We performed a preliminary investigation to determine how similar radiologists’ interpretations of screening mammograms are. Our dataset consisted of 50 cancer cases and 50 normal cases that were read by 50 radiologists. We computed sensitivity, specificity, and interpretation on a case-by-case basis to study similarity between pairs of radiologists. We failed to find any pairs of radiologists who read all the cases, only the normal cases, or only the cancer cases the same. There were very few radiologists who read both cancer cases and normal cases in a similar manner. Even radiologists who had similar sensitivities or similar specificities differed substantially on the interpretation of individual cases. Our data indicate that there may be an underlying variability between radiologists in terms of image features used to detect cancers and when a false detection is made. This underlying variability may make the development and implementation of model observers more difficult.

PURPOSETo develop algorithms for creating realistic three-dimensional (3D) simulated breast masses and embedding them within actual clinical mammograms. The proposed techniques yield high-resolution simulated breast masses having randomized shapes, with user-defined mass type, size, location, and shape characteristics.METHODSThe authors describe a method of producing 3D digital simulations of breast masses and a technique for embedding these simulated masses within actual digitized mammograms. Simulated 3D breast masses were generated by using a modified stochastic Gaussian random sphere model to generate a central tumor mass, and an iterative fractal branching algorithm to add complex spicule structures. The simulated masses were embedded within actual digitized mammograms. The authors evaluated the realism of the resulting hybrid phantoms by generating corresponding left- and right-breast image pairs, consisting of one breast image containing a real mass, and the opposite breast image of the same patient containing a similar simulated mass. The authors then used computer-aided diagnosis (CAD) methods and expert radiologist readers to determine whether significant differences can be observed between the real and hybrid images.RESULTSThe authors found no statistically significant difference between the CAD features obtained from the real and simulated images of masses with either spiculated or nonspiculated margins. Likewise, the authors found that expert human readers performed very poorly in discriminating their hybrid images from real mammograms.CONCLUSIONSThe authors' proposed method permits the realistic simulation of 3D breast masses having user-defined characteristics, enabling the creation of a large set of hybrid breast images containing a well-characterized mass, embedded within real breast background. The computational nature of the model makes it suitable for detectability studies, evaluation of computer aided diagnosis algorithms, and teaching purposes.

Computer-aided diagnosis has potential in improving radiologists' diagnosis, and presentation of similar images as a reference may provide additional useful information for distinction between benign and malignant lesions. In this study, we evaluated the usefulness of presentation of reference images in observer performance studies and compared the results obtained by groups of observers practicing in the United States and Japan. The results showed that the presentation of the reference images was generally effective for both groups, as the areas under the receiver operating characteristic curves improved from 0.915 to 0.924 for the group in the US and from 0.913 to 0.925 for the group in Japan, although the differences were marginally (p = 0.047) and not (p = 0.13) statistically significant, respectively. There was a slight difference between the two groups in the way that the observers reacted to some benign cases, which might be due to differences in the population of screenees and in the socioclinical environment. In the future, it may be worthwhile to investigate the development of a customized system for physicians in different socio-clinical environments.

OBJECTIVEThe objective of our study was to report the positive predictive value (PPV) of ultrasound of the axilla to predict pN2 or higher disease in breast cancer patients.MATERIALS AND METHODSA retrospective study of 559 patients with newly diagnosed invasive breast cancer from 2005 through 2009 was performed. All patients underwent ipsilateral axillary ultrasound for staging purposes. Ultrasound findings were considered suspicious for metastasis if cortical thickening or nonhilar blood flow to the cortex was present. Suspicious lymph nodes were classified on the basis of their features as high, intermediate, or low suspicion. The standard of truth was confirmed pathologically.RESULTSEither pN2 or pN3 disease was found in 50 of 181 (28%) patients with positive findings on an ultrasound study and 10 of 378 (3%) patients with a negative ultrasound study (p < 0.01). When two or more lymph nodes of high suspicion or a total of three or more lymph nodes of any combination of high suspicion and intermediate suspicion were detected, patients were likely to have pN2 or pN3 disease (PPV, 82%). Either pN2 or pN3 disease was found in two of 122 (2%) patients whose primary cancers were up to 10 mm and 58 of 437 (13%) patients whose primary cancers were larger than 10 mm (p < 0.001). Ultrasound of the patient with tumors larger than 10 mm showing at least two highly suspicious nodes had a PPV of 87% for predicting pN2 or higher disease.CONCLUSIONUltrasound was useful for predicting pN2 or higher axillary disease in breast cancer patients. Preoperative ultrasound assessment for staging of axillary lymph nodes might help avoid underestimation at sentinel lymph node biopsy.

