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Abstract
Fluorescence lifetime imaging ophthalmoscopy (FLIO) provides information on fluorescence lifetimes in two spectral channels as well as the peak emission wavelength (PEW) of the fluorescence. Here, we combine these measures in an integral three-dimensional lifetime-PEW metric vector and determine a normal range for this vector from measurements in young healthy subjects. While for these control subjects 97 (±8) % (median (interquartile range)) of all para-macular pixels were covered by this normal vector range, it was 67 (±55) % for the elderly healthy, 38 (±43) % for age-related macular degeneration (AMD)-suspect subjects, and only 6 (±4) % for AMD patients. The vectors were significantly different for retinal pigment epithelium (RPE) lesions in AMD patients from that of non-affected tissue (p < 0.001). Lifetime- PEW plots allowed to identify possibly pathologic fundus areas by fluorescence parameters outside a 95% quantile per subject. In a patient follow-up, changes in fluorescence parameters could be traced in the lifetime-PEW metric, showing their change over disease progression.
© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
Fluorescence can be described by different measures such as quantum yield, excitation and emission spectra, fluorescence lifetime, and anisotropy. In biomedical imaging, all these measures can reveal information on the physiological state of tissue as well as pathologic alterations [1].
Observation of the ocular fundus autofluorescence (FAF) is an established technique of ophthalmic diagnostics [2]. FAF intensity may be quantified [3]. A more detailed quantification of fluorescence parameters became possible by the introduction of fluorescence lifetime imaging ophthalmoscopy (FLIO) [4–6], which records the fluorescence decay per pixel in an image in two spectral channels providing us with two mean fluorescence lifetimes τm (one per channel) and the peak emission wavelength (PEW) of the fluorescence emission spectrum. Among other applications, FLIO was shown to reveal early pathologic alteration of the retinal pigment epithelium in age-related macular degeneration AMD [7–11].
Combining these parameters of fluorescence may be of advantage for a more comprehensive investigation of retinal pathology. In a clinical setting, however, it might be difficult to overlook a variety of parameters. Therefore, here we describe a metric, combining spectral and lifetime information from FLIO, and explore its possible application for ophthalmologic diagnostics.
2. Methods
2.1 FLIO measurement
FLIO is described in detail elsewhere [12–14]. FLIO image capturing is based on a picosecond laser diode coupled with a laser scanning ophthalmoscope (Spectralis, Heidelberg Engineering GmbH, Heidelberg, Germany), exciting retinal autofluorescence at 473 nm with a repetition rate of 80 Mhz. Fluorescence photons were detected by time-correlated single photon counting (SPC-150, Becker & Hickl GmbH, Berlin, Germany) in a short-wavelength (SSC: 498–560 nm) and a long-wavelength spectral channel (LSC: 560–720 nm). FLIO provides 30-degree field images with a frame rate of nine frames per second and a resolution of 256 × 256 pixels. Photon histograms over time, describing the autofluorescence decay, were least-square fitted with a series of three exponential functions using the software SPCImage 6.0 (Becker & Hickl GmbH, Berlin, Germany). The amplitude-weighted mean decay time τm was used for further analysis. The peak emission wavelength (PEW) of the fluorescence was determined from the ratio of photon counts (autofluorescence intensity) in SSC and LSC as described by Schultz et al. [15].
2.2 Data analysis and representation
All data analysis was implemented in the software FLIMX, which is documented and freely available for download under an open-source BSD license (http://www.flimx.de) [16]. As shown in Fig. 1, along with an FAF intensity image (Fig. 1(a)), FLIO provides images of FAF lifetimes in SSC and LSC (Fig. 1(b) and (c)) and the PEW (Fig. 1(d)). All information from Fig. 1(b), (c), and d was combined as a lifetime – PEW metric in one 3D-vector (τm –SSC, τm –LSC, PEW) per pixel (Fig. 1(e)). As, however, this 3D-representation is difficult to survey, we present projections in τm –LSC and τm –SSC direction (Figs. 1(f) and (g), respectively) throughout this paper. As we found these lifetime vs. PEW plots well structured, we manually marked rectangular regions of interest (ROI) representing the macula, the optic disc, the retinal vessels, as well as the retina and retinal pigment epithelium (RPE) (Fig. 2). For this purpose, the borders of the ROI were adjusted stepwise till the pixels inside the ROI represent the respective anatomical entities (Fig. 2(right)). This gave us individual ROI borders for each subject (Fig. 3).
