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import_pentacam: Open-Source OCR Recovery of Corneal Tomography Measurements From Pentacam DICOM, PDF, and Image
Katerina Kiroshka1, Tobias Elze2
1Lumael Eye Medical Institute Ltd., Ashkelon, Israel.
Purpose:
Pentacam corneal tomography data accumulate in clinical Digital Imaging and Communications in Medicine (DICOM) archives as embedded portable document format (PDF) printouts and proprietary binary readouts rather than structured records; the device's comma-separated values (CSV) export is impractical for retrospective multisite use. We describe an open-source pipeline that recovers structured Pentacam measurements from archives.
Methods:
import_pentacam is an open-source Rust tool that extracts up to 66 numerical fields and embedded corneal-map images per examination from DICOM, PDF, or image inputs, with single-file, file-list, and recursive picture archiving and communication system (PACS) directory modes supporting continuous incremental updates. Cross-firmware layout variation is normalized by affine transforms onto printout templates. The pipeline was developed on 300 examinations across three printout types and evaluated on a 200-examination holdout; Belin/Ambrósio Ectasia was added as a new printout type without retraining and tested on 333 examinations. Ground truth was derived from automated annotators with manual review of disagreements.
Results:
Field-level accuracy was 99.46% on training, 98.70% on the holdout, and 99.03% on the Belin/Ambrósio corpus. Agreement with paired DICOM Structured Reports was 100% on 518 fields. Institutional deployment recovered 126,184 eye visits from 29,550 patients across an 18-year archive.
Conclusions:
Automated recovery of structured Pentacam data from clinical DICOM archives is feasible at large multisite institutional scale. The software supports continuous incremental updates and is deployable at other Pentacam-equipped institutions for longitudinal ectasia research.
Translational Relevance:
Routinely collected institutional Pentacam examinations are a substantial resource for longitudinal corneal tomography research. This pipeline converts that resource into structured data without disrupting clinical workflows, enabling continuously updated retrospective cohorts and federated extraction across institutions.
