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8. Preinterventional Third-Molar Assessment Using Robust Machine Learning

Author

Carvalho, J S, Lotz, M, Rubi, L, Unger, S, Pfister, T, Buhmann, J M, Stadlinger, B; https://orcid.org/0000-0001-5044-7052, Carvalho, J S, Lotz, M, Rubi, L, Unger, S, Pfister, T, Buhmann, J M, and Stadlinger, B; https://orcid.org/0000-0001-5044-7052

Abstract

Machine learning (ML) models, especially deep neural networks, are increasingly being used for the analysis of medical images and as a supporting tool for clinical decision-making. In this study, we propose an artificial intelligence system to facilitate dental decision-making for the removal of mandibular third molars (M3M) based on 2-dimensional orthopantograms and the risk assessment of such a procedure. A total of 4,516 panoramic radiographic images collected at the Center of Dental Medicine at the University of Zurich, Switzerland, were used for training the ML model. After image preparation and preprocessing, a spatially dependent U-Net was employed to detect and retrieve the region of the M3M and inferior alveolar nerve (IAN). Image patches identified to contain a M3M were automatically processed by a deep neural network for the classification of M3M superimposition over the IAN (task 1) and M3M root development (task 2). A control evaluation set of 120 images, collected from a different data source than the training data and labeled by 5 dental practitioners, was leveraged to reliably evaluate model performance. By 10-fold cross-validation, we achieved accuracy values of 0.94 and 0.93 for the M3M-IAN superimposition task and the M3M root development task, respectively, and accuracies of 0.9 and 0.87 when evaluated on the control data set, using a ResNet-101 trained in a semisupervised fashion. Matthew's correlation coefficient values of 0.82 and 0.75 for task 1 and task 2, evaluated on the control data set, indicate robust generalization of our model. Depending on the different label combinations of task 1 and task 2, we propose a diagnostic table that suggests whether additional imaging via 3-dimensional cone beam tomography is advisable. Ultimately, computer-aided decision-making tools benefit clinical practice by enabling efficient and risk-reduced decision-making and by supporting less experienced practitioners before the surgical removal of the M3M.

Published
2023

10. Perturbateurs endocriniens : nouveau facteurs de risque d’arthrose ? Données expérimentales sur modèle murin d’arthrose liée à l’âge

Author

Berkani, S., primary, Kouki, I., additional, Babajko, S., additional, Pigenet, A., additional, Bahieddine, S., additional, Natarajan, P., additional, Ordoukhanian, P., additional, Houard, X., additional, Lotz, M., additional, Demeneix, B., additional, Fini, J.B., additional, Berenbaum, F., additional, Sellam, J., additional, and Courties, A., additional

Published
2022
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17. The TAT protein transduction domain as an intra-articular drug delivery technology

Author

Mailhiot, S. E. (Sarah E.), Thompson, M. A. (Matthew A.), Eguchi, A. E. (Akiko E.), Dinkel, S. E. (Sabrina E.), Lotz, M. K. (Martin K.), Dowdy, S. F. (Steven F.), and June II, R. K. (Ronald K.)

Subjects
musculoskeletal diseases, protein transduction, osteoarthritis, viruses, drug delivery, intra-articular therapeutics, cartilage
Abstract

Objective: Intra-articular drug delivery holds great promise for the treatment of joint diseases such as osteoarthritis. The objective of this study was to evaluate the TAT peptide transduction domain (TAT-PTD) as a potential intra-articular drug delivery technology for synovial joints. Design: Experiments examined the ability of TAT conjugates to associate with primary chondrocytes and alter cellular function both in vitro and in vivo. Further experiments examined the ability of the TAT-PTD to bind to human osteoarthritic cartilage. Results: The results show that the TAT-PTD associates with chondrocytes, is capable of delivering siRNA for chondrocyte gene knockdown, and that the recombinant enzyme TAT-Cre is capable of inducing in vivo genetic recombination within the knee joint in a reporter mouse model. Last, binding studies show that osteoarthritic cartilage preferentially uptakes the TAT-PTD from solution. Conclusions: The results suggest that the TAT-PTD is a promising delivery strategy for intra-articular therapeutics.

Published
2021

36. Molecular subtype, biological sex and age shape melanoma tumour evolution.

Author

Lotz, M., Budden, T., Furney, S.J., and Virós, A.

Subjects
*SEX (Biology), *ENVIRONMENTAL degradation, *GENETIC load, *SOMATIC mutation, *CELL division, *RADIATION damage, *CYCLIN-dependent kinase inhibitor-2A, *MELANOMA
Abstract

Summary: Background: Many cancer types display sex and age disparity in incidence and outcome. The mutational load of tumours, including melanoma, varies according to sex and age. However, there are no tools to explore systematically whether clinical variables such as age and sex determine the genomic landscape of cancer. Objectives: To establish a mathematical approach using melanoma mutational data to analyse how sex and age shape the tumour genome. Methods: We model how age‐related (clock‐like) somatic mutations that arise during cell division, and extrinsic (environmental ultraviolet radiation) mutations accumulate in cancer genomes. Results: Melanoma is driven primarily by cell‐intrinsic age‐related mutations and extrinsic ultraviolet radiation‐induced mutations, and we show that these mutation types differ in magnitude and chronology and by sex in the distinct molecular melanoma subtypes. Our model confirms that age and sex are determinants of cellular mutation rate, shaping the final mutation composition. We show mathematically for the first time how, similarly to noncancer tissues, melanoma genomes reflect a decline in cell division during ageing. We find that clock‐like mutations strongly correlate with the acquisition of ultraviolet‐induced mutations, but critically, men present a higher number and rate of cell‐division‐linked mutations. Conclusions: These data indicate that the contribution of environmental damage to melanoma likely extends beyond genetic damage to affect cell division. Sex and age determine the final mutational composition of melanoma. What is already known about this topic? Cancer incidence and mortality are influenced by sex and age.Melanoma is more frequent in men, and the incidence and mortality rise with increasing age.The main mutations driving melanoma are linked predominantly to ultraviolet (UV) radiation damage and to errors accumulated in the DNA after each cell division, which are unrepaired.These clock‐like mutations linked to cell division accumulate steadily over time in both healthy tissue and cancers. What does this study add? Clock and UV mutations are tightly correlated and arise in melanoma as a function of age and sex.The molecular subtypes have a distinct pattern and rate of UV and clock mutations, and clock mutations depend on the amount of UV damage.The rate of clock mutations decreases as individuals age, reflecting a decrease in tissue proliferation during ageing.Men have more clock mutations, which reflect a distinct proliferation rate. What is the translational message? This study indicates that age and sex shape the rate of mutations observed in melanoma.The burden of mutation affects response to novel immunotherapies, so this work supports the rationale to stratify patients by their mutational landscape, age and sex to discriminate possible responders most easily.These data can better inform public health prevention campaigns. Linked Comment: Toland. Br J Dermatol 2021; 184:197–198. [ABSTRACT FROM AUTHOR]

Published
2021
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38. THU0030 Molecular mechanisms of autophagic memory in pathogenic t cells in human rheumatoid arthritis

Author

Kumar, P., primary, Leong, J.Y., additional, Saidin, S., additional, Paleja, B., additional, Loosdregt, J.V., additional, Chua, C., additional, Arkachaisri, T., additional, Consolaro, A., additional, Gattorno, M., additional, Martini, A., additional, Williams, G.W., additional, Pischel, K.D, additional, Lotz, M., additional, and Albani, S., additional

Published
2018
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