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169 results on '"Vandersteen, Clair"'

4. A Deep Learning based Fast Signed Distance Map Generation

Author

Wang, Zihao, Vandersteen, Clair, Demarcy, Thomas, Gnansia, Dan, Raffaelli, Charles, Guevara, Nicolas, and Delingette, Hervé

Subjects
Computer Science - Graphics, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Signed distance map (SDM) is a common representation of surfaces in medical image analysis and machine learning. The computational complexity of SDM for 3D parametric shapes is often a bottleneck in many applications, thus limiting their interest. In this paper, we propose a learning based SDM generation neural network which is demonstrated on a tridimensional cochlea shape model parameterized by 4 shape parameters. The proposed SDM Neural Network generates a cochlea signed distance map depending on four input parameters and we show that the deep learning approach leads to a 60 fold improvement in the time of computation compared to more classical SDM generation methods. Therefore, the proposed approach achieves a good trade-off between accuracy and efficiency.

Published
2020

6. Robust Cochlear Modiolar Axis Detection in CT

Author

Wimmer, Wilhelm, Vandersteen, Clair, Guevara, Nicolas, Caversaccio, Marco, and Delingette, Hervé

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

The cochlea, the auditory part of the inner ear, is a spiral-shaped organ with large morphological variability. An individualized assessment of its shape is essential for clinical applications related to tonotopy and cochlear implantation. To unambiguously reference morphological parameters, reliable recognition of the cochlear modiolar axis in computed tomography (CT) images is required. The conventional method introduces measurement uncertainties, as it is based on manually selected and difficult to identify landmarks. Herein, we present an algorithm for robust modiolar axis detection in clinical CT images. We define the modiolar axis as the rotation component of the kinematic spiral motion inherent in the cochlear shape. For surface fitting, we use a compact shape representation in a 7-dimensional kinematic parameter space based on extended Pl\"ucker coordinates. It is the first time such a kinematic representation is used for shape analysis in medical images. Robust surface fitting is achieved with an adapted approximate maximum likelihood method assuming a Student-t distribution, enabling axis detection even in partially available surface data. We verify the algorithm performance on a synthetic data set with cochlear surface subsets. In addition, we perform an experimental study with four experts in 23 human cochlea CT data sets to compare the automated detection with the manually found axes. Axes found from co-registered high resolution micro-CT scans are used for reference. Our experiments show that the algorithm reduces the alignment error providing more reliable modiolar axis detection for clinical and research applications., Comment: Accepted for MICCAI 2019

Published
2019

9. One-Shot Learning for Landmarks Detection

Author

Wang, Zihao, Vandersteen, Clair, Raffaelli, Charles, Guevara, Nicolas, Patou, François, Delingette, Hervé, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Engelhardt, Sandy, editor, Oksuz, Ilkay, editor, Zhu, Dajiang, editor, Yuan, Yixuan, editor, Mukhopadhyay, Anirban, editor, Heller, Nicholas, editor, Huang, Sharon Xiaolei, editor, Nguyen, Hien, editor, Sznitman, Raphael, editor, and Xue, Yuan, editor

Published
2021
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11. Study protocol: the biologics in severe chronic rhinosinusitis with nasal polyps survey

Author

Favier, Valentin, primary, Daveau, Clémentine, additional, Carsuzaa, Florent, additional, Fieux, Maxime, additional, Vandersteen, Clair, additional, Castillo, Laurent, additional, Papon, Jean Francois, additional, de Gabory, Ludovic, additional, Saroul, Nicolas, additional, Verillaud, Benjamin, additional, Rumeau, Cécile, additional, Jankowski, Roger, additional, Michel, Justin, additional, de Bonnecaze, Guillaume, additional, Lecanu, Jean-Baptiste, additional, Coste, Andre, additional, Béquignon, Emilie, additional, Malard, Olivier, additional, and Mortuaire, Geoffrey, additional

Published
2024
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12. A decision-making algorithm for remote digital assessments of Alzheimer’s Disease

