Machine leArning Based CT angiograpHy derIved FFR: a Multi-ceNtEr, Registry

Coronary Artery Disease Clinical Trial

— Machine  

Official title:

Machine leArning Based CT angiograpHy derIved FFR a Multi-ceNtEr, Registry

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT02805621
• Other study ID #: Machine
• Status: Completed
• Phase: N/A
• First received: June 15, 2016
• Last updated: January 3, 2017
• Start date: April 2016
• Est. completion date: January 2017

Study information

• Verified date: January 2017
• Source: Erasmus Medical Center
• Contact: n/a
• Is FDA regulated: No
• Health authority: Netherlands: Medical Ethics Review Committee (METC)
• Study type: Observational

Clinical Trial Summary

Demonstrate in a large multicenter population the diagnostic performance of a pre-commercial on-site, local, CT angiography derived FFR algorithm in comparison to invasive FFR.

Description:

To retrospectively evaluate the diagnostic accuracy of FFRCT, in patients with known or suspected CAD. the investigators propose to do technical assessment of the software and evaluate how different parameters effect the outcome. Validate the FFTCT outcome by comparing the FFRCT values with invasive FFR values from retrospective patient data. To analyze the potential of FFRCT on decision making and prognosis.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 352
• Est. completion date: January 2017
• Est. primary completion date: January 2017
• Accepts healthy volunteers: No
• Gender: Both
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Know or suspect coronary artery disease followed within 6 months by an invasive FFR measurement.

Exclusion Criteria:

• Cardiac event between coronary CT angiography and the invasive FFR procedure, noninterpretable coronary CT angiography image quality, or incomplete coronary CT angiography coverage.

Study Design

Observational Model: Cohort, Time Perspective: Retrospective

Related Conditions & MeSH terms

• Coronary Artery Disease
• Coronary Disease
• Coronary Heart Disease
• Heart Diseases
• Myocardial Ischemia

Locations

Country	Name	City	State
Netherlands	ErasmusMC	Rotterdam	Zuid Holland

Sponsors (6)

Lead Sponsor	Collaborator
Erasmus Medical Center	Asan Medical Center, Institute of Cardiology, Warsaw, Poland, Medical University of South Carolina, Siemens Healthcare Diagnostics Inc, University Hospital, Linkoeping

Country where clinical trial is conducted

Netherlands, 

References & Publications (5)

Baumann S, Wang R, Schoepf UJ, Steinberg DH, Spearman JV, Bayer RR 2nd, Hamm CW, Renker M. Coronary CT angiography-derived fractional flow reserve correlated with invasive fractional flow reserve measurements--initial experience with a novel physician-driven algorithm. Eur Radiol. 2015 Apr;25(4):1201-7. doi: 10.1007/s00330-014-3482-5. — View Citation

Coenen A, Lubbers MM, Kurata A, Kono A, Dedic A, Chelu RG, Dijkshoorn ML, Gijsen FJ, Ouhlous M, van Geuns RJ, Nieman K. Fractional flow reserve computed from noninvasive CT angiography data: diagnostic performance of an on-site clinician-operated computational fluid dynamics algorithm. Radiology. 2015 Mar;274(3):674-83. doi: 10.1148/radiol.14140992. — View Citation

De Geer J, Sandstedt M, Björkholm A, Alfredsson J, Janzon M, Engvall J, Persson A. Software-based on-site estimation of fractional flow reserve using standard coronary CT angiography data. Acta Radiol. 2016 Oct;57(10):1186-92. doi: 10.1177/0284185115622075. — View Citation

Kruk M, Wardziak L, Demkow M, Pleban W, Pregowski J, Dzielinska Z, Witulski M, Witkowski A, Ruzyllo W, Kepka C. Workstation-Based Calculation of CTA-Based FFR for Intermediate Stenosis. JACC Cardiovasc Imaging. 2016 Jun;9(6):690-9. doi: 10.1016/j.jcmg.2015.09.019. — View Citation

Yang DH, Kim YH, Roh JH, Kang JW, Ahn JM, Kweon J, Lee JB, Choi SH, Shin ES, Park DW, Kang SJ, Lee SW, Lee CW, Park SW, Park SJ, Lim TH. Diagnostic performance of on-site CT-derived fractional flow reserve versus CT perfusion. Eur Heart J Cardiovasc Imaging. 2016 Jun 28. pii: jew094. [Epub ahead of print] — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Diagnostic accuracy of local reduced order CFD and machine learning based CT angiography derived FFR, both validated against invasive FFR. Measured at both vessel and patient level.		6 months	No
Secondary	Influence of calcium on diagnostic accuracy of CT angiography derived FFR.		6 months	No
Secondary	Confidence intervals of CT angiography derived FFR		6 months	No
Secondary	Direct vessel based comparison between CT angiography derived FFR and QCT stenosis measurements		6 months	No
Secondary	Analysis of anatomically mild stenosis (<50% lumen diameter reduction) but functionally significant (invasive FFR = 0.80)		6 months	No
Secondary	Long term clinical outcome of CT angiography derived FFR		12 months	No