scholarly journals Feasibility and Validity of Computed Tomography-Derived Fractional Flow Reserve in Patients With Severe Aortic Stenosis

2020 ◽  
Author(s):  
Michael Michail ◽  
Abdul-Rahman Ihdayhid ◽  
Andrea Comella ◽  
Udit Thakur ◽  
James D. Cameron ◽  
...  
Keyword(s):  
Aortic Stenosis ◽  
Diagnostic Accuracy ◽  
Operating Characteristic ◽  
Severe Aortic Stenosis ◽  
Characteristic Curve ◽  
Fractional Flow ◽  
Predictive Values ◽  
Flow Reserve ◽  
Artery Disease ◽  
Sensitivity Specificity

Background: Coronary artery disease is common in patients with severe aortic stenosis. Computed tomography-derived fractional flow reserve (CT-FFR) is a clinically used modality for assessing coronary artery disease, however, its use has not been validated in patients with severe aortic stenosis. This study assesses the safety, feasibility, and validity of CT-FFR in patients with severe aortic stenosis. Methods: Prospectively recruited patients underwent standard-protocol invasive FFR and coronary CT angiography (CTA). CTA images were analyzed by central core laboratory (HeartFlow, Inc) for independent evaluation of CT-FFR. CT-FFR data were compared with FFR (ischemia defined as FFR ≤0.80). Results: Forty-two patients (68 vessels) underwent FFR and CTA; 39 patients (92.3%) and 60 vessels (88.2%) had interpretable CTA enabling CT-FFR computation. Mean age was 76.2±6.7 years (71.8% male). No patients incurred complications relating to premedication, CTA, or FFR protocol. Mean FFR and CT-FFR were 0.83±0.10 and 0.77±0.14, respectively. CT calcium score was 1373.3±1392.9 Agatston units. On per vessel analysis, there was positive correlation between FFR and CT-FFR (Pearson correlation coefficient, R =0.64, P <0.0001). Sensitivity, specificity, positive predictive value, and negative predictive values were 73.9%, 78.4%, 68.0%, and 82.9%, respectively, with 76.7% diagnostic accuracy. The area under the receiver-operating characteristic curve for CT-FFR was 0.83 (0.72–0.93, P <0.0001), which was higher than that of CTA and quantitative coronary angiography ( P =0.01 and P <0.001, respectively). Bland-Altman plot showed mean bias between FFR and CT-FFR as 0.059±0.110. On per patient analysis, the sensitivity, specificity, positive predictive, and negative predictive values were 76.5%, 77.3%, 72.2%, and 81.0% with 76.9% diagnostic accuracy. The per patient area under the receiver-operating characteristic curve analysis was 0.81 (0.67–0.95, P <0.0001). Conclusions: CT-FFR is safe and feasible in patients with severe aortic stenosis. Our data suggests that the diagnostic accuracy of CT-FFR in this cohort potentially enables its use in clinical practice and provides the foundation for future research into the use of CT-FFR for coronary evaluation pre-aortic valve replacement.

Comparison of FFR with iFR and QFR in assessment of intermediate coronary artery disease in patients with severe aortic stenosis

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
P Kleczynski ◽  
A Dziewierz ◽  
L Rzeszutko ◽  
D Dudek ◽  
J Legutko
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Aortic Stenosis ◽  
Severe Aortic Stenosis ◽  
Funding Source ◽  
Fractional Flow ◽  
Roc Curve Analysis ◽  
Flow Reserve ◽  
Coronary Lesions ◽  
Artery Disease

