Validation of a Computed Tomography (CT) Based Fractional Flow Reserve (FFR) Software Using the 320 Detector Aquilion ONE CT Scanner.

NCT03149042 | Completed Results FDA Device

• 1 other identifier: 01
• Study Type: observational
• Target: 75
• Locations: 1 country
• Sites: 1

Brief Summary

Coronary Computed Tomography Angiography (CCTA) contrast opacification gradients and FFR-CT estimation can aid in the severity estimation of significant atherosclerotic lesions. Currently, FFR-CT algorithms can only be optimized using theoretical models and can only be validated in large multi-center clinical trials. Using patient specific 3D printed coronary phantoms would allow optimization of FFR-CT algorithms with a measured validation technique without the need for large clinical trials. Thus the investigators believe that this study will result in a FFR-CT algorithm/method with a better predictability for arterial lesion severity than those existing on the market today. Flow measurements will be compared with: CT-FFR for both patients and phantoms, angio lab FFR measurements and 30 days follow-up. This pilot clinical study includes \~50 patients over a year and half at GVI.

Conditions

Atherosclerosis, Coronary

Keywords

FFR; Fractional Flow Reserve; Atherosclerosis; Coronary; stenosis

Outcome Measures

Primary Outcomes (4)

• Comparison of CT Based FFR With Invasive FFR, ROC Analysis

  Patient CCTA images were imported into Vitrea segmentation software (Vital Images, Minnetonka, MN) for use in the research-based CT based FFR algorithm. The software analyzes four data volumes acquired a 70%, 80%, 90% and 99% of the R-R interval and computes the FFR based on the changes in vessel diameter and computational fluid dynamics. Within the algorithm, the aortic root and three main coronary arteries (LAD, LCX, and RCA) were automatically segmented, and then manually adjusted to obtain accurate centerline and contours. The CT based FFR was calculated and the user adjusted the location of the distal pressure measurement to calculate the CT basedFFR at the same location as Invasive-FFR, two lesion lengths below the distal end of the lesion. Area under the Receiver Operator Characteristic were measured where an Invasive FFR\<=0.8 was considered positive.

  24 hours

• Comparison of CT Based FFR With Invasive FFR, Correlation Analysis

  Patient CCTA images were imported into Vitrea segmentation software (Vital Images, Minnetonka, MN) for use in the research-based CT based FFR algorithm. The software analyzes four data volumes acquired a 70%, 80%, 90% and 99% of the R-R interval and computes the FFR based on the changes in vessel diameter and computational fluid dynamics. Within the algorithm, the aortic root and three main coronary arteries (LAD, LCX, and RCA) were automatically segmented, and then manually adjusted to obtain accurate centerline and contours. The CT based FFR was calculated and the user adjusted the location of the distal pressure measurement to calculate the CT basedFFR at the same location as Invasive-FFR, two lesion lengths below the distal end of the lesion. Pearson Correlation between Invasive FFR and CT based FFR was measured

  24 hours

• Comparison of CT Based FFR With Invasive FFR, Sensitivity

  Patient CCTA images were imported into Vitrea segmentation software (Vital Images, Minnetonka, MN) for use in the research-based CT based FFR algorithm. The software analyzes four data volumes acquired a 70%, 80%, 90% and 99% of the R-R interval and computes the FFR based on the changes in vessel diameter and computational fluid dynamics. Within the algorithm, the aortic root and three main coronary arteries (LAD, LCX, and RCA) were automatically segmented, and then manually adjusted to obtain accurate centerline and contours. The CT based FFR was calculated and the user adjusted the location of the distal pressure measurement to calculate the CT basedFFR at the same location as Invasive-FFR, two lesion lengths below the distal end of the lesion. Sensitivity were measured where an Invasive FFR\<=0.8 was considered positive. Sensitivity reflects the percentage of true positive cases identified by CT-FFR compared to I-FFR

