Why Decentralized Storage is Critical for Medical Imaging Sovereignty

Replaces opaque cloud bills with a transparent, open market for provable storage. Its cryptographic proofs guarantee data integrity over decades, a non-negotiable for longitudinal studies and legal compliance.\n- Cost: ~$0.0000002/GB/month for cold storage, undercutting AWS S3 Glacier by ~75%.\n- Guarantee: Proof-of-Replication and Proof-of-Spacetime provide verifiable custody, eliminating 'trust-me' audits.

Solves the data rot problem for critical medical archives. Pay once, store forever with built-in endowment, making imaging data a permanent, immutable asset with a complete audit trail.\n- Model: Single upfront fee for 200+ years of storage, predictable for long-term budgeting.\n- Integrity: Each image's hash is woven into the blockweave, creating an unbreakable chain of custody for regulatory audits.

Breaks vendor lock-in by making medical images addressable by content (CID), not location. Enables peer-to-peer sharing between institutions without central servers, critical for second opinions and research collaboration.\n- Protocol: Content Identifiers (CIDs) ensure the image itself is the source of truth, not a mutable URL.\n- Speed: Local network caching can reduce retrieval latency for frequently accessed images by >90% versus cloud fetch.

Public blockchain storage seems antithetical to patient privacy. The solution is client-side encryption and zero-knowledge proofs, making the network a dumb hard drive for ciphertext.\n- Approach: Protocols like Bacalhau (compute-over-data) and Lit Protocol (access control) enable private computation on encrypted DICOM files.\n- Compliance: Encryption keys are held off-chain by the data owner, making the storage provider a mere custodian of meaningless bits.

Removes migration friction by offering a decentralized backend with an S3-compatible API. Targets hospitals with existing PACS systems that can't afford a full stack rewrite.\n- Performance: Global edge caching delivers <100ms latency for hot data, matching centralized CDNs.\n- Security: Client-side AES-256-GCM encryption and erasure coding across >80 global nodes by default.

Medical imaging is static, but patient metadata is not. These protocols provide mutable, composable data layers on top of immutable storage, enabling updatable consent logs and AI model attribution.\n- Use Case: Streams (Ceramic) track patient consent changes; Tables (Tableland) log which AI model analyzed an MRI, creating a tamper-proof audit trail.\n- Composability: Data becomes a portable asset that can be permissioned to new DeFi health pools or DeSci research DAOs.

Proprietary PACS (Picture Archiving Systems) create data silos, charging $1-5 per GB/year for archival and exorbitant egress fees for patient migration. This locks hospitals into contracts and prevents patient data portability.

• Monopoly Pricing: Single vendor controls access, audit, and pricing.
• Fragmented Records: Patient history is scattered across incompatible systems.
• Innovation Stifle: New AI diagnostic tools can't access the unified dataset.

Arweave's permaweb provides a one-time, upfront payment for ~200 years of storage. Patient imaging data, encrypted and anchored on-chain, becomes an immutable, sovereign asset.

• True Ownership: Cryptographic keys control access, not hospital admin logins.
• Data Persistence: Eliminates costly, recurring vendor maintenance fees.
• Global Accessibility: Authorized specialists anywhere can access a unified record.

A hybrid stack uses Filecoin for verifiable, incentivized hot/cold storage and IPFS for low-latency content delivery. This mirrors clinical workflows where recent images need <2s retrieval.

• Economic Layer: Filecoin's proof-of-spacetime ensures data integrity.
• Performance Layer: IPFS provides ~500ms retrieval via distributed caching.
• Modular Design: Enables plug-in compute (e.g., Bacalhau, Fluence) for on-demand AI analysis.

Patient-consented imaging data becomes a composable asset in a tokenized data economy. Platforms like Ocean Protocol enable patients to license de-identified datasets for AI training, creating a new revenue stream.

• Monetization: Patients earn from research, breaking the free-data-for-tech-giants model.
• Quality Data: Incentivizes contribution to high-fidelity, labeled medical datasets.
• Auditable Consent: Smart contracts enforce usage terms and transparently track access.

zk-SNARKs (e.g., zkSync, Aztec) enable compliance without disclosure. A verifier can cryptographically prove a scan is from an accredited facility and that the patient has consented, without leaking the image or PHI.

• Privacy-Preserving: Raw data never leaves patient custody.
• Regulatory Proof: Audit trails are generated as verifiable compute.
• Selective Disclosure: Patients reveal only specific metadata (e.g., "MRI, 2024, knee") for network queries.

Sovereign imaging enables a persistent, patient-controlled health avatar. This portable medical record moves with the patient across borders and providers, interoperable via open standards like DICOM-on-IPLD.

• Global Continuity: A doctor in Berlin can access childhood scans from Tokyo.
• Longitudinal Analysis: Enables lifelong trend tracking for preventative care.
• Provider Agnostic: Breaks the hospital-as-data-owner paradigm forever.