A CT-based Medina classification in coronary bifurcations: does the lumen assessment provide sufficient information?

AIMS: To evaluate the distribution of atherosclerosis at bifurcations with computed tomography coronary angiography (CTCA) and propose a novel CT-Medina classification for bifurcation lesions. METHODS: In 26 patients (age 55 ± 10 years, 81% male) imaged with CTCA, 39 bifurcations were studied. The bifurcations analysis included the proximal main vessel, the distal main vessel and the side branch (SB). Plaque contours were manually traced on CTCA; the lumen, vessel and plaque area were measured, as well as plaque burden (%). The carina cross-sections were divided into four equal parts according to the expected wall shear stress (WSS) to assess circumferential plaque distribution. All the bifurcation lesions were classified using the Medina classification and a novel CT-Medina classification combining lumen narrowing and plaque burden ≥70%. RESULTS: Presence of severe plaque (plaque burden ≥70%) by CTCA was demonstrated in 12.8% (5/39) of the proximal segments, 15.4% (6/39) of the distal segments and 7.7% (3/39) of the SB segments. The thickest plaque was located more often in low WSS parts of the carina cross-sections, whereas the flow divider was rarely affected. Although in the majority of bifurcations plaque was present, based on the Medina classification 92% of the assessed bifurcations were identified as 0,0,0. Characterization of bifurcation lesions using the new CT-Medina classification provided additional information in seven cases (18%) compared to the Medina classification CONCLUSION: Atherosclerotic plaque is widely present in all bifurcation segments, even in the absence of coronary lumen stenosis. A CT-Medina classification combining lumen and plaque parameters is more informative than angiographic classification of bifurcation lesions and could potentially facilitate the decision-making on the treatment of these lesions.

Artificial intelligence-assisted evaluation of cardiac function by oncology staff in chemotherapy patients.

Aims: Left ventricular ejection fraction (LVEF) calculation by echocardiography is pivotal in evaluating cancer patients' cardiac function. Artificial intelligence (AI) can facilitate the acquisition of optimal images and automated LVEF (autoEF) calculation. We sought to evaluate the feasibility and accuracy of LVEF calculation by oncology staff using an AI-enabled handheld ultrasound device (HUD). Methods and results: We studied 115 patients referred for echocardiographic LVEF estimation. All patients were scanned by a cardiologist using standard echocardiography (SE), and biplane Simpson's LVEF was the reference standard. Hands-on training using the Kosmos HUD was provided to the oncology staff before the study. Each patient was scanned by a cardiologist, a senior oncologist, an oncology resident, and a nurse using the TRIO AI and KOSMOS EF deep learning algorithms to obtain autoEF. The correlation between autoEF and SE-ejection fraction (EF) was excellent for the cardiologist (r = 0.90), the junior oncologist (r = 0.82), and the nurse (r = 0.84), and good for the senior oncologist (r = 0.79). The Bland-Altman analysis showed a small underestimation by autoEF compared with SE-EF. Detection of impaired LVEF < 50% was feasible with a sensitivity of 95% and specificity of 94% for the cardiologist; sensitivity of 86% and specificity of 93% for the senior oncologist; sensitivity of 95% and specificity of 91% for the junior oncologist; and sensitivity of 94% and specificity of 87% for the nurse. Conclusion: Automated LVEF calculation by oncology staff was feasible using AI-enabled HUD in a selected patient population. Detection of LVEF < 50% was possible with good accuracy. These findings show the potential to expedite the clinical workflow of cancer patients and speed up a referral when necessary.

Relationship of 24-h ambulatory blood pressure variability with micro and macrovascular parameters and hypertension status.

