Satisfactory Debulking Prediction Model for Advanced Ovarian Cancer Based on PET-CT Image Data

NCT ID: NCT06533709

Last Updated: 2024-08-01

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 146 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-06-01
• Study Completion Date: 2026-05-31

Brief Summary

This project intends to conduct a multicenter retrospective study to evaluate the satisfactory reduction of advanced ovarian cancer using PET-CT images, and explore the correlation between molecular biological characteristics and clinical characteristics of ovarian cancer through high-throughput sequencing genomics combined with radiomics.

Detailed Description

Ovarian cancer is the gynecological malignant tumor with the highest fatality rate. More than 70% of patients are diagnosed with advanced stage, often involving various organs of the pelvis and abdomen, which increases the difficulty of surgical resection, and the 5-year survival rate is only 30%. Surgical treatment is the cornerstone of the treatment of ovarian cancer, and whether it can achieve satisfactory tumor reduction is an important factor affecting the prognosis of ovarian cancer. At present, the methods used to evaluate whether satisfactory tumor reduction can be achieved include Suidan score based on CT image and Fagotti score based on laparoscopic exploration, but there are problems such as low sensitivity, poor specificity or strong subjectivity, and the efficiency of predicting satisfactory tumor reduction is only about 60%. In recent years, PET-CT has been widely used in tumor diagnosis. Pet-ct combined with PET metabolic imaging technology and traditional CT scanning can help to distinguish the nature of tumors, assess the systemic tumor load, define the scope of the lesion, and provide the metabolic status of various parts of the body. The application value of PET-CT related imaging features and metabolic information in ovarian cancer needs to be clarified. Our team's previous study found that PET-CT related images and metabolic information showed certain advantages in predicting satisfactory resection of ovarian cancer, and the AUC reached 0.85, which was better than the current CT image score and laparoscopic score. Therefore, this project intends to conduct a multicenter retrospective study to evaluate the satisfactory tumor reduction rate of advanced ovarian cancer using PET-CT images to guide clinical practice and predict the prognosis of patients. At the same time, we will explore the molecular biological characteristics and clinical relevance of ovarian cancer through the combination of high-throughput sequencing genomics and radiomics.

Conditions

Ovarian Cancer; Image; Predation

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: RETROSPECTIVE

Study Groups

SYSU cohort

Patients cohort from Sun Yat-sen Memorial Hospital, as the training cohort.

Radio-score

Intervention Type: DIAGNOSTIC_TEST

A score based on the LASSO regression model predicting the R0 resection of the primary debulking surgery of advanced ovarian cancer.

ZJCH cohort

Patients cohort from Zhejiang Cancer Hospital, as the external validation cohort.

Radio-score

Intervention Type: DIAGNOSTIC_TEST

A score based on the LASSO regression model predicting the R0 resection of the primary debulking surgery of advanced ovarian cancer.

Interventions

Radio-score

A score based on the LASSO regression model predicting the R0 resection of the primary debulking surgery of advanced ovarian cancer.

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

• Pathological type is epithelial ovarian cancer.
• Underwent primary debulking surgery at our hospital.
• Postoperative pathological staging is FIGO stage IIB or above.
• Clinical, surgical, and pathological data of the patient are mostly complete.

Exclusion Criteria

• Pathological type is non-epithelial ovarian cancer.
• Underwent fertility-preserving surgery or palliative surgery.
• Presence of infection during PET/CT image acquisition.
• Concurrent other malignant tumors.
• Severe diseases of other major organs.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: No

Sponsors

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

huaiwu Lu

Role: PRINCIPAL_INVESTIGATOR

The Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Locations

The Sun Yat-sen Memorial Hospital of Sun Yat-sen University

Guangzhou, Guangdong, China

Site Status: RECRUITING

Countries

China

Central Contacts

Huaiwu Lu

Role: CONTACT

luhuaiwu@mail.sysu.edu.cn

86+ 18688395806

Dongdong Ye

Role: CONTACT

yedd3@mail2.sysu.edu.cn

86+ 15218054426

Facility Contacts

huaiwu Lu

Role: primary

luhuaiwu@mail.sysu.edu.cn

86+ 18688395806

References

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Reference Type: RESULT

PMID: 11870167 (View on PubMed)

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Reference Type: RESULT

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Reference Type: RESULT

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Reference Type: RESULT

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Reference Type: RESULT

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Dondi F, Albano D, Bellini P, Camoni L, Treglia G, Bertagna F. Relationship between Baseline [18F]FDG PET/CT Semiquantitative Parameters and BRCA Mutational Status and Their Prognostic Role in Patients with Invasive Ductal Breast Carcinoma. Tomography. 2022 Oct 27;8(6):2662-2675. doi: 10.3390/tomography8060222.

Reference Type: RESULT

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Other Identifiers

SYSKY-2024-503-01

Identifier Type: -

Identifier Source: org_study_id