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Multiphoton microscopy (MPM) is an approach now well established in biomedical sciences, especially thanks to its excitation spectrum in the near infrared range (NIR). The simultaneous imaging of numerous of these substances imposes the use of a wideband excitation spectrum, indispensable in the case of in vivo and in live imaging or for detecting phenomena at video rates. A unique spectral bandwidth, covering the range between 750 and 1000 nm has been recently demonstrated and has made emerging a simplification in MPM: the excitation system is now no longer an lock for generating multiphoton images of numerous fluorophores. But such a solution might be highly sensitive to chromatic distortions and diffraction limit which might result in detrimental effects on image quality and especially on resolution performance. This question is at the core of the current presentation. A point-spread function (PSF) estimation is realized with a standard computational tool. Our experimental strategy has shown two interesting points. First, the resolution is preserved in the lateral plan (xy) regardless of the excitation procedure chosen. Second, a significant deterioration of the resolution is observed in the axial direction (z), with a factor 4 between the best resolution obtained with a standard imaging procedure and the worst one obtained with the wider spectral bandwidth. Starting with this result, the role of a computational solution of image reconstruction is highlighted for reducing the gap observed in axial resolution between standard and wideband excitation solution of MPM. The illustration of the interest of a large spectral bandwidth of excitation is then shown on a mouse muscle sample presenting 3 fluorophores having a spectral bandwidth of excitation spread along 300 nm. This set of experiments illustrates the impact of chromatic distortions and diffraction limit on the deterioration of resolution. As a conclusion, a basic protocol for image reconstruction is used in order to highlight the interesting level of improvement of the visual image quality generated by a standard computational image restoration.
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