Download PDF
Klin Monbl Augenheilkd 2025; 242(04): 384-391
DOI: 10.1055/a-2469-8403
Klinische Studie

Evaluation of Reproducibility of Measurements of Peripapillary Blood Flow with Laser Speckle Flowgraphy in Healthy and POAG Subjects

Evaluation der Reproduzierbarkeit der Messung des peripapillären Blutflusses durch Laser Speckle Flowgraphy bei Gesunden und Patienten mit primärem Offenwinkelglaukom
Alexander von Vopelius-Feldt
1   Ophthalmology, University Hospital Zurich, Switzerland
,
Timothy Hamann 
1   Ophthalmology, University Hospital Zurich, Switzerland
,
Andreas Mayr
2   Institute for Medical Biometry and Statistics, Philipps-University-Marburg, Germany
,
Marc Töteberg-Harms
3   Ophthalmology, Department of Ophthalmology & Visual Sciences, University of Iowa Health Care, Iowa City, IA, United States
› Author Affiliations
› Further Information
Also available at
    Permissions and Reprints

Abstract

Background Peripapillary blood flow is of diagnostic value in glaucoma.

Material and Methods We investigated the reproducibility of peripapillary blood flow measurements in healthy individuals and in open-angle glaucoma (OAG) patients with the Nidek laser speckle flowgraphy (LSFG)-NAVI system. Blood flow was calculated as the mean of vascular area (MV), mean of tissue area (MT), and mean of overall flow (MA). Intra-rater, inter-session, and inter-rater reproducibility were assessed by determining the intraclass correlation coefficient (ICC) and coefficient of variance (COV).

Results There were 28 healthy subjects and 16 patients with OAG who participated in this prospective single-center trial. ICC and COV of intra-rater reproducibility were assessed in MV as 0.901; 6.424, MT as 0.909; 4.025, and MA as 0.965; 4.168. Inter-session reproducibility yielded ICC and COV values of MV (0.834; 9.223), MT (0.904; 6.215), MA (0.909; 7.069). Inter-rater reproducibility was computed for MV as 0.78; 9.758, MT as 0.890; 7.210, and MA as 0.888; 6.942. There was a significant difference in MA (p = 0.0184) between the healthy individuals (mean 36.299) and the OAG group (mean 24.944), which was not observed for MV (p = 0.0735) or MT (p = 0.1351).

Conclusion High reproducibility of measurements of peripapillary blood flow with the LSFG system was demonstrated in both groups. There is a difference in peripapillary blood flow between healthy controls and OAG patients.

Zusammenfassung

Hintergrund Die peripapilläre Perfusion hat einen diagnostischen Wert beim Glaukom.

Material und Methoden Wir untersuchten die Reproduzierbarkeit der Messung der peripapillären Durchblutung bei gesunden Personen und bei Patienten mit Offenwinkelglaukom (OAG). Die peripapilläre Durchblutung wurde durch die Nidek Laser Speckle Flowgraphy (LSFG) im NAVI-System ermittelt. Der Blutfluss wurde als Mittelwert des Gefäßbereichs (MV), Mittelwert des Gewebebereichs (MT) und Mittelwert des Gesamtflusses (MA) berechnet. Die Intrarater-, Intersession- und Interrater-Reproduzierbarkeit wurden durch Bestimmung des Intraklassen-Korrelationskoeffizienten (ICC) und des Variationskoeffizienten (COV) bewertet.

Ergebnisse 28 gesunde Probanden und 16 Patienten mit OAG nahmen an dieser prospektiven Single-Center-Studie teil. Der ICC und COV der Intrarater-Reproduzierbarkeit wurden für MV mit (0,901; 6,424), MT (0,909; 4,025), MA (0,965; 4,168) berechnet. Die Intersession-Reproduzierbarkeit ergab ICC- und COV-Werte von MV (0,834; 9,223), MT (0,904; 6,215), MA (0,909; 7,069). Die Interrater-Reproduzierbarkeit wurde für MV mit 0,78; 9,758, MT 0,890; 7,210, MA 0,888; 6,942 berechnet. Es zeigte sich ein signifikanter Unterschied für MA (p = 0,0184) zwischen den gesunden Probanden (Mittelwert 36,299) und der OAG-Gruppe (Mittelwert 24,944). Ein Signifikanzniveau, dass sich nicht für MV (p = 0,0735) oder MT (p = 0,1351) darstellte.