Fig. 1. Representation of FAF parameters in a young, healthy subject: (a) fluorescence intensity (LSC), (b) fluorescence lifetime (SSC, the standard ETDRS-grid is shown), (c) fluorescence lifetime (LSC), (d) PEW, (e) 3-D plot of lifetimes and PEW, (f) projection of (e) in τm –LSC direction, (g) projection of (e) in τm –SSC direction.
Fig. 2. lifetime vs. PEW plot (left, SSC, same as Fig. 1(f)). Lifetime – PEW combinations representing the macula, optic disc, retinal vessels and retina/RPE (right) are marked by respective rectangles.
Fig. 3. Box plots of the lower and upper border of lifetime and PEW regions found for macula, optic disc, vessels, and retina/RPE in young, healthy subjects. The range between the median values is marked by respectively colored bars. Top left: lifetime (SSC), bottom: PEW, top right: region-specific color-coded lifetime – PEW plot.
Next, we defined normative lifetime and PEW data for young healthy subjects by determining ROI borders representing most of the pixels of the macula, optic disc, and retina/RPE in all subjects of the respective cohort (see 2.3). A standard ETDRS-grid, as it is used in many clinical studies, was placed onto the FAF images and centered at the macula (Fig. 1(b)). The percentage of pixels within the inner and outer ring of the grid with lifetime-PEW metric vectors covered by the cubic ROI of norm values for the retina/RPE in young healthy controls, was determined for this group as well as for other cohorts of healthy subjects and AMD patients (paragraph 2.3).
For individual patients, an ROI, covering all pixels within the 2.5th to 97.5th (τm) or 5th to 100th (PEW) percentile of each component of the metric vector (τm –SSC, τm –LSC, PEW) was established and pixels outside the ROI were considered as potentially pathologic. In order to exclude values from the optic disc and the macula, only vectors for pixels within the inner and outer ring of the ETDRS-grid were considered for further analysis. The macula was excluded since the macular pigment can cause variability of fluorescence parameters independent from pathology.
Finally, pathologic entities such as dysmorphic or migrated RPE were marked in the FAF images. The metric vectors of the respective pixels were analyzed statistically (see 2.4) and highlighted in the lifetime – PEW plots in different color and the change of their fluorescence properties over follow-up investigations of the patients was visualized by changes of the metric vectors in the plot.
2.3 Subjects
In order to test our lifetime-PEW metric, we used data from previous studies [11,12,17]. All investigations were carried out according to the guidelines of the Declaration of Helsinki. The studies were approved by the ethics committee of the University Hospital Jena and all subjects gave their informed consent to the investigations as well as the use of the data for further scientific analysis. We included 37 young healthy control subjects (mean age: 23.6 ± 3.6 years), 24 AMD patients (79.1 ± 5.8 years), and 32 undiagnosed elderly subjects. The latter were grouped in 21 elderly healthy (71.9 ± 8.1 years) and 11 AMD-suspect subjects (71.7 ± 11.3 years) due to inspection of FAF and optical coherence tomography (OCT) recordings. There was no statistically significant difference in mean age between the elderly healthy and the AMD-suspect. The AMD patients were significantly older than the elderly healthy (p = 0.003) but not as the AMD-suspect. As the fluorescence of the natural lens is known to interfere with the FAF in elderly subjects [17], in the groups elderly healthy, AMD suspect, and AMD only pseudophakic subjects were included.
