Digital mammography: observer performance study of the effects of pixel size on radiologists' characterization of malignant and benign microcalcifications

Heang-Ping Chan; Mark A. Helvie M.D.; Nicholas Petrick; Berkman Sahiner; Dorit D. Adler; Caroline E. Blane; Lynn K. Joynt; Chintana Paramagul; Marilyn A. Roubidoux; Todd E. Wilson; Lubomir M. Hadjiiski; Mitchell M. Goodsitt

doi:10.1117/12.349514

28 May 1999 Digital mammography: observer performance study of the effects of pixel size on radiologists' characterization of malignant and benign microcalcifications

Heang-Ping Chan, Mark A. Helvie M.D., Nicholas Petrick, Berkman Sahiner, Dorit D. Adler, Caroline E. Blane, Lynn K. Joynt, Chintana Paramagul, Marilyn A. Roubidoux, Todd E. Wilson, Lubomir M. Hadjiiski, Mitchell M. Goodsitt

Author Affiliations +

Proceedings Volume 3659, Medical Imaging 1999: Physics of Medical Imaging; (1999) https://doi.org/10.1117/12.349514
Event: Medical Imaging '99, 1999, San Diego, CA, United States

Abstract

A receiver operating characteristic (ROC) experiment was conducted to evaluate the effects of pixel size on the characterization of mammographic microcalcifications. Digital mammograms were obtained by digitizing screen-film mammograms with a laser film scanner. One hundred twelve two-view mammograms with biopsy-proven microcalcifications were digitized at a pixel size of 35 micrometer X 35 micrometer. A region of interest (ROI) containing the microcalcifications was extracted from each image. ROI images with pixel sizes of 70 micrometers, 105 micrometers, and 140 micrometers were derived from the ROI of 35 micrometer pixel size by averaging 2 X 2, 3 X 3, and 4 X 4 neighboring pixels, respectively. The ROI images were printed on film with a laser imager. Seven MQSA-approved radiologists participated as observers. The likelihood of malignancy of the microcalcifications was rated on a 10-point confidence rating scale and analyzed with ROC methodology. The classification accuracy was quantified by the area, A_z, under the ROC curve. The statistical significance of the differences in the A_z values for different pixel sizes was estimated with the Dorfman-Berbaum-Metz (DBM) method for multi-reader, multi-case ROC data. It was found that five of the seven radiologists demonstrated a higher classification accuracy with the 70 micrometer or 105 micrometer images. The average A_z also showed a higher classification accuracy in the range of 70 to 105 micrometer pixel size. However, the differences in A(subscript z/ between different pixel sizes did not achieve statistical significance. The low specificity of image features of microcalcifications an the large interobserver and intraobserver variabilities may have contributed to the relatively weak dependence of classification accuracy on pixel size.

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Heang-Ping Chan, Mark A. Helvie M.D., Nicholas Petrick, Berkman Sahiner, Dorit D. Adler, Caroline E. Blane, Lynn K. Joynt, Chintana Paramagul, Marilyn A. Roubidoux, Todd E. Wilson, Lubomir M. Hadjiiski, and Mitchell M. Goodsitt "Digital mammography: observer performance study of the effects of pixel size on radiologists' characterization of malignant and benign microcalcifications", Proc. SPIE 3659, Medical Imaging 1999: Physics of Medical Imaging, (28 May 1999); https://doi.org/10.1117/12.349514

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