Research Program Five:  Advanced Imaging

Program Leader:  Maryellen L. Giger, PhD

Overview and Scientific Goals

The University of Chicago Cancer Research Center is at the forefront of the imaging revolution that is transforming cancer care. Extraordinary advances in imaging pioneered at the Cancer Center are helping specialists diagnose cancer in its early, less harmful stages, and attack cancerous tumors with greater precision and with less harm to healthy tissue. Imaging is a crucial element in cancer treatment, in the analysis of many animal models of cancer, and in a large number of in vitro cancer-related experiments. Consequently, the Advanced Imaging Program plays a key role in research at the Center.

The Advanced Imaging Program consists of 25 members from two departments.  The scientific goals of the Program include:

  • investigating new methods for computerized image analysis to help in the early diagnosis of cancer (breast, lung, colon, and prostate carcinomas);
  • investigating new methods of image reconstruction for use in CT (computed tomography), SPECT (single photon emission computed tomography), and PET imaging;
  • developing new methods of image acquisition such as MRIS (magnetic resonance imaging and spectroscopy) and EPR (electron paramagnetic resonance imaging) methods;
  • identifying  imaging methods for oncology practice and for the evaluation of response to target-based cancer drugs; and
  • investigating methods for the evaluation of imaging systems, especially as they apply to computer-aided diagnosis and new imaging instrumentation. The Program strives to achieve these goals by integrating and focusing the work of investigators with established research programs and by promoting collaborations.

Program Highlights 2005 – 2007

  • Gregory Karczmar, PhD, Gillian Newstead, MB, ChB, FACR, and their colleagues are exploring an enhanced form of magnetic resonance imaging (MRI). Their development of high spectral and spatial resolution (HiSS) MRI is proving instrumental in the early detection and staging of breast cancer by producing three-dimensional MRIs, which show breast tissue with extraordinary clarity. Preliminary clinical evaluation shows that images produced from HiSS data have improved fat suppression, texture, and lesion conspicuity compared to conventional fat-saturated images. Tumors and other breast abnormalities can be detected with HiSS before contrast agents are injected. Because of the potential improvements in sensitivity and specificity for early breast cancer detection, industry is collaborating with them to develop clinical applications of this method. (Fan et al. Magn Reson Med 45:1046, 2001; Du et al. Radiology 224:577, 2002; Medved et al. Magn Reson Med 52:193, 2004;  Medved et al. Am J Roentgenol,186:30, 2006).
     
  • Robert M. Nishikawa, PhD, Ingrid Reiser, PhD, Maryellen Giger, PhD and their colleagues are investigating computerized detection of mass lesions on breast tomosynthesis images. Results indicate that computerized detection can be used to locate lesions on breast tomosynthesis, and that a combination of analyses – either on the projection images or on the reconstructed slices – can reduce the number of false-positive detections (Reiser et al. Technol Cancer Res Treat 3:437, 2004; Reiser et al. Med Phys 33:482, 2006).
     
  • Dr. Giger, Dr. Nishikawa, Yulei Jiang, PhD and their colleagues are working with mammographers to translate their multimodality breast imaging workstations to the clinical arena for evaluation. (Horsch et al. Radiology 240:357, 2006).
     
  • Drs. Giger and Newstead are collaborating with Dr. Olopade (Cancer Risk and Prevention Program) in developing image-based methods for the computerized assessment of breast cancer risk. The project that involves mammography and breast MRI is one of four in a recently funded Breast Cancer SPORE (PI: O. Olopade).

  • Samuel Armato III, PhD and Hedy Kindler, MD, (Clinical and Experimental Therapeutics Program) are advancing the methods for objective means to assess mesothelioma due to the variability of mesothelioma tumor response. The mean concordance rate for tumor response between computerized measurements and measurements of human observers was found to be 84%, compared with a mean concordance rate of 88% between human observers. (Armato et al. AJR Am J Roentgenol 186:1000, 2006).

  • Heber MacMahon, MD, Armato, and Kunio Doi, PhD, are developing and evaluating automated methods for comparing multiple chest radiographs and thoracic CTs. They are evaluating a technique called temporal subtraction images to accurately integrate serial chest radiographs and help radiologists identify subtle, but critically significant changes.

  • Xiaochuan Pan, PhD and colleagues have made significant contributions to tomographic imaging theory. They have developed theoretically exact algorithms for obtaining accurate images in helical cone-beam CT, and based upon their imaging theory, they have been able to design innovative scanning strategies and algorithms for obtaining images with improved resolution properties.

  • Charles Pelizzari, PhD, Howard Halpern, MD, PhD, and colleagues have made substantial contributions in developing adaptive image-guided therapy based on a combination of Magnetic Resonance Imaging (MRI) and Electron Paramagnetic Resonance Imaging (EPRI) techniques which will allow non-invasive image based assessment of changes in hemodynamic parameters, oxygen levels, and vascular anatomy during therapy (Mailer. Magn Reson Med 55:904, 2006).

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Links

Program 1
Cell Signaling and Gene Regulation
Program Leaders: Marsha Rosner, PhD and Suzanne Conzen, MD

Program 2
Molecular Genetics and Hematopoiesis
Program Leaders: Wendy Stock, MD and Michael Thirman, MD

Program 3
Immunology and Cancer
Program Leader: Thomas F. Gajewski, MD, PhD

Program 4
Clinical and Experimental Therapeutics
Program Leaders: Everett E. Vokes, MD and M. Eileen Dolan, PhD

Program 5
Advanced Imaging
Program Leaders: Maryellen L. Giger, PhD and Heber MacMahon, MD

Program 6
Cancer Risk and Prevention
Program Leaders: Olufunmilayo (Funmi) I. Olopade, MBBS and Andrea King, PhD