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CTRI Number  CTRI/2026/03/105664 [Registered on: 09/03/2026] Trial Registered Prospectively
Last Modified On: 06/03/2026
Post Graduate Thesis  Yes 
Type of Trial  Interventional 
Type of Study   Medical Device
Diagnostic
Screening 
Study Design  Other 
Public Title of Study   A Study on How Artificial Intelligence Can Help Doctors Identify Voice Box Diseases Earlier. 
Scientific Title of Study   Strategic Implementation of Artificial Intelligence in Diagnosing Laryngeal Diseases 
Trial Acronym  Nil 
Secondary IDs if Any  
Secondary ID  Identifier 
NIL  NIL 
 
Details of Principal Investigator or overall Trial Coordinator (multi-center study)  
Name  Neha Chaudhary  
Designation   
Affiliation  GSVM MEDICAL COLLEGE KANPUR  
Address  Department of Otorhinolaryngology Ganesh Shankar Vidyarthi Memorial Medical College ENT Department Lala Lajpat Rai Hospital Campus Kanpur, Uttar Pradesh, India

Kanpur Nagar
UTTAR PRADESH
208002
India 
Phone  8077785858  
Fax    
Email  cneha620@gmail.com  
 
Details of Contact Person
Scientific Query  
Name  Neha Chaudhary  
Designation  Junior resident  
Affiliation  GSVM MEDICAL COLLEGE KANPUR  
Address  GSVM MEDICAL COLLEGE KANPUR

Kanpur Nagar
UTTAR PRADESH
208002
India 
Phone  8077785858  
Fax    
Email  cneha620@gmail.com  
 
Details of Contact Person
Public Query  
Name  Neha Chaudhary  
Designation   
Affiliation  GSVM MEDICAL COLLEGE KANPUR  
Address  Department of Otorhinolaryngology Ganesh Shankar Vidyarthi Memorial Medical College ENT Department Lala Lajpat Rai Hospital Campus Kanpur, Uttar Pradesh, India

Kanpur Nagar
UTTAR PRADESH
208002
India 
Phone  8077785858  
Fax    
Email  cneha620@gmail.com  
 
Source of Monetary or Material Support  
ICMR-MD/MS THESIS SUPPORT PROGRAM Department of health ministry New Delhi India 
 
Primary Sponsor  
Name  Neha Chaudhary  
Address  GSVM MEDICAL COLLEGE KANPUR Uttar Pradesh India  
Type of Sponsor  Other [Self] 
 
Details of Secondary Sponsor  
Name  Address 
Abhishek Kesarwani  Manipal University Jaipur 
NIL  NIL 
 
Countries of Recruitment     India  
Sites of Study  
No of Sites = 1  
Name of Principal Investigator  Name of Site  Site Address  Phone/Fax/Email 
Neha Chaudhary  GSVM MEDICAL COLLEGE Kanpur  Department of otorhinolaryngology Gsvm medical college kanpur
Kanpur Nagar
UTTAR PRADESH 		 8077785858

cneha620@gmail.com 
 
Details of Ethics Committee  
No of Ethics Committees= 1  
Name of Committee  Approval Status 
Ethics committee (for biomedical and research purpose)GSVM MEDICAL COLLEGE   Approved 
 
Regulatory Clearance Status from DCGI  
Status 
Not Applicable 
 
Health Condition / Problems Studied  
Health Type  Condition 
Patients  (1) ICD-10 Condition: D498||Neoplasm of unspecified behavior of other specified sites,  
 
Intervention / Comparator Agent  
Type  Name  Details 
Comparator Agent  Comparing benign and malignant laryngeal disorders.  The voice samples of patients with benign and malignant laryngeal lesions will be compared by the AI tool Compared every 4 weeks 
Intervention  Diagnostic intervention   Artificial intelligence tool which will analyse voice samples of patients. Duration 22 months 
 
Inclusion Criteria  
Age From  18.00 Year(s)
Age To  65.00 Year(s)
Gender  Both 
Details  Voice change due to laryngeal diseases  
 
