Smartphone App Detection for Retinoblastoma

Overseen By Carlos Rodriguez-Galindo, MD

Age: < 18

Sex: Any

Trial Phase: Academic

Sponsor: St. Jude Children's Research Hospital

Disqualifiers: Prior treatment cataracts, glaucoma, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 4

290 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial is testing a smartphone app called CRADLE to help detect leukocoria in children. The app takes pictures of the eyes and looks for signs of this condition. It aims to improve early detection in kids who have or might have serious eye diseases.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It seems focused on using a smartphone app for detection, so it's unlikely to require changes to your medication.

Is the smartphone app for detecting retinoblastoma safe to use?

The smartphone app for detecting retinoblastoma is safe as it is non-invasive, meaning it doesn't require any medical procedures or drugs, and it uses photographs to help identify eye conditions. ^{1 2 3 4 5}

How does the smartphone app treatment for retinoblastoma differ from other treatments?

The smartphone app treatment for retinoblastoma is unique because it allows for early detection of the condition through a simple, non-invasive method using a smartphone camera to identify leukocoria (white pupil) in photographs. This approach is more accessible and affordable compared to traditional methods that require specialized equipment and healthcare professionals. ^{1 2 5 6 7}

What data supports the effectiveness of the treatment CRADLE, White Eye Detector, ComputeR Assisted Detector of LEukocoria, Red reflex testing, Red Reflex Test, Ophthalmoscope Examination for detecting retinoblastoma?

Research shows that the CRADLE app, also known as the White Eye Detector, can identify leukocoria (white pupil) in photos, detecting eye disorders like retinoblastoma up to 1.3 years before diagnosis. This app, along with red reflex testing, helps in early detection, which is crucial for better outcomes. ^{1 2 3 5 8}

Who Is on the Research Team?

Carlos Rodriguez-Galindo, MD

Principal Investigator

St. Jude Children's Research Hospital

Are You a Good Fit for This Trial?

This trial is for patients with retinoblastoma, congenital cataracts, or glaucoma who are visiting St. Jude Children's Research Hospital or University of Tennessee Hamilton Eye Institute. It includes new or minimally treated retinoblastoma cases and those referred for eye conditions like leukocoria.

Inclusion Criteria

I have a diagnosis of cataracts, glaucoma, or retinoblastoma and am seeing an eye specialist at St. Jude or UT.

Stratum II: Patient without prior diagnosis has been referred for ophthalmological evaluation, including leukocoria or other conditions.

I am receiving treatment to save my eye from retinoblastoma.

Exclusion Criteria

I have had treatment for cataracts or glaucoma.

I am unable or unwilling to give consent for the study.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Initial Evaluation

Participants undergo initial evaluation using the CRADLE application and ophthalmoscope to assess leukocoria

1 day

1 visit (in-person)

Follow-up Evaluation

Participants in Stratum III undergo additional CRADLE evaluations on Days 2, 3, and 4 to compare with ophthalmoscope results

4 days

3 visits (in-person)

Follow-up

Participants are monitored for safety and effectiveness after initial evaluations

3-4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• CRADLE
• Red reflex testing

Trial Overview The study tests the CRADLE smartphone app's ability to detect leukocoria compared to traditional red reflex testing using an ophthalmoscope. The trial has two parts: finding the best way to use CRADLE and measuring its accuracy (sensitivity and specificity).

How Is the Trial Designed?

Group I: Stratum III: Retinoblastoma Group Experimental Treatment 2 Interventions

A separate group of participants with known retinoblastoma and who are undergoing ocular salvage treatments will be screened with red reflex testing using direct ophthalmoscopy on Day 1. They will also undergo testing with the CRADLE software application defined as the most effect in Stratum I on Day 1 then for three additional consecutive visits which typically occur every 3 to 4 weeks.

Group II: Stratum II: Leukocoria Evaluation Group Experimental Treatment 2 Interventions

A separate group of participants who are referred for evaluation of leukocoria or any other eye condition will undergo red reflex testing testing with CRADLE on Day 1.

Group III: Stratum I: Initial Evaluation Group Experimental Treatment 1 Intervention

Initially, a small group of patients diagnosed with congenital or infantile cataracts, congenital glaucoma or retinoblastoma and who meet the eligibility criteria will undergo testing with CRADLE on Day 1.

Who Is Running the Clinical Trial?

St. Jude Children's Research Hospital

Lead Sponsor

Trials

451

Recruited

5,326,000+

Published Research Related to This Trial

The red-reflex test is significantly more effective at detecting simulated retinoblastoma lesions when using oblique viewing and pupil dilation, with detection rates improving from less than 48% to 96% for larger lesions.

