Multi-Institutional Audit of FLASH and Conventional Dosimetry With a 3D Printed Anatomically Realistic Mouse Phantom.

PURPOSE: We conducted a multi-institutional dosimetric audit between FLASH and conventional dose rate (CONV) electron irradiations by using an anatomically realistic 3-dimensional (3D) printed mouse phantom. METHODS AND MATERIALS: A computed tomography (CT) scan of a live mouse was used to create a 3D model of bony anatomy, lungs, and soft tissue. A dual-nozzle 3D printer was used to print the mouse phantom using acrylonitrile butadiene styrene (∼1.02 g/cm3) and polylactic acid (∼1.24 g/cm3) simultaneously to simulate soft tissue and bone densities, respectively. The lungs were printed separately using lightweight polylactic acid (∼0.64 g/cm3). Hounsfield units (HU), densities, and print-to-print stability of the phantoms were assessed. Three institutions were each provided a phantom and each institution performed 2 replicates of irradiations at selected anatomic regions. The average dose difference between FLASH and CONV dose distributions and deviation from the prescribed dose were measured with radiochromic film. RESULTS: Compared with the reference CT scan, CT scans of the phantom demonstrated mass density differences of 0.10 g/cm3 for bone, 0.12 g/cm3 for lung, and 0.03 g/cm3 for soft tissue regions. Differences in HU between phantoms were <10 HU for soft tissue and bone, with lung showing the most variation (54 HU), but with minimal effect on dose distribution (<0.5%). Mean differences between FLASH and CONV decreased from the first to the second replicate (4.3%-1.2%), and differences from the prescribed dose decreased for both CONV (3.6%-2.5%) and FLASH (6.4%-2.7%). Total dose accuracy suggests consistent pulse dose and pulse number, although these were not specifically assessed. Positioning variability was observed, likely due to the absence of robust positioning aids or image guidance. CONCLUSIONS: This study marks the first dosimetric audit for FLASH using a nonhomogeneous phantom, challenging conventional calibration practices reliant on homogeneous phantoms. The comparison protocol offers a framework for credentialing multi-institutional studies in FLASH preclinical research to enhance reproducibility of biologic findings.

A clinical solution for non-toxic 3D-printed photon blocks in external beam radiation therapy.

PURPOSE: A well-known limitation of multi-leaf collimators is that they cannot easily form island blocks. This can be important in mantle region therapy. Cerrobend photon blocks, currently used for supplementary shielding, are labor-intensive and error-prone. To address this, an innovative, non-toxic, automatically manufactured photon block using 3D-printing technology is proposed, offering a patient-specific and accurate alternative. METHODS AND MATERIALS: The study investigates the development of patient-specific photon shielding blocks using 3D-printing for three different patient cases. A 3D-printed photon block shell filled with tungsten ball bearings (BBs) was designed to have similar dosimetric properties to Cerrobend standards. The generation of the blocks was automated using the Eclipse Scripting API and Python. Quality assurance was performed by comparing the expected and actual weight of the tungsten BBs used for shielding. Dosimetric and field geometry comparisons were conducted between 3D-printed and Cerrobend blocks, utilizing ionization chambers, imaging, and field geometry analysis. RESULTS: The quality assurance assessment revealed a -1.3% average difference in the mass of tungsten ball bearings for different patients. Relative dose output measurements for three patient-specific blocks in the blocked region agreed within 2% of each other. Against the Treatment Planning System (TPS), both 3D-printed and Cerrobend blocks agreed within 2%. For each patient, 6 MV image profiles taken through the 3D-printed and Cerrobend blocks agreed within 1% outside high gradient regions. Jaccard distance analysis of the MV images against the TPS planned images, found Cerrobend blocks to have 15.7% dissimilarity to the TPS, while that of the 3D-printed blocks was 6.7%. CONCLUSIONS: This study validates a novel, efficient 3D-printing method for photon block creation in clinical settings. Despite potential limitations, the benefits include reduced manual labor, automated processes, and greater precision. It holds potential for widespread adoption in radiation therapy, furthering non-toxic radiation shielding.

Tungsten Filled 3-Dimensional Printed Lung Blocks for Total Body Irradiation.

