Clinical evaluation of a novel CT image reconstruction algorithm for direct dose calculations

Brent van der Heyden, Michel Ollers, André Ritter, Frank Verhaegen, Wouter van Elmpt*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Background and purpose: Computed tomography (CT) imaging is frequently used in radiation oncology to calculate radiation dose distributions. In order to calculate doses, the CT numbers must be converted into densities by an energy dependent conversion curve. A recently developed algorithm directly reconstructs
CT projection data into relative electron densities which eliminates the use of separate conversion curves for different X-ray tube potentials. Our work evaluates this algorithm for various cancer sites and shows its applicability in a clinical workflow.
Materials and methods: The Gammex phantom with tissue mimicking inserts was scanned to characterize the CT number to density conversion curves. In total, 33 patients with various cancer sites were scanned using multiple tube potentials. All CT acquisitions were reconstructed with the standard filtered back-
projection (FBP) and the new developed DirectDensityTM  (DD) algorithm. The mean tumor doses and the volume percentage that receives more than 95% of the prescribed dose were calculated for the planning target volume. Relevant parameters for the organs at risk for each tumor site were also calculated.
Results: The relative mean dose differences between the standard 120 kVp FBP CT scan workflow and the DD CT scans (80, 100, 120 and 140 kVp) were in general less than 1% for the planned target volume and organs at risk.
Conclusion: The energy independent DD algorithm allows for accurate dose calculations over a variety of body sites. This novel algorithm eliminates the tube potential specific calibration procedure and thereby simplifies the clinical radiotherapy workflow.
Original languageEnglish
Pages (from-to)11-16
Number of pages6
JournalPhysics & Imaging in Radiation Oncology
Publication statusPublished - Mar 2017

Cite this