Chapter 10

Core Messages

■Studies of metabolism can be performed with regard to the external or the internal aspect at the fundus.

■The external aspect of metabolism is characterised by parameters of microcirculation (blood flow, oxygen saturation).

■The internal aspect describes the cellular metabolism.

■The cellular metabolic state can be determined by the fluorescence of endogenous fluorophores.

■The fluorescence of redox pairs NAD+ / NADH and FAD/FADH depends on the availability of the dissolved oxygen.

■Several other substances fluoresce in ocular tissue.

■Fluorophores can be discriminated by excitation and emission spectra as well as by decay of fluorescence intensity (lifetime).

■The transmission of ocular media hinders the excitation of fluorophores in their maxima below 400 nm.

■Several fluorophores emit a weak fluorescence below 560 nm.

■The fundus fluorescence above 560 nm is dominated by lipofuscin.

■Lifetime measurements are independent of fluorophore concentration and absorption into the surrounding tissue.

■Lifetime measurements permit the discrimination of a weakly emitting fluorophore whose emission spectrum is covered by a strongly emitting fluorophore.

■A fluorescence lifetime mapping ophthalmoscope permits excitation at different wavelengths and time-resolved fluorescence measurements of two spectral ranges (490–560 nm, 560–700 nm).

■The results of up to three exponential approximations of fluorescence decay can be presented in images, histograms and cluster diagrams of lifetimes or of amplitudes.

■Early phases of age-related macular degeneration (AMD) can be discriminated from healthy subjects by lifetimes t1 and t2 in the short-wavelength channel and by t2 in the long-wavelength channel.

■Reduced metabolic activity can be demonstrated in arterial branch occlusion.

■Regions of reduced metabolism can be found in mild non-exudative diabetic retinopathy.

10.1  Aspects of Metabolism

The first pathological signs occur in metabolism. Thus, an important goal in ophthalmic research is to find the methods of objective evaluation of retinal metabolism. The metabolism in the retina can be considered with regard to the external and the internal aspects. The external aspect is characterised by blood flow in arterioles and in venules. The blood flow as blood volume/time can be calculated from measurements of the physical parameters, such as blood velocity and vessel diameter. In addition to blood flow, the concentration of metabolites is important in the blood, e.g. oxygen saturation. In this

way, the supply and the consumption of oxygen can be determined in retinal tissue according to (10.1) [1]:

Assuming a blood flow Q = 21 µL/s, an arterial oxygen saturation OSa = 95%, a total haemoglobin concentration/4 ctotal = 8.9 mmol/L and a transport effectiveness h0, which means that 1 mol O2 (32 g) is transported by 1 mol haemoglobin (»16,100 g), and the tissue is supplied with 0.358 ng/s of oxygen. If the arterio-venous difference

108 10  Metabolic Mapping

OSa–v = 35%, then the consumption of oxygen is about 0.132 ng/s in the supplied retinal tissue.

Different methods for the measurement of the blood flow have been published, determined as volume/time.

10  Most accurate in clinical application is the measurement of blood velocity by bi-directional laser Doppler anemometry and the simultaneous determination of vessel diameter[2].Newdevelopmentsinopticalcoherencetomography are promising for the determination of blood flow simultaneously in multiple vessels of a 3D retina volume [3].

The measurement of oxygen saturation in the retinal vessels has been a subject of research for several years. The simplest methods are based on reflection measurements at two wavelengths. One measurement is performed at an isosbestic point, where the extinction coefficients of reduced and oxygenated haemoglobin are identical. The other is done at a wavelength with the largest difference between the two components of haemoglobin. Despite this latter method being a raw approximation of the interaction between light and blood, several studies use the algorithm, which is described in Beach et al. [4]. In the most accurate method for the measurement of oxygen saturation, a complete reflection spectrum is detected [1, 5]. The oxygen saturation is then calculated by an approximation of this spectrum by the complete extinction spectrum of haemoglobin and oxyhaemoglobin. In addition to the absorption, the scattering of light is also included in the model function. The oxygen saturation can be determined in an artery, a vein and also in the retinal tissue, simultaneously.

On studying the oxygen saturation in the retinal vessels in early diabetes, no change in arterial oxygen saturation was found in relation to age-matched controls, but venous oxygen saturation was increased [6]. In other words, the consumption of oxygen was reduced, indicating a virtual over-supplying of the retinal tissue. These measurements demonstrate the limitation of measurements of oxygen saturation, because in diabetic tissue, there is a lack of oxygen.

There has been no technical solution for the simultaneous measurement of blood flow and oxygen saturation until now. Such a solution would be helpful for the interpretation of the complicated control mechanism of blood flow and oxygen saturation.

