Search

Objective. In proton therapy, range uncertainties prevent to optimally benefit from the superior depth-dose characteristics of proton beams over conventional photon-based radiotherapy. To reduce these uncertainties we recently proposed the use of phase-change ultrasound contrast agents as an affordable and effective range verification tool. In particular, superheated nanodroplets can convert into echogenic microbubbles upon proton irradiation, whereby the resulting ultrasound contrast relates to the proton range with high reproducibility. Here, we provide a first in vivo proof-of-concept of this technology.&#xD;&#xD; Approach. First, the in vitro biocompatibility of radiation-sensitive poly(vinyl) alcohol perfluorobutane nanodroplets was investigated using several colorimetric assays. Then, in vivo ultrasound contrast was characterized using acoustic droplet vaporization and later using proton beam irradiations at varying energies (49.7 MeV and 62 MeV) in healthy Sprague Dawley rats. A preliminary evaluation of the in vivo biocompatibility was performed using acoustic droplet vaporization and a combination of physiology monitoring and histology.&#xD;&#xD; Main results. Nanodroplets were non-toxic over a wide concentration range (< 1 mM). In healthy rats, intravenously injected nanodroplets primarily accumulated in the organs of the reticuloendothelial system, where the lifetime of the generated ultrasound contrast (< 30 min) was compatible with a typical radiotherapy fraction (< 5 min). Spontaneous droplet vaporization did not result in significant background signals. Online ultrasound imaging of the liver of droplet-injected rats demonstrated an energy-dependent proton response, which can be tuned by varying the nanodroplet concentration. However, caution is warranted when deciding on the exact nanodroplet dose regimen as a mild physiological response (drop in cardiac rate, granuloma formation) was observed after acoustic droplet vaporization.&#xD; &#xD; Significance. These findings underline the potential of phase-change ultrasound contrast agents for in vivo proton range verification and provide the next step towards eventual clinical applications.&#xD., (© 2024 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Objective. External beam radiotherapy is aimed to precisely deliver a high radiation dose to malignancies, while optimally sparing surrounding healthy tissues. With the advent of increasingly complex treatment plans, the delivery should preferably be verified by quality assurance methods. Recently, online ultrasound imaging of vaporized radiosensitive nanodroplets was proposed as a promising tool for in vivo dosimetry in radiotherapy. Previously, the detection of sparse vaporization events was achieved by applying differential ultrasound (US) imaging followed by intensity thresholding using subjective parameter tuning, which is sensitive to image artifacts. Approach . A generalized deep learning solution (i.e. BubbleNet) is proposed to localize vaporized nanodroplets on differential US frames, while overcoming the aforementioned limitation. A 5-fold cross-validation was performed on a diversely composed 5747-frame training/validation dataset by manual segmentation. BubbleNet was then applied on a test dataset of 1536 differential US frames to evaluate dosimetric features. The intra-observer variability was determined by scoring the Dice similarity coefficient (DSC) on 150 frames segmented twice. Additionally, the BubbleNet generalization capability was tested on an external test dataset of 432 frames acquired by a phased array transducer at a much lower ultrasound frequency and reconstructed with unconventional pixel dimensions with respect to the training dataset. Main results. The median DSC in the 5-fold cross validation was equal to ∼0.88, which was in line with the intra-observer variability (=0.86). Next, BubbleNet was employed to detect vaporizations in differential US frames obtained during the irradiation of phantoms with a 154 MeV proton beam or a 6 MV photon beam. BubbleNet improved the bubble-count statistics by ∼30% compared to the earlier established intensity-weighted thresholding. The proton range was verified with a -0.8 mm accuracy. Significance. BubbleNet is a flexible tool to localize individual vaporized nanodroplets on experimentally acquired US images, which improves the sensitivity compared to former thresholding-weighted methods., (© 2022 Institute of Physics and Engineering in Medicine.)

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.