Detection of non-ST-elevation myocardial infarction and unstable angina in the acute setting: meta-analysis of diagnostic performance of multi-detector computed tomographic angiography

<p>Abstract</p> <p>Background</p> <p>Multi-detector computed tomography angiography (MDCTA) has been increasingly used in the evaluation of the coronary arteries. The purpose of this study was to review the literature on the diagnostic performance of MDCTA in the acute setting, for the detection of non-ST-elevation myocardial infarction (NSTEMI) and unstable angina pectoris (UAP).</p> <p>Methods</p> <p>A Pubmed and manual search of the literature published between January 2000 and June 2007 was performed. Studies were included that compared MDCTA with clinical outcome and/or CA in patients with acute chest pain, presenting at the emergency department. More specifically, studies that only included patients with initially negative cardiac enzymes suspected of having NSTEMI or UAP were included. Summary estimates of diagnostic odds ratio (DOR), sensitivity and specificity, negative (NLR) and positive likelihood ratio (PLR) were calculated on a patient basis. Random-effects models and summary receiver operating curve (SROC) analysis were used to assess the diagnostic performance of MDCTA with 4 detectors or more. The proportion of non assessable scans (NAP) on MDCTA was also evaluated. In addition, the influence of study characteristics of each study on diagnostic performance and NAP was investigated with multivariable logistic regression.</p> <p>Results</p> <p>Nine studies totalling 566 patients, were included in the meta-analysis: one randomised trial and eight prospective cohort studies. Five studies on 64-detector MDCTA and 4 studies on MDCTA with less than 64 detectors were included (32 detectors n = 1, 16 detectors n = 2, 16 and 4 detectors n = 1). Pooled DOR was 131.81 (95%CI, 50.90–341.31). The pooled sensitivity and specificity were 0.95 (95%CI, 0.90–0.98) and 0.90 (95%CI, 0.87–0.93). The pooled NLR and PLR were 0.12 (95%CI, 0.06–0.21) and 8,60 (95%CI, 5.03–14,69).</p> <p>The results of the logistic regressions showed that none of the investigated variables had influence on the diagnostic performance or NAP</p> <p>Conclusion</p> <p>MDCTA of the coronary arteries performs good to excellent in the diagnosis of coronary artery disease in the acute setting and it can be used for early exclusion of NSTEMI or UAP in patients in the emergency department.</p

Multidetector computed tomography angiography for assessment of in-stent restenosis: meta-analysis of diagnostic performance

<p>Abstract</p> <p>Background</p> <p>Multi-detector computed tomography angiography (MDCTA)of the coronary arteries after stenting has been evaluated in multiple studies.</p> <p>The purpose of this study was to perform a structured review and meta-analysis of the diagnostic performance of MDCTA for the detection of in-stent restenosis in the coronary arteries.</p> <p>Methods</p> <p>A Pubmed and manual search of the literature on in-stent restenosis (ISR) detected on MDCTA compared with conventional coronary angiography (CA) was performed. Bivariate summary receiver operating curve (SROC) analysis, with calculation of summary estimates was done on a stent and patient basis. In addition, the influence of study characteristics on diagnostic performance and number of non-assessable segments (NAP) was investigated with logistic meta-regression.</p> <p>Results</p> <p>Fourteen studies were included. On a stent basis, Pooled sensitivity and specificity were 0.82(0.72–0.89) and 0.91 (0.83–0.96). Pooled negative likelihood ratio and positive likelihood ratio were 0.20 (0.13–0.32) and 9.34 (4.68–18.62) respectively. The exclusion of non-assessable stents and the strut thickness of the stents had an influence on the diagnostic performance. The proportion of non-assessable stents was influenced by the number of detectors, stent diameter, strut thickness and the use of an edge-enhancing kernel.</p> <p>Conclusion</p> <p>The sensitivity of MDTCA for the detection of in-stent stenosis is insufficient to use this test to select patients for further invasive testing as with this strategy around 20% of the patients with in-stent stenosis would be missed. Further improvement of scanner technology is needed before it can be recommended as a triage instrument in practice. In addition, the number of non-assessable stents is also high.</p

Bilateral intramuscular pseudotumor in a bodybuilder

A 29-year-old bodybuilder presented with a bilateral palpable and painful soft tissue mass in the deltoid region. CT scan showed a bilateral intramuscular mass within the deltoid muscle with intralesional fat (not shown). For further differentiation and exclusion of a fat-containing sarcomatous lesion, MRI of both shoulders was performed. Axial T1-weighted images (WI) of the right shoulder showed a heterogeneous mass lesion containing multiple fatty components (Fig. A, arrows). Axial T1-WI of the left shoulder depicted a mass with a T1-hyperintense fatty component and marked fat-fluid level (Fig. B, arrow). The lesion also demonstrated a fat-fluid level on a sagittal fat suppressed T2-WI (Fig. C, arrow)

Value of Relative Myocardial Perfusion at MRI for Fractional Flow Reserve-Defined Ischemia: A Pilot Study.

