Purpose: A joint-statistical image reconstruction method built on a basis-vector model (JSIR-BVM) for dual-energy CT (DECT) has previously been shown to accurately map stopping-power ratios (SPRs) with subpercentage range uncertainty levels for proton-therapy planning. However, the clinical impact of such highly accurate SPR images has not yet been studied. This study reports the benefits of our JSIR-BVM SPR maps compared to the standard stoichiometric single-energy CT (SECT) method for different treatment planning scenarios.
Methods: Electron-density, mean excitation-energy and SPR maps were reconstructed with our well-established JSIR-BVM method in three head-and-neck patients scanned at 90 and 140 kVp. Clinical plans created on 120kVp SECT scan with corresponding stoichiometric CT calibration were recalculated on the reconstructed DECT datasets. The resulting SECT and DECT dose distributions were compared in terms of dose-volume histograms (DVHs) in the clinical target volume (CTV), planning target volume (PTV), and organs at risk (OARs). Dose coverage in the CTV and maximum dose within serial OARs were reported and the clinical impact of the dose distribution difference was evaluated.
Results: In 2 of the 3 cases, no recalculated DVH metric differed by more than 0.37%. However, in the third case with the brainstem overlapping the CTV, when recalculating on the DECT SPR map, the mean dose to the CTV and the maximum dose in the brainstem increased from 54 Gy to 56 Gy and 55.1 Gy to 57.7 Gy, respectively, indicating a non-trivial risk in treatment toxicity associated with inaccurate prediction of proton beam range.
Conclusion: A methodology for evaluating the clinical impact of highly accurate DECT SPR maps has been developed. In one of the three evaluated patient cases, the differences between SECT and DECT dose distributions were judged to be clinically meaningful.
Dual-energy Imaging, Stopping Power, Treatment Planning
TH- External Beam- Particle/high LET therapy: Dual energy/spectral CT-based stopping power mapping