2.4 Statistics
Subject cohort median values of percentages of pixels, covered by the normative lifetime – PEW vector ROI for retina/RPE, were compared by Kruskal-Wallis test. Subsequent Mann-Whitney U-tests were performed for pairwise comparison of single groups. In order to correct for multiple testing in four cohorts, the significance level was set to p < 0.0125. These tests were performed in SPSS 28.0 (IBM Corp., Armonk, NY, U.S.A.).
The means of lifetime – PEW metric vectors for different entities in an image, such as dysmorphic or migrated RPE and unaffected tissue, were compared by MANOVA (Matlab R2021a, The Mathworks Inc., Natick, MA).
3. Results
In the lifetime – PEW plot, the macula, optic disc, vessels, and retina/RPE are clearly distinguished by specific areas of lifetimes and PEW combinations (Fig. 2(left)). The borders of these areas were determined for each subject in the young healthy cohort; boxplots of these upper and lower borders are shown in Fig. 3.
Considering the ranges between the respective medians of the lower and upper border, describing lifetimes and PEW separately for the entities macula, optic disc, vessels, and retina/RPE, we see that these ranges greatly overlap. If we, however, use a combination of PEW and lifetime (shown for SSC in Fig. 3), the entities can be clearly separated (right upper part of Fig. 3).
This allowed us to determine ranges of the lifetime – PEW space, in which the majority of pixels of the macula, optic disc, and retina/RPE were found for the young controls. The borders of these ranges are given in Table 1. The retinal vessels were not considered as their fluorescence is (i) generally weak, (ii) highly variable in lifetime and PEW (see Fig. 2(left)), and (iii) of no clinical relevance.
Table 1. Ranges of lifetimes and PEW representing macula, optic disc, and retina/RPE in young healthy subjects
Within the inner and outer ring of the ETDRS-grid, the average percentage (median (interquartile range)) of pixels inside the normal range of lifetimes and PEW for retina/RPE was 97 (8) % for the young controls, 67 (55) % for the elderly healthy, 38 (43) % for the AMD-suspect, and 6 (4) % for the AMD patients (Fig. 4, two outliers are indicated by open circles in the AMD patients). The percentages were significantly different between the groups (p < 0.001 in Kruskal-Wallis test). Also, pairwise comparisons by Mann-Whitney U-test showed significant differences (p = 0.007 for elderly healthy vs. AMD suspect, all other comparisons p < 0.001). For illustration, Fig. 5 shows the FAF intensity image (left) and the pixels within the lifetime – PEW range of young healthy controls (shown in white, right side, also outside of the ETDRS rings) for a control (top) and a subject with early AMD (bottom).
Fig. 4. Rate of pixels within the borders of lifetime – PEW metric established for young healthy controls (Table 1)
Fig. 5. All pixels within the lifetime – PEW range of young healthy controls for retina / RPE (shown in white, right side) in a control (top) and a subject with early AMD (bottom). FAF intensity images are shown left. For statistical analysis (see text) only pixels within the inner and outer ring of the ETDRS grid, depicted right, were evaluated.
Pathologic RPE lesions (confirmed in fundus photography and OCT) were found in 12 out of the 24 AMD patients. These regions were marked manually in the images and the respective lifetime – PEW vectors were compared with that of non-affected pixels within the inner and outer ring of the ETDRS-grid. The vectors were significantly (p < 0.001) different in all patients. An example is given in Fig. 6 (top). RPE lesions can be distinguished as hyperpigmentation and RPE cells, detached from the underlying Bruch’s membrane and migrated into the retina. In 6 patients, we found both entities. The lifetime – PEW vectors for hyperpigmentation and migrated RPE were significantly different (p < 0.001 to 0.025; example in Fig. 6(bottom)).
