Central aortic valve coaptation area during diastole as seen by 64-multidetector computed tomography (MDCT)

As multiple new procedures now require better visualization of the aortic valve, we sought to better define the central aortic valve coaptation area seen during diastole on multi-detector row cardiac computed tomography (MDCT). 64-MDCT images of 384 symptomatic consecutive patients referred for coronary artery disease evaluation were included in the study. Planimetric measurements of this area were performed on cross-sectional views of the aortic valve at 75% phase of the cardiac cycle. Planimetric measurement of central regurgitation orifice area (ROA) seen in patients with aortic regurgitation and Hounsfield units of the central aortic valve coaptation area were performed. Mean area of the central aortic valve coaptation area was 5.34 ± 5.19 mm2 and Hounsfield units in this area were 123.69 ± 31.31 HU. The aortic valve coaptation area (mm2) measurement in patients without AR was: 4.90 ± 0.17 and in patients with AR: 10.53 ± 0.26 (P = <0.05). On Bland–Altman analysis a very good correlation between central aortic valve coaptation area and central ROA was found (r = 0.80, P = <0.001). Central aortic valve coaptation area is a central area present at the coaptation of nodules of arantius of aortic cusps during diastole; it is incompetent and increased in size in patients with aortic regurgitation

Left ventricular volume: an optimal parameter to detect systolic dysfunction on prospectively triggered 64-multidetector row computed tomography: another step towards reducing radiation exposure

In this study, we define the correlation between LV volumes (both LV end-diastolic volume [LVEDV] and LV end-systolic volume [LVESV]) and ejection fraction (EF) on 64 slice multi-detector computed tomography (MDCT). We also determine the accuracy of all the LV volume (LVV) parameters to detect LV systolic dysfunction (LVSD) and investigate the feasibility of using LVV as a surrogate of LVSD on prospectively gated imaging to prevent the radiation exposure of retrospective imaging. 568 patients undergoing 64-detector MDCT were divided into 2 groups: Group 1—subjects without any heart disease and LVEF ≥ 50%; and Group 2—patients with coronary artery disease and LVEF < 50% (defined as LVSD). The LVV (LV cavity only) and Total LV volume (cavity + LV mass) at end-systole and end-diastole (LVESV, Total LVESV, LVEDV and Total LVEDV) were measured. The upper limit values (mean + 2 SD) of all LVV parameters in Group 1 were used as the reference criterion to diagnose LVSD in Group 2. An exponential correlation was found between LVEF and all the LVV parameters. The specificity to detect LVSD in Group 2 was >90% and the sensitivity was 88.9, 83.3, 61.3 and 74.9% by using LVESV, Total LVESV, LVEDV and Total LVEDV, respectively. Systolic and diastolic LV volumes had a high correlation with LVEF and a high accuracy to detect LVSD. Thus, on prospectively triggered imaging, ventricular volumes can predict patients with reduced LVEF, and appropriate referrals can be made

Non-contrast cardiac computed tomography can accurately detect chronic myocardial infarction: Validation study

BackgroundThis study evaluates whether non-contrast cardiac computed tomography (CCT) can detect chronic myocardial infarction (MI) in patients with irreversible perfusion defects on nuclear myocardial perfusion imaging (MPI).MethodsOne hundred twenty-two symptomatic patients with irreversible perfusion defect (N = 62) or normal MPI (N = 60) underwent coronary artery calcium (CAC) scanning. MI on these non-contrast CCTs was visually detected based on the hypo-attenuation areas (dark) in the myocardium and corresponding Hounsfield units (HU) were measured.ResultsNon-contrast CCT accurately detected MI in 57 patients with irreversible perfusion defect on MPI, yielding a sensitivity of 92%, specificity of 72%, negative predictive value (NPV) of 90%, and a positive predictive value (PPV) of 77%. On a per myocardial region analysis, non-contrast CT showed a sensitivity of 70%, specificity of 85%, NPV of 91%, and a PPV of 57%. The ROC curve showed that the optimal cutoff value of LV myocardium HU to predict MI on non-contrast CCT was 21.7 with a sensitivity of 97.4% and specificity of 99.7%.ConclusionNon-contrast CCT has an excellent agreement with MPI in detecting chronic MI. This study highlights a novel clinical utility of non-contrast CCT in addition to assessment of overall burden of atherosclerosis measured by CAC

Providing an OAI-PMH Interface to the Storage Resource Broker With OAISRB

The OAISRB software was developed by Michael Witt and Jigar Kadakia of the Purdue University Libraries provide an Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) interface to expose metadata from digital objects residing on the Storage Resource Broker (SRB) to OAI service providers. By harvesting metadata from the SRB, grid resources such as large research datasets from computational sciences can be represented alongside more conventional digital library objects such as e-prints and digitized archival collections. This poster was presented at the 2nd International Digital Curation Conference in Glasgow, Scotland, on November 22, 2006

Left ventricular volume: an optimal parameter to detect systolic dysfunction on prospectively triggered 64-multidetector row computed tomography: another step towards reducing radiation exposure.

In this study, we define the correlation between LV volumes (both LV end-diastolic volume [LVEDV] and LV end-systolic volume [LVESV]) and ejection fraction (EF) on 64 slice multi-detector computed tomography (MDCT). We also determine the accuracy of all the LV volume (LVV) parameters to detect LV systolic dysfunction (LVSD) and investigate the feasibility of using LVV as a surrogate of LVSD on prospectively gated imaging to prevent the radiation exposure of retrospective imaging. 568 patients undergoing 64-detector MDCT were divided into 2 groups: Group 1-subjects without any heart disease and LVEF ≥ 50%; and Group 2-patients with coronary artery disease and LVEF &lt; 50% (defined as LVSD). The LVV (LV cavity only) and Total LV volume (cavity + LV mass) at end-systole and end-diastole (LVESV, Total LVESV, LVEDV and Total LVEDV) were measured. The upper limit values (mean + 2 SD) of all LVV parameters in Group 1 were used as the reference criterion to diagnose LVSD in Group 2. An exponential correlation was found between LVEF and all the LVV parameters. The specificity to detect LVSD in Group 2 was &gt;90% and the sensitivity was 88.9, 83.3, 61.3 and 74.9% by using LVESV, Total LVESV, LVEDV and Total LVEDV, respectively. Systolic and diastolic LV volumes had a high correlation with LVEF and a high accuracy to detect LVSD. Thus, on prospectively triggered imaging, ventricular volumes can predict patients with reduced LVEF, and appropriate referrals can be made