Artificial intelligence-assisted ultrasound-guided focused ultrasound therapy: a feasibility study.

OBJECTIVES: Focused ultrasound (FUS) therapy has emerged as a promising noninvasive solution for tumor ablation. Accurate monitoring and guidance of ultrasound energy is crucial for effective FUS treatment. Although ultrasound (US) imaging is a well-suited modality for FUS monitoring, US-guided FUS (USgFUS) faces challenges in achieving precise monitoring, leading to unpredictable ablation shapes and a lack of quantitative monitoring. The demand for precise FUS monitoring heightens when complete tumor ablation involves controlling multiple sonication procedures. METHODS: To address these challenges, we propose an artificial intelligence (AI)-assisted USgFUS framework, incorporating an AI segmentation model with B-mode ultrasound imaging. This method labels the ablated regions distinguished by the hyperechogenicity effect, potentially bolstering FUS guidance. We evaluated our proposed method using the Swin-Unet AI architecture, conducting experiments with a USgFUS setup on chicken breast tissue. RESULTS: Our results showed a 93% accuracy in identifying ablated areas marked by the hyperechogenicity effect in B-mode imaging. CONCLUSION: Our findings suggest that AI-assisted ultrasound monitoring can significantly improve the precision and control of FUS treatments, suggesting a crucial advancement toward the development of more effective FUS treatment strategies.

Real-time monitoring of focused ultrasound therapy using intelligence-based thermography: A feasibility study.

Focused ultrasound (FUS) therapy has been widely studied for breast cancer treatment due to its potential as a fully non-invasive method to improve cosmetic and oncologic results. However, real-time imaging and monitoring of the therapeutic ultrasound delivered to the target area remain challenges for precision breast cancer therapy. The main objective of this study is to propose and evaluate a novel intelligence-based thermography (IT) method that can monitor and control FUS treatment using thermal imaging with the fusion of artificial intelligence (AI) and advanced heat transfer modeling. In the proposed method, a thermal camera is integrated into FUS system for thermal imaging of the breast surface, and an AI model is employed for the inverse analysis of the surface thermal monitoring, thereby estimating the features of the focal region. This paper presents experimental and computational studies conducted to assess the feasibility and efficiency of IT-guided FUS (ITgFUS). Tissue phantoms, designed to mimic the properties of breast tissue, were used in the experiments to investigate detectability and the impact of temperature rise at the focal region on the tissue surface. Additionally, an AI computational analysis employing an artificial neural network (ANN) and FUS simulation was carried out to provide a quantitative estimation of the temperature rise at the focal region. This estimation was based on the observed temperature profile on the breast model's surface. The results proved that the effects of temperature rise at the focused area could be detected by the thermal images acquired with thermography. Moreover, it was demonstrated that the AI analysis of the surface temperature measurement could result in near real-time monitoring of FUS by quantitative estimation of the temporal and spatial temperature rise profiles at the focal region.

Magnetic nanoparticles-enhanced focused ultrasound heating: size effect, mechanism, and performance analysis.

High intensity focused ultrasound (HIFU) has attracted great interest as a new energy-based technique to treat disordered tissues, such as tumors, through a hyperthermal mechanism using ultrasonic waves. However, long treatment times and collateral damage to healthy tissues due to high acoustic powers are still challenges for the clinical application of HIFU. One possible strategy to enhance the deposition efficiency of HIFU at the tumor site is to employ magnetic nanoparticles (MNPs) as ultrasound absorption agents for the thermal therapy. The objectives of the current study are threefold: (i) to examine the effects of MNP features, including the size and volume concentration, on the thermal mechanism of HIFU (ii) to investigate the performance of MNPs as they were exposed to ultrasound fields at different ranges of power and frequency (iii) and to study the interaction mechanism between MNPs and ultrasonic waves during the MNPs-enhanced HIFU process. To this end, we developed an ultrasound-guided HIFU system to conduct an in vitro experimental study on tissue phantoms containing MNPs of different sizes and volume concentrations. A set of HIFU parameters such as temperature rise and the rate of absorbed energy was monitored to examine the role of MNPs during the NPs-enhanced HIFU thermal procedure. Results showed that the MNPs significantly improved the thermal effect of HIFU by enhancing the rate of energy converted to heat and the temperature rise at the focal region. Moreover, it was demonstrated that the increase of MNP size and volume concentration greatly enhanced the HIFU parameters; the effects of MNPs were further improved by increasing the power and frequency of acoustic field.

Analytical and Numerical Model of High Intensity Focused Ultrasound Enhanced With Nanoparticles.

