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FLIMX: A Software Package to Determine and Analyze the Fluorescence Lifetime in Time-Resolved Fluorescence Data from the Human Eye.

Klemm M, Schweitzer D, Peters S, Sauer L, Hammer M, Haueisen J - PLoS ONE (2015)

Bottom Line: Specifically, we introduce a new adaptive binning approach as an optimal tradeoff between the spatial resolution and the number of photons required per pixel.An overview of the visualization capabilities and a comparison of static and adaptive binning is shown for a patient with macular hole.FLIMX's applicability to fluorescence lifetime imaging microscopy is shown in the ganglion cell layer of a porcine retina sample, obtained by a laser scanning microscope using two-photon excitation.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, POB 100565, 98694, Ilmenau, Germany.

ABSTRACT
Fluorescence lifetime imaging ophthalmoscopy (FLIO) is a new technique for measuring the in vivo autofluorescence intensity decays generated by endogenous fluorophores in the ocular fundus. Here, we present a software package called FLIM eXplorer (FLIMX) for analyzing FLIO data. Specifically, we introduce a new adaptive binning approach as an optimal tradeoff between the spatial resolution and the number of photons required per pixel. We also expand existing decay models (multi-exponential, stretched exponential, spectral global analysis, incomplete decay) to account for the layered structure of the eye and present a method to correct for the influence of the crystalline lens fluorescence on the retina fluorescence. Subsequently, the Holm-Bonferroni method is applied to FLIO measurements to allow for group comparisons between patients and controls on the basis of fluorescence lifetime parameters. The performance of the new approaches was evaluated in five experiments. Specifically, we evaluated static and adaptive binning in a diabetes mellitus patient, we compared the different decay models in a healthy volunteer and performed a group comparison between diabetes patients and controls. An overview of the visualization capabilities and a comparison of static and adaptive binning is shown for a patient with macular hole. FLIMX's applicability to fluorescence lifetime imaging microscopy is shown in the ganglion cell layer of a porcine retina sample, obtained by a laser scanning microscope using two-photon excitation.

No MeSH data available.


Related in: MedlinePlus

Example of TCSPC data approximated by the multi-exponential model and the lens-corrected approach.TCSPC data obtained from a healthy volunteer is evaluated using adaptive binning (black) and approximated by the multi-exponential approach (left) using three exponential functions and the lens-corrected approach (right) using two exponential function and a separate measurement of the crystalline lens. The data are divided into three intervals: the pre-excitation interval (A), the fluorescence rising edge (B) and the fluorescence decay (C). The measured data and the multi-exponential model diverge due to the fluorescence of the crystalline lens in interval (B), which is magnified in the inset. The lens-corrected approach utilizes a scaled and shifted curve of a separate measurement of the crystalline lens to correct for the influence of the crystalline lens fluorescence in interval (B). For better visibility, the fluorescence intensity is plotted on a logarithmic scale. The fluorescence lifetimes of the exponential components (τ1, τ2, τ3), the average fluorescence lifetime τm as well figure of merit χ2 (Eqs 10 and 11) are shown next to the photon histogram.
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pone.0131640.g003: Example of TCSPC data approximated by the multi-exponential model and the lens-corrected approach.TCSPC data obtained from a healthy volunteer is evaluated using adaptive binning (black) and approximated by the multi-exponential approach (left) using three exponential functions and the lens-corrected approach (right) using two exponential function and a separate measurement of the crystalline lens. The data are divided into three intervals: the pre-excitation interval (A), the fluorescence rising edge (B) and the fluorescence decay (C). The measured data and the multi-exponential model diverge due to the fluorescence of the crystalline lens in interval (B), which is magnified in the inset. The lens-corrected approach utilizes a scaled and shifted curve of a separate measurement of the crystalline lens to correct for the influence of the crystalline lens fluorescence in interval (B). For better visibility, the fluorescence intensity is plotted on a logarithmic scale. The fluorescence lifetimes of the exponential components (τ1, τ2, τ3), the average fluorescence lifetime τm as well figure of merit χ2 (Eqs 10 and 11) are shown next to the photon histogram.

Mentions: An example of a time-resolved fluorescence signal from a single fundus-pixel from a healthy volunteer, approximated using the multi-exponential model (Eq 3) and the lens-corrected approach (Eq 8), is shown in Fig 3. There are three main intervals in the fluorescence signal: the pre-excitation interval, the fluorescence rising edge and the fluorescence decay. Usually in FLIM, the shape of the excitation pulse, the detector response function, dispersion in the optical pathway as well as relaxation processes directly after excitation and immediately before fluorescence emission determine the rising edge. In FLIO, the autofluorescence of the crystalline lens also affects the rising edge, as discussed above. The autofluorescence of the crystalline lens is visible as a shoulder in the rising edge in Fig 3 (inset).


