SU‐E‐J‐95: Increasing Soft Tissue Contrast by Combining New CT Technologies and Imaging Dose for Radiation Treatment Planning and Delivery Guidance

Abstract

Purpose: CT dose is normally minimized based on ALARA principle. For radiation therapy (RT), a slightly increased CT dose in exchange for improved soft‐tissue contrast may be justified. In this work, we investigate the impact of CT imaging dose and other acquisition and reconstruction parameters on CT quality for RT planning and delivery guidance. Methods: CT data of various phantoms were acquired using a CT‐on‐rails (Somaton Definition AS Open, Siemens) with a series of acquisition parameters, such as tube voltage and current, rotation time, pitch, imaging dose control methods, and reconstruction algorithms, and were analyzed based on contrast‐to‐noise ratio (CNR) and dose‐weighted CNR (CNRD) to identify image quality enhancement protocols (IQEP). The IQEPs were then used to acquire CT during daily IGRT for selected patients with head and neck, prostate, and pancreas cancers. The impact of the improved CT images on RT was assessed with (1) accuracy and reproducibility of auto‐segmentation using ABAS (Elekta) and (2) intra‐and inter‐variability of manual contouring of the relevant organs by 10 observers. Results: As expected, the CNR generally increases with mAs from phantom CT data, while CNRD experiences a slow increase with mAs or reaches a plateau and then drops above certain mAs depending phantom size and relative electron density or contrast level. There is complicated interplay between kVp and mAs, particularly with regards to perception. Visual inspection of the patient CTs obtained with IQEPs showed clearer organ boundaries as compared to those from the standard CT protocols. This improvement was supported by the reduced intra‐and inter‐variability of manual contouring. The CT doses with IQEPs were 2–3 times higher than those from the standard protocols. Conclusion: CT quality can be improved by optimizing parameters in CT protocols for modern scanners, leading to improved accuracy of organ delineation for RT planning and delivery.