Elodia B. Cole

A comparative study of mobile electronic data entry systems for clinical trials data collection

PURPOSE To determine the speed, accuracy, ease of use, and user satisfaction of various electronic data entry platforms for use in the collection of mammography clinical trials data. METHOD AND MATERIALS Four electronic data entry platforms were tested: standalone personal digital assistant (PDA), Tablet PC, digitizer Tablet/PDA Hybrid (DTP Hybrid), and digital pen (d-pen). Standard paper data entry was used as control. Each of five radiologist readers was assigned to enter interpretations for 20 screening mammograms using three out of the five data entry methods. Assistants recorded both start and stop data entry times of the radiologists and the number of help requests made. Data were checked for handwriting recognition accuracy for the d-pen platform using handwriting verification software. A user satisfaction survey was administered at the end of each platform reading session. RESULTS Tablet PC and d-pen were statistically equivalent to conventional pen and paper in initial data entry speed. Average verification time for d-pen was significantly less than secondary electronic data entry of paper forms (p-value <0.001). The number of errors in handwriting recognition for d-pen was less than secondary electronic data entry of the paper forms data. Users were most satisfied with Tablet PC, d-pen, and conventional pen and paper for data entry. CONCLUSIONS Tablet PC and d-pen are equally fast and easy-to-use data entry methods that are well tolerated by radiologist users. Handwriting recognition review and correction for the d-pen is significantly faster and more accurate than secondary manual keyboard and mouse data entry.

Accuracy of Soft-Copy Digital Mammography versus That of Screen-Film Mammography according to Digital Manufacturer: ACRIN DMIST Retrospective Multireader Study

PURPOSE To retrospectively compare the accuracy for cancer diagnosis of digital mammography with soft-copy interpretation with that of screen-film mammography for each digital equipment manufacturer, by using results of biopsy and follow-up as the reference standard. MATERIALS AND METHODS The primary HIPAA-compliant Digital Mammographic Imaging Screening Trial (DMIST) was approved by the institutional review board of each study site, and informed consent was obtained. The approvals and consent included use of data for future HIPAA-compliant retrospective research. The American College of Radiology Imaging Network DMIST collected screening mammography studies performed by using both digital and screen-film mammography in 49 528 women (mean age, 54.6 years; range, 19-92 years). Digital mammography systems from four manufacturers (Fischer, Fuji, GE, and Hologic) were used. For each digital manufacturer, a cancer-enriched reader set of women screened with both digital and screen-film mammography in DMIST was constructed. Each reader set contained all cancer-containing studies known for each digital manufacturer at the time of reader set selection, together with a subset of negative and benign studies. For each reader set, six or 12 experienced radiologists attended two randomly ordered reading sessions 6 weeks apart. Each radiologist identified suspicious findings and rated suspicion of breast cancer in identified lesions by using a seven-point scale. Results were analyzed according to digital manufacturer by using areas under the receiver operating characteristic curve (AUCs), sensitivity, and specificity for soft-copy digital and screen-film mammography. Results for Hologic digital are not presented owing to the fact that few cancer cases were available. The implemented design provided 80% power to detect average AUC differences of 0.09, 0.08, and 0.06 for Fischer, Fuji, and GE, respectively. RESULTS No significant difference in AUC, sensitivity, or specificity was found between Fischer, Fuji, and GE soft-copy digital and screen-film mammography. Large reader variations occurred with each modality. CONCLUSION No statistically significant differences were found between soft-copy digital and screen-film mammography for Fischer, Fuji, and GE digital mammography equipment.

Comparison of Calcification Specificity in Digital Mammography Using Soft-Copy Display Versus Screen-Film Mammography