Abstract Background The functional assessment of coronary artery disease (CAD) in patients with severe aortic stenosis (AS) has been barely examined so far, and the best strategy to physiologically investigate the relevance of coronary stenosis in this specific setting of patients remains undetermined. The aim of the study is to compare the diagnostic performance of instantaneous wave-free ratio (iFR), quantitative flow ratio (QFR) and fractional flow reserve (FFR) in patients with severe AS. Methods The functional significance of 416 coronary lesions was investigated with iFR, FFR and QFR measurements in 221 AS patients. The iFR-FFR and QFR-FFR diagnostic agreement has been tested using the conventional 0.80 FFR cut-off. Results Mean value of FFR was 0.85±0.07; iFR – 0.90±0.04; QFR – 0.84±0.07. The correlation between iFR and FFR was good (r=0.83, p&lt;0.001) and QFR and FFR was goot too (r=0.77, p&lt;0.001), as well as the area under the curve at ROC curve analysis 0,995 (0,983 to 0,999, p&lt;0.001) for iFR and 0,988 (0,972 to 0,996, p&lt;0.001) for QFR. However, using the standard iFR 0.89 and QFR 0.8 threshold, the diagnostic accuracy of iFR was 100% sensitivity and 90.26% specificity and for QFR – 100% and 92.21%, respectively. According to ROC analysis, the best iFR cut-off in predicting FFR ≤0.8 was 0.88 (J=0.94), the best QFR cut-off value was 0.80 (J=0.92). Conclusions In the presence of severe AS, iFR and QFR had good agreement with FFR values for assessment of borderline coronary lesions. However, iFR threshold for predicting FFR below 0.8 may be different from a standard value of 0.89. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Science Centre

scholarly journals INTRAVENOUS ADENOSINE INFUSION IS SAFE AND WELL TOLERATED DURING CORONARY FRACTIONAL FLOW RESERVE ASSESSMENT IN SEVERE AORTIC STENOSIS

2015 ◽  
Vol 65 (10) ◽  
pp. A1931
Author(s):  
Dusan A. Stanojevic ◽  
Prasad Gunasekaran ◽  
Micah Levine ◽  
Mark Reichuber ◽  
Randall Genton ◽  
...  
Keyword(s):  
Aortic Stenosis ◽  
Fractional Flow Reserve ◽  
Severe Aortic Stenosis ◽  
Adenosine Infusion ◽  
Fractional Flow ◽  
Flow Reserve

scholarly journals Diagnostic Performance of Deep LearnIng AlgoriThm for Analysis of Computed Tomography Myocardial PerfusION

2021 ◽  
Author(s):  
Giuseppe Muscogiuri ◽  
Mattia Chiesa ◽  
Andrea Baggiano ◽  
Pierino Spadafora ◽  
Rossella De Santis ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Deep Learning ◽  
Diagnostic Accuracy ◽  
Learning Algorithm ◽  
Significant Coronary Artery Disease ◽  
Patient Specific ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Specific Sensitivity ◽  
Sensitivity Specificity

Abstract Purpose: Artificial intelligence could play a key role in cardiac imaging analysis. To evaluate the diagnostic accuracy of a deep learning (DL) algorithm predicting hemodynamically significant coronary artery disease (CAD) by using a rest dataset of myocardial computed tomography perfusion (CTP) as compared to invasive evaluation. Methods: One hundred and twelve consecutive symptomatic patients scheduled for clinically indicated invasive coronary angiography (ICA) underwent CCTA plus static stress CTP and ICA with invasive fractional flow reserve (FFR) for stenoses ranging between 30% and 80%. Subsequently, a DL algorithm for the prediction of significant CAD by using the rest dataset (CTP-DLrest) and stress dataset (CTP-DLstress) was developed. The diagnostic accuracy for identification of significant CAD using CCTA, CCTA+CTPStress, CCTA+CTP-DLrest, and CCTA+CTP-DLstress were measured and compared. The time of analysis for CTPStress, CTP-DLrest and CTP-DLStress were recorded. Results: Patient-specific sensitivity, specificity, NPV, PPV, accuracy and area under the curve (AUC) of CCTA alone and CCTA+CTPStress were 100%, 33%, 100%, 54%, 63%, 67% and 86%, 89%, 89%, 86%, 88%, 87%, respectively. Patient-specific sensitivity, specificity, NPV, PPV, accuracy and AUC of CCTA+DLrest and CCTA+DLstress were 100%, 72%, 100%, 74%, 84%, 96% and 93%, 83%, 94%, 81%,88%,98%, respectively. All CCTA+CTPStress, CCTA+CTP-DLRest and CCTA+CTP-DLStress significantly improved detection of hemodynamically significant CAD (p<0.01).Time of CTP-DL was significantly lower as compared to human analysis (39.2±3.2 vs. 379.6±68.0 seconds, p<0.001).Conclusion: Evaluation of myocardial ischemia using a DL approach on rest CTP datasets is feasible and accurate. This approach may be a useful gatekeeper prior to CTPStress.

