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Clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: pediatric congenital heart disease conditions

Ryan, Justin R; Ghosh, Reena; Sturgeon, Greg; Ali, Arafat; Arribas, Elsa; Braden, Eric; Chadalavada, Seetharam; Chepelev, Leonid; Decker, Summer; Huang, Yu-Hui; Ionita, Ciprian; Lee, Joonhyuk; Liacouras, Peter; Parthasarathy, Jayanthi; Ravi, Prashanth; Sandelier, Michael; Sommer, Kelsey; Wake, Nicole; Rybicki, Frank; Ballard, David
BACKGROUND:The use of medical 3D printing (focusing on anatomical modeling) has continued to grow since the Radiological Society of North America's (RSNA) 3D Printing Special Interest Group (3DPSIG) released its initial guideline and appropriateness rating document in 2018. The 3DPSIG formed a focused writing group to provide updated appropriateness ratings for 3D printing anatomical models across a variety of congenital heart disease. Evidence-based- (where available) and expert-consensus-driven appropriateness ratings are provided for twenty-eight congenital heart lesion categories. METHODS:A structured literature search was conducted to identify all relevant articles using 3D printing technology associated with pediatric congenital heart disease indications. Each study was vetted by the authors and strength of evidence was assessed according to published appropriateness ratings. RESULTS:Evidence-based recommendations for when 3D printing is appropriate are provided for pediatric congenital heart lesions. Recommendations are provided in accordance with strength of evidence of publications corresponding to each cardiac clinical scenario combined with expert opinion from members of the 3DPSIG. CONCLUSIONS:This consensus appropriateness ratings document, created by the members of the RSNA 3DPSIG, provides a reference for clinical standards of 3D printing for pediatric congenital heart disease clinical scenarios.
PMCID:10823658
PMID: 38282094
ISSN: 2365-6271
CID: 5627742

Clinical situations for which 3D Printing is considered an appropriate representation or extension of data contained in a medical imaging examination: vascular conditions

Lee, Joonhyuk; Chadalavada, Seetharam C; Ghodadra, Anish; Ali, Arafat; Arribas, Elsa M; Chepelev, Leonid; Ionita, Ciprian N; Ravi, Prashanth; Ryan, Justin R; Santiago, Lumarie; Wake, Nicole; Sheikh, Adnan M; Rybicki, Frank J; Ballard, David H
BACKGROUND:Medical three-dimensional (3D) printing has demonstrated utility and value in anatomic models for vascular conditions. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (3DPSIG) provides appropriateness recommendations for vascular 3D printing indications. METHODS:A structured literature search was conducted to identify all relevant articles using 3D printing technology associated with vascular indications. Each study was vetted by the authors and strength of evidence was assessed according to published appropriateness ratings. RESULTS:Evidence-based recommendations for when 3D printing is appropriate are provided for the following areas: aneurysm, dissection, extremity vascular disease, other arterial diseases, acute venous thromboembolic disease, venous disorders, lymphedema, congenital vascular malformations, vascular trauma, vascular tumors, visceral vasculature for surgical planning, dialysis access, vascular research/development and modeling, and other vasculopathy. Recommendations are provided in accordance with strength of evidence of publications corresponding to each vascular condition combined with expert opinion from members of the 3DPSIG. CONCLUSION/CONCLUSIONS:This consensus appropriateness ratings document, created by the members of the 3DPSIG, provides an updated reference for clinical standards of 3D printing for the care of patients with vascular conditions.
PMCID:10688120
PMID: 38032479
ISSN: 2365-6271
CID: 5616942

Clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: neurosurgical and otolaryngologic conditions

Ali, Arafat; Morris, Jonathan M; Decker, Summer J; Huang, Yu-Hui; Wake, Nicole; Rybicki, Frank J; Ballard, David H
BACKGROUND:Medical three dimensional (3D) printing is performed for neurosurgical and otolaryngologic conditions, but without evidence-based guidance on clinical appropriateness. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (SIG) provides appropriateness recommendations for neurologic 3D printing conditions. METHODS:A structured literature search was conducted to identify all relevant articles using 3D printing technology associated with neurologic and otolaryngologic conditions. Each study was vetted by the authors and strength of evidence was assessed according to published guidelines. RESULTS:Evidence-based recommendations for when 3D printing is appropriate are provided for diseases of the calvaria and skull base, brain tumors and cerebrovascular disease. Recommendations are provided in accordance with strength of evidence of publications corresponding to each neurologic condition combined with expert opinion from members of the 3D printing SIG. CONCLUSIONS:This consensus guidance document, created by the members of the 3D printing SIG, provides a reference for clinical standards of 3D printing for neurologic conditions.
PMCID:10680204
PMID: 38008795
ISSN: 2365-6271
CID: 5617562

