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Improving liver lesion biopsy in the CT suite through fusion with PET images
Phone: (202) 476-3809
Phone: (202) 994-6255
Phone: () -
Type: Nonprofit College or University
DESCRIPTION (provided by applicant): The broad objective of this proposal is to improve the clinical effectiveness of liver lesion biopsy by fusing respiratory-compensated PET with CT images in the CT suite. On CT imaging alone, localization of liver lesions can potentially be challenging, particularly in selected cases where differentiation of the tumor from adjacent liver parenchyma may be difficult. Given the ability of PET to localize malignancies in situations where the same tumors do not have a CT correlate, we believe that PET-CT guided biopsy would improve the diagnostic yield of liver lesion biopsies by providing guidance in targeting a metabolically active lesion or a specific metabolic hot spot within a larger liver lesion. However, the diagnostic benefit of using PET scans (even from hybrid PET/CT machines) is gravely affected by respiratory motion artifacts. CT data is acquired in a short time representing an instantaneous snapshot during the breathing cycle. On the other hand, PET data acquisition takes an average 3-10 minutes per gantry table position. For typical procedures, 5 -7 gantry positions are required on average. These prolonged acquisition times lead to respiratory motion artifacts in the images. These artifacts, in turn, cause discrepancy in spatial correspondence between the CT and PET data, inaccurate tumor localization, and incorrect tumor staging. Hence, development of an effective PET-CT guided biopsy for liver lesions requires a robust respiratory motion correction technique. We propose to develop respiratory motion correction and registration components suitable for abdominal imaging and extend our open source image-guided surgery system (IGSTK) to enable PET/CT guided liver lesion biopsy in the CT suite. The respiratory motion correction algorithm will utilize phase matched respiratory-gated PET and CT data and super- resolution reconstruction algorithm to generate a motion-free high quality PET image. We will develop a novel image registration algorithm that will compensate for respiration-induced organ- sliding. Organ-sliding is not handled well by traditional registration methods which assume that one image can be smoothly deformed into the next. PUBLIC HEALTH RELEVANCE: PET/CT imaging plays a key role in early detection, staging, and evaluation of suspicious lesions. PET imaging provides information on functional or metabolic characteristics of tumors, whereas CT predominately assesses the tumor's anatomical and morphological features. By fusing these two imaging techniques and incorporating advanced image registration and respiratory motion compensation techniques, clinicians can effectively biopsy liver lesions.
* Information listed above is at the time of submission. *