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Designing Customized 3D Printed Models for Surgical Planning in Repair of Congenital Heart Defects

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Designing Customized 3D Printed Models for Surgical Planning in Repair of Congenital Heart Defects Designing Customized 3D Printed Models for Surgical Planning in Repair of Congenital Heart Defects by Sarah Alicia Chen A thesis submitted to Johns Hopkins University in conformity with the requirements for the degree of Master of Arts Baltimore, Maryland March, 2017 © 2017 Sarah Alicia Chen All Rights Reserved ABSTRACT Congenital heart defects (CHD) present with a wide variety of structural anomalies that range in severity, creating a need for personalized, precision treatment. Recent advances in diagnostic imaging DQG'SULQWLQJWHFKQRORJ\KDYHHQDEOHGWKHFUHDWLRQRISDWLHQWVSHFLÀFPRGHOVZKLFKKDYH revolutionized the understanding and management of these conditions. The objective of this research was to explore each step of generating such prints, and to establish a QRYHOZRUNÁRZIRUFUHDWLQJ&+'PRGHOV7KHUHVHDUFKIRFXVHGVSHFLÀFDOO\RQFUHDWLQJDRUWLFDUFK models optimized for surgical planning for patients with hypoplastic left heart syndrome (HLHS), a CHD in which the left heart and aorta are severely underdeveloped. Like most CHDs, there is substantial variability in HLHS anatomy, and the 3D shape of the aortic arch after reconstruction is critical in determining proper cardiac output, justifying a need to create customized 3D prints for improved surgical outcome. While several software options exist for segmentation, this project concentrated on evaluating the following six to segment anatomy: Mimics, inPrint, OsiriX MD, Vitrea, D2P, and 3D Slicer. Meshmixer and 3-matic were used to manipulate the data exported from the segmentation software, to create life-sized models of pre-operative anatomy, an approximation of desired post-operative anatomy, and a customized homograft patch for aortic arch reconstruction. The models were printed on a Stratasys &RQQH[2EMHFWSULQWHUXVLQJ7DQJR3OXVÁH[LEOHPDWHULDOWRDOORZVXUJLFDOVXWXULQJ Although some models were segmented from CT acquired data, emphasis was placed on establishing methods for utilizing 3D ultrasound derived data. This alternative provides a safe, cost-effective, and accessible imaging modality without harmful radiation, contrast, or anesthesia in vulnerable pediatric patients. Additional proof of concept models were derived from 3D fetal cardiac ultrasound data, since WKHÀUVWVWDJHRSHUDWLRQIRU+/+6³DVZHOODVRWKHUFRPSOH[&+'V³PXVWRIWHQEHSHUIRUPHGGD\V after birth. Customized 3D printed models have the potential to improve treatment planning, reduce SURFHGXUHWLPHDQGLPSURYHSDWLHQWRXWFRPHV7KH:RUNÁRZSURSRVHGLQWKLVSURMHFWIDFLOLWDWHVD safer and more effective method for producing 3D printed models of a pediatric heart. Author: Sarah A. Chen ii CHAIRPERSONS OF THE SUPERVISORY COMMITTEE Preceptor: Narutoshi Hibino, M.D., Ph.D. Assistant Professor of Cardiac Surgery, Johns Hopkins Hospital Faculty Advisor: Juan R. García, M.A., C.C.A. Associate Professor of the Department of Art as Applied to Medicine, Johns Hopkins University School of Medicine iii ACKNOWLEDGEMENTS I would like to thank Dr. Narutoshi Hibino, for serving as my preceptor and instigating the very inquiry that fueled this wonderful exploration. His extensive surgical expertise, valuable feedback, and enthusiasm were integral to the advancement of this project, and I am grateful for the time he took to meticulously evaluate my 3D printed models. Thanks to Juan García, my faculty advisor, for his unwavering support and guidance, and for being an advocate of my success and encouraging me to push the boundaries to come up with creative solutions. I greatly appreciate his 3D printing expertise and proactive networking efforts, which allowed me to sample a range of cutting edge technology. In the true collaborative spirit of medical illustration, I would also like to extend my heartfelt appreciation to a multitude of people from a number of departments, without whom this project would not have been possible. From pediatric cardiology, thank you to Dr. Priya Sekar for helping me access echocardiography data. Special thanks goes to Cathy Evans, who kindly spent many hours with me in the echo lab and helped me make sense of ultrasound imaging. Thanks to Dr. Philip Spevak and Dr. Luca Vricella for their uplifting words, and Diane Alejo for helping me with IRB logistics. From radiology, thank you to Dr. Nagina Malguria for helping me access cardiac CT datasets, and more importantly, helping me to decipher them. Thanks also to Dr. Stefan Zimmerman for responding to my inquiries. From maternal fetal medicine, thank you to Dr. Jena Miller and Cici McShane, for helping me acquire 3D fetal ultrasound data, and sharing an interest in medical 3D printing. Thank you also to all of the representatives who generously allowed