xml: <clinical_study>
    <!-- This xml conforms to an XML Schema at:
      https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
    <required_header>
      <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
      <link_text>Link to the current ClinicalTrials.gov record.</link_text>
      <url>https://clinicaltrials.gov/ct2/show/NCT06018194</url>
    </required_header>
    <id_info>
      <org_study_id>3-ST-03-03</org_study_id>
      <nct_id>NCT06018194</nct_id>
    </id_info>
    <brief_title>ELUCIDATE FFRct Study</brief_title>
    <official_title>The ELUCIDATE FFRct Study</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Elucid Bioimaging Inc.</agency>
        <agency_class>Industry</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Lundquist Institute at Harbor-UCLA Medical Center</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>Elucid Bioimaging Inc.</source>
    <oversight_info>
      <has_dmc>No</has_dmc>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>Yes</is_fda_regulated_device>
      <is_us_export>Yes</is_us_export>
    </oversight_info>
    <brief_summary>
      <textblock>
        The goal of this study is to evaluate the diagnostic accuracy of a novel plaque-based&#xD;
        coronary CT angiography (CCTA) fractional flow reserve (FFRct) software device for the&#xD;
        estimation of invasive fractional flow reserve (FFR).&#xD;
  &#xD;
        Researchers will compare the Elucid plaque-based FFRct analysis to invasively measured FFR in&#xD;
        patients who have previously undergone CCTA and invasively assessed FFR.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        Invasive fractional flow reserve is a clinically validated measure of lesion-specific&#xD;
        ischemia and is preferred over visual estimation of diameter stenosis for clinical&#xD;
        decision-making regarding coronary revascularization in patients with stable clinical&#xD;
        presentations. Fractional flow reserve derived from coronary computed tomography angiography&#xD;
        (FFRct) using computational fluid dynamic (CFD)-based software has been shown to be a&#xD;
        reasonably accurate estimate of invasive FFR and is included in contemporary guidelines as a&#xD;
        decision-tool for management of patients with intermediate stenosis on CCTA. However,&#xD;
        CFD-based FFRct is calculated based predominately on detailed coronary lumen geometry. It is&#xD;
        understood that the burden and type of coronary atherosclerosis, in addition to lumen&#xD;
        geometry, significantly impacts the vasodilatory capacity of the coronary endothelium.&#xD;
  &#xD;
        Preliminary studies suggest that invasive FFR can be accurately estimated based on the&#xD;
        quantification of coronary plaque burden and the assessment of plaque composition.&#xD;
        Previously, the investigators have demonstrated that a novel plaque-based FFRct approach,&#xD;
        using a histologically validated software (ElucidVivoTM) for the measurement of plaque&#xD;
        morphology (volume, plaque risk characteristics, and stenosis) to train a deep-learning&#xD;
        model, was shown to be accurate and superior to lumen stenosis for predicting invasive FFR in&#xD;
        a single-site feasibility study.&#xD;
  &#xD;
        In this study, the investigators seek to assess the diagnostic accuracy of the Elucid&#xD;
        plaque-based FFRct software to estimate invasive FFR in patients at multiple centers.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Recruiting</overall_status>
    <start_date type="Anticipated">September 1, 2023</start_date>
    <completion_date type="Anticipated">January 31, 2024</completion_date>
    <primary_completion_date type="Anticipated">January 31, 2024</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Cohort</observational_model>
