LASTIC: A Light Aspiration Device for in vivo Soft TIssue Characterization

In-vivo tongue stiffness measured by aspiration: Resting vs general anesthesia

Tongue cancer treatment often results in impaired speech, swallowing, or mastication. Simulating the effect of treatments can help the patient and the treating physician to understand the effects and impact of the intervention. To simulate deformations of the tongue, identifying accurate mechanical properties of tissue is essential. However, not many succeeded in characterizing in-vivo tongue stiffness. Those who did, measured the tongue At Rest (AR), in which muscle tone subsides even if muscles are not willingly activated. We expected to find an absolute rest state in participants 'under General Anesthesia' (GA). We elaborated on previous work by measuring the mechanical behavior of the in-vivo tongue under aspiration using an improved volume-based method. Using this technique, 5 to 7 measurements were performed on 10 participants both AR and under GA. The obtained Pressure-Shape curves were first analyzed using the initial slope and its variations. Hereafter, an inverse Finite Element Analysis (FEA) was applied to identify the mechanical parameters using the Yeoh, Gent, and Ogden hyperelastic models. The measurements AR provided a mean Young's Modulus of 1638 Pa (min 1035 - max 2019) using the Yeoh constitutive model, which is in line with previous ex-vivo measurements. However, while hoping to find a rest state under GA, the tongue unexpectedly appeared to be approximately 2 to 2.5 times stiffer under GA than AR. Explanations for this were sought by examining drugs administered during GA, blood flow, perfusion, and upper airway reflexes, but neither of these explanations could be confirmed.

Personalized modeling for real-time pressure ulcer prevention in sitting posture

Ischial pressure ulcer is an important risk for every paraplegic person and a major public health issue. Pressure ulcers appear following excessive compression of buttock's soft tissues by bony structures, and particularly in ischial and sacral bones. Current prevention techniques are mainly based on daily skin inspection to spot red patches or injuries. Nevertheless, most pressure ulcers occur internally and are difficult to detect early. Estimating internal strains within soft tissues could help to evaluate the risk of pressure ulcer. A subject-specific biomechanical model could be used to assess internal strains from measured skin surface pressures. However, a realistic 3D non-linear Finite Element buttock model, with different layers of tissue materials for skin, fat and muscles, requires somewhere between minutes and hours to compute, therefore forbidding its use in a real-time daily prevention context. In this article, we propose to optimize these computations by using a reduced order modeling technique (ROM) based on proper orthogonal decompositions of the pressure and strain fields coupled with a machine learning method. ROM allows strains to be evaluated inside the model interactively (i.e. in less than a second) for any pressure field measured below the buttocks. In our case, with only 19 modes of variation of pressure patterns, an error divergence of one percent is observed compared to the full scale simulation for evaluating the strain field. This reduced model could therefore be the first step towards interactive pressure ulcer prevention in a daily set-up.

Linear elastic properties of the facial soft tissues using an aspiration device: towards patient specific characterization

Biomechanical modeling of the facial soft tissue behavior is needed in aesthetic or maxillo-facial surgeries where the simulation of the bone displacements cannot accurately predict the visible outcome on the patient's face. Because these tissues have different nature and elastic properties across the face, depending on their thickness, and their content in fat or muscle, individualizing their mechanical parameters could increase the simulation accuracy. Using a specifically designed aspiration device, the facial soft tissues deformation is measured at four different locations (cheek, cheekbone, forehead, and lower lip) on 16 young subjects. The stiffness is estimated from the deformations generated by a set of negative pressures using an inverse analysis based on a Neo Hookean model. The initial Young's modulus of the cheek, cheekbone, forehead, and lower lip are respectively estimated to be 31.0 kPa±4.6, 34.9 kPa±6.6, 17.3 kPa±4.1, and 33.7 kPa±7.3. Significant intra-subject differences in tissue stiffness are highlighted by these estimations. They also show important inter-subject variability for some locations even when mean stiffness values show no statistical difference. This study stresses the importance of using a measurement device capable of evaluating the patient specific tissue stiffness during an intervention.