Application of Quantum Detection-Driven Artificial Intelligence Algorithms for Single-Molecule cfDNA Characterization in the Early Diagnosis of Prostate Cancer

November 15, 2025 updated by: Ren Shancheng, Shanghai Changzheng Hospital
This research project aims to develop a novel blood testing method integrating cutting-edge quantum sensing and artificial intelligence technologies to achieve precise, non-invasive early diagnosis of prostate cancer. The research will employ quantum sensors to perform ultra-high-sensitivity measurements of circulating free DNA (cfDNA) in blood, thereby training a dedicated AI diagnostic model. The ultimate objective is to establish the diagnostic efficacy of this approach through clinical validation, providing clinicians with a novel diagnostic tool capable of significantly reducing unnecessary prostate biopsy procedures.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

1100

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

  • Name: Duocai Li

Study Locations

  • China
    • Beijing Municipality
      • Beijing, Beijing Municipality, China, 100021
        • Cancer hospital, Chinese Academy of Medical Sciences
        • Contact:
    • Guangdong
      • Guangzhou, Guangdong, China, 510120
        • The First Affiliated Hospital of Guangzhou Medical University
        • Contact:
        • Contact:
    • Jiangsu
      • Nanjing, Jiangsu, China
        • Jiangsu Provincial People's Hospital
      • Suzhou, Jiangsu, China
        • the First Affiliated Hospital of Soochow University
        • Contact:
    • Shanghai Municipality
      • Shanghai, Shanghai Municipality, China, 201209
        • Shanghai Changzheng Hospital
    • Sichuan
      • Chengdu, Sichuan, China, 610041
        • West China Hospital, Sichuan University
        • Contact:
    • Zhejiang
      • Ningbo, Zhejiang, China
        • Ningbo No. 1 Hospital
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

Males aged 18-80 years with elevated PSA (>4 ng/ml) and clinical indications for prostate biopsy.

Description

Inclusion Criteria:

  1. Male, aged 18-80 years;
  2. PSA > 4 ng/ml;

  3. Patients meeting criteria for prostate biopsy:

    • fPSA/PSA < 0.16 or PSA D > 0.15 or PSA V > 0.75; ② Positive digital rectal examination (DRE); ③ Imaging studies (ultrasound/MRI) showing suspicious lesions.

Exclusion Criteria:

