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临床试验/NCT05466760
NCT05466760Unknown不适用

Use of PET/MR Radiomics to Evaluate the Clinical Phenotypes, Response Status of Neoadjuvant Chemotherapy and Long-term Prognosis of Breast Cancer: a Preliminary Study

Taipei Veterans General Hospital, Taiwan1 个研究点 分布在 1 个国家目标入组 120 人开始时间: 2018年7月6日最近更新:
适应症

试验速览

阶段
不适用
入组人数
120
试验地点
1
主要终点
Diagnostic performance of PET/MR imaging metrics in prediction of treatment response to chemotherapy

研究概览

简要总结

Breast cancer is the most common malignancy in women in our country (2013 cancer registry report, Health Promotion Administration). MRI is a more accurate imaging modality for breast lesion diagnosis, monitoring of treatment response, and local staging than compared with mammography and ultrasound. ¹⁸ F-FDG PET was reported to be used for breast cancer diagnosis, staging, and prediction of treatment response as well. We usually interpret the aforementioned imaging modalities by qualitative methods for decision-making. Radiomics is a process involving the conversion of images to quantitative data for subsequent data mining to improve decisional making for patient care, to adjust the patient management, that is so-called precision medicine. Our study is to use semantic and agnostic features of radiomics by hybrid PET/MR for 1. The pre-operative breast cancer patients (without neoadjuvant chemotherapy before operation). 2. The patients will receive neoadjuvant chemotherapy (NAC). The study intends to investigate the association of PET/MR radiomics data with the probability of metastasis or risk of recurrences and survival. We will also investigate if the BD and BPE (measured on MRI) are associated with molecular subtypes, histologic grade and clinical outcome, risk of metastases, and long-term survival of breast cancer patients for the study participants.

详细描述

Purposes and background introduction:

Breast cancer is the most common malignancy in women in our country (2013 cancer registry report, Health Promotion Administration). MRI is a more accurate imaging modality for breast lesion diagnosis, monitoring of treatment response, and local staging than compared with mammography and ultrasound. ¹⁸ F-FDG PET was reported to be used for breast cancer diagnosis, staging, and prediction of treatment response as well. We usually interpret the aforementioned imaging modalities by qualitative methods for decision-making. In recent years, the concept of "Radiomics" is emerging. Radiomics is a process involving the conversion of images (imaging phenotypes) to quantitative data for subsequent data mining to improve decisional making for patient care, to adjust the patient management, that is so-called precision medicine. Radiomics is applied for the diagnostic, prognostic, and predictive purposes of diseases. There are two main approaches to radiomics: First, the semantic approach, which uses the usual radiological lexicon derived from regions of interest; second, the agnostic approach is higher-order, mathematically computed data derived from images instead of the commonly used radiologists' lexicon. MRI and PET can be used in breast radiomics studies. Hybrid PET/MR is a machine that the PET and MRI can be performed on the same table at the same time slot, therefore, the imaging data of MRI and PET can be obtained at the same examination, with less radiation dosage, more reliable lesion mapping than separate examinations of PET/CT and MRI.

Material and methods:

There is a total of 120 patients would like to be included in the study. Our study is to use semantic and agnostic features of radiomics by hybrid PET/MR for:

  1. The pre-operative breast cancer patients (without neoadjuvant chemotherapy before operation): to investigate the association of PET/MR imaging data with molecular subtypes, cell proliferation (Ki-67), tumor aggressiveness (by histologic grade).
  2. The patients who will receive neoadjuvant chemotherapy (NAC): PET/MR study will be performed for 3 times: pre-MAC (study 1), PET/MR after 1st dose of NAC (study 2), and PET/MR after 3rd or 4th NAC (study 3). We will investigate the predictive ability of PET/MR imaging data for NAC response. And we will investigate which parameters at which series of examinations are more predictive of the final NAC response. Therefore, we can adjust the NAC regimen as early as possible.
  3. The breast cancer patients mentioned above: we will investigate the association of PET/MR radiomics data with the probability of metastasis or risk of recurrences and survival.
  4. We will also investigate if the BD and BPE (measured on MRI) are associated with molecular subtypes, histologic grade and clinical outcome, risk of metastases, and long-term survival of breast cancer patients for the study participants.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
25 Years 至 75 Years(Adult, Older Adult)
性别
Female
接受健康志愿者

入选标准

  • Women aged 25-75 years old.
  • Women with recently diagnosed breast cancer.

排除标准

  • Estimated GFR (eGFR) < 60 mL/min/1.73 m2 and blood glucose > 135 mg/dl; Past/ present history of acute renal failure, renal dialysis, DM.
  • Women with metallic fixation, coronary artery stent in recent 3 months; or women with mechanical valve replacement not compatible with MR magnet; or women with aneurysmal clips, pacemakers.
  • Past history of claustrophobia.
  • Women who are pregnant or who are planning to be pregnant, or who are lactating
  • Past history of breast cancer within recent 5 years
  • Women undergoing chemotherapy for other disease entity in recent 1 year.
  • Women who cannot cooperate with the examinations.

结局指标

主要结局

Diagnostic performance of PET/MR imaging metrics in prediction of treatment response to chemotherapy

时间窗: 40 weeks

Determination of the sensitivity, specificity of PET/MR imaging metrics to predict treatment response to neoadjuvant chemotherapy. The treatment response will be determined by RCB (residual cancer burden) index at surgical pathology after completion of neoadjuvant chemotherapy and further categorized as group 1: RCB 0 or I; group 2: RCB II or III. The logistic regression will be performed with the groups (1 or 2) as dependent variable and the different PET/MR imaging metrics as independent variables, the ROC analysis and sensitivity, specificity of the PET/MR imaging metrics will be inferred from the regression models.

次要结局

  • Comparison of PET/MR imaging metrics among patients with different molecular subtypes.(2 weeks)
  • Comparison of PET/MR imaging metrics among patients with different histologic grades(2 weeks)
  • Performance of PET/MR imaging metrics to predict the recurrence status.(5 years)

研究者

申办方类型
Other Gov
责任方
Sponsor

研究点 (1)

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