Fig. 6. left: FAF intensity images (top left: SSC, pathological RPE alterations marked orange, all other pixels blue, bottom left LSC, hyperpigmentation marked in orange, migrated RPE in blue, for color fundus photography see Fig. 7, middle left). Lifetime – PEW plot of pixels of pathologically altered RPE (orange) vs. non-affected pixels in the inner and outer ring of the ETDRS-grid in an AMD patient (top right and middle). Bottom: Separation of the pixel of altered RPE in hyperpigmentation (orange) and migrated RPE (blue).
Furthermore, the lifetime – PEW metric can be used to automatically identify pixels within the FAF image, which have altered fluorescence properties. For this purpose, we established a cube within the lifetime – PEW space, comprising 95% of all pixels inside the ETDRS grid. All pixels outside this 95% Quantile were highlighted as suspicious in the fundus image. This is shown in Fig. 7 in three examples.
Fig. 7. Fundus photographs of three patients suffering from intermediate AMD (left) semi-transparently overlaid with the respective FAF images (middle) and masks, showing pixels of the lifetime – PEW cube with fluorescence lifetimes and PEW outside the 95% Quantile of the ETDRS grid as dark spots (right)
Finally, the fate of pathologic fundus lesions can be tracked over time in the lifetime – PEW plots. As an example, Fig. 8 shows an AMD patient at baseline and at a follow-up investigation 56 months later. Fundus photography (not shown here), FAF-, and OCT imaging showed a spot of hyperpigmentation (red arrowhead), which developed into a detachment of RPE cells and subsequent migration into the retina (see intra-retinal hyper-reflective foci in Fig. 8(f)) along with an increase of the fluorescence intensity. The lifetime – PEW plots reveal a change in fluorescence properties. Besides a general broadening of the lifetime as well as PEW range with a shift towards shorter PEW and longer lifetimes (Fig. 8(c), (d), (g), and h, blue pixels), a clear change in lifetimes and PEW of the RPE lesion (orange pixels) upon RPE migration in the follow-up is visible.
Fig. 8. FAF images (a and e), OCT (b and f), and lifetime – PEW metric (c and g: SSC, d and h: LSC) of an AMD patient at baseline investigation (a-d) and 56 months later (e-h). The red arrowhead points to an RPE lesion which was hyperpigmented in fundus photography (not shown), hyperfluorescent in FAF (a and e, red arrowhead). OCT reveals an elevation and slight thickening of the RPE at baseline (b). At follow up, the fluorescence increased (e) and the OCT showed an RPE detachment with hyperreflective spots inside the retina indicating migrating RPE cells detached from Bruch’s membrane. The lifetime –PEW plots (c, d, g, h) show pixels within the inner and outer ring of the ETDRS grid in blue and pixels of the RPE lesion in orange at baseline (c, d) and follow-up (g, h).
4. Discussion
Previous investigations have described pathologic changes in fluorescence lifetimes [7–11,18–21] or emission spectra [22–26] as possible biomarkers in AMD and other retinal and systemic diseases [27–44]. Here, for the first time, we introduce an integral description of FAF by a lifetime – PEW metric. This approach might help clinicians to survey molecular changes, indicated by alterations in fluorescence properties, at a glance rather than examining various parameters provided by FLIO. Thus, it gives the doctor a rapid hint on eventual pathology and where to find it by automatic highlighting suspect structures as shown in three examples in Fig. 7. For research purposes, this comprehensive description of fluorescence properties in one vector allows to describe pathologic lesions and retrieve their alteration over follow-up investigations. It allows to separate the fluorescence of the macula, the optic disk, the retinal vessels, and the retina/RPE despite overlap in lifetime and PEW alone (Fig. 3). Furthermore, the lifetime – PEW metric approach provided normative ranges within this metric, which can be addressed to the fluorescence of the macula, the optic disk, and the retina/RPE in young, healthy subjects (Table 1). The comparison of the metric from individual patients with this norm ranges can show the deviation of their lifetime – PEW combination from a healthy state and it also can indicate, which retinal areas are affected. The example in Fig. 5 shows abnormal para-macular fluorescence in AMD, which is in agreement with the literature [8].