  24 hours

• Comparison of CT Based FFR With Invasive FFR, Specificity

  Patient CCTA images were imported into Vitrea segmentation software (Vital Images, Minnetonka, MN) for use in the research-based CT based FFR algorithm. The software analyzes four data volumes acquired a 70%, 80%, 90% and 99% of the R-R interval and computes the FFR based on the changes in vessel diameter and computational fluid dynamics. Within the algorithm, the aortic root and three main coronary arteries (LAD, LCX, and RCA) were automatically segmented, and then manually adjusted to obtain accurate centerline and contours. The CT based FFR was calculated and the user adjusted the location of the distal pressure measurement to calculate the CT basedFFR at the same location as Invasive-FFR, two lesion lengths below the distal end of the lesion. Specificity was measured, where an Invasive FFR\<=0.8 was considered positive. Specificity reflects the percentage of true negative cases identified by CT-FFR compared to I-FFR

  24 hours

Secondary Outcomes (5)

• Comparison of CT Based FFR With Bench-top FFR Using 3D Printed Patient Specific Phantoms

  4 weeks from baseline

• Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, ROC Analysis

  4 weeks from baseline

• Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, Pearson Correlation

  4 weeks from baseline

• Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, Sensitivity

  4 weeks from baseline

• Comparison of Bench-top FFR Using 3D Printed Patient Specific Phantoms With Invasive FFR, Specificity

  4 weeks from baseline

Study Arms (1)

CCTA

Patients who are scheduled for clinically mandated elective invasive coronary angiography (ICA) at Buffalo General Hospital.

Diagnostic Test: CCTA

Interventions

CCTA DIAGNOSTIC_TEST

Diagnostic Test

CCTA

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients who are (1) scheduled for clinically mandated elective invasive coronary angiography (ICA) at Buffalo General Hospital or Juntendo Hospital Japan (2) clinically mandated CTA will be screened.

You may qualify if:

• All the patients \>18 yrs of age , who are undergoing CCTA and angio-FFR. Patients who are (1) scheduled for clinically mandated elective invasive coronary angiography (ICA) at Buffalo General Hospital or (2) clinically mandated CTA will be screened.

You may not qualify if:

• Adults unable to consent
• Individuals who are not yet adults (infants, children, teenagers)
• Pregnant women
• Prisoners
• atrial fibrillation,
• Renal insufficiency (estimated glomerular filtration rate (GFR) \<60 ml/min/1.73 m2),
• Active Bronchospasm prohibiting the use of beta blockers
• Morbid obesity (body mass index 40 kg/m2)
• Contraindications to iodinated contrast.
• Emergencies requiring immediate intervention or patients unable to consent.
• Patients not showing coronary calcium during Calcium Scoring procedures

Sponsors & Collaborators

• State University of New York at Buffalo: lead

Study Sites (1)

Clinical and Translational Research Center Room 8052

Buffalo, New York, 14021, United States

Location

Related Publications (9)

• Sommer K, Izzo RL, Shepard L, Podgorsak AR, Rudin S, Siddiqui AH, Wilson MF, Angel E, Said Z, Springer M, Ionita CN. Design Optimization for Accurate Flow Simulations in 3D Printed Vascular Phantoms Derived from Computed Tomography Angiography. Proc SPIE Int Soc Opt Eng. 2017 Feb 11;10138:101380R. doi: 10.1117/12.2253711. Epub 2017 Mar 13.

  PMID: 28663663 BACKGROUND

• Ionita, C., Angel, E., Mitsouras, D., Rudin, S., Bednarek, D., Zaid, S., Wilson, M. and Rybicki, F. (2016), TU-H-CAMPUS-IeP2-03: Development of 3D Printed Coronary Phantoms for In-Vitro CT-FFR Validation Using Data from 320- Detector Row Coronary CT Angiography. Med. Phys., 43: 3781. doi:10.1118/1.4957681

  BACKGROUND

• Kelsey N. Sommer, Lauren M. Shepard, Vijay Iyer, Erin Angel, Michael F. Wilson, Frank J. Rybicki, Dimitrios Mitsouras, Kanako Kunishima Kumamaru, Stephen Rudin, and Ciprian N. Ionita. Comparison of benchtop pressure gradient measurements in 3D printed patient specific cardiac phantoms with CT-FFR and computational fluid dynamic simulations, Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 109531P (15 March 2019);

  BACKGROUND

• Shepard LM, Sommer KN, Angel E, Iyer V, Wilson MF, Rybicki FJ, Mitsouras D, Molloi S, Ionita CN. Initial evaluation of three-dimensionally printed patient-specific coronary phantoms for CT-FFR software validation. J Med Imaging (Bellingham). 2019 Apr;6(2):021603. doi: 10.1117/1.JMI.6.2.021603. Epub 2019 Mar 12.

