Why it matters
Without AI analysis, tendon issues may go unnoticed until advanced degeneration or re-injury occurs, causing costly downtime, missed racing opportunities, and ownership disputes.
From design to safety
Design
AI-guided tendon health strategy
Data inputs define selection criteria, scan protocols, baseline cross-sectional area targets, lesion risk profiles, and scanning frequency aligned with training cycles and welfare policy, plus documentation for passport and stable inspections.
- superficial digital flexor tendon
- deep flexor tendon
- suspensory ligament
- scans
Build
integrate ultrasound workflow and records
Install high-frequency linear transducers, portable carts, and secure data servers; implement standardized scanning templates, lesion tagging with anatomical coordinates, and automated data pipelines into the horse medical portal and stable management ERP.
- ultrasound transducer
- scans
- lesions
Operation
continuous monitoring through scans
Schedule weekly or biweekly scans, compare sectional readings with baseline, track progression via AI risk score, automatically adjust training load, and flag rehab windows in the master calendar.
- scans
- lesions
Maintenance
verify imaging integrity and records
Perform quarterly calibrations of transducers, conduct image quality audits with phantom tests, and maintain a complete, time-stamped audit trail for each scan to satisfy welfare and regulator checks.
- ultrasound transducer
- scans
- lesions
Safety
safeguard welfare and compliance
Automated alerts trigger veterinary review for any progressive lesion, run drug withdrawal checks against passport data, ensure stable inspection readiness, and archive all actions in regulatory files with versioning and access controls.
- scans
- lesions
- suspensory ligament
Part by part
- 1
superficial digital flexor tendon
- Watch for
- early microtears or thinning signs indicating overreach or overuse.
- AI action
- AI detects pattern shifts in cross-sectional thickness and echoes, flags high-risk scans for vet review, initiates conservative rehab protocol if confirmed.
- 2
deep flexor tendon
- Watch for
- signal changes suggesting strain near the carpus or metacarpophalangeal region.
- AI action
- AI flags tapering CSA and edema, prompts rehab or rest orders, schedules follow-up ultrasound to confirm healing trajectory.
- 3
suspensory ligament
- Watch for
- new or enlarging lesions at ligament branches or body.
- AI action
- AI triggers load reduction and targeted physio programs, recommends ultrasound re-evaluation in 14 days if lesion growth persists.
- 4
scans
- Watch for
- inconsistent image quality or missing frames across sessions.
- AI action
- AI prompts recalibration or retakes, logs integrity of imaging series, records operator ID and probe serial number.
- 5
lesions
- Watch for
- presence of fiber disruption or scar tissue.
- AI action
- AI classifies lesion stage and informs treatment pathway and withdrawal times, stores location-based lesion maps for rehab planning.
- 6
ultrasound transducer
- Watch for
- calibration drift or probe wear affecting image clarity.
- AI action
- AI flags hardware maintenance need and schedules calibration, records probe history and service events.
Worked example
Catching a subtle SDFT change before a race
Illustrative scenario with sample data.
A gelding scheduled for a flat race shows minor SDFT signal change on a routine scan; AI flags potential early degeneration.
Signal in
horseId: 112, date: 2026-11-01, location: stable A, region: forelimb, tendon: SDFT, CSA: 0.95 cm2, echotexture: mild heterogeneous, lesionFlag: false, previousCSA: 0.88 cm2
System out
alert: SDFT early-change detected; recommended rest 7 days, re-scan in 14 days, update training plan; record in medication and passport notes.
Human sign-off: Yard vet reviews the image, approves rest period and rescan, trainer signs off on temporary withdrawal and subsequent program.
How to roll it out
Phase 1
Weeks 1 to 4: Baseline
Establish scan protocols, baseline CSA values, label conventions, and interoperability; integrate data with welfare and entries systems to map risk to events.
Phase 2
Weeks 5 to 8: Deepening
Implement automated scoring, lesion tagging, and threshold alerts; train staff on interpretation, action triggers, and documentation standards for welfare audits.
Phase 3
Weeks 9 to 12: Stabilization
Embed AI-driven decisions into routine, with governance audits, regular data integrity checks, and cross-department sign-off procedures.
Where people stay in charge
- Decisions on rest, withdrawal, and rehab must be signed off by the yard vet or licensed trainer.
- All imaging data must be auditable with time-stamped records for welfare and regulatory inspections.
- No autonomous withdrawal or race-entry actions without veterinary and regulatory validation and log adherence.
Questions owners and crews ask
What happens if the AI flags a potential SDFT issue before training today?
If AI flags an issue, the yard vet reviews the image, confirms the finding, and may adjourn training or modify work until a re-scan confirms stability; records updated in passport and notes.
How often should scans be performed for a high-risk tendon?
In high-risk cases, scans should occur at least weekly during rehab phases and before every race entry if the risk score remains elevated; findings drive rehab pacing and race eligibility decisions.
Who signs off on withdrawal times and race entries related to tendon data?
Withdrawal decisions and race entries must be signed off by the licensed trainer in consultation with the yard vet and regulator guidelines; all actions logged in the horse's medical passport.
How is data kept compliant with regulation and passport records?
All scan results, lesion classifications, and action notes are logged in the horse’s medical passport and stable records with audit trails, time stamps, and access controls to meet inspections.