| CTRI Number |
CTRI/2025/08/093300 [Registered on: 20/08/2025] Trial Registered Prospectively |
| Last Modified On: |
19/08/2025 |
| Post Graduate Thesis |
No |
| Type of Trial |
Observational |
|
Type of Study
|
Cohort Study |
| Study Design |
Single Arm Study |
|
Public Title of Study
|
Evaluation of an AI system for detecting tuberculosis from chest X-rays at KLE Hospital, Belagavi |
|
Scientific Title of Study
|
Evaluating and Refining Al Model for TB Identification from Chest X-rays |
| Trial Acronym |
NIL |
|
Secondary IDs if Any
|
| Secondary ID |
Identifier |
| NIL |
NIL |
|
|
Details of Principal Investigator or overall Trial Coordinator (multi-center study)
|
| Name |
Dr Pradeep S Goudar |
| Designation |
Associate Professor |
| Affiliation |
KLES Dr. Prabhakar Kore Hospital & Medical Research Centre |
| Address |
84 room number, X ray department
JNMC Campus, Nehru Nagar, Belagavi, Karnataka – 590010, India
Belgaum
KARNATAKA
590010
India |
| Phone |
07411188888 |
| Fax |
|
| Email |
pradeepsgoudar6543@icloud.com |
|
Details of Contact Person
Scientific Query
|
| Name |
Noor Fatma |
| Designation |
CTO |
| Affiliation |
Easiofy Solutions Pvt Ltd |
| Address |
I 1607, AVJ HEIGHTS ZETA-1 GREATER NOIDA, Gautam Buddha Nagar, UP -201307
Gautam Buddha Nagar
UTTAR PRADESH
201307
India |
| Phone |
09958499337 |
| Fax |
|
| Email |
noor.fatma@easiofy.com |
|
Details of Contact Person
Public Query
|
| Name |
Noor Fatma |
| Designation |
CTO |
| Affiliation |
Easiofy Solutions Pvt Ltd |
| Address |
I 1607, AVJ HEIGHTS ZETA-1 GREATER NOIDA, Gautam Buddha Nagar, UP -201307
UTTAR PRADESH
201307
India |
| Phone |
09958499337 |
| Fax |
|
| Email |
noor.fatma@easiofy.com |
|
|
Source of Monetary or Material Support
|
| Easiofy Solutions Pvt ltd |
|
|
Primary Sponsor
|
| Name |
Easiofy Solutions Pvt Ltd |
| Address |
I 1607, AVJ Heights Zeta-1, Greater Noida, Gautam Buddha Nagar, UP -201307 |
| Type of Sponsor |
Other [Pvt Ltd] |
|
|
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 |
| Dr Pradeep S Goudar |
KLES Dr. Prabhakar Kore Hospital & Medical Research Centre |
84 room number,
X ray department,JNMC Campus, Nehru Nagar, Belagavi, Karnataka – 590010, India
Belgaum
KARNATAKA |
07411188888
pradeepsgoudar6543@icloud.com |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 1 |
| Name of Committee |
Approval Status |
| Institutional Ethics Committee of KLE Academy of Higher Education and Research |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Patients |
(1) ICD-10 Condition: J984||Other disorders of lung, |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Comparator Agent |
Standard Radiological Interpretation |
Standard diagnostic workflow for suspected TB cases at KLE Hospital. Chest X-rays are interpreted by qualified radiologists, and findings are correlated with confirmatory tests such as High-Resolution CT (HRCT), nucleic acid amplification tests (NAAT e.g., GeneXpert, Truenat), and documented clinical diagnoses. This represents the current standard of care against which the AI model’s performance will be compared. |
|
|
Inclusion Criteria
|
| Age From |
18.00 Year(s) |
| Age To |
90.00 Year(s) |
| Gender |
Both |
| Details |
Patients who have undergone a chest X-ray as part of their diagnostic evaluation for suspected TB or other respiratory illness within the study period.
Availability of confirmatory test results (e.g., NAAT such as GeneXpert or Truenat, HRCT, or clinical diagnosis).
Complete imaging and clinical records available in the PACS and hospital database. |
|
| ExclusionCriteria |
| Details |
Patients younger than 18 years of age.
Poor-quality chest X-rays (e.g., underexposure, overexposure, excessive motion artifacts, or significant image degradation).
Incomplete imaging records or missing confirmatory test results.
Cases lacking adequate clinical metadata or follow-up information.
Duplicate imaging records of the same episode without added diagnostic value. |
|
|
Method of Generating Random Sequence
|
Not Applicable |
|
Method of Concealment
|
Not Applicable |
|
Blinding/Masking
|
Not Applicable |
|
Primary Outcome
|
| Outcome |
TimePoints |
| Diagnostic accuracy of ImagiXAI-CXR for Active TB detection from chest X-rays, quantified by sensitivity, specificity, PPV, NPV, and AUC, using confirmatory clinical and radiological findings as reference standards, assessed at the time of retrospective analysis. |
16 weeks |
|
|
Secondary Outcome
|
| Outcome |
TimePoints |
| Nil |
Nil |
|
|
Target Sample Size
|
Total Sample Size="1000"
Sample Size from India="1000"
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)
|
03/09/2025 |
| 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="0"
Months="4"
Days="0" |
|
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
|
This retrospective observational study at KLE Hospital, Belagavi, aims to evaluate the diagnostic accuracy of ImagiXAI-CXR, an AI-based system for detecting tuberculosis (TB) from chest X-rays. A total of 1,000 retrospective CXR cases from the hospital’s PACS archive will be analyzed, including both TB-positive and TB-negative patients. Reference standards will include confirmatory tests such as High-Resolution CT (HRCT), nucleic acid amplification tests (NAAT), and documented clinical diagnoses. The primary objective is to determine the sensitivity, specificity, positive predictive value, negative predictive value, and area under the ROC curve (AUC) for Active TB detection. All AI misclassifications will be reviewed by a radiologist and clinical team to identify error patterns, and findings will be used for iterative AI model refinement. The study’s outcomes will inform the integration of AI into real-world TB screening workflows to improve diagnostic accuracy and public health impact. |