A Roadmap to Holographic Focused Ultrasound Approaches for Generating Gradient Thermal Patterns.

Area of Science:

• Acoustics and Biomedical Engineering
• Computational Modeling and Simulation
• Medical Physics

Background:

• Effective therapeutic focused ultrasound (FUS) requires precise control of acousto-thermal effects for applications like thermal ablation and hyperthermia.
• Acoustic holographic lenses (AHLs) offer advanced capabilities for shaping complex and multifocal ultrasound fields.
• The potential of AHLs in precisely controlling ultrasound-induced heating patterns remains an under-explored area.

Purpose of the Study:

• To establish a roadmap for acousto-thermal modeling in the design of AHLs for therapeutic FUS.
• To compare the efficacy of different modeling approaches in shaping ultrasound-induced thermal patterns.
• To introduce novel metrics for evaluating modeling performance and guide the selection of appropriate methods.

Main Methods:

• Investigated three primary modeling approaches: pressure-based time reversal (TR) (basic and iterative), temperature-based inverse heat transfer optimization (IHTO-TR), and machine learning (ML)-based methods (generative adversarial networks - GaN and Feat-GAN).
• Utilized four distinct target field shapes to contrast the modeling techniques.
• Introduced new metrics: image quality, thermal efficiency, thermal control, and computational time.

Main Results:

• Each modeling approach demonstrated unique strengths and weaknesses based on target pattern complexity, thermal/pressure requirements, and computational resources.
• Iterative TR (ITER-TR) refines patterns based on target shape, while IHTO-TR excels in thermal control.
• ML-based methods (GaN, Feat-GAN) offer rapid solutions, with Feat-GAN providing adaptability for varying conditions.

Conclusions:

• The study provides a practical reference for selecting acousto-thermal modeling approaches for AHL design in therapeutic FUS.
• Established methods (BSC-TR, ITER-TR) and novel techniques (IHTO-TR, GaN, Feat-GAN) offer distinct advantages for different therapeutic goals and modeling constraints.
• Case studies in transcranial FUS and liver hyperthermia highlight the practical applicability of acoustic holography in clinical settings.