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Abstract #3628

Automatic Alignment for Tumor Assessment

Alexander Brost1, Neilesh Gupta1, Christoph Seeger1, 2, Aaryani Tipirneni1, Zhaoying Han1, Sjoerd B. Vos1, 3, Julian R. Maclaren1, Matus Straka1, Nancy J. Fischbein1, Roland Bammer1

1Center for Quantitative Neuroimaging, Stanford University, Stanford, CA, United States; 2Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany; 3Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands

The assessment of brain tumor progression or regression is an important task in neuroradiology. To standardize review, baseline 3D MRI brain scans were first registered to an atlas and kept in a research PACS system (RAPID). When patients presented for follow-up studies, these were registered to the baseline data set and displayed next to each. Comparison of tumor behavior between the two scans was also more accurate and interpreted with higher confidence. Automatic registration of 3D data for image alignment on serial studies offers a faster and more accurate assessment of changes in tumor size than the standard clinical assessment.