Digital Surgery

441 Pages·2021·22.193 MB·English

by  Sam Atallah

Digital Surgery
Sam Atallah
Editor
123
Digital Surgery
Sam Atallah
Editor
Digital Surgery
Editor
Sam Atallah
Orlando, FL
USA
ISBN 978-3-030-49099-7 ISBN 978-3-030-49100-0 (eBook)
https://doi.org/10.1007/978-3-030-49100-0
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To my youngest child, Addyson.
What wonders await you in your lifetime?
Preface
The future. Sometimes, we can close our eyes and almost see it. In the years
leading up to 2020, digital surgery had reached a fever pitch. Abraham
Lincoln once said, “the best way to predict the future is to create it.” In this
context, the coming age of surgery will be formed in the present by our own
design. This book is written by many of those who, today, are laying the foun-
dation for tomorrow’s operating environment. This textbook provides a trove
of insightful perspectives on where we are at this instant in time … and the
trek ahead toward the realization of digital surgery.
What is digital surgery? Perhaps its definition should be left bound not by
diction but rather by imagination. To some degree, digital surgery is kaleido-
scopic—its facets and shapes, shifting. In its commonest context, it entails the
application of artificial intelligence toward computer vision and automation in
robotic-assisted surgery. More generally, however, the objective is to digitally
define the patient, the surgical field, and the surgical problem or task at hand—
to operate based on information, rather than based on anatomic planes alone.
But digital surgery has shapeshifted into other, equally intriguing facets—
many of which are exemplified by chapter headings throughout this book.
Digital surgery is fundamental to 3D-printed organs, mind-controlled limbs,
image-g uided navigation, and tele-mentoring. It is the key that unlocks the
metaphorical doorway to surgical access, thereby creating a global frame-
work for surgical training, education, planning, and much more. This 4.0-ver-
sion of surgery will also provide methods of measurement and perception
outside of the human umwelt—including the ability to visualize fields beyond
the visible light spectrum, via near infrared fluorescent organic dyes which
are rapidly being bioengineered to target specific tumors, as well as native
anatomic structures of interest.
Digital surgery ushers in the era of patient centricity. Rather than focusing
solely on the anatome, surgeons will operate with an enriched understanding
of an individual’s specific attributes: including the human phenome, physi-
ome, microbiome, genome, and epigenome. In parallel, digital surgery will
harness the power and fluidity of the cloud. The cloud is poised to emerge as
a significant resource for surgeons over the next decade—especially through
shared machine learning, both regionally and globally. It is important to
understand that digital surgery is not the last step in evolution, but only the
next. A touchstone towards computer-centric surgery and the new age of sur-
gical automation, robotic-machine learning, augmented environments, and
the like.
vii
viii Preface
In 2005, when I was a fourth-year surgical resident in training, I was
reminded of where we stand with regard to innovation in surgery on a grand
scale. I had the opportunity to meet famed surgeon Michael DeBakey that
year. At our encounter, I asked him with genuine curiosity, “do you think the
era of innovation and discovery in surgery is over and done?” I went on to
ramble off several seismic milestones—the first heart transplant in a human,
the development of general anesthetics, the creation of the lung-heart bypass
machine, electrocautery, and so on. He shook his head at me and, with a wide
grin and a sparkle of certainty in his eyes, said, “Not at all!” … he added with
a chuckle, “This is just the beginning!”
DeBakey was right. Indeed, we are at one of the most exciting times in the
history of surgery, and we are only getting started. Off we go... a great odys-
sey lies ahead!
We are at the very beginning of time for the human race. It is not unreasonable that
we grapple with problems. But there are tens of thousands of years in the future. Our
responsibility is to do what we can, learn what we can, improve the solutions, and
pass them on. ― Richard P. Feynman
Orlando, FL, USA Sam Atallah, MD
Contents
1 The Cognitive Revolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Thomas M. Ward and Ozanan Meireles
