PURPOSE: To study the use of a computer vision method as a second read
er for the detection of spiculated lesions on screening mammograms. MA
TERIALS AND METHODS: An algorithmic computer process for the detection
of spiculated lesions on digitized screen-film mammograms was applied
to 85 four-view clinical cases: 36 cases with cancer proved by means
of biopsy and 49 cases with negative findings at examination and follo
w-up. The computer detections were printed as film with added outlines
that indicated the suspected cancers. Four radiologists screened the
85 cases twice, once without and once with the computer reports as anc
illary films. RESULTS: The algorithm alone achieved 100% sensitivity,
with a specificity of 82%. The computer reports increased the average
radiologist sensitivity by 9.7% (P = .005), moving from 80.6% to 90.3%
, with no decrease in average specificity. CONCLUSION: The study demon
strated that computer analysis of mammograms can provide a substantial
and statistically significant increase in radiologist screening effic
acy.