Part 1 book “Digital mammography“ has contents: Clinical digital mammography - overview and introduction, physics of digital mammography, detectors for digital mammography, digital mammography clinical trials, image processing, quality control for digital mammography,… and other contents.
DIGITAL MAMMOGRAPHY DIGITAL MAMMOGRAPHY ETTA D PISANO, MD, FACR Professor of Radiology and Biomedical Engineering Department of Radiology University of North Carolina School of Medicine UNC-Lineberger Comprehensive Cancer Center Chapel Hill, North Carolina MARTIN J YAFFE, PhD Senior Scientist Imaging and Bioengineering Research Sunnybrook & Women’s College Health Sciences Centre Professor of Medical Imaging and Medical Biophysics University of Toronto Toronto, Ontario, Canada CHERIE M KUZMIAK, DO Assistant Professor of Radiology Department of Radiology University of North Carolina School of Medicine UNC-Lineberger Comprehensive Cancer Center Chapel Hill, North Carolina Acquisitions Editor: Lisa McAllister Developmental Editor: Scott Scheidt Supervising Editor: Mary Ann McLaughlin Production Editor: Kathy Cleghorn, Chernow Editorial Services, Inc Manufacturing Manager: Ben Rivera Cover Designer: Armen Kojoyian Compositor: Lippincott Williams & Wilkins Desktop Division Printer: Maple Press © 2004 by LIPPINCOTT WILLIAMS & WILKINS 530 Walnut Street Philadelphia, PA 19106 USA LWW.com All rights reserved This book is protected by copyright No part of this book may be reproduced in any form or by any means, including photocopying, or utilized by any information storage and retrieval system without written permission from the copyright owner, except for brief quotations embodied in critical articles and reviews Materials appearing in this book prepared by individuals as part of their official duties as U.S government employees are not covered by the above-mentioned copyright Printed in the USA Library of Congress Cataloging-in-Publication Data Digital mammography / editors, Etta D Pisano, Martin J Yaffe, Cherie M Kuzmiak p cm Includes bibliographical references and index ISBN 0-7817-4142-4 Breast—Radiography Breast—Imaging Breast—Cancer—Diagnosis I Pisano, Etta D II Yaffe, Martin J (Martin Joel), 1949– III Kuzmiak, Cherie M RG493.5.R33D537 2003 618.1′907572—dc21 2003051682 Care has been taken to confirm the accuracy of the information presented and to describe generally accepted practices However, the authors, editors, and publisher are not responsible for errors or omissions or for any consequences from application of the information in this book and make no warranty, expressed or implied, with respect to the currency, completeness, or accuracy of the contents of the publication Application of this information in a particular situation remains the professional responsibility of the practitioner The authors, editors, and publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accordance with current recommendations and practice at the time of publication However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any change in indications and dosage and for added warnings and precautions This is particularly important when the recommended agent is a new or infrequently employed drug Some drugs and medical devices presented in this publication have Food and Drug Administration (FDA) clearance for limited use in restricted research settings It is the responsibility of the health care provider to ascertain the FDA status of each drug or device planned for use in their clinical practice 10 To our families, our professional mentors, and our colleagues TABLE OF CONTENTS Contributing Authors ix Foreword xi Preface xiii Acknowledgments xv Clinical Digital Mammography: Overview and Introduction Physics of Digital Mammography Detectors for Digital Mammography 15 Digital Mammography Clinical Trials 27 Image Processing 49 Image Display: Softcopy and Printed Film Basics of Digital Mammography Display 58 PACS Issues 62 10 Advanced Applications of Digital Mammography 67 11 Digital Mammography Cases with Masses 77 12 Digital Mammography Cases with Calcifications 158 Quality Control for Digital Mammography 33 13 Miscellaneous Digital Mammography 209 Computer-Aided Detection in Digital Mammography 43 Subject Index 225 CONTRIBUTING AUTHORS Fred M Behlen, PhD, President, LAI Technology, Homewood, Illinois Robert M Nishikawa, PhD, Professor of Radiology, Department of Radiology, University of Chicago, Chicago, Illinois Cherie M Kuzmiak, DO, Assistant Professor of Radiology, Department of Radiology, University of North Carolina School of Medicine, UNC-Lineberger Comprehensive Cancer Center, Chapel Hill, North Carolina Etta D Pisano, MD, FACR, Professor of Radiology and Biomedical Engineering, Department of Radiology, University of North Carolina School of Medicine, UNC-Lineberger Comprehensive Cancer Center, Chapel Hill, North Carolina James G Mainprize, PhD, Research Associate, Imaging Research Program, Sunnybrook & Women’s College Health Sciences Centre, Toronto, Ontario, Canada Martin J Yaffe, PhD, Senior Scientist, Imaging and Bioengineering Research, Sunnybrook & Women’s College Health Sciences Centre, and Professor of Medical Imaging and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada Computer-Aided Detection in Digital Mammography decreased from 140 to 35 µ (25) However, for classifying microcalcifications as benign or malignant, the scheme’s performance did not improve as the pixel size decreased from 100 µ down to 35 µ (26) Most radiologists and medical physicists argue that higher spatial resolution is needed in screening mammography because the presence of a calcification can be seen at somewhat “coarse” resolution, but fine detail and, therefore high spatial resolution, are needed to distinguish benign from malignant calcifications for diagnostic mammography This author interprets this paradox as follows For a computer to distinguish an actual calcification from a computer detected false-positive, high spatial resolution is needed because, for the computer, fine detail is necessary to distinguish an actual calcification from, for example, a film artifact on a digitized image To distinguish benign from malignant calcifications, the relevant shape factor is whether the calcifications are linear or branching and this can be done at 100-µ pixel resolution The exact shape of calcifications is not diagnostic, because the SNR of the image is insufficient to determine accurately the precise shape or border of small calcifications Evidence to support this assertion comes from an observer study conducted by Jiang et al (11) They had 10 radiologists rating the likelihood that calcifications were malignant and whether they would recommend that the patient have a biopsy The radiologists read the original mammograms: the four standard views and two spot-magnification views A computer analyzed only the standard view mammograms digitized at 100-µ pixel resolution As can be seen in Table 6–1, the computer outperformed the radiologists in terms of area under the ROC curve, sensitivity, and specificity Furthermore Chan et al also conducted an observer study asking radiologists to read clusters extracted from digitized mammograms (27) They found no significant difference in radiologists’ performance in classifying the clusters Thus, this author concludes that 100-µ pixel size is sufficient for digital mammography, if the system has high detective quantum efficiency (DQE) at intermediate spatial frequencies (approximately 1–3 cycles/mm) In many digital systems, this can only be obtained by having a small pixel size, but newer so-called direct digital detectors can achieve this goal with 100-µ pixel size, at least in theory (28) Impact of CAD/FFDM on Radiologists’ Performance Evidence is accumulating that CAD can improve radiologists’ performance, at least in simulated clinical situations These are for the cases where radiologists are reading screenfilm mammograms and computer algorithms are operating on digitized film mammograms While the same is probably true for radiologists reading FFDM images and the computer operating on FFDM images, it remains to be proven It is possible that both the computer and the radiologist perform better using FFDM images, but the improvement by the radiologist is such that the added value of CAD is small If the image quality of FFDM were so great that radiologists could clearly see all cancers, even those in dense tissue, then CAD would have limited value since radiologists would not miss many cancers However, initial studies indicate that this is not true for the present generation of digital systems (29) The observer study of CAD applied to FFDM was by Nawano et al (22) They used ROC analysis on data collected from five radiologists reading using 344 mammograms from 86 women They found that the average area under the ROC curve increased by a statistically significant amount (p