OBJECTIVES: Increased blood pressure variability (BPV) has been associated with an increased risk of subclinical organ damage and cardiovascular events, independently of elevated average BP values. We aimed to investigate the association of BPV indices with micro- and macrovascular parameters, some of them not previously studied. METHODS: We evaluated 344 individuals (233 never-treated/newly diagnosed hypertensive and 111 normotensive individuals). BPV was assessed using average real variability (ARV) during 24-h, daytime and night-time ambulatory blood pressure monitoring, and systolic weighted standard deviation (wSD). Retinal microvascular diameter was assessed by nonmydriatic retinal photography. Arterial stiffness was assessed by pulse wave velocity (PWV) and aortic augmentation index (AIx); subendocardial variability ratio (SEVR) was used as an index of myocardial perfusion. Carotid intima-media thickness (cIMT) was measured by ultrasound. Data were analyzed using multiple regression analysis. RESULTS: After adjusting for potential confounders, PWV and cIMT were independently associated with ARV components in the total sample (P < 0.023 and P < 0.014, respectively). Within hypertensives only PWV and cIMT were independently associated with ARV components (P < 0.002 for PWV and P < 0.003 for cIMT). In contrast, within normotensives, only retinal parameters and AIx were associated with ARV components (P < 0.017 and P = 0.013, respectively). None of the univariate correlations between vascular parameters and wSD remained significant after adjustment for potential confounders. CONCLUSION: Short-term BPV as assessed by ARV is independently associated with macrovascular parameters in untreated hypertensive patients, and with microvascular parameters in normotensive individuals.

A Novel Handheld Echocardiography Device with Continuous-Wave Doppler Capability: Implications for the Evaluation of Aortic Stenosis Severity.

BACKGROUND: The aim of this study was to evaluate the ability of a novel handheld echocardiography (HHE) device with continuous-wave Doppler (CWD) capability to measure aortic valve peak jet velocity (Vmax) and facilitate aortic stenosis (AS) severity grading. METHODS: One hundred twenty-one consecutive patients with known or suspected AS were prospectively included. All patients were scanned with the HHE device and a high-end echocardiography system (the reference standard) to obtain CWD signal across the aortic valve. Aortic Vmax measurements were acquired from the apical five-chamber view using both methods and were compared to assess method agreement using the intraclass correlation coefficient, linear regression analysis, and Bland-Altman analysis. Diagnostic accuracy for the detection of at least moderate AS (Vmax ≥ 3 m/sec) was calculated. Also, the utility of HHE with CWD to reclassify patients compared with the visual estimation of AS severity was assessed. RESULTS: The acquisition of CWD signal using HHE was feasible in 118 of 121 patients (mean age, 68 ± 17 years; 57% men). There was excellent agreement between the HHE CWD and the cart-based measurements (intraclass correlation coefficient = 0.97 [95% CI: 0.83-0.99] and r = 0.98 [95% CI: 0.91-0.99], P < .001 for both). The Bland-Altman plot showed a small underestimation bias of -0.2 m/sec (P < .001), with limits of agreement ±0.44 m/sec for Vmax. Detection of at least moderate AS using HHE with CWD was feasible with sensitivity of 93% (95% CI: 83%-98%), specificity of 98% (95% CI: 91%-100%), positive predictive value of 98% (95% CI: 88%-100%), negative predictive value of 94% (95% CI: 85%-97%), and total diagnostic accuracy of 96%. Patients visually assessed as having mild AS were reclassified as having no stenosis (17%), mild AS (72%), or moderate AS (11%) with the addition of CWD imaging. CONCLUSIONS: Use of a novel HHE device with CWD spectral analysis by experienced operators can reliably detect clinically significant AS and facilitate AS grading. This technology may improve screening and diagnostic workup of AS compared with current practice.

Clinical validation of an artificial intelligence-assisted algorithm for automated quantification of left ventricular ejection fraction in real time by a novel handheld ultrasound device.

