The ideal vision for cancer treatment is the complete removal of tumors while leaving the rest of the body intact. Among various therapeutic approaches, focused ultrasound (FUS) stands out as a truly non-invasive method that targets cancerous tumors with high accuracy using ultrasonic waves from an external energy source. FUS offers safer, lower-cost therapy with better precision and shorter recovery times compared to invasive surgical approaches. The primary effect of FUS is tissue heating, which leads to irreversible biological effects such as cell necrosis and tumor ablation. Guided by advanced imaging techniques like MRI and ultrasound, FUS has been applied to treat various benign and malignant tumors, including those in the prostate, liver, breast, brain, bone, and kidney.

However, clinical acceptance of FUS has been hindered by several challenges: prolonged treatment durations, especially for large tumors; the risk of cancer cell survival between focal regions; and collateral thermal damage to healthy tissues. To achieve results comparable to total tumor surgery, FUS must ensure complete tumor ablation, which currently requires multiple ablations, resulting in lengthy procedures. Additionally, there is a risk of cancer recurrence due to surviving cancer cells and the possibility of overheating healthy tissue. These issues have prevented FDA approval of FUS for certain applications. Therefore, there is a pressing need for new methods and apparatuses to improve the precision and safety of FUS treatment.

Objectives

This research project aims to revolutionize FUS surgery by integrating it with advanced technologies such as artificial intelligence (AI), automation, and robotics. The goal is to develop a fully autonomous and intelligent FUS system for precise cancer treatment. The system, equipped with an intelligent control unit, will be capable of preoperative planning, real-time monitoring, and autonomous operation of tumor ablation procedures. Key objectives include:

• Development of IntelFocus: A cloud-based software technology to assist physicians with real-time treatment planning, monitoring, and control of FUS therapy.

• Autonomous and Intelligent Control Unit: In collaboration with AI specialists, FUS researchers, and physicians, an advanced AI-based software unit will be developed to control and operate FUS procedures autonomously. The system will encompass preoperative planning, real-time analysis, and intelligent operation of FUS treatments.

Key Milestones

• M1: Preoperative Planning: Developing a simulation model for FUS treatment based on preoperative images to determine optimal therapeutic parameters and scanning pathways.

• M2: AI-based Monitoring: Creating intelligence-based image processing algorithms for real-time analysis of ultrasound images to assess the ablated region and total tumor volume. Training AI algorithms with B-mode images from FUS experiments and simulations.

• M3: Autonomous Control: Implementing advanced AI algorithms for supervisory control of the FUS procedure. The intelligent system will be trained and tested across various scenarios to ensure detailed and responsive operation based on real-time feedback from ultrasound imaging.

This project represents a significant step towards enhancing the precision, safety, and efficiency of FUS cancer treatments, potentially transforming the landscape of non-invasive cancer therapy.