Breast Reconstruction Clinical Outcomes
We investigate the efficacy of neurotized DIEP flap reconstruction, meticulously analyzing patient outcomes to refine surgical techniques and optimize functional and aesthetic results. Additionally, our basic science research focuses on volume retention post-fat grafting, employing cutting-edge methodologies to unravel the mechanisms underlying graft survival and integration. Furthermore, we leverage machine learning techniques to predict patient outcomes after plastic surgery, pioneering innovative approaches that personalize care and enhance surgical decision-making processes. Through these interconnected avenues of research, we aspire to elevate standards of care and empower patients on their reconstructive journey.
Recent Publications
Umbilical Complications following DIEP Flap Breast Reconstruction: Demonstrating the Added Benefit of Preoperative Imaging
Huang et al.
Machine-Learning Prediction of Capsular Contraction after Two-Stage Breast Reconstruction
Chen et al.
Timeline and Incidence of Postoperative Complications in Prepectoral, Dual-Plane, and Total Submuscular Alloplastic Reconstruction With and Without Biosynthetic Scaffold Usage
Chen et al.
An Evaluation of Native Breast Dimension and Tissue Expander Inflation Rate on the Risk of Capsular Contracture Development in Postmastectomy Reconstruction
Chen et al.
Comparing Autologous to Device-Based Breast Reconstruction : A Pilot Study of Return in Breast Sensation
Huang et al.
A Pilot Study Comparing Sensation in Buried Versus Nonburied Deep Inferior Epigastric Perforator Flaps
Lu Wang et al.