Clinical benefit of range uncertainty reduction in proton treatment planning based on dual-energy CT for neuro-oncological patients

First clinical experience following the consensus guide for calibrating a proton stopping power ratio curve in a new proton centre

BACKGROUND AND PURPOSE

This work introduces the first assessment of CT calibration following the ESTRO's consensus guidelines and validating the HLUT through the irradiation of biological material.

METHODS

Two electron density phantoms were scanned with two CT scanners using two CT scan energies. The stopping power ratio (SPR) and mass density (MD) HLUTs for different CT scan energies were derived using Schneider's and ESTRO's methods. The comparison metric in this work is based on the Water-Equivalent Thickness (WET) difference between the treatment planning system and biological irradiation measurement. The SPR HLUTs were compared between the two calibration methods. To assess the accuracy of using MD HLUT for dose calculation in the treatment planning system, MD vs SPR HLUT was compared. Lastly, the feasibility of using a single SPR HLUT to replace two different energy CT scans was explored.

RESULTS

The results show a WET difference of less than 3.5% except for the result in the Bone region between Schneider's and ESTRO's methods. Comparing MD and SPR HLUT, the results from MD HLUT show less than a 3.5% difference except for the Bone region. However, the SPR HLUT shows a lower mean absolute percentage difference as compared to MD HLUT between the measured and calculated WET difference. Lastly, it is possible to use a single SPR HLUT for two different CT scan energies since both WET differences are within 3.5%.

CONCLUSION

This is the first report on calibrating an HLUT following the ESTRO's guidelines. While our result shows incremental improvement in range uncertainty using the ESTRO's guideline, the prescriptional approach of the guideline does promote harmonization of CT calibration protocols between different centres.

Prediction of proton stopping power ratios using dual-energy CT basis material decomposition

BACKGROUND

Proton radiotherapy treatment plans are currently restricted by the range uncertainties originating from the stopping power ratio (SPR) prediction based on single-energy computed tomography (SECT). Various studies have shown that multi-energy CT (MECT) can reduce the range uncertainties due to medical implant materials and age-related variations in tissue composition. None of these has directly applied the basis material density (MD) images produced by projection-based MECT systems for SPR prediction.

PURPOSE

To present and evaluate a novel proton SPR prediction method based on MD images from dual-energy CT (DECT), which could reduce the range uncertainties currently associated with proton radiotherapy.

METHODS

A theoretical basis material decomposition into water and iodine material densities was performed for various pediatric and adult human reference tissues, as well as other non-tissue materials, by minimizing the root-mean-square relative attenuation error in the energy interval from 40 to 140 keV. A model (here called MD-SPR) mapping predicted MDs to theoretically calculated reference SPRs was created with locally weighted scatterplot smoothing (LOWESS) data-fitting. The goodness of fit of the MD-SPR model was evaluated for the included reference tissues. MD images of two electron density phantoms, combined to form a head- and an abdomen-sized phantom setup, were acquired with a clinical projection-based fast-kV switching DECT scanner. The MD images were compared to the theoretically predicted MDs of the tissue surrogates and other non-tissue materials in the phantoms, as well as used for input to the MD-SPR model for generation of SPR images. The SPR images were subsequently compared to theoretical reference SPRs of the materials in the phantoms, as well as to SPR images from a commercial algorithm (DirectSPR, Siemens Healthineers, Forchheim, Germany) using image-based consecutive scan DECT for the same phantom setups.

RESULTS

The predicted SPRs of the tissue surrogates were similar for MD-SPR and DirectSPR, where the adipose and bone tissue surrogates were within 1% difference to the reference SPRs, while other non-adipose soft tissue surrogates (breast, brain, liver, muscle) were all underestimated by between -0.7% and -1.8%. The SPRs of the non-tissue materials (polymethyl methacrylate (PMMA), polyether ether ketone (PEEK), graphite and Teflon) were within 2.8% for MD-SPR images, compared to 6.8% for DirectSPR.

CONCLUSIONS

The MD-SPR model performed similar compared to other published methods for the human reference tissues. The SPR prediction for tissue surrogates was similar to DirectSPR and showed potential to improve SPR prediction for non-tissue materials.

Virtual unenhanced dual-energy computed tomography for photon radiotherapy: The effect on dose distribution and cone-beam computed tomography based position verification

Background and Purpose

Virtual Unenhanced images (VUE) from contrast-enhanced dual-energy computed tomography (DECT) eliminate manual suppression of contrast-enhanced structures (CES) or pre-contrast scans. CT intensity decreases in high-density structures outside the CES following VUE algorithm application. This study assesses VUE's impact on the radiotherapy workflow of gynecological tumors, comparing dose distribution and cone-beam CT-based (CBCT) position verification to contrast-enhanced CT (CECT) images.

Materials and Methods

A total of 14 gynecological patients with contrast-enhanced CT simulation were included. Two CT images were reconstructed: CECT and VUE. Volumetric Modulated Arc Therapy (VMAT) plans generated on CECT were recalculated on VUE using both the CECT lookup table (LUT) and a dedicated VUE LUT. Gamma analysis assessed 3D dose distributions. CECT and VUE images were retrospectively registered to daily CBCT using Chamfer matching algorithm..

Results

Planning target volume (PTV) dose agreement with CECT was within 0.35% for D2%, Dmean, and D98%. Organs at risk (OARs) D2% agreed within 0.36%. A dedicated VUE LUT lead to smaller dose differences, achieving a 100% gamma pass rate for all subjects. VUE imaging showed similar translations and rotations to CECT, with significant but minor translation differences (<0.02 cm). VUE-based registration outperformed CECT. In 24% of CBCT-CECT registrations, inadequate registration was observed due to contrast-related issues, while corresponding VUE images achieved clinically acceptable registrations.

Conclusions

VUE imaging in the radiotherapy workflow is feasible, showing comparable dose distributions and improved CBCT registration results compared to CECT. VUE enables automated bone registration, limiting inter-observer variation in the Image-Guided Radiation Therapy (IGRT) process.