      <time_perspective>Retrospective</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>Sensitivity of FFRct versus invasive FFR for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-vessel</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Specificity of FFRct versus invasive FFR for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-vessel</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Sensitivity of FFRct for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-patient</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Specificity of FFRct for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-patient</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Area under the receiver-operating characteristic curve (AUC) of FFRct for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-vessel</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Area under the receiver-operating characteristic curve (AUC) of FFRct for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-patient</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Accuracy of FFRct for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-vessel</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Accuracy of FFRct for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-patient</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Negative predictive value of FFRct for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-vessel</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Negative predictive value of FFRct for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-patient</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Positive predictive value of FFRct for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-vessel</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Positive predictive value of FFRct for detecting invasive FFR ≤ 0.80</measure>
      <time_frame>1 day</time_frame>
      <description>Per-patient</description>
    </secondary_outcome>
    <number_of_groups>2</number_of_groups>
    <enrollment type="Anticipated">350</enrollment>
    <condition>Coronary Artery Disease</condition>
    <arm_group>
      <arm_group_label>Low FFR</arm_group_label>
      <description>Invasive FFR &lt;= 0.80</description>
    </arm_group>
    <arm_group>
      <arm_group_label>High FFR</arm_group_label>
      <description>Invasive FFR &gt; 0.80</description>
    </arm_group>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>ElucidVivo</intervention_name>
      <description>Plaque morphology characterization on coronary CTA for predicting fractional flow reserve (FFRct)</description>
      <arm_group_label>High FFR</arm_group_label>
      <arm_group_label>Low FFR</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          Adults &gt;=18 years with at least one 30-90% stenosis on CCTA (&gt;64- detector row) performed&#xD;
          within 60 days of undergoing invasive FFR.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
          - Adults &gt;=18 years with at least one 30-90% stenosis on CCTA (&gt;64- detector row) performed&#xD;
          within 60 days of undergoing invasive FFR.&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  History of coronary revascularization with coronary artery bypass graft (CABG) surgery&#xD;
               and/or percutaneous coronary intervention (PCI) (stent or balloon angioplasty) prior&#xD;
               to CCTA and invasive FFR.&#xD;
  &#xD;
            -  History of myocardial infarction prior to CCTA and invasive FFR.&#xD;
  &#xD;
            -  Known complex congenital heart disease.&#xD;
  &#xD;
            -  Existing pacemaker or internal defibrillator lead implantation(s).&#xD;
  &#xD;
            -  Existing prosthetic heart valve.&#xD;
  &#xD;
            -  Absence of CCTA Digital Imaging and Communications in Medicine (DICOM) data for&#xD;
               analysis.&#xD;
  &#xD;
            -  Absence of invasive coronary angiography imaging or adequate description defining the&#xD;
               position of the invasive FFR wire location.&#xD;
  &#xD;
            -  Poor CCTA image quality that does not meet Elucid image processing requirements for&#xD;
               plaque and FFRct.&#xD;
  &#xD;
            -  Absence of study date for CCTA or invasive FFR.&#xD;
  &#xD;
            -  Interval clinical myocardial infarction, diagnosis of decompensated heart failure,&#xD;
               stroke, or coronary revascularization procedure between CCTA and invasive FFR.&#xD;