2 The Vision of Digital Surgery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Bernhard Fuerst, Danyal M. Fer, David Herrmann,
and Pablo Garcia Kilroy
3 Artificial Intelligence for Next- Generation
Medical Robotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
M. Mahir Ozmen, Asutay Ozmen, and Çetin Kaya Koç
4 Cloud Computing for Robotics and Surgery . . . . . . . . . . . . . . . . 37
Asa B. Atallah and Sam Atallah
5 Quantum Theory and Computing for Surgeons . . . . . . . . . . . . . 59
Sam Atallah and Asa B. Atallah
6 5G Networks, Haptic Codecs, and the Operating Theatre . . . . . 71
Mischa Dohler
7 Haptics and Vision Systems for Surgical Robots . . . . . . . . . . . . . 87
Marco Ferrara and Mark K. Soliman
8 Digital and 3D Printed Models for Surgical Planning . . . . . . . . . 95
Jordan Fletcher and Danilo Miskovic
9 Realistic Organ Models for Simulation and Training . . . . . . . . . 111
Pratik M. S. Gurung and Ahmed E. Ghazi
10 The Challenge of Augmented Reality in Surgery . . . . . . . . . . . . . 121
P. J. “ Eddie” Edwards, Manish Chand, Manuel Birlo, and
Danail Stoyanov
11 Navigation and Image-Guided Surgery . . . . . . . . . . . . . . . . . . . . 137
Arthur Randolph Wijsmuller,
Luis Gustavo Capochin Romagnolo, Esther Consten,
Armando Errando Franchini Melani, and Jacques Marescaux
12 Operating in the Near-Infrared Spectrum . . . . . . . . . . . . . . . . . . 145
Thomas George Barnes
ix
x Contents
13 Fluorescence-Guided Resections: A Binary
Approach to Surgery. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
Stephanie Schipmann and Walter Stummer
14 A Virtual Reality for the Digital Surgeon . . . . . . . . . . . . . . . . . . . 183
Diana Velazquez-Pimentel, Thomas Hurkxkens,
and Jean Nehme
15 Robotic Automation for Surgery . . . . . . . . . . . . . . . . . . . . . . . . . . 203
Hossein Dehghani and Peter C. W. Kim
16 3D Bioprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
Ippokratis Pountos, Nazzar Tellisi, Mohammad Ali Darabi,
Ahmet Erdem, Tamer Mohamed, Murat Guvendiren,
and Nureddin Ashammakhi
17 Augmented Reality for Interventional Procedures . . . . . . . . . . . 233
Atul Gupta, Daniel Ruijters, and Molly L. Flexman
18 The Visible Patient: Augmented Reality in the
Operating Theater . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
Luc Soler, Alexandre Hostettler, Toby Collins,
Patrick Pessaux, Didier Mutter, and Jacques Marescaux
19 Augmented Cognition in the Operating Room . . . . . . . . . . . . . . . 261
Roger Daglius Dias, Steven J. Yule, and Marco A. Zenati
20 Cooperative and Miniature Robotics: Potential
Applications in Surgery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269
Joseph J. Eid and Dmitry Oleynikov
21 Human-Machine Integration and the Evolution
of Neuroprostheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275
William Kethman and Richard F. ff. Weir
22 Nonlinear Robotics in Surgery . . . . . . . . . . . . . . . . . . . . . . . . . . . 285
Deborah Keller, Sam Atallah, Rithvik Seela, Barbara Seeliger,
and Eduardo Parra-Davila
23 Artificial Intelligence and Machine Learning:
Implications for Surgery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311
David Hindin
24 AI and Endoscopy: Future Perspectives . . . . . . . . . . . . . . . . . . . . 319
Daljeet Chahal, Neal Shahidi, and Michael F. Byrne
25 Explainable AI for the Operating Theater . . . . . . . . . . . . . . . . . . 339
Frank Rudzicz and Shalmali Joshi
26 A Digital Doorway to Global Surgery . . . . . . . . . . . . . . . . . . . . . . 351
Nadine Hachach-Haram
Contents xi
27 Telementoring for Minimally Invasive Surgery . . . . . . . . . . . . . . 361
Justin W. Collins, Runzhuo Ma, Yanick Beaulieu,
and Andrew J. Hung
28 Digital Medical School: New Paradigms for
Tomorrow’s Surgical Education . . . . . . . . . . . . . . . . . . . . . . . . . . 379
Joanna Ashby, Isaac Ndayishimiye, Arsen Muhumuza,
and Sylvine Niyoyita
29 3D Simulation and Modeling for Surgeon Education
and Patient Engagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389
Anna Przedlacka, Przemyslaw Korzeniowski,
Paris Tekkis, Fernando Bello, and Christos Kontovounisios
30 Next-Generation Surgical Robots . . . . . . . . . . . . . . . . . . . . . . . . . 401
Shinil K. Shah, Melissa M. Felinski, Todd D. Wilson,
Kulvinder S. Bajwa, and Erik B. Wilson
31 Artificial Intelligence and Computer Vision . . . . . . . . . . . . . . . . . 407
Sam Atallah
32 The Future of Surgery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419
Rebecca A. Fisher, Suewan Kim, and Prokar Dasgupta
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429