Dosimetric study on learning-based cone-beam CT correction in adaptive radiation therapy.

Area of Science:

• Medical Physics
• Radiotherapy Technology
• Image Processing

Background:

• Cone-beam CT (CBCT) image quality is crucial for quantitative analysis in adaptive radiation therapy.
• Artifacts in CBCT limit its use to patient setup verification, hindering quantitative analysis.
• A novel learning-based method has been developed to enhance CBCT image quality to levels comparable to planning CTs (pCTs).

Purpose of the Study:

• To investigate the dosimetric accuracy of a corrected CBCT (CCBCT) method for brain stereotactic radiosurgery (SRS) and pelvic radiotherapy.
• To evaluate the impact of CBCT image quality improvement on dose calculations in radiotherapy planning.

Main Methods:

• Retrospective analysis of 32 treatment plans from 22 patients with both pCTs and CBCTs.
• Generation of CCBCT-based and OCBCT-based treatment plans, with pCT-based plans as ground truth.
• Comparison of dose volume histogram (DVH) metrics and gamma analysis between pCT, OCBCT, and CCBCT plans.

Main Results:

• CCBCTs exhibited improved image contrast and more accurate Hounsfield Unit (HU) ranges than original CBCTs (OCBCTs).
• For pelvic radiotherapy, mean dose error in DVH metrics for PTV, bladder, and rectum decreased from 1% to 0.3% after CBCT correction.
• Gamma analysis pass rates improved from 94.5% (OCBCT) to 99.0% (CCBCT), indicating enhanced dose distribution accuracy.

Conclusions:

• The corrected CBCT (CCBCT) method achieves dose accuracy comparable to pCTs for brain and prostate radiotherapy planning.
• The proposed CBCT correction technique is valuable for improving CBCT-guided adaptive radiotherapy.
• Enhanced CBCT image quality facilitates more reliable quantitative analysis and dose calculations in radiotherapy.