Impact of 3D printed models on quantitative surgical outcomes for patients undergoing robotic-assisted radical prostatectomy: a cohort study

Wake, Nicole; Rosenkrantz, Andrew B; Huang, Richard; Ginocchio, Luke A; Wysock, James S; Taneja, Samir S; Huang, William C; Chandarana, Hersh
BACKGROUND:Three-dimensional (3D) printed anatomic models can facilitate presurgical planning by providing surgeons with detailed knowledge of the exact location of pertinent anatomical structures. Although 3D printed anatomic models have been shown to be useful for pre-operative planning, few studies have demonstrated how these models can influence quantitative surgical metrics. OBJECTIVE:To prospectively assess whether patient-specific 3D printed prostate cancer models can improve quantitative surgical metrics in patients undergoing robotic-assisted radical prostatectomy (RARP). METHODS:Patients with MRI-visible prostate cancer (PI-RADS V2 ≥ 3) scheduled to undergo RARP were prospectively enrolled in our IRB approved study (n = 82). Quantitative surgical metrics included the rate of positive surgical margins (PSMs), operative times, and blood loss. A qualitative Likert scale survey to assess understanding of anatomy and confidence regarding surgical approach was also implemented. RESULTS:The rate of PSMs was lower for the 3D printed model group (8.11%) compared to that with imaging only (28.6%), p = 0.128. The 3D printed model group had a 9-min reduction in operating time (213 ± 42 min vs. 222 ± 47 min) and a 5 mL reduction in average blood loss (227 ± 148 mL vs. 232 ± 114 mL). Surgeon anatomical understanding and confidence improved after reviewing the 3D printed models (3.60 ± 0.74 to 4.20 ± 0.56, p = 0.62 and 3.86 ± 0.53 to 4.20 ± 0.56, p = 0.22). CONCLUSIONS:3D printed prostate cancer models can positively impact quantitative patient outcomes such as PSMs, operative times, and blood loss in patients undergoing RARP.
PMID: 36749368
ISSN: 2366-0058
CID: 5420812

Advanced 3D Visualization and 3D Printing in Radiology

Fidvi, Shabnam; Holder, Justin; Li, Hong; Parnes, Gregory J; Shamir, Stephanie B; Wake, Nicole
Since the discovery of X-rays in 1895, medical imaging systems have played a crucial role in medicine by permitting the visualization of internal structures and understanding the function of organ systems. Traditional imaging modalities including Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and Ultrasound (US) present fixed two-dimensional (2D) images which are difficult to conceptualize complex anatomy. Advanced volumetric medical imaging allows for three-dimensional (3D) image post-processing and image segmentation to be performed, enabling the creation of 3D volume renderings and enhanced visualization of pertinent anatomic structures in 3D. Furthermore, 3D imaging is used to generate 3D printed models and extended reality (augmented reality and virtual reality) models. A 3D image translates medical imaging information into a visual story rendering complex data and abstract ideas into an easily understood and tangible concept. Clinicians use 3D models to comprehend complex anatomical structures and to plan and guide surgical interventions more precisely. This chapter will review the volumetric radiological techniques that are commonly utilized for advanced 3D visualization. It will also provide examples of 3D printing and extended reality technology applications in radiology and describe the positive impact of advanced radiological image visualization on patient care.
PMID: 37016113
ISSN: 0065-2598
CID: 5463702

Three-Dimensional Printed Anatomic Models Derived From Magnetic Resonance Imaging Data: Current State and Image Acquisition Recommendations for Appropriate Clinical Scenarios