Measurements of the external aspect of metabolism are necessary, but they are not sufficient.

The internal aspect of metabolism describes the basic mechanisms, e.g. of energy production. These processes are glycolysis, the citrate acid cycle, the respiratory chain and oxidative phosphorylation, and act inside the cells in cytosol (glycolysis) and mitochondria (citrate acid cycle) [7]. They require metabolites, e.g. glucose and dissolved oxygen,

which have to diffuse through the vessel wall and cell membranes. Here, an increased resistance of diffusion might explain the discrepancy between increased venous oxygen saturation and lack of oxygen in the cells in diabetes.

Besides the mechanisms of energy production, the internal aspect of metabolism also includes processes like accumulation of pigments, e.g. the macular pigment xanthophyll, as protection against energy-rich radiation, metabolic end products like lipofuscin, or advanced glycation end products (AGEs). The formation of scars can also be considered a result of changed internal metabolism.

The internal aspect of metabolism can be studied by the fluorescence of endogenous fluorophores. Of special interest are changes in the fluorescence of the redox pairs NAD+/ NADH (oxidised and reduced nicotinamide adenine dinucleotide) and FAD/FADH2 (flavin adenine dinucleotide). These redox pairs act as electron transporters in the basic mechanisms of energy production. The change in fluorescence of both the redox pairs allows an estimation of the availability of oxygen inside the cells. The reduced form, NADH, emits fluorescence if there is a relative lack of oxygen, whereas the oxidised NAD is non-fluorescent. In contrast, the oxidised FAD fluoresces if there is sufficient oxygen and the reduced FADH2 exhibits no fluorescence. Unfortunately, the fluorescence of these redox pairs is covered by the fluorescence of several other fluorophores in the ocular tissue. Most prominent is the fluorescence of lipofuscin, which accumulates in the cells of the retinal pigment epithelium, especially in age-related macular degeneration (AMD). Glycolised proteins (AGEs) are found in the lens and fundus tissue in diabetic patients. All connective tissues contain the fluorophores collagens and elastin. The fluorophores pyridoxal and protoporphyrin IX act in haem synthesis. The amino acids such as tryptophan, tyrosine, and kynurenine also emit strong fluorescence.

However, the problem is how these fluorophores, can be discriminated from each other. There are three properties that are characteristic of each fluorophore. The excitation spectrum describes the wavelength range in which the energy of light is high enough to move the electrons from the singlet ground state, S0, to an excited singlet state, S1 or higher. The excitation spectrum characterises the structure of the excited state. Through a radiation-less internal conversation, the electrons move from the higher excited states in the first excited state, S1. It is also possible for the electrons to move from higher excited singlet states into excited triplet states via intersystem crossing.

The electrons go back from the S1 state to the singlet ground state S0 in the time scale of psto ns-emitting fluorescence light. This fluorescence spectrum is the second characteristic parameter of each fluorophore. It characterises the structure of the ground state. The wavelength

of the fluorescence light is longer than the excitation light. Besides the emission of fluorescence light, there is also a radiation-less relaxation. Both processes depopulate the excited singlet state S1. The inverse sum of the emission rate G and the non-radiative decay rate knr is the mean lifetime t of electrons in the excited state (10.2):

The lifetime tis the third parameter for characterising each fluorophore.

The lifetime tis detectable as the decay rate of normalised fluorescence intensity. On the other hand, the spin orientation of electrons is anti-parallel in S1 and S0, and the spins are parallel in the excited triplet state T1 and the singlet state S0. Hence, relaxation from T1 to S0 is forbidden and occurs much longer than fluorescence as phosphorescence in the millisecond time scale.

The shape of both the excitation and the emission spectrum are influenced by the absorption spectrum of the neighbouring substances. Furthermore, a strongly emitted fluorescence spectrum covers the fluorescence spectra of weakly emitting fluorophores. Thus, the discrimination of a single fluorophore is difficult in a mixture of absorbing and fluorescing substances. In contrast, the fluorescence lifetime is independent of the absorption in the neighbourhood. Strongly and weakly emitting fluorophores can be separated from each other, if the lifetimes are sufficiently different. The lifetime is independent of the fluorophore concentration. As the lifetime depends on viscosity, pH and temperature, information can be attained about the embedding matrix of the cells.

