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Biomedical Optics & Medical Imaging

Absolute blood flow measured by optical methods

Monitoring of disease development and response to treatment could be improved by the use of optical coherence tomography in blood-flow measurement.
28 November 2011, SPIE Newsroom. DOI: 10.1117/2.1201111.003945

Absolute blood flow (volume of blood per unit time serving a tissue mass or organ) is a physiological parameter that becomes altered in many diseases. In the retina, blood-flow impairment may occur early in diseases such as glaucoma and diabetic retinopathy. In the brain, cerebral blood-flow loss occurs in conditions such as stroke and Alzheimer's disease. In the kidneys, renal blood flow is a primary factor in acute injury and other nephropathies. Whether a loss of blood flow directly causes cell death or merely reflects a reduction in tissue demand, in vivo blood flow measurements have the potential to improve understanding of disease processes and monitoring the response to treatment.

Optical coherence tomography (OCT) is a non-invasive imaging technology and a clinical standard in ophthalmology. It is also gaining popularity in other fields, such as cardiology. However, its primary use is to identify and quantify tissue structure in vivo. In contrast, our group uses Doppler OCT to provide objective measurements of absolute blood flow. This is particularly important because subtle functional and metabolic changes can precede visible structural changes in many pathologies.

Figure 1. (a) Diffusible tracer methods use the Fick principle to calculate blood flow from tracer kinetics. (b) Doppler optical coherence tomography (OCT) is based on direct measurements of flow in individual vessels. The composite arterial (FA) or venous flow (FV) must be normalized to an estimated tissue volume/mass (V) or assigned to an organ of interest to obtain an absolute measurement.

Classical methods to quantify cerebral blood flow, pioneered by Kety and colleagues,1–3 introduce a chemically inert tracer that diffuses freely across the blood-brain barrier. The Fick principle states that the quantity of a tracer taken up by a volume of tissue per unit time is equal to the product of the blood flow and the difference between arterial and venous concentrations. Therefore, blood flow can be calculated by measuring tracer concentrations in various compartments over time: see Figure 1(a). Further developments of this concept showed that, by locally recording tracer kinetics and applying the Fick principle, it is possible to determine local tissue blood flow. Similar ideas have been used in magnetic-resonance-imaging arterial spin labeling and positron-emission-tomography radiotracer methods to quantify tissue perfusion.

Our group is studying optical measurement of blood flow in individual vessels using Doppler OCT: see Figure 1(b).4,5 In our method, the flow in each vessel that supplies or drains a known tissue volume is optically measured. We sum these values together and normalize to a corresponding estimated tissue volume/mass or organ of interest. We assign flow to a known tissue volume/mass or organ in order to provide intersubject comparisons. This is necessary because flow in arbitrarily chosen individual vessels cannot be compared across subjects in a meaningful way due to intersubject variations in vascular topology. (Figure 2 shows an OCT angiogram6 of the vasculature of a rat somatosensory cortex showing a range of vessel sizes that correspond to a range of flows.) However, when we normalize flow to an estimated tissue volume/mass or organ (either supplied or drained), we obtain an absolute measure that can then be compared across subjects.

Figure 2. (a) OCT angiogram of a rat somatosensory cortex, acquired through a closed cranial window. (b) Zoom of a region of interest shows a labeled artery (A) and vein (V) supplying and draining the cortex respectively. In principle, assuming that all flow is supplied and drained via the cortical surface, cortical blood flow can be calculated by summing flow over either all diving arterioles or all ascending venules.

In the case of cortical measurements, we sum flow over either all diving arterioles or all ascending venules in a given cortical surface area. We then normalize this value to an estimated tissue volume/mass corresponding to this cortical surface area. The advantage of such direct vascular methods of measurement is that they do not require models of tracer uptake or clearance; instead, they require estimation of a tissue volume/mass and assume flow conservation at steady state.

Wang et al used Doppler OCT to quantify total retinal blood flow by measuring flow in all veins draining the retina.7 They used a dual circumpapillary scan, consisting of two circles around the optic nerve head that intersect all vessels draining the retina, to determine vessel angles. Recently, our group developed a simple technique of en face integration to calculate blood flow directly from volumetric Doppler OCT data without explicit calculation of vessel angles.8 This greatly simplifies flow measurements in individual vessels and the principle can be applied to calculate flow in any Doppler-based technique, such as OCT or ultrasound, where the axial projection of velocity is measured. Our group applied en face integration to calculate flow using Doppler OCT in the brain8 and other groups have applied the technique to the retina,9 and the kidneys.10 In particular, these results show that flow in the central retinal artery9 (49ul/min in a single subject) calculated by en face integration agrees reasonably well with flow summed across all retinal veins7 (53ul/min and 45ul/min in two different subjects) calculated using the dual circumpapillary scan.

