PyOPV: An Open-Source Python Package for Ophthalmic Visual Field Data Management.

PRCIS

PyOPV is a software designed and validated for handling standard visual field DICOM files, enabling multiple functionalities for glaucoma researchers.

PURPOSE

To introduce PyOPV, a novel vendor-agnostic Python-based software package we designed for the management and analysis of OPhthalmic Visual field (OPV) DICOM data. PyOPV addresses limitations in interoperability and data accessibility encountered by vision researchers by providing tools that check DICOM compliance, parse, and convert OPV DICOM files into formats easily usable for research and integration with research data systems (eg, Pandas Dataframes, JSON).

METHODS

PyOPV was developed using Python 3.8.2. It uses Supplement 146 of the DICOM standard to check compliance, which defines the "ophthalmic-visual-field-static-perimetry-measurements" Composite Information Object Definition. Sample OPV DICOM files from 3 vendors that provide perimetry devices were used to design the package and analyzed for DICOM. The functionalities were then validated at 2 different institutions.

RESULTS

PyOPV successfully extracted and converted OPV DICOM data into Pandas DataFrames and JSON formats, facilitating data access, analysis, and visualization. The validation on longitudinal files from different protocols demonstrated excellent agreement between PyOPV outputs and ground truth data extracted using in-place workflows of each institution. Further, it highlighted significant interoperability challenges by demonstrating missing attributes across vendors, with a considerable proportion (range: 17%-51%) of the required tags missing from the files.

CONCLUSIONS

PyOPV provides an efficient solution for handling ophthalmic visual field data, bridging a critical gap in data interoperability and research scalability. It can incorporate OPV files from different vendors and distinct protocols in bulk, thereby enhancing the ability to analyze and integrate visual field data into large-scale health data warehouses, supporting ophthalmic informatics and advancing clinical research. PyOPV is limited by the vendors' failure to provide all data elements.