Talanki, Varsha R; Peng, Qi; Shamir, Stephanie B; Baete, Steven H; Duong, Timothy Q; Wake, Nicole
Three-dimensional (3D) printing technologies have been increasingly utilized in medicine over the past several years and can greatly facilitate surgical planning thereby improving patient outcomes. Although still much less utilized compared to computed tomography (CT), magnetic resonance imaging (MRI) is gaining traction in medical 3D printing. The purpose of this study was two-fold: 1) to determine the prevalence in the existing literature of using MRI to create 3D printed anatomic models for surgical planning and 2) to provide image acquisition recommendations for appropriate clinical scenarios where MRI is the most suitable imaging modality. The workflow for creating 3D printed anatomic models from medical imaging data is complex and involves image segmentation of the regions of interest and conversion of that data into 3D surface meshes, which are compatible with printing technologies. CT is most commonly used to create 3D printed anatomic models due to the high image quality and relative ease of performing image segmentation from CT data. As compared to CT datasets, 3D printing using MRI data offers advantages since it provides exquisite soft tissue contrast needed for accurate organ segmentation and it does not expose patients to unnecessary ionizing radiation. MRI, however, often requires complicated imaging techniques and time-consuming postprocessing procedures to generate high-resolution 3D anatomic models needed for 3D printing. Despite these challenges, 3D modeling and printing from MRI data holds great clinical promises thanks to emerging innovations in both advanced MRI imaging and postprocessing techniques. EVIDENCE LEVEL: 2 TECHNICAL EFFICATCY: 5.
PMID: 34046959
ISSN: 1522-2586
CID: 4888362

A workflow to generate patient-specific three-dimensional augmented reality models from medical imaging data and example applications in urologic oncology

Wake, Nicole; Rosenkrantz, Andrew B; Huang, William C; Wysock, James S; Taneja, Samir S; Sodickson, Daniel K; Chandarana, Hersh
Augmented reality (AR) and virtual reality (VR) are burgeoning technologies that have the potential to greatly enhance patient care. Visualizing patient-specific three-dimensional (3D) imaging data in these enhanced virtual environments may improve surgeons' understanding of anatomy and surgical pathology, thereby allowing for improved surgical planning, superior intra-operative guidance, and ultimately improved patient care. It is important that radiologists are familiar with these technologies, especially since the number of institutions utilizing VR and AR is increasing. This article gives an overview of AR and VR and describes the workflow required to create anatomical 3D models for use in AR using the Microsoft HoloLens device. Case examples in urologic oncology (prostate cancer and renal cancer) are provided which depict how AR has been used to guide surgery at our institution.
PMCID:8554989
PMID: 34709482
ISSN: 2365-6271
CID: 5042602

A guideline for 3D printing terminology in biomedical research utilizing ISO/ASTM standards

Alexander, Amy E; Wake, Nicole; Chepelev, Leonid; Brantner, Philipp; Ryan, Justin; Wang, Kenneth C
First patented in 1986, three-dimensional (3D) printing, also known as additive manufacturing or rapid prototyping, now encompasses a variety of distinct technology types where material is deposited, joined, or solidified layer by layer to create a physical object from a digital file. As 3D printing technologies continue to evolve, and as more manuscripts describing these technologies are published in the medical literature, it is imperative that standardized terminology for 3D printing is utilized. The purpose of this manuscript is to provide recommendations for standardized lexicons for 3D printing technologies described in the medical literature. For all 3D printing methods, standard general ISO/ASTM terms for 3D printing should be utilized. Additional, non-standard terms should be included to facilitate communication and reproducibility when the ISO/ASTM terms are insufficient in describing expository details. By aligning to these guidelines, the use of uniform terms for 3D printing and the associated technologies will lead to improved clarity and reproducibility of published work which will ultimately increase the impact of publications, facilitate quality improvement, and promote the dissemination and adoption of 3D printing in the medical community.
PMCID:7986506
PMID: 33751279
ISSN: 2365-6271
CID: 4822402

The Future of Medical 3D Printing in Radiology

Chapter by: Jakus, Adam E; Huang, Yu-Hui; Wake, Nicole
in: 3D printing for the radiologist by Wake, Nicole (Ed)
[S.l.] : Elsevier, 2021
pp. 201-214
ISBN: 032377573x
CID: 4903422

3D Printing in Interventional Radiology

Chapter by: Wattamwar, Kapil; Wake, Nicole
in: 3D printing for the radiologist by Wake, Nicole (Ed)
[S.l.] : Elsevier, 2021
pp. 131-142
ISBN: 032377573x
CID: 4903382