Retinal sublayer defect is independently associated with the severity of hypertensive white matter hyperintensity

Qu, Man; Kwapong, William Robert; Peng, Chenlei; Cao, Yungang; Liu, Fan; Shen, Meixiao; Han, Zhao

doi:10.1002/brb3.1521

Cited by 10 publications

(11 citation statements)

References 34 publications

(36 reference statements)

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“…Interestingly, the INL+HFL contains bundles of unmyelinated cone and rod photoreceptor axons (Lujan et al, 2011 ), whereas the OS is equivalent to the dendritic part of a photoreceptor cell. The decrease of the thickness of these two layers is consistent with the findings of a prior study of ganglion cells, in which the sublayer of axons and dendrites became thinner (Qu et al, 2020 ). This provides new evidence for a correlation between the neurites of retinal cells and white matter.…”

Section: Discussionsupporting

confidence: 91%

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Outer Retinal Layer Thickness Changes in White Matter Hyperintensity and Parkinson's Disease

Zhao

et al. 2021

Front. Neurosci.

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Purpose: To investigate the thickness changes of outer retinal layers in subjects with white matter hyperintensities (WMH) and Parkinson's Disease (PD).Methods: 56 eyes from 31 patients with WMH, 11 eyes from 6 PD patients, and 58 eyes from 32 healthy controls (HC) were enrolled in this study. A macular-centered scan was conducted on each participant using a spectral-domain optical coherence tomography (SD-OCT) device. After speckle noise reduction, a state-of-the-art deep learning method (i.e., a context encoder network) was employed to segment the outer retinal layers from OCT B-scans. Thickness quantification of the outer retinal layers was conducted on the basis of the segmentation results.Results: WMH patients had significantly thinner Henle fiber layers, outer nuclear layers (HFL+ONL) and photoreceptor outer segments (OS) than HC (p = 0.031, and p = 0.005), while PD patients showed a significant increase of mean thickness in the interdigitation zone and the retinal pigment epithelium/Bruch complex (IZ+RPE) (19.619 ± 4.626) compared to HC (17.434 ± 1.664). There were no significant differences in the thickness of the outer plexiform layer (OPL), the myoid and ellipsoid zone (MEZ), and the IZ+RPE layer between WMH and HC subjects. Similarly, there were also no obvious differences in the thickness of the OPL, HFL+ONL, MEZ and the OS layer between PD and HC subjects.Conclusion: Thickness changes in HFL+ONL, OS, and IZ+RPE layers may correlate with brain-related diseases such as WMH and PD. Further longitudinal study is needed to confirm HFL+ONL/OS/IZ+RPE layer thickness as potential biomarkers for detecting certain brain-related diseases.

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Section: Discussionsupporting

confidence: 91%

“…The GCL is composed of cell bodies, and it is more likely to be related to gray matter (Mutlu et al, 2017). Qu et al (2020) has also recently reported that the thickness of the NFL and GCL+IPL were associated with WMH, and deteriorate with the severity of lesions.…”

Section: White Matter Hyperintensities and The Onl+hfl/os Layer Of The Retinamentioning

confidence: 96%

Outer Retinal Layer Thickness Changes in White Matter Hyperintensity and Parkinson's Disease

Zhao

et al. 2021

Front. Neurosci.

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“…Therefore the RNFL represents the direct neuroretinal contributions to the central nervous system and has been shown to correlate with cerebral white matter atrophy in neurodegenerative disease. [24][25][26][27] Kochunov et al 28,29 and others recently characterized white matter abnormalities as an underlying neural mechanism in schizophrenia. [30][31][32] Therefore preferential axonal loss in SSD might be related to similar white matter abnormalities evidenced in this disease.…”

Section: Discussionmentioning

confidence: 99%

Neuroretinal Biomarkers for Schizophrenia Spectrum Disorders

Asanad

O’Neill

Addis

et al. 2021

Trans. Vis. Sci. Tech.