Author

Manera, Valeria, primary, Vandersteen, Clair, additional, Plonka, Alexandra, additional, Lafontaine, Constance, additional, Galery, Kevin, additional, Derreumaux, Alexandre, additional, Ben Gaied, Nouha, additional, Mouton, Aurélie, additional, Sacco, Guillaume, additional, Launay, Cyrille, additional, Guérin, Olivier, additional, Robert, Philippe, additional, Allali, Gilles, additional, Sawchuk, Kim, additional, Beauchet, Olivier, additional, and Gros, Auriane, additional

Published
2024
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16. Deep Learning Based Metal Artifacts Reduction in Post-operative Cochlear Implant CT Imaging

Author

Wang, Zihao, Vandersteen, Clair, Demarcy, Thomas, Gnansia, Dan, Raffaelli, Charles, Guevara, Nicolas, Delingette, Hervé, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Shen, Dinggang, editor, Liu, Tianming, editor, Peters, Terry M., editor, Staib, Lawrence H., editor, Essert, Caroline, editor, Zhou, Sean, editor, Yap, Pew-Thian, editor, and Khan, Ali, editor

Published
2019
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20. Pilot Study on the Use of Untargeted Metabolomic Fingerprinting of Liquid-Cytology Fluids as a Diagnostic Tool of Malignancy for Thyroid Nodules

Author

D’Andréa, Grégoire, primary, Jing, Lun, additional, Peyrottes, Isabelle, additional, Guigonis, Jean-Marie, additional, Graslin, Fanny, additional, Lindenthal, Sabine, additional, Sanglier, Julie, additional, Gimenez, Isabel, additional, Haudebourg, Juliette, additional, Vandersteen, Clair, additional, Bozec, Alexandre, additional, Guevara, Nicolas, additional, and Pourcher, Thierry, additional

Published
2023
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21. Alzheimer's early detection in post-acute COVID-19 syndrome: a systematic review and expert consensus on preclinical assessments

Author

Vandersteen, Clair, primary, Plonka, Alexandra, additional, Manera, Valeria, additional, Sawchuk, Kim, additional, Lafontaine, Constance, additional, Galery, Kevin, additional, Rouaud, Olivier, additional, Bengaied, Nouha, additional, Launay, Cyrille, additional, Guérin, Olivier, additional, Robert, Philippe, additional, Allali, Gilles, additional, Beauchet, Olivier, additional, and Gros, Auriane, additional

Published
2023
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22. Uncertainty Quantification of Cochlear Implant Insertion from CT Images

Author

Demarcy, Thomas, Vandersteen, Clair, Raffaelli, Charles, Gnansia, Dan, Guevara, Nicolas, Ayache, Nicholas, Delingette, Hervé, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Shekhar, Raj, editor, Wesarg, Stefan, editor, González Ballester, Miguel Ángel, editor, Drechsler, Klaus, editor, Sato, Yoshinobu, editor, Erdt, Marius, editor, Linguraru, Marius George, editor, and Oyarzun Laura, Cristina, editor

Published
2016
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26. Application of machine learning methods to guide patient management by predicting the risk of malignancy of Bethesda III-V thyroid nodules

Author

D’Andréa, Grégoire, primary, Gal, Jocelyn, additional, Mandine, Loïc, additional, Dassonville, Olivier, additional, Vandersteen, Clair, additional, Guevara, Nicolas, additional, Castillo, Laurent, additional, Poissonnet, Gilles, additional, Culié, Dorian, additional, Elaldi, Roxane, additional, Sarini, Jérôme, additional, Decotte, Anne, additional, Renaud, Claire, additional, Vergez, Sébastien, additional, Schiappa, Renaud, additional, Chamorey, Emmanuel, additional, Château, Yann, additional, and Bozec, Alexandre, additional

Published
2023
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28. Anatomical Variations of the Human Cochlea Using an Image Analysis Tool

