4D Dynamic Contrast Enhanced Breast-CT: System Optimization and Quantitative Validation
Aim and outline of the thesis:
This thesis addresses the challenges of optimizing and validating 4D DCE-bCT to help bring the concept into practical application. Its primary goals are to improve imaging performance, optimize reconstruction parameters, and evaluate the modality’s quantitative accuracy.
The technical chapters detail the contributions made in this field. Chapter 2 focuses on developing a deep learning-based scatter correction method for bCT. Using Monte Carlo-simulated patient-based phantom data, the model estimates and corrects scatter in projection images, with validation on internal and external datasets demonstrating its effectiveness.
Chapter 3 compares first- and second-generation bCT systems, evaluating imaging quality and dose efficiency to highlight advancements and key differences.
Chapter 4 addresses spectral optimization and second-generation system characterization. A parallel-cascaded model is developed to optimize parameters. such as tube voltage and x-ray filtration to enhance iodine signal detection. Experimental validation demonstrates the model’s ability to optimize projection data quality, which is crucial for accurate reconstruction.
Expanding on the findings of the previous chapter, Chapter 5 focuses on optimizing reconstruction parameters for 4D DCE-bCT to achieve high spatio-temporal resolution during dynamic contrast-enhanced scans while maintaining a reasonable radiation dose. The reconstruction method employed in this work is derived from another PhD thesis in our lab, titled Reconstruction for four-dimensional dynamic contrast-enhanced dedicated breast computed tomography (4D DCE-bCT). These refinements significantly enhance the modality’s ability to detect subtle changes in contrast uptake, improving its diagnostic potential.
In Chapter 6, quantitative accuracy is evaluated through phantom-based experiments using a custom-designed breast phantom with controlled iodine
perfusion. These experiments validate the system’s accuracy in measuring iodine concentrations during wash-in and wash-out phases, with the aim of ensuring the reliability of reconstructed data for clinical use. The thesis concludes with a General Discussion of the findings, their relevance, and recommendations for future research.