Faculty Bibliography

BACKGROUND:Patient-specific 3D models are being used increasingly in medicine for many applications including surgical planning, procedure rehearsal, trainee education, and patient education. To date, experiences on the use of 3D models to facilitate patient understanding of their disease and surgical plan are limited. The purpose of this study was to investigate in the context of renal and prostate cancer the impact of using 3D printed and augmented reality models for patient education. METHODS:Patients with MRI-visible prostate cancer undergoing either robotic assisted radical prostatectomy or focal ablative therapy or patients with renal masses undergoing partial nephrectomy were prospectively enrolled in this IRB approved study (n = 200). Patients underwent routine clinical imaging protocols and were randomized to receive pre-operative planning with imaging alone or imaging plus a patient-specific 3D model which was either 3D printed, visualized in AR, or viewed in 3D on a 2D computer monitor. 3D uro-oncologic models were created from the medical imaging data. A 5-point Likert scale survey was administered to patients prior to the surgical procedure to determine understanding of the cancer and treatment plan. If randomized to receive a pre-operative 3D model, the survey was completed twice, before and after viewing the 3D model. In addition, the cohort that received 3D models completed additional questions to compare usefulness of the different forms of visualization of the 3D models. Survey responses for each of the 3D model groups were compared using the Mann-Whitney and Wilcoxan rank-sum tests. RESULTS:All 200 patients completed the survey after reviewing their cases with their surgeons using imaging only. 127 patients completed the 5-point Likert scale survey regarding understanding of disease and surgical procedure twice, once with imaging and again after reviewing imaging plus a 3D model. Patients had a greater understanding using 3D printed models versus imaging for all measures including comprehension of disease, cancer size, cancer location, treatment plan, and the comfort level regarding the treatment plan (range 4.60-4.78/5 vs. 4.06-4.49/5, p < 0.05). CONCLUSIONS:All types of patient-specific 3D models were reported to be valuable for patient education. Out of the three advanced imaging methods, the 3D printed models helped patients to have the greatest understanding of their anatomy, disease, tumor characteristics, and surgical procedure.

Background/UNASSIGNED:The aim of this study was to evaluate the accuracy of three-dimensional (3D) printed liver models developed by a cost-effective approach for establishing validity of using these models in a clinical setting. Methods/UNASSIGNED:Fifteen patients undergoing laparoscopic liver resection in a single surgical department were included. Patient-specific, 1-1 scale 3D printed liver models including the liver, tumor, and vasculature were created from contrast-enhanced computed tomography (CT) images using a cost-effective approach. The 3D models were subsequently CT scanned, 3D image post-processing was performed, and these 3D computer models (MCT) were compared to the original 3D models created from the original patient images (PCT). 3D computer models of each type were co-registered using a point set registration method. 3D volume measurements of the liver and lesions were calculated and compared for each set. In addition, Hausdorff distances were calculated and surface quality was compared by generated heatmaps. Results/UNASSIGNED:in PCT. Analysis of differences between surfaces showed that the median value of mean Hausdorff distances for liver parenchyma was 1.92 mm. Bland-Altman plots revealed no significant bias in liver volume and diameters of hepatic veins and tumor location. Median errors of all measured vessel diameters were smaller than CT slice height. There was a slight trend towards undersizing anatomical structures, although those errors are most likely due to source imaging. Conclusions/UNASSIGNED:We have confirmed the accuracy of 3D printed liver models created by using the low-cost method. 3D models are useful tools for pre-operative planning and intra-operative guidance. Future research in this field should continue to move towards clinical trials for assessment of the impact of these models on pre-surgical planning decisions and perioperative outcomes.

Medical three-dimensional (3D) printing has expanded dramatically over the past three decades with growth in both facility adoption and the variety of medical applications. Consideration for each step required to create accurate 3D printed models from medical imaging data impacts patient care and management. In this paper, a writing group representing the Radiological Society of North America Special Interest Group on 3D Printing (SIG) provides recommendations that have been vetted and voted on by the SIG active membership. This body of work includes appropriate clinical use of anatomic models 3D printed for diagnostic use in the care of patients with specific medical conditions. The recommendations provide guidance for approaches and tools in medical 3D printing, from image acquisition, segmentation of the desired anatomy intended for 3D printing, creation of a 3D-printable model, and post-processing of 3D printed anatomic models for patient care.

INTRODUCTION/BACKGROUND:-weighted DCE-MRI. MATERIALS AND METHODS/METHODS:) and arterial input function (AIF). In addition, the effect of the conversion method on the diagnostic accuracy was evaluated with 36 breast lesions (19 benign and 17 malignant). RESULTS:. CONCLUSION/CONCLUSIONS:measurement is not available and a low FA is used for DCE-MRI, the uncertainty in the contrast kinetic parameter estimation can be reduced by using the LC method with pAIF, without compromising the diagnostic accuracy.

