The Utility of Robotics in Total Knee Arthroplasty View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009-06-22

AUTHORS

Mohanjit Kochhar , Giles R. Scuderi

ABSTRACT

In the last decade, instrumentation for total knee arthroplasty (TKA) has improved the accuracy, reproducibility, and reliability of the procedure. In recent years, minimally invasive surgery (MIS) TKA introduced instrumentation that was reduced in size to fit within the smaller operative field. As the operative field becomes reduced in size, the impact and influence of technology becomes proportionately larger.1 The introduction of computer navigation with MIS is an attempt to improve the surgeon’s visibility in a reduced operative field. The intended goal is to improve the position of the resection guides and ultimately the position of the final components, in essence, providing improved visualization in the limited field. This new technology is an enhancement tool or enabler in MIS TKA because, after registration of the anatomic landmarks, the instruments are dynamically tracked with real-time feedback on the angle and depth of the femoral and tibial resection. Currently, there are two types of computer-navigated systems for TKA: imaged-guided and imageless systems. Image-guided systems rely on data from preoperative radiographs or computed tomography (CT) scans that are registered into the computer system. Imageless navigation systems eliminate the need for preoperative imaging and rely on the registration of intraoperative landmarks, and then compare the registered data with a library of anatomic specimens recorded within the computer databank. The next distinctive feature is the mode of instrument tracking, which can be either by optical line of sight with a series of arrays that are detected by an infrared camera, or an electromagnetic (EM) system that utilizes trackers that are attached to the bone and an EM field generator. Each computer navigation system has their proponents. Either way, advocates of computer-navigated surgery have reported in clinical studies that navigation has shown an improvement in the accuracy of component position within 3° of the desired position over conventional instrumentation.2,3 The computer relies on the registration of anatomic landmarks and interprets this data to create a three-dimensional (3D) virtual model of the knee. Refinements in the process of collecting the landmark data will create a more accurate virtual model and guidance system. The ideal system should be simple to use, accurate, and reliable without interfering with the operative field and should serve as an enabler in the limited operative field, reliably reporting the knee alignment and intraoperative kinematics.4 More... »

