Technologies enabling in vivo range verification during proton therapy are actively sought as a means to reduce the clinical safety margins currently adopted to avoid tumor underdosage. In this contribution, we applied the semi-empirical theory of radiation-induced vaporization of superheated liquids to coated nanodroplets. Nanodroplets are injectable phase-change contrast agents that can vaporize into highly echogenic microbubbles to provide contrast in ultrasound images. We exposed nanodroplet dispersions in aqueous phantoms to monoenergetic proton beams of varying energies and doses. Ultrasound imaging of the phantoms revealed that radiation-induced droplet vaporization occurred in regions proximal to the proton Bragg peak. A statistically significant increase in contrast was observed in irradiated regions for doses as low as 2 Gy and found to be proportional to the proton fluence. The absence of enhanced response in the vicinity of the Bragg peak, combined with theoretical considerations, suggest that droplet vaporization is induced by high linear energy transfer (LET) recoil ions produced by nuclear reactions with incoming protons. Vaporization profiles were compared to non-elastic cross sections and LET characteristics of oxygen recoils. Shifts between the ultrasound image contrast drop and the expected proton range showed a sub-millimeter reproducibility. These early findings confirm the potential of superheated nanodroplets as a novel tool for proton range verification.

Ultrasound-driven microbubble (MB) activity is used in therapeutic applications such as blood clot dissolution and targeted drug delivery. The safety and performance of these technologies are linked to the type and distribution of MB activities produced within the targeted area, but controlling and monitoring these activities in vivo and in real time has proven to be difficult. As therapeutic pulses are often milliseconds long, MB monitoring currently requires a separate transducer used in a passive reception mode. Here, we present a simple, inexpensive, integrated setup, in which a focused single-element transducer can perform ultrasound therapy and monitoring simultaneously. MBs were made to flow through a vesselmimicking tube, placed within the transducer's focus, and were sonicated with therapeutic pulses (peak rarefactional pressure: 75-827 kPa, pulse lengths: 200 μs and 20 ms). The MB-seeded acoustic emissions were captured using the same transducer. The received signals were separated from the therapeutic signal with a hybrid coupler and a high-pass filter. We discriminated the MB-generated cavitation signal from the primary acoustic field and characterized MB behavior in real time. The simplicity and versatility of our circuit could make existing single-element therapeutic transducers also act as cavitation detectors, allowing the production of compact therapeutic systems with real time monitoring capabilities.

Superheated nanodroplet (ND) vaporization by proton radiation was recently demonstrated, opening the door to ultrasound-based in vivo proton range verification. However, at body temperature and physiological pressures, perfluorobutane nanodroplets (PFB-NDs), which offer a good compromise between stability and radiation sensitivity, are not directly sensitive to primary protons. Instead, they are vaporized by infrequent secondary particles, which limits the precision for range verification. The radiation-induced vaporization threshold (i.e., sensitization threshold) can be reduced by lowering the pressure in the droplet such that ND vaporization by primary protons can occur. Here, we propose to use an acoustic field to modulate the pressure, intermittently lowering the proton sensitization threshold of PFB-NDs during the rarefactional phase of the ultrasound wave. Simultaneous proton irradiation and sonication with a 1.1 MHz focused transducer, using increasing peak negative pressures (PNPs), were applied on a dilution of PFB-NDs flowing in a tube, while vaporization was acoustically monitored with a linear array. Sensitization to primary protons was achieved at temperatures between $29~^{\circ }\text{C}$ and 40 °C using acoustic PNPs of relatively low amplitude (from 800 to 200 kPa, respectively), while sonication alone did not lead to ND vaporization at those PNPs. Sensitization was also measured at the clinically relevant body temperature (i.e., 37 °C) using a PNP of 400 kPa. These findings confirm that acoustic modulation lowers the sensitization threshold of superheated NDs, enabling a direct proton response at body temperature.

Cardiac ultrasound imaging is widely used in the clinical setting. Deep learning algorithms have shown increased potential in automating routine clinical tasks for improved diagnosis and prognosis. However, the lack of large and diverse training databases hinders their employment on a full scale in clinics. Difficulties associated with creating large training databases include scarcity of clinical data, privacy related data access concerns and labor-intensive ground-truth annotations. To overcome these issues, realistic cardiac ultrasound simulation is considered advantageous. Nevertheless, our state-of-the-art cardiac ultrasound simulation pipeline is limited to small-scale databases particularly because of the underlying computationally complex finite-element heart model. In this paper, we developed a realistic simulation pipeline to facilitate large-scale synthetic cardiac ultrasound datasets. This pipeline utilizes a well-validated and computationally efficient lump-parameter heart model for generating cardiovascular mechanics, and the convolution based ultrasound simulator COLE for short simulation times. We implemented the proposed pipeline to create a large open-access database of 2-D realistic cardiac ultrasound recordings with diversity in the geometries, ultrasound speckle texture and motions of the left ventricle. Quantitative assessment of the simulated data demonstrated that the synthetic cardiac ultrasound frames contained realistic speckle patterns. Moreover, the left ventricular motion in the simulated frames was tracked using the medical imaging tracking toolbox and was shown to closely match the kinematically imposed ground-truth left ventricular motion. The presented pipeline is valuable for creating large and diverse ground-truth training databases. The resulting database is a potential augmentation tool for machine learning-based ultrasound data processing algorithms and made publicly available.

Superheated nanodroplets (NDs) were recently proposed for in vivo proton range verification, owing to their ability to vaporize into echogenic microbubbles (MBs) upon exposure to ionizing radiation. In a previous publication, vaporization events were detected with 2D Ultrasound Localization Microscopy (ULM) based on a pulse-echo method. Here, we introduce P-ULM, a passive version of ULM, based on the detection of acoustic signatures emitted by vaporizing NDs, without actively transmitting ultrasound. Due to the lack of a time reference for the trigger of the ND vaporization, the time differences of arrival to each transducer element are used to retrieve the position of vaporizing NDs. P-ULM, compared to ULM, can continuously detect and super-localize sparse radiation-induced vaporization events with inherent specificity against already existing microbubbles, which otherwise would hinder range verification in the presence of vascular flow. We evaluated the localization performances of both methods theoretically and experimentally, by interleaving active and passive acquisitions on ND-phantoms irradiated with protons. P-ULM offered a higher sensitivity to vaporizations, as it detected twice as many events as ULM. Both methods retrieved, in the acoustic lateral direction, the proton range and range dispersion with sub-millimeter accuracy. In the acoustic axial direction, despite a degraded theoretical resolution limit, P-ULM retrieved the proton spot size with an accuracy similar to ULM. Importantly, P-ULM detected vaporization events with high specificity in the presence of flowing MBs, which makes the technique a candidate for in vivo proton range verification in the presence of flow.