Schlussfolgerung Es wurde eine hohe Reproduzierbarkeit der Messungen der peripapillären Durchblutung mit dem LSFG-System in beiden Gruppen nachgewiesen. Es zeigt sich ein Unterschied im peripapillären Blutfluss zwischen gesunden Probanden und OAG-Patienten.

Keywords

glaucoma - perfusion - laser speckle flowgraphy

Schlüsselwörter

Glaukom - Perfusion - Laser Speckle Flowgraphy

Supplement

    Detailed comparative values of ONH flow analysis between the healthy controls and the OAG group as mean blur rate of vessels (MV) and tissue (MT) and combined analysis of vessels and tissue (MA), individual measurements for the superior (S), temporal (T), inferior (I) and nasal (N) sector and the respective subsegments nasal (n), central (c), temporal (t), superior (s), and inferior (i) [please compare [Fig. 1], i.e., SnT refers to S the superior sector, n the nasal subsegment of the superior sector, and T to the measurement of the blur rate over the tissue] are available as supplementary material.

  • Supporting Information


Publication History

Received: 14 July 2024

Accepted: 12 November 2024

Article published online:
18 December 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

 

  • References

  • 1 Türksever C, Todorova MG. Peripapillary Oxygenation and Retinal Vascular Responsiveness to Flicker Light in Primary Open Angle Glaucoma. Metabolites 2022; 12: 597
    CrossrefPubMedSearch in Google Scholar
  • 2 Melgarejo JD, Maestre GE, Mena LJ. et al. Normal-tension glaucomatous optic neuropathy is related to blood pressure variability in the Maracaibo Aging Study. Hypertens Res 2021; 44: 1105-1112
    CrossrefPubMedSearch in Google Scholar
  • 3 Gugleta K, Kochkorov A, Waldmann N. et al. Dynamics of retinal vessel response to flicker light in glaucoma patients and ocular hypertensives. Graefes Arch Clin Exp Ophthalmol 2012; 250: 589-594
    CrossrefPubMedSearch in Google Scholar
  • 4 Garhöfer G, Zawinka C, Resch H. et al. Response of retinal vessel diameters to flicker stimulation in patients with early open angle glaucoma. J Glaucoma 2004; 13: 340-344
    CrossrefPubMedSearch in Google Scholar
  • 5 Seifertl BU, Vilser W. Retinal Vessel Analyzer (RVA)–design and function. Biomed Tech (Berl) 2002; 47 (Suppl. 1) S678-S681
    CrossrefPubMedSearch in Google Scholar
  • 6 Gugleta K, Zawinka C, Rickenbacher I. et al. Analysis of retinal vasodilation after flicker light stimulation in relation to vasospastic propensity. Invest Ophthalmol Vis Sci 2006; 47: 4034-4041
    CrossrefPubMedSearch in Google Scholar
  • 7 Gugleta K, Türksever C, Polunina A. et al. Effect of ageing on the retinal vascular responsiveness to flicker light in glaucoma patients and in ocular hypertension. Br J Ophthalmol 2013; 97: 848-851
    CrossrefPubMedSearch in Google Scholar
  • 8 Ramm L, Jentsch S, Peters S. et al. Investigation of blood flow regulation and oxygen saturation of the retinal vessels in primary open-angle glaucoma. Graefes Arch Clin Exp Ophthalmol 2014; 252: 1803-1810
    CrossrefPubMedSearch in Google Scholar
  • 9 Kiyota N, Kunikata H, Shiga Y. et al. Relationship between laser speckle flowgraphy and optical coherence tomography angiography measurements of ocular microcirculation. Graefes Arch Clin Exp Ophthalmol 2017; 255: 1633-1642
    CrossrefPubMedSearch in Google Scholar
  • 10 Spaide RF. Age-related choroidal atrophy. Am J Ophthalmol 2009; 147: 801-810
    CrossrefPubMedSearch in Google Scholar
  • 11 Yuan S, Devor A, Boas DA. et al. Determination of optimal exposure time for imaging of blood flow changes with laser speckle contrast imaging. Appl Opt 2005; 44: 1823-1830
    CrossrefPubMedSearch in Google Scholar
  • 12 Srienc A, Kurth-Nelson Z, Newman E. Imaging retinal blood flow with laser speckle flowmetry. Front Neuroenergetics 2010; 2: 128
