Computational adaptive optics powers long-term 3D dual-modal live-cell imaging

Microscopy is a vital tool for exploring the mysteries of life, enabling scientists to observe the dynamic changes of cells and organelles across spatial and temporal scales. However, because cells are primarily composed of water and exhibit low refractive-index contrast, it remains challenging to clearly visualize their internal structures. In recent years, Intensity Diffraction Tomography (IDT), an emerging label-free 3D imaging technique, has attracted increasing attention. Instead of relying on fluorescent dyes, IDT directly exploits the intrinsic refractive-index distribution of cells for imaging, thereby avoiding phototoxicity and photobleaching and making it particularly suitable for long-term live-cell observation. When combined with 3D fluorescence microscopy, this dual-modal approach can simultaneously provide molecular specificity and global structural information, offering a powerful tool for deciphering cellular components and their interactions. Nevertheless, long-term imaging (from several hours to days) is often hindered by the optical complexity of cells, environmental thermal drift, and mechanical instabilities of the microscope, which lead to time-varying aberrations and focal drift. Achieving stable, high-quality tracking of subcellular structures over extended periods therefore remains a key challenge.

To address these challenges, the research team from the Smart Computational Imaging Laboratory (SCILab) at Nanjing University of Science and Technology, led by Prof. Chao Zuo, has developed a novel adaptive optics-assisted 3D dual-modal imaging approach (AO-FIDT). The results were published in Laser & Photonics Reviews (Vol. 19, Issue 15, August 2025) and selected as the front cover article of the issue. In this work, the authors established an imaging framework that integrates adaptive-optics aberration correction with IDT. Based on an iterative ptychographic algorithm, the method effectively disentangles 3D IDT reconstructions and time-varying aberrations directly from label-free intensity images. The estimated aberrations are then dynamically incorporated into the system point spread function (PSF) to synchronously correct 3D fluorescence reconstructions and enhance image quality. With this technique, the researchers achieved long-term, high-spatiotemporal-resolution 3D dual-modal reconstructions, providing a robust tool for stable tracking of subcellular structures.

“With adaptive optics, we can achieve long-term, high spatiotemporal resolution observation and tracking of subcellular structures without additional hardware or complex post-processing,” said Prof. Zuo. “This is the unique charm of computational optics.”

The team conducted a series of experiments using the self-developed ZRICON 3000 label-free 3D dual-modal microscope to validate the performance and stability of AO-FIDT. With a ring-shaped, numerical-aperture-matched illumination configuration, the IDT module achieved 175 nm lateral and 775 nm axial resolution at 7.5 volumes/s (160 × 160 × 30 μm³). Image stacks acquired through axial scanning in the fluorescence module further assisted IDT in resolving cellular structures. With adaptive optics, imaging stability was markedly enhanced. Even when pronounced time-varying aberrations arose from environmental thermal drift and mechanical instabilities, AO-FIDT clearly and stably tracked the dynamics and morphological changes of subcellular organelles over extended periods.

Prof. Zuo emphasized the transformative potential of AO-FIDT, stating: “AO-FIDT integrates label-free diffraction tomography with fluorescence imaging, delivering not only exceptional spatiotemporal resolution but also a balance between global structural visualization and molecular specificity, offering broad application prospects in cell and subcellular research.”

Looking ahead, Prof. Zuo and his team plan to integrate fluorescence super-resolution techniques—such as structured illumination microscopy (SIM)—into AO-FIDT. By leveraging SIM’s super-resolution capability and low phototoxicity, the system can provide additional biomolecular specificity, including fine structural details of subcellular organelles such as mitochondrial cristae. This dual-modal synergistic strategy not only addresses limitations of existing 3D fluorescence methods but also opens a new avenue for comprehensive exploration of cellular and subcellular dynamics, with the potential to significantly advance bioimaging.

The research team noted: “This is the first application of adaptive optics in 3D dual-modal imaging, enabling long-term, high spatiotemporal resolution cellular imaging. It underscores the significant potential of AO-FIDT as a non-invasive imaging tool for biomedical research, including drug screening, cellular analysis, and dynamic subcellular monitoring.”

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Reference
Authors: Ning Zhou^1,2,3, Runnan Zhang^1,2,3, Ruizhi Zhu^1,2,3, Zihao Zhou^1,2,3, Hongjun Wu^1,2,3, Qian Chen ^1,2,3, Jiasong Sun ^4,, Chao Zuo^1,2,3,4, , Chao Zuo^1,2,3,4,
DOI: https://doi.org/10.1002/lpor.202570059
Affiliations: ¹Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China
²Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China
³Jiangsu Key Laboratory of Visual Sensing & Intelligent Perception, Nanjing, Jiangsu Province 210094, China
⁴School of Physics, Xidian University, Xi’an Province 710126, China

About The Smart Computational Imaging Laboratory in Nanjing University of Science and Technology, China
The Smart Computational Imaging Laboratory (SCILab: www.scilaboratory.com), led by Professor Chao Zuo, is affiliated to the “Spectral Imaging and Information Processing” Innovation Team of the Ministry of Education's Changjiang Scholar and the first batch of “National Huang Danian-style Teacher Team”, led by Professor Qian Chen, the leader of the national first-level key discipline of optical engineering at Nanjing University of Science and Technology. The laboratory is committed to developing a new generation of computational imaging and sensing technologies. The research results have been published in more than 270 SCI journals, of which 46 papers were selected as cover papers of journals such as Light, Optica, AP, PhotoniX, etc., 25 papers were selected as ESI highly cited/hot papers, and the papers have been cited nearly 20,000 times.

About Professor Chao Zuo from Nanjing University of Science and Technology, China
Professor Chao Zuo, the academic leader of the Smart Computational Imaging Laboratory, is a distinguished professor of the Ministry of Education's Changjiang Scholars Program, a Fellow of SPIE | Optica | IOP, and is selected as a Clarivate Analytics Highly Cited Scientist in the World. He has won the Fresnel Prize of the European Physical Society, the first prize of the Technological Invention Award of the Chinese Society of Optical Engineering, the first prize of the Basic Category of the Jiangsu Science and Technology Award, and the “Special Commendation Gold Award” of the Geneva International Invention Exhibition.