Carl J. D'Orsi

Bio: Carl J. D'Orsi is an academic researcher from Emory University Hospital. The author has contributed to research in topics: Mammography & Mass screening. The author has an hindex of 23, co-authored 41 publications receiving 3787 citations.

Diagnostic Performance of Digital versus Film Mammography for Breast-Cancer Screening

Abstract: Previous trials, limited in many respects, have not found digital mammography to be significantly more accurate than the standard film method. A total of 42,760 asymptomatic women seen at 33 sites in the United States and Canada requested screening mammography and underwent both film and digital examinations. Two radiologists independently interpreted the film and digital mammograms. All participants either had breast biopsy within 15 months after evaluation or had a follow-up mammogram 10 months or longer after entry to the study. The results were assessed by receiver operating characteristic analysis. Both digital and film mammograms were positive in 0.5% of women. Another 2.2% had only a positive digital study, whereas 1.9% had only a positive film study. In the remaining women, approximately 95% of the total, both imaging studies were negative. Of 335 breast cancers diagnosed within 455 days after entry to the study, approximately three fourths were found within a year after evaluation. There were no substantial differences between the digital and film findings with respect to histology or stage of disease. The area under the curve was similar for the 2 studies and was not influenced by race or the risk of breast cancer. Digital mammography did, however, perform significantly better than the film method in women less than 50 years of age, in those having heterogeneously dense or very dense breasts, and premenopausal or perimenopausal women. The digital and film methods performed equally well in women age 50 years and older, those with fatty breasts or scattered fibroglandular densities, and those who were postmenopausal.

Potential contribution of computer-aided detection to the sensitivity of screening mammography.

Abstract: PURPOSE: To determine the false-negative rate in screening mammography, the capability of computer-aided detection (CAD) to identify these missed lesions, and whether or not CAD increases the radiologists' recall rate. MATERIALS AND METHODS: All available screening mammograms that led to the detection of biopsy-proved cancer (n = 1,083) and the most recent corresponding prior mammograms (n = 427) were collected from 13 facilities. Panels of radiologists evaluated the retrospectively visible prior mammograms by means of blinded review. All mammograms were analyzed by a CAD system that marks features associated with cancer. The recall rates of 14 radiologists were prospectively measured before and after installation of the CAD system. RESULTS: At retrospective review, 67% (286 of 427) of screening mammography–detected breast cancers were visible on the prior mammograms. At independent, blinded review by panels of radiologists, 27% (115 of 427) were interpreted as warranting recall on the basis of a statisti...

Diagnostic accuracy of digital versus film mammography: exploratory analysis of selected population subgroups in DMIST.

Abstract: Purpose: To retrospectively compare the accuracy of digital versus film mammography in population subgroups of the Digital Mammographic Imaging Screening Trial (DMIST) defined by combinations of age, menopausal status, and breast density, by using either biopsy results or follow-up information as the reference standard. Materials and Methods: DMIST included women who underwent both digital and film screening mammography. Institutional review board approval at all participating sites and informed consent from all participating women in compliance with HIPAA was obtained for DMIST and this retrospective analysis. Areas under the receiver operating characteristic curve (AUCs) for each modality were compared within each subgroup evaluated (age < 50 vs 50–64 vs ≥ 65 years, dense vs nondense breasts at mammography, and pre- or perimenopausal vs postmenopausal status for the two younger age cohorts [10 new subgroups in toto]) while controlling for multiple comparisons (P < .002 indicated a significant difference...

ACR Appropriateness Criteria Breast Cancer Screening

Abstract: Mammography is the recommended method for breast cancer screening of women in the general population. However, mammography alone does not perform as well as mammography plus supplemental screening in high-risk women. Therefore, supplemental screening with MRI or ultrasound is recommended in selected high-risk populations. Screening breast MRI is recommended in women at high risk for breast cancer on the basis of family history or genetic predisposition. Ultrasound is an option for those high-risk women who cannot undergo MRI. Recent literature also supports the use of breast MRI in some women of intermediate risk, and ultrasound may be an option for intermediate-risk women with dense breasts. There is insufficient evidence to support the use of other imaging modalities, such as thermography, breast-specific gamma imaging, positron emission mammography, and optical imaging, for breast cancer screening. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every 2 years by a multidisciplinary expert panel. The guideline development and review includes an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances in which evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.

