Development of a customized three-dimensional airway model Article Swipe
Mateus Samuel Tonetto
,
Hugo Goulart de Oliveira
,
André Frotta Müller
,
Paulo Roberto Stefani Sanches
,
Luciano Folador
,
Felipe Soares Torres
,
Tiago Severo Garcia
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.33448/rsd-v11i9.31721
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.33448/rsd-v11i9.31721
This study aimed to develop a customized, three-dimensional airway model based on relevant medical images, using additive manufacturing techniques. We evaluated the model’s ability to replicate the dimensions of the images acquired from the chest of a patient using multi-detector computed tomography (CT). Using dedicated software, a three-dimensional mesh was created based on the images. A multi-detector CT study of the full-scale printed three-dimensional airways model was subsequently carried out to compare its dimensions with that of the original study at four predetermined points. The observed median differences at the four points were 0.4 mm (p = 0.686), -1.3 mm (p = 0.138), 0.7 mm (p = 0.141), and 0.1 mm (p = 0.892). The intraclass correlation coefficient between the measurements made on the patient and those on the model was 0.98 (95% confidence interval: 0.96–0.99, p < 0.001). We successfully developed a three-dimensional model of the airway based on its corresponding medical images. The differences in the dimensions between the model and the original images were in line with those observed in previous studies and are presumably irrelevant for most applications.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.33448/rsd-v11i9.31721
- https://rsdjournal.org/index.php/rsd/article/download/31721/27463
- OA Status
- diamond
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4286785473
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4286785473Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.33448/rsd-v11i9.31721Digital Object Identifier
- Title
-
Development of a customized three-dimensional airway modelWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-07-20Full publication date if available
- Authors
-
Mateus Samuel Tonetto, Hugo Goulart de Oliveira, André Frotta Müller, Paulo Roberto Stefani Sanches, Luciano Folador, Felipe Soares Torres, Tiago Severo GarciaList of authors in order
- Landing page
-
https://doi.org/10.33448/rsd-v11i9.31721Publisher landing page
- PDF URL
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https://rsdjournal.org/index.php/rsd/article/download/31721/27463Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
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https://rsdjournal.org/index.php/rsd/article/download/31721/27463Direct OA link when available
- Concepts
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Intraclass correlation, Confidence interval, Computed tomography, Nuclear medicine, Airway, Replicate, Software, 3d model, Biomedical engineering, Computer science, Artificial intelligence, Medicine, Mathematics, Radiology, Statistics, Surgery, Psychometrics, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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27Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.in | 156, 167, 172 |
| abstract_inverted_index.mm | 94, 99, 104, 110 |
| abstract_inverted_index.of | 28, 35, 59, 76, 145 |
| abstract_inverted_index.on | 11, 52, 122, 127, 149 |
| abstract_inverted_index.to | 3, 24, 70 |
| abstract_inverted_index.0.1 | 109 |
| abstract_inverted_index.0.4 | 93 |
| abstract_inverted_index.0.7 | 103 |
| abstract_inverted_index.The | 84, 114, 154 |
| abstract_inverted_index.and | 108, 125, 162, 175 |
| abstract_inverted_index.are | 176 |
| abstract_inverted_index.for | 179 |
| abstract_inverted_index.its | 72, 150 |
| abstract_inverted_index.out | 69 |