scholarly journals Diagnostic accuracy of a urine dipstick for detecting albuminuria in hypertensive patients

F1000Research ◽  
2021 ◽  
Vol 9 ◽  
pp. 1244
Author(s):  
Phornwipa Panta ◽  
Win Techakehakij
Keyword(s):  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Hypertensive Patients ◽  
Spot Urine ◽  
Urine Dipstick ◽  
Urine Albumin ◽  
Low Sensitivity ◽  
Sensitivity Specificity

Background: Screening for albuminuria is generally recommended among patients with hypertension. While the urine dipstick is commonly used for screening urine albumin, there is little evidence about its diagnostic accuracy among these patients in Thailand. This study aimed to assess the diagnostic accuracy of a dipstick in Thai hypertensive patients for detecting albuminuria. Methods: This study collected the data of 3,067 hypertensive patients, with the results of urine dipstick and urine albumin-to-creatinine ratio (ACR) from random single spot urine being examined in the same day at least once, at Lampang Hospital, Thailand, during 2018. For ACR, a reference standard of ≥ 30 mg/g was applied to indicate the presence of albuminuria. Results: The sensitivity, specificity, positive predictive value (PPV), and negative predictive value of the trace result from dipsticks were 53.6%, 94.5%, 86.5%, and 75.5%, respectively. The area under the receiver operating characteristic curve of the dipstick was 0.748. Conclusion: Using the dipstick for screening albuminuria among hypertensive patients should not be recommended for mass screening due to its low sensitivity. In response to high PPV, a trace threshold of the dipstick may be used to indicate presence of albuminuria.

scholarly journals Diagnostic accuracy of a urine dipstick for detecting albuminuria in hypertensive patients

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1244
Author(s):  
Phornwipa Panta ◽  
Win Techakehakij
Keyword(s):  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Hypertensive Patients ◽  
Spot Urine ◽  
Urine Dipstick ◽  
Urine Albumin ◽  
Low Sensitivity ◽  
Sensitivity Specificity

Background: Screening for albuminuria is generally recommended among patients with hypertension. While the urine dipstick is commonly used for screening urine albumin, there is little evidence about its diagnostic accuracy among these patients. This study aimed to assess the diagnostic accuracy of a dipstick in Thai hypertensive patients for detecting albuminuria. Methods: This study collected the data of 3,067 hypertensive patients, with the results of urine dipstick and urine albumin-to-creatinine ratio (ACR) from random single spot urine being examined in the same day at least once, at Lampang Hospital, Thailand, during 2018. For ACR, a reference standard of ≥ 30 mg/g was applied to indicate the presence of albuminuria. Results: The sensitivity, specificity, positive predictive value (PPV), and negative predictive value of the trace result from dipsticks were 53.6%, 94.5%, 86.5%, and 75.5%, respectively. The area under the receiver operating characteristic curve of the dipstick was 0.748. Conclusion: Using the dipstick for screening albuminuria among hypertensive patients should not be recommended due to its low sensitivity. In response to high PPV, a trace threshold of the dipstick may be used to indicate presence of albuminuria.

scholarly journals Diagnostic performance of wireless fractional flow reserve: a meta-analysis

2021 ◽  
Author(s):  
Wen Pan ◽  
Qing-Jun Liu
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Likelihood Ratio ◽  
Fractional Flow Reserve ◽  
Diagnostic Performance ◽  
Meta Analysis ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Artery Disease ◽  
Sensitivity Specificity

