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DESCRIPTION (provided by applicant): A long-term objective of this work is the development of a dedicated breast PET scanner that can be used for accurately characterizing and monitoring response of early stage breast tumors (stages I and II). This scanner will provide tomographic reconstructed images with very high resolution and sensitivity to detect, characterize, and monitor response in small tumors with low tracer uptake, something that is not performed well in the multi-purpose clinical PET scanners. It will be a partial ring scanner design in order to provide flexibility in imaging the whole breast (including chest wall) and possibly the axilla, to vary the detector separation for different breast sizes, to provide biopsy capability, as well as the potential to combine with other imaging modalities such as optical, mammography, or MR. Dedicated breast PET scanners currently available are forced to trade-off between spatial resolution and sensitivity, and until now the partial ring geometry leads one to choose between low contrast planar images or artifactual tomographic images with limited quantification capability. It is possible to achieve (improved) high quality tomographic images by rotating the detectors, but this adds complexity to the system and also restricts the dynamic imaging capabilities that are key to testing new radio-tracers. In contrast, our design will use time-of-flight (TOF) information to attain high quality and quantitative tomographic images for the partial ring scanner with stationary detectors, while maintaining high spatial resolution and sensitivity throughout the scanner field-of-view (FOV). Our aims are four fold: (i) develop a detector which maintains very good timing resolution while using small and long crystals for high spatial resolution and sensitivity, (ii) demonstrate the extent by which TOF information can compensate for the missing projection data, and investigate the trade-offs involved between spatial resolution, sensitivity, and timing resolution, as well as scanner angular coverage, to achieve an optimal scanner design, (iii) develop a coincidence imaging setup, and (iv) develop data correction and imaging reconstruction techniques for quantitative images followed by a characterization of the imaging performance of the coincidence setup. The work will involve detector measurements and simulations for testing varying crystal sizes and surface finishes, different types of photo-multiplier tubes, and full detector arrays. Full system simulations will be performed based upon detector measurement results for varying scanner geometries as well. Finally, an optimal detector design will be developed into coincident detector arrays and imaging experiments will be performed to demonstrate its capabilities. PUBLIC HEALTH RELEVANCE: Clinically for human imaging, limited spatial resolution and sensitivity of current generation of clinical PET scanners leads to reduced detection and quantification of small breast tumors. By developing a dedicated breast scanner with high resolution and sensitivity, as well as production of full tomographic images, will help in the detection and staging of early stage breast cancer. Hence, the development of a dedicated, TOF, breast scanner has the potential to significantly impact patient treatment for breast cancer.
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DOI: 10.1053/j.semnuclmed.2013.03.003
发表时间: 2013-07
期刊: Seminars in nuclear medicine
影响因子: 4.9
作者: [Surti S]
通讯作者: Surti S
Data Driven Background Estimation in PET Using Event Energy Information
  • 批准号:
    10644161
  • 项目类别:
  • 资助金额:
    $57.86万
  • 财政年份:
    2022
  • 负责人:
    Suleman Surti
  • 依托单位:
Optimization of Clinical and Research PET Imaging
  • 批准号:
    10322759
  • 项目类别:
  • 资助金额:
    $49.55万
  • 财政年份:
    2020
  • 负责人:
    Suleman Surti
  • 依托单位:
Optimization of Clinical and Research PET Imaging
  • 批准号:
    10580601
  • 项目类别:
  • 资助金额:
    $49.55万
  • 财政年份:
    2020
  • 负责人:
    Suleman Surti
  • 依托单位:
Energy-Based Scatter Estimation Algorithm for Accurate Quantitative PET Imaging
  • 批准号:
    9975773
  • 项目类别:
  • 资助金额:
    $19.39万
  • 财政年份:
    2019
  • 负责人:
    Suleman Surti
  • 依托单位:
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