  1. Patients diagnosed with any malignant tumour within the past five years;
  2. Patients who have undergone transurethral resection or enucleation of the prostate;
  3. Patients who have previously received treatment for prostate cancer, including but not limited to endocrine therapy, targeted therapy, or immunotherapy;
  4. Patients on long-term anticoagulant or antiplatelet therapy (anticoagulants discontinued for less than one week);
  5. Patients who have received any form of tumour treatment prior to enrolment blood sampling, including surgery, radiotherapy/chemotherapy, endocrine therapy, targeted therapy, or immunotherapy;
  6. Concurrent severe systemic diseases deemed by the investigator likely to interfere with trial treatment, evaluation, or compliance, including serious respiratory, circulatory, neurological, psychiatric, gastrointestinal, endocrine, immunological, or urological disorders;
  7. Organ transplant recipients or individuals with prior non-autologous (allogeneic) bone marrow or stem cell transplantation;
  8. Subjects who have undergone blood transfusion within one month prior to blood sampling;
  9. Patients currently participating in other clinical trials, or who have participated in other clinical trials within the past year;
  10. Patients deemed unsuitable for this clinical trial by the investigator;
  11. Patients meeting any of the above criteria shall not be eligible for inclusion as subjects.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Retrospective Testing Cohort
Diagnostic test: Quantum Detection
This cohort will utilize archived plasma samples from a historical patient population with confirmed diagnoses (prostate cancer vs. controls). The objective is model development. The intervention involves analyzing these stored samples using the quantum sensing platform to extract multi-modal cfDNA features (e.g., fragmentomics, methylation). This data is then used to train and optimize the initial AI diagnostic algorithm, establishing the core model before prospective validation.
Diagnostic test: Quantum Detection
This cohort will prospectively enroll new patients with suspected prostate cancer from the same institution as testing cohort. The objective is initial model validation. The intervention entails collecting pre-biopsy blood samples from these participants. The cfDNA from these fresh samples is analyzed using the locked model from the training phase. The model's predictions are then compared against the gold-standard prostate biopsy results to assess initial diagnostic performance.
Diagnostic test: Quantum Detection
This cohort will prospectively recruit patients from multiple independent clinical centers. The objective is to test the model's generalizability. The intervention involves standardized blood collection across all external sites, with samples sent to a central lab for blinded cfDNA analysis using the finalized, locked-down model.
Prospective Internal Validation Cohort
Diagnostic test: Quantum Detection
This cohort will utilize archived plasma samples from a historical patient population with confirmed diagnoses (prostate cancer vs. controls). The objective is model development. The intervention involves analyzing these stored samples using the quantum sensing platform to extract multi-modal cfDNA features (e.g., fragmentomics, methylation). This data is then used to train and optimize the initial AI diagnostic algorithm, establishing the core model before prospective validation.
Diagnostic test: Quantum Detection
This cohort will prospectively enroll new patients with suspected prostate cancer from the same institution as testing cohort. The objective is initial model validation. The intervention entails collecting pre-biopsy blood samples from these participants. The cfDNA from these fresh samples is analyzed using the locked model from the training phase. The model's predictions are then compared against the gold-standard prostate biopsy results to assess initial diagnostic performance.
Diagnostic test: Quantum Detection
This cohort will prospectively recruit patients from multiple independent clinical centers. The objective is to test the model's generalizability. The intervention involves standardized blood collection across all external sites, with samples sent to a central lab for blinded cfDNA analysis using the finalized, locked-down model.
Prospective external Validation Cohort
Diagnostic test: Quantum Detection
This cohort will utilize archived plasma samples from a historical patient population with confirmed diagnoses (prostate cancer vs. controls). The objective is model development. The intervention involves analyzing these stored samples using the quantum sensing platform to extract multi-modal cfDNA features (e.g., fragmentomics, methylation). This data is then used to train and optimize the initial AI diagnostic algorithm, establishing the core model before prospective validation.
Diagnostic test: Quantum Detection
This cohort will prospectively enroll new patients with suspected prostate cancer from the same institution as testing cohort. The objective is initial model validation. The intervention entails collecting pre-biopsy blood samples from these participants. The cfDNA from these fresh samples is analyzed using the locked model from the training phase. The model's predictions are then compared against the gold-standard prostate biopsy results to assess initial diagnostic performance.
Diagnostic test: Quantum Detection
This cohort will prospectively recruit patients from multiple independent clinical centers. The objective is to test the model's generalizability. The intervention involves standardized blood collection across all external sites, with samples sent to a central lab for blinded cfDNA analysis using the finalized, locked-down model.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
Area under the receiver operating characteristic curve (AUC-ROC) for the predictive model in the general population for prostate cancer.
Time Frame: Through primary completion which may take 12 months.
Through primary completion which may take 12 months.
Sensitivity of the predictive model in detecting prostate cancer within the general population.
Time Frame: Through primary completion which may take 12 months.
Through primary completion which may take 12 months.
Specificity of the predictive model in detecting prostate cancer within the general population.
Time Frame: Through primary completion which may take 12 months.
Through primary completion which may take 12 months.

Secondary Outcome Measures

Outcome Measure
Time Frame
Area under the ROC curve for the predictive model in identifying prostate cancer within the PSA grey zone cohort.
Time Frame: Through primary completion which may take 12 months.
Through primary completion which may take 12 months.
Sensitivity of the predictive model in identifying prostate cancer within the PSA grey zone cohort.
Time Frame: Through primary completion which may take 12 months.
Through primary completion which may take 12 months.
The specificity of the predictive model in identifying prostate cancer among individuals in the PSA grey zone.
Time Frame: Through primary completion which may take 12 months.
Through primary completion which may take 12 months.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Shanghai Changzheng Hospital

Collaborators

Cancer Institute and Hospital, Chinese Academy of Medical Sciences
West China Hospital
The First Affiliated Hospital of Soochow University
The First Affiliated Hospital of Guangzhou Medical University
Jiangsu Provincial People's Hospital
First Affiliated Hospital of Ningbo University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

December 1, 2025

Primary Completion (Estimated)

December 1, 2026

Study Completion (Estimated)

December 1, 2027

Study Registration Dates

First Submitted

November 15, 2025

First Submitted That Met QC Criteria

November 15, 2025

First Posted (Actual)

November 20, 2025

Study Record Updates

Last Update Posted (Actual)

November 20, 2025

Last Update Submitted That Met QC Criteria

November 15, 2025

Last Verified

November 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • CaPS

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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