Ultrasound monitoring of microcirculation: An original study from the laboratory bench to the clinic.

OBJECTIVE: Monitoring microcirculation and visualizing microvasculature are critical for providing diagnosis to medical professionals and guiding clinical interventions. Ultrasound provides a medium for monitoring and visualization; however, there are challenges due to the complex microscale geometry of the vasculature and difficulties associated with quantifying perfusion. Here, we studied established and state-of-the-art ultrasonic modalities (using six probes) to compare their detection of slow flow in small microvasculature. METHODS: Five ultrasonic modalities were studied: grayscale, color Doppler, power Doppler, superb microvascular imaging (SMI), and microflow imaging (MFI), using six linear probes across two ultrasound scanners. Image readability was blindly scored by radiologists and quantified for evaluation. Vasculature visualization was investigated both in vitro (resolution and flow characterization) and in vivo (fingertip microvasculature detection). RESULTS: Superb Microvascular Imaging (SMI) and Micro Flow Imaging (MFI) modalities provided superior images when compared with conventional ultrasound imaging modalities both in vitro and in vivo. The choice of probe played a significant difference in detectability. The slowest flow detected (in the lab) was 0.1885 ml/s and small microvasculature of the fingertip were visualized. CONCLUSIONS: Our data demonstrated that SMI and MFI used with vascular probes operating at higher frequencies provided resolutions acceptable for microvasculature visualization, paving the path for future development of ultrasound devices for microcirculation monitoring.

DESIGN OF AN ULTRASOUND PROBE HOLDER TO MINIMIZE MOTION ARTIFACT DURING SONOGRAPHY.

Standard diagnostic ultrasound imaging procedures heavily rely on the human operator for image acquisition. This may lead to unnecessary artifacts in the images, since involuntary hand movement is unavoidable. Certain surgical procedures also involve "jump" movement of the subject on the operating table, further exacerbating image quality. In this study, we attempt to mitigate the problem by designing an ultrasound probe holder using 3D printing. This holder would potentially be light enough to attach to surgical retractors, thus eliminating operator intervention and relative motion between the probe and the patient.

Development of a Smart Hospital Assistant: Integrating Artificial Intelligence and a Voice-User Interface for Improved Surgical Outcomes.

Patient safety and efficiency are top priorities in any surgical procedure. One effective way to achieve these objectives is to automate the logistical and routine tasks that occur in the operating suite. Inspired by smart assistant technology already widely used in the consumer sector, we engineered the Smart Hospital Assistant (SHA), a smart, voice-controlled virtual assistant that handles natural speech recognition while executing non-surgical functions to aid any surgery. In simulated procedures, the SHA reduced operating time, optimized surgical staff resources, and reduced the number of major touch-points that can lead to surgical site infections. The SHA holds promise not only for use in the operating theater, but also in understaffed healthcare environments where automation can improve healthcare delivery.

Burden and Unmet Needs with Portable Oxygen in Patients on Long-Term Oxygen Therapy.

Rationale: Over 1.5 million Americans receive long-term oxygen therapy (LTOT) for the treatment of chronic hypoxemia to optimize functional status and quality of life. However, current portable oxygen equipment, including portable gas tanks (GTs), portable liquid tanks (LTs), and portable oxygen concentrators (POCs), each have limitations that can hinder patient mobility and daily activities. Objectives: To examine patient experiences with portable oxygen to guide equipment innovation and thereby improve patient care on oxygen therapy. Methods: The burden and unmet needs with portable oxygen equipment were assessed in 836 LTOT patients with chronic lung disease (chronic obstructive pulmonary disease [COPD], interstitial lung disease, and pulmonary hypertension) through an online survey. The survey included a combination of multiple-choice, Likert-scale, short-answer, and open-ended questions. Distribution was achieved through patient support organizations, including the U.S. COPD Coalition, the Pulmonary Fibrosis Foundation, and the Pulmonary Hypertension Association. Results: Improvements in portability were ranked as the highest priority by patients across all equipment types, followed by increases in the duration of oxygen supply for GTs, accessibility for LTs, and flow capabilities for POCs. All device types were found to be burdensome, with the greatest burden among GT users, 51% of whom characterized GT use as "strenuous" or "extremely strenuous" (high burden). POCs ranked as the most common (61%) and least burdensome devices; however, 29% of POC users still reported a high associated burden. Forty-seven percent of POC respondents described using a POC despite it not meeting their oxygen needs to benefit from advantages over alternative equipment. Among non-POC users, limited oxygen flow rate capabilities and cost were the top reasons preventing POC use. Conclusions: Although improvements have been made to portable oxygen equipment, this study highlights the burden that remains and reveals a clear need for advances in technology to improve the functional status and quality of life of portable LTOT users.

Automatic detection of cotton balls during brain surgery: Where deep learning meets ultrasound imaging to tackle foreign objects.

Cotton balls are a versatile and efficient tool commonly used in neurosurgical procedures to absorb fluids and manipulate delicate tissues. However, the use of cotton balls is accompanied by the risk of accidental retention in the brain after surgery. Retained cotton balls can lead to dangerous immune responses and potential complications, such as adhesions and textilomas. In a previous study, we showed that ultrasound can be safely used to detect cotton balls in the operating area due to the distinct acoustic properties of cotton compared with the acoustic properties of surrounding tissue. In this study, we enhance the experimental setup using a 3D-printed custom depth box and a Butterfly IQ handheld ultrasound probe. Cotton balls were placed in variety of positions to evaluate size and depth detectability limits. Recorded images were then analyzed using a novel algorithm that implements recently released YOLOv4, a state-of-the-art, real-time object recognition system. As per the radiologists' opinion, the algorithm was able to detect the cotton ball correctly 61% of the time, at approximately 32 FPS. The algorithm could accurately detect cotton balls up to 5mm in diameter, which corresponds to the size of surgical balls used by neurosurgeons, making the algorithm a promising candidate for regular intraoperative use.