| abstract_inverted_index.the | 21, 26, 29, 33, 53, 60, 77, 89, 119, 123, 128, 146, 157, 160, 163 |
| abstract_inverted_index.was | 49, 66, 130 |
| abstract_inverted_index.< | 137 |
| abstract_inverted_index.(95% | 132 |
| abstract_inverted_index.-1.3 | 98 |
| abstract_inverted_index.0.98 | 131 |
| abstract_inverted_index.This | 0 |
| abstract_inverted_index.four | 81, 90 |
| abstract_inverted_index.from | 32 |
| abstract_inverted_index.line | 168 |
| abstract_inverted_index.made | 121 |
| abstract_inverted_index.mesh | 48 |
| abstract_inverted_index.most | 180 |
| abstract_inverted_index.that | 75 |
| abstract_inverted_index.were | 92, 166 |
| abstract_inverted_index.with | 74, 169 |
| abstract_inverted_index.(CT). | 42 |
| abstract_inverted_index.Using | 43 |
| abstract_inverted_index.aimed | 2 |
| abstract_inverted_index.based | 10, 51, 148 |
| abstract_inverted_index.chest | 34 |
| abstract_inverted_index.model | 9, 65, 129, 144, 161 |
| abstract_inverted_index.study | 1, 58, 79 |
| abstract_inverted_index.those | 126, 170 |
| abstract_inverted_index.using | 15, 38 |
| abstract_inverted_index.airway | 8, 147 |
| abstract_inverted_index.images | 30, 165 |
| abstract_inverted_index.median | 86 |
| abstract_inverted_index.points | 91 |
| abstract_inverted_index.0.001). | 138 |
| abstract_inverted_index.0.138), | 102 |
| abstract_inverted_index.0.141), | 107 |
| abstract_inverted_index.0.686), | 97 |
| abstract_inverted_index.0.892). | 113 |
| abstract_inverted_index.ability | 23 |
| abstract_inverted_index.airways | 64 |
| abstract_inverted_index.between | 118, 159 |
| abstract_inverted_index.carried | 68 |
| abstract_inverted_index.compare | 71 |
| abstract_inverted_index.created | 50 |
| abstract_inverted_index.develop | 4 |
| abstract_inverted_index.images, | 14 |
| abstract_inverted_index.images. | 54, 153 |
| abstract_inverted_index.medical | 13, 152 |
| abstract_inverted_index.patient | 37, 124 |
| abstract_inverted_index.points. | 83 |
| abstract_inverted_index.printed | 62 |
| abstract_inverted_index.studies | 174 |
| abstract_inverted_index.acquired | 31 |
| abstract_inverted_index.additive | 16 |
| abstract_inverted_index.computed | 40 |
| abstract_inverted_index.observed | 85, 171 |
| abstract_inverted_index.original | 78, 164 |
| abstract_inverted_index.previous | 173 |
| abstract_inverted_index.relevant | 12 |
| abstract_inverted_index.dedicated | 44 |
| abstract_inverted_index.developed | 141 |
| abstract_inverted_index.evaluated | 20 |
| abstract_inverted_index.interval: | 134 |
| abstract_inverted_index.model’s | 22 |
| abstract_inverted_index.replicate | 25 |
| abstract_inverted_index.software, | 45 |
| abstract_inverted_index.confidence | 133 |
| abstract_inverted_index.dimensions | 27, 73, 158 |
| abstract_inverted_index.full-scale | 61 |
| abstract_inverted_index.intraclass | 115 |
| abstract_inverted_index.irrelevant | 178 |
| abstract_inverted_index.presumably | 177 |
| abstract_inverted_index.tomography | 41 |
| abstract_inverted_index.coefficient | 117 |
| abstract_inverted_index.correlation | 116 |
| abstract_inverted_index.customized, | 6 |
| abstract_inverted_index.differences | 87, 155 |
| abstract_inverted_index.techniques. | 18 |
| abstract_inverted_index.0.96–0.99, | 135 |
| abstract_inverted_index.measurements | 120 |
| abstract_inverted_index.subsequently | 67 |
| abstract_inverted_index.successfully | 140 |
| abstract_inverted_index.applications. | 181 |
| abstract_inverted_index.corresponding | 151 |
| abstract_inverted_index.manufacturing | 17 |
| abstract_inverted_index.predetermined | 82 |
| abstract_inverted_index.multi-detector | 39, 56 |
| abstract_inverted_index.three-dimensional | 7, 47, 63, 143 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile.value | 0.14140786 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |