scispace - formally typeset
S

Stephane Carlier

Researcher at University of Mons

Publications -  219
Citations -  7932

Stephane Carlier is an academic researcher from University of Mons. The author has contributed to research in topics: Intravascular ultrasound & Stent. The author has an hindex of 45, co-authored 218 publications receiving 7454 citations. Previous affiliations of Stephane Carlier include Columbia University & Rotterdam University of Applied Sciences.

Papers
More filters
Journal ArticleDOI

Residual Plaque Burden, Delivered Dose, and Tissue Composition Predict 6-Month Outcome After Balloon Angioplasty and β-Radiation Therapy

TL;DR: Residual plaque burden, delivered dose, and morphological characteristics of coronary stenoses treated with beta-radiation therapy and BA play a fundamental role in the volumetric outcome at 6-month follow-up after beta- Radiation Therapy and BA.
Journal ArticleDOI

Necrotic Core and Its Ratio to Dense Calcium Are Predictors of High-Risk Non–ST-Elevation Acute Coronary Syndrome

TL;DR: VH-IVUS analysis showed that the percentage of NC and its ratio to DC in diseased coronary segments are positively associated with a high-risk ACS presentation.
Journal ArticleDOI

Intravascular ultrasonic assessment of stent diameters derived from manufacturer's compliance charts.

TL;DR: In this paper, the authors used intravascular ultrasound (IVUS) to assess the accuracy of manufacturers' stent balloon compliance charts and found that the predicted stent diameters were significantly smaller than those predicted by in vitro compliance charts.
Journal ArticleDOI

Intravascular ultrasound profile analysis of ruptured coronary plaques.

TL;DR: In conclusion, plaque ruptures do not occur at minimal disease sites, Rather, vulnerable (rupture-prone) plaques predictably have significant plaque accumulation and remodeling and occur in larger arteries.
Journal ArticleDOI

Stent implant follow-up in intravascular optical coherence tomography images

TL;DR: Low variability between the expert and automatic method was observed in the computations of the most important parameters assessing the degree of neointimal tissue growth in stents imaged by OCT pullbacks, suggesting a robust automated tool that will improve the evaluation and follow-up monitoring of in-stent restenosis in patients.