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Clinical Trial Details — Status: Not yet recruiting

Administrative data

NCT number NCT05850845
Other study ID # HSI in CTX treaatment of IMN
Secondary ID
Status Not yet recruiting
Phase
First received
Last updated
Start date June 25, 2023
Est. completion date December 30, 2023

Study information

Verified date April 2023
Source Qianfoshan Hospital
Contact Wang Zunsong, doctor
Phone 18660190175
Email wzsong3@163.com
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Investigators propose hyperspectral imaging analysis as a method to distinguish the efficacy of hormone-combined cyclophosphamide therapy for PMN, and classify sensitive and insensitive patients treated with hormone-combined cyclophosphamide regimen. A variety of machine learning models were used to prove that hyperspectral imaging technology could assist patients in selecting the optimal treatment plan, and further explore the predictive indicators of PMN treatment effect.


Description:

Renal puncture pathological sections from patients with nephropathy. ENVI Classic software was used to process the hyperspectral images and delineate the region of interest, and the one-dimensional spectral data of each pixel in each region were derived. Machine learning and deep learning methods were used to analyze the characteristics of hyperspectral data and classify them. The data of the previous study came from the Department of Pathology and Nephrology of Qianfoshan Hospital in Shandong Province. Under the light microscope, electron microscope and immunofluorescence microscope, the pathological types of glomerular diseases in patients with proteinuria were identified. By scanning the corresponding patient's H&E stained pathological sections, the hyperspectral microscopic images were classified by machine learning and deep learning methods, and the classification accuracy was greater than 85%. It was concluded that hyperspectral imaging technology can be used as a non-invasive diagnostic method to predict treatment response.


Recruitment information / eligibility

Status Not yet recruiting
Enrollment 40
Est. completion date December 30, 2023
Est. primary completion date July 20, 2023
Accepts healthy volunteers No
Gender All
Age group 18 Years to 90 Years
Eligibility Inclusion Criteria: - Over 18 years old; - Patients with idiopathic membranous nephropathy confirmed by renal biopsy; - Had not received hormone and/or immunosuppressive therapy before renal biopsy; - Complete clinical data, all signed the "Admission Certificate of Qianfoshan Hospital of Shandong Province", and agreed to use relevant medical information, biological specimen examination and examination results for scientific research. Exclusion Criteria: - 1.There are factors causing secondary membranous nephropathy, such as immune diseases (systemic lupus erythematosus), tumors/infections (viral hepatitis), drugs or poisons, etc. ; - Severe infection: fever, cough and expectoration, sore throat, abdominal pain, diarrhea, carbuncle and furuncle and other clinical manifestations of skin and soft tissue infection, blood routine white blood cell count beyond the normal range (10×109/L); - Severe cardiovascular disease: including chronic heart failure grade 3 or above and various arrhythmias; - Infectious diseases: active hepatitis, AIDS, syphilis, etc. ; - Tumor evidence: it has been found that there is a certain tumor or clinical manifestations, tumor markers, etc., suggesting the possibility of tumor; - Patients with follow-up time less than 6 months, incomplete data or missed diagnosis;

Study Design


Related Conditions & MeSH terms


Intervention

Device:
Microscopic hyperspectral imaging system
CTX for idiopathic membranous nephropathy

Locations

Country Name City State
n/a

Sponsors (1)

Lead Sponsor Collaborator
Qianfoshan Hospital

Outcome

Type Measure Description Time frame Safety issue
Primary Microhyperspectral image of a transrenal specimen The microscopic hyperspectral images could accurately distinguish the remission group from the remission group with an accuracy of more than 80% 2023.3-2023.12
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