Ocular Optical Coherence Tomography in the Evaluation of Sellar and Parasellar Masses: A Review

A novel predictive model utilizing retinal microstructural features for estimating survival outcome in patients with glioblastoma

PURPOSE

Glioblastoma is a highly aggressive brain tumor with poor prognosis despite surgery and chemoradiation. The visual sequelae of glioblastoma have not been well characterized. This study assessed visual outcomes in glioblastoma patients through neuro-ophthalmic exams, imaging of the retinal microstructures/microvasculature, and perimetry.

METHODS

A total of 19 patients with glioblastoma (9 male, 10 female, average age at diagnosis 69 years) were enrolled. Tumor characteristic, neuro-ophthalmic exam data, Optical Coherence Tomography (OCT) and OCT-Angiography data of all patient eyes were analyzed using Microsoft Excel and a Machine Learning algorithm.

RESULTS

Best-corrected visual acuity ranged from 20/20 - 20/50. Occipital tumors showed worse visual fields than frontal tumors (mean deviation -14.9 and -0.23, respectively, p < 0.0001). Those with overall survival (OS)< 15 months demonstrated thinner retinal nerve fiber layer and ganglion cell complex (p < 0.0001) and enlarged foveal avascular zone starting from 4 months post-diagnosis (p = 0.006). There was no significant difference between eyes ipsilateral and contralateral to radiation fields (average doses were 1370 cGy and 1180 cGy, respectively, p = 0.42). A machine learning algorithm using retinal microstructure and visual fields predicted patients with long (≥15 months) progression-free and overall survival with 78 % accuracy.

CONCLUSION

Glioblastoma patients frequently present with visual field defects despite normal visual acuity. Patients with poor survival duration demonstrated significant retinal thinning and decreased microvascular density. A machine learning algorithm predicted survival though further validation is warranted.

Visual morbidity in macroprolactinoma: A retrospective cohort study

OBJECTIVE

The management of visual field damage in patients with macroprolactinomas is a major therapeutic challenge. We aimed to study the visual morbidity associated with macroprolactinoma and its outcomes following medical and surgical treatment. We aimed to identify predictors of visual recovery.

METHODS

We retrospectively reviewed patient's data including clinical presentation, serial pituitary magnetic resonance imaging, laboratory tests, visual symptoms and neuro-ophthalmologic examination, visual field tests and optical coherence tomography tests. The main outcome was complete visual field recovery. Descriptive analyses were conducted. Predictors of visual recovery were investigated.

PATIENTS

The study cohort included 150 patients with macroprolactinoma [median follow-up, 6.0 years (interquartile range (IQR) 2.9-10.6)].

RESULTS

At diagnosis, visual field defects were evident in 40 patients (26.7%). At the end of follow-up, 24 out of 39 available visual field tests (61.5%) exhibited complete recovery. Patients that achieved complete visual recovery had smaller macroadenomas at diagnosis [30.5 mm (15.0-80.0) vs. 42.0 mm (30.0-85.0), p < .01], lower baseline serum prolactin levels [1414 mcg/L (489-3586) vs. 4119 mcg/L (2715-6315), p < .01], lower rates of central hypogonadism (78.3% vs. 93.3%, p = .05) and central hypothyroidism (20.8% vs. 53.3%, p = .04), lower rates of compressive optic neuropathy (35.3% vs. 87.5%, p = .02) and a better visual acuity (better than 6/8 in both eyes, 93.7% vs. 28.6%, p < .01).

CONCLUSIONS

In our cohort of 150 patients with macroprolactinoma, 40 patients (26.7%) presented with visual field defects, of which 61.5% achieved complete visual recovery with treatment. Patients that achieved complete visual recovery presented with smaller macroadenomas, lower serum prolactin levels, lower rates of central hypogonadism and central hypothyroidism, lower rates of compressive optic neuropathy and better visual acuity.