Aims: We sought to evaluate the reliability and diagnostic accuracy of a novel handheld ultrasound device (HUD) with artificial intelligence (AI) assisted algorithm to automatically calculate ejection fraction (autoEF) in a real-world patient population. Methods and results: We studied 100 consecutive patients (57 ± 15 years old, 61% male), including 38 with abnormal left ventricular (LV) function [LV ejection fraction (LVEF) < 50%]. The autoEF results acquired using the HUD were independently compared with manually traced biplane Simpson's rule measurements on cart-based systems to assess method agreement using intra-class correlation coefficient (ICC), linear regression analysis, and Bland-Altman analysis. The diagnostic accuracy for the detection of LVEF <50% was also calculated. Test-retest reliability of measured EF by the HUD was assessed by calculating the ICC and the minimal detectable change (MDC). The ICC, linear regression analysis, and Bland-Altman analysis revealed good agreement between autoEF and reference manual EF (ICC = 0.85; r = 0.87, P < 0.001; mean bias -1.42% with limits of agreement 14.5%, respectively). Detection of abnormal LV function (EF < 50%) by autoEF algorithm was feasible with sensitivity 90% (95% CI 75-97%), specificity 87% (95% CI 76-94%), PPV 81% (95% CI 66-91%), NPV 93% (95% CI 83-98%), and a total diagnostic accuracy of 88%. Test-retest reliability was excellent (ICC = 0.91, P < 0.001; r = 0.91, P < 0.001; mean difference ± SD: 0.54% ± 5.27%, P = 0.308) and MDC for LVEF measurement by autoEF was calculated at 4.38%. Conclusion: Use of a novel HUD with AI-enabled capabilities provided similar LVEF results with those derived by manual biplane Simpson's method on cart-based systems and shows clinical potential.

Transaortic flow velocity from dual-source MDCT for the diagnosis of aortic stenosis severity.

OBJECTIVES: To describe a method for the estimation of transaortic flow from multidetector computer tomography (MDCT). BACKGROUND: Cardiac MDCT may not allow instantaneous flow measurement yet the components of flow, namely, volume change over time and lumenal area are recorded. METHODS: In 36 patients, the transaortic flow velocity was determined on transthoracic echocardiography and also with cardiac MDCT as follows: On MDCT an axial orientation through the aortic root was obtained so that the nadir of all three aortic leaflets could be seen simultaneously in one axial image. Aortic valve area (AVA) was determined by planimetry and left ventricular volumes by endocardial border mapping at every 5% increment of the RR intervals. Flow velocity was then calculated as the incremental ejection volume ÷ duration of the increment ÷ AVA. RESULTS: The transthoracic echocardiography (TTE) peak velocity and MDCT peak velocity were highly correlated (r = 0.75, P < 0.01). Transaortic peak velocity was higher when measured by MDCT as compared to TTE, with respectively a median [IQ-range] of 4.5 [2.9-5.3] and 4.0 [3.0-4.6], P < 0.01. For the diagnosis of severe aortic stenosis greater concordance with TTE peak velocity was seen with MDCT peak velocity (sensitivity 100%, specificity 76%) than with MDCT AVA (sensitivity 74%, specificity 76%). CONCLUSIONS: We show for the first time that transaortic flow velocity can be estimated by dual-source MDCT and has a better sensitivity for the detection of severe aortic stenosis than AVA planimetry when compared to the gold standard of TTE peak flow velocity.

The effect of coronary bifurcation and haemodynamics in prediction of atherosclerotic plaque development: a serial computed tomographic coronary angiographic study.

AIMS: The aim of this study was to examine the effect of the daughter branches on the haemodynamics and the potential prediction of atherosclerotic plaque development as well as the best flow division model for accurate blood flow modelling. METHODS AND RESULTS: We analysed computed tomography coronary angiography retrospective data portraying 17 coronary artery bifurcations in 15 patients recruited into the PROSPECT MSCT study. Baseline and three-year follow-up imaging data were used to reconstruct coronary artery anatomy. In the baseline models blood flow simulations were performed using three flow division approaches: stress-free, Murray's law and Doriot's fit. Blood flow simulation was also performed omitting the daughter branch. The association between ESS estimated in models that incorporated the daughter branches and lumen reduction was higher than the cases where the side branch was omitted. Murray's law provides the most accurate results when comparing the different flow division models. More specifically, low ESS is a predictor of significant lumen reduction (p=0.007), plaque burden increase (p=0.0006) and necrotic core change (p=0.025). CONCLUSIONS: The ESS distribution in coronary models including the daughter branches and based on the calculations implementing Murray's law allows more accurate prediction of atherosclerotic evolution than ESS estimated in models including only the main vessel.

Prediction of atherosclerotic disease progression using LDL transport modelling: a serial computed tomographic coronary angiographic study.