OBJECTIVE The purpose of this study was to compare specificity in the interpretation of calcifications in soft-copy reviewing of digital mammograms versus hard-copy reviewing of screen-film mammograms. MATERIALS AND METHODS A total of 130 consecutive cases with calcifications (44 malignant and 86 benign) that had been evaluated with needle or surgical biopsy were collected. Both screen-film mammography and soft-copy digital mammography were obtained in the same patients under existing research protocols using Fischer Imagings SenoScan (n = 71), Lorads digital mammography system (n = 35), and GE Healthcares Senographe 2000D (n = 24). Eight trained radiologists scored all lesions--cropped or masked to display just the region of interest--both on screen-film and soft-copy digital mammography with a month between reviews to reduce the effects of learning and memory. A 5-point malignancy scale was used, with 1 as definitely not, 2 as probably not, 3 as possibly, 4 as probably, and 5 as definitely. Reviewers were randomly assigned condition order, and images within each condition were randomly ordered. Repeated measures analysis of variance was used to test for differences between conditions in specificity computed via nonparametric receiver operating characteristic (ROC) study separately for each reviewer and condition. RESULTS Across all reviewers, the mean specificity for 1 or 2 versus 3, 4, or 5 was 0.803 for screen-film mammography (range, 0.413-0.938; SD +/- 0.166) and 0.833 for soft-copy image (range, 0.375-0.951; SD +/- 0.187). Although not statistically significant (Students t test p values from 0.19 to 0.99 across all cut points), numeric values of specificity were consistently higher for soft-copy versus screen-film mammography. No statistical significance in specificity was seen using all possible cut points in the 5-point scale, although the primary analysis used the cutpoint for differentiation between benign and malignant cases as 1 or 2 versus 3, 4, or 5. CONCLUSION No statistically significant difference was shown in specificity achievable using soft-copy digital versus screen-film mammography in this study.

Cancer Cases from ACRIN Digital Mammographic Imaging Screening Trial: Radiologist Analysis with Use of a Logistic Regression Model

PURPOSE To determine which factors contributed to the Digital Mammographic Imaging Screening Trial (DMIST) cancer detection results. MATERIALS AND METHODS This project was HIPAA compliant and institutional review board approved. Seven radiologist readers reviewed the film hard-copy (screen-film) and digital mammograms in DMIST cancer cases and assessed the factors that contributed to lesion visibility on both types of images. Two multinomial logistic regression models were used to analyze the combined and condensed visibility ratings assigned by the readers to the paired digital and screen-film images. RESULTS Readers most frequently attributed differences in DMIST cancer visibility to variations in image contrast--not differences in positioning or compression--between digital and screen-film mammography. The odds of a cancer being more visible on a digital mammogram--rather than being equally visible on digital and screen-film mammograms--were significantly greater for women with dense breasts than for women with nondense breasts, even with the data adjusted for patient age, lesion type, and mammography system (odds ratio, 2.28; P < .0001). The odds of a cancer being more visible at digital mammography--rather than being equally visible at digital and screen-film mammography--were significantly greater for lesions imaged with the General Electric digital mammography system than for lesions imaged with the Fischer (P = .0070) and Fuji (P = .0070) devices. CONCLUSION The significantly better diagnostic accuracy of digital mammography, as compared with screen-film mammography, in women with dense breasts demonstrated in the DMIST was most likely attributable to differences in image contrast, which were most likely due to the inherent system performance improvements that are available with digital mammography. The authors conclude that the DMIST results were attributable primarily to differences in the display and acquisition characteristics of the mammography devices rather than to reader variability.

Automated Delineation of Calcified Vessels in Mammography by Tracking With Uncertainty and Graphical Linking Techniques

As a potential biomarker for womens cardiovascular and chronic kidney diseases, breast arterial calcification (BAC) in mammography has become an emerging research topic in recent years. To provide more objective measurement for vascular structures with calcium depositions in mammography, a new computerized method is introduced in this paper to delineate the calcified vessels. Specifically, we leverage two underlying cues, namely calcification and vesselness, into a multiple seeded tracking with uncertainty scheme. This new vessel-tracking scheme generates plenty of sampling paths to describe the complicated topology of the vascular structures with calcium depositions. A compiling and linking process is further carried out to organize the sampling paths together to be the vessel segments that likely belong to the same vessel tract. The proposed method has been evaluated on 63 mammograms, by comparison with manual delineations from two experts using various assessment metrics. The experiment results confirm the efficacy and stability of the proposed method, and also indicate that the proposed method can be potentially used as a convenient BAC measurement tool in replacement of the trivial and tedious manual delineation tasks.