FLIMX: A Software Package to Determine and Analyze the Fluorescence Lifetime in Time-Resolved Fluorescence Data from the Human Eye.

Klemm M, Schweitzer D, Peters S, Sauer L, Hammer M, Haueisen J - PLoS ONE (2015)

Example of TCSPC data approximated by the multi-exponential model and the lens-corrected approach.TCSPC data obtained from a healthy volunteer is evaluated using adaptive binning (black) and approximated by the multi-exponential approach (left) using three exponential functions and the lens-corrected approach (right) using two exponential function and a separate measurement of the crystalline lens. The data are divided into three intervals: the pre-excitation interval (A), the fluorescence rising edge (B) and the fluorescence decay (C). The measured data and the multi-exponential model diverge due to the fluorescence of the crystalline lens in interval (B), which is magnified in the inset. The lens-corrected approach utilizes a scaled and shifted curve of a separate measurement of the crystalline lens to correct for the influence of the crystalline lens fluorescence in interval (B). For better visibility, the fluorescence intensity is plotted on a logarithmic scale. The fluorescence lifetimes of the exponential components (τ1, τ2, τ3), the average fluorescence lifetime τm as well figure of merit χ2 (Eqs 10 and 11) are shown next to the photon histogram.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507995&req=5

pone.0131640.g003: Example of TCSPC data approximated by the multi-exponential model and the lens-corrected approach.TCSPC data obtained from a healthy volunteer is evaluated using adaptive binning (black) and approximated by the multi-exponential approach (left) using three exponential functions and the lens-corrected approach (right) using two exponential function and a separate measurement of the crystalline lens. The data are divided into three intervals: the pre-excitation interval (A), the fluorescence rising edge (B) and the fluorescence decay (C). The measured data and the multi-exponential model diverge due to the fluorescence of the crystalline lens in interval (B), which is magnified in the inset. The lens-corrected approach utilizes a scaled and shifted curve of a separate measurement of the crystalline lens to correct for the influence of the crystalline lens fluorescence in interval (B). For better visibility, the fluorescence intensity is plotted on a logarithmic scale. The fluorescence lifetimes of the exponential components (τ1, τ2, τ3), the average fluorescence lifetime τm as well figure of merit χ2 (Eqs 10 and 11) are shown next to the photon histogram.
Mentions: An example of a time-resolved fluorescence signal from a single fundus-pixel from a healthy volunteer, approximated using the multi-exponential model (Eq 3) and the lens-corrected approach (Eq 8), is shown in Fig 3. There are three main intervals in the fluorescence signal: the pre-excitation interval, the fluorescence rising edge and the fluorescence decay. Usually in FLIM, the shape of the excitation pulse, the detector response function, dispersion in the optical pathway as well as relaxation processes directly after excitation and immediately before fluorescence emission determine the rising edge. In FLIO, the autofluorescence of the crystalline lens also affects the rising edge, as discussed above. The autofluorescence of the crystalline lens is visible as a shoulder in the rising edge in Fig 3 (inset).

Bottom Line: Specifically, we introduce a new adaptive binning approach as an optimal tradeoff between the spatial resolution and the number of photons required per pixel.An overview of the visualization capabilities and a comparison of static and adaptive binning is shown for a patient with macular hole.FLIMX's applicability to fluorescence lifetime imaging microscopy is shown in the ganglion cell layer of a porcine retina sample, obtained by a laser scanning microscope using two-photon excitation.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, POB 100565, 98694, Ilmenau, Germany.

ABSTRACT
Fluorescence lifetime imaging ophthalmoscopy (FLIO) is a new technique for measuring the in vivo autofluorescence intensity decays generated by endogenous fluorophores in the ocular fundus. Here, we present a software package called FLIM eXplorer (FLIMX) for analyzing FLIO data. Specifically, we introduce a new adaptive binning approach as an optimal tradeoff between the spatial resolution and the number of photons required per pixel. We also expand existing decay models (multi-exponential, stretched exponential, spectral global analysis, incomplete decay) to account for the layered structure of the eye and present a method to correct for the influence of the crystalline lens fluorescence on the retina fluorescence. Subsequently, the Holm-Bonferroni method is applied to FLIO measurements to allow for group comparisons between patients and controls on the basis of fluorescence lifetime parameters. The performance of the new approaches was evaluated in five experiments. Specifically, we evaluated static and adaptive binning in a diabetes mellitus patient, we compared the different decay models in a healthy volunteer and performed a group comparison between diabetes patients and controls. An overview of the visualization capabilities and a comparison of static and adaptive binning is shown for a patient with macular hole. FLIMX's applicability to fluorescence lifetime imaging microscopy is shown in the ganglion cell layer of a porcine retina sample, obtained by a laser scanning microscope using two-photon excitation.

No MeSH data available.


Related in: MedlinePlus