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Otolaryngology in Clinical Practice: The Necessity of Personalized Medicine
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Otolaryngology in Clinical Practice: The Necessity of Personalized Medicine

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Personalized Therapy in Clinical Medicine".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 1494

Special Issue Editor

Prof. Dr. Jerome Rene Lechien

E-Mail Website
Guest Editor
Department of Otorhinolaryngology and Head and Neck Surgery, CHU de Bruxelles, CHU Saint-Pierre, School of Medicine, 64000 Brussels, Belgium
Interests: otolaryngology; laryngology; oncology; artificial intelligence; reflux disease
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Background:

Otolaryngology-Head and Neck Surgery is confronted with challenges in treatment optimization due to the complex interplay of anatomical, physiological, and histopathological findings of ear, nose, and throat pathologies affecting individual patients' quality of life. Traditional "one-size-fits-all" approaches often yield suboptimal outcomes, highlighting the need for personalized therapeutic strategies.

History:

The field has evolved from standardized protocols to increasingly individualized approaches, initially through clinical phenotyping and biomarker identification. Recent technological advances, especially in artificial intelligence, have accelerated the shift toward precision medicine in otolaryngology.

Aim and Scope:

This Special Issue aims to provide insight into the integration of personalized medicine approaches in otolaryngology-head and neck surgery, emphasizing how patient-specific factors (genetic profiles, environmental influences, comorbidities) can be considered to lead to tailored therapeutic strategies. A particular focus on the synergistic potential of artificial intelligence and machine learning in advancing personalized care can be performed through improved diagnostic accuracy, treatment selection, and outcome prediction.

Cutting-edge Research:

Current innovations include AI-powered imaging analysis for surgical planning, machine learning algorithms for treatment response prediction, personalized tissue engineering, targeted molecular therapies, and the application of big data analytics to identify patient-specific risk factors and optimal intervention timing.

Papers Solicited:

We welcome original research, systematic reviews, and comprehensive reviews dedicated to:

  • AI/ML applications in personalized diagnosis and treatment;
  • Novel biomarker identification and validation studies;
  • Patient-specific outcome prediction models;
  • Precision therapeutics in head and neck surgery;
  • Integration of multi-omics data in personalized care;
  • Real-world implementation of personalized medicine approaches.

Prof. Dr. Jerome Rene Lechien
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • otolaryngology
  • otorhinolaryngology
  • artificial Intelligence
  • personalized Medicine
  • treatments

