Smartphone-based Ophthalmic Imaging Compared With Spectral-domain Optical Coherence Tomography Assessment of Vertical Cup-to-disc Ratio Among Adults in Southwestern Uganda

Agreement of a Novel Artificial Intelligence Software With Optical Coherence Tomography and Manual Grading of the Optic Disc in Glaucoma

PRCIS

The offline artificial intelligence (AI) on a smartphone-based fundus camera shows good agreement and correlation with the vertical cup-to-disc ratio (vCDR) from the spectral-domain optical coherence tomography (SD-OCT) and manual grading by experts.

PURPOSE

The purpose of this study is to assess the agreement of vCDR measured by a new AI software from optic disc images obtained using a validated smartphone-based imaging device, with SD-OCT vCDR measurements, and manual grading by experts on a stereoscopic fundus camera.

METHODS

In a prospective, cross-sectional study, participants above 18 years (Glaucoma and normal) underwent a dilated fundus evaluation, followed by optic disc imaging including a 42-degree monoscopic disc-centered image (Remidio NM-FOP-10), a 30-degree stereoscopic disc-centered image (Kowa nonmyd WX-3D desktop fundus camera), and disc analysis (Cirrus SD-OCT). Remidio FOP images were analyzed for vCDR using the new AI software, and Kowa stereoscopic images were manually graded by 3 fellowship-trained glaucoma specialists.

RESULTS

We included 473 eyes of 244 participants. The vCDR values from the new AI software showed strong agreement with SD-OCT measurements [95% limits of agreement (LoA)=-0.13 to 0.16]. The agreement with SD-OCT was marginally better in eyes with higher vCDR (95% LoA=-0.15 to 0.12 for vCDR>0.8). Interclass correlation coefficient was 0.90 (95% CI, 0.88-0.91). The vCDR values from AI software showed a good correlation with the manual segmentation by experts (interclass correlation coefficient=0.89, 95% CI, 0.87-0.91) on stereoscopic images (95% LoA=-0.18 to 0.11) with agreement better for eyes with vCDR>0.8 (LoA=-0.12 to 0.08).

CONCLUSIONS

The new AI software vCDR measurements had an excellent agreement and correlation with the SD-OCT and manual grading. The ability of the Medios AI to work offline, without requiring cloud-based inferencing, is an added advantage.

Smartphone ophthalmoscopy versus slit-lamp biomicroscopy for optic nerve head evaluation: A digital apparatus into medical education

OBJECTIVE

Th aim of this study is to explore the diagnostic accuracy of smartphone-based D-EYE ophthalmoscopy in the diagnosis of optic nerve head (ONH) abnormalities and screening for glaucoma.

METHODS

This is a prospective clinical-based validation study performed on 90 patients recruited from a tertiary teaching hospital. Patients underwent dilated fundus examination by slit-lamp and smartphone-based D-EYE fundoscopy operated by two experienced ophthalmologists.

RESULTS

The diagnostic accuracy of smartphone-based D-EYE ophthalmoscopy of normal vertical cup-to-disc ratio (VCDR) was acceptable (sensitivity 85.8%-96.4%; specificity 51.4%-96.4%). The D-EYE would often underestimate VCDR values as mean VCDR was significantly lower among overall and glaucoma cohorts (all p-value <0.001) for D-EYE in comparison with slit-lamp. In terms of ONH abnormalities, the D-EYE adequately demonstrated high sensitivity in the identification of only margins-related abnormalities (sensitivity 92.5%-96.6%). Overall, the diagnostic accuracy and agreement between expert ophthalmologists using the D-EYE and the reference slit-lamp examination were significantly poor.

CONCLUSION

We demonstrated that the D-EYE is a highly specific tool for VCDR within the normal range but not in patients with glaucoma. Despite being an easy and portable tool to measure VCDR, it is limited in terms of diagnosing ONH and blood vessel abnormalities.