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(Radiology. 2000;215:703-707.)
© RSNA, 2000


Computer Applications

Breast Cancer: Importance of Spiculation in Computer-aided Detection1

Carl J. Vyborny, MD, PhD, Takeshi Doi, MS, Kathryn F. O'Shaughnessy, PhD, Harlan M. Romsdahl, BS, Alexander C. Schneider, BS and Alan A. Stein, PhD

1 From the Department of Radiology, LaGrange Memorial Hospital, 5100 S Willow Springs Rd, LaGrange, IL 60525 (C.J.V.); University of Chicago Hospitals, Ill (C.J.V.); and R2 Technology, Los Altos, Calif (T.D., K.F.O., H.M.R., A.C.S., A.A.S.). From the 1999 RSNA scientific assembly. Received September 9; revision requested October 14; revision received November 11; accepted November 15. Address correspondence to C.J.V.

PURPOSE: To determine the prevalence of spiculation in a large series of screening-detected breast cancers appearing as masses on mammograms and to assess the sensitivity of a computer-aided detection (CAD) algorithm that uses spiculation measures in the detection of such lesions.

MATERIALS AND METHODS: Six hundred seventy-seven consecutive cases of breast cancers detected as masses on mammograms were independently reviewed by three radiologists who determined if the lesions were spiculated. All cancers were then analyzed by the CAD system.

RESULTS: All three radiologists interpreted 375 (55%) of the 677 masses as being spiculated on at least one view. The CAD algorithm correctly marked 322 (86%) of the 375 clearly spiculated masses, with a mean of 0.24 additional mass mark per image. With a looser definition of spiculation, 585 (86%) of the 677 masses were called spiculated by at least one radiologist on one view. The algorithm correctly marked 464 (79%) of the 585 lesions that were spiculated or possibly spiculated.

CONCLUSION: Spiculation was clearly present in a majority (55%) of consecutive screening-detected breast cancer masses found on mammograms in a large clinical trial. Incorporation of spiculation measures is, therefore, an important strategy in the detection of breast cancer with CAD. A present-generation CAD algorithm correctly identified a large proportion (86%) of spiculated breast cancers.

Index terms: Breast neoplasms, 00.32 • Breast neoplasms, diagnosis, 00.32 • Cancer screening, 00.11, 00.32 • Computers, diagnostic aid




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