ExclusionCriteria 
Details  Voice change due to rhinological cause
Cleft lip and palate
Clinical and radiological lungi abnormalities
Psychogenic abnormalities
Voice change due to central nervous system causes
 
 
Method of Generating Random Sequence   Other 
Method of Concealment   Other 
Blinding/Masking   Not Applicable 
Primary Outcome  
Outcome  TimePoints 
Asses the accuracy of Artificial intelligence tool in differentiating benign from malignant laryngeal disease   Asses the accuracy of Artificial intelligence tool in differentiating benign from malignant laryngeal disease  
 
Secondary Outcome  
Outcome  TimePoints 
Na  Na 
 
Target Sample Size   Total Sample Size="150"
Sample Size from India="150" 
Final Enrollment numbers achieved (Total)= "Applicable only for Completed/Terminated trials"
Final Enrollment numbers achieved (India)="Applicable only for Completed/Terminated trials" 
Phase of Trial   N/A 
Date of First Enrollment (India)   13/04/2026 
Date of Study Completion (India) Applicable only for Completed/Terminated trials 
Date of First Enrollment (Global)  Date Missing 
Date of Study Completion (Global) Applicable only for Completed/Terminated trials 
Estimated Duration of Trial   Years="3"
Months="0"
Days="0" 
Recruitment Status of Trial (Global)   Not Applicable 
Recruitment Status of Trial (India)  Not Yet Recruiting 
Publication Details   N/A 
Individual Participant Data (IPD) Sharing Statement

Will individual participant data (IPD) be shared publicly (including data dictionaries)?  

Response - YES
  1. What data in particular will be shared?
    Response - All of the individual participant data collected during the trial, after de-identiļ¬cation.

  2. What additional supporting information will be shared?
    Response - Informed Consent Form

  3. Who will be able to view these files?
    Response - Researchers who provide a methodologically sound proposal.

  4. For what types of analyses will this data be available?
    Response - Any purpose.

  5. By what mechanism will data be made available?
    Response (Others) -  Voice

  6. For how long will this data be available start date provided 01-07-2024 and end date provided 09-10-2026?
    Response - Beginning 9 months and ending 36 months following article publication.

  7. Any URL or additional information regarding plan/policy for sharing IPD? 
    Additional Information - Nil
Brief Summary  


Study Objectives



Primary Objective

To evaluate the role of Artificial Intelligence in assisting the diagnosis of laryngeal diseases using laryngeal imaging.


Secondary Objectives


  1. To compare the diagnostic accuracy of Artificial Intelligence with clinical assessment by ENT specialists.
  2. To assess the ability of Artificial Intelligence to differentiate between normal, benign, and malignant laryngeal lesions.
  3. To determine whether Artificial Intelligence can support early detection of laryngeal diseases.






2. Inclusion Criteria



  1. Patients presenting with symptoms suggestive of laryngeal disease such as hoarseness of voice, throat discomfort, or voice change.
  2. Patients undergoing laryngeal examination using laryngoscopy or videostroboscopy in the ENT department.
  3. Patients aged 18 years and above.
  4. Patients who are willing to participate and provide informed consent.






3. Exclusion Criteria



  1. Patients who do not provide consent to participate in the study.
  2. Patients with incomplete clinical or imaging data.
  3. Patients with previous laryngeal surgery that significantly alters normal anatomy.
  4. Poor quality laryngeal images that cannot be analyzed by the Artificial Intelligence system.






4. Primary Outcome Measure



Accuracy of Artificial Intelligence in diagnosing laryngeal diseases based on analysis of laryngeal imaging.





5. Secondary Outcome Measures



  1. Sensitivity and specificity of Artificial Intelligence in detecting laryngeal lesions.
  2. Ability of Artificial Intelligence to classify lesions as normal, benign, or malignant.
  3. Agreement between Artificial Intelligence diagnosis and clinical diagnosis by ENT specialists.


 
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