Recently, our group compared Doppler OCT cerebral blood flow values to those obtained by the hydrogen clearance method, a classical technique based on kinetics of tissue hydrogen concentration measured with a platinum electrode. We found Doppler OCT and hydrogen clearance cerebral blood flow values to be linearly correlated across subjects when we measured both simultaneously.11 However, hydrogen clearance consistently produced lower blood flow values than Doppler OCT. While the reasons for this discrepancy require further investigation, it may be related to damage introduced by the insertion of the electrode, or systematic biases in the Doppler velocity estimation algorithm.

In conclusion, direct optical measurement of blood flow with Doppler OCT represents a novel and promising avenue for quantifying tissue perfusion at the microscopic level. Unlike tracer-based methods, Doppler OCT does not require a model of tracer uptake or clearance. Instead, Doppler OCT requires an accurate Doppler velocity estimation algorithm. Our future work will include algorithm development as these methods have the potential to become widespread in both clinical practice and in preclinical research.

Vivek Srinivasan
Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Harvard Medical School
Charlestown, MA

1. S. S. Kety, C. F. Schmidt, The nitrous oxide method for the quantitative determination of cerebral blood flow in man: theory, procedure and normal values, J. Clin. Invest. 27, pp. 476-483, 1948.
2. S. S. Kety, The theory and applications of the exchange of inert gas at the lungs and tissues, Pharmacol. Rev. 3, pp. 1-41, 1951.
3. O. Sakurada, C. Kennedy, J. Jehle, J. D. Brown, G. L. Carbin, L. Sokoloff, Measurement of local cerebral blood flow with iodo [14C] antipyrine, Am. J. Physiol. 234, pp. H59-66, 1978.
4. Z. Chen, T. E. Milner, D. Dave, J. S. Nelson, Optical Doppler tomographic imaging of fluid flow velocity in highly scattering media, Opt. Lett. 22, pp. 64-66, 1997.
5. J. A. Izatt, M. D. Kulkami, S. Yazdanfar, J. K. Barton, A. J. Welch, In vivo bidirectional color Doppler flow imaging of picoliter blood volumes using optical coherence tomography, Opt. Lett. 22, pp. 1439-1441, 1997.
6. R. K. Wang, S. L. Jacques, Z. Ma, S. Hurst, S. R. Hanson, A. Gruber, Three dimensional optical angiography, Opt. Express 15, pp. 4083-4097, 2007.
7. Y. Wang, B. A. Bower, J. A. Izatt, O. Tan, D. Huang, Retinal blood flow measurement by circumpapillary Fourier domain Doppler optical coherence tomography, J. Biomed. Opt. 13, pp. 064003, 2008.
8. V. J. Srinivasan, S. Sakadzic, I. Gorczynska, S. Ruvinskaya, W. Wu, J. G. Fujimoto, D. A. Boas, Quantitative cerebral blood flow with optical coherence tomography, Opt. Express 18, pp. 2477-2494, 2010.
9. B. Baumann, B. Potsaid, M. F. Kraus, J. J. Liu, D. Huang, J. Hornegger, A. E. Cable, J. S. Duker, J. G. Fujimoto, Total retinal blood flow measurement with ultrahigh speed swept source/Fourier domain OCT, Biomed. Opt. Express 2, pp. 1539-1552, 2011.
10. J. Wierwille, P. M. Andrews, M. L. Onozato, J. Jiang, A. Cable, Y. Chen, In vivo, label-free, three-dimensional quantitative imaging of kidney microcirculation using Doppler optical coherence tomography, Lab. Invest., 2011.
11. V. J. Srinivasan, D. N. Atochin, H. Radhakrishnan, J. Y. Jiang, S. Ruvinskaya, W. Wu, S. Barry, A. E. Cable, C. Ayata, P. L. Huang, D. A. Boas, Optical coherence tomography for the quantitative study of cerebrovascular physiology, J. Cereb. Blood Flow Metab. 31, pp. 1339-1345, 2011.