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NCT Number: NCT07238959

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

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.

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Key information

Age range

18 year–80 year

Sex eligibility

Male

Study type

Observational

Primary location

Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, Beijing Municipality, China

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Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Male, aged 18-80 years;
  • PSA > 4 ng/ml;
  • 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

  • Patients diagnosed with any malignant tumour within the past five years;
  • Patients who have undergone transurethral resection or enucleation of the prostate;
  • Patients who have previously received treatment for prostate cancer, including but not limited to endocrine therapy, targeted therapy, or immunotherapy;
  • Patients on long-term anticoagulant or antiplatelet therapy (anticoagulants discontinued for less than one week);
  • Patients who have received any form of tumour treatment prior to enrolment blood sampling, including surgery, radiotherapy/chemotherapy, endocrine therapy, targeted therapy, or immunotherapy;
  • 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;
  • Organ transplant recipients or individuals with prior non-autologous (allogeneic) bone marrow or stem cell transplantation;
  • Subjects who have undergone blood transfusion within one month prior to blood sampling;
  • Patients currently participating in other clinical trials, or who have participated in other clinical trials within the past year;
  • Patients deemed unsuitable for this clinical trial by the investigator;
  • Patients meeting any of the above criteria shall not be eligible for inclusion as subjects.

Treatment and study plan

Quantum Detection

Diagnostic Test

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.

Primary outcomes

  1. 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.

  2. Sensitivity of the predictive model in detecting prostate cancer within the general population.

    Time frame: Through primary completion which may take 12 months.

  3. Specificity of the predictive model in detecting prostate cancer within the general population.

    Time frame: Through primary completion which may take 12 months.

Secondary outcomes

  1. 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.

  2. 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.

  3. 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.

Study contacts

Contact information is provided by the study sponsor or research team.

Duocai Li

CONTACT

Shancheng Ren, MD,PhD

CONTACT

[email protected]

86021-81886999

Sponsors and collaborators

Lead sponsor

Shanghai Changzheng Hospital

Other

Collaborators

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

Registry information

Important dates

Study start
2025
Primary completion
2026
Study completion
2027
First posted
Nov 20, 2025
Registry last updated
Nov 20, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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