Mobile Imaging Workflows

Why Mobile Imaging Needs More Control

Mobile imaging vehicles operate where network connectivity is intermittent, unreliable, or entirely unavailable for stretches of the day. That is manageable for small studies. It becomes much more serious as study sizes grow — large CT volumes, multi-sequence MR, digital breast tomosynthesis — and downstream workflows become less forgiving:

• Cellular signals drop mid-transfer
• VPN tunnels time out
• LTE throughput fluctuates wildly between stops

Without an intermediary, these conditions lead to failed sends at the modality, partial studies in PACS, duplicated exams, patient-matching risk, and technologists managing retransmissions instead of patients.

DICOM Capacitor absorbs these problems without changing the technologist workflow.

Typical Mobile Imaging Setup

The modality talks only to Capacitor. Capacitor worries about connectivity, retries, integrity, and delivery.

How the Workflow Holds Together

Study Acquisition

• Modality sends the study to Capacitor via standard DICOM C-STORE
• Capacitor is on the local network, so transfer completes at LAN speed — effectively instant
• No waiting, no failed sends on the modality console, no technologist intervention required

Local Caching and Validation

Once received, Capacitor:

• Writes the study to local encrypted storage
• Validates SOP completeness, image count, and DICOM header integrity
• Queues the study for delivery

At this point the study is safe, even if the vehicle loses signal entirely.

Connectivity-Aware Transmission

When a network path is available and the current delivery policy allows it, Capacitor begins transmitting queued studies to PACS asynchronously:

• Automatic retries on failure
• Bandwidth throttling to avoid saturating the link
• Resume-on-failure — picks up exactly where it left off
• No corruption, no duplicates, no human involvement required

Interrupted Transfer Resume

Transmission batch size is fully configurable:

• By count — a specific number of images at a time
• By size — a defined amount in megabytes or gigabytes
• By study — entire studies as a unit
• Single or multiple associations — Capacitor manages both

If the connection drops, Capacitor tracks exactly which images were successfully acknowledged and resumes by sending only the balance of undelivered images. Nothing is resent unnecessarily, and nothing is lost.

Guaranteed Delivery

A study is marked complete only when:

• PACS sends a successful DICOM acknowledgment
• All SOP instances are confirmed delivered

Until then, the study remains queued and retries continue automatically.

Worklist Caching

In mobile environments, the modality needs access to a worklist to pull scheduled orders — but the worklist server is back at the facility, on the other side of an unreliable link. Capacitor solves this by acting as a local worklist proxy.

Zero-Configuration Destination Management

In many mobile programs, a single vehicle travels between multiple facilities. Each facility has its own PACS, and images from one site must never be delivered to another.

Capacitor supports a zero-configuration mode:

• Modality sends to one destination — the local Capacitor
• Capacitor manages all downstream routing automatically
• Uses geolocation, network detection via IP address, and node detection to determine the current facility
• Switches destinations automatically when the vehicle moves
• Optionally isolates the cache so studies from the previous stop don't straggle to the new location
• Each facility receives exactly and only the images that belong to it

Flexible Delivery Policies

Some programs want studies moving over wireless immediately. Others prefer to hold them for a known network or scheduled window. Capacitor supports both while preserving the same fire-and-forget experience for technologists:

These policies can be combined. Studies are still validated, queued, and deduplicated regardless of when delivery occurs. The technologist workflow stays the same: acquire the exam, send to Capacitor, move on.

Adaptive Network Intelligence

Capacitor continuously monitors network conditions and self-tunes for best-effort delivery:

• Detects current transmission speed in real time
• Reconfigures timeout values and retry intervals on the fly
• Widens tolerances on slow, intermittent connections to maximize delivery within each connectivity window
• Tightens parameters when throughput improves to move studies faster
• Learns from its own success and failure rates — no manual tuning required

This adaptive behavior extends to time-to-live values for queued images. Network conditions change from stop to stop, and study sizes vary widely — from lightweight ultrasound to large CT or DBT acquisitions. Capacitor adjusts automatically.