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Deformable mapping of MRI and MRSI data to TRUS images to guide prostate biopsy

Deformable mapping of MRI and MRSI data to TRUS images to guide prostate biopsy
将 MRI 和 MRSI 数据变形映射到 TRUS 图像以指导前列腺活检
批准号:
7472018
负责人:
STEPHEN M PIZER
金额:
$18.61万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-09-24 至 2010-08-31

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英文摘要
DESCRIPTION (provided by applicant): The most common procedure for prostate biopsy for cancer diagnosis and staging involves the introduction of small-gauge needles from the rectum under the guidance of trans-rectal ultrasound imaging (TRUS). In most cases TRUS differentiates poorly or not at all between normal tissue and cancer in the prostate and therefore provides minimal guidance for targeting localized regions at risk within the prostate. Our hypothesis is that this shortcoming can be overcome by methodology to deformably map a patient-specific atlas of suspicious tissue volumes within the prostate, built from pre-biopsy magnetic resonance (MR) and magnetic resonance spectroscopic (MRS) images, to TRUS images during biopsy to serve as targets for accurate needle placement. The near-term research described in this proposal involves pilot studies using a novel and especially effective class of statistically trainable deformable-shape model (SDSM) called m-reps to perform this mapping. The most common procedure for prostate biopsy for cancer diagnosis and staging involves the introduction of small-gauge needles from the rectum under the guidance of trans-rectal ultrasound imaging (TRUS). In most cases TRUS differentiates poorly or not at all between normal tissue and cancer in the prostate and therefore provides minimal guidance for targeting localized regions at risk within the prostate. The proposed methodology will overcome this shortcoming by mapping a patient-specific atlas of suspicious tissue volumes from pre-biopsy magnetic resonance (MR) and magnetic resonance spectroscopic (MRS) images to TRUS images during biopsy to serve as targets for accurate needle placement.
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Deformable mapping of MRI and MRSI data to TRUS images to guide prostate biopsy
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