  &#xD;
            -  Non-diagnostic CCTA or invasive FFR. Studies where the results of the study were&#xD;
               deemed non-diagnostic for clinical decision-making will be excluded.&#xD;
  &#xD;
            -  CCTA or invasive FFR studies performed prior to 1 January 2016.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Ziad Ali, MD</last_name>
      <role>Principal Investigator</role>
      <affiliation>Catholic Health - St. Francis Hospital</affiliation>
    </overall_official>
    <overall_official>
      <last_name>Todd C Villines, MD</last_name>
      <role>Principal Investigator</role>
      <affiliation>Elucid Bioimaging Inc.</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Todd C Villines, MD</last_name>
      <phone>978-468-0508</phone>
      <email>todd.villines@elucid.com</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>John Aluru, MBBS</last_name>
      <phone>978-468-0508</phone>
      <email>john.aluru@elucid.com</email>
    </overall_contact_backup>
    <location>
      <facility>
        <name>Cardiovascular Medical Group of Southern California</name>
        <address>
          <city>Beverly Hills</city>
          <state>California</state>
          <zip>90210</zip>
          <country>United States</country>
        </address>
      </facility>
      <status>Not yet recruiting</status>
      <contact>
        <last_name>Ronald P Karlsberg, MD</last_name>
      </contact>
    </location>
    <location>
      <facility>
        <name>Piedmont Healthcare</name>
        <address>
          <city>Atlanta</city>
          <state>Georgia</state>
          <zip>30309</zip>
          <country>United States</country>
        </address>
      </facility>
      <status>Not yet recruiting</status>
      <contact>
        <last_name>Venkateshwar Polsani, MD</last_name>
      </contact>
    </location>
    <location>
      <facility>
        <name>Parkview Health</name>
        <address>
          <city>Fort Wayne</city>
          <state>Indiana</state>
          <zip>46845</zip>
          <country>United States</country>
        </address>
      </facility>
      <status>Not yet recruiting</status>
      <contact>
        <last_name>Dustin Thomas, MD</last_name>
      </contact>
    </location>
    <location>
      <facility>
        <name>Midwest Heart and Vascular Specialists</name>
        <address>
          <city>Overland Park</city>
          <state>Kansas</state>
          <zip>66211</zip>
          <country>United States</country>
        </address>
      </facility>
      <status>Recruiting</status>
      <contact>
        <last_name>Stephen A Bloom, MD</last_name>
      </contact>
    </location>
    <location>
      <facility>
        <name>Valley Health System</name>
        <address>
          <city>Ridgewood</city>
          <state>New Jersey</state>
          <zip>07450</zip>
          <country>United States</country>
        </address>
      </facility>
      <status>Not yet recruiting</status>
      <contact>
        <last_name>Himanshu Gupta, MD</last_name>
      </contact>
    </location>
    <location>
      <facility>
        <name>Cleveland Clinic</name>
        <address>
          <city>Cleveland</city>
          <state>Ohio</state>
          <zip>44195</zip>
          <country>United States</country>
        </address>
      </facility>
      <status>Not yet recruiting</status>
      <contact>
        <last_name>Milind Desai, MD, MBA</last_name>
      </contact>
    </location>
    <location>
      <facility>
        <name>Centennial Heart</name>
        <address>
          <city>Nashville</city>
          <state>Tennessee</state>
          <zip>37203</zip>
          <country>United States</country>
        </address>
      </facility>
      <status>Not yet recruiting</status>
      <contact>
        <last_name>David Huneycutt, MD</last_name>
      </contact>
    </location>
    <location>
      <facility>
        <name>Ascension Medical Group</name>
        <address>
          <city>Nashville</city>
          <state>Tennessee</state>
          <zip>37205</zip>
          <country>United States</country>
        </address>
      </facility>
      <status>Not yet recruiting</status>
