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Abstract This study investigates a novel microfluidic mixing technique that uses the resonant oscillation of coalescent droplets. During the vertical contact-separation process, solutes are initially separated as a result of the combined effects of diffusion and gravity. We show that the application of alternating current (AC) voltage to microelectrodes below the droplets causes a resonant oscillation, which enhances the even distribution of the solute. The difference in concentration between the top and bottom droplets exhibits frequency dependence and indicates the existence of a particular AC frequency that results in a homogeneous concentration. This frequency corresponds to the resonance frequency of the droplet oscillation that is determined using particle tracking velocimetry. To understand the mixing process, a phenomenological model based on the equilibrium between surface tension, viscosity, and electrostatic force was developed. This model accurately predicted the resonance frequency of droplet flow and was consistent with the experimental results. These results suggest that the resonant oscillation of droplets driven by AC voltage significantly enhances the diffusion of solutes, which is an effective approach to microfluid mixing.

Background With the advent of cranial orthoses as therapeutic medical devices for the treatment of severe positional head deformities in Japan, an increasing number of patients are being treated with them. However, assessing the effectiveness of a treatment is often difficult due to the use of different metrics. This study aimed to evaluate the effectiveness of cranial orthoses for deformational plagiocephaly using two- (2D) and three-dimensional (3D) evaluation metrics.

Summary:. Deep inferior epigastric perforator flaps are commonly used for breast reconstruction using autologous tissue. For such free flaps, the internal mammary artery provides stable blood flow as the recipient for anastomosis. We report a novel dissection method of the internal mammary artery. First, the perichondrium and costal cartilage of the sternocostal joint are dissected with electrocautery. Then, the incision on the perichondrium is extended along the cephalic and caudal ends. Next, this C-shaped superficial layer of perichondrium is elevated from the cartilage. The cartilage is incompletely fractured with electrocautery, with the deep layer of perichondrium intact. Then, the cartilage is completely fractured by leverage and removed. The remaining deep layer of perichondrium is incised at the costochondral junction and shifted aside, revealing the internal mammary artery. The preserved perichondrium creates a rabbet joint to protect the anastomosed artery. This method not only enables a more reliable, safer dissection of the internal mammary artery, but also allows reusage of the perichondrium as underlayment in the setting of anastomosis, and coverage for the incised rib edge, protecting the anastomosed vessels.

Background Dermal backflow (DBF), which refers to lymphatic reflux due to lymphatic valve insufficiency, is a diagnostic finding in lymphedema. However, the three-dimensional structure of DBF remains unknown. Photoacoustic lymphangiography (PAL) is a new technique that enables the visualization of the distribution of light-absorbing molecules, such as hemoglobin or indocyanine green (ICG), and can provide three-dimensional images of superficial lymphatic vessels and the venous system. This study reports the use of PAL to visualize DBF structures in the extremities of patients with lymphedema after cancer surgery. Methods Patients with a clinical or lymphographic diagnosis of lymphedema who previously underwent surgery for cancer at one of two participating hospitals were included in this study. PAL was performed using the PAI-05 system. ICG was administered subcutaneously in the affected hand or foot, and ICG fluorescence lymphography was performed using a nearinfrared camera system prior to PAL. Results Between April 2018 and January 2019, 21 patients were enrolled and examined using PAL. The DBF was composed of dense, interconnecting, three-dimensional lymphatic vessels. It was classified into three patterns according to the composition of the lymphatic vessels: a linear structure of lymphatic collectors (pattern 1), a network of lymphatic capillaries and lymphatic collectors in an underlying layer (pattern 2), and lymphatic capillaries and precollectors with no lymphatic collectors (pattern 3). Conclusions PAL showed the structure of DBF more precisely than ICG fluorescence lymphography. The use of PAL to visualize DBF assists in understanding the pathophysiology and assessing the severity of cancer-related lymphedema.

Background Lymphaticovenular anastomosis (LVA) is a minimally invasive surgical procedure used to treat lymphedema. Volumetric measurements and quality-of-life assessments are often performed to assess the effectiveness of LVA, but there is no method that provides information regarding postoperative morphological changes in lymphatic vessels and veins after LVA. Photoacoustic lymphangiography (PAL) is an optical imaging technique that visualizes the distribution of light-absorbing molecules, such as hemoglobin or indocyanine green (ICG), and provides three-dimensional images of superficial lymphatic vessels and the venous system simultaneously. In this study, we performed PAL in lymphedema patients before and after LVA and compared the images to evaluate the effect of LVA. Methods PAL was performed using the PAI-05 system in three patients (one man, two women) with lymphedema, including one primary case and two secondary cases, before LVA. ICG fluorescence lymphography was performed in all cases before PAL. Follow-up PAL was performed between 5 days and 5 months after LVA. Results PAL enabled the simultaneous visualization of clear lymphatic vessels that could not be accurately seen with ICG fluorescence lymphography and veins. We were also able to observe and analyze morphological changes such as the width and the number of lymphatic vessels and veins during the follow-up PAL after LVA. Conclusions By comparing preoperative and postoperative PAL images, it was possible to analyze the morphological changes in lymphatic vessels and veins that occurred after LVA. Our study suggests that PAL would be useful when assessing the effect of LVA surgery.

BackgroundFibrotic scars are common in both human and mouse skin wounds. However, wound-induced hair neogenesis in the murine wounding models often results in regenerative repair response. Herein, we aimed to uncover cellular functional heterogeneity in dermis between fibrotic and regenerative wound healing fates.MethodsThe expression matrix of single-cell RNA sequencing (scRNA-seq) data of fibrotic and regenerative wound dermal cells was filtered, normalized, and scaled; underwent principal components analysis; and further analyzed by Uniform Manifold Approximation and Projection (UMAP) for dimension reduction with the Seurat package. Cell types were annotated, and cell–cell communications were analyzed. The core cell population myofibroblast was identified and the biological functions of ligand and receptor genes between myofibroblast and macrophage were evaluated. Specific genes between fibrotic and regenerative myofibroblast and macrophage were identified. Temporal dynamics of myofibroblast and macrophage were reconstructed with the Monocle tool.ResultsAcross dermal cells, there were six cell types, namely, EN1-negative myofibroblasts, EN1-positive myofibroblasts, hematopoietic cells, macrophages, pericytes, and endothelial cells. Ligand and receptor genes between myofibroblasts and macrophages mainly modulated cell proliferation and migration, tube development, and the TGF-β pathway. Specific genes that were differentially expressed in fibrotic compared to regenerative myofibroblasts or macrophages were separately identified. Specific genes between fibrotic and regenerative myofibroblasts were involved in the mRNA metabolic process and organelle organization. Specific genes between fibrotic and regenerative macrophages participated in regulating immunity and phagocytosis. We then observed the underlying evolution of myofibroblasts or macrophages.ConclusionCollectively, our findings reveal that myofibroblasts and macrophages may alter the skin wound healing fate through modulating critical signaling pathways.

Abstract This paper presents progress in the automation of cell and tissue systems and attempts toward the in situ feedback control of organs-on-a-chip. Our study aims to achieve feedback control of a cell and tissue system by a personal computer (PC), whereas most studies on organs-on-a-chip focus on the automation of status monitoring. The implemented system is composed of subsystems including automated culture, stimulation, and monitoring. The monitoring function provides imaging as well as sampling and dispensing in combination with an external analyzer. Individual subsystems can be combined accordingly. First, monitoring of skeletal muscle (SM) and adipose tissues using this system was demonstrated. The highlight of this paper is the application of the system to the feedback control of the lipid droplet (LD) size, where biochemical stimulation using insulin and adrenaline is controlled by a PC according to the obtained LD imaging data. In this study, the system demonstrated its function of maintaining the desired size of LDs. Our results expand the possibility of PC-controllable cell and tissue systems by addressing the challenge of feedback control of organs-on-a-chip. The PC-controllable cell and tissue systems will contribute to living systems-on-a-chip based on homeostasis phenomena involving interactions between organs or tissues.

Recording surgery is an important technique for education and the evaluation of medical treatments. However, capturing targets such as the surgical field, surgical tools, and the surgeon’s hands, is almost impossible since these targets are heavily occluded by the surgeon’s head and body during a surgery. We used a recording system in which multiple cameras are installed in the surgical lump, supposing at least one camera would capture the target without occlusion. As this system records multiple video sequences, we address the task to select a best view camera automatically. Recently, learning-based approaches in a fully supervised manner have been proposed for this task, but these previous approaches completely rely on manual annotation of the training data. In this paper, we focus on the eye tracker mounted on the surgeon’s head, which can capture the recording targets without occlusion. Employing this first-person-view video synchronized with multiple videos of the surgical lump, we propose a novel camera selection approach using a self-supervised learning framework. In experiments, we created a dataset composed of four different breast surgery. Our extended experiments showed that our approach successfully switched to the best camera view without manual annotation and achieved competitive accuracy compared with conventional supervised methods. Also, our approach yielded effective visual representations comparable to state-of-the-art self-supervised learning frameworks.

Mounting multi-view cameras within a surgical light is a practical choice since some cameras are expected to observe surgery with few occlusions. Such multi-view videos must be reassembled for easy reference. A typical way is to reconstruct the surgery in 3D. However, the geometrical relationship among cameras is changed because each camera independently moves every time the lighting is reconfigured (i.e., every time surgeons touch the surgical light). Moreover, feature matching between surgical images is potentially challenging because of missing rich features. To address the challenge, we propose a feature-matching strategy that enables robust calibration of the multi-view camera system by collecting a set of a small number of matches over time while the cameras stay stationary. Our approach would enable conversion from multi-view videos to a 3D video. However, surgical videos are long and, thus, the cost of the conversion rapidly grows. Therefore, we implement a video player where only selected frames are converted to minimize time and data until playbacks. We demonstrate that sufficient calibration quality with real surgical videos can lead to a promising 3D mesh and a recently emerged 3D multi-layer representation. We reviewed comments from surgeons to discuss the differences between those 3D representations on an autostereoscopic display with respect to medical usage.

Detecting surgical tools is an essential task for analyzing and evaluating surgical videos. However, most studies focus on minimally invasive surgery (MIS) and cataract surgery. Mainly because of a lack of a large, diverse, and well-annotated dataset, research in the area of open surgery has been limited so far. Open surgery video analysis is challenging because of its properties: varied number and roles of people (e.g., main surgeon, assistant surgeons, and nurses), a complex interaction of tools and hands, various operative environments, and lighting conditions. In this paper, to handle these limitations and difficulties, we introduce an egocentric open surgery dataset that includes 15 open surgeries recorded with a head-mounted camera. More than 67k bounding boxes are labeled to 19k images with 31 surgical tool categories. Finally, we present a surgical tool detection baseline model based on recent advances in object detection. The results of our new dataset show that our presented dataset provides enough interesting challenges for future methods and that it can serve as a strong benchmark to address the study of tool detection in open surgery.

Multi-camera multi-person (MCMP) tracking and re-identification (ReID) are essential tasks in safety, pedestrian analysis, and so on; however, most research focuses on outdoor scenarios because they are much more complicated to deal with occlusions and misidentification in a crowded room with obstacles. Moreover, it is challenging to complete the two tasks in one framework. We present a trajectory-based method, integrating tracking and ReID tasks. First, the poses of all surgical members captured by each camera are detected frame-by-frame; then, the detected poses are exploited to track the trajectories of all members for each camera; finally, these trajectories of different cameras are clustered to re-identify the members in the operating room across all cameras. Compared to other MCMP tracking and ReID methods, the proposed one mainly exploits trajectories, taking texture features that are less distinguishable in the operating room scenario as auxiliary cues. We also integrate temporal information during ReID, which is more reliable than the state-of-the-art framework where ReID is conducted frame-by-frame. In addition, our framework requires no training before deployment in new scenarios. We also created an annotated MCMP dataset with actual operating room videos. Our experiments prove the effectiveness of the proposed trajectory-based ReID algorithm. The proposed framework achieves 85.44% accuracy in the ReID task, outperforming the state-of-the-art framework in our operating room dataset.

Summary:. It is difficult to evaluate the postoperative patency of lymphaticovenular anastomosis, but this evaluation is essential for determining surgical results. When using the current standard modality, near-infrared fluorescent lymphography, it is difficult to observe patency if the anastomotic point is veiled by dermal backflow. In this study, we used a new photoacoustic imaging device, PAI-05, to check the patency of anastomosis. We performed photoacoustic lymphangiography after lymphaticovenular anastomosis surgery. By digitally subtracting the superficial area, we can examine an area deeper than the dermal backflow, which is not visible by near-infrared fluorescent lymphography. The connection between the lymphatic vessel and the venule observed in the image is an indication of the patency of anastomosis. However, in a non-patent anastomosed site, the lymphatic vessel has a gap that separates it from the venule at the anastomosed site. Although photoacoustic lymphangiography cannot be used to visualize the lymphatic vessels that are not contrasted by indocyanine green, the resulting high-resolution images and clear anastomosis evaluation afforded by it will contribute to the development of future lymphedema treatments.

Lymphaticovenular anastomosis (LVA) is a widely performed surgical procedure for the treatment of lymphedema. For good LVA outcomes, identifying lymphatic vessels and venules is crucial. Photoacoustic lymphangiography (PAL) is a new technology for visualizing lymphatic vessels. It can depict lymphatic vessels at high resolution; therefore, this study focused on how to apply PAL for lymphatic surgery. To visualize lymphatic vessels, indocyanine green was injected as a color agent. PAI-05 was used as the photoacoustic imaging device. Lymphatic vessels and veins were visualized at 797- and 835-nm wavelengths. First, it was confirmed whether the branching of the vasculature as depicted by the PAL was consistent with the actual branching of the vasculature as confirmed intraoperatively. Second, to use PAL images for surgical planning, preoperative photoacoustic images were superimposed onto the patient limb through augmented reality (AR) glasses (MOVERIO Smart Glass BT-30E). Lymphatics and venule markings drawn using AR glasses were consistent with the actual intraoperative images obtained during LVA. To anastomose multiple lymphatic vessels, a site with abundant venous branching was selected as the incision site; and selecting the incision site became easier. The anatomical morphology obtained by PAL matched the surgical field. AR-based marking could be very useful in future LVA.

Detecting surgical tools is an essential task for the analysis and evaluation of surgical videos. However, in open surgery such as plastic surgery, it is difficult to detect them because there are surgical tools with similar shapes, such as scissors and needle holders. Unlike endoscopic surgery, the tips of the tools are often hidden in the operating field and are not captured clearly due to low camera resolution, whereas the movements of the tools and hands can be captured. As a result that the different uses of each tool require different hand movements, it is possible to use hand movement data to classify the two types of tools. We combined three modules for localization, selection, and classification, for the detection of the two tools. In the localization module, we employed the Faster R-CNN to detect surgical tools and target hands, and in the classification module, we extracted hand movement information by combining ResNet-18 and LSTM to classify two tools. We created a dataset in which seven different types of open surgery were recorded, and we provided the annotation of surgical tool detection. Our experiments show that our approach successfully detected the two different tools and outperformed the two baseline methods.