Introduction: The high discordance currently identified in the scoring of breast cancer biomarkers ER, PR, Ki67 and Her2, which directly impact patient management, drives a growing clinical need for the development of diagnostic tests which will offer enhanced reproducibility while maintaining accuracy in a high throughput environment. We currently offer AQUA® technology in our clinical lab for breast cancer. A significant limitation to using this technology within a diagnostic laboratory is low throughput and manual annotation of patient invasive tumor. To address this, we evaluated the Vectra2™ automated multispectral slide analysis system to address these issues in a clinical environment with a focus on quality and pathologist involvement.

Materials and Methods: All results were generated using clinical samples. The Vectra system was used to acquire breast biomarker expression in invasive tumor regions scored by AQUA technology. The multi-step process of image acquisition was assessed in conjunction with the reproducibility of region selection for scoring as determined by invasive cancer tissue classifier algorithms developed through the use of Inform and Nuance applications. We also developed a review application to allow remote access to images prior to reporting of patient results.

Results: Normalization of system intensity compensation produced intensity values approaching unity. Algorithms defining invasive tissue score were found to be highly correlative (R2=0.949) to the current clinical platform with pathologist annotation. Together, these features resulted in acquisition of conserved regions of invasive tumor in a highly reproducible fashion, such that for the same sample on multiple days and instruments, R2=0.9571 (∼12%CV). Scores were consistent amongst varying parameters, including repeated scanning (∼9 %CV, n=13 runs) and differing field sampling parameters while decreasing time to 15 min per slide for processing with parallel analysis. Our development of the Vectra Review software enables visualization of regions selected for biomarker scoring that can be reviewed by clinical staff remotely, while not impacting overall workflow.

Conclusion: We show that the Vectra 2 platform is as accurate as our currently clinically validated platform for AQUA scoring of ER, PR, Her2, and Ki67. Introduction of advanced tissue finding algorithms concisely recognize relevant tissue regions unique to each biomarker without manual annotation, greatly improving the clinical workflow. This deployment of digitalized pathology results in a reduction of time to generate scores which marks a significant advance for our clinical lab. Overall, we demonstrate the AQUA paired Vectra2 system as a highly robust, reproducible and high throughput advance to our currently available diagnostic breast cancer platform, while addressing the need to easily allow for clinical lab and pathologist review.

Citation Format: Cristen K. Hays, Danielle Murphy, Bana Mouwakeh, Peter Miller, Clifford Hoyt, Jason Christiansen. Clinical validation of high throughput AQUA and multispectral imaging for breast cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2679. doi:10.1158/1538-7445.AM2013-2679