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Siemens Healthineers machine learning based ct ffr software
$Flowchart of study design. DM, diabetes mellitus; CCTA, coronary computed tomography angiography; CAD, coronary artery disease; <t>CT-FFR,</t> CCTA-derived fractional flow reserve; FAI, fat attenuation index; MACE, major adverse cardiovascular events$
Machine Learning Based Ct Ffr Software, supplied by Siemens Healthineers, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/machine-learning+software/ct+ffr/pmc12870152-141-6-12
Average 86 stars, based on 1 article reviews

machine learning based ct ffr software - by Bioz Stars, 2026-09

86/100 stars

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1) Product Images from "Incremental prognostic value of pericoronary fat attenuation index in diabetic patients with non-obstructive coronary artery disease"

Article Title: Incremental prognostic value of pericoronary fat attenuation index in diabetic patients with non-obstructive coronary artery disease

Journal: BMC Medical Imaging

doi: 10.1186/s12880-025-02146-6

$Flowchart of study design. DM, diabetes mellitus; CCTA, coronary computed tomography angiography; CAD, coronary artery disease; CT-FFR, CCTA-derived fractional flow reserve; FAI, fat attenuation index; MACE, major adverse cardiovascular events$
Figure Legend Snippet: Flowchart of study design. DM, diabetes mellitus; CCTA, coronary computed tomography angiography; CAD, coronary artery disease; CT-FFR, CCTA-derived fractional flow reserve; FAI, fat attenuation index; MACE, major adverse cardiovascular events

Techniques Used: Computed Tomography, Derivative Assay

$Kaplan–Meier curves for cumulative MACE rates ( A , B , C ) and cumulative MACCE rates ( D , E , F ) for stratified groups based on HRP, CT-FFR, and pericoronary FAI. MACE, major adverse cardiovascular events; MACCE, major adverse cardiovascular and cerebrovascular events; HRP, high-risk plaque; CT-FFR, CCTA-derived fractional flow reserve; FAI, fat attenuation index; HU, Hounsfield units$
Figure Legend Snippet: Kaplan–Meier curves for cumulative MACE rates ( A , B , C ) and cumulative MACCE rates ( D , E , F ) for stratified groups based on HRP, CT-FFR, and pericoronary FAI. MACE, major adverse cardiovascular events; MACCE, major adverse cardiovascular and cerebrovascular events; HRP, high-risk plaque; CT-FFR, CCTA-derived fractional flow reserve; FAI, fat attenuation index; HU, Hounsfield units

Techniques Used: Derivative Assay

$ROC curves of all models in predicting MACE ( A ) and MACCE ( B ). Model 1: HRP; Model 2: CT-FFR; Model 3: pericoronary FAI; Model 4: HRP + CT-FFR; Model 5: Model 4 + pericoronary FAI. ROC, receiver operating characteristic; MACE, major adverse cardiovascular events; MACCE, major adverse cardiovascular and cerebrovascular events; HRP, high-risk plaque; CT-FFR, CCTA-derived fractional flow reserve; FAI, fat attenuation index; AUC, area under the curve; CI, confidence interval$
Figure Legend Snippet: ROC curves of all models in predicting MACE ( A ) and MACCE ( B ). Model 1: HRP; Model 2: CT-FFR; Model 3: pericoronary FAI; Model 4: HRP + CT-FFR; Model 5: Model 4 + pericoronary FAI. ROC, receiver operating characteristic; MACE, major adverse cardiovascular events; MACCE, major adverse cardiovascular and cerebrovascular events; HRP, high-risk plaque; CT-FFR, CCTA-derived fractional flow reserve; FAI, fat attenuation index; AUC, area under the curve; CI, confidence interval

Techniques Used: Derivative Assay

$A representative case of DM patients with non-obstructive CAD. CCTA showed CAD-RADS 2, with 25–49% stenosis in LAD as well as 1–24% stenosis in RCA, and there was a HRP characterized by low attenuation plaque and spotty calcification in LAD; CT-FFR was 0.88; pericoronary FAI was − 60.97 HU. This patient underwent acute non-ST-segment elevation myocardial infarction 40 months after CCTA. DM, diabetes mellitus; CAD, coronary artery disease; CCTA, coronary computed tomography angiography; CAD-RADS, Coronary Artery Disease-Reporting and Data System; LAD, left anterior descending; LCX, left circumflex; RCA, right coronary artery; HRP, high-risk plaque; CT-FFR, CCTA-derived fractional flow reserve; FAI, fat attenuation index; HU, Hounsfield units$
Figure Legend Snippet: A representative case of DM patients with non-obstructive CAD. CCTA showed CAD-RADS 2, with 25–49% stenosis in LAD as well as 1–24% stenosis in RCA, and there was a HRP characterized by low attenuation plaque and spotty calcification in LAD; CT-FFR was 0.88; pericoronary FAI was − 60.97 HU. This patient underwent acute non-ST-segment elevation myocardial infarction 40 months after CCTA. DM, diabetes mellitus; CAD, coronary artery disease; CCTA, coronary computed tomography angiography; CAD-RADS, Coronary Artery Disease-Reporting and Data System; LAD, left anterior descending; LCX, left circumflex; RCA, right coronary artery; HRP, high-risk plaque; CT-FFR, CCTA-derived fractional flow reserve; FAI, fat attenuation index; HU, Hounsfield units

