Low-dose CT allows for accurate proton therapy dose calculation and plan optimization

Quantitative use of cone-beam computed tomography in proton therapy: challenges and opportunities

The fundamental goal in radiation therapy (RT) is to simultaneously maximize tumor cell killing and healthy tissue sparing. Reducing uncertainty margins improves normal tissue sparing, but generally requires advanced techniques. Adaptive RT (ART) is a compelling technique that leverages daily imaging and anatomical information to support reduced margins and to optimize plan quality for each treatment fraction. An especially exciting avenue for ART is proton therapy (PT), which aims to combine daily plan re-optimization with the unique advantages provided by protons, including reduced integral dose and near-zero dose deposition distal to the target along the beam direction. A core component for ART is onboard image guidance, and currently two options are available on proton systems, including cone-beam computed tomography (CBCT) and CT-on-rail (CToR) imaging. While CBCT suffers from poorer image quality compared to CToR imaging, CBCT platforms can be more easily integrated with PT systems and thus may support more streamlined adaptive proton therapy (APT). In this review, we present current status of CBCT application to proton therapy dose evaluation and plan adaptation, including progress, challenges and future directions.

Dose distributions of proton therapy plans are robust against lowering the resolution of CTs combined with increasing noise

BACKGROUND

Treatment planning in radiation therapy (RT) is performed on image sets acquired with commercial x-ray computed tomography (CT) scanners. Considering an increased frequency of verification scans for adaptive RT and the advent of alternatives to x-ray CTs, there is a need to review the requirements for image sets used in RT planning.

PURPOSE

This study aims to derive the required image quality (IQ) for the computation of the dose distribution in proton therapy (PT) regarding spatial resolution and the combination of spatial resolution and noise. The knowledge gained is used to explore the potential for dose reduction in tomography-guided PT.

METHODS

Mathematical considerations indicate that the required spatial resolution for dose computation is on the scale of the set-up margins fed into the robust optimization. This hypothesis was tested by processing retrospectively 12 clinical PT cases, which reflect a variety of tumor localizations. Image sets were low-pass filtered and were made noisy in a generic manner. Dose distributions on the modified CT scans were computed with a Monte-Carlo dose engine. The similarity of these dose distributions with clinical ones was quantified with the gamma-index (1 mm/1%). The potential reduction of the x-ray exposure compared to the planning CT scan was estimated.

RESULTS

Dose distributions within the irradiated volume were robust against low-pass filtering of the CTs with kernels up to a full-width-at-half-maximum of 4 mm, that is, the gamma pass rate (1 mm/1%) was ≥ $\ge$ 98%. The limit of the filter width was 6 mm for brain tumors and 8 mm for targets in the abdomen. These pass rates remained approximately unchanged if a limited amount of noise was added to the CT image sets. The estimated potential reductions of the x-ray exposure were at least a factor of 20.

CONCLUSIONS

The requirements on IQ in terms of spatial resolution in combination with noise for computing the dose in PT are clearly lower than the IQ of current clinical planning. The results apply, for example, to ultra-low dose x-ray CTs, proton CTs with coarse spatial detection, and attenuation images from the joint reconstruction of time-of-flight PET scans.

Survey on fan-beam computed tomography for radiotherapy: Imaging for dose calculation and delineation

Background and purpose

To obtain an understanding of current practice, professional needs and future directions in the field of fan-beam CT in RT, a survey was conducted. This work presents the collected information regarding the use of CT imaging for dose calculation and structure delineation.

Materials and methods

An online institutional survey was distributed to medical physics experts employed at Belgian and Dutch radiotherapy institutions to assess the status, challenges, and future directions of QA practices for fan-beam CT. A maximum of 143 questions covered topics such as CT scanner availability, CT scanner specifications, QA protocols, treatment simulation workflow, and radiotherapy dose calculation. Answer forms were collected between 1-Sep-2022 and 10-Oct-2022.

Results

A 66 % response rate was achieved, yielding data on a total of 58 CT scanners. For MV photon therapy, all single-energy CT scans are reconstructed in Hounsfield Units for delineation or dose calculation, and a direct- or stoichiometric method was used to convert CT numbers for dose calculation. Limited use of dual-energy CT is reported for photon (N = 3) and proton dose calculations (N = 1). For brachytherapy, most institutions adopt water-based dose calculation, while approximately 26 % of the institutions take tissue heterogeneity into account. Commissioning and regular QA include eleven tasks, which are performed by two or more professions (29/31) with varying frequencies.

Conclusions

Dual usage of a planning CT limits protocol optimization for both tissue characterization and delineation. DECT has been implemented only gradually. A variation of QA testing frequencies and tests are reported.

Low-Dose Computed Tomography Scanning Protocols for Online Adaptive Proton Therapy of Head-and-Neck Cancers

PURPOSE

To evaluate the suitability of low-dose CT protocols for online plan adaptation of head-and-neck patients.

METHODS

We acquired CT scans of a head phantom with protocols corresponding to CT dose index volume CTDI_vol in the range of 4.2-165.9 mGy. The highest value corresponds to the standard protocol used for CT simulations of 10 head-and-neck patients included in the study. The minimum value corresponds to the lowest achievable tube current of the GE Discovery RT scanner used for the study. For each patient and each low-dose protocol, the noise relative to the standard protocol, derived from phantom images, was applied to a virtual CT (vCT). The vCT was obtained from a daily CBCT scan corresponding to the fraction with the largest anatomical changes. We ran an established adaptive workflow twice for each low-dose protocol using a high-quality daily vCT and the corresponding low-dose synthetic vCT. For a relative comparison of the adaptation efficacy, two adapted plans were recalculated in the high-quality vCT and evaluated with the contours obtained through deformable registration of the planning CT. We also evaluated the accuracy of dose calculation in low-dose CT volumes using the standard CT protocol as reference.

RESULTS

The maximum differences in D₉₈ between low-dose protocols and the standard protocol for the high-risk and low-risk CTV were found to be 0.6% and 0.3%, respectively. The difference in OAR sparing was up to 3%. The Dice similarity coefficient between propagated contours obtained with low-dose and standard protocols was above 0.982. The mean 2%/2 mm gamma pass rate for the lowest-dose image, using the standard protocol as reference, was found to be 99.99%.

CONCLUSION

The differences between low-dose protocols and the standard scanning protocol were marginal. Thus, low-dose CT protocols are suitable for online adaptive proton therapy of head-and-neck cancers. As such, considering scanning protocols used in our clinic, the imaging dose associated with online adaption of head-and-neck cancers treated with protons can be reduced by a factor of 40.