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In vivo dual-axis confocal microscopy of 5-ALA-induced PpIX to guide low-grade glioma resections

In vivo dual-axis confocal microscopy of 5-ALA-induced PpIX to guide low-grade glioma resections
5-ALA 诱导的 PpIX 体内双轴共聚焦显微镜指导低级别胶质瘤切除
批准号:
10407972
负责人:
Jonathan T.C. Liu
金额:
$53.94万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-06-01 至 2025-05-31

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Summary Extent-of-resection is correlated with glioma patient outcomes such as progression-free survival. Image- guidance technologies, based on MRI and now fluorescence-guided surgery (FGS), have been developed to improve the surgeon’s ability to visualize gross tumor margins. However, there are fundamental limitations to wide-field imaging methods such as MRI and FGS, such as poor sensitivity to detect disseminated tumor cells at the infiltrative margins of diffuse gliomas, as well as the non-quantitative and subjective nature of image interpretation. With the emergence of FGS using 5-ALA, and its recent approval by the FDA in 2017, the gap between low-grade glioma (LGG) and high-grade glioma (HGG) patients, in terms of extent of resection, will likely widen since LGGs rarely generate sufficient PpIX fluorescence to be detected via wide-field FGS. Consequently, there is a clear need for improved intraoperative techniques with the sensitivity to detect and quantify residual LGGs at the margins of the tumor cavity in order to improve the extent of resection and delay recurrence. We have shown that high-resolution confocal microscopy has the sensitivity to visualize the sparse sub-cellular expression of PpIX in LGG patients treated with 5-ALA, even beyond the radiographic margins. Therefore, we will optimize a handheld optical-sectioning microscope to image 5-ALA-induced PpIX at the final resection margins in LGG patients, together with real-time video mosaicking to facilitate the imaging of large tissue areas, which will minimize sampling bias when imaging heterogeneous brain tissues (Aim 1). In order to facilitate the clinical acceptance of these techniques, we will establish a relationship between the microscopic patterns of PpIX expression and well-established biological metrics such as tumor burden and proliferative index (Aim 2). Finally, we will explore the hypothesis that quantitative microscopic imaging of PpIX of the resection margins is predictive of extent of resection, as currently defined by post-operative MRI, which would suggest that it has value for optimizing resections to minimize and/or delay recurrence (Aim 3). Collectively, these results will pave the way for future randomized controlled clinical studies to optimize resection procedures and outcomes for LGG patients (adults and children), many of whom can have good survival outcomes and quality of life.
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Prostate cancer risk stratification via computational 3D pathology
  • 批准号:
    10647788
  • 项目类别:
  • 资助金额:
    $60.92万
  • 财政年份:
    2022
  • 负责人:
    Jonathan T.C. Liu
  • 依托单位:
Prostate cancer risk stratification via computational 3D pathology
  • 批准号:
    10459767
  • 项目类别:
  • 资助金额:
    $62.44万
  • 财政年份:
    2022
  • 负责人:
    Jonathan T.C. Liu
  • 依托单位:
Instrumentation platform for 3D pathology with open-top light-sheet microscopy
  • 批准号:
    10434718
  • 项目类别:
  • 资助金额:
    $46.94万
  • 财政年份:
    2021
  • 负责人:
    Jonathan T.C. Liu
  • 依托单位:
Instrumentation platform for 3D pathology with open-top light-sheet microscopy
  • 批准号:
    10178401
  • 项目类别:
  • 资助金额:
    $55.87万
  • 财政年份:
    2021
  • 负责人:
    Jonathan T.C. Liu
  • 依托单位:
海外基金