AIM: To investigate the efficacy of low-density lipoprotein (LDL) transport simulation in reconstructed arteries derived from computed tomography coronary angiography (CTCA) to predict coronary segments that are prone to progress. METHODS AND RESULTS: Thirty-two patients admitted with an acute coronary event who underwent 64-slice CTCA after percutaneous coronary intervention and at 3-year follow-up were included in the analysis. The CTCA data were used to reconstruct the coronary anatomy of the untreated vessels at baseline and follow-up, and LDL transport simulation was performed in the baseline models. The computed endothelial shear stress (ESS), LDL concentration, and CTCA-derived plaque characteristics were used to identify predictors of substantial disease progression (defined as an increase in the plaque burden at follow-up higher than two standard deviations of the intra-observer variability of the expert who performed the analysis). Fifty-eight vessels were analysed. High LDL concentration [odds ratio (OR): 2.16; 95% confidence interval (CI): 1.64-2.84; P = 0.0054], plaque burden (OR: 1.40; 95% CI: 1.13-1.72; P = 0.0017), and plaque area (OR: 3.46; 95% CI: 2.20-5.44; P≤ 0.0001) were independent predictors of a substantial disease progression at follow-up. The ESS appears as a predictor of disease progression in univariate analysis but was not an independent predictor when the LDL concentration was entered into the multivariate model. The accuracy of the model that included the LDL concentration was higher than the accuracy of the model that included the ESS (65.1 vs. 62.5%). CONCLUSIONS: LDL transport modelling appears a better predictor of atherosclerotic disease progression than the ESS, and combined with the atheroma characteristics provided by CTCA is able to detect with a moderate accuracy segments that will exhibit a significant plaque burden increase at mid-term follow-up.

Quantitative computed tomographic coronary angiography: does it predict functionally significant coronary stenoses?

BACKGROUND: Coronary lesions with a diameter narrowing ≥50% on visual computed tomographic coronary angiography (CTCA) are generally considered for referral to invasive coronary angiography. However, similar to invasive coronary angiography, visual CTCA is often inaccurate in detecting functionally significant coronary lesions. We sought to compare the diagnostic performance of quantitative CTCA with visual CTCA for the detection of functionally significant coronary lesions using fractional flow reserve (FFR) as the reference standard. METHODS AND RESULTS: CTCA and FFR measurements were obtained in 99 symptomatic patients. In total, 144 coronary lesions detected on CTCA were visually graded for stenosis severity. Quantitative CTCA measurements included lesion length, minimal area diameter, % area stenosis, minimal lumen diameter, % diameter stenosis, and plaque burden [(vessel area-lumen area)/vessel area×100]. Optimal cutoff values of CTCA-derived parameters were determined, and their diagnostic accuracy for the detection of flow-limiting coronary lesions (FFR≤0.80) was compared with visual CTCA. FFR was ≤0.80 in 54 of 144 (38%) coronary lesions. Optimal cutoff values to predict flow-limiting coronary lesion were 10 mm for lesion length, 1.8 mm2 for minimal area diameter, 73% for % area stenosis, 1.5 mm for minimal lumen diameter, 48% for % diameter stenosis, and 76% for plaque burden. No significant difference in sensitivity was found between visual CTCA and quantitative CTCA parameters (P>0.05). The specificity of visual CTCA (42%; 95% confidence interval [CI], 31%-54%) was lower than that of minimal area diameter (68%; 95% CI, 57%-77%; P=0.001), % area stenosis (76%; 95% CI, 65%-84%; P<0.001), minimal lumen diameter (67%; 95% CI, 55%-76%; P=0.001), % diameter stenosis (72%; 95% CI, 62%-80%; P<0.001), and plaque burden (63%; 95% CI, 52%-73%; P=0.004). The specificity of lesion length was comparable with that of visual CTCA. CONCLUSIONS: Quantitative CTCA improves the prediction of functionally significant coronary lesions compared with visual CTCA assessment but remains insufficient. Functional assessment is still required in lesions of moderate stenosis to accurately detect impaired FFR.

Reproducibility of computed tomography angiography data analysis using semiautomated plaque quantification software: implications for the design of longitudinal studies.