me to use proprietary 3D segmentation software, some of which were still in the beta phases. Many thanks to Maureen Schickel and Todd Pietila from Materialise, for their long continued support and invaluable expertise. Thanks also to Ilan Shacham from 3D Systems, Yeshai Goodman from Vital Images, Yves Martel from TomoVision, and Nick Kloski from HoneyPoint3D for their support. Thanks to everyone at the Carnegie Center for Surgical Innovation for making me feel welcome whenever I visited the 3D printing lab. Thank you to the Vesalius Trust for their generous grant to help fund this project, and to Sarah Poynton for her astute feedback on my proposal. Thanks also to Norm Barker for sharing his photography equipment and expertise. iv 7RP\GHDUFODVVPDWHV'DQ(OOLH-XOLD.DWLH/LDQG1LFN³DVZHOODVWKHFODVVHVRIDQG³ thank you for being a constant uplifting and inspiring presence, and for the lifelong friendships. 7KDQNVDOVRWR,QJ\6ROLPDQIRUVXJJHVWLQJWKHFOHYHUZDWHUÁRVVHULGHD7KDQNVWRWKHLQFUHGLEOH faculty at the Department of Art as Applied to Medicine for creating a nurturing environment for us to thrive creatively and professionally. Special thanks to Cory Sandone and Kimberly Duncan for LQWURGXFLQJPHWR'U+LELQRDQGIDFLOLWDWLQJWKLVUHVHDUFKSURMHFWLQWKHÀUVWSODFH Thanks to Chris, for his endless support, and steady stream of encouragement and boxes of chocolate to keep me going through many late nights. Thanks to my parents and sisters for their unconditional love and support always. This was truly a multidisciplinary effort, and I look forward to future collaborations to expand and improve upon this project. v TABLE OF CONTENTS ABSTRACT ..................................................................... ii Chairpersons of the Supervisory Committee .......................................iii ACKNOWLEDGEMENTS .......................................................iv INTRODUCTION ............................................................... 1 Congenital Heart Defects ....................................................... 1 Hypoplastic Left Heart Syndrome ........................................... 2 A Need for Pre-surgical Planning in CHD Repair .............................. 6 3D Printing Applications in Cardiology: ........................................... Cardiovascular Imaging Data Acquisition .....................................10 Post-processing of Imaging Data ...........................................17 Generation of 3D Printed Models ..........................................21 The Role of Medical Artists in Creating 3D Prints ...................................23 Designing a Custom Model for HLHS Surgical Planning ........................23 Objectives ..............................................................24 A Multidisciplinary Collaborative Approach ...................................24 MATERIALS AND METHODS ....................................................26 Cardiovascular Imaging Data Acquisition ..........................................26 CT ....................................................................26 3D Ultrasound ..........................................................26 3D Fetal Ultrasound ......................................................27 Post-processing of Imaging Data ................................................. Segmentation of Cartesian DICOM – CT .................................... Segmentation of Non-Cartesian DICOM – Ultrasound ......................... Mesh Clean Up ..........................................................42 Model Optimization ...........................................................42 Determining Limits of Print Thickness ......................................43 Pre-op HLHS Model .....................................................44 Approximated Post-op HLHS Model ........................................45 Homograft Model ........................................................47 vi Pulmonary Artery Model ..................................................47 Additional Hypoplastic Aortic Arch Model ................................... 3D Ultrasound Model. 3D Fetal Ultrasound Model ................................................49 Generation of 3D Printed Models ................................................49 Printer Used and Settings ..................................................49 Post-print Processing .....................................................49 Surgical Simulation ............................................................51 RESULTS .......................................................................52 :RUNÁRZ ....................................................................52 Segmentation Software Chart ....................................................54 Segmentation Results ..........................................................55 Segmentation of Cartesian DICOM .........................................55 Segmentation of Non-Cartesian
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