    CrossrefPubMedSearch in Google Scholar
  • 13 Sugiyama T, Araie M, Riva CE. et al. Use of laser speckle flowgraphy in ocular blood flow research. Acta Ophthalmol 2010; 88: 723-729
    CrossrefPubMedSearch in Google Scholar
  • 14 Wang L, Cull GA, Piper C. et al. Anterior and posterior optic nerve head blood flow in nonhuman primate experimental glaucoma model measured by laser speckle imaging technique and microsphere method. Invest Ophthalmol Vis Sci 2012; 53: 8303-8309
    CrossrefPubMedSearch in Google Scholar
  • 15 Iwase T, Akahori T, Yamamoto K. et al. Evaluation of optic nerve head blood flow in response to increase of intraocular pressure. Sci Rep 2018; 8: 17235
    CrossrefPubMedSearch in Google Scholar
  • 16 Iwase T, Yamamoto K, Ra E. et al. Diurnal variations in blood flow at optic nerve head and choroid in healthy eyes: diurnal variations in blood flow. Medicine (Baltimore) 2015; 94: e519
    CrossrefPubMedSearch in Google Scholar
  • 17 Matlach J, Bender S, König J. et al. Investigation of intraocular pressure fluctuation as a risk factor of glaucoma progression. Clin Ophthalmol 2019; 13: 9-16
    CrossrefPubMedSearch in Google Scholar
  • 18 Gordon MO, Beiser JA, Brandt JD. et al. The Ocular Hypertension Treatment Study: baseline factors that predict the onset of primary open-angle glaucoma. Arch Ophthalmol 2002; 120: 714-720
    CrossrefPubMedSearch in Google Scholar
  • 19 Enomoto N, Anraku A, Tomita G. et al. Characterization of laser speckle flowgraphy pulse waveform parameters for the evaluation of the optic nerve head and retinal circulation. Sci Rep 2021; 11: 6847
    CrossrefPubMedSearch in Google Scholar
  • 20 Kiyota N, Kunikata H, Shiga Y. et al. Ocular microcirculation measurement with laser speckle flowgraphy and optical coherence tomography angiography in glaucoma. Acta Ophthalmol 2018; 96: e485-e492
    CrossrefPubMedSearch in Google Scholar
  • 21 Luft N, Wozniak PA, Aschinger GC. et al. Measurements of Retinal Perfusion Using Laser Speckle Flowgraphy and Doppler Optical Coherence Tomography. Invest Ophthalmol Vis Sci 2016; 57: 5417-5425
    CrossrefPubMedSearch in Google Scholar
  • 22 Luft N, Wozniak PA, Aschinger GC. et al. Ocular Blood Flow Measurements in Healthy White Subjects Using Laser Speckle Flowgraphy. PLoS One 2016; 11: e0168190
    CrossrefPubMedSearch in Google Scholar
  • 23 Briers JD, Fercher AF. Retinal blood-flow visualization by means of laser speckle photography. Invest Ophthalmol Vis Sci 1982; 22: 255-259
    PubMedSearch in Google Scholar
  • 24 Aizawa N, Nitta F, Kunikata H. et al. Laser speckle and hydrogen gas clearance measurements of optic nerve circulation in albino and pigmented rabbits with or without optic disc atrophy. Invest Ophthalmol Vis Sci 2014; 55: 7991-7996
    CrossrefPubMedSearch in Google Scholar
  • 25 Takahashi H, Sugiyama T, Tokushige H. et al. Comparison of CCD-equipped laser speckle flowgraphy with hydrogen gas clearance method in the measurement of optic nerve head microcirculation in rabbits. Exp Eye Res 2013; 108: 10-15
    CrossrefPubMedSearch in Google Scholar
  • 26 Okamoto M, Matsuura T, Ogata N. Effects of Panretinal Photocoagulation on Choroidal Thickness and Choroidal Blood Flow in Patients with Severe Nonproliferative Diabetic Retinopathy. Retina 2016; 36: 805-811
    CrossrefPubMedSearch in Google Scholar
  • 27 Sugiyama T, Kojima S, Ishida O. et al. Changes in optic nerve head blood flow induced by the combined therapy of latanoprost and beta blockers. Acta Ophthalmol 2009; 87: 797-800
    CrossrefPubMedSearch in Google Scholar
  • 28 Aizawa N, Yokoyama Y, Chiba N. et al. Reproducibility of retinal circulation measurements obtained using laser speckle flowgraphy-NAVI in patients with glaucoma. Clin Ophthalmol 2011; 5: 1171-1176
    PubMedSearch in Google Scholar
