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Removing Subjective Post-Mortem Grading from Posterior Capsular Opacification: A New Automated Detector Opacification Software, ADOS

, , , , , & show all
Pages 1362-1368 | Received 27 Nov 2017, Accepted 11 Jul 2018, Published online: 25 Jul 2018
 

ABSTRACT

Purpose/aim: Posterior capsular opacification (PCO) is the leading complication following cataract surgery. However, PCO grading methods vary between studies and rely on subjective scoring methods; hence, they are prone to error. Therefore, software that reduces subjectivity and enhances reproducibility is needed. The aim of the study was to evaluate the reproducibility and objectivity of a novel automated custom-designed PCO detection software.

Materials and Methods: In total, 165 fixed eyes with intraocular lenses were sectioned to obtain a Miyake Apple view (MAV) image. The capsular bag (CB) with the in situ IOL was removed and imaged using the Olympus DSX110 stereoscope. Central, peripheral, and Soemmering’s ring area (SRA) and intensity (SRI) were graded by two ophthalmologists using a scale of 0–4. Software was developed to detect PCO, and these values were correlated with subjective scoring.

Results: Intra-observer agreement for MAV and CB images ranged from poor to moderate, with very good agreement for SRI (k = 0.88, 0.86, respectively). Agreement between graders was fair to good (k = 0.31–0.77). Miyake Apple view and capsular bag images showed good correlation; central PCO showed the least correlation for both evaluators (k = 0.29, 0.72). Subjective average grading versus software correlation demonstrated very good correlation for intensity and good for area (r = 0.85, 0.61). Reproducibility of the methodology resulted in good to very good correlation.

Conclusions: Software correlates with previous scoring methods and is a reliable and reproducible system. Moreover, the capsular bag view, as opposed to the Miyake Apple view, allows visualization of the capsular bag directly and avoids overlapping structures (vitreous, cornea) that may interfere with proper PCO quantification.

Declaration of Interest

Mr. Balazsi reports that he has a patent null pending and is the founder of Medical Parachute, a company that offers software services to medical professionals. For this project, the MUHC-McGill University Ocular Pathology Laboratory has employed the services of Medical Parachute along with their software to analyze the digital slides for a fee. Although the software has not been patented, Medical Parachute reserves the right to license the use of the software to other laboratories. All other authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

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