PAGES

651-653

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-0-387-76608-9_77

DOI

http://dx.doi.org/10.1007/978-0-387-76608-9_77

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018958263


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Insall Scott Kelly Institute, 210 East 64th Street, 4th Floor, 10021, New York, NY, USA", 
          "id": "http://www.grid.ac/institutes/grid.418091.5", 
          "name": [
            "Insall Scott Kelly Institute, 210 East 64th Street, 4th Floor, 10021, New York, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kochhar", 
        "givenName": "Mohanjit", 
        "id": "sg:person.016675147421.29", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016675147421.29"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Insall Scott Kelly Institute, 210 East 64th Street, 4th Floor, 10021, New York, NY, USA", 
          "id": "http://www.grid.ac/institutes/grid.418091.5", 
          "name": [
            "Insall Scott Kelly Institute, 210 East 64th Street, 4th Floor, 10021, New York, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Scuderi", 
        "givenName": "Giles R.", 
        "id": "sg:person.01033173111.30", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01033173111.30"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2009-06-22", 
    "datePublishedReg": "2009-06-22", 
    "description": "In the last decade, instrumentation for total knee arthroplasty (TKA) has improved the accuracy, reproducibility, and reliability of the procedure. In recent years, minimally invasive surgery (MIS) TKA introduced instrumentation that was reduced in size to fit within the smaller operative field. As the operative field becomes reduced in size, the impact and influence of technology becomes proportionately larger.1 The introduction of computer navigation with MIS is an attempt to improve the surgeon\u2019s visibility in a reduced operative field. The intended goal is to improve the position of the resection guides and ultimately the position of the final components, in essence, providing improved visualization in the limited field. This new technology is an enhancement tool or enabler in MIS TKA because, after registration of the anatomic landmarks, the instruments are dynamically tracked with real-time feedback on the angle and depth of the femoral and tibial resection. Currently, there are two types of computer-navigated systems for TKA: imaged-guided and imageless systems. Image-guided systems rely on data from preoperative radiographs or computed tomography (CT) scans that are registered into the computer system. Imageless navigation systems eliminate the need for preoperative imaging and rely on the registration of intraoperative landmarks, and then compare the registered data with a library of anatomic specimens recorded within the computer databank. The next distinctive feature is the mode of instrument tracking, which can be either by optical line of sight with a series of arrays that are detected by an infrared camera, or an electromagnetic (EM) system that utilizes trackers that are attached to the bone and an EM field generator. Each computer navigation system has their proponents. Either way, advocates of computer-navigated surgery have reported in clinical studies that navigation has shown an improvement in the accuracy of component position within 3\u00b0 of the desired position over conventional instrumentation.2,3 The computer relies on the registration of anatomic landmarks and interprets this data to create a three-dimensional (3D) virtual model of the knee. Refinements in the process of collecting the landmark data will create a more accurate virtual model and guidance system. The ideal system should be simple to use, accurate, and reliable without interfering with the operative field and should serve as an enabler in the limited operative field, reliably reporting the knee alignment and intraoperative kinematics.4", 
    "editor": [
      {
        "familyName": "Scuderi", 
        "givenName": "Giles R.", 
        "type": "Person"
      }, 
      {
        "familyName": "Tria", 
        "givenName": "Alfred J.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-0-387-76608-9_77", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-0-387-76607-2", 
        "978-0-387-76608-9"
      ], 
      "name": "Minimally Invasive Surgery in Orthopedics", 
      "type": "Book"
    }, 
    "keywords": [
      "virtual model", 
      "navigation system", 
      "accurate virtual model", 
      "three-dimensional virtual models", 
      "real-time feedback", 
      "computer-navigated surgery", 
      "computer systems", 
      "instrument tracking", 
      "utility of robotics", 
      "image-guided system", 
      "resection guide", 
      "enhancement tool", 
      "limited field", 
      "EM field generator", 
      "guidance system", 
      "navigation", 
      "surgeon\u2019s visibility", 
      "computer navigation system", 
      "enablers", 
      "registration", 
      "new technologies", 
      "imageless navigation system", 
      "landmarks", 
      "technology", 
      "robotics", 
      "system", 
      "accuracy", 
      "infrared camera", 
      "recent years", 
      "computer", 
      "intended goal", 
      "camera", 
      "tracker", 
      "tracking", 
      "small operative field", 
      "influence of technology", 
      "landmark data", 
      "visibility", 
      "visualization", 
      "imageless system", 
      "intraoperative kinematics", 
      "improved visualization", 
      "computer navigation", 
      "distinctive features", 
      "final component", 
      "data", 
      "last decade", 
      "computer databanks", 
      "tool", 
      "library", 
      "feedback", 
      "model", 
      "reliability", 
      "instrumentation", 
      "features", 
      "goal", 
      "field", 
      "electromagnetic system", 
      "field generator", 
      "position", 
      "limited operative field", 
      "way", 
      "refinement", 
      "alignment", 
      "generator", 
      "databank", 
      "essence", 
      "need", 
      "series of arrays", 
      "kinematics", 
      "anatomic landmarks", 
      "improvement", 
      "utility", 
      "operative field", 
      "sight", 
      "process", 
      "conventional instrumentation", 
      "array", 
      "MIS", 
      "size", 
      "components", 
      "ideal system", 
      "optical lines", 
      "component position", 
      "guide", 
      "introduction", 
      "procedure", 
      "types", 
      "decades", 
      "mode", 
      "attempt", 
      "scans", 
      "imaging", 
      "MIS total knee arthroplasty", 
      "impact", 
      "instrument", 
      "lines", 
      "angle", 
      "series", 
      "depth", 
      "years", 
      "reproducibility", 
      "tomography scan", 
      "proponents", 
      "intraoperative landmark", 
      "radiographs", 
      "study", 
      "advocates", 
      "tibial resection", 
      "knee alignment", 
      "preoperative imaging", 
      "anatomic specimens", 
      "influence", 
      "total knee arthroplasty", 
      "knee arthroplasty", 
      "knee", 
      "clinical studies", 
      "bone", 
      "surgery", 
      "arthroplasty", 
      "preoperative radiographs", 
      "resection", 
      "specimens", 
      "invasive surgery (MIS) TKA", 
      "surgery (MIS) TKA", 
      "computer-navigated systems", 
      "next distinctive feature"
    ], 
    "name": "The Utility of Robotics in Total Knee Arthroplasty", 
    "pagination": "651-653", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1018958263"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-0-387-76608-9_77"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-0-387-76608-9_77", 
      "https://app.dimensions.ai/details/publication/pub.1018958263"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2021-11-01T18:50", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211101/entities/gbq_results/chapter/chapter_208.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-0-387-76608-9_77"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-0-387-76608-9_77'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-0-387-76608-9_77'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-0-387-76608-9_77'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-0-387-76608-9_77'


 

This table displays all metadata directly associated to this object as RDF triples.

