Global end-diastolic volume increases to maintain fluid responsiveness in sepsis-induced systolic dysfunction

Background: Sepsis-induced cardiac dysfunction may limit fluid responsiveness and the mechanism thereof remains unclear. Since cardiac function may affect the relative value of cardiac filling pressures, such as the recommended central venous pressure (CVP), versus filling volumes in guiding fluid loading, we studied these parameters as determinants of fluid responsiveness, according to cardiac function.Methods: A delta CVP-guided, 90 min colloid fluid loading protocol was performed in 16 mechanically ventilated patients with sepsis-induced hypotension and three 30 min consecutive fluid loading steps of about 450 mL per patient were evaluated. Global end-diastolic volume index (GEDVI), cardiac index (CI) and global ejection fraction (GEF) were assessed from transpulmonary dilution. Baseline and changes in CVP and GEDVI were compared among responding (CI increase ≥10% and ≥15%) and non-responding fluid loading steps, in patient with low (<20%, n = 9) and near-normal (≥20%) GEF (n = 7) at baseline.Results: A low GEF was in line with other indices of impaired cardiac (left ventricular) function, prior to and after fluid loading. Of 48 fluid loading steps, 9 (of 27) were responding when GEF <20% and 6 (of 21) when GEF ≥20. Prior to fluid loading, CVP did not differ between responding and non-responding steps and levels attained were 23 higher in the latter, regardless of GEF (P = 0.004). Prior to fluid loading, GEDVI (and CI) was higher in responding (1007 ± 306 mL/m2) than non-responding steps (870 ± 236 mL/m2) when GEF was low (P = 0.002), but did not differ when GEF was near-normal. Increases in GEDVI were associated with increases in CI and fluid responsiveness, regardless of GEF (P < 0.001).Conclusions: As estimated from transpulmonary dilution, about half of patients with sepsis-induced hypotension have systolic cardiac dysfunction. During dysfunction, cardiac dilation with a relatively high baseline GEDVI maintains fluid responsiveness by further dilatation (increase in GEDVI rather than of CVP) as in patients without dysfunction. Absence of fluid responsiveness during systolic cardiac dysfunction may be caused by diastolic dysfunction and/or right ventricular dysfunction

Recovery of myocardial perfusion after percutaneous coronary intervention of chronic total occlusions is comparable to hemodynamically significant non-occlusive lesions.

BACKGROUND: The benefits of chronic coronary total occlusion (CTO) percutaneous coronary intervention (PCI) are being questioned. The aim of this study was to assess the effects of CTO PCI on absolute myocardial perfusion, as compared with PCI of hemodynamically significant non-CTO lesions. METHODS: Consecutive patients with a preserved left ventricular ejection fraction (≥50%) and a CTO or non-CTO lesion, in whom [15 O]H2 O positron emission tomography was performed prior and after successful PCI, were included. Change in quantitative (hyperemic) myocardial blood flow (MBF), coronary flow reserve (CFR) and perfusion defect size (in myocardial segments) were compared between CTOs and non-CTO lesions. RESULTS: In total 92 patients with a CTO and 31 patients with a non-CTO lesion were included. CTOs induced larger perfusion defect sizes (4.51 ± 1.69 vs. 3.23 ± 2.38 segments, P < 0.01) with lower hyperemic MBF (1.30 ± 0.37 vs. 1.58 ± 0.62 mL·min-1 ·g-1 , P < 0.01) and similarly impaired CFR (1.66 ± 0.75 vs. 1.89 ± 0.77, P = 0.17) compared with non-CTO lesions. After PCI both hyperemic MBF and CFR increased similarly between groups (P = 0.57 and 0.35) to normal ranges with higher hyperemic MBF values in non-CTO compared with CTO (2.89 ± 0.94 vs. 2.48 ± 0.73 mL·min-1 ·g-1 , P = 0.03). Perfusion defect sizes decreased similarly after CTO PCI and non-CTO PCI (P = 0.14), leading to small residual defect sizes in both groups (1.15 ± 1.44 vs. 0.61 ± 1.45 segments, P = 0.054). CONCLUSIONS: Myocardial perfusion findings are slightly more hampered in patients with a CTO before and after PCI. Percutaneous revascularization of CTOs, however, improves absolute myocardial perfusion similarly to PCI of hemodynamically significant non-CTO lesions, leading to satisfying results

