Simulator · v1.0
STEMI Simulator — Culprit Artery Localisation and ST-Elevation Mimics
Occlude a coronary segment and watch the 18-lead ECG that results — then work backwards from the tracing to the culprit vessel, with the mimics that catch people out.
Pick an occlusion site on the coronary tree and the ECG follows from it. Proximal LAD, first diagonal, septal branch, proximal or distal RCA, circumflex, obtuse marginal, PDA, left main — each produces its own pattern, and the 3D angiographic view sits alongside the tracing so the anatomy and the ECG stay connected.
Run it the other way for teaching: show the tracing first, ask the room to name the vessel, then reveal the occlusion. Quiz mode does exactly this.
Localising the culprit
The quick rules are on screen, but the simulator exists because rules learnt as a list do not survive contact with an atypical tracing. Moving the occlusion one segment at a time — proximal LAD, then past the first diagonal, then past the first septal — shows why the rules work and where they stop working.
Posterior infarction is worth its own five minutes. So is aVR in left main and severe triple-vessel disease, where the pattern is the diagnosis and the territory logic runs backwards.
The mimics
ST elevation is not the same thing as infarction, and the mimics are where diagnostic errors concentrate: acute pericarditis, benign early repolarisation, Brugada type 1, LV aneurysm, Takotsubo, hyperkalaemia, and the discordant elevation of a paced or bundle-blocked ventricle. Each is included so trainees see the differences side by side rather than as separate lectures months apart.
There is also the reverse problem — occlusion without ST elevation. De Winter T waves and hyperacute T waves are included for the same reason.
Time and evolution
Occlusion time is adjustable, so hyperacute T waves, established elevation, T inversion and Q wave formation appear as a sequence rather than as four unrelated figures in a textbook.
What the model simplifies
Territories follow conventional teaching rather than any individual patient’s anatomy, and dominance is a switch rather than a spectrum. The ECG is generated from the model, not recorded from patients, so it is cleaner than anything you will see on a real machine. That predictability is useful for teaching and is the reason this is not a diagnostic tool.