Abstract 2465: Aperio manual scan software: beta testing for challenging slide imaging in research
Abstract Purpose: The Aperio Manual Scan feature was developed to improve whole slide imaging for challenging samples, including faintly stained, sparse, or artifact-laden slides. This study evaluated the feature's usability and its ability to address imaging challenges. Experimental Procedures: Fifteen challenging slides, including cytospins, wet tissue touch preps, immunohistochemistry (IHC), and in situ hybridization (ISH) samples, were scanned during a beta test at a pharmaceutical research facility. Laboratory scientists and technicians used the manual scan feature to adjust scan areas, focus points, and calibration points. Participants provided feedback through a structured questionnaire. Results: Of 15 slides, 6 were successfully scanned using the automated workflow, while 9 required manual adjustments. The manual scan feature allowed successful imaging of sparse or faintly stained specimens, precise exclusion of artifacts, and focus optimization for multi-plane samples such as cell pellet arrays. Users highlighted the feature's intuitive interface and its ability to generate high-quality images for previously unscannable slides. Conclusions: The Aperio Manual Scan software enhances flexibility and precision in whole slide imaging, complementing the automated workflow. It allows researchers to overcome imaging challenges efficiently and is anticipated to benefit research facilities significantly. Citation Format: Erica Pawlak, Shubham Dayal, Elizabeth Sullivan, Jacob Persky, Diane Robirds, Timothy Murphy-Stevens, Duff Pickering. Aperio manual scan software: beta testing for challenging slide imaging in research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2465.
Authors
- Diane Robirds
- Duff Pickering
- Erica A. Pawlak
- E. Sullivan
- Shubham Dayal
- Jacob Persky
- Timothy Murphy-Stevens
Institutions
- Cascade Biosystems (United States) (US)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1158/1538-7445.am2025-2465
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00