Tissue capture and recovery for molecular analyses such as immunostaining and gene expressionanalysis is important for gleaning information from tissue blocks relating to disease. The difficulty with existingsolutions is that if tissue recovery is envisioned, sectioning and recovering thin tissue sections from target tissuesor organs from an entire organism is not possible. Existing solutions provide manual tissue recovery, requiringthe operator to be present to determine whether or not to collect a section from a tissue of interest. To addressthis challenge, BioInVision will bring to market a 3D tissue imaging solution for preclinical applications that em-ploys automatic, deep-learning, on-the-fly target tissue recognition from a whole organism and semi-automatedtissue recovery. BioInVision pioneered the CryoVizTM instrument and has successfully commercialized fee-for-service CryoVizTM imaging for over 10 years. Our existing fee-for-service framework is well-adopted and em-braced by 75+ customers and institutions all over the world. High-resolution, broad-fluorescence-support (visibleand NIR fluorophores), high-sensitivity block-face CryoVizTM imaging of preclinical frozen tissue blocks createsanatomical brightfield and molecular marker fluorescence 3D microscopic image volumes. AI-based software fordeep-learning that will notify the operator in real-time upon encountering tissues of interest in color anatomy, orupon encountering molecular fluorescence such as eGFP cancer cells, enabling further interrogation of thesetissues either through ultra-high-resolution tissue imaging (2µm-scale), or semi-automatic tissue capture for his-tological analyses and immunostaining (what we term "image-guided histology"). Semi-automatic tissue capturethrough speed and temperature control will enable recovery of tissue for molecular analyses. A demonstrationproject is outlined that involves characterizing whole mice with fluorescent-reporter metastatic cancer cells andfluorophore-tethered cancer targeted imaging agent. Here, we will study distribution of breast cancer metastasesthroughout the whole mouse and co-localization with immune cells or disease biomarkers. Our solution will alsomake possible drug delivery studies with fluorescent tracers. It will enable tracking of multiple fluorescently la-beled markers of cell types helping one better understand the tumor micro-environment in cancer biology. It willreduce manual labor and personnel costs and lead to better throughput to enable image-guided histology. Thisnovel solution will cater to a wide variety of application areas including cancer biology, drug delivery, imagingagents and gene expression.
Public Health Relevance Statement: Narrative. We will create a 3D tissue imaging solution for preclinical applications that automatically identifies the
tissue being imaged and/or when a fluorescence signal is encountered during imaging so that tissue-of-interest
can be collected and processed. It will provide high resolution imaging with broad fluorescence support and
serve a wide variety of application areas including cancer biology, drug delivery, imaging agents and gene ex-
pression.
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