The prognostic value of visual and automatic coronary calcium scoring from low-dose computed tomography-[15O]-water positron emission tomography

Aims: The study aimed, firstly, to validate automatically and visually scored coronary artery calcium (CAC) on low-dose computed tomography (CT) (LDCT) scans with a dedicated calcium scoring CT (CSCT) scan and, secondly, to assess the added value of CAC scored from LDCT scans acquired during [15O]-water-positron emission tomography (PET) myocardial perfusion imaging (MPI) on prediction of major adverse cardiac events (MACE).Methods and results: Five hundred seventy-two consecutive patients with suspected coronary artery disease, who underwent [15O]-water-PET MPI with LDCT and a dedicated CSCT scan were included. In the reference CSCT scans, manual CAC scoring was performed, while LDCT scans were scored visually and automatically using deep learning approach. Subsequently, based on CAC score results from CSCT and LDCT scans, each patient’s scan was assigned to one out of five cardiovascular risk groups (0, 1–100, 101–400, 401–1000, &gt;1000), and the agreement in risk group classification between CSCT and LDCT scans was investigated. MACE was defined as a composite of all-cause death, non-fatal myocardial infarction, coronary revascularization, and unstable angina. The agreement in risk group classification between reference CSCT manual scoring and visual/automatic LDCT scoring from LDCT was 0.66 [95% confidence interval (CI): 0.62–0.70] and 0.58 (95% CI: 0.53–0.62), respectively. Based on visual and automatic CAC scoring from LDCT scans, patients with CAC &gt; 100 and CAC &gt; 400, respectively, were at increased risk of MACE, independently of ischaemic information from the [15O]-water-PET scan.Conclusion: There is a moderate agreement in risk classification between visual and automatic CAC scoring from LDCT and reference CSCT scans. Visual and automatic CAC scoring from LDCT scans improve identification of patients at higher risk of MACE.</p

Atherosclerosis Imaging Quantitative Computed Tomography (AI-QCT) to guide referral to invasive coronary angiography in the randomized controlled CONSERVE trial

Aims: We compared diagnostic performance, costs, and association with major adverse cardiovascular events (MACE) of clinical coronary computed tomography angiography (CCTA) interpretation versus semiautomated approach that use artificial intelligence and machine learning for atherosclerosis imaging-quantitative computed tomography (AI-QCT) for patients being referred for nonemergent invasive coronary angiography (ICA). Methods: CCTA data from individuals enrolled into the randomized controlled Computed Tomographic Angiography for Selective Cardiac Catheterization trial for an American&nbsp;College&nbsp;of&nbsp;Cardiology&nbsp;(ACC)/American&nbsp;Heart&nbsp;Association&nbsp;(AHA) guideline indication for ICA were analyzed. Site interpretation of CCTAs were compared to those analyzed by a cloud-based software (Cleerly, Inc.) that performs AI-QCT for stenosis determination, coronary vascular measurements and quantification and characterization of atherosclerotic plaque. CCTA interpretation and AI-QCT guided findings were related to MACE at 1-year follow-up. Results: Seven hundred forty-seven&nbsp;stable patients (60 ± 12.2 years, 49% women) were included. Using AI-QCT, 9% of patients had no CAD compared with 34% for clinical CCTA interpretation. Application of AI-QCT to identify obstructive coronary stenosis at the ≥50% and ≥70% threshold would have reduced ICA by 87% and 95%, respectively. Clinical outcomes for patients without AI-QCT-identified obstructive stenosis was excellent; for 78% of patients with maximum stenosis &lt; 50%, no cardiovascular death or acute myocardial infarction occurred. When applying an AI-QCT referral management approach to avoid ICA in patients with &lt;50% or &lt;70% stenosis, overall costs were reduced by 26% and 34%, respectively. Conclusions: In stable patients referred for ACC/AHA guideline-indicated nonemergent ICA, application of artificial intelligence and machine learning for AI-QCT can significantly reduce ICA rates and costs with no change in 1-year MACE

