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A Comprehensive Cancer Center Designated by the National Cancer Institute

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Advanced Imaging

Members in the Advanced Imaging Program have made significant advances in computer-aided diagnosis, new methods for image reconstruction and acquisition, new imaging techniques for cancer therapy evaluation, and image-guided therapy for in vitro cancer-related applications.

Over the past year, members of the Program have produced 50 published articles, with 20% being intraprogrammatic and 24% interprogrammatic collaborations. The publications summarized below highlight pioneering research that emphasizes collaboration and the use of new technologies and equipment.

Research Highlights

Researchers develop a targeted method to deliver therapeutic and imaging agents into tumor cells 
Anthony Kossiakoff, PhD, engineered a variant of SP (SPv) that enables specific delivery of proteins to NK1R-expressing cells. This method of receptor-mediated delivery targets diseased cells, while sparing normal cells and, concomitantly, conjugation with tracers for imaging can lead to high specificity. Unlike larger ligands that could be used in receptor-mediated delivery, SPv is easily chemically synthesized, allowing the incorporation of various reactive groups to facilitate coupling to myriad biomolecular cargos, including therapeutic and imaging agents. (Rizk et al., Bioconjug Chem 18:42-6, 2012)
This work was funded by grants U54 GM087519 and F32DK080619 from the National Institutes of Health. 

T2* weighted MR imaging may help identify early pre-invasive breast cancers
Gregory Karczmar, PhD, and colleagues including Dr. Suzanne Conzen (Molecular Mechanisms of Cancer Program) investigated the feasibility of using T2* weighted MR imaging, an alternative imaging approach that is sensitive to deoxygenated blood found in tumor blood vessels and does not require contrast injection, as a diagnostic indicator of early breast cancer in a mouse model. The researchers found statistically significant differences in T2* values between normal mammary tissue and intraductal cancers. These results are the first reported T2* measurements from single mammary ducts and demonstrate the potential utility for identifying early pre-invasive cancers. (Hipp et al., Med Phys 39:1309-13, 2012)
This work was supported by grants from the Segal Foundation, the National Institutes of Health (P50 CA125183-01, R33CA100996-02, R01CA133490-01A2), and the UCCCC.

PET/CT scanning predicts overall survival rates in patients with non-small-cell lung cancer
New research shows that tumor measurements from PET/CT scanning can be used as a prognostic index of survival in patients who have undergone surgery for non-small-cell lung cancer (NSCLC). Yonglin Pu, MD, PhD, and colleagues performed a retrospective study of surgical patients diagnosed with NSCLC who had baseline tumor measurements taken from 18Flurodeoxyglucose (FDG)-PET/CT scans. Whole-body metabolic tumor burden was assessed by measuring the volume of tumor tissue showing increased uptake of FDG on PET, known as metabolic tumor volume (MTV), and total lesion glycolysis (TLG), a measure that reflects both the volume and metabolic rate of tumors. High MTV and TLG measurements were both associated with decreased overall survival rates. Previous studies have already shown the prognostic value of these PET/CT measurements in nonsurgical patients with NSCLC. However, this is the first study demonstrating its value in surgical patients with NSCLC independent of disease stage. (Zhang et al., Acad Radiol published online ahead of print, September 2012)

Texture correlates with genotype on full-field digital mammograms
With the goal of determining whether individual breast cancer risk can be accurately assessed using image-based biomarkers, Charlene Sennett, MD, and colleagues including Drs. Olufunmilayo I. Olopade (Cancer Control and Prevention Program) and Maryellen L. Giger used quantitative image analysis on a large dataset of full-field digital mammograms (FFDM) of women at both high and low risk for breast cancer. Their results from computerized texture analysis on digital mammograms demonstrated that high-risk and low-risk women have different mammographic parenchymal patterns. This study validated the team’s methods for quantitative analyses of mammographic patterns on FFDM and statistically demonstrated again that women at high risk tend to have dense breasts with coarse and low-contrast texture patterns. (Li et al., J Digit Imaging 25:591-9, 2012)
This research was supported in part by the University of Chicago Breast SPORE P50-CA125183, Department of Energy grant DE-FG02-08ER6478, and National Institute of Health grants S10 RR021039, and P30 CA14599. 

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