by Marcello Cherchi, MD PhD
Quantitative measurement of horizontal and vertical eye movements has been well studied in several modalities, including electronystagmography, videonystagmography and magnetic scleral search coils.
Quantitative measurement of torsional eye movements (rotation about the visual axis) has been less well studied. The scleral search coil system developed by David Robinson (Robinson 1963), enhanced with the dual coil technique developed by Collewijn and colleagues (Collewijn et al. 1975), provided spatial and temporal measurement of torsional eye movements whose accuracy has not yet been surpassed by other techniques, but the cumbersome and technologically demanding nature of this method has limited it to research settings.
Improvement in imaging technologies is beginning to provide clinically feasible methods for measuring ocular torsion.
One approach for measuring dynamic ocular torsion relies on video oculography. The most common approach for this leverages the iris signature technique originally developed by John Daugman (Daugman 2004; Daugman 1994) for biometric purposes, and uses cross-correlation of serial iris signatures to quantify torsion (Otero-Millan et al. 2015). This technique can be used, for example, in quantifying ocular counter-roll (Otero-Millan et al. 2017; Sadeghpour et al. 2021). These approaches measure ocular cycloposition of one video frame relative to some other video frame.
Measurement of static ocular cycloposition relative to the head requires tracking stable anatomical landmarks of the eye relative to landmarks of the head. The usual ophthalmologic anatomical landmarks are the optic disc and the fovea; the usual head anatomical landmarks are an inter-canthal line or inter-aural line. The angle at which the disc-foveal line intersects the inter-canthal or inter-aural line provides a metric for ocular cycloposition. Various imaging modalities have been studied for identifying the disc-foveal line, including fundus photography, optical coherence tomography (Kang et al. 2020) and scanning laser ophthalmoscopy (Lengwiler et al. 2018). Automated identification of landmarks in fundus photography has proved challenging (Felius et al. 2009; Gegundez-Arias et al. 2013; Onal et al. 2016; Piedrahita-Alonso et al. 2014; Sekhar et al. 2011; Sinthanayothin et al. 1999; Trucco et al. 2013). Optical coherence tomography (OCT) compares favorably with other modalities since the 3D capabilities of OCT identify retinal topography, which is a more reliable method of landmark identification (Sophocleous 2017; Yamadera et al. 2020). As image acquisition speeds improve, OCT may eventually be able to track torsional eye movements (Brodsky et al. 2014) at frame rates needed for characterizing torsional nystagmus.
In clinical practice, analysis of torsional eye movements is particularly helpful in the diagnosis of posterior canal benign paroxysmal positional vertigo. Ocular cycloposition is also useful in the assessment of otolith (specifically utricular) function; it is well known that vestibular deafferentation causes static ocular cyclodeviation toward the deafferented side (Curthoys et al. 1991a; Curthoys et al. 1991b), and also affects the ocular counter-roll response (Diamond and Markham 1981; Otero-Millan et al. 2017). The static and dynamic aspects of the ocular counter-roll response reflect different aspects of otolith function (Markham and Diamond 2001, 2002).
References
Brodsky MC, Klaehn L, Goddard SM, Link TP (2014) Heidelberg Spectralis infrared video imaging: a clinical tool for diagnosing ocular torsional instability. J AAPOS 18: 306-7. doi: 10.1016/j.jaapos.2014.01.009
Collewijn H, van der Mark F, Jansen TC (1975) Precise recording of human eye movements. Vision Res 15: 447-50. doi: 10.1016/0042-6989(75)90098-x
Curthoys IS, Dai MJ, Halmagyi GM (1991a) Human ocular torsional position before and after unilateral vestibular neurectomy. Exp Brain Res 85: 218-25.
Curthoys IS, Halmagyi GM, Dai MJ (1991b) The acute effects of unilateral vestibular neurectomy on sensory and motor tests of human otolithic function. Acta Otolaryngol Suppl 481: 5-10.
Daugman J (2004) How iris recognition works. IEEE Transactions on Circuits and Systems for Video Technology 14: 21-30. doi: 10.1109/TCSVT.2003.818350
Daugman JG (1994) Biometric personal identification system based on iris analysis. In: Office USPaT (ed), G06K 9/00 edn, vol A. Iri Scan Incorporated, United States
Diamond SG, Markham CH (1981) Binocular counterrolling in humans with unilateral labyrinthectomy and in normal controls. Ann N Y Acad Sci 374: 69-79.
