Quantitative determination of age-related geometric changes in the normal abdominal aorta.

PURPOSE: We conducted a novel quantitative three-dimensional analysis of computed tomography (CT) angiograms to establish the relationship between aortic geometry and age, sex, and body surface area in healthy subjects. METHODS: Abdominal helical CT angiograms from 77 healthy potential renal donors (33 men/44 women; mean age, 44 years; age range, 19-67 years) were selected. In each dataset, orthonormal cross-sectional area and diameter measurements were obtained at 1-mm intervals along the automatically calculated central axis of the abdominal aorta. The aorta was subdivided into six consecutive anatomic segments (supraceliac, supramesenteric, suprarenal, inter-renal, proximal infrarenal, and distal infrarenal). The interrelated effects of anatomic segment, age, sex, and body surface area on cross-sectional dimensions were analyzed with linear mixed-effects and varying-coefficient statistical models. RESULTS: We found that significant effects of sex and of body surface area on aortic diameters were similar at all anatomic levels. The effect of age, however, was interrelated with anatomic position, and gradually decreasing slopes of significant diameter-versus-age relationships along the aorta, which ranged from 0.14 mm/y (P <.0001) proximally to 0.03 mm/y (P =.013) distally in the abdominal aorta, were shown. CONCLUSION: The abdominal aorta undergoes considerable geometric changes when a patient is between 19 and 67 years of age, leading to an increase of aortic taper with time. The hemodynamic consequences of this geometric evolution for the development of aortic disease still need to be established.

Tree stability diagnostics and some remedies for instability.

Stability aspects of recursive partitioning procedures are investigated. Using resampling techniques, diagnostic tools to assess single split stability and overall tree stability are introduced. To correct for the procedure's preference for covariates with many unique realizations, corrected p-values are used in the factor selection component of the algorithm. Finally, methods to stabilize tree-based predictors are discussed.

Identifying and modelling prognostic factors with censored data.

A major issue in the analysis of diseases is the identification and assessment of prognostic factors relevant to the development of the illness. Statistical analyses within the proportional hazards framework suffer from a lack of flexibility due to stringent model assumptions such as additivity and time-constancy of effects. In this paper we use tree-based models and varying coefficient models to allow for detectability of prognostic factors with possibly non-additive, non-linear and time-varying impact on disease development. Questions concerning model and smoothing parameter selection are addressed. An analysis of a data set of breast cancer patients demonstrates the ability of these methods to reveal additional insight into the disease influencing mechanisms.

Bimodal distribution of angiographic measures of restenosis six months after coronary stent placement.

BACKGROUND: Restenosis has been perceived as the tail end of a normal distribution of the response of the vessel to the intervention. However, recent studies have described a bimodal distribution for de novo lesions after percutaneous transluminal coronary angioplasty. This finding suggests that some lesions may be more susceptible for restenosis. Whether this holds true for a wider spectrum of lesions undergoing stent placement is not yet known. The present study analyzes the frequency distribution of angiographic indexes of restenosis 6 months after coronary stent implantation. METHODS AND RESULTS: Quantitative angiographic evaluation was performed in 1084 lesions of 1084 patients before, immediately after, and 6 months after successful Palmaz-Schatz stent placement; this represented 80.4% of patients eligible for follow-up angiography. Principal end points of the analysis were angiographic indexes of restenosis at 6 months. Twenty-two lesions that became totally occluded at follow-up were excluded from most parts of the analysis. Diameter stenosis, minimal luminal diameter (MLD), and lumen loss at 6 months did not follow a normal pattern; the bimodal pattern was demonstrated through deconvolution that yielded two separate normal components delineating two lesion populations, which developed distinctively different degrees of lumen renarrowing. The first and larger subgroup of lesions, which was less prone to restenosis, was centered around a mean value of 27% for diameter stenosis and 2.19 mm for MLD, whereas the second subgroup, with a greater tendency for restenosis, was situated around a mean value of 68% for diameter stenosis and 0.76 mm for MLD. The intersection point between the two theoretical normal distribution components was 53.5% for diameter stenosis and 1.09 mm for MLD at follow-up. CONCLUSIONS: Frequency-distribution curves of angiographic indexes of restenosis after coronary stent placement have a bimodal pattern, suggesting the existence of two distinct populations with different propensity to restenosis. These findings may encourage future efforts for the timely identification of the subset with a higher risk as the target of specific antirestenotic strategies.