      <contact>
        <last_name>Andrew O Zurich, MD</last_name>
      </contact>
    </location>
    <location>
      <facility>
        <name>University of Virginia</name>
        <address>
          <city>Charlottesville</city>
          <state>Virginia</state>
          <zip>22908</zip>
          <country>United States</country>
        </address>
      </facility>
      <status>Recruiting</status>
      <contact>
        <last_name>Patricia Rodriguez-Lozano, MD</last_name>
      </contact>
    </location>
    <location_countries>
      <country>United States</country>
    </location_countries>
    <reference>
      <citation>Lawton JS, Tamis-Holland JE, Bangalore S, Bates ER, Beckie TM, Bischoff JM, Bittl JA, Cohen MG, DiMaio JM, Don CW, Fremes SE, Gaudino MF, Goldberger ZD, Grant MC, Jaswal JB, Kurlansky PA, Mehran R, Metkus TS Jr, Nnacheta LC, Rao SV, Sellke FW, Sharma G, Yong CM, Zwischenberger BA. 2021 ACC/AHA/SCAI Guideline for Coronary Artery Revascularization: Executive Summary: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022 Jan 18;145(3):e4-e17. doi: 10.1161/CIR.0000000000001039. Epub 2021 Dec 9. Erratum In: Circulation. 2022 Mar 15;145(11):e771.</citation>
      <PMID>34882436</PMID>
    </reference>
    <reference>
      <citation>Gulati M, Levy PD, Mukherjee D, Amsterdam E, Bhatt DL, Birtcher KK, Blankstein R, Boyd J, Bullock-Palmer RP, Conejo T, Diercks DB, Gentile F, Greenwood JP, Hess EP, Hollenberg SM, Jaber WA, Jneid H, Joglar JA, Morrow DA, O'Connor RE, Ross MA, Shaw LJ. 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2021 Nov 30;144(22):e368-e454. doi: 10.1161/CIR.0000000000001029. Epub 2021 Oct 28. Erratum In: Circulation. 2021 Nov 30;144(22):e455.</citation>
      <PMID>34709879</PMID>
    </reference>
    <reference>
      <citation>Tesche C, De Cecco CN, Caruso D, Baumann S, Renker M, Mangold S, Dyer KT, Varga-Szemes A, Baquet M, Jochheim D, Ebersberger U, Bayer RR 2nd, Hoffmann E, Steinberg DH, Schoepf UJ. Coronary CT angiography derived morphological and functional quantitative plaque markers correlated with invasive fractional flow reserve for detecting hemodynamically significant stenosis. J Cardiovasc Comput Tomogr. 2016 May-Jun;10(3):199-206. doi: 10.1016/j.jcct.2016.03.002. Epub 2016 Mar 10.</citation>
      <PMID>26993434</PMID>
    </reference>
    <reference>
      <citation>Ahmadi A, Stone GW, Leipsic J, Serruys PW, Shaw L, Hecht H, Wong G, Norgaard BL, O'Gara PT, Chandrashekhar Y, Narula J. Association of Coronary Stenosis and Plaque Morphology With Fractional Flow Reserve and Outcomes. JAMA Cardiol. 2016 Jun 1;1(3):350-7. doi: 10.1001/jamacardio.2016.0263.</citation>
      <PMID>27438119</PMID>
    </reference>
    <reference>
      <citation>Diaz-Zamudio M, Dey D, Schuhbaeck A, Nakazato R, Gransar H, Slomka PJ, Narula J, Berman DS, Achenbach S, Min JK, Doh JH, Koo BK. Automated Quantitative Plaque Burden from Coronary CT Angiography Noninvasively Predicts Hemodynamic Significance by using Fractional Flow Reserve in Intermediate Coronary Lesions. Radiology. 2015 Aug;276(2):408-15. doi: 10.1148/radiol.2015141648. Epub 2015 Apr 17.</citation>
      <PMID>25897475</PMID>
    </reference>
    <reference>
      <citation>Varga-Szemes A, Schoepf UJ, Maurovich-Horvat P, Wang R, Xu L, Dargis DM, Emrich T, Buckler AJ. Coronary plaque assessment of Vasodilative capacity by CT angiography effectively estimates fractional flow reserve. Int J Cardiol. 2021 May 15;331:307-315. doi: 10.1016/j.ijcard.2021.01.040. Epub 2021 Jan 30.</citation>
      <PMID>33529657</PMID>
    </reference>
    <reference>
      <citation>Stuijfzand WJ, van Rosendael AR, Lin FY, Chang HJ, van den Hoogen IJ, Gianni U, Choi JH, Doh JH, Her AY, Koo BK, Nam CW, Park HB, Shin SH, Cole J, Gimelli A, Khan MA, Lu B, Gao Y, Nabi F, Nakazato R, Schoepf UJ, Driessen RS, Bom MJ, Thompson R, Jang JJ, Ridner M, Rowan C, Avelar E, Genereux P, Knaapen P, de Waard GA, Pontone G, Andreini D, Al-Mallah MH, Lu Y, Berman DS, Narula J, Min JK, Bax JJ, Shaw LJ; CREDENCE Investigators. Stress Myocardial Perfusion Imaging vs Coronary Computed Tomographic Angiography for Diagnosis of Invasive Vessel-Specific Coronary Physiology: Predictive Modeling Results From the Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia (CREDENCE) Trial. JAMA Cardiol. 2020 Dec 1;5(12):1338-1348. doi: 10.1001/jamacardio.2020.3409.</citation>