Author

Hussain, Raabid, primary, Frater, Attila, additional, Calixto, Roger, additional, Karoui, Chadlia, additional, Margeta, Jan, additional, Wang, Zihao, additional, Hoen, Michel, additional, Delingette, Herve, additional, Patou, François, additional, Raffaelli, Charles, additional, Vandersteen, Clair, additional, and Guevara, Nicolas, additional

Published
2023
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29. A Web-Based Automated Image Processing Research Platform for Cochlear Implantation-Related Studies

Author

Margeta, Jan, primary, Hussain, Raabid, additional, López Diez, Paula, additional, Morgenstern, Anika, additional, Demarcy, Thomas, additional, Wang, Zihao, additional, Gnansia, Dan, additional, Martinez Manzanera, Octavio, additional, Vandersteen, Clair, additional, Delingette, Hervé, additional, Buechner, Andreas, additional, Lenarz, Thomas, additional, Patou, François, additional, and Guevara, Nicolas, additional

Published
2022
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32. Pilot Study on the Use of Untargeted Metabolomic Fingerprinting of Liquid-Cytology Fluids as a Diagnostic Tool of Malignancy for Thyroid Nodules.

Author

D'Andréa, Grégoire, Jing, Lun, Peyrottes, Isabelle, Guigonis, Jean-Marie, Graslin, Fanny, Lindenthal, Sabine, Sanglier, Julie, Gimenez, Isabel, Haudebourg, Juliette, Vandersteen, Clair, Bozec, Alexandre, Guevara, Nicolas, and Pourcher, Thierry

Subjects
THYROID cancer, METABOLOMIC fingerprinting, NEEDLE biopsy, PILOT projects, PAPILLARY carcinoma
Abstract

Although it is the gold standard for assessing the malignancy of thyroid nodules (TNs) preoperatively, the cytological analysis of fine-needle aspiration cytology (FNAC) samples results in 20–30% of cases in indeterminate lesions (ITNs). As two-thirds of these lesions will appear benign after diagnostic surgery, improved preoperative diagnostic methods need to be developed. In this pilot study, we evaluate if the metabolomic profiles of liquid-based (CytoRich®) FNAC samples of benign and malignant nodules can allow the molecular diagnosis of TNs. We performed untargeted metabolomic analyses with CytoRich® FNAC in a monocentric retrospective study. The cohort was composed of cytologically benign TNs, histologically benign or papillary thyroid carcinomas (PTCs) cytologically ITNs, and suspicious/malignant TNs histologically confirmed as PTCs. The diagnostic performance of the identified metabolomic signature was assessed using several supervised classification methods. Seventy-eight patients were enrolled in the study. We identified 7690 peaks, of which 2697 ions were included for further analysis. We selected a metabolomic signature composed of the top 15 metabolites. Among all the supervised classification methods, the supervised autoencoder deep neural network exhibited the best performance, with an accuracy of 0.957 (0.842–1), an AUC of 0.945 (0.833–1), and an F1 score of 0.947 (0.842–1). Here, we report a promising new ancillary molecular technique to differentiate PTCs from benign TNs (including among ITNs) based on the metabolomic signature of FNAC sample fluids. Further studies with larger cohorts are now needed to identify a larger number of biomarkers and obtain more robust signatures. [ABSTRACT FROM AUTHOR]

Published
2023
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33. Evaluation of the Cognitive Function of Adults with Severe Hearing Loss Pre- and Post-Cochlear Implantation Using Verbal Fluency Testing.

