Assessing craniofacial growth and form without landmarks: A new automatic approach based on spectral methods.
craniofacial malformation
diagnostic tool
functional maps
landmark-free morphometrics
metopic ridge
morphometrics
skull malformation
spectral analysis
trigonocephaly
Journal
Journal of morphology
ISSN: 1097-4687
Titre abrégé: J Morphol
Pays: United States
ID NLM: 0406125
Informations de publication
Date de publication:
08 2023
08 2023
Historique:
revised:
19
05
2023
received:
17
10
2022
accepted:
29
05
2023
medline:
18
7
2023
pubmed:
17
7
2023
entrez:
17
7
2023
Statut:
ppublish
Résumé
We present a novel method for the morphometric analysis of series of 3D shapes, and demonstrate its relevance for the detection and quantification of two craniofacial anomalies: trigonocephaly and metopic ridges, using CT-scans of young children. Our approach is fully automatic, and does not rely on manual landmark placement and annotations. Our approach furthermore allows to differentiate shape classes, enabling successful differential diagnosis between trigonocephaly and metopic ridges, two related conditions characterized by triangular foreheads. These results were obtained using recent developments in automatic nonrigid 3D shape correspondence methods and specifically spectral approaches based on the functional map framework. Our method can capture local changes in geometric structure, in contrast to methods based, for instance, on global shape descriptors. As such, our approach allows to perform automatic shape classification and provides visual feedback on shape regions associated with different classes of deformations. The flexibility and generality of our approach paves the way for the application of spectral methods in quantitative medicine.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e21609Informations de copyright
© 2023 Wiley Periodicals LLC.
Références
Adams, D. C., Rohlf, F. J., & Slice, D. E. (2004). Geometric morphometrics: Ten years of progress following the ‘revolution’. Italian Journal of Zoology, 71(1), 5-16.
Arnqvist, G., & Mårtensson, T. (1998). Measurement error in geometric morphometrics: Empirical strategies to assess and reduce its impact on measures of shape. Acta Zoologica Academiae Scientiarum Hungaricae, 44, 73-96.
Attaiki, S., Pai, G., & Ovsjanikov, M. (2021). “DPFM: Deep partial functional maps”. In: 2021 International Conference on 3D Vision (3DV). IEEE, pp. 175-185.
Besl, P. J., & McKay, N. D. (1992). Sensor fusion IV: Control paradigms and data structures, Method for registration of 3-D shapes (Vol. 1611, pp. 586-606). Spie.
Bhalodia, R., Dvoracek, L. A., Ayyash, A. M., Kavan, C., Whitaker, R., & Goldstein, J. A. (2020). Quantifying the severity of metopic craniosynostosis: A pilot study application of machine learning in craniofacial surgery. Journal of Craniofacial Surgery, 31(3), 697-701.
Biasotti, S., Cerri, A., Bronstein, A., & Bronstein, N. (2016). Recent trends, applications, and perspectives in 3D shape similarity assessment. Computer Graphics Forum, 35(6), 87-119.
Birgfeld, C. B., Heike, C. L., Al-Mufarrej, F., Oppenheimer, A., & Kamps, S. E. (2019). Practical computed tomography scan findings for distinguishing metopic craniosynostosis from metopic ridging. Plastic and Reconstructive Surgery. Global Open, 7(3):e1944.
Birgfeld, C. B., Saltzman, B. S., Hing, A. V., Heike, C. L., Khanna, P. C., Gruss, J. S., & Hopper, R. A. (2013). Making the diagnosis: Metopic ridge versus metopic craniosynostosis. The Journal of Craniofacial Surgery, 24(1), 178-185.
Bloch, K. (n.d.). “New diagnostic criteria for metopic ridges and trigonocephaly: A 3D geometric approach.” Submitted in Plastic and Reconstructed Surgery.
Bookstein, F. L. (1982). Foundations of morphometrics. Annual Review of Ecology and Systematics, 13(1), 451-470.