      <PMID>32822476</PMID>
    </reference>
    <reference>
      <citation>Lin A, van Diemen PA, Motwani M, McElhinney P, Otaki Y, Han D, Kwan A, Tzolos E, Klein E, Kuronuma K, Grodecki K, Shou B, Rios R, Manral N, Cadet S, Danad I, Driessen RS, Berman DS, Norgaard BL, Slomka PJ, Knaapen P, Dey D. Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood Flow. Circ Cardiovasc Imaging. 2022 Oct;15(10):e014369. doi: 10.1161/CIRCIMAGING.122.014369. Epub 2022 Oct 13.</citation>
      <PMID>36252116</PMID>
    </reference>
    <reference>
      <citation>Buckler AJ, Sakamoto A, Pierre SS, Virmani R, Budoff MJ. Virtual pathology: Reaching higher standards for noninvasive CTA tissue characterization capability by using histology as a truth standard. Eur J Radiol. 2023 Feb;159:110686. doi: 10.1016/j.ejrad.2022.110686. Epub 2022 Dec 31.</citation>
      <PMID>36603478</PMID>
    </reference>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>August 23, 2023</study_first_submitted>
    <study_first_submitted_qc>August 28, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 30, 2023</study_first_posted>
    <last_update_submitted>August 28, 2023</last_update_submitted>
    <last_update_submitted_qc>August 28, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 30, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>coronary computed tomographic angiography</keyword>
    <keyword>coronary CTA</keyword>
    <keyword>cardiac CT</keyword>
    <keyword>fractional flow reserve</keyword>
    <keyword>plaque</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Coronary Artery Disease</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: download date: ClinicalTrials.gov processed this data on September 20, 2023
  link text: Link to the current ClinicalTrials.gov record.
  url: https://clinicaltrials.gov/ct2/show/NCT06018194
  org study id: 3-ST-03-03
  nct id: NCT06018194
  lead sponsor: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: Yes
  is us export: Yes
  The goal of this study is to evaluate the diagnostic accuracy of a novel plaque-based
        coronary CT angiography (CCTA) fractional flow reserve (FFRct) software device for the
        estimation of invasive fractional flow reserve (FFR).
  
        Researchers will compare the Elucid plaque-based FFRct analysis to invasively measured FFR in
        patients who have previously undergone CCTA and invasively assessed FFR.
  Invasive fractional flow reserve is a clinically validated measure of lesion-specific
        ischemia and is preferred over visual estimation of diameter stenosis for clinical
        decision-making regarding coronary revascularization in patients with stable clinical
        presentations. Fractional flow reserve derived from coronary computed tomography angiography
        (FFRct) using computational fluid dynamic (CFD)-based software has been shown to be a
        reasonably accurate estimate of invasive FFR and is included in contemporary guidelines as a
        decision-tool for management of patients with intermediate stenosis on CCTA. However,
        CFD-based FFRct is calculated based predominately on detailed coronary lumen geometry. It is
        understood that the burden and type of coronary atherosclerosis, in addition to lumen
        geometry, significantly impacts the vasodilatory capacity of the coronary endothelium.
  
        Preliminary studies suggest that invasive FFR can be accurately estimated based on the
        quantification of coronary plaque burden and the assessment of plaque composition.
        Previously, the investigators have demonstrated that a novel plaque-based FFRct approach,
        using a histologically validated software (ElucidVivoTM) for the measurement of plaque
        morphology (volume, plaque risk characteristics, and stenosis) to train a deep-learning
        model, was shown to be accurate and superior to lumen stenosis for predicting invasive FFR in
        a single-site feasibility study.