The prognostic value of visual and automatic coronary calcium scoring from low-dose computed tomography-[15O]-water positron emission tomography

Aims: The study aimed, firstly, to validate automatically and visually scored coronary artery calcium (CAC) on low-dose computed tomography (CT) (LDCT) scans with a dedicated calcium scoring CT (CSCT) scan and, secondly, to assess the added value of CAC scored from LDCT scans acquired during [15O]-water-positron emission tomography (PET) myocardial perfusion imaging (MPI) on prediction of major adverse cardiac events (MACE). Methods and results: Five hundred seventy-Two consecutive patients with suspected coronary artery disease, who underwent [15O]-water-PET MPI with LDCT and a dedicated CSCT scan were included. In the reference CSCT scans, manual CAC scoring was performed, while LDCT scans were scored visually and automatically using deep learning approach. Subsequently, based on CAC score results from CSCT and LDCT scans, each patient's scan was assigned to one out of five cardiovascular risk groups (0, 1-100, 101-400, 401-1000, >1000), and the agreement in risk group classification between CSCT and LDCT scans was investigated. MACE was defined as a composite of all-cause death, non-fatal myocardial infarction, coronary revascularization, and unstable angina. The agreement in risk group classification between reference CSCT manual scoring and visual/automatic LDCT scoring from LDCT was 0.66 [95% confidence interval (CI): 0.62-0.70] and 0.58 (95% CI: 0.53-0.62), respectively. Based on visual and automatic CAC scoring from LDCT scans, patients with CAC > 100 and CAC > 400, respectively, were at increased risk of MACE, independently of ischaemic information from the [15O]-water-PET scan. Conclusion: There is a moderate agreement in risk classification between visual and automatic CAC scoring from LDCT and reference CSCT scans. Visual and automatic CAC scoring from LDCT scans improve identification of patients at higher risk of MACE

Data on the impact of scan quality on the diagnostic performance of CCTA, SPECT, and PET for diagnosing myocardial ischemia defined by fractional flow reserve on a per vessel level

Scan quality directly impacts the diagnostic performance of non-invasive imaging modalities as reported in a substudy of the PACIFC-trial: "Impact of Scan Quality on the Diagnostic Performance of CCTA, SPECT, and PET for Diagnosing Myocardial Ischemia Defined by Fractional Flow Reserve" [1]. This Data-in-Brief paper supplements the hereinabove mentioned article by presenting the diagnostic performance of CCTA, SPECT, and PET on a per vessel level for the detection of hemodynamic significant coronary artery disease (CAD) when stratified according to scan quality and vascular territory

Automated SPECT analysis compared with expert visual scoring for the detection of FFR-defined coronary artery disease

PurposeTraditionally, interpretation of myocardial perfusion imaging (MPI) is based on visual assessment. Computer-based automated analysis might be a simple alternative obviating the need for extensive reading experience. Therefore, the aim of the present study was to compare the diagnostic performance of automated analysis with that of expert visual reading for the detection of obstructive coronary artery disease (CAD).Methods206 Patients (64% men, age 58.2 ± 8.7 years) with suspected CAD were included prospectively. All patients underwent 99mTc-tetrofosmin single-photon emission computed tomography (SPECT) and invasive coronary angiography with fractional flow reserve (FFR) measurements. Non-corrected (NC) and attenuation-corrected (AC) SPECT images were analyzed both visually as well as automatically by commercially available SPECT software. Automated analysis comprised a segmental summed stress score (SSS), summed difference score (SDS), stress total perfusion deficit (S-TPD), and ischemic total perfusion deficit (I-TPD), representing the extent and severity of hypoperfused myocardium. Subsequently, software was optimized with an institutional normal database and thresholds. Diagnostic performances of automated and visual analysis were compared taking FFR as a reference.ResultsSensitivity did not differ significantly between visual reading and most automated scoring parameters, except for SDS, which was significantly higher than visual assessment (p ConclusionAutomated analysis of myocardial perfusion SPECT can be as accurate as visual interpretation by an expert reader in detecting significant CAD defined by FFR.</div

