An observational study in Graft Rejection, Kidney Transplantation and Glomerulonephritis, sponsored by Chen Dajin. Active, not recruiting at 1 site in China. Open to participants aged 18 Years to 75 Years. Per ClinicalTrials.gov, last updated 2026-08-03.
Sponsored by Chen Dajin · Observational
This prospective research collects leftover kidney biopsy tissue slides and matching routine clinical data from patients who received kidney transplants and underwent standard kidney puncture biopsy at Zhejiang University School of Medicine First Affiliated Hospital starting November 2025. A total of around 1,000 patient samples will be included, covering transplant rejection (including TCMR and ABMR subtypes, acute and chronic rejection), polyomavirus infection and recurrent original kidney disease after transplantation.
All study materials come from residual biopsy specimens generated during regular clinical examinations, with no extra invasive operations, additional medical costs or physical trauma for participants. We will scan pathological slides into digital images and combine them with patients' medical records, lab test results, medication history and follow-up information. After full anonymization and standardized labeling by senior renal pathologists following the Banff standard, we will build an artificial intelligence (AI) multi-task model.
This AI system will serve three core clinical functions: accurately distinguish different types of transplant kidney lesions, quantitatively measure tissue damage caused by rejection, and predict the risk of recurrent rejection after surgery. We will optimize and verify the model's diagnostic accuracy, stability and reliability through dataset segmentation, cross validation and algorithm adjustment.
For patients, this study brings no extra physical or economic burden. If suspicious pathological changes are found during data analysis, relevant clues will be fed back to attending doctors to support individual treatment management. For clinical providers, the finished AI tool can reduce pathologists' reading workload, lower missed diagnosis and misdiagnosis caused by individual experience differences, especially improve detection of subclinical and borderline rejection. It helps clinicians evaluate injury severity and forecast recurrence risk, so as to formulate personalized immunosuppression regimens, reduce rejection relapse and prolong graft survival.
Strict privacy protection measures are implemented throughout the whole research process: all personal identifiable information will be completely removed, and encrypted classified data management is adopted to prevent information leakage. Every participant signs a written informed consent and retains the right to withdraw from the study at any time without affecting their regular medical care. All research procedures have passed ethical review supervision, and all collected data and specimens will be properly stored or destroyed in accordance with standardized medical management rules after the study ends.
The research aims to fill the gap of prospective multi-dimensional AI auxiliary diagnosis research in kidney transplantation, promote standardized, intelligent and precise post-transplant pathological evaluation, and provide new technical support to improve long-term survival outcomes of kidney transplant recipients.
115 studies on the registry are indexed under Glomerulonephritis; 32 are open to participants now.
This study's planned enrollment of 1,000 is above the median of 100 across 27 observational studies indexed under Glomerulonephritis.
Browse Glomerulonephritis studies →This is the only study on the registry with Chen Dajin as lead sponsor.
Counted across the registry records on this site, refreshed daily.
This prospective observational study consecutively enrolls up to 1,000 eligible adult kidney transplant recipients aged 18-75 at The First Affiliated Hospital, Zhejiang University School of Medicine starting November 2025. Participants undergo clinically indicated renal allograft biopsy for monitoring or disease evaluation.
The population includes cases with TCMR, ABMR, chronic rejection, polyomavirus nephropathy, recurrent primary renal disease and non-rejection controls. Only residual biopsy slides and anonymized clinical data are collected, with no additional invasive procedures.
Subjects with poor specimens, incomplete data or unavailable follow-up records will be excluded. All participants provide informed consent and can withdraw freely. All identifiable information will be removed to protect privacy.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
A biopsy takes a small piece of tissue to examine. “Archival tissue” is a sample already taken, for example at diagnosis, and kept by the hospital.
Whether a stored sample will do depends on when it was taken, how much there is and what the study needs. Ask whether the study accepts your stored sample or needs a new biopsy.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Biopsy and archival tissue
A biopsy takes a small piece of tissue to examine. “Archival tissue” is a sample already taken, for example at diagnosis, and kept by the hospital.
Whether a stored sample will do depends on when it was taken, how much there is and what the study needs. Ask whether the study accepts your stored sample or needs a new biopsy.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
ROC AUC of multi-task AI model for identification of renal allograft lesions
Area under receiver operating characteristic curve to evaluate model ability to detect rejection subtypes, polyomavirus nephropathy and recurrent primary renal disease.
Time frame: After model training and internal verification（through study completion, an average of 24 months）
Sensitivity and specificity of multi-task AI model for renal allograft lesion diagnosis
Sensitivity and specificity of the AI model discriminating TCMR, ABMR, polyomavirus nephropathy and recurrent primary renal disease.
Time frame: After model training and internal verification（through study completion, an average of 24 months）
Diagnostic accuracy of multi-task AI model for renal allograft lesions
Overall accuracy of the AI model in differentiating post-transplant renal pathological lesions.
Time frame: After model training and internal verification（through study completion, an average of 24 months）
ICC/Kappa consistency between AI quantitative scoring and pathologists' Banff evaluation
Agreement comparison between automated AI lesion quantification and manual Banff scoring by senior renal transplant pathologists.
Time frame: After model training, optimization and internal test set verification（through study completion, an average of 24 months）
ROC AUC of AI sub-model for prediction of recurrent renal allograft rejection
AUC for the AI prediction model to identify patients at risk of subsequent recurrent rejection within 12 months after biopsy.
Time frame: After extraction of 12-month routine follow-up data（through study completion, an average of 24 months）
Change in inter-pathologist diagnostic Kappa with AI model assistance
Comparison of pathologists' inter-observer consistency with and without auxiliary AI diagnosis of transplant kidney lesions.
Time frame: After model training and internal verification（through study completion, an average of 24 months）
This study is active, not recruiting, as verified in Jul 2026. You cannot join it, but the record below documents what was studied.
Get an email when the registry record changes — status, dates, results — or when someone posts here.
Sign in to followQuestions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.
Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.
Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.