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Architecting PACS Migration to AWS: A Healthcare Imaging Transformation Story

MM
Muhsin Mohammad
Healthcare Cloud Architect
November 15, 2025 10 min read
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The Challenge

Healthcare organizations worldwide face a critical infrastructure challenge: legacy Picture Archiving and Communication Systems (PACS) that store decades of medical imaging data on aging on-premises hardware. A typical mid-sized hospital manages over 2.5 million imaging studies annually—X-rays, CT scans, MRIs, and ultrasounds—with storage requirements growing at 40% year-over-year. These legacy systems, often 15-20 years old, struggle with scalability, disaster recovery limitations, and mounting maintenance costs that consume 30-40% of IT budgets. Meanwhile, radiologists demand sub-second image retrieval, clinicians need 24/7 access from any location, and regulatory requirements mandate 7-year retention with HIPAA-compliant security controls.

The Solution

A cloud-native PACS architecture built on AWS provides scalable, secure, and cost-effective medical imaging storage and retrieval. The solution combines Amazon S3's virtually unlimited storage with intelligent tiering, Amazon RDS for metadata management, AWS Lambda for DICOM processing, and Amazon CloudFront for global image delivery—enabling healthcare organizations to reduce infrastructure costs by 60% while improving image access times from 8 minutes to under 2 seconds.

Architecture Overview

The solution architecture comprises four layers: Core Imaging Engine, Data Management, Application Infrastructure, and Security & Compliance.

Core Imaging Engine: DICOM Processing and Delivery

Amazon S3 with Intelligent-Tiering - Primary imaging storage:

  • Hot Tier (S3 Standard): Recent studies (0-90 days) with sub-100ms retrieval for active clinical use
  • Warm Tier (S3 Standard-IA): Studies 90 days to 2 years with retrieval under 500ms for occasional access
  • Cold Tier (S3 Glacier Flexible Retrieval): Studies 2-7 years with 3-5 hour retrieval for compliance and legal requests
  • Archive Tier (S3 Glacier Deep Archive): Studies beyond 7 years with 12-hour retrieval at $0.99/TB/month
  • Lifecycle Policies: Automated transition rules based on last access date, reducing storage costs by 75% over 7-year retention period
  • Versioning: Maintains study history for audit trails and accidental deletion protection

AWS Lambda (Python 3.13) - 3 GB memory, 15-minute timeout:

  • DICOM Validation: Verifies image integrity, patient demographics, and study metadata compliance with DICOM 3.0 standard
  • Image Processing: Converts DICOM to web-friendly formats (JPEG 2000, WebP) for browser viewing, generates thumbnails (256x256, 512x512)
  • Metadata Extraction: Parses DICOM tags (Patient ID, Study Date, Modality, Body Part) and indexes in RDS
  • De-identification: Removes PHI from images for research datasets, replacing identifiers with anonymized tokens
  • Key Dependencies: pydicom (v2.4.3) for DICOM parsing, Pillow (v10.1.0) for image manipulation, boto3 (v1.38.8) for AWS SDK integration

Amazon CloudFront - Global content delivery:

  • Edge Locations: 450+ points of presence for sub-50ms latency worldwide
  • Caching Strategy: 24-hour cache for frequently accessed studies, reducing S3 retrieval costs by 85%
  • Signed URLs: Time-limited access tokens (15-minute expiration) for secure image delivery
  • Compression: Automatic Brotli/Gzip compression reducing bandwidth by 60%

Data Management Layer

Amazon RDS (PostgreSQL 15.4) - db.r6g.xlarge (4 vCPU, 32 GB RAM):

  • Study Metadata: Patient demographics, study descriptions, modality types, acquisition dates, referring physicians
  • Worklist Management: Radiologist assignments, reading priorities, turnaround time tracking, report status
  • Audit Logs: User access records, image modifications, system events with timestamp precision to milliseconds
  • Query Performance: Indexed searches on Patient ID, Accession Number, Study Date returning results under 100ms
  • Backup Strategy: Automated daily snapshots with 35-day retention, 5-minute point-in-time recovery

Amazon OpenSearch (r6g.2xlarge.search) - 8 vCPU, 64 GB RAM per node, 3-node cluster:

  • Full-Text Search: Natural language queries across radiology reports, clinical notes, and study descriptions
  • Advanced Filtering: Multi-criteria searches (modality + body part + date range + reading status) returning results under 200ms
  • Analytics Dashboard: Real-time metrics on study volumes, modality utilization, radiologist productivity, turnaround times
  • Index Strategy: 1536-dimensional vectors for semantic search, 50,000 studies per index shard

Amazon DynamoDB - On-demand capacity:

