Deep learning based ultrasonic visualization of distal humeral cartilage for image-guided therapy: a pilot validation study.

Background: Ultrasound is widely used for image-guided therapy (IGT) in many surgical fields, thanks to its various advantages, such as portability, lack of radiation and real-time imaging. This article presents the first attempt to utilize multiple deep learning algorithms in distal humeral cartilage segmentation for dynamic, volumetric ultrasound images employed in minimally invasive surgery. Methods: The dataset, consisting 5,321 ultrasound images were collected from 12 healthy volunteers. These images were randomly split into training and validation sets in an 8:2 ratio. Based on deep learning algorithms, 9 semantic segmentation networks were developed and trained using our dataset at Southern University of Science and Technology Hospital in September 2022. The performance of the networks was evaluated based on their segmenting accuracy and processing efficiency. Furthermore, these networks were implemented in an IGT system to assess their feasibility in 3-dimentional imaging precision. Results: In 2D segmentation, Medical Transformer (MedT) showed the highest accuracy result with a Dice score of 89.4%, however, the efficiency in processing images was relatively lower at 2.6 frames per second (FPS). In 3D imaging, the average root mean square (RMS) between ultrasound (US)-generated models based on the networks and magnetic resonance imaging (MRI)-generated models was no more than 1.12 mm. Conclusions: The findings of this study indicate the technological feasibility of a novel method for real-time visualization of distal humeral cartilage. The increased precision of ultrasound calibration and segmentation are both important approaches to improve the accuracy of 3D imaging.

Incorporating spin-orbit coupling promoted functional group into an enhanced electron D-A system: A useful designing concept for fabricating efficient photosensitizer and imaging-guided photodynamic therapy.

Intersystem crossing (ISC) is of great significance in photochemistry, and has a decisive influence on the properties of photosensitizers (PSs) for use in photodynamic therapy (PDT). However, the rationally design PSs with efficient ISC processes to implement superb reactive oxygen species (ROS) production is still a very challenging work. In this contribution, we described how a series of high-performance PSs were constructed through electron acceptor and donor engineering by integrating the smaller singlet-triplet energy gap (ΔEST) and larger spin-orbit coupling (SOC)-beneficial functional groups into the PS frameworks. Among the yielded various PSs, TaTIC was confirmed as the best candidate for application in PDT, which was due to its most outstanding ROS generation capability, bright near-infrared (NIR) fluorescence with peak over 840 nm, as well as desired aggregation-induced emission (AIE) features. Importantly, the ROS generation efficiency of TaTIC was even superior to that of some popularly used PSs, including the most reputable PS of Rose Bengal. In order to further extend therapeutic applications, TaTIC was encapsulated with biocompatible amphiphilic matrix and formulated into water-dispersed nanoparticles (NPs). More excitedly, the as-prepared TaTIC NPs gave wonderful PDT performance on tumor-bearing mouse model, actualizing complete tumor elimination outcomes. Coupled with excellent biosecurity, TaTIC NPs would be a promising theranostic agent for practical clinical application.

Optimization for customized trajectories in cone beam computed tomography.

PURPOSE: We developed a target-based cone beam computed tomography (CBCT) imaging framework for optimizing an unconstrained three dimensional (3D) source-detector trajectory by incorporating prior image information. Our main aim is to enable a CBCT system to provide topical information about the target using a limited angle noncircular scan orbit with a minimal number of projections. Such a customized trajectory should include enough information to sufficiently reconstruct a particular volume of interest (VOI) under kinematic constraints, which may result from the patient size or additional surgical or radiation therapy-related equipment. METHODS: A patient-specific model from a prior diagnostic computed tomography (CT) volume is used as a digital phantom for CBCT trajectory simulations. Selection of the best projection views is accomplished through maximizing an objective function fed by the imaging quality provided by different x-ray positions on the digital phantom data. The final optimized trajectory includes a limited angular range and a minimal number of projections which can be applied to a C-arm device capable of general source-detector positioning. The performance of the proposed framework is investigated in experiments involving an in-house-built box phantom including spherical targets as well as an Alderson-Rando head phantom. In order to quantify the image quality of the reconstructed image, we use the average full-width-half-maximum (FWHMavg ) for the spherical target and feature similarity index (FSIM), universal quality index (UQI), and contrast-to-noise ratio (CNR) for an anatomical target. RESULTS: Our experiments based on both the box and head phantom showed that optimized trajectories could achieve a comparable image quality in the VOI with respect to the standard C-arm circular CBCT while using approximately one quarter of projections. We achieved a relative deviation <7% for FWHMavg between the reconstructed images from the optimized trajectories and the standard C-arm CBCT for all spherical targets. Furthermore, for the anatomical target, the relative deviation of FSIM, UQI, and CNR between the reconstructed image related to the proposed trajectory and the standard C-arm circular CBCT was found to be 5.06%, 6.89%, and 8.64%, respectively. We also compared our proposed trajectories to circular trajectories with equivalent angular sampling as the optimized trajectories. Our results show that optimized trajectories can outperform simple partial circular trajectories in the VOI in term of image quality. Typically, an angular range between 116° and 152° was used for the optimized trajectories. CONCLUSION: We demonstrated that applying limited angle noncircular trajectories with optimized orientations in 3D space can provide a suitable image quality for particular image targets and has a potential for limited angle and low-dose CBCT-based interventions under strong spatial constraints.