Reproducibility of the quantitative assessment of atherosclerosis by computed tomography coronary angiography (CTCA) is paramount for the design of longitudinal studies. The purpose of this study was to assess the inter- and intra-observer reproducibility using semiautomated CT plaque analysis software in symptomatic individuals. CTCA was performed in 10 symptomatic patients after percutaneous treatment of the culprit lesions and was repeated after 3 years. The plaque quantitative analysis was performed in untreated vessels with mild-to-moderate atherosclerosis and included geometrical and compositional characteristics using semiautomated CT plaque analysis software. A total of 945 matched cross-sections from 21 segments were analyzed independently by a second reviewer to assess inter-observer variability; the first observer repeated all the analyses after 3 months to assess intra-observer variability. The observer variability was also compared to the absolute plaque changes detected over time. Agreement was evaluated by Bland-Altman analysis and concordance correlation coefficient. Inter-observer relative differences for lumen, vessel, plaque area and plaque burden were 1.2, 0.6, 2.2, 1.6% respectively. Intra-observer relative differences for lumen, vessel, plaque area and plaque burden were 1.0, 0.4, 0.2, 0.4% respectively. For the average plaque attenuation values the inter- and intra-observer variability was 5 and 2% respectively. For the % low-attenuation-plaque the inter- and intra-observer variability was 16 and 6% respectively. The absolute intra-observer variability for the plaque burden was 1.30 ± 1.09%, while the temporal plaque burden difference was 3.55 ± 3.02 % (p = 0.001). The present study shows that the geometrical assessment of coronary atherosclerosis by CTCA is highly reproducible within and between observers using semiautomated quantification software and that serial plaque changes can be detected beyond observer variability. The compositional measurements are more variable between observers than geometrical measurements.

Patients with hypertrophic cardiomyopathy at risk for paroxysmal atrial fibrillation: advanced echocardiographic evaluation of the left atrium combined with non-invasive P-wave analysis.

AIMS: The maintenance of sinus rhythm is crucial for the functional capacity of patients with hypertrophic cardiomyopathy (HCM). Using a multimodality approach, we attempted to identify potential predictors of paroxysmal atrial fibrillation (PAF) in HCM patients. METHODS AND RESULTS: Thirty HCM patients (17 males, mean age 57.9 ± 13.6) with at least one documented PAF episode and 32 age- and sex-matched HCM control patients as well as 25 healthy volunteers were studied in sinus rhythm. Study subjects underwent 2D echocardiography including a colour Doppler myocardial imaging evaluation of the left atrium (LA). Additionally, an orthogonal electrocardiogram was acquired; P-wave duration, maximum, and mean energies were calculated for each subject at each orthogonal lead and the composite vector axis using the Morlet wavelet analysis. Compared with HCM controls, in HCM-PAF patients, LA antero-posterior diameter was significantly enlarged (LADAP: 46.1 ± 5.9 vs. 40.0 ± 4.7 mm, P < 0.001), peak strain rate of the LA lateral wall in the reservoir phase was significantly decreased (LAT peak SR-S: 1.93 ± 0.51 vs. 2.55 ± 0.83 s(-1), P < 0.01), and P-wave duration in the Z-lead was significantly prolonged (P-durZ: 106.9 ± 24.6 vs. 86.2 ± 14.3 ms, P < 0.001). Cut-off values and areas under the curve (AUCs) for individual parameters were 42.0 mm, 2.32 s(-1), and 98.8 ms and 0.81, 0.74, and 0.78, respectively. A multivariable model combining LADAP, LAT peak SR-S and P-durZ had an AUC of 0.90, a sensitivity of 0.87, and a specificity of 0.91 for identifying PAF patients. CONCLUSION: P-wave duration combined with LA antero-posterior diameter and myocardial deformation indices resulted in a higher power for discriminating HCM-PAF patients, when compared with individual parameters derived from either wavelet analysis or 2D echocardiography.

Assessment of atherosclerotic plaques at coronary bifurcations with multidetector computed tomography angiography and intravascular ultrasound-virtual histology.