  PMID: 30891468 BACKGROUND

• Sommer KN, Shepard L, Karkhanis NV, Iyer V, Angel E, Wilson MF, Rybicki FJ, Mitsouras D, Rudin S, Ionita CN. 3D Printed Cardiovascular Patient Specific Phantoms Used for Clinical Validation of a CT-derived FFR Diagnostic Software. Proc SPIE Int Soc Opt Eng. 2018 Feb;10578:105780J. doi: 10.1117/12.2292736. Epub 2018 Mar 12.

  PMID: 29899591 BACKGROUND

• Shepard L, Sommer K, Izzo R, Podgorsak A, Wilson M, Said Z, Rybicki FJ, Mitsouras D, Rudin S, Angel E, Ionita CN. Initial Simulated FFR Investigation Using Flow Measurements in Patient-specific 3D Printed Coronary Phantoms. Proc SPIE Int Soc Opt Eng. 2017 Feb 11;10138:101380S. doi: 10.1117/12.2253889. Epub 2017 Mar 13.

  PMID: 28649159 BACKGROUND

• Kelsey N. Sommer, Lauren M. Shepard, Vijay Iyer, Erin Angel, Michael F. Wilson, Frank J. Rybicki, Dimitrios Mitsouras, Ciprian Ionita. Study of the effect of boundary conditions on fractional flow reserve using patient specific coronary phantoms. Proceedings Volume 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging; 113171J (2020) https://doi.org/10.1117/12.2548472

  BACKGROUND

• Sommer KN, Shepard LM, Mitsouras D, Iyer V, Angel E, Wilson MF, Rybicki FJ, Kumamaru KK, Sharma UC, Reddy A, Fujimoto S, Ionita CN. Patient-specific 3D-printed coronary models based on coronary computed tomography angiography volumes to investigate flow conditions in coronary artery disease. Biomed Phys Eng Express. 2020 May 14;6(4):045007. doi: 10.1088/2057-1976/ab8f6e.

  PMID: 33444268 RESULT

• Kumamaru KK, Angel E, Sommer KN, Iyer V, Wilson MF, Agrawal N, Bhardwaj A, Kattel SB, Kondziela S, Malhotra S, Manion C, Pogorzelski K, Ramanan T, Sawant AC, Suplicki MM, Waheed S, Fujimoto S, Sharma UC, Rybicki FJ, Ionita CN. Inter- and Intraoperator Variability in Measurement of On-Site CT-derived Fractional Flow Reserve Based on Structural and Fluid Analysis: A Comprehensive Analysis. Radiol Cardiothorac Imaging. 2019 Aug 29;1(3):e180012. doi: 10.1148/ryct.2019180012. eCollection 2019 Aug.

  PMID: 33778507 RESULT

Related Links

• results

MeSH Terms

Conditions

Coronary Artery Disease; Atherosclerosis; Constriction, Pathologic

Condition Hierarchy (Ancestors)

Coronary Disease; Myocardial Ischemia; Heart Diseases; Cardiovascular Diseases; Arteriosclerosis; Arterial Occlusive Diseases; Vascular Diseases; Pathological Conditions, Anatomical; Pathological Conditions, Signs and Symptoms

Limitations and Caveats

Operators were not blinded to the invasive-FFR results at the time of calculating the CT based FFR and Bench-top measurements

Results Point of Contact

• Title: Dr. Ciprian Ionita
• Organization: University at Buffalo

cnionita@buffalo.edu

7164004283

Publication Agreements

• PI is Sponsor Employee: No
• Restrictive Agreement: No

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: May 8, 2017
• First Posted: May 11, 2017
• Study Start: May 28, 2016
• Primary Completion: December 31, 2018
• Study Completion: April 21, 2019
• Last Updated: November 17, 2020
• Results First Posted: June 23, 2020

Record last verified: 2020-11

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)