Slicer+PLUS: Collaborative, open-source software for ultrasound analysis

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Abstract The target users of the proposed Slicer+PLUS framework are researchers and developers who are focusing on low-cost point-of-care ultrasound (POCUS) applications. POCUS applications are characterized by utilizing low-cost, portable U/S systems; in the hands of novice operators; with novel data acquisition, signal processing, and machine learning methods; with imprecise trackers; and in highly unconstrained point-of-care environments, e.g.: at the scene of accidents for patient triage, in the offices of general practitioners for scoliosis detection and monitoring, in patients' homes for an aging population, as well as throughout hospitals. In these contexts, many are considering POCUS devices to be the stethoscopes of the future. The foundation of Slicer+PLUS is the integration and extension of 3D Slicer, PLUS, and MUSiiC. We are the developers of these libraries. We, and the users of our libraries, are proposing Slicer+PLUS so that the Slicer, PLUS, and MUSiiC communities can come together and cohesively address the important challenges and opportunities posed by POCUS applications. Over 30 letters of support are included with this application. 3D Slicer is a world-class, freely available open-source platform for medical image segmentation, registration, and visualization. PLUS is a world-class, open-source library for communicating with ultrasound machines and trackers (for following objects in 3D using magnetic, optical, and other technologies). MUSiiC is a (previously closed source) library that focuses on advanced ultrasound acquisition and analysis methods, such as ultrasound reconstruction pipelines, elastography, and photoacoustic imaging. Together, these toolkits have averaged over 5,100 downloads per month for the past year. A central tenant of our work is that POCUS applications should not be viewed as simply involving the use of inexpensive, portable U/S systems; POCUS must be viewed as a new modality for it to attain its full potential. POCUS must involve innovative, automated data analysis methods and workflows that can guide a user to properly place and manipulate an ultrasound probe and interpret the returned ultrasound data. In particular, the output of those workflows and analyses should be quantitative measures, not b-mode images, since the expertise to interpret such images will not be readily available at points-of-care. To that end, the proposed work goes well beyond simple integration of Slicer, PLUS, and MUSiiC. Multiple innovations are proposed such as Ultrasound Spectroscopy for tissue labeling, Dynamic Textures for anatomic localization of ultrasound probes, and self-tracking ultrasound probes. To assess our progress towards our goals, our team includes our target users: researchers, medical device manufacturers, and clinical innovators dedicated to low-cost POCUS applications. They will be validating our efforts by integrating them into their research and translational POCUS product development projects.