Pseudo In Vivo Patient Dosimetry Using A 3d-Printed Patient-Specific Phantom

Purpose: To test the feasibility of using 3D-printed patient-specific phantoms for intensity-modulated radiation therapy (IMRT) quality assurance (QA). Methods: We created a patient-specific whole-head phantom using a 3D printer. The printer data file was created from high-resolution DICOM computed tomography (CT) images of 3-year old child treated at our institution for medulloblastoma. A custom-modified extruder system was used to create tissue-equivalent materials. For the printing process, the Hounsfield Units from the CT images were converted to proportional volumetric densities. A 5-field IMRT plan was created from the patient CT and delivered to the 3D- phantom. Dose was measured by an ion chamber placed through the eye. The ion chamber was placed at the posterior edge of the planning target volume in a high dose gradient region. CT scans of the patient and 3D-phantom were fused by using commercial treatment planning software (TPS). The patient’s plan was calculated on the phantom CT images. The ion chamber’s active volume was delineated in the TPS; dose per field and total dose were obtained. Measured and calculated doses were compared. Results: The 3D-phantom dimensions and tissue densities were in good agreement with the patient. However, because of a printing error, there was a large discrepancy in the density in the frontal cortex. The calculated and measured treatment plan doses were 1.74 Gy and 1.72 Gy, respectively. For individual fields, the absolute dose difference between measured and calculated values was on average 3.50%. Conclusion: This study demonstrated the feasibility of using 3D-printed patient-specific phantoms for IMRT QA. Such phantoms would be particularly advantageous for complex IMRT treatment plans featuring high dose gradients and/or for anatomical sites with high variation in tissue densities. Our preliminary findings are promising. We anticipate that, once the printing process is further refined, the agreement between measured and calculated doses will improve.