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Contrast-enhanced CT-based Deep Learning Model for Preoperative Prediction of Disease-free Survival (DFS) in Localized Clear Cell Renal Cell Carcinoma (ccRCC)

Contrast-enhanced CT-based Deep Learning Model for Preoperative Prediction of Disease-free Survival (DFS) in Localized Clear Cell Renal Cell Carcinoma (ccRCC)

Recruiting
All
Phase N/A
  • Technical (Original)
  • Simplified (AI rewritten)

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Overview

This study aims to preoperatively predict DFS of patients with localised ccRCC using a deep learning prognostic model based on enhanced contrast CT images, validate it's predictive ability in multicentre data and compare it's predictive ability with traditional models.

Eligibility

Inclusion Criteria:

  • Patients who underwent partial/radical nephrectomies and histologically diagnosed as ccRCC

Exclusion Criteria:

  • (1) with incomplete clinic-pathological data; (2) lack of preoperative contrast-enhanced CT images or the image quality was unsuitable for analysis; (3) who received pre-surgery neoadjuvant or adjuvant therapies; (4) with multiple renal tumors or/and had synchronous metastasis

Study details
    Predictive Ability of Contrast-enhanced CT-based Deep Learning Model in Patients With Localised ccRCC
    Generalisation of a Deep Learning Prediction Model in Multicentre Data
    Comparison of Prediction Performance Between Deep Learning Prediction Model and Traditional Prediction Models

NCT06088134

Mingzhao Xiao

27 January 2024

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