Author

Baranger, Manon, Manera, Valeria, Sérignac, Chloé, Derreumaux, Alexandre, Cancian, Elisa, Vandersteen, Clair, Gros, Auriane, and Guevara, Nicolas

Subjects
VERBAL behavior testing, HEARING disorders, LEXICAL access, COGNITIVE ability, COGNITIVE testing, COCHLEAR implants, AUDITORY perception, DEAFNESS
Abstract

Hearing loss is a major public health problem with significant evidence correlating it with cognitive performance. Verbal fluency tests are commonly used to assess lexical access. They provide a great deal of information about a subject's cognitive function. The aim of our study was to evaluate phonemic and semantic lexical access abilities in adults with bilateral severe to profound hearing loss and then to re-evaluate a cohort after cochlear implantation. 103 adult subjects underwent phonemic and semantic fluency tests during a cochlear implant candidacy evaluation. Of the total 103 subjects, 43 subjects underwent the same tests at 3 months post-implantation. Our results showed superior performance in phonemic fluency compared to semantic fluency in subjects prior to implantation. Phonemic fluency was positively correlated with semantic fluency. Similarly, individuals with congenital deafness had better semantic lexical access than individuals with acquired deafness. Results at 3 months post-implantation showed an improvement in phonemic fluency. No correlation was found between the evolution of pre- and post-implant fluency and the auditory gain of the cochlear implant, and we found no significant difference between congenital and acquired deafness. Our study shows an improvement in global cognitive function after cochlear implantation without differentiation of the phonemic-semantic pathway. [ABSTRACT FROM AUTHOR]

Published
2023
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34. Induction chemotherapy-based larynx preservation program for locally advanced hypopharyngeal cancer: oncologic and functional outcomes and prognostic factors

Author

Bozec, Alexandre, Benezery, Karen, Ettaiche, Marc, Chamorey, Emmanuel, Vandersteen, Clair, Dassonville, Olivier, Poissonnet, Gilles, Riss, Jean-Christophe, Hannoun-Lévi, Jean-Michel, Chand, Marie-Eve, Leysalle, Axel, Saada, Esma, Guigay, Joël, Sudaka, Anne, Demard, François, Santini, José, and Peyrade, Frédéric

Published
2016
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35. Nutritional status and feeding-tube placement in patients with locally advanced hypopharyngeal cancer included in an induction chemotherapy-based larynx preservation program

Author

Bozec, Alexandre, Benezery, Karen, Chamorey, Emmanuel, Ettaiche, Marc, Vandersteen, Clair, Dassonville, Olivier, Poissonnet, Gilles, Riss, Jean-Christophe, Hannoun-Lévi, Jean-Michel, Chand, Marie-Eve, Leysalle, Axel, Saada, Esma, Sudaka, Anne, Haudebourg, Juliette, Hebert, Christophe, Falewee, Marie-Noelle, Demard, François, Santini, José, and Peyrade, Frédéric

Published
2016
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38. Olfactory Training in Post-COVID-19 Persistent Olfactory Disorders: Value Normalization for Threshold but Not Identification

Author

Vandersteen, Clair, primary, Payne, Magali, additional, Dumas, Louise-Émilie, additional, Cancian, Élisa, additional, Plonka, Alexandra, additional, D’Andréa, Grégoire, additional, Chirio, David, additional, Demonchy, Élisa, additional, Risso, Karine, additional, Askenazy-Gittard, Florence, additional, Savoldelli, Charles, additional, Guevara, Nicolas, additional, Robert, Philippe, additional, Castillo, Laurent, additional, Manera, Valeria, additional, and Gros, Auriane, additional

Published
2022
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39. A Web-Based Automated Image Processing Research Platform for Cochlear Implantation-Related Studies

Author

Margeta, Jan, Hussain, Raabid, López Diez, Paula, Morgenstern, Anika, Demarcy, Thomas, Wang, Zihao, Gnansia, Dan, Martinez Manzanera, Octavio, Vandersteen, Clair, Delingette, Hervé, Buechner, Andreas, Lenarz, Thomas, Patou, François, Guevara, Nicolas, Margeta, Jan, Hussain, Raabid, López Diez, Paula, Morgenstern, Anika, Demarcy, Thomas, Wang, Zihao, Gnansia, Dan, Martinez Manzanera, Octavio, Vandersteen, Clair, Delingette, Hervé, Buechner, Andreas, Lenarz, Thomas, Patou, François, and Guevara, Nicolas

Abstract

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.

