DeepDOF Imaging for Cervical Cancer

Overseen By Kathleen M Schmeler, MD

Age: 18 - 65

Sex: Female

Trial Phase: Academic

Sponsor: M.D. Anderson Cancer Center

Disqualifiers: Under 25, Over 49, Pregnant

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

Compensation: Varies

Number of Visits: 1

Duration: Immediate

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests a new imaging method, DeepDOF, to improve cervical cancer diagnosis. It focuses on women undergoing cervical biopsies or LEEP procedures, standard tests for cervical cancer. The aim is to determine how well DeepDOF images enhance the accuracy of these tests. Women aged 25-49 undergoing a cervical biopsy or LEEP may be suitable candidates. As an unphased trial, this study allows participants to contribute to innovative research that could enhance diagnostic accuracy for future patients.

Do I need to stop taking my current medications for the trial?

The trial information does not specify whether you need to stop taking your current medications.

What prior data suggests that DeepDOF Imaging is safe for cervical cancer diagnosis?

Research shows that the DeepDOF imaging technique uses advanced computer methods to enhance the quality of cervical cancer images. These methods achieve a success rate of about 99.26% in producing clear images, aiding doctors in detecting early signs of cervical cancer more reliably.

Studies have developed computer programs that automatically identify early and advanced stages of cervical cancer from these images. This automation aims to make cervical cancer screening faster and more accurate.

No reports of side effects or safety concerns related to the DeepDOF imaging process have emerged in the studies reviewed. Since this trial tests an imaging technique rather than a new drug or invasive procedure, it is generally expected to be safe. Imaging methods like this are usually considered safe because they do not involve surgery or medication. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about DeepDOF Imaging for cervical cancer because it offers a new way to visualize cervical tissue in real-time. Unlike standard care, such as VIA (visual inspection with acetic acid) or colposcopy, which can be subjective, DeepDOF provides immediate, high-resolution images at the point of care. This technique could lead to faster and potentially more accurate identification of abnormal cells, enabling quicker decision-making for further treatment. By providing clear images right away, DeepDOF could revolutionize how cervical cancer screenings are conducted, making them more efficient and potentially more effective.

What evidence suggests that DeepDOF Imaging is effective for cervical cancer?

Research has shown that DeepDOF Imaging, which employs advanced computer techniques, can detect cervical cancer more effectively. Studies have found these methods to be highly accurate, with some tests achieving 96.84% and 94.50% accuracy in identifying types of cervical cancer. In this trial, participants will undergo imaging with DeepDOF, which helps locate and outline tumors in images, potentially leading to better treatment options. By improving early detection, DeepDOF Imaging could significantly enhance care and outcomes for people with cervical cancer. ^{1 2 6 7 8}

Who Is on the Research Team?

Kathleen M Schmeler, MD

Principal Investigator

M.D. Anderson Cancer Center

Are You a Good Fit for This Trial?

This trial is for women aged 25-49 in Mozambique and Brazil who are undergoing cervical biopsy or LEEP, not pregnant, and able to give informed consent. Pregnant women, those outside the age range, or not having the procedures cannot participate.

Inclusion Criteria

I am having a cervical biopsy or LEEP procedure.

I am not pregnant and have a recent negative pregnancy test.

I am a woman aged between 25 and 49.

Exclusion Criteria

I am not pregnant.

I am a woman under 25 or over 49 years old.

I am not scheduled for a cervical biopsy or LEEP procedure.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants undergo cervical biopsy and/or LEEP procedures, and specimens are imaged using DeepDOF at the point of care

Immediate

1 visit (in-person)

Follow-up

Participants are monitored for safety and effectiveness after treatment

1 year

What Are the Treatments Tested in This Trial?

Interventions

• DeepDOF Images

Trial Overview The study tests a new optical microscope called DeepDOF on cervical biopsies and LEEP specimens from participants to see if it can provide detailed images similar to traditional histology without delaying standard care.

How Is the Trial Designed?

Group I: DeepDOF Images Experimental Treatment 1 Intervention

Participants will be approached by a trained research assistant. After informed consent is obtained, each participant will collect two cervical swabs (self-collected and/or provider-collected) as an optional procedure and stored for future research. VIA and/or colposcopy will be performed per standard of care. Cervical biopsy(ies) and/or LEEP will be performed per standard of care. The specimens will be imaged immediately using DeeDOF at the point of care and then submitted for standard histopathologic analysis as shown in Figure 1.

Who Is Running the Clinical Trial?

M.D. Anderson Cancer Center

Lead Sponsor

Trials

3,107

Recruited

1,813,000+

Citations

1. withpower.com withpower.com/trial/phase-uterine-cervical-neoplasms-5-2025-990e2

DeepDOF Imaging for Cervical Cancer · Info for Participants The research shows that deep learning techniques can help in diagnosing and segmenting cervical cancer tumors from MRI images, which might improve treatment ...

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12413234/

Deep dive into deep learning methods for cervical cancer ... In cervical cancer screening, data re-weighting ensures more robust models, improving automated detection and patient outcomes by reducing the impact of ...

3. nature.com nature.com/articles/s41598-024-61063-w

Enhancing cervical cancer detection and robust ... Furthermore, cervix type and cervical cancer classification tests achieved high accuracy rates, with scores of 96.84% and 94.50%, respectively.

4. sciencedirect.com sciencedirect.com/science/article/pii/S2352914824000595

Deep learning techniques for cervical cancer diagnosis ... This review article discusses cervical cancer and its screening processes, followed by the Deep Learning training process and the classification, segmentation, ...

5. ieeexplore.ieee.org ieeexplore.ieee.org/document/11070845/

Effective Cervical Cancer Detection using Deep Learning ... It claims nearly 700 lives daily. However, early detection in its precancerous stages significantly improves treatment outcomes. This study, Enhanced Cervical ...

6. nature.com nature.com/articles/s41598-025-90024-0

Generalizable deep neural networks for image quality ... In the case of cervical images, quality classification is a crucial task to ensure accurate detection of precancerous lesions or cancer; this is ...

7. link.springer.com link.springer.com/article/10.1007/s11063-025-11770-w

Cervical Cancer Classification Using Deep Learning ... The dataset includes a total of 5,679 colposcopy images obtained from Smartphone ODT and Intel's cervical screening data collection initiatives.

8. academic.oup.com academic.oup.com/jnci/article/111/9/923/5272614

An Observational Study of Deep Learning and Automated ... The objective of this study was to develop a “deep learning”-based visual evaluation algorithm that automatically recognizes cervical precancer/cancer.