IntroductionThe aim of this study was to evaluate diagnostic performance of wireless fractional flow reserve (FFR) used in patients with coronary artery disease (CAD).Material and methodsPubMed, Cochrane Library, Embase and Clinical trial.gov databases were searched by computer search and manual retrieval. The search terms included fractional flow reserve, quantitative coronary angiography, computational fluid dynamics and coronary artery disease. The meta-analysis was conducted with Stata12.0. Clinical outcomes included accuracy, sensitivity, specificity, positive likelihood ratio (+LR), negative likelihood ratio (–LR), diagnostic odds ratio (DOR) and area under the receiver operating curve.ResultsNine studies comprising 2052 vessels were included in the present meta-analysis. The sensitivity, specificity, +LR, –LR, DOC and accuracy were 87% (95% CI: 83–94%), 88% (95% CI: 82–92%), 7.28 (95% CI: 4.78–11.08), 0.14 (95% CI: 0.10–0.21), 50.69 (95% CI: 25.22–101.88) and 0.94 (95% CI: 0.91–0.96) respectively. No significant publication bias was detected.ConclusionsThis meta-analysis suggests that the clinical performance such as accuracy, sensitivity and specificity of wireless FFR is good to detect stenotic lesions with pressure-wire measured FFR as a reference.

Abstract 1634: Validation of 64-Slice Multi-Detector Computed Tomography Coronary Angiography Against Invasive Hemodynamic Measurements of Fractional Flow Reserve in the Detection of Non-Flow-Limiting Coronary Stenoses

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
Kamran Akram ◽  
Robert O’Donnell ◽  
Jennifer LaCorte ◽  
Charles Brown ◽  
Szilard Voros
Keyword(s):  
Coronary Angiography ◽  
Fractional Flow Reserve ◽  
Area Under The Curve ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Minimal Lumen Area ◽  
Coronary Stenoses ◽  
Artery Disease ◽  
Sensitivity Specificity ◽  
Hemodynamic Measurements

Introduction. Multi-detector CT coronary angiography (CorCTA) has been introduced for coronary artery disease (CAD) detection and been validated against invasive angiography (XRA) and intravascular ultrasound (IVUS). However, the diagnostic accuracy of CorCTA-derived area stenosis (%AS), diameter stenosis (%DS), minimal lumen area (MLA) and minimal lumen diameter (MLD) have not been previously validated against fractional flow reserve (FFR). Methods. Twenty consecutive patients enrolled in a study of non-obstructive CAD underwent CorCTA and invasive FFR measurements within 2 weeks. Patients without prior CAD with visual intermediate stenoses (40–70%) by either XRA or CorCTA were eligible. CorCTA was performed on a 64-slice scanner. %AS, %DS, MLA and MLD were measured quantitatively with commercial software (SurePlaque; Vital Images). FFR was determined by averaging 3 independent measurements after intracoronary injection of adenosine. Statistical analysis was done using Analyse-It software. Results. CorCTA-derived values (mean±SD) in the group were as follows: %AS=43.8±21.3%, %DS=58.9±21.4%, MLA=3.9±3.0mm 2 , MLD=1.4±0.8mm, FFR=0.89±0.09. Two patients had flow-limiting stenoses by FFR. Table shows the area under the curve (AUC), optimal cutpoint, sensitivity, specificity, PPV and NPV for the parameters to predict non-flow-limiting FFR. All parameters performed well in predicting non-flow-limiting FFR as expressed by the AUC; these were highly significant. Values below stenosis cutpoints (%AS<60%, %DS<77%) and MLA>3.0 mm 2 , MLD>0.89 mm reliably excluded flow-limiting stenoses. Cutpoints were higher for %DS vs %AS (77% vs. 60%). Conclusions. To our knowledge, this is the first study to compare CorCTA to FFR. %AS, %DS, MLA and MLD performed very well in excluding hemodynamically significant stenoses. While%DS and MLD by CorCTA tend to overestimate the significance of stenosis, %AS and MLA correlate well to similar values derived from IVUS. Accuracy of CorCTA in Excluding Flow Limiting Stenoses As Measured by FFR

Angiography-based quantitative flow ratio versus fractional flow reserve in patients with coronary artery disease and severe aortic stenosis

2020 ◽  
Vol 16 (4) ◽  
pp. e285-e292 ◽  
Author(s):  
Hernán Mejía-Rentería ◽  
Luis Nombela-Franco ◽  
Jean-Michel Paradis ◽  
Mattia Lunardi ◽  
Joo Myung Lee ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Severe Aortic Stenosis ◽  
Flow Ratio ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Artery Disease ◽  
Quantitative Flow Ratio ◽  
Ratio Versus ◽  
Quantitative Flow
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