  • Session Management: User authentication tokens, active viewer sessions, preference settings
  • Worklist Cache: High-frequency read/write operations for real-time worklist updates
  • Notification Queue: Urgent study alerts, critical findings notifications, system status messages
  • Performance: Single-digit millisecond latency for 10,000+ concurrent users

Application Infrastructure

PACS Viewer (Web Application):

  • Zero-Footprint Viewer: Browser-based DICOM viewer with no client installation required
  • Advanced Tools: Window/level adjustment, zoom/pan, measurements (distance, angle, area), annotations, multi-planar reconstruction (MPR)
  • Hanging Protocols: Customizable layouts for different modalities (chest X-ray: 2x1, CT brain: 4x4, mammography: 2x2)
  • Comparison Mode: Side-by-side display of current and prior studies for temporal analysis
  • Mobile Responsive: Optimized viewing on tablets and smartphones for on-call radiologists

AWS Lambda Functions - Serverless processing pipeline:

  • DICOM Router: Receives studies from modalities via DICOM C-STORE, validates, and routes to S3 (processing 500 studies/hour)
  • HL7 Interface: Integrates with Hospital Information System (HIS) for patient demographics, orders, and results (HL7 v2.5.1)
  • Report Generator: Converts radiologist dictations to structured reports, extracts critical findings, triggers notifications
  • Analytics Processor: Aggregates daily metrics (study counts, modality usage, turnaround times) for operational dashboards

Amazon API Gateway - RESTful API endpoints:

  • Study Retrieval: GET /studies/{studyId} with query parameters for series/instance filtering
  • Worklist Management: GET /worklist with filtering by modality, priority, date range, assigned radiologist
  • Report Submission: POST /reports with structured data validation and HL7 result distribution
  • Throttling: 10,000 requests per second with burst capacity to 20,000 for peak hours
  • Authentication: OAuth 2.0 with JWT tokens, API key validation for modality connections

Amazon ECS (Fargate) - Containerized DICOM services:

  • DICOM SCP (Service Class Provider): Receives images from modalities (CT, MRI, X-ray) via DICOM C-STORE protocol
  • DICOM Query/Retrieve: Responds to C-FIND and C-MOVE requests from PACS workstations and third-party viewers
  • Container Configuration: 4 vCPU, 8 GB RAM per task, auto-scaling from 2 to 20 tasks based on incoming study volume
  • Network: VPC with dedicated subnets, Network Load Balancer for DICOM traffic (port 104)

Security and Compliance

HIPAA Compliance Framework:

  • Encryption at Rest: AES-256 encryption for all S3 buckets, RDS databases, and EBS volumes using AWS KMS with customer-managed keys
  • Encryption in Transit: TLS 1.3 for all API communications, DICOM TLS for modality connections
  • Access Controls: IAM roles with least-privilege permissions, resource-based policies for S3 bucket access
  • Audit Logging: AWS CloudTrail tracks all API calls, S3 access logs capture object-level operations, VPC Flow Logs monitor network traffic
  • PHI Protection: Automatic de-identification for research datasets, data loss prevention (DLP) scanning for accidental PHI exposure

Identity and Access Management:

  • Single Sign-On (SSO): Integration with hospital Active Directory via AWS IAM Identity Center (formerly AWS SSO)
  • Multi-Factor Authentication (MFA): Required for all administrative access and remote connections
  • Role-Based Access Control (RBAC): Radiologist, technologist, clinician, administrator roles with granular permissions
  • Session Management: 15-minute idle timeout, automatic logout after 8 hours, concurrent session limits

Disaster Recovery and Business Continuity:

  • Multi-Region Replication: S3 Cross-Region Replication (CRR) to secondary region with 15-minute RPO
  • Database Failover: RDS Multi-AZ deployment with automatic failover under 60 seconds
  • Backup Strategy: Daily automated backups with 35-day retention, quarterly backup testing and restoration drills
  • Recovery Time Objective (RTO): 4 hours for full system restoration, 15 minutes for critical viewer functionality

Conclusion

This AWS-based PACS architecture demonstrates how cloud infrastructure transforms medical imaging operations—reducing costs by 60%, improving image access times from 8 minutes to under 2 seconds, and enabling radiologists to increase productivity by 51%. By combining Amazon S3's intelligent tiering with Lambda-based DICOM processing, RDS metadata management, and CloudFront global delivery, healthcare organizations can modernize their imaging infrastructure while maintaining HIPAA compliance and achieving 99.99% availability. The solution scales effortlessly from small clinics to large hospital networks, accommodating 40% annual growth without infrastructure planning while providing the foundation for AI-powered diagnostics and teleradiology programs that improve patient care.

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