Temporal change analysis for improved tumor detection in dedicated CT breast imaging using affine and free-form deformation

Joyoni Dey, University of Massachusetts Medical School
J. Michael O'Connor, University of Massachusetts Medical School
Yu Chen, University of Massachusetts Medical School
Stephen J. Glick, University of Massachusetts Medical School


Preliminary evidence has suggested that computerized tomographic (CT) imaging of the breast using a cone-beam, flat-panel detector system dedicated solely to breast imaging has potential for improving detection and diagnosis of early-stage breast cancer. Hypothetically, a powerful mechanism for assisting in early stage breast cancer detection from annual screening breast CT studies would be to examine temporal changes in the breast from year-to-year. We hypothesize that 3D image registration could be used to automatically register breast CT volumes scanned at different times (e.g., yearly screening exams). This would allow radiologists to quickly visualize small changes in the breast that have developed during the period since the last screening CT scan, and use this information to improve the diagnostic accuracy of early-stage breast cancer detection. To test our hypothesis, fresh mastectomy specimens were imaged with a flat-panel CT system at different time points, after moving the specimen to emulate the re-positioning motion of the breast between yearly screening exams. Synthetic tumors were then digitally inserted into the second CT scan at a clinically realistic location (to emulate tumor growth from year-to-year). An affine and a spline-based 3D image registration algorithm was implemented and applied to the CT reconstructions of the specimens acquired at different times. Subtraction of registered image volumes was then performed to better analyze temporal change. Results from this study suggests that temporal change analysis in 3D breast CT can potentially be a powerful tool in improving the visualization of small lesion growth.