Bookstein, F. L. (1997). Morphometric tools for landmark data.
Bookstein, F. L. (2019). Pathologies of between groups principal components analysis in geometric morphometrics. Evolutionary Biology, 46(4), 271-302.
Calandrelli, R., Pilato, F., Massimi, L., Marrazzo, A., Panfili, M., Di Rocco, C., & Colosimo, C (2020). Orbito-facial dysmorphology in patients with different degrees of trigonocephaly severity: Quantitative morpho-volumetric analysis in infants with non-syndromic metopic craniosynostosis. Child's Nervous System: ChNS: Official Journal of the International Society for Pediatric Neurosurgery, 36(6), 1263-1273.
Cho, M.-J., Kane, A. A., Seaward, J. R., & Hallac, R. R. (2016). Metopic “ridge” vs. “craniosynostosis”: Quantifying severity with 3D curvature analysis. Journal of Cranio-MaxilloFacial Surgery: Official Publication of the European Association for Cranio-Maxillo-Facial Surgery, 44(9), 1259-1265.
von Cramon-Taubadel, N., Frazier, B. C., & Lahr, M. M. (2007). The problem of assessing landmark error in geometric morphometrics: Theory, methods, and modifications. American Journal of Physical Anthropology, 134(1), 24-35.
Daboul, A., Ivanovska, T., Bülow, R., Biffar, R., & Cardini, A. (2018). Procrustes-based geometric morphometrics on MRI images: An example of inter-operator bias in 3D landmarks and its impact on big datasets. PLOS One, 13(5):e0197675.
Dyke, R. M., Lai, Y.-K., Rosin, P. L., Zappalà, S., Dykes, S., Guo, D., Li, K., Marin, R., Melzi, S., & Yang, J. (2020). SHREC’20: Shape correspondence with non-isometric deformations. Computers & Graphics, 92, 28-43.
Eisenberger, M., Lahner, Z., & Cremers, D. (2020). “Smooth shells: Multi-scale shape registration with functional maps”. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 12265-12274.
Eisenberger, M., Toker, A., Leal-Taixé, L., & Cremers, D. (2020). “Deep shells: Unsupervised shape correspondence with optimal transport”. In: Advances in Neural Information Processing Systems 33.
Fabre, A.-C., Bardua, C., Bon, M., Clavel, J., Felice, R. N., Streicher, J. W., Bonnel, J., Stanley, E. L., Blackburn, D. C., & Goswami, A. (2020). Metamorphosis shapes cranial diversity and rate of evolution in salamanders. Nature Ecology & Evolution, 4(8), 1129-1140.
Fedorov, A., Beichel, R., Kalpathy-Cramer, J., Finet, J., Fillion-Robin, J. C., Pujol, S., Bauer, C., Jennings, D., Fennessy, F., Sonka, M., Buatti, J., Aylward, S., Miller, J. V., Pieper, S., & Kikinis, R. (2012). 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magnetic Resonance Imaging, 30(9), 1323-1341.
Gillet, A., Frédérich, B., & Parmentier, E. (2019). Divergent evolutionary morphology of the axial skeleton as a potential key innovation in modern cetaceans. Proceedings of the Royal Society B: Biological Sciences, 286(1916):20191771.
Gunz, P., & Mitteroecker, P. (2013). Semilandmarks: a method for quantifying curves and surfaces. Hystrix, the Italian Journal of Mammalogy, 24(1), 103-109.
Huang, R., Achlioptas, P., Guibas, L., & Ovsjanikov, M. (2019). Limit shapes-A tool for understanding shape differences and variability in 3D model collections. Computer Graphics Forum, 38(5), 187-202.
Huang, R., Ren, J., Wonka, P., & Ovsjanikov, M. (2020). Consistent ZoomOut: Efficient spectral map synchronization. Computer Graphics Forum, 39(5), 265-278.