Detection rates for peripheral lesions were notably low with straight-on viewing (as low as 16%), but improved to 70% or higher with oblique viewing, highlighting the importance of viewing technique in identifying potential retinoblastoma.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The detection of simulated retinoblastoma by using red-reflex testing. Li, J., Coats, DK., Fung, D., et al.[2010]

The modified MDEyeCare app successfully detected leukocoria in early stages of retinoblastoma (RB) in 50% of cases in Group B and 83% in Group C, indicating its potential for early diagnosis by non-ophthalmologists.

In late-stage RB cases, the app achieved a 100% detection rate, suggesting that the improved smartphone methodology could lead to better treatment outcomes and vision preservation for affected children.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Smartphone-based application improves the detection of retinoblastoma. Khedekar, A., Devarajan, B., Ramasamy, K., et al.[2021]

The EyeScreen smartphone application demonstrated a high sensitivity of 87% and specificity of 73% in detecting leukocoria, indicating its potential as an effective screening tool for retinoblastoma in low-income regions.

This study, involving 1,457 participants in Ethiopia, highlights the promising use of low-cost technology and machine learning to improve early diagnosis of retinoblastoma, which is crucial for better clinical outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

EyeScreen: Development and Potential of a Novel Machine Learning Application to Detect Leukocoria. Bernard, A., Xia, SZ., Saleh, S., et al.[2022]

The CRADLE smartphone application effectively detects leukocoria in photographs, identifying 80% of children with serious eye disorders up to 1.3 years before clinical diagnosis, based on an analysis of 52,982 photographs.

This tool provides a valuable supplement to traditional screening methods, allowing parents to help monitor their children's eye health through casual photography.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Autonomous early detection of eye disease in childhood photographs. Munson, MC., Plewman, DL., Baumer, KM., et al.[2020]

Survival rates for retinoblastoma in South Africa are only 50% due to late diagnosis, highlighting the urgent need for effective screening methods.

Implementing mandatory red reflex tests at neonatal discharge and during routine health visits could significantly improve early detection of retinoblastoma, potentially reducing mortality rates.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Towards early detection of retinoblastoma. Freeman, N., Meyer, D.[2019]

The implementation of the red reflex test in newborns led to the early identification of five cases of congenital cataracts, demonstrating its effectiveness in detecting serious ocular conditions shortly after birth.

Despite its importance, less than half of the neonatology departments in Israel routinely perform the red reflex test, highlighting a gap in adherence to the American Academy of Pediatrics' recommendations for early ocular assessment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The red reflex examination in neonates: an efficient tool for early diagnosis of congenital ocular diseases. Eventov-Friedman, S., Leiba, H., Flidel-Rimon, O., et al.[2019]

Retinoblastoma (RB) is a common eye cancer in children, and its diagnosis can be delayed due to factors like small tumor size and missed appointments, highlighting the need for improved screening methods.

This systematic review of 10 studies suggests that mobile devices and applications could potentially enhance the early detection of RB by both healthcare providers and parents, although more research is needed to confirm their effectiveness.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Detection and Diagnosis of Retinoblastoma: Can Mobile Devices Be the Next Step Toward Early Intervention? Jabir, AR., Zaheer, HA., Zaheer, MA., et al.[2022]

Diabetic retinopathy (DR) is a major cause of vision impairment in adults, and early detection is crucial for improving patient outcomes; traditional detection methods can be costly and require specialized professionals.

This scoping review will evaluate the accuracy of smartphone-based ophthalmoscopy for detecting DR, potentially offering a more accessible and affordable alternative for patients, with plans to analyze data from studies published since 2000.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Use of smartphones for detecting diabetic retinopathy: a protocol for a scoping review of diagnostic test accuracy studies. Tan, CH., Quah, WH., Tan, CSH., et al.[2020]

Citations

1. United States pubmed.ncbi.nlm.nih.gov

The detection of simulated retinoblastoma by using red-reflex testing. [2010]

2. England pubmed.ncbi.nlm.nih.gov

Smartphone-based application improves the detection of retinoblastoma. [2021]

3. Netherlands pubmed.ncbi.nlm.nih.gov

EyeScreen: Development and Potential of a Novel Machine Learning Application to Detect Leukocoria. [2022]

4. United States pubmed.ncbi.nlm.nih.gov

Autonomous early detection of eye disease in childhood photographs. [2020]

5. South Africa pubmed.ncbi.nlm.nih.gov

Towards early detection of retinoblastoma. [2019]

6. Israel pubmed.ncbi.nlm.nih.gov

The red reflex examination in neonates: an efficient tool for early diagnosis of congenital ocular diseases. [2019]

7. United States pubmed.ncbi.nlm.nih.gov

Detection and Diagnosis of Retinoblastoma: Can Mobile Devices Be the Next Step Toward Early Intervention? [2022]

8. England pubmed.ncbi.nlm.nih.gov

Use of smartphones for detecting diabetic retinopathy: a protocol for a scoping review of diagnostic test accuracy studies. [2020]