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Medical Imaging 2016
October 20-21, 2016
Volume 5, Issue 5(Suppl) OMICS J Radiol
ISSN: 2167-7964 ROA, an open access journal
conferenceseries .com
October 20-21, 2016 Chicago, USA
International Conference on
Medical Imaging & Diagnosis
Michael L Goris et al., OMICS J Radiol 2016, 6:5(Suppl)
Analytical fusion of different modality images based on prior knowledge
Michael L Goris1, J Hongyun Zhu1 and Daniel Y Sze2
1Division of Nuclear Medicine
1Stanford University School of Medicine, California
2Division of Interventional Radiology
Background: Fusion is the simultaneous and combined analysis of two images mapping identically in the same object space,
but recording a different attribute of the object. Most fusion has been performed as visual representation in which the attributes
are represented independently into overlapping but independent color scales. In this work we explore fusion, in which the
attributes are combined in a mathematical or logical manner, to address a specific goal.
Methods: The first approach is mathematical, and concerns a particular combination of brain imaging: In patients treated for
brain tumors, the usually clear delineation of pathology by MRI is compromised because the treatment itself may produce
an ambiguous signal. Specifically, a FLAIR sequence will show post-treatment edema and recurrent tumor as a high signal
intensity region. FDG PET on the other hand will show little or no density in the former, and (near normal) in the latter.
A viable tumor would also show increased density in PET and post contrast T1 sequence, but not all post T1 high densities
represent regions with high metabolic activity. The combination of these a-priori judgments (or prior knowledge) can be done
in different manners: After normalization, the product MxP would favor viable tumor and the artangent of (P/M) would likely
represent non-viable or non-malignant lesions.
In the second approach, in preparation for a treatment of liver metastases with radioactive 90Y-labeled microspheres, the liver
is infused intra-arterially with 99mTc macro aggregates, imaged, and reinjected with 99mTc colloid and imaged. The result is
two in-line registered image volumes, defining MAA perfused tumor and liver, and functional liver (colloid) (Figure 2). The
analysis of the fusion allows the computation of relative and absolute volumes, and relative doses to liver and tumor. We found
that the relative dose to normal liver perfused by MAA is the best predictor of post therapy toxicity (as measured by the liver
enzyme elevation). In cases of toxicity, the average relative volume was 66%, in the absence of toxicity, the relative volume was
33% (p<0.01), with only one case overlapping.
Biography
Michael Goris has a Medical degree from the University of Leuven in Belgium and a PhD degree in Medical Physics from UC Berkeley. He has been a Professor
in the Stanford Medical School and is Emeritus since 2012 and served as a Chairman for University panel on Radiation safety during 2003-2010. He has more
than 120 publications in peer reviewed, journals. His research interests are Radio-immunotherapy, Medical Imaging Processing and Quantification for diagnosis
Clinical validations.