OBJECTIVE:The purpose of this study was to determine the effectiveness with which radiologists can use computer-aided detection (CADe) to detect cancer missed at screening.MATERIALS AND METHODS:An observer study was performed to measure the ability of radiologists to detect breast cancer on mammograms with and without CADe. The images in the study were from 300 analog mammographic examinations. In 234 cases the mammograms were read clinically as normal and free of cancer for at least 2 subsequent years. In the other 66 cases, cancers were missed clinically. In 256 cases, current and previous mammograms were available. Eight radiologists read the dataset and recorded a BI-RADS assessment, the location of the lesion, and their level of confidence that the patient should be recalled for diagnostic workup for each suspicious lesion. Jackknife alternative free-response receiver operating characteristic analysis was used.RESULTS:The jackknife alternative free-response receiver operating characteristic figure of merit was 0.641 without aid and 0.659 with aid (p = 0.06; 95% CI, -0.001 to 0.036). The sensitivity increased 9.9% (95% CI, 3.4-19%) and the callback rate 12.1% (95% CI, 7.3-20%) with CADe. Both increases were statistically significant (p < 0.001). Radiologists on average ignored 71% of correct computer prompts.CONCLUSION:Use of CADe can increase radiologist sensitivity 10% with a comparable increase in recall rate. There is potential for CADe to have a bigger clinical impact because radiologists failed to recognize a correct computer prompt in 71% of missed cancer cases [corrected].

OBJECTIVE:The objective of our study was to determine the sensitivity of cancer detection at breast MRI using current imaging techniques and to evaluate the characteristics of lesions with false-negative examinations.MATERIALS AND METHODS:Two hundred seventeen patients with 222 newly diagnosed breast cancers or highly suspicious breast lesions that were subsequently shown to be malignant underwent breast MRI examinations for staging. Two breast imaging radiologists performed a consensus review of the breast MRI examinations. The absence of perceptible contrast enhancement at the expected site was considered to be a false-negative MRI. Histology of all lesions was reviewed by an experienced breast pathologist.RESULTS:Enhancement was observed in 213 (95.9%) of the 222 cancer lesions. Of the nine lesions without visible enhancement, two lesions were excluded because the entire tumor had been excised at percutaneous biopsy performed before the MRI examination and no residual tumor was noted on the final histology. The overall sensitivity of MRI for the known cancers was 96.8% (213/220); for invasive cancer, 98.3% (176/179); and for ductal carcinoma in situ, 90.2% (37/41).CONCLUSION:In a population of 220 sequentially diagnosed breast cancer lesions, we found seven (3.2%) MRI-occult cancers, fewer than seen in other published studies. Small tumor size and diffuse parenchymal enhancement were the principal reasons for these false-negative results. Although the overall sensitivity of cancer detection was high (96.8%), it should be emphasized that a negative MRI should not influence the management of a lesion that appears to be of concern on physical examination or on other imaging techniques.

The effect of the presentation of similar images for distinction between benign and malignant masses on mammograms was evaluated in the observer performance study. Images of masses were obtained from the Digital Database for Screening Mammography. We selected 50 benign and 50 malignant masses by a stratified randomization method. For each case, similar images were selected based on the size of masses and the similarity measures. Radiologists were shown images with unknown masses and asked to provide their confidence level that the lesions were malignant before and after the presentation of the similar images. Eleven observers, including three attending breast radiologists, three breast imaging fellows, and five residents, participated. The average areas under the receiver operating characteristic curves without and with the presentation of the similar images were almost equivalent. However, there were many cases in which the similar images caused beneficial effects to the observers, whereas there were a small number of cases in which the similar images had detrimental effects. From a detailed analysis of the reasons for these detrimental effects, we found that the similar images would not be useful for diagnosis of rare and very difficult cases, i.e., benign-looking malignant and malignant-looking benign cases. In addition, these cases should not be included in the reference database, because radiologists would be confused by these unusual cases. The results of this study could be very important and useful for the future development and improvement of a computer-aided diagnosis system.

