Self-administered Remote Neurological Examination Using Mobile Application in Patients With Brain Tumors

NCT ID: NCT07236840

Last Updated: 2026-02-03

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 600 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2026-03-01
• Study Completion Date: 2027-11-05

Brief Summary

The goal of this observational study is to evaluate the feasibility and accuracy of a self-administered remote neurological examination using the "Iskhaa" mobile application in patients with brain tumors aged above 5 years who are able to follow app-based instructions.

The main questions it aims to answer are:

1. Development of a mobile application equipped with symptom assessment and recording videos as patients perform specific neurological tasks.

2. Development and validation of the AI model to detect functional changes and predict subsequent neurological deterioration.

Participants will:

1. Use the Iskhaa mobile application to perform guided self-neurological examinations following pre-recorded video instructions.

2. Complete EORTC QLQ-C30 and BN20 questionnaires for quality of life assessment.

3. Record and upload videos (e.g., speech, walking, limb movements) using their mobile camera for analysis.

4. In Phase 1 (onsite), 100 participants will use the app under supervision to ensure usability and accuracy.

5. In Phase 2 (offsite), 500 participants will use the app independently at home for monthly self-assessments, with reminders and follow-up support.

6. Continue routine clinic visits every 3-6 months and imaging every 6-12 months as per standard clinical care.

The study will compare app-recorded data with physician assessments to determine agreement and validity of remote neurological monitoring using artificial intelligence analysis.

Detailed Description

The mobile application "Iskhaa" will be developed in collaboration with the Electronics Division, Bhabha Atomic Research Centre (BARC). The application will be compatible with Android version 8.0 or above. The software will have two components-mobile application (for patients and healthcare providers) and a desktop application (for healthcare providers). The data recorded using the app will be stored in a secured hospital server accessible via the hospital network. The sample of different clinical features to be recorded by the application is included in Annexure A. The mobile application will be initially developed in English and subsequently translated to Hindi, Marathi, and Bengali in upgraded versions over initial 3-6 months. Pre-recorded videos will be used to guide the patients in repeating the actions that will be recorded for neurological examination. Examples of such instructions will include speech (patient asked to speak fixed sentences), gait, e.g., walking 20 steps, tandem walking to check cerebellar function, lifting individual limbs, etc. In addition, the European Organisation for Research and Treatment of Cancer (EORTC) quality of life core questionnaire (QLQ-C30) and brain cancer module (BN20) will be available in the mobile application. The recorded symptoms will be stored in a secured database, and the study investigators will have access to review them using either mobile or desktop applications. Once an assessment (either onsite or onsite) is completed, the data will be updated electronically at the central site housed in Tata Memorial Centre, and the investigator will receive a reminder. Version upgradation for better improvement of the application interface for better user compliance and software updates will be done periodically as required. A sample of the application interface is provided in the diagram below.

Patients aged more than 5 years with a diagnosis of brain tumor, having an expected life expectancy of more than 6 months, and able to follow instructions of the mobile application will be screened for the study. They will be accrued after signing a written consent or assent form as appropriate. The initial phase of the study will include an onsite assessment of 100 patients who will be required to use the mobile application to assess symptoms and record videos for neurological functional assessment. In this phase, the application will be installed on specific mobile phones (not belonging to the patient). After performing the evaluation, all the patients will be evaluated by the responsible physician in the clinic, who will follow standard protocols. A detailed neurological examination will be conducted to cover all aspects of the symptoms and functional assessment as available in the mobile application. The primary purpose of the on-site evaluation is to provide any technical support for the application use by the in-house team before installation on mobile devices for patients to allow seamless transition and use. The second phase of assessment will include 500 patients who will perform the virtual examination (off-site). The mobile application will be installed on individual phones when consent is obtained for study participation. Patients will be required to undergo monthly assessments at home with reminders set up for performing the timely evaluations, and they will be reminded by telephone in case of delay in taking the assessment by 7 days. Patients and caregivers will be able to record and upload the video using the mobile camera. Additionally, patients will be instructed to undergo self-assessments (unscheduled) in case of symptomatic worsening. Patients will continue follow-up in the clinic for physical evaluation every 3-6 months as per standard institutional practice and imaging scheduled every 6-12 monthly specific for the histological diagnosis or as mandated clinically in case of neurological worsening as decided by the responsible physician without any influence of the study participation.

All the data completed will be available for study investigators to retrieve. The symptomatology assessment will be presented as descriptive statistics and serial changes will be analyzed. The data recorded using the app will be correlated with the assessment by the physician during each clinic visit. Computational analysis will be performed for all the individual tasks undertaken by the patient and recorded in the video format. Neurological functioning (e.g., gait and movement) will be recorded using artificial intelligence algorithms with a hybrid model that combines convolutional neural networks (CNNs) and vision transformers (ViTs). The video data will undergo preprocessing steps to extract relevant features, such as silhouettes, skeletal representations, or pose key points, using advanced pose estimation tools like OpenPose. Each frame will be processed by a CNN backbone, such as ResNet or EfficientNet, to extract low-level spatial features. These features will then be fed into a Vision Transformer module, which will model global temporal dependencies across the sequence of frames, providing a robust representation of the patient's gait. This combined framework will enable the detection of subtle anomalies, abnormalities, or variations in gait, which are critical for clinical monitoring. The model will be trained and validated using video data captured from diverse patient populations, and clinical scenarios. By leveraging the granularity of high-speed footage, the model will aim to deliver high-precision outputs such as gait classification, anomaly detection, or parameter regression tailored to the specific needs of applications. The integration of state-of-the-art techniques, such as 3D Vision Transformers for enhanced spatiotemporal analysis, will ensure the model's robustness and generalizability. Furthermore, Explainable AI (XAI) methodologies will be incorporated to interpret the model's predictions, providing actionable insights and fostering trust in the system.

Conditions

CNS Tumor; Artificial Intelligence (AI); Glioma; Digital Health

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Interventions

Neurological assessment

This assessment will include Speech, Cerebellar function and Quality of Life questionnaires using mobile application.

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

1. Diagnosis of brain tumors (histopathology/ radiology).

2. Age > 5 years

3. Patient or caregiver have access to an android smart phone and is able to install the mobile application.

4. Expected survival more than 6 months during study accrual.

5. Signing patient consent or parent consent/ child assent form (as appropriate).

Exclusion Criteria

1. Patient or caregiver is not reliable to follow instructions or use the mobile application.

2. Patient with severe cognitive or psychiatric issues causing difficulty in using the app or follow instructions.

3. Karnofsky Performance Status (KPS) or Lansky Performance Status LPS) <50.

4. Terminal illness with expected life expectancy (<6 months).

• Minimum Eligible Age: 5 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Bhabha Atomic Research Centre (BARC), Mumbai

UNKNOWN

Sponsor Role: collaborator

Tata Memorial Centre

OTHER

Sponsor Role: lead

Responsible Party

Dr Archya Dasgupta

Associate Professor, Radiation Oncology

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

Tata Memorial Centre

Mumbai, Maharashtra, India

Countries

India

Central Contacts

Dr Archya Dasgupta, Radiation Oncology, MD

Role: CONTACT

archya1010@gmail.com

8097081506 ext. 91-22-24177000

Facility Contacts

Dr Archya Dasgupta, MD

Role: primary

archya1010@gmail.com

8097081506

Other Identifiers

4752

Identifier Type: -

Identifier Source: org_study_id