Design and fabrication of a personalized anthropomorphic phantom using 3D printing and tissue equivalent materials

Introduction

The goal of radiotherapy is to deliver the highest possible dose of radiation to a tumor while minimizing normal tissue toxicities (1). The dose distribution needs to be calculated with a radiation treatment planning system (TPS), and verified by quality assurance (QA) tests (2). In recent years, some researchers used three-dimensional (3D) printing technology to make phantoms for QA and dose verification. Similar ideas are used for fabricating a kidney phantom reported by Adams et al, which used agarose in phantom production (3). Ehler et al. used fused deposition printing technology to make anthropomorphic phantoms for radiation therapy dose measurements (4).

By using a PolyJet printer, Mayer et al. presented a chest phantom for detection of dose inside and outside a moving tumor and in lung tissues (5). Menikou et al. reported a 3D printed MRI compatible head phantom (6). Adams et al. further constructed soft phantoms using a novel technique that combined 3D wax printing and polymer molding. Similar method was also found in the studies on bone and lung tissues, MR images, and small animal experiments (7-11). Despite these advanced technologies, these previously reported methods are complicated and hard to be practically adopted for clinical use. In addition, the tissue-equivalency of previously used materials has not been proved in terms of radiation attenuation. The clinical applications of various anthropomorphic phantoms include equipment calibration, QA, dose verification, teaching, surgical guidance, etc. (12-15). For these purposes, they should be designed with similar human anatomy and attenuation characteristics (16). However, the tissue equivalent materials are not readily available for 3D printing (17,18).

We herein proposed a formula that can produce adequate tissue-equivalency in terms of radiological attenuation and dose deposition. We also fabricated a chest phantom via 3D printing technique, and filled with the proposed materials to simulate soft tissue and fat. The purpose of our study is to create an anthropomorphic chest phantom with similar human anatomy and radiation attenuation properties of individual patient.

Materials and methods

3D phantom design

An anonymized chest CT was obtained from the Department of Radiology, Hubei Cancer Hospital using the Brilliance CT scanner (Philips, Netherlands, 256-slice spiral CT, pitch value 0.27). The scanning parameters are as follows: tube voltage 120 kVp, current 260 mAs, slice thickness 0.5 mm, a total of 596 2D axial slices. The DICOM (Digital Imaging and Communications in Medicine) images were imported into Mimics Research 17.0 image analysis software (Materialize, Belgium). The chest phantom was divided into ribs, scapula, sternal angle, fat tissue, muscle tissue, lung tissue and lesion. Based on the image, each part of the bones and tissues were segmented and 3D reconstructed.

The models were created from the CT images in the Magic 10.0 software (Materialize, Belgium). The 3D models of fat tissue shell, lung tissue shell, ribs, scapula, and sternum were transformed to Magic 10.0 software and processed with solid generation and noise reduction, as shown in Figure 1.

Figure 1 The regions of interest in patient CT data were processed by Mimics Research 17.0 (deep purple part represents lesions). (A) Coronal section; (B) transverse section; (C) sagittal plane; (D) 3D reconstruction; (E) the shell model of the muscle tissue opened up, the lung tissue shell model opened downward, and the rib model wrapped around the lung tissue model; (F) the shell model of muscle tissue (opening upwards); (G) the ribs and chest bone model; (H) the lung tissue shell model (opening downward); (I) the scapula model.

3D printing models and materials

The segmented mesh files for the chest shell (mentioned in section “3D phantom design”) were converted into the Standard Tessellation Language (STL) format for 3D printing. The material used in printing the fat and chest wall shell is acrylonitrile butadiene styrene (ABS). The radiation equivalent material of ribs, sternum angle and scapula was made with modified resin polymer material (8). The printed phantom shell is shown in Figure 2.

Figure 2 3D printed phantom shell. (A) Ribs, scapula, sternum angle, fat and lung tissue shells. (B) The phantom with fat tissue equivalent material.

Selection of radiation equivalent materials

Various equivalent materials and blending ratios were selected via CT equivalent test (19,20). These materials were further tested and modified in our study to improve tissue equivalency for four tissue/organs, including fat, muscle, tumor lesion, and lung.

Figure 3 shows the comparison of unmodified and modified materials for all four tissue types. For fat tissue, the molted M3 wax was selected as the solvent, while CaCO₃ and MgO were used as solutes. For muscle tissue, water was chosen as the solvent, with agarose, NaCl, and pearl powder as solutes. For tumor lesions, water was used as solvent, with agarose, NaCl, and pearl powder as solute. For lung tissue, the foamed silica gel was made up of silica gel and curing agent by 1:1. Then, the silica gel was injected directly into the lung tissue shell. As shown in Table 1, the modified materials were in close approximation to human tissues in terms of CT numbers.

Figure 3 CT images of the unmodified materials (left column) and improved materials (right column). (A) Agarose, (B) wax and (C) printed materials.

