Rolling into the genome: linking mutations to cellular structure through label-free holographic cytometry

TL;DR

This paper introduces a label-free method to detect leukemia mutations by analyzing cell shape using holographic imaging and virtual reality.

Contribution

The novel use of holo-tomographic flow cytometry and concave segmentation to link NPM1 mutations with nuclear morphology in leukemia cells.

Findings

Holo-tomographic flow cytometry enables label-free phenotyping of acute myeloid leukemia blasts.

A concave segmentation algorithm quantifies NPM1-mutation-associated cup-like nuclear morphologies.

Virtual reality visualization enhances the analysis of 3D cell morphology changes.

Abstract

Holo-tomographic flow cytometry for label-free phenotyping of suspended acute myeloid leukemia blasts is demonstrated. A concave segmentation algorithm is applied to 3D refractive index tomograms to quantify NPM1-mutation-associated cup-like nuclear morphologies, with virtual reality visualization offering engaging immersion. The method enables population-level detection of statistically significant shifts in 3D cell morphology, originally correlating phenotype with genotype.

Holo-tomographic flow cytometry allows label-free phenotyping of acute myeloid leukemia blasts, originally correlating phenotype with genotype. A concave segmentation algorithm is applied to 3D refractive index tomograms to quantify NPM1-mutation-associated cup-like nuclear morphologies, with virtual reality visualization offering engaging immersion.

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