| CTRI Number |
CTRI/2025/09/094516 [Registered on: 10/09/2025] Trial Registered Prospectively |
| Last Modified On: |
10/09/2025 |
| Post Graduate Thesis |
Yes |
| Type of Trial |
Interventional |
|
Type of Study
|
Diagnostic |
| Study Design |
Other |
|
Public Title of Study
|
Detection of Androgenetic alopecia using Dermascopy |
|
Scientific Title of Study
|
TRICHOLENS An Artificial Intelligence Enabled Mobile Application to Enhance the Diagnostic Utility of Trichoscopy in Dermatological Practice |
| Trial Acronym |
NIL |
|
Secondary IDs if Any
|
| Secondary ID |
Identifier |
| NIL |
NIL |
|
|
Details of Principal Investigator or overall Trial Coordinator (multi-center study)
|
| Name |
Ragadharshini Eswaran |
| Designation |
Post graduate |
| Affiliation |
Saveetha medical college and hospital, Saveetha institute of medical and technical sciences. |
| Address |
Saveetha medical college and hospital, Saveetha institute of medical
and technical sciences, Saveetha nagar, Thandalam. Chennai.
Saveetha medical college and hospital, Saveetha institute of medical
and technical sciences, Saveetha nagar, Thandalam. Chennai.602105
Chennai
TAMIL NADU
602105
India |
| Phone |
9786844567 |
| Fax |
|
| Email |
dharshinieshwaran125@gmail.com |
|
Details of Contact Person
Scientific Query
|
| Name |
Varun Rajagopal |
| Designation |
Professor |
| Affiliation |
Saveetha medical college and hospital, Saveetha institute of medical and technical sciences |
| Address |
Saveetha medical college and hospital, Saveetha institute of medical
and technical sciences, Saveetha nagar, Thandalam. Chennai.
Chennai
TAMIL NADU
602105
India |
| Phone |
8610424075 |
| Fax |
|
| Email |
drvarunrajagopal@gmail.com |
|
Details of Contact Person
Public Query
|
| Name |
Varun Rajagopal |
| Designation |
Professor |
| Affiliation |
Saveetha medical college and hospital, Saveetha institute of medical and technical sciences |
| Address |
Saveetha medical college and hospital, Saveetha institute of medical
and technical sciences, Saveetha nagar, Thandalam. Chennai.
Chennai
TAMIL NADU
602105
India |
| Phone |
8610424075 |
| Fax |
|
| Email |
drvarunrajagopal@gmail.com |
|
|
Source of Monetary or Material Support
|
| Saveetha Medical College Hospital, Saveetha Nagar, Thandalam,Chennai,India-602105. |
|
|
Primary Sponsor
|
| Name |
E. Ragadharshini |
| Address |
Saveetha Medical College Hospital, Saveetha Nagar, Thandalam,Chennai-602105 |
| Type of Sponsor |
Other [Self] |
|
|
Details of Secondary Sponsor
|
|
|
Countries of Recruitment
|
India |
|
Sites of Study
|
| No of Sites = 1 |
| Name of Principal
Investigator |
Name of Site |
Site Address |
Phone/Fax/Email |
| DrRagadharshini Eswaran |
Saveetha Medical college Hospital |
Room no .401, Department of dermatology,Saveetha medical college and hospital, Saveetha institute of medicaland technical sciences, Saveetha nagar, Thandalam. Chennai.
Saveetha medical college and hospital, Saveetha institute of medicaland technical sciences, Saveetha nagar, Thandalam. Chennai.602105
Chennai
TAMIL NADU |
9786844567
dharshinieshwaran125@gmail.com |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 1 |
| Name of Committee |
Approval Status |
| Saveetha Medical College and Hospital Institutional Ethics Committee |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Healthy Human Volunteers |
With Androgenetic alopecia and normal participants |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Intervention |
Nil |
Nil |
| Comparator Agent |
Nil |
Nil |
|
|
Inclusion Criteria
|
| Age From |
18.00 Year(s) |
| Age To |
40.00 Year(s) |
| Gender |
Both |
| Details |
Presenting with concerns of hair loss or scalp abnormalities.
Willing to provide consent for scalp imaging and participation in the study.
No previous diagnosis or treatment for AGA.
|
|
| ExclusionCriteria |
| Details |
Previous treatments for AGA (e.g., minoxidil or finasteride) within the last six months.
Any skin condition that may interfere with scalp imaging (e.g., active psoriasis, eczema).
Unwillingness to Participate: Patients unwilling to participate in the study or to give informed consent.
Experimental Treatments: Patients enrolled in other clinical trials for experimental hair loss treatments may be excluded to prevent confounding factors. |
|
|
Method of Generating Random Sequence
|
Not Applicable |
|
Method of Concealment
|
Not Applicable |
|
Blinding/Masking
|
Not Applicable |
|
Primary Outcome
|
| Outcome |
TimePoints |
Demonstrate high sensitivity and specificity in detecting early AGA, improving diagnostic accuracy.
Reduce the time required for dermatologists to interpret trichoscopic images.
Improve the consistency of diagnoses between dermatologists, reducing variability in clinical decision-making.
Enable early intervention and treatment of AGA, resulting in better patient outcomes, especially in cases where early signs of hair thinning are subtle.
|
1 week |
|
|
Secondary Outcome
|
| Outcome |
TimePoints |
To make the diagnosis of early Androgenetic alopecia easier.
A study tool for all budding dermatologists. |
|
To make the diagnosis of early Androgenetic alopecia easier.
A study tool for all budding dermatologists. |
4 weeks |
|
|
Target Sample Size
|
Total Sample Size="100"
Sample Size from India="100"
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)
|
25/09/2025 |
| 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="1"
Months="2"
Days="10" |
|
Recruitment Status of Trial (Global)
|
Not Yet Recruiting |
| 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 - NO
|
|
Brief Summary
|
Androgenetic alopecia (AGA) is the most common type of hair loss, affecting both men and women. Early diagnosis is critical to slow its progression, yet identifying AGA in its initial stages can be challenging. Trichoscopy, a non-invasive tool that uses dermoscopy to examine the scalp and hair, is increasingly used for diagnosing AGA, but it requires significant expertise. Misinterpretation of trichoscopic images can lead to delayed diagnosis and treatment.
TRICHOLENS aims to bridge this gap by leveraging artificial intelligence (AI) to assist dermatologists in the early detection of AGA. The app will analyze trichoscopy images using machine learning algorithms to recognize early signs of alopecia, distinguishing them from a normal scalp or other hair loss conditions. This approach can reduce subjectivity in diagnosis and improve consistency across different clinicians.
|