Comparison between the performance of quantitative flow ratio and perfusion imaging for diagnosing myocardial ischemia

OBJECTIVES This study compared the performance of the quantitative flow ratio (QFR) with single-photon emission computed tomography (SPECT) and positron emission tomography (PET) myocardial perfusion imaging (MPI) for the diagnosis of fractional flow reserve (FFR)-defined coronary artery disease (CAD).BACKGROUND QFR estimates FFR solely based on cine contrast images acquired during invasive coronary angiography (ICA). Head-to-head studies comparing QFR with noninvasive MPI are lacking.METHODS A total of 208 (624 vessels) patients underwent technetium -99m tetrofosmin SPECT and [15O]H2O PET imaging before ICA in conjunction with FFR measurements. ICA was obtained without using a dedicated QFR acquisition protocol, and QFR computation was attempted in all vessels interrogated by FFR (552 vessels).RESULTS QFR computation succeeded in 286 (52%) vessels. QFR correlated well with invasive FFR overall (R = 0.79; p < 0.001) and in the subset of vessels with an intermediate (30% to 90%) diameter stenosis (R = 0.76; p < 0.001). Overall, per-vessel analysis demonstrated QFR to exhibit a superior sensitivity (70%) in comparison with SPECT (29%; p < 0.001), whereas it was similar to PET (75%; p = 1.000). Specificity of QFR (93%) was higher than PET (79%; p < 0.001) and not different from SPECT (96%; p = 1.000). As such, the accuracy of QFR (88%) was superior to both SPECT (82%; p = 0.010) and PET (78%; p = 0.004). Lastly, the area under the receiver operating characteristics curve of QFR, in the overall sample (0.94) and among vessels with an intermediate lesion (0.90) was higher than SPECT (0.63 and 0.61; p < 0.001 for both) and PET (0.82; p < 0.001 and 0.77; p = 0.002), respectively.CONCLUSIONS In this head-to-head comparative study, QFR exhibited a higher diagnostic value for detecting FFRdefined significant CAD compared with perfusion imaging by SPECT or PET. (J Am Coll Cardiol Img 2020;13:1976-85) (c) 2020 by the American College of Cardiology Foundation.Cardiovascular Aspects of Radiolog

Functional stress imaging to predict abnormal coronary fractional flow reserve: the PACIFIC 2 study

AimsThe diagnostic performance of non-invasive imaging in patients with prior coronary artery disease (CAD) has not been tested in prospective head-to-head comparative studies. The aim of this study was to compare the diagnostic performance of qualitative single-photon emission computed tomography (SPECT), quantitative positron emission tomography (PET), and qualitative magnetic resonance imaging (MRI) in patients with a prior myocardial infarction (MI) or percutaneous coronary intervention (PCI).Methods and resultsIn this prospective clinical study, all patients with prior MI and/or PCI and new symptoms of ischaemic CAD underwent 99mTc-tetrofosmin SPECT, [15O]H2O PET, and MRI, followed by invasive coronary angiography with fractional flow reserve (FFR) in all coronary arteries. All modalities were interpreted by core laboratories. Haemodynamically significant CAD was defined by at least one coronary artery with an FFR ≤0.80. Among the 189 enrolled patients, 63% had significant CAD. Sensitivity was 67% (95% confidence interval 58–76%) for SPECT, 81% (72–87%) for PET, and 66% (56–75%) for MRI. Specificity was 61% (48–72%) for SPECT, 65% (53–76%) for PET, and 62% (49–74%) for MRI. Sensitivity of PET was higher than SPECT (P = 0.016) and MRI (P = 0.014), whereas specificity did not differ among the modalities. Diagnostic accuracy for PET (75%, 68–81%) did not statistically differ from SPECT (65%, 58–72%, P = 0.03) and MRI (64%, 57–72%, P = 0.052). Using FFR ConclusionIn this prospective head-to-head comparative study, SPECT, PET, and MRI did not show a significantly different accuracy for diagnosing FFR defined significant CAD in patients with prior PCI and/or MI. Overall diagnostic performances, however, were discouraging and the additive value of non-invasive imaging in this high-risk population is questionable.</p