Development of an abdominal phantom for the validation of an oligometastatic disease diagnosis workflow.

PURPOSE: The liver is a common site for metastatic disease, which is a challenging and life-threatening condition with a grim prognosis and outcome. We propose a standardized workflow for the diagnosis of oligometastatic disease (OMD), as a gold standard workflow has not been established yet. The envisioned workflow comprises the acquisition of a multimodal image data set, novel image processing techniques, and cone beam computed tomography (CBCT)-guided biopsy for subsequent molecular subtyping. By combining morphological, molecular, and functional information about the tumor, a patient-specific treatment planning is possible. We designed and manufactured an abdominal liver phantom that we used to demonstrate multimodal image acquisition, image processing, and biopsy of the OMD diagnosis workflow. METHODS: The anthropomorphic abdominal phantom contains a rib cage, a portal vein, lungs, a liver with six lesions, and a hepatic vessel tree. This phantom incorporates three different lesion types with varying visibility under computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography CT (PET-CT), which reflects clinical reality. The phantom is puncturable and the size of the corpus and the organs is comparable to those of a real human abdomen. By using several modern additive manufacturing techniques, the manufacturing process is reproducible and allows to incorporate patient-specific anatomies. As a first step of the OMD diagnosis workflow, a preinterventional CT, MRI, and PET-CT data set of the phantom was acquired. The image information was fused using image registration and organ information was extracted via image segmentation. A CBCT-guided needle puncture experiment was performed, where all six liver lesions were punctured with coaxial biopsy needles. RESULTS: Qualitative observation of the image data and quantitative evaluation using contrast-to-noise ratio (CNR) confirms that one lesion type is visible only in MRI and not CT. The other two lesion types are visible in CT and MRI. The CBCT-guided needle placement was performed for all six lesions, including those visible only in MRI and not CBCT. This was possible by successfully merging multimodal preinterventional image data. Lungs, bones, and liver vessels serve as realistic inhibitions during needle path planning. CONCLUSIONS: We have developed a reusable abdominal phantom that has been used to validate a standardized OMD diagnosis workflow. Utilizing the phantom, we have been able to show that a multimodal imaging pipeline is advantageous for a comprehensive detection of liver lesions. In a CBCT-guided needle placement experiment we have punctured lesions that are invisible in CBCT using registered preinterventional MRI scans for needle path planning.

CT and MRI compatibility of flexible 3D-printed materials for soft actuators and robots used in image-guided interventions.

PURPOSE: Three-dimensional (3D) printing allows for the fabrication of medical devices with complex geometries, such as soft actuators and robots that can be used in image-guided interventions. This study investigates flexible and rigid 3D-printing materials in terms of their impact on multimodal medical imaging. METHODS: The generation of artifacts in clinical computer tomography (CT) and magnetic resonance (MR) imaging was evaluated for six flexible and three rigid materials, each with a cubical and a cylindrical geometry, and for one exemplary flexible fluidic actuator. Additionally, CT Hounsfield units (HU) were quantified for various parameter sets iterating peak voltage, x-ray tube current, slice thickness, and convolution kernel. RESULTS: We found the image artifacts caused by the materials to be negligible in both CT and MR images. The HU values mainly depended on the elemental composition of the materials and applied peak voltage was ranging between 80 and 140 kVp. Flexible, nonsilicone-based materials were ranged between 51 and 114 HU. The voltage dependency was less than 29 HU. Flexible, silicone-based materials were ranged between 60 and 365 HU. The voltage-dependent influence was as large as 172 HU. Rigid materials ranged between -69 and 132 HU. The voltage-dependent influence was <33 HU. CONCLUSIONS: All tested materials may be employed for devices placed in the field of view during CT and MR imaging as no significant artifacts were measured. Moreover, the material selection in CT could be based on the desired visibility of the material depending on the application. Given the wide availability of the tested materials, we expect our results to have a positive impact on the development of devices and robots for image-guided interventions.