Paper
4 May 2004 How do radiographic techniques affect mass lesion detection performance in digital mammography?
Walter Huda, Kent M. Ogden, Ernest M. Scalzetti, Eric F. Dudley, David R. Dance
Author Affiliations +
Abstract
We investigated how the x-ray tube kV and mAs affected the detection of simulated lesions with diameters between 0.24 and 12 mm. Digital mammograms were acquired with and without mass lesions, permitting a difference image to be generated corresponding to the lesion alone. Isolated digital lesions were added at a reduced intensity to non-lesion images, and used in Four-Alternate Forced Choice (4-AFC) experiments to determine the lesion intensity that corresponded to an accuracy of 92% (I92%). Values of I92% were determined at x-ray tube output values ranging from 40 to 120 mAs, and x-ray tube voltages ranging from 24 to 32 kV. For mass lesions larger than ~0.8 mm, there was no significant change in detection peformance with changing mAs. Doubling of the x-ray tube output from 60 to 120 mAs resulted in an average change in I92% of only +3.8%, whereas the Rose model of lesion detection predicts a reduction in the experimental value of I92% of -29%. For the 0.24 mm lesion, however, reducing the x-ray beam mAs from 100 to 40 mAs reduced the average detection performance by ~60%. Contrast-detail curves for lesions with diameter ≥ 0.8 mm had a slope of ~+0.23, whereas the Rose model predicts a slope of -0.5. For lesions smaller than ~0.8 mm, contrast-detail slopes were all negative with the average gradient increasing with decreasing mAs value. Increasing the x-ray tube voltage from 24 to 32 kV at a constant display contrast resulted in a modest improvement in low contrast lesion detection performance of ~10%. Increasing the display window width from 2000 to 2500 reduced the average observer performance by ~6%. Our principal finding is that radiographic technique factors have little effect on detection performance for lesions larger than ~0.8 mm, but that the visibility of smaller lesions is affected by quantum mottle in qualitative agreement with the predictions of the Rose model.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Walter Huda, Kent M. Ogden, Ernest M. Scalzetti, Eric F. Dudley, and David R. Dance "How do radiographic techniques affect mass lesion detection performance in digital mammography?", Proc. SPIE 5372, Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment, (4 May 2004); https://doi.org/10.1117/12.535672
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Cited by 14 scholarly publications.
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KEYWORDS
X-rays

Digital mammography

Image quality

Digital imaging

Mammography

Breast

Solids

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