SEATTLE, WA, April 16, 2018 (GLOBE NEWSWIRE) -- VisionGate, a clinical stage oncology pharmaceutical and diagnostics company, today presented a breakthrough research study demonstrated its Cell-CT™ platform can detect subtle changes in cellular and nuclear morphology of cancer-associated cells (CACs) as a result of the cancer field effect. These non-cancerous cells have been affected by the presence of the cancer cells and have undergone structural changes which include alterations in nuclear chromatin compaction – a phenomenon also known as Malignancy Associated Change (MAC). This is the first study report of VisionGate’s use of its Cell-CT 3D optical computed tomography platform to detect these changes in non-cancerous cells that presumably reside in tumor microenvironment. The study was presented at the 2018 American Association of Cancer Research (AACR) annual meeting in Chicago, Illinois.

A spectrum of change in the cellular composition is typical in patients with cancer so that malignant, pre-malignant and atypical cells are observed in biopsy specimens. Cell diagnosis is based on microscopic evaluation of cells on slides. This process is compromised by obscuration and fundamentally limited by the nature of 2D imaging. For many cells the changes imparted to them through the tumor field are so subtle that they fall beneath the threshold of human perception and are thus understood to be within normal limits. The Cell-CT platform renders cells through optical computed tomography and presents cells in true 3D with sub-micron resolution. The system characterizes the cells analytically and repeatably allowing measure of cell biosignatures that cannot be reliably perceived through human review.

The research presented was performed using cells that were within normal limits from patients with biopsy confirmed lung cancer and from donors who were cancer free. Cells from sputum were imaged by the Cell-CT platform which produced a set of morphometric biosignatures from each cell. The feature data was analyzed to select those features that best allowed detection of the cells from the cancer patients. The result was the creation of artificial intelligence (AI) networks to process cells from the risk population at large.
With this study, VisionGate has demonstrated these conclusions:

The Cell-CT platform improves upon cytology, can detect cell changes beyond human visual perception and, aided by artificial intelligence, can provide detailed insights into subtle morphological alterations that are beyond the capabilities of human visual perception.

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