PURPOSE:The goal of this study is to develop a computerized method that identifies a specific axillary lymph node (ALN) seen on ultrasound (US) with its most likely corresponding node on breast MRI (BMRI). This goal is an important step in developing a preoperative non-invasive method for staging breast cancer on the basis of multi-modality imaging.METHODS:Twenty patients with newly diagnosed breast cancer were scanned on US and MRI. Two expert breast imaging radiologists independently correlated ALNs seen on US with BMRI, and this correlation was used as the gold standard. To correlate ALNs on US and BMRI, the cortex and hilum of each ALN was segmented using an ellipse fitting algorithm, then the ALN long and short axes and maximum cortical thickness (MCT) were computed. Three ALNs were chosen as candidates from the BMRI datasets for each lymph node seen on US. Finally, the Euclidean distances across all measurements between the US ALN and each of the three BMRI candidates were computed, and the smallest distance was reported as the correlation result.RESULTS:Using the expert radiologists identified correlated BMRI slice as the ground truth, the shortest Euclidean distance successfully identified the same lymph node as the radiologists in 13 out of 16 ALNs (81.25%). In negative ALNs, the standard deviation for long and short axes was relatively large but that of maximum cortical thickness was small. Average maximum cortical thickness and its standard deviation measured in US were very close to those measured in MRI. There were no significant differences among the long axis, short axis, and MCT measurements between US and MRI-T2 weighted sequence (P > 0.05 paired t-test).CONCLUSION:We performed a feasibility study which showed that computerized measurements of ALNs might be used to identify the same ALN on different modalities such as US and BMRI. This type of correlation would be valuable as it would allow the use of combined imaging parameters to be applied to the evaluation of ALNs in patients with breast cancer. It is hoped that the combined multi-modality information would provide a more robust non-invasive method of staging the axilla than is currently available.

We evaluated the potential utility of a newly developed liquid-crystal display (LCD), which used an independent sub-pixel drive (ISD) technique for increasing the spatial resolution of a standard LCD three times in one direction, by use of receiver operating characteristic (ROC) analysis and a two-alternative-forced-choice (2AFC) method to determine improvement in radiologists' accuracy in the detection of clustered microcalcifications (MCLs) on digital mammograms. We used a standard LCD without and with the ISD technique, which can increase the spatial resolution of the LCD three times in one direction from three mega- to nine megapixels without changes in the size of the display. We used 60 single views of digital mammograms (30 with and 30 without clustered MCLs) for ROC studies and 60 regions of interest (ROIs) with clustered MCLs for 2AFC studies. In the ROC study, seven radiologists attempted to detect clustered MCLs without and with the ISD on the same LCD. In the 2AFC study, the same observer group compared the visibility of MCLs by use of the LCD without and with the ISD. Our institutional review board approved the use of this database and the participation of radiologists in this study. The accuracy in detecting clustered MCLs in the ROC study was improved by use of the LCD with the ISD, but the improvement was not statistically significant (p = 0.08). However, the superiority of the LCD with the ISD was demonstrated as significant (p < 0.001) in the 2AFC study. An LCD with ISD can improve the visibility of clustered MCLs when high-resolution digital mammograms are available.

OBJECTIVE The objective of our study was to assess the clinical utility of MR-directed ("second-look") ultrasound examination to search for breast lesions detected initially on MRI. MATERIALS AND METHODS A retrospective review was performed of the records of 158 consecutive patients (202 lesions) with breast abnormalities initially detected on MRI between July 2003 and May 2006. All lesions were detected as enhancing findings on a dynamic contrast MR study and were subsequently evaluated with ultrasound. Ultrasound was performed using MR images as a guide to lesion location, size, and morphology. Pathology findings were confirmed by subsequent percutaneous biopsy or lesion excision. Imaging follow-up was used for probably benign lesions, which were not biopsied. RESULTS Of the 202 MRI-detected lesions, ultrasound correlation was made in 115 (57%) including 33 malignant lesions and 82 benign lesions. The remaining 87 lesions were not sonographically correlated and included 11 malignant lesions and 76 nonmalignant lesions. Mass lesions identified on MRI were more likely to have a sonographic correlate than nonmasslike lesions (65% vs 12%, respectively); malignant mass lesions were more likely to show an ultrasound correlation (85%). The malignant lesions with successful sonographic correlation tended to present with subtle sonographic findings. CONCLUSION MR-directed ultrasound of MRI-detected lesions was useful for decision making as part of the diagnostic workup. Malignant lesions were likely to have an ultrasound correlate, especially when they presented as masses on MRI. However, the sonographic findings of these lesions were often subtle, and careful scanning technique was needed for successful MRI-ultrasound correlation.

