Faculty Bibliography

Three-dimensional (3D) printing, augmented reality (AR), and virtual reality (VR) technologies have an increasing presence in the management of prostate and kidney cancer.  To assess the utility of 3D printing, AR, and VR for 1) quantitative outcomes, 2) surgical planning, 3) intra-operative guidance, 4) training and simulation, and 5) patient education for patients with kidney and prostate cancer a systematic literature review was performed. Existing evidence demonstrates improvement in clinical outcomes, surgical planning and intra-operative guidance, as well as training. Future studies are needed to assess the impact of 3D technologies on long term patient related outcomes.

BACKGROUND:Medical 3D printing has demonstrated value in anatomic models for abdominal, hepatobiliary, and gastrointestinal conditions. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (SIG) provides appropriateness criteria for abdominal, hepatobiliary, and gastrointestinal 3D printing indications. METHODS:A literature search was conducted to identify all relevant articles using 3D printing technology associated with a number of abdominal pathologic processes. Each included study was graded according to published guidelines. RESULTS:Evidence-based appropriateness guidelines are provided for the following areas: intra-hepatic masses, hilar cholangiocarcinoma, biliary stenosis, biliary stones, gallbladder pathology, pancreatic cancer, pancreatitis, splenic disease, gastric pathology, small bowel pathology, colorectal cancer, perianal fistula, visceral trauma, hernia, abdominal sarcoma, abdominal wall masses, and intra-abdominal fluid collections. CONCLUSION/CONCLUSIONS:This document provides initial appropriate use criteria for medical 3D printing in abdominal, hepatobiliary, and gastrointestinal conditions.

Editor's Note.-Articles in the RadioGraphics Update section provide current knowledge to supplement or update information found in full-length articles previously published in RadioGraphics. Authors of the previously published article provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes. Articles in this section are published solely online and are linked to the original article.

BACKGROUND:Breast cancer is the most commonly diagnosed malignancy in females and frequently requires core needle biopsy (CNB) to guide management. Adequate training resources for CNB suffer tremendous limitations in reusability, accurate simulation of breast tissue, and cost. The relatively recent advent of 3D printing offers an alternative for the development of breast phantoms for training purposes. However, the feasibility of this technology for the purpose of ultrasound (US) guided breast intervention has not been thoroughly studied. METHODS:We designed three breast phantom models that were printed in multiple resins available through Stratasys, including VeroClear, TangoPlus and Tissue Matrix. We also constructed several traditional breast phantoms using chicken breast and Knox gelatin for comparison. These phantoms were compared side-by-side for ultrasound penetrance, simulation of breast tissue integrity, anatomic accuracy, reusability, and cost. RESULTS:3D printed breast phantoms were more anatomically accurate models than traditional breast phantoms. The chicken breast phantom provided acceptable US beam penetration and material hardness for simulation of human breast tissue integrity. Sonographic image quality of the chicken breast phantom was the most accurate overall. The gelatin-based phantom also had acceptable US beam penetration and image quality; however, this material was too soft and poorly simulated breast tissue integrity. 3D printed phantoms were not visible under US. CONCLUSIONS:There is a large unmet need for a printable material that is truly compatible with multimodality imaging for breast and other soft tissue intervention. Further research is warranted to create a realistic, reusable and affordable material to 3D print phantoms for US-guided intervention training.

Advanced visualization of medical image data in the form of three-dimensional (3D) printing continues to expand in clinical settings and many hospitals have started to adapt 3D technologies to aid in patient care. It is imperative that radiologists and other medical professionals understand the multi-step process of converting medical imaging data to digital files. To educate health care professionals about the steps required to prepare DICOM data for 3D printing anatomical models, hands-on courses have been delivered at the Radiological Society of North America (RSNA) annual meeting since 2014. In this paper, a supplement to the RSNA 2018 hands-on 3D printing course, we review methods to create cranio-maxillofacial (CMF), orthopedic, and renal cancer models which can be 3D printed or visualized in augmented reality (AR) or virtual reality (VR).

Face transplantation has evolved into a viable reconstructive option for patients with extensive facial disfigurement. Because the first face transplant procedure was described in 2005, the safety and feasibility of the procedure have been validated, and the focus of the field has shifted toward refining functional and esthetic outcomes. Recovery of muscle function following facial transplantation is critical to achieving optimal facial function and restoring facial expression. Assessment of facial muscle function in face transplant recipients has traditionally relied on clinical evaluation. In this study, we describe longitudinal changes in facial muscle volumes captured through quantitative magnetic resonance imaging in a face transplant recipient and compare these findings with functional outcomes evaluated through clinical assessment.

OBJECTIVE:To quantify how surgeons translate two-dimensional (2D) CT or MRI data to a three-dimensional (3D) model and evaluate if 3D printed models improve tumor localization. MATERIALS AND METHODS/METHODS:Twenty patients with renal masses were randomly selected from our IRB approved prospective 3D modeling study. Three surgeons reviewed the clinically available CT or MRI data; and using computer-aided design (CAD) software, translated the renal tumor to the position on the kidney that corresponded with the image interpretation. The renal tumor location determined by each surgeon was compared to the true renal mass location determined by the segmented imaging data and the Dice Similarity Coefficient (DSC) was calculated to evaluate the spatial overlap accuracy. The exercise was repeated for a subset of patients with a 3D printed model. RESULTS:The mean DSC was 0.243 ± 0.236 for the entire cohort (n=60). There was no overlap between the actual renal tumor and renal tumor identified by the surgeons in 16/60 cases (26.67%). Seven cases were reviewed again by two surgeons in a different setting with a 3D printed renal cancer model. For these cases, the DSC improved from 0.277 ± 0.248 using imaging only to 0.796 ± 0.090 with the 3D printed model (p < 0.01). CONCLUSIONS:In this study, cognitive renal tumor localization based on CT and MRI data was poor. This study demonstrates that experienced surgeons cannot always translate 2D imaging studies into 3D. Furthermore, 3D printed models can improve tumor localization and potentially assist with appropriate surgical approach.