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Differentiating Tumor-stroma Ratio in Pancreatic Ductal Adenocarcinoma


2013-01


2022-07


2024-03


207

Study Overview

Differentiating Tumor-stroma Ratio in Pancreatic Ductal Adenocarcinoma

This study introduces a novel transfer learning-based contrastive language-image pretraining adapter (CLIP-adapter) model for predicting the tumor-stroma ratio (TSR) in pancreatic ductal adenocarcinoma (PDAC) using preoperative dual-phase CT images. The primary aim is to develop an efficient and accessible tool for risk stratification and personalized treatment planning.

The proposed novel Contrastive Language-Image Pretraining-Adapter (CLIP-adapter) model, leveraging transfer learning, framing CLIP and a self-attention mechanism for predicting TSR in PDAC, in order to exhibit high performance in distinguishing low and high TSR PDAC in the test cohort. We speculated the CLIP-adapter model outperformed single-phase models, specifically CLIP models based on arterial or venous phase images alone. The addition of a feature fusion module could enhance the model's differentiation capacity, emphasizing its superiority over single-phase models. Besides, the model we designed utilized both image and text information during network training, instead of focusing on images only. This underscores the importance of comprehensive assessment in PDAC imaging evaluation, with the potential to contribute to risk stratification and personalized treatment planning.

  • Pancreatic Ductal Adenocarcinoma
    • liaohongfan

    Study Record Dates

    These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

    Study Registration Dates Results Reporting Dates Study Record Updates

    2024-02-29  

    N/A  

    2024-03-07  

    2024-03-07  

    N/A  

    2024-03-12  

    2024-03-12  

    N/A  

    2024-02  

    Study Plan

    This section provides details of the study plan, including how the study is designed and what the study is measuring.

    Design Details

    Primary Purpose:
    N/A


    Allocation:
    N/A


    Interventional Model:
    N/A


    Masking:
    N/A


    Arms and Interventions

    Participant Group/ArmIntervention/Treatment
    : low TSR and high TSR group

    The assessment of the tumor-stroma ratio (TSR) entailed measuring the percentage of tumor and stroma constituents. Based on earlier research, 5/5 was deemed as ideal threshold of TSR measurement.

    Primary Outcome MeasuresMeasure DescriptionTime Frame
    The diagnostic AUC value of pancreatic ductal adenocarcinoma with deep learning algorithm.AUC=(Sensitivity+Specificity)-11 year
    Secondary Outcome MeasuresMeasure DescriptionTime Frame
    The diagnostic accuracy of pancreatic ductal adenocarcinoma with deep learning algorithm.The diagnostic accuracy of pancreatic ductal adenocarcinoma with deep learning algorithm.1 year
    The diagnostic sensitivity of pancreatic ductal adenocarcinoma with deep learning algorithm.The diagnostic sensitivity of pancreatic ductal adenocarcinoma with deep learning algorithm.1 year
    The diagnostic specificity of pancreatic ductal adenocarcinoma with deep learning algorithm.The diagnostic specificity of pancreatic ductal adenocarcinoma with deep learning algorithm.1 year
    The diagnostic positive predictive value of pancreatic ductal adenocarcinoma with deep learning algorithm.The diagnostic positive predictive value of pancreatic ductal adenocarcinoma with deep learning algorithm.1 year
    The diagnostic negative predictive value of pancreatic ductal adenocarcinoma with deep learning algorithm.The diagnostic negative predictive value of pancreatic ductal adenocarcinoma with deep learning algorithm.1 year

    Contacts and Locations

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    Participation Criteria

    Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person’s general health condition or prior treatments.

    Ages Eligible for Study:
    ALL

    Sexes Eligible for Study:

    Accepts Healthy Volunteers:

      Inclusion Criteria:
      1. patients with pathologically proven PDAC by surgical resection 2. patients who underwent CT scan within a month before surgery 3. observable pancreatic lesions on available images.
      Exclusion Criteria:
      1. any anti-cancer therapy before CT scanning 2. conspicuous interference or significant motion distortions found on images 3. partial clinical data 4. patients with liver metastases or peritoneal carcinomatosis prior to surgical intervention.

    Collaborators and Investigators

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    Publications

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    General Publications

    No publications available