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Residual bubbles produced after collapse of a cavitation cloud provide cavitation nuclei for subsequent cavitation events, causing cavitation to occur repeatedly at the same discrete set of sites. This effect, referred to as cavitation memory, limits the efficiency of histotripsy soft tissue fractionation. Besides passively mitigating cavitation memory by using a low pulse repetition frequency (~1 Hz), an active strategy was developed by our group. In this strategy, low-amplitude ultrasound sequences were used to stimulate coalescence of residual bubbles. The goal of this work is to remove cavitation memory and achieve rapid, homogeneous lesion formation using a single phased array transducer. A 1-MHz integrated histotripsy and bubble coalescing (BC) transducer system with a specialized electronic driving system was built in house. High-amplitude ($P- >= 30$ MPa) histotripsy pulses and subsequent low-amplitude (~1–2 MPa) BC sequences were applied to a red blood cell tissue-mimicking phantom at a single focal site. Significant reduction of the cavitation memory effect and increase in the fractionation rate were observed by introducing BC sequence. Effects of BC pulsing parameters were further studied. The optimal BC parameters were then utilized to homogenize a $10 \times 10$ mm2 region at high rate. [ABSTRACT FROM AUTHOR]

An approach was demonstrated to gather, fix, and controllably shift flowing microbubbles in a blood vessel phantom. An ultrasonic standing wave field was generated by the superposition of the emission of a 5 MHz conventional transducer and the reflection from a bone surface. The acoustic radiation force gathered flowing microbubbles into the nodes, fixed some accumulated microbubble clusters in the flow condition, and shifted microbubbles to target site with stepwise frequency. The resolution of microbubble shift was approximately 4 μm, and the low acoustic pressure range was from 4 to 16 kPa to avoid microbubble rupture. [ABSTRACT FROM AUTHOR]

Parkinson's disease is the second most common neurodegenerative disease. It is characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta. 1-Methyl-4-phenylpyridinium (MPP+) is a dopaminergic neuronal toxin that is widely used in constructing Parkinson's disease models in vitro. Low-intensity pulsed ultrasound (LIPUS) is a non-invasive therapeutic approach that has neuromodulation and neuroprotective effects in the central neural system; however, whether LIPUS can provide protection for dopaminergic neurons against MPP+-induced neurocytotoxicity remains unknown. In this study, we found that pre-treatment with LIPUS (1 MHz, 50 mW/cm2, 20% duty cycle and 100-Hz pulse repetition frequency, 10 min) inhibited MPP+-induced neurotoxicity and mitochondrial dysfunction in PC12 cells. LIPUS decreased MPP+-induced oxidative stress by modulating antioxidant proteins, including thioredoxin-1 and heme oxygenase-1, and prevented neurocytotoxicity via the phosphoinositide 3-kinase (PI3K)-Akt and ERK1/2 pathways. Furthermore, these beneficial effects were attributed to the activation of K2P channels and stretch-activated ion channels by LIPUS. These data indicate that LIPUS protects neuronal cells from MPP+-induced cell death through the K2P channel- and stretch-activated ion channel-mediated downstream pathways. The data also suggest that LIPUS could be a promising therapeutic method in halting or retarding the degeneration of dopaminergic neurons in Parkinson's disease in a non-invasive manner. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to propose and evaluate a novel three-dimensional (3D) V-Net and two-dimensional (2D) U-Net mixed (VUMix-Net) architecture for a fully automatic and accurate gross tumor volume (GTV) in esophageal cancer (EC)-delineated contours., Methods: We collected the computed tomography (CT) scans of 215 EC patients. 3D V-Net, 2D U-Net, and VUMix-Net were developed and further applied simultaneously to delineate GTVs. The Dice similarity coefficient (DSC) and 95th-percentile Hausdorff distance (95HD) were used as quantitative metrics to evaluate the performance of the three models in ECs from different segments. The CT data of 20 patients were randomly selected as the ground truth (GT) masks, and the corresponding delineation results were generated by artificial intelligence (AI). Score differences between the two groups (GT versus AI) and the evaluation consistency were compared., Results: In all patients, there was a significant difference in the 2D DSCs from U-Net, V-Net, and VUMix-Net (p=0.01). In addition, VUMix-Net showed achieved better 3D-DSC and 95HD values. There was a significant difference among the 3D-DSC (mean ± STD) and 95HD values for upper-, middle-, and lower-segment EC (p<0.001), and the middle EC values were the best. In middle-segment EC, VUMix-Net achieved the highest 2D-DSC values (p<0.001) and lowest 95HD values (p=0.044)., Conclusion: The new model (VUMix-Net) showed certain advantages in delineating the GTVs of EC. Additionally, it can generate the GTVs of EC that meet clinical requirements and have the same quality as human-generated contours. The system demonstrated the best performance for the ECs of the middle segment., Competing Interests: Author QC, AS, and SW were employed by MedMind Technology Co, Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Jin, Chen, Shi, Wang, Ren, Zheng, Song, Zhang, Wang, Wang, Wang, Cheng, Wang and Ge.)