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Innovative Medical Technology Overview: Artificial intelligence (AI) estimated computed tomography fractional flow reserve (CT-FFR). May 2026, Key messages.","title":"Innovative Medical Technology Overview: Artificial intelligence (AI) estimated computed tomography fractional flow reserve (CT-FFR)","url":"https://admin.shtg.scot/media/udwcvr0v/2026-05-18-ct-ffr-imto-v10.pdf","written_by":"independent","quote":"AI-estimated CT-FFR showed good agreement with results from invasive fractional flow reserve (FFR) measurement for assessing functionally significant coronary artery stenosis. The use of non-invasive AI-estimated CT-FFR could avoid the need for invasive FFR in some patients."}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["evidence"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"sources[].upstream_sources":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"strategic_assessments[]":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"strategic assessments"},"summary":{"state":"value_present","value":{"kind":"record_fields","fields":{"summary":"SHTG found that machine-learning CT-FFR agrees well with invasive FFR, with pooled sensitivity of 0.86 and specificity of 0.87 per patient. No study followed patients or costs.","account":"The Scottish Health Technologies Group (SHTG) published an overview of AI-estimated CT fractional flow reserve (CT-FFR) in May 2026. The software computes FFR, a measure of blood flow past a coronary narrowing, from a standard CT angiogram. In some patients, it could replace an invasive pressure-wire test. SHTG reviewed three meta-analyses. In one, covering 17 studies and 3,255 patients, pooled sensitivity was 0.86 and specificity 0.87 per patient. The tools in that analysis included cFFR and DEEPVESSEL-FFR. In an indirect comparison, AI tools were as specific as tools based on computational fluid dynamics but less sensitive. SHTG concluded that AI-estimated CT-FFR agrees well with invasive FFR and could spare some patients invasive testing. It found substantial uncertainty because studies defined AI differently, used different thresholds and were mostly retrospective. No study looked at later tests, health outcomes, patient experience or costs. No study tested whether CT-FFR adds value to CT angiography alone."}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["summary","account"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"systems[].autonomy_permissions":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].component_role":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].deployment_configuration":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].inputs_outputs":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].model_name":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].model_version":{"state":"value_present","value":{"kind":"record_fields","fields":{"model_version":"cFFR versions 1.4 to 3.2 in one meta-analysis"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["model_version"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"systems[].product_name":{"state":"value_present","value":{"kind":"record_fields","fields":{"system":"Machine-learning CT-FFR software in the meta-analyses that SHTG reviewed: cFFR, DEEPVESSEL-FFR, skCT-FFR and XFFR"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["system"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"systems[].provider":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"taxonomy_crosswalks[]":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"title":{"state":"value_present","value":{"kind":"record_fields","fields":{"title":"SHTG finds that AI-estimated CT-FFR agrees well with invasive FFR and could spare some patients invasive testing, though no outcome studies exist","headline":"*AI-estimated CT-FFR* agrees well with invasive heart tests, SHTG finds"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["title","headline"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"version":{"state":"value_present","value":{"kind":"identifiers","identifiers":["50ada1515d20e5ffb7eab593676322a9bc1b397eddc7da40e92b50ed12ae5197"],"role":"SHA-256 of the complete public record and its assessments"},"provenance":{"kind":"curatorial","basis":"SHA-256 of the public record, its assessments, and its displayed answers and notes, excluding its own identifier and the derived coverage summary.","record_fields":[],"source_refs":[]},"review_state":"record_mapped","coverage":"complete"},"workflow":{"state":"value_present","value":{"kind":"record_fields","fields":{"account":"The Scottish Health Technologies Group (SHTG) published an overview of AI-estimated CT fractional flow reserve (CT-FFR) in May 2026. The software computes FFR, a measure of blood flow past a coronary narrowing, from a standard CT angiogram. In some patients, it could replace an invasive pressure-wire test. SHTG reviewed three meta-analyses. In one, covering 17 studies and 3,255 patients, pooled sensitivity was 0.86 and specificity 0.87 per patient. The tools in that analysis included cFFR and DEEPVESSEL-FFR. In an indirect comparison, AI tools were as specific as tools based on computational fluid dynamics but less sensitive. SHTG concluded that AI-estimated CT-FFR agrees well with invasive FFR and could spare some patients invasive testing. It found substantial uncertainty because studies defined AI differently, used different thresholds and were mostly retrospective. No study looked at later tests, health outcomes, patient experience or costs. No study tested whether CT-FFR adds value to CT angiography alone.","replication":{"produced_by":["The software computed FFR from standard CT coronary angiography images.","The studies measured invasive FFR in the same patients as the reference test."],"must_hold":["CT images are of high quality, since some studies excluded poor-quality images and so inflated accuracy.","Patients are adults with stable chest pain and suspected coronary artery disease."],"echoes":[]}}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["account","replication"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"}},"summary":{"total":91,"addressed":91,"known":28,"reviewed":2,"reviewed_complete":2,"reviewed_partial":0,"record_mapped":26,"review_not_assessed":63,"not_assessed":0,"complete":false,"by_state":{"value_present":28,"not_reported":0,"unresolved":63,"not_assessed":0,"not_applicable":0,"withheld":0,"source_unavailable":0}}},"presentation_version":"33e120c20a7169e6924aed621754d5613cc216fd45e1acd2fc03fca7966eba59"}