Microscopic examination of formalin fixed, paraffin embedded (FFPE) tissue sections mounted on glass slides is the cornerstone of clinical histopathology. Ancillary molecular testing is often required for diagnosis, risk stratification, ad treatment planning, particularly in cancer. Molecular testing often involves mutation or expression analysis of nucleic acids (DNA and RNA) recovered from FFPE tissue sections. Due to tissue heterogeneity, nucleic acids are often isolated from dissected regions of the FFPE tissue section using current dissection methods, including: Manual Macrodissection, Manual Microdissection, and Laser Capture Microdissection (LCM). This Phase I grant application is for the development of an Automated Macrodissection Device for clinicians that significantly advances productivity and quality of results ahead of existing competitive devices and methods. The goal of the proposed Phase I project is to develop a novel system that encompasses a software application and user interface that will allow a pathologist to indicate an area of interet on a digital image of a tissue section. The software will transfer that area of interest to secondary slides on a new fully automated 12 slide tissue removal and recovery instrument. The new instrument will be a computer controlled system that will includes x.y.z positioning, integrated optics, and multiple choices of specialized tissue removal and recovery tips. Using image recognition the system will automatically identify the tissue section area of interest on the secondary slide, move the specialized tip over this area to displace tissue fragments from the slide surface, and simultaneously recover the liquid containing the suspended tissue section fragments for the ancillary molecular testing. The system will be based on dissection technology co.invented and exclusively licensed from the University of Utah's ARUP Laboratories. The subsequent commercial instrument would fill the need in the clinical market for a high throughput macrodissection (down to 0.25mm resolution) instrument with full automation, process monitoring and reporting, ease of use, with the recovery efficiency of manual dissection techniques, but with far better precision. The system will be validated for tissue image recognition capability, slide to slide scaling and registration, and the capability for integrationto primary digital pathology imaging systems. The system will also be validated for mechanical automation performance including both slide fiducial and automated x.y.? correction protocols for 12 slides as well as automated consumable loading and sample handling. Ultimately, the system will also be validated for dissection resolution, efficiency, and accuracy of tissue recovery. Validation strategies are defined based on a model system of digitally imaging system, 12 slide batches, and a defined set of tissue types and slide types. By quantifying the imaging, mechanical and dissection performance in Phase I on prototype instruments, we will demonstrate feasibility for Phase II development and commercialization.
The Automated Macrodissection Device will provide a highly affordable automated system for integrated digital slide imaging and walk-away tissue dissection and recovery for up to twelve slides per batch. The integrated imaging will expedite pathologist review of slides requiring microdissection and will enable consultation with expert pathologists via digital pathology. The system will improve process documentation and verification, enhancing the efforts toward electronic medical records. The device's technical performance includes a dissection resolution down to 0.25mm and an order of magnitude lower investment than that required for laser capture microdissection technologies, enabling much broader access to the new technology. The new device will promote productivity and quality of results for clinicians working in cancer diagnostics, as well as diverse areas of cancer and non-cancer research requiring high throughput tissue dissection from slides.
|Geiersbach, Katherine; Adey, Nils; Welker, Noah et al. (2016) Digitally guided microdissection aids somatic mutation detection in difficult to dissect tumors. Cancer Genet 209:42-9|