We propose to develop an operating-room-ready system for needle guidance in soft tissue, which fuses intra- operative ultrasound and pre-operative X-ray computed tomography (CT) data by combining two novel technologies: 1) a radically different way of visualizing and interacting with the fused ultrasound and CT images, which we call Spotlight"""""""";and 2) an innovative algorithm that automatically and continuously performs ultrasound-to-CT registration. Conventional image guidance during surgery has several problems. For example, intra-operative ultrasound guidance gives real-time feedback about the patient's anatomy, but some tumors are only visible in CT, which offers a higher resolution (and a larger 3D volume). On the other hand, a CT scan of soft tissue becomes obsolete as soon as the organs move by even a small amount, for example, due to breathing. The two modalities are usually viewed on separate monitors, which amplifies another problem: the appearance of anatomical features is usually different in ultrasound and in CT, and there is no visual correspondence between them. Furthermore, the pre-operative annotations of the CT-indicating the locations of tumors or lesions-cannot be seen in the context of the ultrasound. In this proposal, we address these problems by developing a guidance system that: 1) registers and fuses pre- operative CT with intra-operative ultrasound;2) dynamically volume-renders the CT scan and its pre-operative annotations in such a way as to highlight the most relevant portions of the dataset given the position of the ultrasound transducer and needle, while still indicating the remaining portions of the dataset for context;and 3) allows for intra-operative annotation to both modalities. To this end, we propose to refine and evaluate Spotlight iteratively, using phantoms and human patients. We also propose to develop a novel ultrasound-to- CT registration technique, to make it suitable for real-time operation during interventions, and to evaluate it, integrated with Spotlight, on human patients. For the evaluation, we will initially deploy the system in open surgical microwave ablation of liver tumors, but the technology is not limited to that specific intervention. In the future, it would be adapted to any procedure in which needles, ultrasound and pre-operative scans such as CT or MRI are employed. Our proposed system has potential to dramatically improve the utility of CT in the operating room, increasing the likelihood of an effective, efficient and complete intervention and improved patient outcome.

Public Health Relevance

We propose to develop a system that registers and visualizes pre-operative CT and intra-operative ultrasound images during surgical interventions. This system provides to the surgeon a combination of the two modalities'benefits while negating each other's shortcomings, allowing him to more effectively and efficiently perform the intervention. The surgeon can also make intra-operative annotations to both modalities with our system, so that he can mark all tumors that he intends to treat. Patient benefits of such a system will include shorter operating time, reduced risk of injury, and increased probability of complete tumor removal, in a variety of interventions, such as ablation, biopsy, and drug delivery.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
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Special Emphasis Panel (ZRG1-SBIB-T (10))
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Weber, Patricia A
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Inneroptic Technology, Inc.
United States
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Liu, Xiaoxiao; Niethammer, Marc; Kwitt, Roland et al. (2015) Low-Rank Atlas Image Analyses in the Presence of Pathologies. IEEE Trans Med Imaging 34:2583-91
Sindram, David; Simo, Kerri A; Swan, Ryan Z et al. (2015) Laparoscopic microwave ablation of human liver tumours using a novel three-dimensional magnetic guidance system. HPB (Oxford) 17:87-93
Kwitt, R; Vasconcelos, N; Razzaque, S et al. (2013) Localizing target structures in ultrasound video - a phantom study. Med Image Anal 17:712-22
Kwitt, Roland; Vasconcelos, Nuno; Razzaque, Sharif et al. (2012) Recognition in ultrasound videos: where am I? Med Image Comput Comput Assist Interv 15:83-90