Bernard Lamien

Inverse problem in the hyperthermia therapy of cancer with laser heating and plasmonic nanoparticles

Abstract In this paper, laser-induced hyperthermia therapy of cancer is treated as a state estimation problem and solved with a particle filter method, namely the Auxiliary Sampling Importance Resampling algorithm. In state estimation problems, the available measured data are used together with prior knowledge about the physical phenomena, in order to sequentially produce estimates of the desired dynamic variables. Although the hyperthermia treatment of cancer has been addressed in the literature by different computational methods, these usually involved deterministic analyses. On the other hand, state space representation of the problem in a Bayesian framework allows for the analyses of uncertainties present in the mathematical formulation of the problem, as well as in the measured data of observable variables that might be eventually available. Two physical problems are considered in this paper, involving the irradiation with a laser in the near infrared range of a non-homogeneous cylindrical medium representing either a soft-tissue phantom or a skin model, both containing a tumour. The region representing the tumour is assumed to be loaded with nanoparticles in order to enhance the hyperthermia effects and to limit such effects to the tumour. The light propagation problem is coupled with the bioheat transfer equation in the present study. Simulated transient temperature measurements are used in the inverse analysis.

State estimation in bioheat transfer: a comparison of particle filter algorithms

Purpose n n n n nThe purpose of this paper is to focus on applications related to the hyperthermia treatment of cancer, with heating imposed either by a laser in the near-infrared range or by radiofrequency waves. The particle filter algorithms are compared in terms of computational time and solution accuracy. n n n n nDesign/methodology/approach n n n n nThe authors extend the analyses performed in their previous works to compare three different algorithms of the particle filter, as applied to the hyperthermia treatment of cancer. The particle filters examined here are the sampling importance resampling (SIR) algorithm, the auxiliary sampling importance resampling (ASIR) algorithm and Liu & West’s algorithm. n n n n nFindings n n n n nLiu & West’s algorithm resulted in the largest computational times. On the other hand, this filter was shown to be capable of dealing with very large uncertainties. In fact, besides the uncertainties in the model parameters, Gaussian noises, similar to those used for the SIR and ASIR filters, were added to the evolution models for the application of Liu & West’s filter. For the three filters, the estimated temperatures were in excellent agreement with the exact ones. n n n n nPractical implications n n n n nThis work may help medical doctors in the future to prescribe treatment protocols and also opens the possibility of devising control strategies for the hyperthermia treatment of cancer. n n n n nOriginality/value n n n n nThe natural solution to couple the uncertain results from numerical simulations with the measurements that contain uncertainties, aiming at the better prediction of the temperature field of the tissues inside the body, is to formulate the problem in terms of state estimation, as performed in this work.

Computational fluid dynamic analysis reveals the underlying physical forces playing a role in 3D multiplex brain organoid cultures

Organoid cultivation in suspension culture requires agitation at low shear stress to allow for nutrient diffusion, which preserves tissue structure. Multiplex systems for organoid cultivation have been proposed, but whether they meet similar shear stress parameters as the regularly used spinner flask and its correlation with the successful generation of brain organoids, has not been determined. Herein, we used computational fluid dynamics (CFD) analysis to compare two multiplex culture conditions: steering plates on an orbital shaker and the use of a previously described bioreactor. The bioreactor had low speed and high shear stress regions that may affect cell aggregate growth, depending on volume, whereas the CFD parameters of the steering plates were closest to the parameters of the spinning flask. Our protocol improves the initial steps of the standard brain organoid formation, and organoids produced therefrom displayed regionalized brain structures, including retinal pigmented cells. Overall, we conclude that suspension culture on orbital steering plates is a cost-effective practical alternative to previously described platforms for the cultivation of brain organoids for research and multiplex testing. Highlights Improvements to organoid preparation protocol Multiplex suspension culture protocol successfully generate brain organoids Computational fluid dynamics (CFD) reveals emerging properties of suspension cultures CFD of steering plates is equivalent to that of spinner flask cultures

Application of the photoacoustic technique for temperature measurements during hyperthermia

ABSTRACT Non-invasive monitoring of tissues’ temperatures is necessary for some diagnostic and therapeutic applications. Photoacoustic is a new hybrid biomedical imaging technique, combining the high-contrast of optical properties with the high spatial resolution of ultrasound. The estimation of model parameters that are temperature dependent was used in this work to indirectly measure the temperatures of tissues, as the solution of an inverse problem within the Bayesian framework of statistics. A two-dimensional case was examined, which is related to the hyperthermia treatment of cancer with laser heating in the near infrared range. Simulated measurements were used in the inverse analysis. The Markov Chain Monte Carlo method provided accurate estimation of the spatial distribution of the Gruneisen parameter and the temperature distribution in the region of interest could be recovered with discrepancies smaller than 0.03°C.

Estimation of the temperature field in laser-induced hyperthermia experiments with a phantom

Abstract Background: One of the challenges faced during the hyperthermia treatment of cancer is to monitor the temperature distribution in the region of interest. The main objective of this work was to accurately estimate the transient temperature distribution in the heated region, by using a stochastic heat transfer model and temperature measurements. Methods: Experiments involved the laser heating of a cylindrical phantom, partially loaded with iron oxide nanoparticles. The nanoparticles were manufactured and characterized in this work. The solution of the state estimation problem was obtained with an algorithm of the Particle Filter method, which allowed for simultaneous estimation of state variables and model parameters. Measurements of one single sensor were used for the estimation procedure, which is highly desirable for practical applications in order to avoid patient discomfort. Results: Despite the large uncertainties assumed for the model parameters and for the coupled radiation–conduction model, discrepancies between estimated temperatures and internal measurements were smaller than 0.7u2009°C. In addition, the estimated fluence rate distribution was physically meaningful. Maximum discrepancies between the prior means and the estimated means were of 2% for thermal conductivity and heat transfer coefficient, 4% for the volumetric heat capacity and 3% for the irradiance. Conclusions: This article demonstrated that the Particle Filter method can be used to accurately predict the temperatures in regions where measurements are not available. The present technique has potential applications in hyperthermia treatments as an observer for active control strategies, as well as to plan personalized heating protocols.