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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13 pages, 3077 KB  
Article
A Geometric Morphometrics Approach for Predicting Olfactory Region Accessibility: Toward Personalized Nose-to-Brain Drug Delivery
by Priya Vishnumurthy, Thomas Radulesco, Gilles Bouchet, Alain Regard and Justin Michel
J. Pers. Med. 2025, 15(10), 461; https://doi.org/10.3390/jpm15100461 - 30 Sep 2025
Viewed by 152
Abstract
Background: The anatomical variability of the nasal cavity affects intranasal drug delivery, especially to the olfactory region for nose-to-brain treatments. While previous studies used average models or 2D measurements to account for inter-individual variability, 3D shape variation of the region crossed by drug [...] Read more.
Background: The anatomical variability of the nasal cavity affects intranasal drug delivery, especially to the olfactory region for nose-to-brain treatments. While previous studies used average models or 2D measurements to account for inter-individual variability, 3D shape variation of the region crossed by drug particles that target the olfactory area, namely the region of interest (ROI), remains unexplored to our knowledge. Methods: A geometric morphometric analysis was performed on the ROI of 151 unilateral nasal cavities from the CT scans of 78 patients. Ten fixed landmarks and 200 sliding semi-landmarks were digitized, using Viewbox 4.0, and standardized via Generalized Procrustes Analysis. Shape variability was analyzed through Principal Component Analysis. Morphological clusters were identified using Hierarchical Clustering on Principal Components, and characterized with MANOVA, ANOVA, and Tukey tests. Results: Validation tests confirmed the method’s reliability. Three morphological clusters were identified. Variations were significant in the X and Y axes, and minimal in Z. Cluster 1 had a broader anterior cavity with shallower turbinate onset, likely improving olfactory accessibility. Cluster 3 was narrower with deeper turbinates, potentially limiting olfactory accessibility. Cluster 2 was intermediate. Notably, 31.5% of patients had at least one cavity in cluster 1. Conclusions: Three distinct morphotypes of the region of the nasal cavity that potentially influence accessibility were identified. These findings will guide future computational fluid dynamics studies for optimizing nasal drug targeting and represent a practical step toward tailoring nose-to-brain drug delivery strategies in alignment with the principles of personalized medicine. Full article
(This article belongs to the Special Issue Otolaryngology in Clinical Practice: The Necessity of Personalized Medicine)
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11 pages, 814 KB  
Article
Validity and Reliability of the Singer Reflux Symptom Score (sRSS)
by Jérôme R. Lechien
J. Pers. Med. 2025, 15(8), 348; https://doi.org/10.3390/jpm15080348 - 2 Aug 2025
Viewed by 661
Abstract
Objectives: To investigate the reliability and validity of the Singer Reflux Symptom Score (sRSS), a new patient-reported outcome questionnaire documenting the severity of reflux symptoms in singing voice is proposed. Methods: Amateur and professional singers consulting the European Reflux Clinic for [...] Read more.
Objectives: To investigate the reliability and validity of the Singer Reflux Symptom Score (sRSS), a new patient-reported outcome questionnaire documenting the severity of reflux symptoms in singing voice is proposed. Methods: Amateur and professional singers consulting the European Reflux Clinic for laryngopharyngeal reflux disease (LPRD) symptoms and findings were prospectively recruited from January 2022 to February 2023. The diagnosis was based on a Reflux Symptom Score (RSS) > 13 and Reflux Sign Assessment (RSA) > 14. A control group of asymptomatic singer subjects was recruited from the University of Mons. The sRSS was rated within a 7-day period to assess test–retest reliability. Internal consistency was measured using Cronbach’s α in patients and controls. A correlation analysis was performed between sRSS and Singing Voice Handicap Index (sVHI) to evaluate convergent validity. Responsiveness to change was evaluated through pre- to post-treatment sRSS changes. The sRSS threshold for suggesting a significant impact of LPRD on singing voice was determined by receiver operating characteristic (ROC) analysis. Results: Thirty-three singers with suspected LPRD (51.5% female; mean age: 51.8 ± 17.2 years) were consecutively recruited. Difficulty reaching high notes and vocal fatigue were the most prevalent LPRD-related singing complaints. The sRSS demonstrated high internal consistency (Cronbach-α = 0.832), test–retest reliability, and external validity (correlation with sVHI: r = 0.654; p = 0.015). Singers with suspected LPRD reported a significant higher sRSS compared to 68 controls. sRSS item and total scores significantly reduced from pre-treatment to 3 months post-treatment except for the abnormal voice breathiness item. ROC analysis revealed superior diagnostic accuracy for sRSS (AUC = 0.971) compared to sRSS-quality of life (AUC = 0.926), with an optimal cutoff at sRSS > 38.5 (sensitivity: 90.3%; specificity: 85.0%). Conclusions: The sRSS is a reliable and valid singer-reported outcome questionnaire for documenting singing symptoms associated with LPRD leading to personalized management of Singers. Future large-cohort studies are needed to evaluate its specificity for LPRD compared to other vocal fold disorders in singers. Full article
(This article belongs to the Special Issue Otolaryngology in Clinical Practice: The Necessity of Personalized Medicine)
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Other

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15 pages, 1036 KB  
Systematic Review
Computational Fluid Dynamics Approach for Direct Nose-to-Brain Drug Delivery: A Systematic Review and Meta-Analysis
by Priya Vishnumurthy, Thomas Radulesco, Gilles Bouchet, Alain Regard and Justin Michel
J. Pers. Med. 2025, 15(10), 447; https://doi.org/10.3390/jpm15100447 - 24 Sep 2025
Viewed by 430
Abstract
Background/Objectives: Optimizing drug deposition to the olfactory region is key in Nose-to-brain drug delivery strategies. However, findings from computational fluid dynamics (CFD) studies remain inconsistent concerning the parameters influencing olfactory deposition, limiting clinical translation and device optimization. This systematic review aims to [...] Read more.
Background/Objectives: Optimizing drug deposition to the olfactory region is key in Nose-to-brain drug delivery strategies. However, findings from computational fluid dynamics (CFD) studies remain inconsistent concerning the parameters influencing olfactory deposition, limiting clinical translation and device optimization. This systematic review aims to identify robust CFD parameters for optimizing drug delivery to the olfactory region. Methods: A systematic review and meta-analysis were conducted following PRISMA guidelines, selecting studies reporting CFD simulations of nasal drug delivery with evaluation of olfactory deposition efficiency. The primary outcome was the correlation between each CFD parameter and olfactory deposition rate. Parameters included particle size, impaction parameter, flow rate, spray cone angle, insertion angle, injection velocity, head position, release position, and breathing pattern. Data were extracted and standardized, and statistical methods were used to assess correlations, heterogeneity, and potential biases in study results. Results: Smaller particle size (pooled r = −0.42) and lower impaction parameter (r = −0.39) were significantly associated with higher olfactory deposition. No consistent correlation was observed with breathing flow rate. Heterogeneity across studies was high (I2 > 90%). Funnel plots asymmetry suggested potential publication bias in particle-related outcomes. Conclusions: Particle characteristics, especially size and inertia, are the most critical determinants of olfactory deposition in CFD simulations. These findings support design optimization of nasal delivery devices targeting the olfactory region and underscore the need for standardized reporting and validation across CFD studies. Full article
(This article belongs to the Special Issue Otolaryngology in Clinical Practice: The Necessity of Personalized Medicine)
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