arXiv subjects

Pablo Alvarez

Publications and source records attributed to Pablo Alvarez.

4 recordsLinked to original sources

arXiv2026

A Differentiable Simulation of the Eye for Patient-Specific Strabismus Surgery Planning

Purpose: Up to 4% of adults will develop strabismus in their lifetime. The most common surgical intervention involves adjusting the length of one or more extraocular muscles to correct the angular deviation. This correction depends on surgical expertise and statistical reference tables, which often fail to yield optimal results for patients with atypical eye morphology. Our work proposes a physics-based modeling approach to personalized surgical planning, accounting for patient-specific eye anatomy. Methods: We built a physics-based simulator of the eye and its muscles, incorporating patient-specific geometry and Hill-type muscle biomechanics. We solve an optimization problem to find the surgical dosage that minimizes angular deviation. The model is implemented as a fully differentiable simulation, enabling efficient optimization. We validated the framework by comparing its predictions with standard surgical tables for emmetropic eyes before applying it to anatomically atypical virtual patients. Results: Our model's predictions for emmetropic eyes were first validated, demonstrating a strong fit with standard surgical tables. More importantly, for high-myopia models, the framework computed a clinically significant increase in the required surgical dosage compared to standard eyes. This computed recession difference is highly relevant as surgical plans are adjusted in 0.5 mm increments. Conclusion: Our results show that our model provides a calibrated surgical plan that, unlike standard tables, also accounts for pathologies involving atypical eye shapes. This patient-specific model represents a step toward personalized surgical planning, with the potential to improve dosage accuracy and surgical outcomes for atypical cases.

math.NA↗

arXiv2026

A digital twin for microwave liver treatment replanning

Purpose: MicroWave Ablation (MWA) modeling and simulation bear great potential for loco-regional treatment of liver tumors. However, accurately positioning the antenna according to a planned orientation/location is technically challenging. In cases of misplacement, maintaining the original plan may cause incomplete ablation, while repositioning the antenna may induce tumor seeding. In this work, we propose (i) a digital twin of MWA that simulates ablation outcomes, and (ii) an optimizer that suggests corrections to MWA parameters without antenna reinsertion, while ensuring complete tumor ablations. Methods: A finite element scheme was used to solve the coupled microwave propagation and heat transfer equations governing MWA, with personalized dielectric and thermal properties determined from preoperative CT and MRI images. We then proposed an optimization algorithm able to adjust power input, ablation duration, and antenna position to correct for antenna misplacement. Results: The simulator and optimizer were evaluated against in vivo swine experimental data. Three ablations were performed in liver regions with varying vascularization. The simulations accurately predicted the ablation zones despite the presence of large vessels near the antenna, achieving Dice scores of 0.82, 0.81, and 0.79. In the case of replanning scenarios, our optimizer predicted new parameter sets that led to Dice scores of 0.83, 0.83, 0.80, a corresponding improvement of 20.3%, 40.7% and 48.1% in average over the initial ablation result. Conclusion: This paper is the first to address intra-operative replanning of thermal ablation therapy. It demonstrates that optimal ablation results can be achieved without requiring antenna reinsertion by optimizing specific ablation parameters.

physics.med-ph↗

arXiv2023

Deformable Image Registration with Stochastically Regularized Biomechanical Equilibrium

Numerous regularization methods for deformable image registration aim at enforcing smooth transformations, but are difficult to tune-in a priori and lack a clear physical basis. Physically inspired strategies have emerged, offering a sound theoretical basis, but still necessitating complex discretization and resolution schemes. This study introduces a regularization strategy that does not require discretization, making it compatible with current registration frameworks, while retaining the benefits of physically motivated regularization for medical image registration. The proposed method performs favorably in both synthetic and real datasets, exhibiting an accuracy comparable to current state-of-the-art methods.

eess.IV↗

arXiv2022

Measurement and Analysis of Lobar Lung Deformation After a Change of Patient Position During Video-Assisted Thoracoscopic Surgery

Video-assisted thoracoscopic surgery (VATS) is a minimally invasive surgical technique for the diagnosis and treatment of early-stage lung cancer. During VATS, large lung deformation occurs as a result of a change of patient position and a pneumothorax (lung deflation), which hinders the intraoperative localization of pulmonary nodules. Modeling lung deformation during VATS for surgical navigation is desirable, but the mechanisms causing such deformation are yet not well-understood. In this study, we estimate, quantify and analyze the lung deformation occurring after a change of patient position during VATS. We used deformable image registration to estimate the lung deformation between a preoperative CT (in supine position) and an intraoperative CBCT (in lateral decubitus position) of six VATS clinical cases. We accounted for sliding motion between lobes and against the thoracic wall and obtained consistently low average target registration errors (under 1 mm). We observed large lung displacement (up to 40 mm); considerable sliding motion between lobes and against the thoracic wall (up to 30 mm); and localized volume changes indicating deformation. These findings demonstrate the complexity of the change of patient position phenomenon, which should necessarily be taken into account to model lung deformation for intraoperative guidance during VATS.

physics.med-ph↗