Homonymous Hemiatrophy of Macular Ganglion Cell Layer as a Marker of Retrograde Neurodegeneration in Multiple Sclerosis-A Narrative Review

Retrograde axonal neurodegeneration along the visual pathway-either direct or trans-synaptic-has already been demonstrated in multiple sclerosis (MS), as well as in compressive, vascular, or posttraumatic lesions of the visual pathway. Optical coherence tomography (OCT) can noninvasively track macular and optic nerve changes occurring as a result of this phenomenon. Our paper aimed to review the existing literature regarding hemimacular atrophic changes in the ganglion cell layer identified using OCT examination in MS patients without prior history of optic neuritis. Homonymous hemimacular atrophy has been described in post-chiasmal MS lesions, even in patients with normal visual field results. Temporal and nasal macular OCT evaluation should be performed separately in all MS patients, in addition to an optic nerve OCT evaluation and a visual field exam.

A Novel Predictive Model Utilizing Retinal Microstructural Features for Estimating Survival Outcome in Patients with Glioblastoma

Glioblastoma is a highly aggressive brain tumor with poor prognosis despite surgery and chemoradiation. The visual sequelae of glioblastoma have not been well characterized. This study assessed visual outcomes in glioblastoma patients through neuro-ophthalmic exams, imaging of the retinal microstructures/microvasculature, and perimetry. A total of 19 patients (9 male, 10 female, average age at diagnosis 69 years) were enrolled. Best-corrected visual acuity ranged from 20/20-20/50. Occipital tumors showed worse visual fields than frontal tumors (mean deviation - 14.9 and - 0.23, respectively, p < 0.0001). Those with overall survival (OS) < 15 months demonstrated thinner retinal nerve fiber layer and ganglion cell complex (p < 0.0001) and enlarged foveal avascular zone starting from 4 months post-diagnosis (p = 0.006). There was no significant difference between eyes ipsilateral and contralateral to radiation fields (average doses were 1370 cGy and 1180 cGy, respectively, p = 0.42). A machine learning algorithm using retinal microstructure and visual fields predicted patients with long (≥ 15 months) progression free and overall survival with 78% accuracy. Glioblastoma patients frequently present with visual field defects despite normal visual acuity. Patients with poor survival duration demonstrated significant retinal thinning and decreased microvascular density. A machine learning algorithm predicted survival; further validation is warranted.

The Role of Optical Coherence Tomography Angiography in the Evaluation of Chiasmal and Retrochiasmal Compression

The compression of the visual pathway is associated with structural retinal changes due to retrograde neurodegeneration. It was brought into question whether visual pathway compression is also associated with retinal vascular changes as assessed by optical coherence tomography angiography (OCT-A). The objective of this review is to discuss the role of OCT-A in the evaluation of patients with tumours of the sellar, parasellar, and retrochiasmal regions. The reported OCT-A parameters were the vessel densities of radial peripapillary capillary network, macular superficial vascular plexus and/or macular deep vascular complex. Optic nerve and macular OCT-A parameters were impaired in patients versus controls. These changes were associated with altered structural OCT parameters and visual field defects. OCT-A could be considered a marker of neurodegeneration in addition to structural OCT, and it has the potential to become a visual prognostic tool in patients with visual pathway compression.

Interpretation of the Visual Field in Neuro-ophthalmic Disorders

PURPOSE OF REVIEW

In this review, we will describe current methods for visual field testing in neuro-ophthalmic clinical practice and research, develop terminology that accurately describes patterns of field deficits, and discuss recent advances such as augmented or virtual reality-based perimetry and the use of artificial intelligence in visual field interpretation.

RECENT FINDINGS

New testing strategies that reduce testing times, improve patient comfort, and increase sensitivity for detecting small central or paracentral scotomas have been developed for static automated perimetry. Various forms of machine learning-based tools such as archetypal analysis are being tested to quantitatively depict and monitor visual field abnormalities in optic neuropathies. Studies show that the combined use of optical coherence tomography and standard automated perimetry to determine the structure-function relationship improves clinical care in neuro-ophthalmic disorders. Visual field assessment must be performed in all patients with neuro-ophthalmic disorders affecting the afferent visual pathway. Quantitative visual field analysis using standard automated perimetry is critical in initial diagnosis, monitoring disease progression, and guidance of therapeutic plans. Visual field defects can adversely impact activities of daily living such as reading, navigation, and driving and thus impact quality of life. Visual field testing can direct appropriate occupational low vision rehabilitation in affected individuals.