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Purpose We evaluated the patient-control differences and predictive value of the retina as potential biomarkers for schizophrenia. Methods The institutional study included both eyes of 58 schizophrenia spectrum disorder (SSD) patients (age 37.2 ± 12.3 years) and 35 controls (age 41.1 ± 15.2 years). Retinal nerve fiber layer (RNFL), ganglion cell–inner plexiform layer, outer retinal photoreceptor complex, and total macula thicknesses were measured by optical coherence tomography (OCT). Anterior segment parameters including central corneal thickness, anterior chamber depth, and axial length were measured to rule out confounds on the retinal measures. Results The peripapillary RNFL was overall significantly thinner in SSD relative to controls ( F = 3.97, P = 0.049), most pronounced in the temporal (5.2 µm difference, F = 6.95, P = 0.010) and inferior quadrants (12.1 µm difference, F = 7.32, P = 0.009). There were no significant group differences in thickness for the macular RNFL, ganglion, or photoreceptor cell related measures ( P > 0.05). Peripapillary RNFL, central macula, and outer photoreceptor complex thicknesses were together able to classify SSD patients with 80% sensitivity and 71% specificity; area under the curve = 0.82 (95% confidence interval, 0.75–0.88). Conclusions SSD patients exhibited significant RNFL thinning relative to controls. Notably, retinal thickness measures including both peripapillary and macular data exhibited improved diagnostic accuracy for SSD as compared to these regions alone. Translational Relevance This is the first study to evaluate the predictive value of both the inner and outer retina in SSD. OCT retinal thickness measures including peripapillary data in conjunction with macular data may provide an informative, noninvasive in vivo ocular biomarker for schizophrenia.

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“…The risk of pRNFL damage was associated with the occurrence of MRI white matter lesions, hypertension, older age, and male sex. In another study, the authors investigated the thickness of retinal layers in patients with NSWMLs and healthy controls [53]. Thicknesses of the mRNFL and the GCIPL were significantly reduced in NSWMLs patients compared to healthy controls.…”

Section: Discussionmentioning

confidence: 99%

Optical Coherence Tomography in the Differential Diagnosis of Patients with Multiple Sclerosis and Patients with MRI Nonspecific White Matter Lesions

Siger

Owidzka

Świderek-Matysiak

et al. 2021

Sensors

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In the differential diagnosis of nonspecific white matter lesions (NSWMLs) detected on magnetic resonance imaging (MRI), multiple sclerosis (MS) should be taken into consideration. Optical coherence tomography (OCT) is a promising tool applied in the differential diagnostic process of MS. We tested whether OCT may be useful in distinguishing between MS and NSWMLs patients. In patients with MS (n = 41) and NSWMLs (n = 19), the following OCT parameters were measured: thickness of the peripapillary Retinal Nerve Fibre Layer (pRNFL) in superior, inferior, nasal, and temporal segments; thickness of the ganglion cell-inner plexiform layer (GCIPL); thickness of macular RNFL (mRNFL); and macular volume (MV). In MS patients, GCIPL was significantly lower than in NSWMLs patients (p = 0.024). Additionally, in MS patients, mRNFL was significantly lower than in NSWMLs patients (p = 0.030). The average segmental pRNFL and MV did not differ between MS and NSWMLs patients (p > 0.05). GCIPL and macular RNFL thinning significantly influenced the risk of MS (18.6% [95% CI 2.7%, 25.3%]; 27.4% [95% CI 4.5%, 62.3%]), and reduced GCIPL thickness appeared to be the best predictor of MS. We conclude that OCT may be helpful in the differential diagnosis of MS and NSWMLs patients in real-world settings.

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Retinal sublayer defect is independently associated with the severity of hypertensive white matter hyperintensity

Cited by 10 publications

References 34 publications

Outer Retinal Layer Thickness Changes in White Matter Hyperintensity and Parkinson's Disease

Outer Retinal Layer Thickness Changes in White Matter Hyperintensity and Parkinson's Disease

Neuroretinal Biomarkers for Schizophrenia Spectrum Disorders

Optical Coherence Tomography in the Differential Diagnosis of Patients with Multiple Sclerosis and Patients with MRI Nonspecific White Matter Lesions

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