Comparison of Radiologist Performance with Photon-Counting Full-Field Digital Mammography to Conventional Full-Field Digital Mammography

RATIONALE AND OBJECTIVES The purpose of this study was to assess the performance of a MicroDose photon-counting full-field digital mammography (PCM) system in comparison to full-field digital mammography (FFDM) for area under the receiver-operating characteristic (ROC) curve (AUC), sensitivity, specificity, and feature analysis of standard-view mammography for women presenting for screening mammography, diagnostic mammography, or breast biopsy. MATERIALS AND METHODS A total of 133 women were enrolled in this study at two European medical centers, with 67 women who had a pre-existing 10-36 months FFDM enrolled prospectively into the study and 66 women who underwent breast biopsy and had screening PCM and diagnostic FFDM, including standard craniocaudal and mediolateral oblique views of the breast with the lesion, enrolled retrospectively. The case mix consisted of 49 cancers, 17 biopsy-benign cases, and 67 normal cases. Sixteen radiologists participated in the reader study and interpreted all 133 cases in both conditions, separated by washout period of ≥4 weeks. ROC curve and free-response ROC curve analyses were performed for noninferiority of PCM compared to FFDM using a noninferiority margin Δ value of 0.10. Feature analysis of the 66 cases with lesions was conducted with all 16 readers at the conclusion of the blinded reads. Mean glandular dose was recorded for all cases. RESULTS The AUC for PCM was 0.947 (95% confidence interval [CI], 0.920-0.974) and for FFDM was 0.931 (95% CI, 0.898-0.964). Sensitivity per case for PCM was 0.936 (95% CI, 0.897-0.976) and for FFDM was 0.908 (95% CI, 0.856-0.960). Specificity per case for PCM was 0.764 (95% CI, 0.688-0.841) and for FFDM was 0.749 (95% CI, 0.668-0.830). Free-response ROC curve figures of merit were 0.920 (95% CI, 0.881-0.959) and 0.903 (95% CI, 0.858-0.948) for PCM and FFDM, respectively. Sensitivity per lesion was 0.903 (95% CI, 0.846-0.960) and 0.883 (95% CI, 0.823-0.944) for PCM and FFDM, respectively. The average false-positive marks per image of noncancer cases were 0.265 (95% CI, 0.171-0.359) and 0.281 (95% CI, 0.188-0.374) for PCM and FFDM, respectively. Noninferiority P values for AUC, sensitivity (per case and per lesion), specificity, and average false-positive marks per image were all statistically significant (P < .001). The noninferiority P value for free-response ROC was <.025, from the 95% CI for the difference. Feature analysis resulted in PCM being preferred to FFDM by the readers for ≥70% of the cases. The average mean glandular dose for PCM was 0.74 mGy (95% CI, 0.722-0.759 mGy) and for FFDM was 1.23 mGy (95% CI, 1.199-1.262 mGy). CONCLUSIONS In this study, radiologist performance with PCM was not inferior to that with conventional FFDM at an average 40% lower mean glandular dose.

Impact of Computer-Aided Detection Systems on Radiologist Accuracy With Digital Mammography

OBJECTIVE The purpose of this study was to assess the impact of computer-aided detection (CAD) systems on the performance of radiologists with digital mammograms acquired during the Digital Mammographic Imaging Screening Trial (DMIST). MATERIALS AND METHODS Only those DMIST cases with proven cancer status by biopsy or 1-year follow-up that had available digital images were included in this multireader, multicase ROC study. Two commercially available CAD systems for digital mammography were used: iCAD SecondLook, version 1.4; and R2 ImageChecker Cenova, version 1.0. Fourteen radiologists interpreted, without and with CAD, a set of 300 cases (150 cancer, 150 benign or normal) on the iCAD SecondLook system, and 15 radiologists interpreted a different set of 300 cases (150 cancer, 150 benign or normal) on the R2 ImageChecker Cenova system. RESULTS The average AUC was 0.71 (95% CI, 0.66-0.76) without and 0.72 (95% CI, 0.67-0.77) with the iCAD system (p = 0.07). Similarly, the average AUC was 0.71 (95% CI, 0.66-0.76) without and 0.72 (95% CI 0.67-0.77) with the R2 system (p = 0.08). Sensitivity and specificity differences without and with CAD for both systems also were not significant. CONCLUSION Radiologists in our studies rarely changed their diagnostic decisions after the addition of CAD. The application of CAD had no statistically significant effect on radiologist AUC, sensitivity, or specificity performance with digital mammograms from DMIST.

