Publications
2021
Bianchi, J; Goncalves, J R; de Oliveira Ruellas, A C; Ashman, L M; Vimort, J-B; Yatabe, M; Paniagua, B; Hernandez, P; Benavides, E; Soki, F N; Loshida, M; Cevidanes, L H S
Quantitative bone imaging biomarkers to diagnose temporomandibular joint osteoarthritis. Journal Article
In: International Journal of Oral and Maxillofacial Surgery, vol. 50, no. 2, pp. 227-235, 2021.
Abstract | Links | BibTeX | Tags: AAOF, Adolescents, biomarkers, Cone-beam computed tomography, Cranial base, osteoarthritis, temporomandibular joint
@article{Bianchi2021b,
title = {Quantitative bone imaging biomarkers to diagnose temporomandibular joint osteoarthritis.},
author = {J Bianchi and J R Goncalves and A C de Oliveira Ruellas and L M Ashman and J-B Vimort and M Yatabe and B Paniagua and P Hernandez and E Benavides and F N Soki and M Loshida and L H S Cevidanes},
url = {https://pubmed.ncbi.nlm.nih.gov/32605824/},
doi = {10.1016/j.ijom.2020.04.018},
year = {2021},
date = {2021-02-00},
journal = {International Journal of Oral and Maxillofacial Surgery},
volume = {50},
number = {2},
pages = {227-235},
abstract = {Bone degradation of the condylar surface is seen in temporomandibular joint osteoarthritis (TMJ OA); however, the initial changes occur in the subchondral bone. This cross-sectional study was performed to evaluate 23 subchondral bone imaging biomarkers for TMJ OA. The sample consisted of high-resolution cone beam computed tomography scans of 84 subjects, divided into two groups: TMJ OA (45 patients with TMJ OA) and control (39 asymptomatic subjects). Six regions of each mandibular condyle scan were extracted for computation of five bone morphometric and 18 grey-level texture-based variables. The groups were compared using the Mann-Whitney U-test, and the receiver operating characteristics (ROC) curve was determined for each variable that showed a statically significance difference. The results showed statistically significant differences in the subchondral bone microstructure in the lateral and central condylar regions between the control and TMJ OA groups (P< 0.05). The area under the ROC curve (AUC) for these variables was between 0.620 and 0.710. In conclusion, 13 imaging bone biomarkers presented an acceptable diagnostic performance for the diagnosis of TMJ OA, indicating that the texture and geometry of the subchondral bone microarchitecture may be useful for quantitative grading of the disease.},
keywords = {AAOF, Adolescents, biomarkers, Cone-beam computed tomography, Cranial base, osteoarthritis, temporomandibular joint},
pubstate = {published},
tppubtype = {article}
}
2019
L, Michoud; C, Huang; M, Yatabe; J, Bianchi; et al,
A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis. Journal Article
In: Proc SPIE-the Int Soc Opt Eng, vol. 10953, 2019.
Abstract | Links | BibTeX | Tags: biomarkers, Meshes, osteoarthritis, statistics, temporomandibular joint disorders, web-platform
@article{Michoud2019,
title = {A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis.},
author = {Michoud L and Huang C and Yatabe M and Bianchi J and et al},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494085/},
doi = {10.1117/12.2506032},
year = {2019},
date = {2019-05-15},
journal = {Proc SPIE-the Int Soc Opt Eng},
volume = {10953},
abstract = {This study presents a web-system repository: Data Storage for Computation and Integration (DSCI) for Osteoarthritis of the temporomandibular joint (TMJ OA). This environment aims to maintain and allow contributions to the database from multi-clinical centers and compute novel statistics for disease classification. For this purpose, imaging datasets stored in the DSCI consisted of three-dimensional (3D) surface meshes of condyles from CBCT, clinical markers and biological markers in healthy and TMJ OA subjects. A clusterpost package was included in the web platform to be able to execute the jobs in remote computing grids. The DSCI application allowed runs of statistical packages, such as the Multivariate Functional Shape Data Analysis to compute global correlations between covariates and the morphological variability, as well as local p-values in the 3D condylar morphology. In conclusion, the DSCI allows interactive advanced statistical tools for non-statistical experts.},
keywords = {biomarkers, Meshes, osteoarthritis, statistics, temporomandibular joint disorders, web-platform},
pubstate = {published},
tppubtype = {article}
}
Bianchi, J; Goncalves, J R; de Oliveira Ruellas, A C; Ashman, L M; Vimort, J-B; Yatabe, M; Paniagua, B; Hernandez, P; Benavides, E; Soki, F N; Loshida, M; Cevidanes, L H S
Quantitative bone imaging biomarkers to diagnose temporomandibular joint osteoarthritis. Journal Article
In: International Journal of Oral and Maxillofacial Surgery, vol. 50, no. 2, pp. 227-235, 2021.
