Program Information
A Review of Advanced PET and CT Image Features for the Evaluation of Tumor Response
W Lu*, University of Maryland School of Medicine, Baltimore, MD
Presentations
SU-E-QI-20 Sunday 3:00PM - 6:00PM Room: Exhibit HallPurpose: To review the literature in using quantitative PET and CT image features for the evaluation of tumor response.
Methods: We reviewed and summarized more than fifty papers that use advanced, quantitative PET/CT image features for the evaluation of tumor response. We also discussed future works on extracting disease-specific features, combining multiple and complementary features in response modeling, delineating tumor in multi-modality images, and exploring biological explanations of these advanced features.
Results: Advanced PET image features considering spatial information, such as tumor volume, tumor shape, total glycolytic volume, histogram distance, and texture features (characterizing spatial distribution of FDG uptake) have been found more informative than the traditional SUVmax for the prediction of tumor response. Advanced CT features, including volumetric, attenuation, morphologic, structure, and texture descriptors, have also been found advantage over the traditional RECIST and WHO criteria in certain tumor types.
Conclusions: Advanced, quantitative FDG PET/CT image features have been shown promising for the evaluation of tumor response. With the emerging multi-modality imaging performed at multiple time points for each patient, it becomes more important to analyze the serial images quantitatively, select and combine both complementary and contradictory information from various sources, for accurate and personalized evaluation of tumor response to therapy.
Funding Support, Disclosures, and Conflict of Interest: This work was supported in part by the National Cancer Institute Grant R21 CA131979 and R01CA172638.
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