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* Helmholtz Centre for Infection Research, Junior Research Group Immunodynamics, D-38124 Braunschweig, Germany;
Institute of Physical and Theoretical Chemistry, Technical University of Braunschweig, D-38106 Braunschweig, Germany;
LaVision Biotec GmbH, 33607 Bielefeld, Germany; and
Institute for Applied Neuroscience, 39120 Magdeburg, Germany
Correspondence: Address reprint requests to Matthias Gunzer, PhD, Helmholtz Centre for Infection Research, Junior Research Group Immunodynamics, Inhoffenstrasse 7, D-38124 Braunschweig Germany. Tel.: 49-531-6181-3130; Fax: 49-531-6181-3199; E-mail: mgunzer{at}helmholtz-hzi.de; or to Raluca Niesner, PhD, Technical University of Braunschweig, Institute of Physical and Theoretical Chemistry, Hans-Sommer Strasse 10, D-38106 Braunschweig, Germany. Tel.: 49-531-391-5346; Fax: 49-531-391-5396; E-mail: raluca.niesner{at}tu-bs.de.
Two-photon microscopy is indispensable for deep tissue and intravital imaging. However, current technology based on single-beam point scanning has reached sensitivity and speed limits because higher performance requires higher laser power leading to sample degradation. We utilize a multifocal scanhead splitting a laser beam into a line of 64 foci, allowing sample illumination in real time at full laser power. This technology requires charge-coupled device field detection in contrast to conventional detection by photomultipliers. A comparison of the optical performance of both setups shows functional equivalence in every measurable parameter down to penetration depths of 200 µm, where most actual experiments are executed. The advantage of photomultiplier detection materializes at imaging depths >300 µm because of their better signal/noise ratio, whereas only charge-coupled devices allow real-time detection of rapid processes (here blood flow). We also find that the point-spread function of both devices strongly depends on tissue constitution and penetration depth. However, employment of a depth-corrected point-spread function allows three-dimensional deconvolution of deep-tissue data up to an image quality resembling surface detection.
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