Vitreomacular traction quantitative cutoffs for the assessment of resolution after ocriplasmin intravitreal treatment

Abstract

This study aimed to assess optical coherence tomography (OCT) parameters associated with vitreomacular traction (VMT) resolution after ocriplasmin intravitreal injection and also associated with the development of vitreomacular complications. Study designed was a retrospective case series. Structural OCT images were acquired at baseline and over the follow-up after treatment. We developed a mathematical model to provide quantitative parameters associated with VMT resolution. Moreover, we adopted the same model to assess the quantitative parameters associated with development of further vitreomacular complications or with the worsening of the coexisting condition. Main outcome measures were BCVA, central macular thickness (CMT), VMT reflectivity, VMT size, VMT resolution, epiretinal membrane (ERM), macular holes. 73 eyes of 73 VMT patients (mean age 73 ± 9 years) were recruited. The mean follow-up duration was 2.6 ± 1.1 years. Mean baseline BCVA was 0.38 ± 0.18 LogMAR, improving to 0.26 ± 0.20 at the end of the follow-up (p < 0.01). Baseline CMT was 431 ± 118 µm, improving to 393 ± 122 µm at the end of the follow-up (p < 0.01). 38/73 eyes (52%) showed only VMT, whereas 35/73 eyes (48%) also showed coexisting alterations at baseline. VMT resolved in 40/73 eyes (55% of cases). Our model disclosed VMT reflectivity as the most involved parameter in VMT resolution. VMT size showed less influence on the success of ocriplasmin treatment. ERM was negatively associated with VMT resolution. Moreover, VMT reflectivity values and ERM represented the most important parameters for the onset of vitreomacular complications.

Predicting the individual probability of macular hole closure following intravitreal ocriplasmin injections for vitreomacular traction release using baseline characteristics

“…As success rates of VMT release 3 , 5 and FMTH closure 4 still varies in the literature and a common consensus of ideal patients for intravitreal ocriplasmin is still missing 15 , there seems to be a continuing medical need for further improvement in patient selection to increase overall treatment success. The next step could be the use of artificial intelligence (AI) to analyze OCT scans 21 to help ophthalmologists in the decision making process to find the best treatment option for each individual patient affected. In comparison to enzymatic vitreolysis using ocriplasmin with an overall success rate of FTMH closure of 38% herein, vitrectomy showed a success rate of more than 90% 22 .…”

Artificial Intelligence for the Diagnosis and Screening of Retinal Diseases

“…This includes other common retinal diseases, such as retinal vein occlusion, central serous chorioretinopathy and vitreoretinal disorders. [72][73][74][75][76][77][78][79] AI has been tested in inherited retinal dystrophies to segment retinal structures on OCT, to detect atrophic changes and to follow all these alterations over time. In particular, AI models have been used in retinitis pigmentosa, 80-82 choroideremia 80,83 and Stargardt disease.…”