Published
2022

40. Application of machine learning methods to guide patient management by predicting the risk of malignancy of Bethesda III-V thyroid nodules.

Author

D'Andréa, Grégoire, Gal, Jocelyn, Mandine, Loïc, Dassonville, Olivier, Vandersteen, Clair, Guevara, Nicolas, Castillo, Laurent, Poissonnet, Gilles, Culié, Dorian, Elaldi, Roxane, Sarini, Jérôme, Decotte, Anne, Renaud, Claire, Vergez, Sébastien, Schiappa, Renaud, Chamorey, Emmanuel, Château, Yann, and Bozec, Alexandre

Abstract

Objective: Indeterminate thyroid nodules (ITN) are common and often lead to (sometimes unnecessary) diagnostic surgery. We aimed to evaluate the performance of two machine learning methods (ML), based on routinely available features to predict the risk of malignancy (RM) of ITN. Design: Multi-centric diagnostic retrospective cohort study conducted between 2010 and 2020. Methods: Adult patients who underwent surgery for at least one Bethesda III-V thyroid nodule (TN) with fully available medical records were included. Of the 7917 records reviewed, eligibility criteria were met in 1288 patients with 1335 TN. Patients were divided into training (940 TN) and validation cohort (395 TN). The diagnostic performance of a multivariate logistic regression model (LR) and its nomogram, and a random forest model (RF) in predicting the nature and RM of a TN were evaluated. All available clinical, biological, ultrasound, and cytological data of the patients were collected and used to construct the two algorithms. Results: There were 253 (19%), 693 (52%), and 389 (29%) TN classified as Bethesda III, IV, and V, respectively, with an overall RM of 35%. Both cohorts were well-balanced for baseline characteristics. Both models were validated on the validation cohort, with performances in terms of specificity, sensitivity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve of 90%, 57.3%, 73.4%, 81.4%, 84% (CI95%: 78.5%-89.5%) for the LR model, and 87.6%, 54.7%, 68.1%, 80%, 82.6% (CI95%: 77.4%-87.9%) for the RF model, respectively. Conclusions: Our ML models performed well in predicting the nature of Bethesda III-V TN. In addition, our freely available online nomogram helped to refine the RM, identifying low-risk TN that may benefit from surveillance in up to a third of ITN, and thus may reduce the number of unnecessary surgeries. [ABSTRACT FROM AUTHOR]

Published
2023
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41. Correlations between Persistent Olfactory and Semantic Memory Disorders after SARS-CoV-2 Infection

Author

Fiorentino, Julie, primary, Payne, Magali, additional, Cancian, Elisa, additional, Plonka, Alexandra, additional, Dumas, Louise-Émilie, additional, Chirio, David, additional, Demonchy, Élisa, additional, Risso, Karine, additional, Askenazy-Gittard, Florence, additional, Guevara, Nicolas, additional, Castillo, Laurent, additional, Robert, Philippe, additional, Manera, Valeria, additional, Vandersteen, Clair, additional, and Gros, Auriane, additional

Published
2022
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44. Olfactory identification disorders due to Alzheimer's disease: a new test from France to Quebec

Author

Payne, Magali, Manera, Valeria, Robert, Philippe, Vandersteen, Clair, Beauchet, Olivier, Galery, Kevin, Sacco, Guillaume, Fabre, Roxane, Gros, Auriane, and Lee Kong Chian School of Medicine (LKCMedicine)