Techniques Used: Computed Tomography, Derivative Assay

Computed Tomography:

Article Title: Lesser Metatarsals Load after Minimally-Invasive Surgery for Hallux Valgus Correction: A Finite Element Model
Article Snippet: .. The CT scan machine used was Emotion (16 channels, Siemens Healthineers) with a slice interval of 2 mm. ..

Software:

Article Title: Prognostic value of non-alcoholic fatty liver disease, pericoronary fat attenuation index and computed tomography-derived fractional flow reserve in diabetic patients with suspected coronary artery disease.
Article Snippet: Background: This study aimed to investigate the predictive value of non-alcoholic fatty liver disease (NAFLD), pericoronary fat attenuation index (FAI), and computed tomography-derived fractional flow reserve (CT-FFR) for major adverse cardiovascular events (MACE) in diabetic patients with suspected coronary artery disease.. Methods: This study retrospectively included 466 diabetic patients who underwent coronary computed tomography angiography (CCTA) and non-contrast chest CT from January 2017 to December 2018.. The clinical data and imaging parameters of patients were collected.

Article Title: Incremental prognostic value of pericoronary fat attenuation index in diabetic patients with non-obstructive coronary artery disease
Article Snippet: .. CT-FFR analysis was performed using a machine learning-based CT-FFR software (version 3.5, Siemens Healthineers, Germany). ..

Article Title: Incremental prognostic value of pericoronary fat attenuation index in diabetic patients with non-obstructive coronary artery disease.
Article Snippet: .. 210 CT-FFR analysis 211 CT-FFR analysis was performed using a machine learning-based 212 CT-FFR software (version 3.5, Siemens Healthineers, Germany). ..

Imaging:

Article Title: Cardiac Computed Tomography for the Assessment of Myocardial Bridging: A Scoping Review of the Emerging Role of Artificial Intelligence and Machine Learning.
Article Snippet: .. Patients with abnormal FFR were less likely to be asymptomatic and more likely to have typical anginal chest pain Zhou 2019 [57] JACC: Cardiovascular Imaging China Retrospectivecohort To investigate the role of CT-FFR in predicting proximal plaque formation associated with MB in the LAD using ML approaches Patients with MB in the LAD and no atherosclerosis on baseline CCTA who underwent follow-up CCTA with a minimum interval of 3 months 188 55 ± 6 68.6 ML-based CT-FFR (cFFR v3.0.0, Siemens Healthineers); ML-based prediction model using LASSO algorithms Computation of CT-FFR; ML models for prediction of plaque formation CT-FFR distal to LAD MB and ∆CT-FFR significantly differed between patients with CT MB LAD who developed plaque and those who did not. .. ML algorithms further identified CT-FFR and ∆CT-FFR as the strongest predictors of plaque formation proximal to MB LAD Zhou 2019 [38] Canadian Journal of Cardiology China Retrospectivecohort To study the diagnostic performance of ML-based CT-FFR to detect functional ischemia in MB with iFFR as the reference standard Patients who underwent CCTA for the evaluation of suspected or known CAD and were found to have LAD MB who then underwent ICA within 60 days of CCTA 104 61.2 ± 9.1 72.1 ML-based CT-FFR (cFFR v3.2.0, Siemens Healthineers) Automatic generation of centerline and luminal contours of coronary arteries; computation of CT-FFR CT-FFR has high diagnostic performance for functional ischemia in vessels with MB and concomitant proximal atherosclerotic disease compared with iFFR, regardless of length and depth of MB, with a low PPV for lesions of <70% stenosis Table 2.

Article Title: Cardiac Computed Tomography for the Assessment of Myocardial Bridging: A Scoping Review of the Emerging Role of Artificial Intelligence and Machine Learning.
Article Snippet: .. Study Journal Country Study Type Study Aim Population TotalParticipants Age % Male AI/ML Technique Purpose of AI Findings Jubran 2020 [58] Circulation: Cardiovascular Imaging United States Retrospective cohort To compare CT-FFR, dobutamine-stress dFFR, iFFR, and IVUS in assessing the hemodynamic significance of MB Patients with angina who had been found to have an MB in the LAD with ≤50% coronary artery stenosis by ICA and had undergone CCTA CT-FFR: 49 dFFR: 43 iFFR: 28 IVUS: 46 47.5 ± 13.7 39 ML-based CT-FFR (cFFR v3.1.2, Siemens Healthineers) Computation of CT-FFR CT-FFR values measured in LAD MB were lower than arteries without MB. ..