10.2  Limiting Conditions for the Discrimination

of Fluorophores at the Ocular Fundus

The discrimination of fluorophores according to the excitation and emission spectra, and according to fluorescence lifetime, is limited under the conditions of the measurements at the ocular fundus. There are four specific limitations. First, the transmission of the ocular media permits spectral measurements at the fundus only between 400 and 900 nm [8]. The absorption edge of the crystalline lens is at 400 nm and the cornea absorbs the light for wavelengths shorter than 350 nm. Above 900 nm, the light is absorbed by water. Second, the eye is a moving object. That is, measurements of long duration, which are required for a good signal-to-noise ratio (SNR), are impossible at the same position of the fundus. Thus, eye trackers or methods of image registration are required. The next limitation is related to the anatomy of the eye. The eye consists of

several layers, e.g. cornea, lens, vitreous, nerve fibre layer, receptor layer, retinal pigment epithelium and choroid. Nearly the same fluorophores act in all these layers. Thus, in the fluorescence detected, all the emission spectra are superimposed, independent of the point of origin. The influence of lens fluorescence during fundus measurements can be suppressed to a certain degree by confocal laser scanning or by the principle of aperture division. By applying two-photon excitation, the fluorescence is observed to originate only at the focus of the imaging system. Thus, a discrimination of emitting layers is possible in principle. As the threshold between obtaining fluorescence and damaging the fundus tissue is low, the twoor multiphoton technique is a subject of research for fundus imaging [9]. The most important limitation is the maximal permissible exposure for fluorescence measurements in the eye [10]. To obtain an SNR that is high enough, a number of fluorescence images taken under weak excitation should be averaged. The eye movement during the measurement must be compensated for by image registration.

10.3  Excitation and Emission Spectra

and Fluorescence Lifetimes of Expected

Endogenous Fluorophores and Ocular Tissue

Optimal discrimination of fluorophores should include specific excitation and emission as well as measurement of fluorescence lifetime. To find the required spectral ranges and lifetime scale, the excitation and emission spectra and the lifetimes of the isolated substances were determined by Schweitzer et al. [11].

Table 10.1 shows these data. The excitation and emission maxima for collagen and elastin are given by Sionkowska et al. [12]. The absorbance spectra of both components of connective tissue are partly detectable in the visible spectrum. The corresponding emission spectra are detectable up to 650 nm. The lifetime of FAD and NADH changes between the free and the protein-bound state. Besides own measurements [11], the lifetime of free FAD is given as 2.05 ns [13] and 2.3 ns [14]. According to Nakashima et al. [15], the lifetime of the FAD monomer is 140 ps and that of the FAD dimer 40 ps. The quantum yield of the FAD monomer is higher than that of the FAD dimer. Skala et al. [13] determined the lifetime of protein-bound FAD to be about 100 ps.

Reversed behaviour is valid for NADH. The fluorescence lifetime of free NADH was determined to be 300 ps [16] and 400–500 ps [17]. The fluorescence lifetime of protein-bound NADH increases to 1 ns [18], 2 ns [16] and 2–2.5 ns [17].

Elastin

Collagen 1

Collagen 2

Collagen 3

Collagen 4

Ocular tissue

Retina

RPE

Choroid

Sclera

Cornea

Lens

Intensity

Wavelength in nm

Fig. 10.1  Excitation spectra of the structures in porcine eyes

The ratio of amplitudes of free and protein-bound NADH is an indicator of cellular metabolism [18]. It gets reduced if the energy is increasingly delivered under anaerobic conditions.

To investigate whether discrimination of ocular structures might be possible according to the excitation and

emission spectra as well as the fluorescence lifetime, these parameters were measured in isolated structures of porcine eyes [19]. Figure 10.1 shows the excitation spectra, detected by the changes in the fluorescence intensity at 460 nm. This wavelength was chosen because it corresponds to the emission maximum of NADH.

norm. Intensity

0.2Choroid

Aqueous humor

0

370 420 470 520 570 620

Frequency

The fluorescence spectra of these tissues are presented in Fig. 10.2. The excitation was at 350 nm. As demonstrated in these diagrams, spectral discrimination of the ocular structures is quite difficult. No accumulation of ageing pigment lipofuscin was detectable in the retinal pigment epithelium of these young animals. The strong fluorescence of the crystalline lens is remarkable up to 520 nm.

Better discrimination of ocular structures was reached by fluorescence lifetime measurements, as demonstrated in Fig. 10.3. The fluorescence was excited by laser pulses

of 100 ps full width at half maximum at 446 nm. The dynamic emission was detected in the spectrum from 490 to 700 nm.

The decay of fluorescence intensity was bi-exponen- tially approximated. The shortest lifetimes were detected in the RPE (maximal tm = 260 ps) and the neuronal retina (maximal tm = 460 ps). The lifetime histograms of lens (maximal tm = 1,320 ps) and cornea (maximal tm = 1,420) are quite similar just as of choroid (maximal tm = 1,700 ps) and sclera (maximal tm = 1,780 ps).