207 TRIPLES      23 PREDICATES      154 URIs      145 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-0-387-76608-9_77 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 anzsrc-for:11
4 anzsrc-for:1103
5 schema:author Nd4f8e575082e46bfb2e173f39acc20eb
6 schema:datePublished 2009-06-22
7 schema:datePublishedReg 2009-06-22
8 schema:description In the last decade, instrumentation for total knee arthroplasty (TKA) has improved the accuracy, reproducibility, and reliability of the procedure. In recent years, minimally invasive surgery (MIS) TKA introduced instrumentation that was reduced in size to fit within the smaller operative field. As the operative field becomes reduced in size, the impact and influence of technology becomes proportionately larger.1 The introduction of computer navigation with MIS is an attempt to improve the surgeon’s visibility in a reduced operative field. The intended goal is to improve the position of the resection guides and ultimately the position of the final components, in essence, providing improved visualization in the limited field. This new technology is an enhancement tool or enabler in MIS TKA because, after registration of the anatomic landmarks, the instruments are dynamically tracked with real-time feedback on the angle and depth of the femoral and tibial resection. Currently, there are two types of computer-navigated systems for TKA: imaged-guided and imageless systems. Image-guided systems rely on data from preoperative radiographs or computed tomography (CT) scans that are registered into the computer system. Imageless navigation systems eliminate the need for preoperative imaging and rely on the registration of intraoperative landmarks, and then compare the registered data with a library of anatomic specimens recorded within the computer databank. The next distinctive feature is the mode of instrument tracking, which can be either by optical line of sight with a series of arrays that are detected by an infrared camera, or an electromagnetic (EM) system that utilizes trackers that are attached to the bone and an EM field generator. Each computer navigation system has their proponents. Either way, advocates of computer-navigated surgery have reported in clinical studies that navigation has shown an improvement in the accuracy of component position within 3° of the desired position over conventional instrumentation.2,3 The computer relies on the registration of anatomic landmarks and interprets this data to create a three-dimensional (3D) virtual model of the knee. Refinements in the process of collecting the landmark data will create a more accurate virtual model and guidance system. The ideal system should be simple to use, accurate, and reliable without interfering with the operative field and should serve as an enabler in the limited operative field, reliably reporting the knee alignment and intraoperative kinematics.4
9 schema:editor Nd6f70641c1d74c8c9b8ad05e041eae49
10 schema:genre chapter
11 schema:inLanguage en
12 schema:isAccessibleForFree false
13 schema:isPartOf N1472060bbe1745f9a9d118dee7ba88a4
14 schema:keywords EM field generator
15 MIS
16 MIS total knee arthroplasty
17 accuracy
18 accurate virtual model
19 advocates
20 alignment
21 anatomic landmarks
22 anatomic specimens
23 angle
24 array
25 arthroplasty
26 attempt
27 bone
28 camera
29 clinical studies
30 component position
31 components
32 computer
33 computer databanks
34 computer navigation
35 computer navigation system
36 computer systems
37 computer-navigated surgery
38 computer-navigated systems
39 conventional instrumentation
40 data
41 databank
42 decades
43 depth
44 distinctive features
45 electromagnetic system
46 enablers
47 enhancement tool
48 essence
49 features
50 feedback
51 field
52 field generator
53 final component
54 generator
55 goal
56 guidance system
57 guide
58 ideal system
59 image-guided system
60 imageless navigation system
61 imageless system
62 imaging
63 impact
64 improved visualization
65 improvement
66 influence
67 influence of technology
68 infrared camera
69 instrument
70 instrument tracking
71 instrumentation
72 intended goal
73 intraoperative kinematics
74 intraoperative landmark
75 introduction
76 invasive surgery (MIS) TKA
77 kinematics
78 knee
79 knee alignment
80 knee arthroplasty
81 landmark data
