Tissue clearing refers to a group of chemical techniques used to turn tissues transparent. ^{[1] [2] [3]} This allows deep insight into these tissues, while preserving spatial resolution. ^[1] Many tissue clearing methods exist, each with different strengths and weaknesses. ^{[2] [4]} Some are generally applicable, while others are designed for specific applications. ^[4] Tissue clearing is usually combined with one or more labeling techniques and subsequently imaged, most often by optical sectioning microscopy techniques. ^{[1] [5] [6]} Tissue clearing has been applied to many areas in biological research. ^[7]

In the early 1900s, Werner Spalteholz developed a technique that allowed the clarification of large tissues, ^{[2] [8]} using Wintergrünöl ( methyl salicylate) and benzyl benzoate. ^[9] Over the next hundred years, various scientists introduced their own variations on Spalteholz's technique. ^[8] Tuchin et al. introduced TOC in 1997, adding a new branch of tissue clearing that was hydrophilic instead of hydrophobic like Spalteholz's technique. ^{[1] [10]} In 2007, Dodt et al. developed a two step process, wherein tissues were first dehydrated with ethanol and hexane and subsequently made transparent by immersion in benzyl alcohol and benzyl benzoate (BABB), a technique they coupled with light sheet fluorescence microscopy. ^{[2] [3]} Hama et al. developed another hydrophilic approach, Scale, in 2011. ^{[2] [8]} The following year, Ertürk et al. developed a hydrophobic approach called 3DISCO, in which they pretreated tissue with tetrahydrofuran and dichloromethane before clearing it in dibenzyl ether. ^{[3] [8]} A year later, in 2013, Chung et al. developed CLARITY, the first approach to use hydrogel monomers to clear tissue. ^{[2] [3] [8]}

Tissue opacity is thought to be the result of light scattering due to heterogeneous refractive indices. ^{[1] [4] [5]} Tissue clearing methods chemically homogenize refractive indices, resulting in almost completely transparent tissue. ^{[4] [6]}

While multiple classification standards for tissue clearing exist, the most common classifications use the chemical principle and mechanism of clearing to group tissue clearing methods. ^[1] These include hydrophobic clearing methods, ^{[1] [2] [6]} which may also be known as organic, ^[3] solvent-based, ^{[4] [5]} organic solvent-based, ^{[11] [12]} or dehydration ^[13] clearing methods; hydrophilic clearing methods, ^{[1] [2] [6]} which may also be known as aqueous-based ^{[5] [11]} or water-based ^[13] methods, and may be further sub-categorized into simple immersion ^[4] and hyperhydration ^[4] (also called delipidation/ hydration ^[5]); and hydrogel-based clearing methods, which may also be known as detergent ^[3] or hydrogel embedding ^{[4] [5] [11]} methods. Tissue-expansion clearing methods use hydrogel, and may be included under hydrogel-based clearing ^[2] or as their own category. ^[1]

Common methods include those of the DISCO family, including 3DISCO, and CLARITY and related protocols. ^{[1] [2] [3]} Others include BABB, ^{[1] [2] [4]} PEGASOS, ^{[1] [2] [4]} SHANEL, ^{[1] [5]} SeeDB, ^{[1] [2] [4]} CUBIC, ^{[1] [2] [4]} ExM, ^{[1] [2] [4]} and SHIELD. ^{[1] [4] [5]}

Tissue clearing methods have varying compatibility with different methods of fluorescent labeling. ^{[1] [5] [6]} Some are better suited to pre-clearing tagging approaches, such as genetic labeling. ^{[1] [5]} while others require post-clearing tagging, such as immunolabeling and chemical dye labeling. ^{[1] [5]}

After clearing and labeling, tissues are typically imaged using confocal microscopy, ^{[11] [12] [13]} two-photon microscopy, ^{[1] [5] [11]} or one of the many variants of light-sheet fluorescence microscopy. ^{[7] [11] [12]} Other less commonly used methods include optical projection tomography ^{[1] [5]} and stimulated Raman scattering. ^{[5] [7] [11]}

Imaging cleared tissues generates massive volumes of complex data, which requires powerful computational hardware and software to store, process, analyze, and visualize. ^{[1] [6] [13]} A single mouse brain can generate terabytes of data. ^{[2] [6] [13]} Both commercial and open-source software exists to address this need, some of it adapted from solutions for two-dimensional images and some of it designed specifically for the three-dimensional images produced by imaging of cleared tissues. ^{[1] [11] [12]}

Tissue clearing has been applied to the nervous system, ^{[1] [2] [3] [4] [5] [6] [7] [11] [14] [15]} bones (including teeth), ^{[7] [11] [12] [16] [17] [18]} skeletal muscles, ^{[7] [18] [19]} hearts and vasculature, ^{[7] [11] [20]} gastrointestinal organs, ^{[7] [21]} urogenital organs, ^{[7] [11] [22]} skin, ^{[7] [23]} lymph nodes, ^[7] mammary glands, ^[7] lungs, ^[7] eyes, ^[7] tumors, ^{[7] [11]} and adipose tissues. ^{[7] [11]} Whole-body clearing is less common, but has been done in smaller animals, including rodents. ^{[1] [6] [7]} Tissue clearing has also been applied to human cancer tissues ^{[24] [25]}