Detection of Arterial Calcification in Mammograms by Random Walks

A fully automatic algorithm is developed for breast arterial calcification extraction in mammograms. This algorithm is implemented in two major steps: a random-walk based tracking step and a compiling and linking step. With given seeds from detected calcification points, the tracking algorithm traverses the vesselness map by exploring the uncertainties of three tracking factors, i.e., traversing direction, jumping distance, and vesselness value, to generate all possible sampling paths. The compiling and linking algorithm further organizes and groups all sampling paths into calcified vessel tracts. The experimental results show that the performance of the proposed automatic calcification extraction algorithm is statistically close to that obtained by manual delineations.

Assessing the Stand-Alone Sensitivity of Computer-Aided Detection With Cancer Cases From the Digital Mammographic Imaging Screening Trial

OBJECTIVE The purpose of this study was to assess the sensitivities and false-detection rates of two computer-aided detection (CADe) systems when applied to digital or film-screen mammograms in detecting the known breast cancer cases from the Digital Mammographic Imaging Screening Trial (DMIST) breast cancer screening population. MATERIALS AND METHODS Available film-screen and digital mammograms of 161 breast cancer cases from DMIST were analyzed by two CADe systems, iCAD Second-Look and R2 ImageChecker. Three experienced breast-imaging radiologists reviewed the CADe marks generated for each available cancer case, recording the number and locations of CADe marks and whether each CADe mark location corresponded with the known location of the cancer. RESULTS For the 161 cancer cases included in this study, the sensitivities of the DMIST reader without CAD were 0.43 (69/161, 95% CI 0.35-0.51) for digital and 0.41 (66/161, 0.33-0.49) for film-screen mammography. The sensitivities of iCAD were 0.74 (119/161, 0.66-0.81) for digital and 0.69 (111/161, 0.61-0.76) for film-screen mammography, both significantly higher than the DMIST study sensitivities (p < 0.0001 for both). The average number of false CADe marks per case of iCAD was 2.57 (SD, 1.92) for digital and 3.06(1.72) for film-screen mammography. The sensitivity of R2 was 0.74 (119/161, 0.66-0.81) for digital, and 0.60 (97/161, 0.52-0.68) for film-screen mammography, both significantly higher than the DMIST study sensitivities (p < 0.0001 for both). The average number of false CADe marks per case of R2 was 2.07 (1.57) for digital and 1.52 (1.45) for film-screen mammography. CONCLUSION Our results suggest the use of CADe in interpretation of digital and film-screen mammograms could lead to improvements in cancer detection.

Mammographic Findings of Partial Breast Irradiation

RATIONALE AND OBJECTIVES The aim of this study was to determine if patients who underwent partial-breast irradiation followed by segmental mastectomies had fewer mammographic changes on the first post-treatment mammogram than those who underwent segmental mastectomies followed by whole-breast irradiation. MATERIALS AND METHODS Subjects enrolled in a study of partial-breast irradiation therapy after segmental mastectomy (intraoperative radiation therapy) plus a random sample of patients who underwent segmental mastectomies followed by conventional whole-breast radiation therapy were identified through the institutions breast cancer database from March 2003 through February 2006. A radiologist specializing in breast imaging reviewed and recorded each patients pretreatment mammogram for breast density and tumor location and the first post-treatment mammogram, obtained within the first year of treatment, for three common types of mammographic change seen after breast surgery and radiation treatment (breast edema, skin thickening, and surgical scarring), which when severe make it difficult to use mammography for continuing follow-up of the conserved breast. The extent of mammographic change was noted by the radiologist as minimal, moderate, or marked. The data were entered into a database, and statistical analysis was conducted using logistic regression models and chi(2) tests. The effect of breast density on mammographic change was also assessed. RESULTS The severity of edema was lower with decreasing breast density (P < .006). There was no apparent effect of breast density on the severity of skin thickening. The extent of surgical scarring decreased as breast density increased (P < .026). Analysis of the data from the cumulative logistic regression models demonstrated that even after controlling for breast density, patients who underwent whole-breast radiation therapy had significantly more edema (P = .003), skin thickening (P = .003), and surgical scarring than those who underwent intraoperative radiation therapy (P < .001). CONCLUSION Patients have a higher probability of having fewer post-treatment mammographic changes after partial-breast irradiation followed by segmental mastectomy than after breast conservation surgery followed by whole-breast irradiation.