In particular, RPE lesions, considered a risk factor for disease progression in AMD [45–47], were shown to have significantly different lifetime – PEW vectors than the fluorescence of non-affected retina/RPE at the posterior pole. This suggests a change in fluorophore composition or of their environment. This seems to be a gradual process, starting with an early activation of RPE cells and proceeding over a thickening of the cell layer to intra-retinal migration and finally atrophy. Morphologic RPE changes can be observed using OCT. However, OCT should be complemented with FLIO in a multimodal imaging approach such as proposed by Nan et al. [48]. This requires techniques to present a vast amount of information in a form clinicians can survey quickly in their everyday routine. The lifetime – PEW metric can provide that in different ways. Besides a general comparison of patients to normative lifetime – PEW vectors from a control cohort, addressed above, the determination of quantiles for each metric component can point to fundus areas (pixels in the FAF image), which have abnormal fluorescence properties. These areas are suspect to show pathology and highlighting them in a multimodal imaging approach may draw the clinician’s attention to them (Fig. 7). But the lifetime – PEW metric also may provide evidence for the difference in pathologic and apparently healthy tissue as well as pathologic alterations in different stages on a molecular level by comparing the respective metric vectors by a MANOVA.
Although it will not be possible to identify RPE lesions directly from their lifetime – PEW vectors, the graphical representation of the lifetime – PEW plot shows differences in fluorescence properties of healthy tissue and RPE lesions in an intuitive way (Fig. 6). Tracing the lifetime – PEW vectors of a certain lesion in the follow-up of the patient shows cellular alterations on a multidimensional scale. This might help researchers develop new ideas on the fate of cells on a molecular level. This always needs the consideration of all vector components from both spectral channels as LSC is dominated by the fluorescence of lipofuscin whereas SSC represents also other fluorophores [14].
An alternative way to characterize fluorescence by a vector would be the phasor approach [49]. However, we did not pursue this here as the phasor (i) is not well structured for retinal fluorescence, (ii) does not include spectral information, and (iii) is less intuitive in interpretation than the lifetime-PEW combination.
The main limitation of our approach is that only molecular changes, resulting in alterations in fluorescence lifetimes and/or PEW, can be made visible. Furthermore, deviations of the lifetime – PEW vector from the range of young healthy subjects, should not be over-interpreted. Certainly, there is a continuous change of fluorescence properties from young healthy tissue over normal ageing to pathologic alteration. Thus, finding a certain percentage of pixels outside the normal range can give hints to possible pathology. However, this measure alone should not be regarded as a diagnostic marker but should always be combined with other symptoms, possibly found in the specific patient. Similarly, pixels outside a predefined quantile range of the lifetime – PEW vector components within one subject can point to pathology, but doesn’t do necessarily. As the quantile is only a statistical measure, also in healthy subjects, pixels (e.g. representing retinal vessels or the macula) must be outside a given range. Nevertheless, this approach may be helpful as it can alert the clinician about possible pathology. Another limitation arises from the manual adjustment of ROI borders for the anatomic entities macula, optic disc, retinal vessels, and the retina / RPE. Although this may result in somewhat arbitrary ROI borders, adjustment is well possible in a way selecting lifetime and PEW ranges representing the respective entities (Fig. 2(right)).
In summary, in this methodological approach we don’t present new data but a different, integral way to look at the FLIO data by combining lifetime and spectral information. This may help clinicians to see possible pathology at a glance, and it may help researchers to survey fluorescence changes in a more general way. We showed that on RPE lesions in AMD as an example. More research is needed to evaluate the benefit of this method in the FLIO analysis of other pathologic entities.
Funding
Thüringer Aufbaubank (2019 FGR 0083).
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are available in Refs. [11, 12, and 17]. All data analysis was implemented in the software FLIMX [16], which is documented and freely available for download under an open-source BSD license (http://www.flimx.de).
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