RATIONALE AND OBJECTIVES:To determine similarity measures for selection of pathology-known similar images that would be useful for radiologists as a reference guide in the diagnosis of new breast lesions on mammograms.MATERIALS AND METHODS:The images were obtained from the Digital Database for Screening Mammography developed by the University of South Florida. For determination and evaluation of similarity measures, the "gold standard" of similarities for 300 pairs of masses was determined by 10 breast radiologists. For determining similarity measures that would agree with radiologists' similarity determination, an artificial neural network (ANN) was trained with the radiologists' subjective similarity ratings and the image features. The image features were determined subjectively using the Breast Imaging Reporting and Data System (BI-RADS) lesion descriptors and objectively by computerized image analysis. The similarity measures determined by the ANN were compared to the gold standard and evaluated in terms of the correlation coefficient.RESULTS:The similarity measures determined using the BI-RADS descriptors only were not as useful as those determined by use of the image features only. When the BI-RADS margin ratings were combined with the image features, the correlation coefficient between the subjective ratings and the objective measures improved slightly (r = 0.76) compared to those based on the image features alone (r = 0.74).CONCLUSIONS:The inclusion of the BI-RADS margin descriptors may be useful for determination of similarity measures, especially when it is difficult to obtain the manual outlines of the masses and if the BI-RADS descriptors were provided consistently by radiologists.

In this Letter the authors introduce a wide-field transmission ultrasound approach to breast imaging based on the use of a large area acousto-optic (AO) sensor. Accompanied by a suitable acoustic source, such a detector could be mounted on a traditional mammography system and provide a mammographylike ultrasound projection image of the compressed breast in registration with the x-ray mammogram. The authors call the approach acoustography. The hope is that this additional information could improve the sensitivity and specificity of screening mammography. The AO sensor converts ultrasound directly into a visual image by virtue of the acousto-optic effect of the liquid crystal layer contained in the AO sensor. The image is captured with a digital video camera for processing, analysis, and storage. In this Letter, the authors perform a geometrical resolution analysis and also present images of a multimodality breast phantom imaged with both mammography and acoustography to demonstrate the feasibility of the approach. The geometric resolution analysis suggests that the technique could readily detect tumors of diameter of 3 mm using 8.5 MHz ultrasound, with smaller tumors detectable with higher frequency ultrasound, though depth penetration might then become a limiting factor. The preliminary phantom images show high contrast and compare favorably to digital mammograms of the same phantom. The authors have introduced and established, through phantom imaging, the feasibility of a full-field transmission ultrasound detector for breast imaging based on the use of a large area AO sensor. Of course variations in attenuation of connective, glandular, and fatty tissues will lead to images with more cluttered anatomical background than those of the phantom imaged here. Acoustic coupling to the mammographically compressed breast, particularly at the margins, will also have to be addressed.

We have been developing a computerized scheme for selecting visually similar images that would be useful to radiologists in the diagnosis of masses on mammograms. Based on the results of the observer performance study, the presentation of similar images was useful, especially for less experienced observers. The test cases included 50 benign and 50 malignant masses. Ten observers, including five breast radiologists and five residents, were asked to provide the confidence level of the lesions being malignant before and after the presentation of similar images. By use of multireader, multi-case receiver operating characteristic analysis, the average areas under the curves for the five residents were 0.880 and 0.896 without and with similar images, respectively (p=0.040). There were four malignant cases in which the initial ratings were relatively low, but the similar images alerted the residents to increase their confidence levels of malignancy close to those by the breast radiologists. The presentation of similar images may cause some observers falsely to increase their suspicion for some benign cases; however, if similar images can alert radiologists to recognize the signs of malignancy and also help them to decrease their suspicion correctly for some benign cases, they can be useful in the diagnosis on mammograms.

Introduction: MR breast imaging is an emerging technology for detecting and characterizing of breast tumors. During breast MRI examination, all the findings are reported in a standardized way using BI-RADS descriptions. Such a report not only contains the lesions types, but also their positioning relative to the anatomy (breast laterality, o’clock position relative to the nipple, distance from the skin, etc). The reporting automation requires fast automatic detection and segmentation of the breast anatomy, which is particularly difficult given the large variation in anatomical details and MR imaging protocols. In this context of a Breast MR CAD application, we developed a hierarchical approach for automatically detecting breasts regions, segmenting the patient skin, localizing the nipples, and the band of cardiac artifacts when present. This work was focused on automating and facilitating the reporting task. In this paper we will discuss the evaluation of the breast detection algorithm.