PURPOSE: Lung blocks for total-body irradiation are commonly used to reduce lung dose and prevent radiation pneumonitis. Currently, molten Cerrobend containing toxic materials, specifically lead and cadmium, is poured into molds to construct blocks. We propose a streamlined method to create 3-dimensional (3D)-printed lung block shells and fill them with tungsten ball bearings to remove lead and improve overall accuracy in the block manufacturing workflow. METHODS AND MATERIALS: 3D-printed lung block shells were automatically generated using an inhouse software, printed, and filled with 2 to 3 mm diameter tungsten ball bearings. Clinical Cerrobend blocks were compared with the physician drawn blocks as well as our proposed tungsten filled 3D-printed blocks. Physical and dosimetric comparisons were performed on a linac. Dose transmission through the Cerrobend and 3D-printed blocks were measured using point dosimetry (ion-chamber) and the on-board Electronic-Portal-Imaging-Device (EPID). Dose profiles from the EPID images were used to compute the full-width-half-maximum and to compare with the treatment-planning-system. Additionally, the coefficient-of-variation in the central 80% of full-width-half-maximum was computed and compared between Cerrobend and 3D-printed blocks. RESULTS: The geometric difference between treatment-planning-system and 3D-printed blocks was significantly lower than Cerrobend blocks (3D: -0.88 ± 2.21 mm, Cerrobend: -2.28 ± 2.40 mm, P = .0002). Dosimetrically, transmission measurements through the 3D-printed and Cerrobend blocks for both ion-chamber and EPID dosimetry were between 42% to 48%, compared with the open field. Additionally, coefficient-of-variation was significantly higher in 3D-printed blocks versus Cerrobend blocks (3D: 4.2% ± 0.6%, Cerrobend: 2.6% ± 0.7%, P < .0001). CONCLUSIONS: We designed and implemented a tungsten filled 3D-printed workflow for constructing total-body-irradiation lung blocks, which serves as an alternative to the traditional Cerrobend based workflow currently used in clinics. This workflow has the capacity of producing clinically useful lung blocks with minimal effort to facilitate the removal of toxic materials from the clinic.

Multi-Institutional Audit of FLASH and Conventional Dosimetry with a 3D-Printed Anatomically Realistic Mouse Phantom.

We conducted a multi-institutional audit of dosimetric variability between FLASH and conventional dose rate (CONV) electron irradiations by using an anatomically realistic 3D-printed mouse phantom. A CT scan of a live mouse was used to create a 3D model of bony anatomy, lungs, and soft tissue. A dual-nozzle 3D printer was used to print the mouse phantom using acrylonitrile butadiene styrene ($~1.02 g/cm^3$) and polylactic acid ($~1.24 g/cm^3$) simultaneously to simulate soft tissue and bone densities, respectively. The lungs were printed separately using lightweight polylactic acid ($~0.64 g/cm^3$). Hounsfield units (HU) and densities were compared with the reference CT scan of the live mouse. Print-to-print reproducibility of the phantom was assessed. Three institutions were each provided a phantom, and each institution performed two replicates of irradiations at selected mouse anatomic regions. The average dose difference between FLASH and CONV dose distributions and deviation from the prescribed dose were measured with radiochromic film. Compared to the reference CT scan, CT scans of the phantom demonstrated mass density differences of $0.10 g/cm^3$ for bone, $0.12 g/cm^3$ for lung, and $0.03 g/cm^3$ for soft tissue regions. Between phantoms, the difference in HU for soft tissue and bone was <10 HU from print to print. Lung exhibited the most variation (54 HU) but minimally affected dose distribution (<0.5% dose differences between phantoms). The mean difference between FLASH and CONV from the first replicate to the second decreased from 4.3% to 1.2%, and the mean difference from the prescribed dose decreased from 3.6% to 2.5% for CONV and 6.4% to 2.7% for FLASH. The framework presented here is promising for credentialing of multi-institutional studies of FLASH preclinical research to maximize the reproducibility of biological findings.

Shaping success: clinical implementation of a 3D-printed electron cutout program in external beam radiation therapy.