Felius J, Locke KG, Hussein MA, Stager DR, Jr., Stager DR, Sr. (2009) Photographic assessment of changes in torsional strabismus. J AAPOS 13: 593-5. doi: 10.1016/j.jaapos.2009.09.008
Gegundez-Arias ME, Marin D, Bravo JM, Suero A (2013) Locating the fovea center position in digital fundus images using thresholding and feature extraction techniques. Comput Med Imaging Graph 37: 386-93. doi: 10.1016/j.compmedimag.2013.06.002
Kang H, Lee SJ, Shin HJ, Lee AG (2020) Measuring ocular torsion and its variations using different nonmydriatic fundus photographic methods. PLoS One 15: e0244230. doi: 10.1371/journal.pone.0244230
Lengwiler F, Rappoport D, Jaggi GP, Landau K, Traber GL (2018) Reliability of Cyclotorsion measurements using Scanning Laser Ophthalmoscopy imaging in healthy subjects: the CySLO study. Br J Ophthalmol 102: 535-538. doi: 10.1136/bjophthalmol-2017-310396
Markham CH, Diamond SG (2001) Ocular counterrolling differs in dynamic and static stimulation. Acta Otolaryngol Suppl 545: 97-100.
Markham CH, Diamond SG (2002) Ocular counterrolling in response to static and dynamic tilting: implications for human otolith function. J Vestib Res 12: 127-34.
Onal S, Chen X, Satamraju V, Balasooriya M, Dabil-Karacal H (2016) Automated and simultaneous fovea center localization and macula segmentation using the new dynamic identification and classification of edges model. J Med Imaging (Bellingham) 3: 034002. doi: 10.1117/1.JMI.3.3.034002
Otero-Millan J, Roberts DC, Lasker A, Zee DS, Kheradmand A (2015) Knowing what the brain is seeing in three dimensions: A novel, noninvasive, sensitive, accurate, and low-noise technique for measuring ocular torsion. J Vis 15: 11. doi: 10.1167/15.14.11
Otero-Millan J, Trevino C, Winnick A, Zee DS, Carey JP, Kheradmand A (2017) The video ocular counter-roll (vOCR): a clinical test to detect loss of otolith-ocular function. Acta Otolaryngol 137: 593-597. doi: 10.1080/00016489.2016.1269364
Piedrahita-Alonso E, Valverde-Megias A, Gomez-de-Liano R (2014) Rotation of retinal vascular arcades and comparison with disc-fovea angle in the assessment of cycloposition. Br J Ophthalmol 98: 115-9. doi: 10.1136/bjophthalmol-2013-303680
Robinson DA (1963) A Method of Measuring Eye Movement Using a Scleral Search Coil in a Magnetic Field. IEEE Trans Biomed Eng 10: 137-45.
Sadeghpour S, Fornasari F, Otero-Millan J, Carey J, Zee D, Kheradmand A, Motor O, Sadeghpour, Fornasari O-M, Zee K (2021) Evaluation of the Video Ocular Counter-Roll (vOCR) as a New Clinical Test of Otolith Function in Peripheral Vestibulopathy. JAMA Otolaryngology – Head and Neck Surgery. doi: 10.1001/jamaoto.2021.0176
Sekhar S, Abd El-Samie FE, Yu P, Al-Nuaimy W, Nandi AK (2011) Automated localization of retinal features. Appl Opt 50: 3064-75. doi: 10.1364/AO.50.003064
Sinthanayothin C, Boyce JF, Cook HL, Williamson TH (1999) Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images. Br J Ophthalmol 83: 902-10.
Sophocleous S (2017) Use of optical coherence topography for objective assessment of fundus torsion. BMJ Case Rep 2017. doi: 10.1136/bcr-2016-216867
Trucco E, Ruggeri A, Karnowski T, Giancardo L, Chaum E, Hubschman JP, Al-Diri B, Cheung CY, Wong D, Abramoff M, Lim G, Kumar D, Burlina P, Bressler NM, Jelinek HF, Meriaudeau F, Quellec G, Macgillivray T, Dhillon B (2013) Validating retinal fundus image analysis algorithms: issues and a proposal. Invest Ophthalmol Vis Sci 54: 3546-59. doi: 10.1167/iovs.12-10347
Yamadera K, Ishikawa H, Imai A, Okamoto M, Kimura A, Mimura O, Gomi F (2020) A Novel Method for Evaluation of Ocular Torsion Angle by Optical Coherence Tomography. Transl Vis Sci Technol 9: 27. doi: 10.1167/tvst.9.3.27