  
        In this study, the investigators seek to assess the diagnostic accuracy of the Elucid
        plaque-based FFRct software to estimate invasive FFR in patients at multiple centers.
  observational model: Cohort
  time perspective: Retrospective
  measure: Sensitivity of FFRct versus invasive FFR for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-vessel
  measure: Specificity of FFRct versus invasive FFR for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-vessel
  measure: Sensitivity of FFRct for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-patient
  measure: Specificity of FFRct for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-patient
  measure: Area under the receiver-operating characteristic curve (AUC) of FFRct for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-vessel
  measure: Area under the receiver-operating characteristic curve (AUC) of FFRct for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-patient
  measure: Accuracy of FFRct for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-vessel
  measure: Accuracy of FFRct for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-patient
  measure: Negative predictive value of FFRct for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-vessel
  measure: Negative predictive value of FFRct for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-patient
  measure: Positive predictive value of FFRct for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-vessel
  measure: Positive predictive value of FFRct for detecting invasive FFR ≤ 0.80
  time frame: 1 day
  description: Per-patient
  arm group label: Low FFR
  description: Invasive FFR <= 0.80
  arm group label: High FFR
  description: Invasive FFR > 0.80
  intervention type: Device
  intervention name: ElucidVivo
  description: Plaque morphology characterization on coronary CTA for predicting fractional flow reserve (FFRct)
  arm group label: High FFR
  arm group label: Low FFR
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: No
  last name: Ziad Ali, MD
  role: Principal Investigator
  affiliation: Catholic Health - St. Francis Hospital
  last name: Todd C Villines, MD
  role: Principal Investigator
  affiliation: Elucid Bioimaging Inc.
  last name: Todd C Villines, MD
  phone: 978-468-0508
  email: todd.villines@elucid.com
  last name: John Aluru, MBBS
  phone: 978-468-0508
  email: john.aluru@elucid.com
  facility: 
  status: Not yet recruiting
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  status: Not yet recruiting
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  status: Not yet recruiting
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  status: Recruiting
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  status: Not yet recruiting
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  status: Not yet recruiting
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  status: Not yet recruiting
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  status: Not yet recruiting
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  facility: 
  status: Recruiting
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  country: United States
  citation: Lawton JS, Tamis-Holland JE, Bangalore S, Bates ER, Beckie TM, Bischoff JM, Bittl JA, Cohen MG, DiMaio JM, Don CW, Fremes SE, Gaudino MF, Goldberger ZD, Grant MC, Jaswal JB, Kurlansky PA, Mehran R, Metkus TS Jr, Nnacheta LC, Rao SV, Sellke FW, Sharma G, Yong CM, Zwischenberger BA. 2021 ACC/AHA/SCAI Guideline for Coronary Artery Revascularization: Executive Summary: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022 Jan 18;145(3):e4-e17. doi: 10.1161/CIR.0000000000001039. Epub 2021 Dec 9. Erratum In: Circulation. 2022 Mar 15;145(11):e771.
  PMID: 34882436
  citation: Gulati M, Levy PD, Mukherjee D, Amsterdam E, Bhatt DL, Birtcher KK, Blankstein R, Boyd J, Bullock-Palmer RP, Conejo T, Diercks DB, Gentile F, Greenwood JP, Hess EP, Hollenberg SM, Jaber WA, Jneid H, Joglar JA, Morrow DA, O'Connor RE, Ross MA, Shaw LJ. 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2021 Nov 30;144(22):e368-e454. doi: 10.1161/CIR.0000000000001029. Epub 2021 Oct 28. Erratum In: Circulation. 2021 Nov 30;144(22):e455.
  PMID: 34709879
  citation: Tesche C, De Cecco CN, Caruso D, Baumann S, Renker M, Mangold S, Dyer KT, Varga-Szemes A, Baquet M, Jochheim D, Ebersberger U, Bayer RR 2nd, Hoffmann E, Steinberg DH, Schoepf UJ. Coronary CT angiography derived morphological and functional quantitative plaque markers correlated with invasive fractional flow reserve for detecting hemodynamically significant stenosis. J Cardiovasc Comput Tomogr. 2016 May-Jun;10(3):199-206. doi: 10.1016/j.jcct.2016.03.002. Epub 2016 Mar 10.