Subjects
Alzheimer Disease, Medicine [Science], Smelling Disorder
Abstract

Olfactory identification disorder is regarded as an early marker of Alzheimer's disease (AD) and of similar diagnostic significance of biological or cognitive markers. Premature damage of the entorhinal olfactory cortex, the hippocampus and the orbitofrontal cortex characterize AD and suggest a specific impairment of olfactory identification. The use of psychophysical olfactory identification tests in clinical diagnostic practice is therefore strongly recommended, but not required. As these widespread tests are rarely used, an innovative test, adapted to this target group has been developed. It has been used and validated in a routine care protocol at different Memory Centers in France and in Quebec, Canada. A total of 157 participants were recruited: including 63 Alzheimer's patients and 94 healthy controls. The test was composed of 14 odorants diluted into 4 different concentrations. A computer interface generated randomization of 6 odors per participant and the automatic calculation of identification scores, of perceptual thresholds and of composite scores. All participants underwent a Mini Mental Scale Examination within the previous three months or on the same day of the olfactory test. The Alzheimer's patients had a score between 20 and 30 and healthy controls participants had a score above 28 without any loss of points on recalled items. The results show that our olfactory identification test is able to significantly differentiate Alzheimer's patients from healthy controls (p < 0.001), and to distinguish the French population tested from the Quebec population (p < 0.001). This study highlights an olfactory identification disorder as a target for early diagnosis of AD. Its cultural qualities make it a potential candidate for differentiated calibration between France and Quebec. Published version

Published
2022

45. OLFACTORY TRAINING EFFICIENCY IN POST-COVID-19 PERSISTENT OLFACTORY DISORDERS

Author

Vandersteen, Clair, primary, Payne, Magali, additional, Dumas, Louise-Émilie, additional, Cancian, Élisa, additional, Plonka, Alexandra, additional, D’Andrea, Grégoire, additional, Chirio, David, additional, Demonchy, Élisa, additional, Risso, Karine, additional, Askenazy-Gittard, Florence, additional, Savoldelli, Charles, additional, Guevara, Nicolas, additional, Robert, Philippe, additional, Castillo, Laurent, additional, Manera, Valeria, additional, and Gros, Auriane, additional

Published
2022
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48. What about using sniffin’ sticks 12 items test to screen post-COVID-19 olfactory disorders?

Author

Vandersteen, Clair, primary, Payne, Magali, additional, Dumas, Louise-Émilie, additional, Plonka, Alexandra, additional, D’Andréa, Grégoire, additional, Chirio, David, additional, Demonchy, Élisa, additional, Risso, Karine, additional, Robert, Philippe, additional, Fernandez, Xavier, additional, Askenazy-Gittard, Florence, additional, Savoldelli, Charles, additional, Guevara, Nicolas, additional, Castillo, Laurent, additional, Manera, Valeria, additional, and Gros, Auriane, additional

Published
2021
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49. A Concomitant Allergic Fungal Otomastoiditis with an Allergic Fungal Rhinosinusitis

Author

Vandersteen Clair, Johanna Pradelli, Grégoire D’andrea, Elisabeth Lanteri, Laurent Tardivet, Charles Savoldelli, and Nicolas Guevara

Subjects
medicine.medical_specialty, Aspergillus, Meatus, biology, business.industry, medicine.medical_treatment, Cholesteatoma, Mastoidectomy, medicine.disease, biology.organism_classification, Mucus, Dermatology, medicine.anatomical_structure, Concomitant, otorhinolaryngologic diseases, Middle ear, medicine, Allergic bronchopulmonary aspergillosis, business
Abstract

Background: Allergic fungal otomastoiditis is a rare ear condition characterized by the presence of a specific middle ear mucus usually found in allergic bronchopulmonary aspergillosis. Methods: We report a case of concomitant allergic fungal otomastoiditis and rhinosinusitis in an immunocompetent 27-year-old man complaining of right otorrhea and nasal discharge for 6 months resistant to any medical treatment. Examination revealed a sticky mucus arising from a polypoid middle ear associated with a right middle meatus purulent discharge. Surgical treatment revealed no cholesteatoma but thick yellowish mucus and a fungal ball, as targeted by imaging, both of which containing Aspergillus species. Result: The patient received short postoperative systemic corticotherapy and showed no recurrence 6 months after. Discussion: Allergic fungal otomastoidis should be considered in the face of a sticky mucus arising from perforated chronic otitis, especially when associated with allergic fungal rhinosinusitis. Complete surgical debridement is essential.

Published
2020

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