Table 1 Comparison of unmodified materials and improved materials in CT numbers
Full table

End-to-end testing for radiotherapy delivery

The acquired CT images of the phantom were imported into the TPS (Monaco 5.11, Elekta, Sweden). The target area was outlined and a 3D conformal radiotherapy plan with three beams was created using 6 MV X-rays, with a prescription dose of 2 Gy (3,5,21). The tumor dose was calculated in the TPS using the pencil beam convolution (PBC), collapse cone convolution (CCC) and Monte Carlo (MC) algorithms, respectively. The prescription dose was required to cover at least 95% of the planning tumor volume (PTV). The plan was delivered using a linear accelerator (Precise Treatment System™, Elekta, Sweden). The actual delivered dose to the PTV, lung, and spinal cord was measured using an ion chamber (UNIDOS E, PTW, Germany) and compared with the planned doses.

Results

Figure 4 shows the actual constructed chest phantom. The phantom also went through the CT scan (Figure 4A) with the same parameters as the patient scanning. The CT image, as shown in Figure 4B, was compared with the patient chest scan Figure 4C. A CT image fusion of the phantom and the patient’s chest is shown in Figure 5.

Figure 4 Verifying the imaging effect of chest phantom: (A) CT scanning of the phantom; (B) the CT image of the chest phantom; and (C) the CT image of the patient.

Figure 5 Image fusion of phantom and patient CT images.

The CT image of the chest phantom is comparable to the human chest in morphology. Table 2 shows comparison of CT numbers between phantom and patient images for fat tissue, muscle tissue, bone, and tumor. The differences were around 20 HU for fat, muscle and tumor, while around 55 HU on average for bone.

Table 2 Comparison of the CT number of the phantom and patient images
Full table

The dose comparison between calculated and measured methods is shown in Table 3. The ion-chamber measured doses were 213.7 cGy in tumor, 53.85 cGy in normal lung tissue, and 4.1 cGy in spinal cord. Meanwhile the calculated doses obtained by different algorithms were also shown. For the tumor, lung, and spinal cord, PBC reported 215.1, 52.5, and 1.9 cGy; CCC reported 214.6, 54.4, and 4.4 cGy; and MC reported 214.1, 55.2, and 4.5 cGy, respectively. The differences between measured and calculated dose were <1% for tumor, 1–2.5% for lung, and 7–9% for the spinal cord for both CCC and MC. The PBC algorithm is known to be in-accurate in dose calculation especially for lung region, thus showed higher discrepancies.

Table 3 Comparison of the measured dose and calculated dose with TPS algorithms
Full table

Discussion

With the development of 3D printing technology, phantoms can be manufactured in a simple and fast manner. In our experiments, a regular 3D printer can satisfy the 3D printing requirement for radiotherapy clinical use in printing personalized phantoms. Following the same method, other anatomical phantoms can be designed and fabricated, i.e., pelvis, breast, head, etc. Our end-to-end test in dose verification using the present phantom shows an immediate clinical use for individualized dose verification, especially for those complex plans requiring high precision. Through the phantom verification, we showed that both MC and CCC algorithms overestimated the dose in tumor, normal lung and spinal cord. The PBC overestimated the dose of tumor and underestimated the doses of normal lung tissues and spinal cord.

The fused deposition printing technology used in previous studies by Ehler et al. (4) and Bache et al. (11) may produce deformation during the production process. With that in consideration, we used photo-sensitive printers for our phantoms. Compared to the study by Mayer et al. (5), the CT numbers of our phantom is closer to actual human tissues. With the adjustable CT numbers of currently used phantom materials, our future research will be producing various anatomical phantoms with tissue equivalency, such as liver phantom, kidney phantom, etc. Because of the simplicity of 3D printing phantoms, laboratory production is achieved without the need of complex industrial customization.

There are some limitations in our presented method. First, the 3D printer specifications restrict the size of a printable phantom. For larger size body regions (e.g., phantom), the phantom must be divided into several sections, before being printed and glued into a complete one. Second, the dissolution of the equivalent tissue materials requires evaluation and validation. The concentration of the solution affects uniformity and radiation attenuation property of the phantom. Third, the 3D printed phantom shell affects image quality and phantom stability. The 3D printing material of the shell is fragile, so it is necessary to accurately estimate the shell thickness according to the manufacturing method and experimental requirements. Although the production of such phantom is simple and convenient, further exploration and improvement are needed for large-scale clinical applications.

Conclusions

This study introduced a method of fabricating a lung phantom with anatomically accurate and X-ray attenuation equivalency to human tissues. The 3D printed thoracic phantom can be used for radiotherapy QA and dose verification.

Acknowledgements

Funding: This study is funded by National Key Research and Development Project (2016YFC0103400), and by the Shandong Province Key Research and Development Program (2017GSF218075). Jianfeng Qiu is supported by the Taishan Scholars Program of Shandong Province (TS201712065).

Footnote

Conflicts of Interest: The authors have no conflicts of interest to declare.

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