Superparamagnetic iron oxide nanoparticles (SPIONs) are used in nanomedicine as transporter systems for therapeutic cargos, or to magnetize cells to make them magnetically guidable. In cancer treatment, the site-directed delivery of chemotherapeutics or immune effector cells to the tumor can increase the therapeutic efficacy in the target region, and simultaneously reduce toxic side-effects in the rest of the body. To enable the transfer of new methods, such as the nanoparticle-mediated transport from bench to bedside, suitable experimental setups must be developed. In vivo, the SPIONs or SPION-loaded cells must be applied into the blood stream, to finally reach the tumor: consequently, targeting and treatment efficacy should be analyzed under conditions which are as close to in vivo as possible. Here, we established an in vitro method, including tumor spheroids placed in a chamber system under the influence of a magnetic field, and adapted to a peristaltic pump, to mimic the blood flow. This enabled us to analyze the magnetic capture and antitumor effects of magnetically targeted mitoxantrone and immune cells under dynamic conditions. We showed that the magnetic nanoparticle-mediated accumulation increased the anti-tumor effects, and reduced the unspecific distribution of both mitoxantrone and cells. Especially for nanomedical research, investigation of the site-specific targeting of particles, cells or drugs under circulation is important. We conclude that our in vitro setup improves the screening process of nanomedical candidates for cancer treatment.

Magnetic nanoparticles (MNPs) have gained significant attention in biomedical engineering and imaging applications due to their unique magnetic and mechanical properties. With their high magnetization and small size, MNPs serve as excitation sources for magnetically heating to destroy tumors (magnetic hyperthermia) and magnetically controlled drug carriers in magnetic drug targeting. However, effectively visualizing the distribution of MNPs during research or potential clinical use with low-cost modalities remains a critical challenge. Although magnetic resonance imaging provides pre- and post-procedural imaging, it is considered to be high cost, and real-time imaging during clinical procedures is limited. In contrast, ultrasound-based imaging methods offer the advantage of providing the potential for immediate feedback during clinical use and are considered to be a low-cost modality. Ultrasound-based imaging techniques, including magnetomotive ultrasound, magnetoacoustic tomography, and thermoacoustic imaging, emerged as promising approaches for imaging the distribution of MNPs. These techniques offer the potential for real-time imaging, facilitating precise therapy monitoring. By exploring the strengths and limitations of various ultrasound-based imaging techniques for MNPs, this review seeks to provide comprehensive insights that can guide researchers in selecting suitable ultrasound-based modalities and inspire further advancements in this exciting field.

Magnetic nanoparticles guided by an external magnetic field can be used to deliver drugs (e.g., chemotherapeutics) to malignant regions (e.g., tumor tissue). Some nonmagnetic, sonosensitive nanoparticles are known to generate cavitation induced by focused ultrasound. This can can be used to monitor spatial/temporal particle distribution and to stimulate local drug release in target regions. Little to nothing is known about the sonosensitivity of magnetic nanoparticles. Therefore, we investigated this physical phenomenon in the present contribution. We showed that certain magnetic nanoparticles have high cavitation potential and are promising for further research in this regard.

The integration of robotics and artificial intelligence (AI) into nanomedicine represents a significant advancement in developing targeted therapeutic and diagnostic platforms. This field focuses on engineering micro- and nanoscale agents, such as magnetic nanoparticles (MNPs), microbots, and nanobots, for tasks like targeted therapies, sensing, and manipulation at diseased sites. MNPs are typically composed of iron oxides and serve as foundational components due to their biocompatibility, tunable surface chemistry, and responsiveness to external magnetic fields. They are used in targeted drug delivery, magnetic hyperthermia for tumor ablation, and as contrast agents in magnetic resonance imaging (MRI) and magnetic particle imaging (MPI). Microbots and nanobots, which often incorporate MNPs for propulsion, can be actively guided using external magnetic fields to navigate complex biological environments, perform micromanipulation, and enable triggered drug release. The precise control of these magnetic agents relies on electromagnetic or permanent magnet-based guidance systems, which balance magnetic force strength, workspace volume, and clinical integration. Other classes like biohybrid microbots or DNA nanobots, utilize magnetic field independent mechanisms for molecular sensing and cargo delivery. AI and machine learning enhance these systems by optimizing material and bot design through in silico modeling, facilitating real-time navigation via medical imaging feedback, and enabling adaptive pathfinding. AI can also support swarm control and data analysis for diagnostic improvement. However, clinical translation faces challenges, including ensuring long-term biocompatibility and biodistribution, achieving scalable Good Manufacturing Practice (GMP) production, demonstrating therapeutic advantage in preclinical models, navigating evolving regulatory frameworks, and securing sufficient funding.

Drug-loaded magnetic nanoparticles (MNPs) accumulated by an external magnetic field already showed their efficacy in localized tumor treatment in animal studies. Furthermore, specific MNPs are sonosensitive, enabling them to generate inertial cavitation when exposed to a focused ultrasound field. This can be used for controlling drug release, as well as for particle detection and mapping. In addition to inertial cavitation, stable cavitation is also a part of the cavitation process, which has not yet been evaluated on MNPs. While stable cavitation is less harmful to surrounding tissue compared to inertial cavitation, it also contributes to enhanced tumor perfusion. Hence, an optimal strategy could involve inducing inertial cavitation only within the tumor region for drug release and mapping, while employing stable cavitation outside the tumor to enhance perfusion. This study aims to investigate stable cavitation mediated by MNPs for the first time, while examining their overall cavitation behavior.

Ultrasound-induced cavitation can be used in various biomedical therapies, including localized drug delivery, sonoporation, gene transfer, noninvasive sonothrombolysis, lithotripsy, and histotripsy. It can also enhance thermal ablation of tumors and facilitate trans-blood-brain-barrier treatments. Accurate monitoring of cavitation activity, including dose and location, is essential for the safe and effective application of these therapies. Passive cavitation mapping (PCM) is a key technique used to achieve this. However, conventional Delay and Sum (DAS) beamforming methods suffer from low resolution and high side-lobe levels in standard diagnostic ultrasound transducer, limiting their effectiveness or are computationally expensive, in the case of robust capon beamformer (RCB). To address these challenges, we propose a higher-order nonlinear Delay Multiply and Sum (DMAS) beamformer for improved passive cavitation mapping. Our approach utilizes a novel implementation with linear complexity, using a determinant from symmetrical polynomials. Simulation and experimental results demonstrate that the proposed method enhances both axial and lateral point spread function, resolution and increasing image quality, while exhibiting linear complexity. These improvements suggest that higher-order nonlinear beamforming is a promising advancement for more accurate and reliable cavitation monitoring in biomedical applications.