Author: Yanle Hu, Shuai Leng, Cynthia H. McCollough, Maryam Sadeghian, Joe Swicklik 👨🔬
Affiliation: Mayo Clinic Arizona, Mayo Clinic 🌍
Purpose: The dependence of CT number on position in the field-of-view (FOV) imposes challenges in radiotherapy treatment planning. This study aims to decrease this dependence using photon counting detector (PCD) CT.
Methods: A multi-energy CT phantom (Gammex) with a size of 40x30 cm² was used. Cortical bone (𝜌e≈1.78), liver (𝜌e≈1.05), general adipose (𝜌e≈0.94), and LN-300 lung (𝜌e≈0.28) insert were placed in the phantom and scanned on a PCD-CT (NAEOTOM Alpha) using the routine abdominal protocol. Standard mode (144x0.4 mm collimation) and 120 kV were used. Scans were repeated with each insert rotated among the 7 locations: iso-center and six peripheral positions. Both single-energy (SE) images and virtual-monoenergetic-images (VMIs) were generated (40 to 190 keV) using a quantitative kernel (Qr40) and 3-mm thickness. CT numbers were measured in circular regions of interest (ROIs) over the inserts. The mean, standard deviation (std), coefficient of variation (CV), maximum-minimum, and difference between central and mean peripheral regions were calculated and compared.
Results: The variations of CT number within the FOV were different for different tissue types. Cortical bone showed the highest std and maximum-minimum differences. For VMIs at different energies, 80keV VMIs had the lowest variation, with std of 1.21, 1.45, 0.87, and 0.97 for cortical bone, liver, adipose, and lung, respectively. The CV for all inserts was <2.5%, and Maximum-to-Minimum differences and central-to-peripheral differences were <5 HU and 3 HU, respectively. Comparing SE and VMIs, the most noticeable difference was observed in cortical bone, with 80 keV VMIs reducing the variation by 88.87% compared to SE. The difference was much smaller for soft tissues.
Conclusion: PCD-CT VMIs at 80 keV showed the lowest variability in CT numbers (CV<2.5%), a substantial reduction compared to SE images. This could potentially improve planning accuracy and workflow by reducing the number of scans.