Kellogg, R., Allori, A. C., Rogers, G. F., & Marcus, J. R. (2012). Interfrontal angle for characterization of trigonocephaly: Part 1: Development and validation of a tool for diagnosis of metopic synostosis. The Journal of Craniofacial Surgery, 23(3), 799-804.
Kitchell, L., Bullock, D., Hayashi, S., & Pestilli, F. (2018). Shape analysis of white matter tracts via the Laplace-Beltrami spectrum. Shape in Medical Imaging, 11167, 195-206.
Klein, A., Ghosh, S. S., Bao, F. S., Giard, J., Häme, Y., Stavsky, E., Lee, N., Rossa, B., Reuter, M., Neto, E. C., & Keshavan, A. (2017). Mindboggling morphometry of human brains. PLOS Computational Biology, 13(2), e1005350.
Klingenberg, C. P. (2002). Morphometrics and the role of the phenotype in studies of the evolution of developmental mechanisms. Gene, 287(1-2), 3-10.
Klingenberg, C. P. (2016). Size, shape, and form: Concepts of allometry in geometric morphometrics. Development Genes and Evolution, 226(3), 113-137.
Kolar, J. C., & Salter, E. M. (1997). Preoperative anthropometric dysmorphology in metopic synostosis. American Journal of Physical Anthropology, 103(3), 341-351.
Mallet, C., Cornette, R., Billet, G., & Houssaye, A. (2019). Interspecific variation in the limb long bones among modern rhinoceroses-Extent and drivers. PeerJ, 7, e7647.
Mathijssen, I. M. J., Working Group Guideline Craniosynostosis. (2021). Updated guideline on treatment and management of craniosynostosis. The Journal of Craniofacial Surgery, 32(1), 371-450.
Melzi, S., Mella, A., Squarcina, L., Bellani, M., Perlini, C., Ruggeri, M., Altamura, C. A., Brambilla, P., & Castellani, U. (2016). Functional maps for brain classification on spectral domain. In M. Reuter, C. Wachinger, & H. Lombaert (Eds.), Spectral and shape analysis in medical imaging (pp. 25-35). Springer International Publishing.
Melzi, S., Mella, A., Squarcina, L., Bellani, M., Perlini, C., Ruggeri, M., Altamura, C. A., Brambilla, P., & Castellani, U. (2019). ZoomOut: Spectral upsampling for efficient shape correspondence. ACM Transactions on Graphics, 155, 1-14.
van der Meulen, J., van der Hulst, R., van Adrichem, L., Arnaud, E., Chin-Shong, D., Duncan, C., Habets, E., Hinojosa, J., Mathijissen, I., May, P., Morritt, D., Nishikawa, H., Noons, P., Richardson, D., Wall, S., van der Vlugt, J., & Renier, D. (2009). The increase of metopic synostosis: A pan-European observation. The Journal of Craniofacial Surgery, 20(2), 283-286.
Nguyen, A., Ben-Chen, M., Welnicka, K., Ye, Y., & Guibas, L. (2011). An optimization approach toimproving collections of shape maps. Computer Graphics Forum, 30(5), 1481-1491.
Niethammer, M., Reuter, M., Wolter, F.-E., Bouix, S., Peinecke, N., Koo, M-S., & Shenton, M.E. (2007). Global medical shape analysis using the Laplace-Beltrami spectrum. In N. Ayache, S. Ourselin, & A. Maeder (Eds.), Medical image computing and computer-assisted intervention-MICCAI 2007 (Vol. 4791, pp. 850-857).
Nitzken, M. J., Casanova, M. F., Gimel'farb, G., Inanc, T., Zurada, J. M., & El-Baz, A. (2014). Shape analysis of human brain: A brief survey. IEEE Journal of Biomedical and Health Informatics, 18(4), 1337-1354.
O'Higgins, P., & Jones, N. (1998). Facial growth in cercocebus torquatus: An Application of threedimensional geometric morphometric techniques to the study of morphological variation. Journal of Anatomy, 193(Pt 2), 251-272.