AIMS: We evaluated the distribution and composition of atherosclerotic plaques at bifurcations with intravascular ultrasound-virtual histology (IVUS-VH) and multidetector computed tomography (MDCT) in relation to the bifurcation angle (BA). METHODS AND RESULTS: In 33 patients (age 63±11 years, 79% male) imaged with IVUS-VH and MDCT, 33 bifurcations were matched and studied. The analysed main vessel was divided into a 5 mm proximal segment, the in-bifurcation segment, and a 5 mm distal segment. Plaque contours were manually traced on MDCT and IVUS-VH. Plaques with >10% confluent necrotic core and <10% dense calcium on IVUS-VH were considered high risk, whereas plaque composition by MDCT was graded as non-calcified, calcified, or mixed. The maximum BA between the main vessel and the side branch was measured on diastolic MDCT data sets. Overall the mean plaque area decreased from the proximal to the distal segment [8.5±2.8 vs. 6.0±3.0 mm2 (P<0.001) by IVUS-VH and 9.0±2.6 vs. 6.5±2.5 mm2 (P<0.001) by MDCT]. Similarly, the necrotic core area was higher in the proximal compared with the distal segment (1.12±0.7 vs. 0.71±0.7 mm2, P=0.001). The proximal segment had the higher percentage of high-risk plaques (13/25, 52%), followed by the in-bifurcation (6/25, 24%), and the distal segment (6/25, 24%); these plaques were characterized by MDCT as non-calcified (72%) or mixed (28%). The presence of high-risk and non-calcified plaques in the proximal segment was associated with higher BA values (71±19° vs. 55±19°, P=0.028 and 74±20° vs. 50±14°, P=0.001, respectively). CONCLUSION: The proximal segment of bifurcations is more likely to contain high-risk plaques, especially when the branching angle is wide.

Natural history of coronary atherosclerosis by multislice computed tomography.

OBJECTIVES: This study sought to analyze the natural history of coronary atherosclerosis by multislice computed tomography (MSCT) and assess the serial changes in coronary plaque burden, lumen dimensions, and arterial remodeling. BACKGROUND: MSCT can comprehensively assess coronary atherosclerosis by combining lumen and plaque size parameters. METHODS: Thirty-two patients with acute coronary syndromes underwent 64-slice computed tomography angiography after percutaneous coronary intervention at baseline and after a median of 39 months. All patients received contemporary medical treatment. All available coronary segments in every subject were analyzed. The progression of atherosclerosis per segment and per patient was assessed by means of change in percent atheroma volume (PAV), change in normalized total atheroma volume (TAVnorm), and percent change in TAV (% change in TAV). Serial coronary remodeling was also assessed. Measures of lumen stenosis included percent diameter stenosis (%DS), minimum lumen diameter (MLD), percent area stenosis (%AS), and minimum lumen area (MLA). For each patient, the mean of all matched segments was calculated at the 2 time points. Clinical events at follow-up were documented. RESULTS: The PAV did not change significantly (-0.15 ± 3.64%, p = 0.72). The mean change in TAVnorm was 47.36 ± 143.24 mm(3) (p = 0.071), and the % change in TAV was 6.7% (p = 0.029). The MLD and MLA increased by 0.15 mm (-0.09 to 0.24, p = 0.039) and 0.52 mm(2) (-0.38 to 1.04, p = 0.034) respectively, which was accompanied by vessel enlargement, with 53% of the patients showing expansive positive remodeling. Patients with clinical events had a larger TAVnorm at baseline (969.72 mm(3) vs. 810.77 mm(3), p = 0.010). CONCLUSIONS: MSCT can assess the progression of coronary atherosclerosis and may be used for noninvasive monitoring of pharmacological interventions in coronary artery disease. ( PROSPECT: An Imaging Study in Patients With Unstable Atherosclerotic Lesions; NCT00180466).

Aortic annulus dimensions and leaflet calcification from contrast MSCT predict the need for balloon post-dilatation after TAVI with the Medtronic CoreValve prosthesis.