  • 29 Baek J, Park HL, Kim SA. et al. Parapapillary Choroidal Microvasculature Dropout in Branched Retinal Vein Occlusion and Glaucoma. Invest Ophthalmol Vis Sci 2022; 63: 27
    CrossrefPubMedSearch in Google Scholar
  • 30 Suh MH, Jung DH, Weinreb RN. et al. Optic Disc Microvasculature Dropout in Glaucoma Detected by Swept-Source Optical Coherence Tomography Angiography. Am J Ophthalmol 2022; 236: 261-270
    CrossrefPubMedSearch in Google Scholar
  • 31 Song MK, Shin JW, Lee JY. et al. Choroidal microvasculature dropout is spatially associated with optic nerve head microvasculature loss in open-angle glaucoma. Sci Rep 2021; 11: 15181
    CrossrefPubMedSearch in Google Scholar
  • 32 Jo YH, Shin JW, Song MK. et al. Baseline Choroidal Microvasculature Dropout as a Predictor of Subsequent Visual Field Progression in Open-angle Glaucoma. J Glaucoma 2021; 30: 672-681
    CrossrefPubMedSearch in Google Scholar
  • 33 Koo TK, Li MY. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med 2016; 15: 155-163
    CrossrefPubMedSearch in Google Scholar
  • 34 Gu C, Li A, Yu L. Diagnostic performance of laser speckle flowgraphy in glaucoma: a systematic review and meta-analysis. Int Ophthalmol 2021; 41: 3877-3888
    CrossrefPubMedSearch in Google Scholar
  • 35 Yanagi M, Kawasaki R, Wang JJ. et al. Vascular risk factors in glaucoma: a review. Clin Exp Ophthalmol 2011; 39: 252-258
    CrossrefPubMedSearch in Google Scholar
  • 36 Caprioli J, Coleman AL. Blood pressure, perfusion pressure, and glaucoma. Am J Ophthalmol 2010; 149: 704-712
    CrossrefPubMedSearch in Google Scholar
  • 37 Zheng Y, Wong TY, Mitchell P. et al. Distribution of ocular perfusion pressure and its relationship with open-angle glaucoma: the singapore malay eye study. Invest Ophthalmol Vis Sci 2010; 51: 3399-3404
    CrossrefPubMedSearch in Google Scholar
  • 38 Francis BA, Hsieh A, Lai MY. et al. Effects of corneal thickness, corneal curvature, and intraocular pressure level on Goldmann applanation tonometry and dynamic contour tonometry. Ophthalmology 2007; 114: 20-26
    CrossrefPubMedSearch in Google Scholar
  • 39 Park SJ, Ang GS, Nicholas S. et al. The effect of thin, thick, and normal corneas on Goldmann intraocular pressure measurements and correction formulae in individual eyes. Ophthalmology 2012; 119: 443-449
    CrossrefPubMedSearch in Google Scholar
  • 40 Wachtl J, Töteberg-Harms M, Frimmel S. et al. [Evaluation of correction formulas for tonometry: The Goldmann applanation tonometry in approximation to dynamic contour tonometry]. Ophthalmologe 2017; 114: 716-721
    PubMedSearch in Google Scholar
  • 41 Wachtl J, Töteberg-Harms M, Frimmel S. et al. Correlation Between Dynamic Contour Tonometry, Uncorrected and Corrected Goldmann Applanation Tonometry, and Stage of Glaucoma. JAMA Ophthalmol 2017; 135: 601-608
    CrossrefPubMedSearch in Google Scholar
  • 42 Anraku A, Enomoto N, Tomita G. et al. Ocular and Systemic Factors Affecting Laser Speckle Flowgraphy Measurements in the Optic Nerve Head. Transl Vis Sci Technol 2021; 10: 13
    CrossrefPubMedSearch in Google Scholar
  • 43 Türksever C, Orgül S, Todorova MG. Reproducibility of retinal oximetry measurements in healthy and diseased retinas. Acta Ophthalmol 2015; 93: e439-e445
    CrossrefPubMedSearch in Google Scholar
  • 44 Flammer J, Konieczka K. The discovery of the Flammer syndrome: a historical and personal perspective. EPMA J 2017; 8: 75-97
    CrossrefPubMedSearch in Google Scholar
  • 45 Konieczka K, Ritch R, Traverso CE. et al. Flammer syndrome. EPMA J 2014; 5: 11
    CrossrefPubMedSearch in Google Scholar
  • 46 Gu C, Li A, Yu L. Diagnostic performance of laser speckle flowgraphy in glaucoma: a systematic review and meta-analysis. Int Ophthalmol 2021; 41: 3877-3888
    CrossrefPubMedSearch in Google Scholar