OBJECTIVE: Correcting the perfusion in areas distal to coronary stenosis (risk) according to that of normal (remote) areas defines the relative myocardial perfusion index, which is similar to the fractional flow reserve (FFR) concept. The aim of this study was to assess the value of relative myocardial perfusion by MRI in predicting lesion-specific inducible ischemia as defined by FFR. MATERIALS AND METHODS: Forty-six patients (33 men and 13 women; mean [+/- SD] age, 61 +/- 9 years) who underwent adenosine perfusion MRI and FFR measurement distal to 49 coronary artery stenoses during coronary angiography were retrospectively evaluated. Subendocardial time-enhancement maximal upslopes, normalized by the respective left ventricle cavity upslopes, were obtained in risk and remote subendocardium during adenosine and rest MRI perfusion and were correlated to the FFR values. RESULTS: The mean FFR value was 0.84 +/- 0.09 (range, 0.60-0.98) and was less than or equal to 0.80 in 31% of stenoses (n = 15). The relative subendocardial perfusion index (risk-to-remote upslopes) during hyperemia showed better correlations with the FFR value (r = 0.59) than the uncorrected risk perfusion parameters (i.e., both the upslope during hyperemia and the perfusion reserve index [stress-to-rest upslopes]; r = 0.27 and 0.29, respectively). A cutoff value of 0.84 of the relative subendocardial perfusion index had an ROC AUC of 0.88 to predict stenosis at an FFR of less than or equal to 0.80. CONCLUSION: Using adenosine perfusion MRI, the relative myocardial perfusion index enabled the best prediction of FFR-defined lesion-specific myocardial ischemia. This index could be used to noninvasively determine the need for revascularization of known coronary stenoses

Stress perfusion CMR: improved correlation with invasive fractional flow reserve after correction for perfusion changes in remote myocardium.

PURPOSE This study was undertaken, considering fractional flow reserve (FFR) as the reference: (i) to evaluate a predictive model of flow reserve using adenosine cardiac magnetic resonance (CMR) time-signal intensity measurements collected in the area distal to a focal coronary artery stenosis (CAS) and (ii) to assess the incremental value of correcting this model by including similar measurements in remote areas. METHOD AND MATERIALS This retrospective study was approved by the hospital ethics committee. Forty-six patients (mean age 61±9 years; 33 males) who underwent both adenosine first-pass CMR and FFR in the work-up for a focal CAS (n=49) were included after written informed consent. Areas-at-risk (RISK) and remote adenosine/rest time-signal intensity parameters were evaluated. Boosting models were elaborated to predict the FFR value from (i)the whole (extended) and (ii)RISK-only parameters. The relationship between the predictions and FFR value was described with Bland-Altman and summarized with intra-class correlation(ICC). Diagnostic accuracies of the models predicting FFR<=0.80 were calculated. RESULTS The average FFR value was 0.84±0.09 (0.60-0.98 range), 15(31%) were <=0.80. Decreasing FFR was associated with opposite effects on myocardial time-signal intensity responses downstream of the CAS or remotely. Compared to the RISK-only models, the extended models exhibited higher correlations with the FFR value (0.73;95%CI,0.57-0.84 versus 0.25;95%CI,0.03-0.50) and diagnostic accuracy to predict FFR<=0.80 CAS [44/49 (90%; 95%CI,78-98) vs 36/49 (73%;95%CI,55-88)]. CONCLUSION When evaluating the functional significance of a CAS using adenosine first-pass CMR, considering time-signal intensity measurements in remote areas allows a better correlation with invasive FFR and improved diagnostic accuracy for FFR<=0.80. CLINICAL RELEVANCE/APPLICATION To improve the clinical relevance of evaluating coronary stenoses by using adenosine first-pass CMR, each perfusion-related parameter should be corrected by its value in remote segments. Clos