@article {69655,
	title = {Rapid Whole-Organ Characterization via Quantitative Light-Sheet Microscopy},
	journal = {Laser \& Photonics Reviews},
	year = {2024},
	month = {2024 Oct 22},
	pages = {2401177},
	abstract = {<p>Whole-organ imaging and characterization at a submicron level provide abundant information on development and diseases while remaining a big challenge, especially in the context of time load. Herein, a quantitative light-sheet microscopy platform that enabled highly time-efficient assessments of fibrous structures within the intact cleared tissue is developed. Dual-view inverted selective plane illumination microscopy (diSPIM), followed by improved registration and deconvolution, led to submicron isotropic imaging of mouse upper genital tract with one hundred-fold speed-ups than previous efforts. Further, optical metrics quantifying 3D local density and structural complexity of targets based on parallel and vectorized convolution in both spatial and frequency domains are developed. Collectively, ≈400{\textendash}2000 fold increases in time efficiency counting for imaging, postprocessing, and quantitative characterization compared to the traditional method is gained. Using this platform, automatic identification of medulla and cortex within the mouse ovary at over 90\% overlap with manual selection by anatomy experts is achieved. Additionally, heterogeneous distributions of immune cells in the mouse ovary and fallopian tube, offering a unique perspective for understanding the immune microenvironment are discovered. This work paves the way for future whole-organ study, and exhibits potential with promise for offering mechanistic insights into physiological and pathological alterations of biological tissues.</p>
},
	keywords = {immune microenvironment, light-sheet microscopy, quantitative characterization, whole-organ imaging},
	doi = {10.1002/lpor.202401177},
	url = {https://doi.org/10.1002/lpor.202401177},
	author = {Chen, Lingmei and Su, Yijun and Qian, Shuhao and Zhou, Lingxi and Han, Tao and Wang, Chuncheng and Jiang, Rushan and Ding, Zhihua and Guo, Min and Liu, Zhiyi}
}
