How Clario technology detects PHI/PII in DICOM images using Amazon Bedrock

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Clario, part of Thermo Fisher Scientific, uses Amazon Bedrock to automate PHI (Protected Health Information) and PII (Personally Identifiable Information) detection across thousands of DICOM (Digital Imaging and Communications in Medicine) image slices in clinical trials. Each image slice may carry PII or PHI hidden in metadata tags, in custom vendor fields, or burned directly into the pixels. Across imaging sites, central labs, sponsors, and CROs (Contract Research Organizations), every one of those slices must be cleared of PII and PHI before the image moves downstream. DICOM is the universal standard for storing, transmitting, and managing medical imaging data across healthcare systems. In clinical trials, DICOM images play a critical role by providing objective, quantifiable evidence of a patient’s medical condition throughout the study lifecycle. From baseline imaging to follow-up scans, modalities such as MRI, CT, PET, and X-ray generate DICOM files. Radiologists, clinicians, and sponsors use these files to assess treatment efficacy, monitor disease progression, and support regulatory submissions. These images serve as a core component of the clinical evidence package, making their accurate management and standardized handling essential to trial integrity. In this post, we share how the Clario team designed an automated PHI and PII detection solution on AWS for DICOM imaging data, the key design decisions behind the architecture, and the lessons the team learned along the way. About Clario, part of Thermo Fisher Scientific Clario science and endpoint solutions …

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