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Project

Non-invasive quantification of microcirculation heterogeneity as a biomarker for the diagnosis and response prediction of bladder cancer

Funder: Bladder Cancer Advocacy Network

Funding period
USD 2 K
Funding amount
Abstract
The goal of this proposed study is to evaluate and develop a quantitative MRI methodology as a non-invasive biomarker for the diagnosis and response prediction of bladder cancer. The methodology combines pharmacokinetic parameters estimated from dynamic contrast-enhanced MRI (DCE-MRI) with k-means clustering, a data mining tool, to quantify the spatial heterogeneity of microcirculation in bladder tumors. Fifty eligible patients will be enrolled in two years, receive 4 cycles of neoadjuvant chemotherapy, and have three MRIs (baseline, mid-treatment, and post-treatment) followed by radical cystectomy. All cystectomy specimens will be examined by pathology whose findings will be used as a gold standard. The k-means clustering of DCE-MRI pharmacokinetic parameters will be performed for each bladder tumor to acquire the cluster maps and to calculate the volume fraction (VF) of three clusters in the tumor at baseline, mid-treatment, and post-treatment for the visual and quantitative assessments of the microcirculation heterogeneity. These assessments will be correlated with the malignancy, tumor stage, and tumor response using the gold standard. In Aim 1, we will evaluate the ability of k-means clustering of DCE-MRI pharmacokinetic parameters to differentiate malignant tumors from benign wall thickening to improve the cancer detection. Aim 2 is to assess the capability of the MRI methodology in the local staging of bladder cancer, which will include the assessment of stage-by-stage, muscle invasion within the bladder wall, and perivesical fat infiltration. For Aim 3, the methodology will be validated to be used as a biomarker for the prediction of chemotherapeutic response in bladder cancer at the mid-treatment point. In summary, based on our preliminary data, we aim at applying the quantitative MRI methodology as a non-invasive biomarker to improve the detection and local staging as well as to enable the prediction of chemotherapeutic response in bladder cancer.
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System

Categories
  • FOR (ANZSRC)

    1112 Oncology and Carcinogenesis

  • RCDC

    Biomedical Imaging

  • RCDC

    Cancer

  • RCDC

    Clinical Research

  • RCDC

    Urologic Diseases

  • HRCS HC

    Cancer

  • HRCS RAC

    4.2 Evaluation of markers and technologies

  • Broad Research Areas

    Clinical Medicine and Science