Detection of apoptotic and necrotic cell death using holographic microscopy

Kabir, Md. Alamgir; Kharel, Ashish; Malla, Saloni; Kreais, Zachary J.; Nath, Peuli; Wolfe, Jared N.; Hassan, Marwa; Kaur, Devinder; Tiwari, Amit K.; Ray, Aniruddha

doi:10.1117/12.2609690

Cited by 1 publication

(1 citation statement)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The fluorescence-based microscopy techniques require labeling the cells with different fluorophores such as Calcein, Propidium Iodide, fluorescently labeled Annexin V [41][42][43] and others. Label-free techniques such as quantitative phase imaging (QPI), phase contrast microscopy [44][45][46][47], Raman microspectroscopy [48][49][50][51][52], and digital holography [53,54] have also been explored as alternative modalities to visualize (and quantify) some of the morphological hallmarks of cell death, such as cell shape factor, volume, blebbing, shrinkage, and membrane rupture, amongst others. In Phase contrast microscopy [55], the change in phase of light passing through and interacting with sample is visualized as a change in brightness in the image and is not quantitative.…”

Section: Introductionmentioning

confidence: 99%

Label-free identification of cell death mechanism using scattering-based microscopy and deep learning

Khoubafarin,

Kharel,

Malla

et al. 2023

J. Phys. D: Appl. Phys.

Self Cite

View full text Add to dashboard Cite

The detection of cell death and identification of the mechanism underpins many of the biological and medical sciences. A scattering-based microscopy-based method is presented here for identifying, measuring, and quantifying cell death in breast cancer cells using a label-free approach. We identify apoptosis and necrosis pathways by analyzing the temporal changes in morphological features of the cells. Moreover, a neural network was trained to identify the cellular morphological changes and classify cell death mechanisms automatically, with an accuracy of over 95%. A pre-trained network was tested on images of cancer cells treated with different chemotherapeutic drugs, which were not used for training, and it correctly identified cell death mechanisms almost 100% of the time. This automated method will allow for quantification during the incubation steps without the need for additional steps, typically associated with conventional technique like fluorescence microscopy, western blot and ELISAs. As a result, such studies will be faster and cost effective.

show abstract