82 landmarks
83 last decade
84 library
85 limited field
86 limited operative field
87 lines
88 mode
89 model
90 navigation
91 navigation system
92 need
93 new technologies
94 next distinctive feature
95 operative field
96 optical lines
97 position
98 preoperative imaging
99 preoperative radiographs
100 procedure
101 process
102 proponents
103 radiographs
104 real-time feedback
105 recent years
106 refinement
107 registration
108 reliability
109 reproducibility
110 resection
111 resection guide
112 robotics
113 scans
114 series
115 series of arrays
116 sight
117 size
118 small operative field
119 specimens
120 study
121 surgeon’s visibility
122 surgery
123 surgery (MIS) TKA
124 system
125 technology
126 three-dimensional virtual models
127 tibial resection
128 tomography scan
129 tool
130 total knee arthroplasty
131 tracker
132 tracking
133 types
134 utility
135 utility of robotics
136 virtual model
137 visibility
138 visualization
139 way
140 years
141 schema:name The Utility of Robotics in Total Knee Arthroplasty
142 schema:pagination 651-653
143 schema:productId N4d6d08d48d724438b59e7de02838a65d
144 Nee79299817a6419da57817f5076534e1
145 schema:publisher Nccc755b070dd43cfb80b43979760294a
146 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018958263
147 https://doi.org/10.1007/978-0-387-76608-9_77
148 schema:sdDatePublished 2021-11-01T18:50
149 schema:sdLicense https://scigraph.springernature.com/explorer/license/
150 schema:sdPublisher N7e78aec23b68406984a709bc7cd57858
151 schema:url https://doi.org/10.1007/978-0-387-76608-9_77
152 sgo:license sg:explorer/license/
153 sgo:sdDataset chapters
154 rdf:type schema:Chapter
155 N1472060bbe1745f9a9d118dee7ba88a4 schema:isbn 978-0-387-76607-2
156 978-0-387-76608-9
157 schema:name Minimally Invasive Surgery in Orthopedics
158 rdf:type schema:Book
159 N172cbb8c6aee4799a039e4fab77e320d rdf:first Nf35c68535bcf44519f52811a837b04f9
160 rdf:rest rdf:nil
161 N4d6d08d48d724438b59e7de02838a65d schema:name doi
162 schema:value 10.1007/978-0-387-76608-9_77
163 rdf:type schema:PropertyValue
164 N7e78aec23b68406984a709bc7cd57858 schema:name Springer Nature - SN SciGraph project
165 rdf:type schema:Organization
166 Nccc755b070dd43cfb80b43979760294a schema:name Springer Nature
167 rdf:type schema:Organisation
168 Ncf34c90f252a4558838496d49ec70ae7 schema:familyName Scuderi
169 schema:givenName Giles R.
170 rdf:type schema:Person
171 Nd4f8e575082e46bfb2e173f39acc20eb rdf:first sg:person.016675147421.29
172 rdf:rest Nf13e4732eaee4d9fa4c402bd416703fa
173 Nd6f70641c1d74c8c9b8ad05e041eae49 rdf:first Ncf34c90f252a4558838496d49ec70ae7
174 rdf:rest N172cbb8c6aee4799a039e4fab77e320d
175 Nee79299817a6419da57817f5076534e1 schema:name dimensions_id
176 schema:value pub.1018958263
177 rdf:type schema:PropertyValue
178 Nf13e4732eaee4d9fa4c402bd416703fa rdf:first sg:person.01033173111.30
179 rdf:rest rdf:nil
180 Nf35c68535bcf44519f52811a837b04f9 schema:familyName Tria
181 schema:givenName Alfred J.
182 rdf:type schema:Person
183 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
184 schema:name Information and Computing Sciences
185 rdf:type schema:DefinedTerm
186 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
187 schema:name Artificial Intelligence and Image Processing
188 rdf:type schema:DefinedTerm
189 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
190 schema:name Medical and Health Sciences
191 rdf:type schema:DefinedTerm
192 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
193 schema:name Clinical Sciences
194 rdf:type schema:DefinedTerm
195 sg:person.01033173111.30 schema:affiliation grid-institutes:grid.418091.5
196 schema:familyName Scuderi
197 schema:givenName Giles R.
198 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01033173111.30
199 rdf:type schema:Person
200 sg:person.016675147421.29 schema:affiliation grid-institutes:grid.418091.5
201 schema:familyName Kochhar
202 schema:givenName Mohanjit
203 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016675147421.29
204 rdf:type schema:Person
205 grid-institutes:grid.418091.5 schema:alternateName Insall Scott Kelly Institute, 210 East 64th Street, 4th Floor, 10021, New York, NY, USA
206 schema:name Insall Scott Kelly Institute, 210 East 64th Street, 4th Floor, 10021, New York, NY, USA
207 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...