PURPOSE:To study the clinical usefulness of ultrasonography (US)-guided core-needle biopsy (CNB) of axillary lymph nodes and the US-depicted abnormalities that may be used to predict nodal metastases.MATERIALS AND METHODS:This retrospective study was HIPAA compliant and institutional review board approved; the requirement for informed patient consent was waived. US-guided 14-gauge CNB of abnormal axillary lymph nodes was performed in 100 of 144 patients with primary breast cancer who underwent US assessment of axillary lymph nodes. A biopsy needle with controllable action rather than a traditional throw-type needle was used. US findings were considered suspicious for metastasis if cortical thickening and/or nonhilar blood flow (NHBF) to the lymph node cortex was present. The absence of any discernible fatty hilum was also noted.RESULTS:Nodal metastases were documented at CNB in 64 (64%) of the 100 patients. All 36 patients with negative biopsy results underwent subsequent sentinel lymph node biopsy (SLNB), which yielded negative findings in 32 (89%) patients and revealed metastasis in four (11%). All 44 patients who did not undergo CNB because of negative US results subsequently underwent SLNB, which revealed lymph node metastasis in 12 (27%) patients. Cortical thickening was found in 63 (79%) of the total of 80 metastatic nodes, but only a minority (n = 26 [32%]) of the nodes had an absent fatty hilum. NHBF to the cortex was detected in 52 (65%) metastatic nodes. Both absence of a fatty hilum (metastasis detected in 26 [93%] of 28 nodes) and cortical thickening combined with NHBF (metastasis detected in 52 [81%] of 64 nodes) had a high positive predictive value. No clinically important complications were encountered with the biopsy procedures.CONCLUSION:Axillary lymph nodes with abnormal US findings can be sampled with high accuracy and without major complications by using a modified 14-gauge CNB technique.

We document the spring 2007 die-off of 216 Tachycineta bicolor (Tree Swallow) in western New York due to a period of unseasonably warm temperatures followed immediately by a period of unseasonably cold temperatures. Dead swallows were collected from artificial nesting boxes, where they had roosted communally. A subsequent decline in nesting effort was detected during the following nesting season. Implications for future nest-box management are discussed.

To perform a pilot study investigating whether the sensitivity and specificity of kinetic parameters can be improved by considering mass and nonmass breast lesions separately. The contrast media uptake and washout kinetics in benign and malignant breast lesions were analyzed using an empirical mathematical model (EMM), and model parameters were compared in lesions with mass-like and nonmass-like enhancement characteristics. 34 benign and 78 malignant breast lesions were selected for review. Dynamic MR protocol: 1 pre and 5 postcontrast images acquired in the coronal plane using a 3D T1-weighted SPGR with 68 s timing resolution. An experienced radiologist classified the type of enhancement as mass, nonmass, or focus, according to the BI-RADS lexicon. The kinetic curve obtained from a radiologist-drawn region within the lesion was analyzed quantitatively using a three parameter EMM. Several kinetic parameters were then derived from the EMM parameters: the initial slope (Slope(ini)), curvature at the peak (kappa(peak)), time to peak (T(peak)), initial area under the curve at 30 s (iAUC30), and the signal enhancement ratio (SER). The BI-RADS classification of the lesions yielded: 70 mass lesions, 38 nonmass, 4 focus. For mass lesions, the contrast uptake rate (alpha), contrast washout rate (beta), iAUC30, SER, Slope(ini), T(peak) and kappa(peak) differed substantially between benign and malignant lesions, and after correcting for multiple tests of significance SER and T(peak) demonstrated significance (p < 0.007). For nonmass lesions, we did not find statistically significant differences in any of the parameters for benign vs. malignant lesions (p > 0.5). Kinetic parameters could distinguish benign and malignant mass lesions effectively, but were not quite as useful in discriminating benign from malignant nonmass lesions. If the results of this pilot study are validated in a larger trial, we expect that to maximize diagnostic utility, it will be better to classify lesion morphology as mass or nonmass-like enhancement prior to kinetic analysis.