AIMS: We compared the measurement of aortic leaflet calcification on contrast and non-contrast MSCT and investigated predictors of the need for balloon post-dilatation after TAVI. METHODS AND RESULTS: In 110 patients, who had TAVI with a Medtronic CoreValve prosthesis (MCS) for symptomatic aortic stenosis, calcification of the aortic root was measured on non-contrast MSCT (conventionally) and on contrast MSCT (signal attenuation >450 Houndsfield units). Calcium volume was underestimated on contrast- when compared to non-contrast MSCT: median (IQ-range)=759 (466 to 1295) vs. 2016 (1376 to 3262) and the difference between the two methods increased with higher calcium volumes (correlation coefficient r=0.90). Calcium mass was only slightly underestimated on contrast vs. non-contrast MSCT: median (IQ-range)=441 (268 to 809) vs. 555 (341 to 950) and there was no association between the differences and increasing calcium mass (r=0.17). Balloon post-dilatation was performed for significant aortic regurgitation after TAVI in 11 of 110 patients. When compared to controls, the patients who required balloon post-dilatation had higher aortic leaflet calcium on contrast CT (p<0.01), higher aortic annulus diameters (p<0.01) and higher annulus to prosthesis area ratio (p=0.01). ROC curves demonstrated that aortic root or aortic leaflet calcium measured on either contrast- or non-contrast MSCT showed excellent discrimination for the requirement of balloon post-dilatation (area under ROC >0.80 for all), whereas the discriminatory value of aortic annulus dimensions was moderate (area under ROC=0.69) and that of prosthesis to annulus ratio was poor (area under ROC=0.36). CONCLUSIONS: Dense aortic leaflet calcification measured on contrast MSCT discerned well the need for balloon post-dilatation after TAVI with an MCS for significant PAR. Non-contrast MSCT may no longer be needed to quantify aortic root calcium before TAVI.

Detection and quantification of coronary atherosclerotic plaque by 64-slice multidetector CT: a systematic head-to-head comparison with intravascular ultrasound.

OBJECTIVE: We evaluated the ability of 64-slice multidetector computed tomography (MDCT)-derived plaque parameters to detect and quantify coronary atherosclerosis, using intravascular ultrasound (IVUS) as the reference standard. METHODS: In 32 patients, IVUS and 64-MDCT was performed. The MDCT and IVUS datasets of 44 coronary arteries were co-registered using a newly developed fusion technique and quantitative parameters were derived from both imaging modalities. The threshold of >0.5 mm of maximum wall thickness was used to establish plaque presence on MDCT and IVUS. RESULTS: We analyzed 1364 coregistered 1-mm coronary cross-sections and 255 segments of 5-mm length. Compared with IVUS, 64-MDCT enabled correct detection in 957 of 1109 cross-sections containing plaque (sensitivity 86%). In 180 of 255 cross-sections atherosclerosis was correctly excluded (specificity 71%). On the segmental level, MDCT detected 213 of 220 segments with any atherosclerotic plaque (sensitivity 96%), whereas the presence of any plaque was correctly ruled out in 28 of 32 segments (specificity 88%). Interobserver agreement for the detection of atherosclerotic cross-sections was moderate (Cohen's kappa coefficient K=0.51), but excellent for the atherosclerotic segments (K=1.0). Pearson's correlation coefficient for vessel plaque volumes measured by MDCT and IVUS was r=0.91 (p<0.001). Bland-Altman analysis showed a slight non-significant underestimation of any plaque volume by MDCT (p=0.5), with a trend to underestimate noncalcified and overestimate mixed/calcified plaque volumes (p=0.22 and p=0.87 respectively). CONCLUSION: MDCT is able to detect and quantify atherosclerotic plaque. Further improvement in CT resolution is necessary for more reliable assessment of very small and distal coronary plaques.

Invasive functional testing.

The concept of "significant" coronary stenosis has been revisited since the introduction of physiological measurements in the cardiac catheterisation laboratory. Invasive functional testing evaluates coronary physiology by recording blood pressure, flow or velocity and yields important information about the epicardial arteries and the respective myocardial territory. Numerous clinical studies have demonstrated the value of physiological testing in the assessment of challenging angiographic subsets, such as multivessel disease, bifurcation lesions and diffuse coronary atherosclerosis. In selected cases, deferral of revascularisation on the basis of functional indices can actually decrease adverse cardiac events. Furthermore, physiological measurements after angioplasty and stent implantation can be used to optimise the angiographic results and improve patient outcome. This review will discuss the basic concepts of functional testing in the catheterisation laboratory and its main applications for the interventional cardiologist.