The ACR BI-RADS® Experience: Learning From History

Abstract: The Breast Imaging Reporting and Data System ® (BI-RADS ® ) initiative, instituted by the ACR, was begun in the late 1980s to address a lack of standardization and uniformity in mammography practice reporting. An important component of the BI-RADS initiative is the lexicon, a dictionary of descriptors of specific imaging features. The BI-RADS lexicon has always been data driven, using descriptors that previously had been shown in the literature to be predictive of benign and malignant disease. Once established, the BI-RADS lexicon provided new opportunities for quality assurance, communication, research, and improved patient care. The history of this lexicon illustrates a series of challenges and instructive successes that provide a valuable guide for other groups that aspire to develop similar lexicons in the future.

Measuring the accuracy of diagnostic systems

Abstract: Diagnostic systems of several kinds are used to distinguish between two classes of events, essentially "signals" and "noise". For them, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy. It is the only measure available that is uninfluenced by decision biases and prior probabilities, and it places the performances of diverse systems on a common, easily interpreted scale. Representative values of this measure are reported here for systems in medical imaging, materials testing, weather forecasting, information retrieval, polygraph lie detection, and aptitude testing. Though the measure itself is sound, the values obtained from tests of diagnostic systems often require qualification because the test data on which they are based are of unsure quality. A common set of problems in testing is faced in all fields. How well these problems are handled, or can be handled in a given field, determines the degree of confidence that can be placed in a measured value of accuracy. Some fields fare much better than others.

Radiomics: Images Are More than Pictures, They Are Data.

Abstract: In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.

Rapid measurement of B-type natriuretic peptide in the emergency diagnosis of heart failure.

Abstract: Background B-type natriuretic peptide is released from the cardiac ventricles in response to increased wall tension. Methods We conducted a prospective study of 1586 patients who came to the emergency department with acute dyspnea and whose B-type natriuretic peptide was measured with a bedside assay. The clinical diagnosis of congestive heart failure was adjudicated by two independent cardiologists, who were blinded to the results of the B-type natriuretic peptide assay. Results The final diagnosis was dyspnea due to congestive heart failure in 744 patients (47 percent), dyspnea due to noncardiac causes in 72 patients with a history of left ventricular dysfunction (5 percent), and no finding of congestive heart failure in 770 patients (49 percent). B-type natriuretic peptide levels by themselves were more accurate than any historical or physical findings or laboratory values in identifying congestive heart failure as the cause of dyspnea. The diagnostic accuracy of B-type natriuretic peptide at a cutoff ...

Mammographic Density and the Risk and Detection of Breast Cancer

Abstract: Methods We carried out three nested case–control studies in screened populations with 1112 matched case–control pairs. We examined the association of the measured percentage of density in the baseline mammogram with risk of breast cancer, according to method of cancer detection, time since the initiation of screening, and age. Results As compared with women with density in less than 10% of the mammogram, women with density in 75% or more had an increased risk of breast cancer (odds ratio, 4.7; 95% confidence interval [CI], 3.0 to 7.4), whether detected by screening (odds ratio, 3.5; 95% CI, 2.0 to 6.2) or less than 12 months after a negative screening examination (odds ratio, 17.8; 95% CI, 4.8 to 65.9). Increased risk of breast cancer, whether detected by screening or other means, persisted for at least 8 years after study entry and was greater in younger than in older women. For women younger than the median age of 56 years, 26% of all breast cancers and 50% of cancers detected less than 12 months after a negative screening test were attributable to density in 50% or more of the mammogram. Conclusions Extensive mammographic density is strongly associated with the risk of breast cancer detected by screening or between screening tests. A substantial fraction of breast cancers can be attributed to this risk factor.