Ovsjanikov, M., Ben-Chen, M., Solomon, J., Butscher, A., & Guibas, L. (2012). Functional maps: A flexible representation of maps between shapes. ACM Transactions on Graphics (TOG), 31(4), 1-11.
Ovsjanikov, M., Corman, E., Bronstein, M., Rodolà, E., Ben-Chen, M., Guibas, L., Chazal, F., & Bronstein, A. (2017). Computing and processing correspondences with functional maps. In ACM GRAPH 2017 Courses (SIGGRAPH '17) (pp. 1-62).
Palci, A., & Lee, M. S. Y. (2019). Geometric morphometrics, homology and cladistics: Review and recommendations. Cladistics, 35(2), 230-242.
Ren, J., Melzi, S., Wonka, P., & Ovsjanikov, M. (2021). Discrete optimization for shape matching. Computer Graphics Forum, 40(5), 81-96.
Ren, J., Poulenard, A., Wonka, P., & Ovsjanikov, M. (2018). Continuous and orientation-preserving correspondences via functional maps. ACM Transactions on Graphics (ToG), 37(6), 1-16.
Reuter, M., Wolter, F.-E., Shenton, M.E., & Niethammer, M. (2009). Laplace-Beltrami eigenvalues and topological features of eigenfunctions for statistical shape analysis. Computer Aided Design, 41(10), 739-755.
Rodolà, E., Cosmo, L., Bronstein, M., Torsello, A., & CremersHide, D. (2017). Partial functional correspondence. Computer Graphics Forum, 36(1), 222-236.
Rustamov, R. M., Ovsjanikov, M., Azencot, O., Ben-Chen, M., Chazal, F., & Guibas, L. J. (2013). Map-based exploration of intrinsic shape differences and variability. ACM Transactions on Graphics, 32(4), 1.
Rutland, J. W., Bellaire, C. P., Yao, A., Arrighi-Allisan, A., Napoli, J. G., Delman, B. N., & Taub, P. J. (2021). The expanding role of geometric morphometrics in craniofacial surgery. Journal of Craniofacial Surgery, 32(3), 1104-1109.
Sahillioğlu, Y. (2020). Recent advances in shape correspondence. The Visual Computer, 36(8), 1705-1721.
Schaufelberger, M., Kühle, R., Wachter, A., Weichel, F., Hagen, N., Ringwald, F., Eisenmann, U., Hoffmann, J., Engel, M., Freudlsperger, C., & Nahm, W. (2022). A radiation-free classification pipeline for craniosynostosis using statistical shape modeling. Diagnostics, 12(7), 1516.
Shishegar, R., Pizzagalli, F., Georgiou-Karistianis, N., Egan, G. F., Jahanshad, N., & Johnston, L. A. (2021). A gyrification analysis approach based on Laplace Beltrami eigenfunction level sets. Neuroimage, 229, 117751.
Slice, D. E. (2007). Geometric morphometrics. Annual Review of Anthropology, 36, 261-281.
Toussaint, N., Redhead, Y., Vidal-García, M., Vercio, L. L., Liu, W., Fisher, E. M. C., Hallgrímsson, B., Tybulewicz, V. L. J., Schnabel, J. A., & Green, J. B. A. (2021). A landmark-free morphometrics pipeline for high-resolution phenotyping: Application to a mouse model of Down syndrome. Development, 148, 18.
Wärmländer, S. K. T. S., Garvin, H., Guyomarc'h, P., Petaros, A., & Sholts, S. B. (2019). Landmark typology in applied morphometrics studies: What's the point. The Anatomical Record, 302(7), 1144-1153.
Watanabe, A., & Slice, D. E. (2014). The utility of cranial ontogeny for phylogenetic inference: A case study in crocodylians using geometric morphometrics. Journal of Evolutionary Biology, 27(6), 1078-1092.
Webster, M. A. R. K., & Sheets, H. D. (2010). A practical introduction to landmark-based geometric morphometrics. The Paleontological Society Papers, 16, 163-188.