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Biomedical subjects

Frank Miller

Publications and source records attributed to Frank Miller.

6 recordsLinked to original sources

Intrinsic fluorescence and diffuse reflectance spectroscopy identify superficial foam cells in coronary plaques prone to erosion.

OBJECTIVE: Foam cells perform critical functions in atherosclerosis. We hypothesize that coronary segments with superficial foam cells (SFCs) situated in a region of interest with a depth of 200 mum can be identified using intrinsic fluorescence spectroscopy (IFS) and diffuse reflectance spectroscopy (DRS). This is a key step in our ongoing program to develop a spectroscopic technique for real-time in vivo diagnosis of vulnerable atherosclerotic plaque. METHODS AND RESULTS: We subjected 132 human coronary segments to in vitro IFS and DRS. We detected SFCs in 13 thick fibrous cap atheromas and 8 pathologic intimal thickening (PIT) lesions. SFCs colocalized with accumulations of smooth muscle cells and proteoglycans, including hyaluronan (P<0.001). Two spectroscopic parameters were generated from analysis of IFS at 480 nm excitation and DRS. A discriminatory algorithm using these parameters identified specimens with SFC area >40%, 20%, 10%, 5%, 2.5%, and 0% of the region of interest with 98%, 98%, 93%, 94%, 93%, and 90% accuracy, respectively. CONCLUSIONS: Our combined IFS and DRS technique accurately detects SFCs in thick fibrous cap atheromas and PIT lesions. Because SFCs are associated with histological markers of plaque erosion, our spectroscopic technique could prove useful in identifying vulnerable plaques.

Algorithms↗

Variance estimation in clinical studies with interim sample size re-estimation.

We consider clinical studies with a sample size re-estimation based on the unblinded variance estimation at some interim point of the study. Because the sample size is determined in such a flexible way, the usual variance estimator at the end of the trial is biased. We derive sharp bounds for this bias. These bounds have a quite simple form and can help for the decision if this bias is negligible for the actual study or if a correction should be done. An exact formula for the bias is also provided. We discuss possibilities to get rid of this bias or at least to reduce the bias substantially. For this purpose, we propose a certain additive correction of the bias. We see in an example that the significance level of the test can be controlled when this additive correction is used.

Analysis of Variance↗