Detecting circulating tumor cells via laser scanning

Chunjian Yang; Zhongjun Jiang; Songpo Guo

doi:10.1117/12.2604957

13 December 2021 Detecting circulating tumor cells via laser scanning

Chunjian Yang, Zhongjun Jiang, Songpo Guo

Proceedings Volume 12075, 10th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Intelligent Sensing Technologies and Applications; 1207509 (2021) https://doi.org/10.1117/12.2604957
Event: Tenth International Symposium on Advanced Optical Manufacturing and Testing Technologies (AOMATT 2021), 2021, Chengdu, China

Abstract

Circulating tumor cells (CTCs) are generally considered as seeds for metastases, serving as a clinical biomarker for cancer diagnosis and prognosis. However, they are difficult to detect due to their low content in the blood of cancer patients. Consequently detection of CTCs normally requires an antibody-mediated biological enrichment process, which is very time-consuming. In this work, we demonstrate an antibody-free, efficient, fast and cost-effective way of detecting CTCs. That is, CTCs are physically isolated by size using filtration, and subsequently characterized in an optical way via laser scanning. The filtered and stained blood sample, which is placed on a moving and spinning stage, is illuminated by a 405nm diode laser. Then the scattered optical signals are focused using an ellipsoidal mirror for a better photon collection. Eventually CTCs in the scanning image are identified and counted by the clustering algorithm. Our method has advantages in high efficiency and low cost, holding great promise for early diagnosis and prognosis prediction of cancer patients.

Citation Download Citation

Chunjian Yang, Zhongjun Jiang, and Songpo Guo "Detecting circulating tumor cells via laser scanning", Proc. SPIE 12075, 10th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Intelligent Sensing Technologies and Applications, 1207509 (13 December 2021); https://doi.org/10.1117/12.2604957

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KEYWORDS

Laser scanners

Tumors

Blood

Cancer

Image segmentation

Optical filters

Detection and tracking algorithms

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