Improvements in technology and reduction in costs have led to widespread interest in three-dimensional (3D) printing. 3D-printed anatomical models contribute to personalized medicine, surgical planning, and education across medical specialties, and these models are rapidly changing the landscape of clinical practice. A physical object that can be held in one's hands allows for significant advantages over standard two-dimensional (2D) or even 3D computer-based virtual models. Radiologists have the potential to play a significant role as consultants and educators across all specialties by providing 3D-printed models that enhance clinical care. This article reviews the basics of 3D printing, including how models are created from imaging data, clinical applications of 3D printing within the abdomen and pelvis, implications for education and training, limitations, and future directions.

OBJECTIVE:To describe novel 3-dimensional (3D) printing and augmented reality (AR) methods of image data visualization to facilitate anatomic understanding and to assist with surgical planning and decision-making during robotic partial nephrectomy. MATERIALS AND METHODS/METHODS:We created a video of the workflow for creating 3D printed and AR kidney models along with their application to robotic partial nephrectomy. Key steps in their development are (1) radiology examination (magnetic resonance imaging and computed tomography), (2) image segmentation, (3) preparing for 3D printing or AR, and (4) printing the model or deploying the model to the AR device. RESULTS:We demonstrate the workflow and utility of 3D printing and AR kidney models applied to a case of a 70-year-old woman with a 3.4 cm renal mass on her left pelvic kidney. A 3D printed kidney model was created using multicolor PolyJet technology (Stratasys J750), allowing a transparent kidney with coloring of the renal tumor, artery, vein, and ureter. An AR kidney model was created using Unity 3D software and deployed to a Microsoft HoloLens. The 3D printed and AR models were used preoperatively and intraoperatively to assist in robotic partial nephrectomy. To date, we have created 15 3D printed and AR kidney models to use for robotic partial nephrectomy planning and intraoperative guidance. The application of 3D printed and AR models is safe and feasible and can influence surgical decisions. CONCLUSION/CONCLUSIONS:Our video highlights the workflow and novel application of 3D printed and AR kidney models to provide preoperative guidance for robotic partial nephrectomy. The insights gained from advanced visualization can influence surgical planning decisions.

OBJECTIVE: To determine whether patient-specific 3D printed renal tumor models change pre-operative planning decisions made by urological surgeons in preparation for complex renal mass surgical procedures. MATERIALS AND METHODS: From our ongoing IRB approved study on renal neoplasms, ten renal mass cases were retrospectively selected based on Nephrometry Score greater than 5 (range 6-10). A 3D post-contrast fat-suppressed gradient-echo T1-weighted sequence was used to generate 3D printed models. The cases were evaluated by three experienced urologic oncology surgeons in a randomized fashion using (1) imaging data on PACS alone and (2) 3D printed model in addition to the imaging data. A questionnaire regarding surgical approach and planning was administered. The presumed pre-operative approaches with and without the model were compared. Any change between the presumed approaches and the actual surgical intervention was recorded. RESULTS: There was a change in planned approach with the 3D printed model for all ten cases with the largest impact seen regarding decisions on transperitoneal or retroperitoneal approach and clamping, with changes seen in 30%-50% of cases. Mean parenchymal volume loss for the operated kidney was 21.4%. Volume losses >20% were associated with increased ischemia times and surgeons tended to report a different approach with the use of the 3D model compared to that with imaging alone in these cases. The 3D printed models helped increase confidence regarding the chosen operative procedure in all cases. CONCLUSIONS: Pre-operative physical 3D models created from MRI data may influence surgical planning for complex kidney cancer.

Rapid prototyping facilitates comprehension of complex cardiac anatomy. However, determining when this additional information proves instrumental in patient management remains a challenge. We describe our experience with patient-specific anatomic models created using rapid prototyping from various imaging modalities, suggesting their utility in surgical and interventional planning in congenital heart disease (CHD). Virtual and physical 3-dimensional (3D) models were generated from CT or MRI data, using commercially available software for patients with complex muscular ventricular septal defects (CMVSD) and double-outlet right ventricle (DORV). Six patients with complex anatomy and uncertainty of the optimal management strategy were included in this study. The models were subsequently used to guide management decisions, and the outcomes reviewed. 3D models clearly demonstrated the complex intra-cardiac anatomy in all six patients and were utilized to guide management decisions. In the three patients with CMVSD, one underwent successful endovascular device closure following a prior failed attempt at transcatheter closure, and the other two underwent successful primary surgical closure with the aid of 3D models. In all three cases of DORV, the models provided better anatomic delineation and additional information that altered or confirmed the surgical plan. Patient-specific 3D heart models show promise in accurately defining intra-cardiac anatomy in CHD, specifically CMVSD and DORV. We believe these models improve understanding of the complex anatomical spatial relationships in these defects and provide additional insight for pre/intra-interventional management and surgical planning.

In this work, we provide specific clinical examples to demonstrate basic practical techniques involved in image segmentation, computer-aided design, and 3D printing. A step-by-step approach using United States Food and Drug Administration cleared software is provided to enhance surgical intervention in a patient with a complex superior sulcus tumor. Furthermore, patient-specific device creation is demonstrated using dedicated computer-aided design software. Relevant anatomy for these tasks is obtained from CT Digital Imaging and Communications in Medicine images, leading to the generation of 3D printable files and delivery of these files to a 3D printer.