rigid bodies for the bones, joined by ligaments and muscles, and a finite element mesh representing the soft tissues. Using our registration algorithm to conform three datasets, three new patient models were created. After applying a pressure load below these foot models, the Von Mises equivalent strains and "cluster volumes" (i.e. volumes of contiguous elements with strains above a given threshold) were measured within eight functionally meaningful foot regions. The results show the variability of both location and strain values among the three considered patients. This study also confirms that the anatomy of the foot has an influence on the risk of pressure ulcer.

Influence of the calcaneus shape on the risk of posterior heel ulcer using 3D patient-specific biomechanical modeling.

Most posterior heel ulcers are the consequence of inactivity and prolonged time lying down on the back. They appear when pressures applied on the heel create high internal strains and the soft tissues are compressed by the calcaneus. It is therefore important to monitor those strains to prevent heel pressure ulcers. Using a biomechanical lower leg model, we propose to estimate the influence of the patient-specific calcaneus shape on the strains within the foot and to determine if the risk of pressure ulceration is related to the variability of this shape. The biomechanical model is discretized using a 3D Finite Element mesh representing the soft tissues, separated into four domains implementing Neo Hookean materials with different elasticities: skin, fat, Achilles' tendon, and muscles. Bones are modelled as rigid bodies attached to the tissues. Simulations show that the shape of the calcaneus has an influence on the formation of pressure ulcers with a mean variation of the maximum strain over 6.0 percentage points over 18 distinct morphologies. Furthermore, the models confirm the influence of the cushion on which the leg is resting: a softer cushion leading to lower strains, it has less chances of creating a pressure ulcer. The methodology used for patient-specific strain estimation could be used for the prevention of heel ulcer when coupled with a pressure sensor.

Framework for a low-cost intra-operative image-guided neuronavigator including brain shift compensation.

In this paper we present a methodology to address the problem of brain tissue deformation referred to as 'brain-shift'. This deformation occurs throughout a neurosurgery intervention and strongly alters the accuracy of the neuronavigation systems used to date in clinical routine which rely solely on pre-operative patient imaging to locate the surgical target, such as a tumour or a functional area. After a general description of the framework of our intra-operative image-guided system, we describe a procedure to generate patient specific finite element meshes of the brain and propose a biomechanical model which can take into account tissue deformations and surgical procedures that modify the brain structure, like tumour or tissue resection.