Purpose: The integration of 3D-printing technology into radiation therapy (RT) has allowed for a novel method to develop personalized electron field-shaping blocks with improved accuracy. By obviating the need for handling highly toxic Cerrobend molds, the clinical workflow is significantly streamlined. This study aims to expound upon the clinical workflow of 3D-printed electron cutouts in RT and furnish one year of in-vivo dosimetry data. Methods and materials: 3D-printed electron cutouts for 6x6 cm, 10x10 cm, and 15x15 cm electron applicators were designed and implemented into the clinical workflow after dosimetric commissioning to ensure congruence with the Cerrobend cutouts. The clinical workflow consisted of four parts: i) the cutout aperture was extracted from the treatment planning system (TPS). A 3D printable cutout was then generated automatically through custom scripts; ii) the cutout was 3D-printed with PLA filament, filled with tungsten ball bearings, and underwent quality assurance (QA) to verify density and dosimetry; iii) in-vivo dosimetry was performed with optically stimulated luminescence dosimeters (OSLDs) for a patient's first treatment and compared to the calculated dose in the TPS; iv) after treatment completion, the 3D-printed cutout was recycled. Results: QA and in-vivo OSLD measurements were conducted (n=40). The electron cutouts produced were 6x6 cm (n=3), 10x10 cm (n=30), and 15x15 cm (n=7). The expected weight of the cutouts differed from the measured weight by 0.4 + 1.1%. The skin dose measured with the OSLDs was compared to the skin dose in the TPS on the central axis. The difference between the measured and TPS doses was 4.0 + 5.2%. Conclusion: The successful clinical implementation of 3D-printed cutouts reduced labor, costs, and removed the use of toxic materials in the workplace while meeting clinical dosimetric standards.

An Affordable Platform for Virtual Reality-Based Patient Education in Radiation Therapy.

PURPOSE: The goal of this study was to develop and assess the effectiveness of an affordable smartphone-based virtual reality (VR) patient education platform with 360-degree videos produced depicting a first-person patient perspective during the radiation therapy (RT) care path to reduce patient anxiety. METHODS AND MATERIALS: Three disease site-specific (breast, pelvis, head and neck) VR videos were filmed using a 360-degree camera to portray the first-person perspective of a patient's standard RT appointments, including a computed tomography simulation and the first RT treatment session. Instruction is given for possible clinical implementation. Patient participation was divided into 2 groups: (1) Group A (n = 28) included patients participating before simulation and later after the first treatment, and (2) Group B (n = 33) included patients participating only while undergoing treatment. Patients viewed their disease site-specific video using an inexpensive cardboard VR viewer and their smartphone, emulating an expensive VR-headset. Surveys were administered assessing patient anxiety, comfort, satisfaction, and knowledge of RT on a 5-point Likert-type scale. RESULTS: Patients in Group A and Group B while undergoing treatment both indicated that their anxiety "decreased a little" in the survey, after watching the VR video (Group A, median on a 5-point Likert-type scale, 4 [IQR, 4-5]; Group B, 4 [IQR, 4-4]). The VR aspect of the videos was especially liked by patients while undergoing treatment, with 96.4% in Group A and 90.9% in Group B reporting that the VR aspect of the videos was helpful. All Group A participants believed that the VR videos would be beneficial to new patients. CONCLUSIONS: Our affordable VR patient education platform effectively immerses a patient in their care path from simulation through initial treatment delivery, reducing anxiety and increasing familiarity with the treatment process.

Learning image representations for content-based image retrieval of radiotherapy treatment plans.

Objective.In this work, we propose a content-based image retrieval (CBIR) method for retrieving dose distributions of previously planned patients based on anatomical similarity. Retrieved dose distributions from this method can be incorporated into automated treatment planning workflows in order to streamline the iterative planning process. As CBIR has not yet been applied to treatment planning, our work seeks to understand which current machine learning models are most viable in this context.Approach.Our proposed CBIR method trains a representation model that produces latent space embeddings of a patient's anatomical information. The latent space embeddings of new patients are then compared against those of previous patients in a database for image retrieval of dose distributions. All source code for this project is available on github.Main results.The retrieval performance of various CBIR methods is evaluated on a dataset consisting of both publicly available image sets and clinical image sets from our institution. This study compares various encoding methods, ranging from simple autoencoders to more recent Siamese networks like SimSiam, and the best performance was observed for the multitask Siamese network.Significance.Our current results demonstrate that excellent image retrieval performance can be obtained through slight changes to previously developed Siamese networks. We hope to integrate CBIR into automated planning workflow in future works.