Clair VANDERSTEEN

Dr. Clair VANDERSTEEN

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2018 in Journal of Stomatology Oral and Maxillofacial Surgery
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Journal Article
Closed access
Charles SavoldelliCharles Savoldelli
Charles Savoldelli
CVClair VANDERSTEEN
Clair VANDERSTEEN
ODolivier dassonville
olivier dassonville
JSJ. Santini
J. Santini

9 November 2022 in Journal of Clinical Medicine
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Journal Article
Open access
PDF file
JMJan Margeta
Jan Margeta
RHRaabid Hussain
Raabid Hussain
PDPaula López Diez
Paula López Diez
AMAnika Morgenstern
Anika Morgenstern
TDThomas Demarcy
Thomas Demarcy
Nicolas GuevaraNicolas Guevara
Nicolas Guevara
The robust delineation of the cochlea and its inner structures combined with the detection of the electrode of a cochlear implant within these structures is essential for envisaging a safer, more individualized, routine image-guided cochlear implant therapy. We present Nautilus—a web-based research platform for automated pre- and post-implantation cochlear analysis. Nautilus delineates cochlear structures from pre-operative clinical CT images by combining deep learning and Bayesian inference approaches. It enables the extraction of electrode locations from a post-operative CT image using convolutional neural networks and geometrical inference. By fusing pre- and post-operative images, Nautilus is able to provide a set of personalized pre- and post-operative metrics that can serve the exploration of clinically relevant questions in cochlear implantation therapy. In addition, Nautilus embeds a self-assessment module providing a confidence rating on the outputs of its pipeline. We present a detailed accuracy and robustness analyses of the tool on a carefully designed dataset. The results of these analyses provide legitimate grounds for envisaging the implementation of image-guided cochlear implant practices into routine clinical workflows.

Verified
Journal Article
Open access
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CVClair VANDERSTEEN
Clair VANDERSTEEN
MPMagali Payne
Magali Payne
LDLouise-Émilie Dumas
Louise-Émilie Dumas
ÉCÉlisa Cancian
Élisa Cancian
APAlexandra Plonka
Alexandra Plonka
Auriane GrosAuriane Gros
Auriane Gros
(1) Background: Persistent post-viral olfactory disorders (PPVOD) are estimated at 30% of patients one year after COVID-19 infection. No treatment is, to date, significantly effective on PPVOD with the exception of olfactory training (OT). The main objective of this work was to evaluate OT efficiency on post-COVID-19 PPVOD. (2) Methods: Consecutive patients consulting to the ENT department with post-COVID-19 PPVOD were included after completing clinical examination, the complete Sniffin’ Stick Test (TDI), the short version of the Questionnaire of olfactory disorders and the SF-36. Patients were trained to practice a self-olfactory training with a dedicated olfactory training kit twice a day for 6 months before returning to undergo the same assessments. (3) Results: Forty-three patients were included and performed 3.5 months of OT in average. We observed a significant TDI score improvement, increasing from 24.7 (±8.9) before the OT to 30.9 (±9.8) (p < 0.001). Based on normative data, a significant increase in the number of normosmic participants was observed only for the threshold values (p < 0.001). Specific and general olfaction-related quality of life improved after the OT. (4) Conclusions: Olfactory function appeared to improve only in peripheral aspects of post-COVID-19 PPVOD after OT. Future controlled studies must be performed to confirm the OT role and justify new therapeutic strategies that may focus on the central aspects of post-COVID-19 PPVOD.

8 January 2023 in Journal of Clinical Medicine
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Journal Article
Open access
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RHRaabid Hussain
Raabid Hussain
AFAttila Frater
Attila Frater
RCRoger Calixto
Roger Calixto
CKchadlia karoui
chadlia karoui
JMJan Margeta
Jan Margeta
Nicolas GuevaraNicolas Guevara
Nicolas Guevara
Understanding cochlear anatomy is crucial for developing less traumatic electrode arrays and insertion guidance for cochlear implantation. The human cochlea shows considerable variability in size and morphology. This study analyses 1000+ clinical temporal bone CT images using a web-based image analysis tool. Cochlear size and shape parameters were obtained to determine population statistics and perform regression and correlation analysis. The analysis revealed that cochlear morphology follows Gaussian distribution, while cochlear dimensions A and B are not well-correlated to each other. Additionally, dimension B is more correlated to duct lengths, the wrapping factor and volume than dimension A. The scala tympani size varies considerably among the population, with the size generally decreasing along insertion depth with dimensional jumps through the trajectory. The mean scala tympani radius was 0.32 mm near the 720° insertion angle. Inter-individual variability was four times that of intra-individual variation. On average, the dimensions of both ears are similar. However, statistically significant differences in clinical dimensions were observed between ears of the same patient, suggesting that size and shape are not the same. Harnessing deep learning-based, automated image analysis tools, our results yielded important insights into cochlear morphology and implant development, helping to reduce insertion trauma and preserving residual hearing.

1 January 2021 in European Annals of Otorhinolaryngology, Head and Neck Diseases
Verified
Journal Article
Closed access
CVClair VANDERSTEEN
Clair VANDERSTEEN
LCL. Castillo
L. Castillo
CRC. Roger
C. Roger
CSC. Savoldelli
C. Savoldelli
NGN. Guevara
N. Guevara

30 October 2021 in European Archives of Oto-Rhino-Laryngology
Verified
Journal Article
Closed access
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CVClair VANDERSTEEN
Clair VANDERSTEEN
MPMagali Payne
Magali Payne
LDLouise-Émilie Dumas
Louise-Émilie Dumas
APAlexandra Plonka
Alexandra Plonka
GDGrégoire D’aNdréa
Grégoire D’aNdréa
AGAuriane Gros
Auriane Gros