@article{Bianchi2021b,
title = {Quantitative bone imaging biomarkers to diagnose temporomandibular joint osteoarthritis.},
author = {J Bianchi and J R Goncalves and A C de Oliveira Ruellas and L M Ashman and J-B Vimort and M Yatabe and B Paniagua and P Hernandez and E Benavides and F N Soki and M Loshida and L H S Cevidanes},
url = {https://pubmed.ncbi.nlm.nih.gov/32605824/},
doi = {10.1016/j.ijom.2020.04.018},
year = {2021},
date = {2021-02-00},
journal = {International Journal of Oral and Maxillofacial Surgery},
volume = {50},
number = {2},
pages = {227-235},
abstract = {Bone degradation of the condylar surface is seen in temporomandibular joint osteoarthritis (TMJ OA); however, the initial changes occur in the subchondral bone. This cross-sectional study was performed to evaluate 23 subchondral bone imaging biomarkers for TMJ OA. The sample consisted of high-resolution cone beam computed tomography scans of 84 subjects, divided into two groups: TMJ OA (45 patients with TMJ OA) and control (39 asymptomatic subjects). Six regions of each mandibular condyle scan were extracted for computation of five bone morphometric and 18 grey-level texture-based variables. The groups were compared using the Mann-Whitney U-test, and the receiver operating characteristics (ROC) curve was determined for each variable that showed a statically significance difference. The results showed statistically significant differences in the subchondral bone microstructure in the lateral and central condylar regions between the control and TMJ OA groups (P< 0.05). The area under the ROC curve (AUC) for these variables was between 0.620 and 0.710. In conclusion, 13 imaging bone biomarkers presented an acceptable diagnostic performance for the diagnosis of TMJ OA, indicating that the texture and geometry of the subchondral bone microarchitecture may be useful for quantitative grading of the disease.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
L, Michoud; C, Huang; M, Yatabe; J, Bianchi; et al,
A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis. Journal Article
In: Proc SPIE-the Int Soc Opt Eng, vol. 10953, 2019.
@article{Michoud2019,
title = {A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis.},
author = {Michoud L and Huang C and Yatabe M and Bianchi J and et al},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494085/},
doi = {10.1117/12.2506032},
year = {2019},
date = {2019-05-15},
journal = {Proc SPIE-the Int Soc Opt Eng},
volume = {10953},
abstract = {This study presents a web-system repository: Data Storage for Computation and Integration (DSCI) for Osteoarthritis of the temporomandibular joint (TMJ OA). This environment aims to maintain and allow contributions to the database from multi-clinical centers and compute novel statistics for disease classification. For this purpose, imaging datasets stored in the DSCI consisted of three-dimensional (3D) surface meshes of condyles from CBCT, clinical markers and biological markers in healthy and TMJ OA subjects. A clusterpost package was included in the web platform to be able to execute the jobs in remote computing grids. The DSCI application allowed runs of statistical packages, such as the Multivariate Functional Shape Data Analysis to compute global correlations between covariates and the morphological variability, as well as local p-values in the 3D condylar morphology. In conclusion, the DSCI allows interactive advanced statistical tools for non-statistical experts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2021 |
Bianchi, J; Goncalves, J R; de Oliveira Ruellas, A C; Ashman, L M; Vimort, J-B; Yatabe, M; Paniagua, B; Hernandez, P; Benavides, E; Soki, F N; Loshida, M; Cevidanes, L H S: Quantitative bone imaging biomarkers to diagnose temporomandibular joint osteoarthritis.. In: International Journal of Oral and Maxillofacial Surgery, vol. 50, no. 2, pp. 227-235, 2021. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, Adolescents, biomarkers, Cone-beam computed tomography, Cranial base, osteoarthritis, temporomandibular joint)@article{Bianchi2021b, Bone degradation of the condylar surface is seen in temporomandibular joint osteoarthritis (TMJ OA); however, the initial changes occur in the subchondral bone. This cross-sectional study was performed to evaluate 23 subchondral bone imaging biomarkers for TMJ OA. The sample consisted of high-resolution cone beam computed tomography scans of 84 subjects, divided into two groups: TMJ OA (45 patients with TMJ OA) and control (39 asymptomatic subjects). Six regions of each mandibular condyle scan were extracted for computation of five bone morphometric and 18 grey-level texture-based variables. The groups were compared using the Mann-Whitney U-test, and the receiver operating characteristics (ROC) curve was determined for each variable that showed a statically significance difference. The results showed statistically significant differences in the subchondral bone microstructure in the lateral and central condylar regions between the control and TMJ OA groups (P< 0.05). The area under the ROC curve (AUC) for these variables was between 0.620 and 0.710. In conclusion, 13 imaging bone biomarkers presented an acceptable diagnostic performance for the diagnosis of TMJ OA, indicating that the texture and geometry of the subchondral bone microarchitecture may be useful for quantitative grading of the disease. |
2019 |
L, Michoud; C, Huang; M, Yatabe; J, Bianchi; et al,: A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis.. In: Proc SPIE-the Int Soc Opt Eng, vol. 10953, 2019. (Type: Journal Article | Abstract | Links | BibTeX | Tags: biomarkers, Meshes, osteoarthritis, statistics, temporomandibular joint disorders, web-platform)@article{Michoud2019, This study presents a web-system repository: Data Storage for Computation and Integration (DSCI) for Osteoarthritis of the temporomandibular joint (TMJ OA). This environment aims to maintain and allow contributions to the database from multi-clinical centers and compute novel statistics for disease classification. For this purpose, imaging datasets stored in the DSCI consisted of three-dimensional (3D) surface meshes of condyles from CBCT, clinical markers and biological markers in healthy and TMJ OA subjects. A clusterpost package was included in the web platform to be able to execute the jobs in remote computing grids. The DSCI application allowed runs of statistical packages, such as the Multivariate Functional Shape Data Analysis to compute global correlations between covariates and the morphological variability, as well as local p-values in the 3D condylar morphology. In conclusion, the DSCI allows interactive advanced statistical tools for non-statistical experts. |