Abstract
Multi-Detector Computed Tomography is nowadays the gold standard for the pre-operative imaging for several surgical interventions, thanks to its excellent morphological definition. As for vascular structures, only the blood flowing inside vessels can be highlighted, while vessels’ wall remains mostly invisible. Image segmentation and three-dimensional-printing technology can be used to create physical replica of patient-specific anatomy, to be used for the training of novice surgeons in robotic surgery. To this aim, it is fundamental that the model correctly resembles the morphological properties of the structure of interest, especially concerning vessels on which crucial operations are performed during the intervention. To reach the goal, vessels’ actual size must be restored, including information on their wall. Starting from the correlation between vessels’ lumen diameter and their wall thickness, we developed a semi-automatic approach to compute the local vessels’ wall, bringing the vascular structures as close as possible to their actual size. The optimized virtual models are suitable for manufacturing by means of three-dimensional-printing technology to build patient-specific phantoms for the surgical simulation of robotic abdominal interventions. The proposed approach can effectively lead to the generation of vascular models of optimized thickness wall. The feasibility of the approach is also tested on a selection of clinical cases in abdominal surgery, on which the robotic surgery is performed on the three-dimensional-printed replica before the actual intervention.
| Original language | English |
|---|---|
| Journal | International Journal of Artificial Organs |
| DOIs | |
| Publication status | Published - Jan 1 2019 |
Fingerprint
Keywords
- 3D-printing
- anatomical model
- patient-specific model
- training phantom
- vessel model
ASJC Scopus subject areas
- Bioengineering
- Medicine (miscellaneous)
- Biomaterials
- Biomedical Engineering
Cite this
Toward the improvement of 3D-printed vessels’ anatomical models for robotic surgery training. / Marconi, S.; Negrello, E.; Mauri, V.; Pugliese, L.; Peri, A.; Argenti, F.; Auricchio, F.; Pietrabissa, A.
In: International Journal of Artificial Organs, 01.01.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Toward the improvement of 3D-printed vessels’ anatomical models for robotic surgery training
AU - Marconi, S.
AU - Negrello, E.
AU - Mauri, V.
AU - Pugliese, L.
AU - Peri, A.
AU - Argenti, F.
AU - Auricchio, F.
AU - Pietrabissa, A.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Multi-Detector Computed Tomography is nowadays the gold standard for the pre-operative imaging for several surgical interventions, thanks to its excellent morphological definition. As for vascular structures, only the blood flowing inside vessels can be highlighted, while vessels’ wall remains mostly invisible. Image segmentation and three-dimensional-printing technology can be used to create physical replica of patient-specific anatomy, to be used for the training of novice surgeons in robotic surgery. To this aim, it is fundamental that the model correctly resembles the morphological properties of the structure of interest, especially concerning vessels on which crucial operations are performed during the intervention. To reach the goal, vessels’ actual size must be restored, including information on their wall. Starting from the correlation between vessels’ lumen diameter and their wall thickness, we developed a semi-automatic approach to compute the local vessels’ wall, bringing the vascular structures as close as possible to their actual size. The optimized virtual models are suitable for manufacturing by means of three-dimensional-printing technology to build patient-specific phantoms for the surgical simulation of robotic abdominal interventions. The proposed approach can effectively lead to the generation of vascular models of optimized thickness wall. The feasibility of the approach is also tested on a selection of clinical cases in abdominal surgery, on which the robotic surgery is performed on the three-dimensional-printed replica before the actual intervention.
AB - Multi-Detector Computed Tomography is nowadays the gold standard for the pre-operative imaging for several surgical interventions, thanks to its excellent morphological definition. As for vascular structures, only the blood flowing inside vessels can be highlighted, while vessels’ wall remains mostly invisible. Image segmentation and three-dimensional-printing technology can be used to create physical replica of patient-specific anatomy, to be used for the training of novice surgeons in robotic surgery. To this aim, it is fundamental that the model correctly resembles the morphological properties of the structure of interest, especially concerning vessels on which crucial operations are performed during the intervention. To reach the goal, vessels’ actual size must be restored, including information on their wall. Starting from the correlation between vessels’ lumen diameter and their wall thickness, we developed a semi-automatic approach to compute the local vessels’ wall, bringing the vascular structures as close as possible to their actual size. The optimized virtual models are suitable for manufacturing by means of three-dimensional-printing technology to build patient-specific phantoms for the surgical simulation of robotic abdominal interventions. The proposed approach can effectively lead to the generation of vascular models of optimized thickness wall. The feasibility of the approach is also tested on a selection of clinical cases in abdominal surgery, on which the robotic surgery is performed on the three-dimensional-printed replica before the actual intervention.
KW - 3D-printing
KW - anatomical model
KW - patient-specific model
KW - training phantom
KW - vessel model
UR - http://www.scopus.com/inward/record.url?scp=85067816759&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067816759&partnerID=8YFLogxK
U2 - 10.1177/0391398819852957
DO - 10.1177/0391398819852957
M3 - Article
JO - International Journal of Artificial Organs
JF - International Journal of Artificial Organs
SN - 0391-3988
ER -