Photoacoustic lymphangiography provided a detailed, three-dimensional representation of the lymphatic vessels in the calf and their relationship with the surrounding venules. Background Detailed visualization of the lymphatic vessels would greatly assist in the diagnosis and monitoring of lymphatic diseases and aid in preoperative planning of lymphedema surgery and post...

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Lymphedema occurs when interstitial fluid and fibroadipose tissues accumulate abnormally because of decreased drainage of lymphatic fluid as a result of injury, infection, or congenital abnormalities of the lymphatic system drainage pathway. An accurate anatomical map of the lymphatic vasculature is needed not only for understanding the pathophysiology of lymphedema but also for surgical planning. However, because of their limited spatial resolution, no imaging modalities are currently able to noninvasively provide a clear visualization of the lymphatic vessels. Photoacoustic imaging is an emerging medical imaging technique that provides unique scalability of optical resolution and acoustic depth of penetration. Moreover, light-absorbing biomolecules, including oxy- and deoxyhemoglobin, lipids, water, and melanin, can be imaged. Using exogenous contrast agents that are taken up by lymphatic vessels, e.g., indocyanine green, photoacoustic lymphangiography, which has a higher spatial resolution than previous imaging modalities, is possible. Using a new prototype of a photoacoustic imaging system with a wide field of view developed by a Japanese research group, high-resolution three-dimensional structural information of the vasculatures was successfully obtained over a large area in both healthy and lymphedematous extremities. Anatomical information on the lymphatic vessels and adjacent veins provided by photoacoustic lymphangiography is helpful for the management of lymphedema. In particular, such knowledge will facilitate the planning of microsurgical lymphaticovenular anastomoses to bypass the excess fluid component by joining with the circulatory system peripherally. Although challenges remain to establish its implementation in clinical practice, photoacoustic lymphangiography may contribute to improved treatments for lymphedema patients in the near future.

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 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.