Diagnostic Assay:

Article Title: Cardiac Computed Tomography for the Assessment of Myocardial Bridging: A Scoping Review of the Emerging Role of Artificial Intelligence and Machine Learning.
Article Snippet: Patients with abnormal FFR were less likely to be asymptomatic and more likely to have typical anginal chest pain Zhou 2019 [57] JACC: Cardiovascular Imaging China Retrospectivecohort To investigate the role of CT-FFR in predicting proximal plaque formation associated with MB in the LAD using ML approaches Patients with MB in the LAD and no atherosclerosis on baseline CCTA who underwent follow-up CCTA with a minimum interval of 3 months 188 55 ± 6 68.6 ML-based CT-FFR (cFFR v3.0.0, Siemens Healthineers); ML-based prediction model using LASSO algorithms Computation of CT-FFR; ML models for prediction of plaque formation CT-FFR distal to LAD MB and ∆CT-FFR significantly differed between patients with CT MB LAD who developed plaque and those who did not. .. ML algorithms further identified CT-FFR and ∆CT-FFR as the strongest predictors of plaque formation proximal to MB LAD Zhou 2019 [38] Canadian Journal of Cardiology China Retrospectivecohort To study the diagnostic performance of ML-based CT-FFR to detect functional ischemia in MB with iFFR as the reference standard Patients who underwent CCTA for the evaluation of suspected or known CAD and were found to have LAD MB who then underwent ICA within 60 days of CCTA 104 61.2 ± 9.1 72.1 ML-based CT-FFR (cFFR v3.2.0, Siemens Healthineers) Automatic generation of centerline and luminal contours of coronary arteries; computation of CT-FFR CT-FFR has high diagnostic performance for functional ischemia in vessels with MB and concomitant proximal atherosclerotic disease compared with iFFR, regardless of length and depth of MB, with a low PPV for lesions of <70% stenosis Table 2. ..

Functional Assay:

Article Title: Cardiac Computed Tomography for the Assessment of Myocardial Bridging: A Scoping Review of the Emerging Role of Artificial Intelligence and Machine Learning.
Article Snippet: Patients with abnormal FFR were less likely to be asymptomatic and more likely to have typical anginal chest pain Zhou 2019 [57] JACC: Cardiovascular Imaging China Retrospectivecohort To investigate the role of CT-FFR in predicting proximal plaque formation associated with MB in the LAD using ML approaches Patients with MB in the LAD and no atherosclerosis on baseline CCTA who underwent follow-up CCTA with a minimum interval of 3 months 188 55 ± 6 68.6 ML-based CT-FFR (cFFR v3.0.0, Siemens Healthineers); ML-based prediction model using LASSO algorithms Computation of CT-FFR; ML models for prediction of plaque formation CT-FFR distal to LAD MB and ∆CT-FFR significantly differed between patients with CT MB LAD who developed plaque and those who did not. .. ML algorithms further identified CT-FFR and ∆CT-FFR as the strongest predictors of plaque formation proximal to MB LAD Zhou 2019 [38] Canadian Journal of Cardiology China Retrospectivecohort To study the diagnostic performance of ML-based CT-FFR to detect functional ischemia in MB with iFFR as the reference standard Patients who underwent CCTA for the evaluation of suspected or known CAD and were found to have LAD MB who then underwent ICA within 60 days of CCTA 104 61.2 ± 9.1 72.1 ML-based CT-FFR (cFFR v3.2.0, Siemens Healthineers) Automatic generation of centerline and luminal contours of coronary arteries; computation of CT-FFR CT-FFR has high diagnostic performance for functional ischemia in vessels with MB and concomitant proximal atherosclerotic disease compared with iFFR, regardless of length and depth of MB, with a low PPV for lesions of <70% stenosis Table 2. ..

other:

Article Title: CT-FFR: How a new technology could transform cardiovascular diagnostic imaging.
Article Snippet: ▶ Fig.6 Possible benefit of CT-FFR prior to TAVI: On cCTA of an 80-year-old patient prior to TAVI procedure, severe stenosis in the intermediate region of the LADand the LCX was suspected (a), with a value of 0.91 being calculated for both proximal stenoses in the CT-FFR (b, Siemens Healthineers, cFFR, version 3.5).

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