Biomedical subjects

Fiona E Smith

Publications and source records attributed to Fiona E Smith.

3 recordsLinked to original sources

PubMed2003

Comparison of automatic repolarization measurement techniques in the normal magnetocardiogram.

Multichannel MCG noninvasively measures cardiac magnetic field strength from many sites at the body surface, potentially providing useful regional information about ventricular repolarization. Previous work on ECGs has shown that automatic techniques for repolarization measurement are better than manual measurement at discriminating patients with cardiac conditions from normal subjects. Although automatic repolarization measurement techniques have been quantified for ECGs, no comparative data exists for the MCG. In this study four different automatic repolarization (QT) interval techniques for detecting T wave end in the MCG were compared. The influence of MCG filtering on the automatic algorithms was also quantified. MCGs were obtained at 49 sites over the heart from 23 normal subjects. Automatic measurements of the repolarization (QT) interval were made following the addition of different high pass (0.25, 0.5, 1 Hz) and low pass (100, 60, 40, 30 Hz) filters. There were consistent differences between automatic techniques in the unfiltered data amounting to greatest mean difference of 52.3 ms. Low pass filtering significantly increased the automatic repolarization (QT) interval relative to unfiltered measurement by 6.5 (3.2) ms (mean SD) for 100 Hz, 6.0 (3.0) ms for 60 Hz, 8.1 (3.2) ms for 40 Hz, and 8.8 (3.1) ms for 30 Hz across all techniques. High pass filtering significantly decreased the value by -2.6 (6.0) ms for 0.25 Hz, -5.5 (5.3) ms for 0.5 Hz, and -17.1 (7.8) ms for 1 Hz. Automatic measurements of repolarization (QT) in the MCG differ between techniques and are influenced by filtering. These effects should be considered when comparing results.

Analysis of Variance↗

PubMed2002

Errors in repolarization measurement using magnetocardiography.

Multichannel magnetocardiography (MCG) noninvasively measures variations in magnetic field strength from many sites at the body surface, potentially providing useful regional information about ventricular repolarization. MCGs contain features similar to ECGs, and although errors associated with repolarization measurement have been quantified for ECGs, no comparative data exists for MCGs. In this study, errors in manual measurement of repolarization interval in the MCG were determined. Sixteen MCG channels and three ECG leads were recorded simultaneously in eight healthy subjects. Each recording was displayed in a random order on a computer screen, in presentations with different noise levels, time display widths, and amplitude display heights. In total, manual measurement of repolarization intervals in 2,048 (eight subjects x 16 channels x eight presentations x two repeats) MCGs were made by each of four analysts. Measured repolarization intervals were reduced by 3 ms when noise was added and by a further 3 ms when this noise was doubled. Intervals were shortened by 9 ms when the time display width was doubled and by a further 10 ms when the display width was doubled again. Measurements increased by 7 ms for a doubling of amplitude display height, equivalent to a doubling of T wave height. There were also consistent differences between analysts; amounting to a greatest mean difference of 24 ms. Display characteristics, added noise, and different analysts thus affect manual repolarization interval measurements in MCG. The errors detected demonstrate the importance of a standard presentation for repolarization measurement in the MCG.

Electrocardiography↗

PubMed2002

Identification of gene expression profiles that segregate patients with childhood leukemia.

To identify genes whose expression correlated with biological features of childhood leukemia, we prospectively analyzed the expression profiles of 4608 genes using cDNA microarrays in 51 freshly processed bone marrow samples from children with acute leukemia, over a 24-month period, at a single institution. Two supervised methods of analysis were used to identify the 20 best discriminating genes between the following cohorts: acute myelogenous leukemia (AML) versus acute lymphoblastic leukemia (ALL); B-lineage versus T-lineage ALL; newly diagnosed B-lineage standard-risk versus high-risk ALL; and B-lineage leukemia harboring the TEL-AML 1 fusion versus patients without a molecularly characterized translocation. These methods identified overlapping sets of genes that segregated patients within described subgroups. Cross-validation demonstrated that the majority of patients could be correctly classified based on these genes alone, and hierarchical clustering grouped patients with similar clinical and biological disease features. The potential for select genes to discriminate patients was validated using real-time PCR in samples that were analyzed by microarray profiling and in other uniformly processed leukemic marrow samples. As expected, microarray technology can successfully segregate patients defined by traditional measures such as immunophenotype and cytogenetic alterations. However, among specific subgroups, this preliminary analysis also suggests that microarrays can identify unanticipated similarities and diversity in individual patients and thus may be useful in augmenting risk-group stratification in the future.

Child↗