OBJECTIVE: High intensity focused ultrasound (HIFU) is a new noninvasive therapeutics that allows local treatment of solid tumors through a hyperthermal mechanism using ultrasonic energy. One promising strategy to increase the thermal efficiency of HIFU is to employ nanoparticles (NPs) as ultrasound agents for the hyperthermia procedure. However, the interaction mechanism between NPs and ultrasonic waves has not been well understood. METHODS: In an effort to investigate the heating process of NPs-enhanced HIFU, we derived a set of HIFU equations governing the temperature variation during the thermal ablation based on the principle of conservation of energy for heat transfer mechanism. A numerical model was developed to solve the HIFU equations to simulate the absorption mechanism of HIFU in the presence of NPs, the consequent heat transfer process, and the temperature rise profile during the sonication period. The accuracy of numerical model was verified by performing a series of experiments on tissue-mimicking phantoms embedded with magnetic NPs (MNPs). RESULTS: The transport processes taking place at the boundaries between NPs and surrounding medium played the major role in the temperature rise during HIFU sonication. Besides, the effects of MNPs on rising temperature were improved by amplifying the ultrasonic power and frequency as well as by increasing the MNP concentration. CONCLUSION: A quantitative comparison with experimental results demonstrated the potential of the numerical model to accurately predict the heating mechanism of HIFU mediated by NPs. SIGNIFICANCE: The proposed method can help with simulation of HIFU when NPs are employed as ultrasound agents.

Enhancing Thermal Effect of Focused Ultrasound Therapy Using Gold Nanoparticles.

High intensity focused ultrasound (HIFU) has gained increasing attention as a noninvasive therapeutic method for wide range of biomedical applications from drug delivery to cancer treatment. However, high level of ultrasonic power required for efficient HIFU treatment can cause adverse effects such as damage to surrounding healthy tissues and skin burns. One of the strategies to improve the therapeutic mechanism of HIFU is to use ultrasound absorption agents during the treatment. The objectives of current study are to investigate the feasibility of adopting gold nanoparticles (AuNPs) as ultrasound absorption agents to enhance the HIFU thermal ablation when the NPs were injected locally to the focal region; and to examine the dose effects of AuNPs on both heating and cooling mechanisms of HIFU. To this end, we conducted an experimental study on tissue-mimicking phantoms where AuNPs were injected to the focal region under the guidance of ultrasound imaging. A set of thermal parameters including temperature, specific absorption rate of acoustic energy, and cooling rate were measured to monitor the mechanism of AuNPs-mediated HIFU. The results suggest that both heating and cooling rates of HIFU procedure could be greatly improved by injecting AuNPs, which demonstrates the feasibility of using AuNPs to reduce the level of ultrasonic power from extracorporeal source for HIFU treatment.

An experimental and numerical study on tactile neuroimaging: A novel minimally invasive technique for intraoperative brain imaging.

BACKGROUND: The success of tumour neurosurgery is highly dependent on the ability to accurately localize the operative target, which may shift during the operation. Performing intraoperative brain imaging is crucial in minimally invasive neurosurgery to detect the effect of brain shift on the tumour's location, and to maximize the efficiency of tumour resection. METHOD: The major objective of this research is to introduce tactile neuroimaging as a novel minimally invasive technique for intraoperative brain imaging. To investigate the feasibility of the proposed method, an experimental and numerical study was first performed on silicone phantoms mimicking the brain tissue with a tumour. Then the study was extended to a clinical model with the meningioma tumour. RESULTS: The stress distribution on the brain surface has high potential to intraoperatively localize the tumour. CONCLUSION: Results suggest that tactile neuroimaging can be used to provide non-invasive and real-time intraoperative data on a tumour's features.

Finite element modeling of haptic thermography: A novel approach for brain tumor detection during minimally invasive neurosurgery.

Intraoperative Thermal Imaging (ITI) is a novel neuroimaging method that can potentially locate tissue abnormalities and hence improves surgeon's diagnostic ability. In the present study, thermography technique coupled with artificial tactile sensing method called "haptic thermography" is utilized to investigate the presence of an abnormal object as a tumor with an elevated temperature relative to the normal tissue in the brain. The brain tissue is characterized as a hyper-viscoelastic material to be descriptive of mechanical behavior of the brain tissue during tactile palpation. Based on a finite element approach, Magnetic Resonance Imaging (MRI) data of a patient diagnosed to have a brain tumor is utilized to simulate and analyze the capability of haptic thermography in detection and localization of brain tumor. Steady-state thermal results prove that temperature distribution is an appropriate outcome of haptic thermography for the superficial tumors while heat flux distribution can be used as an extra thermal result for deeply located tumors.