  PMID: 26993434
  citation: Ahmadi A, Stone GW, Leipsic J, Serruys PW, Shaw L, Hecht H, Wong G, Norgaard BL, O'Gara PT, Chandrashekhar Y, Narula J. Association of Coronary Stenosis and Plaque Morphology With Fractional Flow Reserve and Outcomes. JAMA Cardiol. 2016 Jun 1;1(3):350-7. doi: 10.1001/jamacardio.2016.0263.
  PMID: 27438119
  citation: Diaz-Zamudio M, Dey D, Schuhbaeck A, Nakazato R, Gransar H, Slomka PJ, Narula J, Berman DS, Achenbach S, Min JK, Doh JH, Koo BK. Automated Quantitative Plaque Burden from Coronary CT Angiography Noninvasively Predicts Hemodynamic Significance by using Fractional Flow Reserve in Intermediate Coronary Lesions. Radiology. 2015 Aug;276(2):408-15. doi: 10.1148/radiol.2015141648. Epub 2015 Apr 17.
  PMID: 25897475
  citation: Varga-Szemes A, Schoepf UJ, Maurovich-Horvat P, Wang R, Xu L, Dargis DM, Emrich T, Buckler AJ. Coronary plaque assessment of Vasodilative capacity by CT angiography effectively estimates fractional flow reserve. Int J Cardiol. 2021 May 15;331:307-315. doi: 10.1016/j.ijcard.2021.01.040. Epub 2021 Jan 30.
  PMID: 33529657
  citation: Stuijfzand WJ, van Rosendael AR, Lin FY, Chang HJ, van den Hoogen IJ, Gianni U, Choi JH, Doh JH, Her AY, Koo BK, Nam CW, Park HB, Shin SH, Cole J, Gimelli A, Khan MA, Lu B, Gao Y, Nabi F, Nakazato R, Schoepf UJ, Driessen RS, Bom MJ, Thompson R, Jang JJ, Ridner M, Rowan C, Avelar E, Genereux P, Knaapen P, de Waard GA, Pontone G, Andreini D, Al-Mallah MH, Lu Y, Berman DS, Narula J, Min JK, Bax JJ, Shaw LJ; CREDENCE Investigators. Stress Myocardial Perfusion Imaging vs Coronary Computed Tomographic Angiography for Diagnosis of Invasive Vessel-Specific Coronary Physiology: Predictive Modeling Results From the Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia (CREDENCE) Trial. JAMA Cardiol. 2020 Dec 1;5(12):1338-1348. doi: 10.1001/jamacardio.2020.3409.
  PMID: 32822476
  citation: Lin A, van Diemen PA, Motwani M, McElhinney P, Otaki Y, Han D, Kwan A, Tzolos E, Klein E, Kuronuma K, Grodecki K, Shou B, Rios R, Manral N, Cadet S, Danad I, Driessen RS, Berman DS, Norgaard BL, Slomka PJ, Knaapen P, Dey D. Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood Flow. Circ Cardiovasc Imaging. 2022 Oct;15(10):e014369. doi: 10.1161/CIRCIMAGING.122.014369. Epub 2022 Oct 13.
  PMID: 36252116
  citation: Buckler AJ, Sakamoto A, Pierre SS, Virmani R, Budoff MJ. Virtual pathology: Reaching higher standards for noninvasive CTA tissue characterization capability by using histology as a truth standard. Eur J Radiol. 2023 Feb;159:110686. doi: 10.1016/j.ejrad.2022.110686. Epub 2022 Dec 31.
  PMID: 36603478
  responsible party type: Sponsor
  mesh term: Coronary Artery Disease
  sharing ipd: No