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MRI for the assessment of malignancy in BI-RADS 4 mammographic microcalcifications.

ABSTRACT: Assess the performance of breast MRI to diagnose breast cancer in BI-RADS 4 microcalcifications detected by mammography.This retrospective, IRB-approved study included 248 consecutive contrast-enhanced breast MRI (1.5T, protocol in accordance with EUSOBI recommendations) performed to further diagnose BI-RADS 4 microcalcifications detected at mammography during a 3-year period. Standard of reference had to be established by histopathology. Routine consensus reading results by two radiologists were dichotomized as positive or negative and compared with the reference standard (benign vs malignant) to calculate diagnostic parameters.There were 107 malignant and 141 benign microcalcifications. Malignancy rates were 18.3% (23/126 BI-RADS 4a), 41.7% (25/60 BI-RADS 4b) and 95% (59/62 BI-RADS 4c). There were 103 true-positive, 116 true-negative, 25 false-positive, and 4 false-negative (one invasive cancer, three DCIS; 2 BI-RADS 4c, 1 BI-RADS 4b on mammography) breast MRI findings, effecting a sensitivity, specificity, PPV, and NPV of 96.3% (95%-CI 90.7-99.0%), 82.3% (95%-CI 75.0-88.2%), 80.5% (95%-CI 72.5-87.0%) and 96.7% (95%-CI 91.7-99.1%), respectively.MRI is an accurate tool to further diagnose BI-RADS 4a and 4b microcalcifications and may be helpful to avoid unnecessary biopsies in BI-RADS 4a and 4b lesions. BI-RADS 4c microcalcifications should be biopsied irrespective of MRI findings.

SUBMITTER: Bennani-Baiti B

PROVIDER: S-EPMC5708819 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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MRI for the assessment of malignancy in BI-RADS 4 mammographic microcalcifications.

Bennani-Baiti Barbara B Dietzel Matthias M Baltzer Pascal A PA

PloS one 20171130 11

<h4>Purpose</h4>Assess the performance of breast MRI to diagnose breast cancer in BI-RADS 4 microcalcifications detected by mammography.<h4>Materials and methods</h4>This retrospective, IRB-approved study included 248 consecutive contrast-enhanced breast MRI (1.5T, protocol in accordance with EUSOBI recommendations) performed to further diagnose BI-RADS 4 microcalcifications detected at mammography during a 3-year period. Standard of reference had to be established by histopathology. Routine con ...[more]

PMID: 29190656

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Project description:ObjectivesMRI is an integral part of breast cancer screening in high-risk patients. We investigated whether the application of the Kaiser score, a clinical decision-support tool, may be used to exclude malignancy in contrast-enhancing lesions classified as BI-RADS 4 on breast MRI screening exams.MethodsThis retrospective study included 183 consecutive, histologically proven, suspicious (MR BI-RADS 4) lesions detected within our local high-risk screening program. All lesions were evaluated according to the Kaiser score for breast MRI by three readers blinded to the final histopathological diagnosis. The Kaiser score ranges from 1 (lowest, cancer very unlikely) to 11 (highest, cancer very likely) and reflects increasing probabilities of malignancy, with scores greater than 4 requiring biopsy. Receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic accuracy.ResultsThere were 142 benign and 41 malignant lesions, diagnosed in 159 patients (mean age, 43.6 years). Median Kaiser scores ranged between 2 and 5 in benign and 7 and 8 in malignant lesions. For all lesions, the Kaiser score's accuracy, represented by the area under the curve (AUC), ranged between 86.5 and 90.2. The sensitivity of the Kaiser score was high, between 95.1 and 97.6% for all lesions, and was best in mass lesions. Application of the Kaiser score threshold for malignancy (≤ 4) could have potentially avoided 64 (45.1%) to 103 (72.5%) unnecessary biopsies in 142 benign lesions previously classified as BI-RADS 4.ConclusionsThe use of Kaiser score in high-risk MRI screening reliably excludes malignancy in more than 45% of contrast-enhancing lesions classified as BI-RADS 4.Key points• The Kaiser score shows high diagnostic accuracy in identifying malignancy in contrast-enhancing lesions in patients undergoing high-risk screening for breast cancer. • The application of the Kaiser score may avoid > 45% of unnecessary breast biopsies in high-risk patients. • The Kaiser score aids decision-making in high-risk breast cancer MRI screening programs.

Project description:PURPOSE: To determine (a) how often the Breast Imaging Reporting and Data System (BI-RADS) category 3 was used in the American College of Radiology Imaging Network (ACRIN) Digital Mammographic Imaging Screening Trial (DMIST), either at the time of screening mammography or after work-up, (b) how often subjects actually returned for the recommended follow-up examination, and (c) the rate and stages of any malignancies subsequently found in subjects for whom short-term interval follow-up was recommended. MATERIALS AND METHODS: This study was approved by the Institutional Review Board at all institutions where subjects were enrolled. All subjects participating in DMIST gave informed consent and the study was HIPAA-compliant. A total of 47,599 DMIST-eligible and evaluable subjects, all of whom consented to undergo both digital and screen-film mammography, were included in this analysis. Cases referred for short-term interval follow-up based on digital, screen-film, or both imaging examinations were determined. Compliance with the recommendations and the final outcome (malignancy diagnosis at biopsy or no malignancy confirmed through follow-up) of each evaluable case were determined. RESULTS: A total of 1114 of the 47,599 (2.34%) subjects had tumors assigned a BI-RADS 3 category and were recommended to undergo short-interval follow-up. In this study, 791 of 1114 (71%) of the subjects were compliant with the recommendation and returned for short-interval follow-up. Of the women who did not return for short-interval follow-up, 70% (226 of 323) did return for their next annual mammography. Among all subjects whose tumors were assigned a BI-RADS 3 category either at screening mammography or after additional work-up, nine of 1114 (0.81%) were found to have cancer. Of the nine biopsy-proved cancers, six were invasive cancers and three were ductal carcinoma in situ stage Tis-T1c. The invasive cancers were all less than 2 cm in size. CONCLUSION: In DMIST, radiologists used the BI-RADS 3 classification infrequently (2.3% of patients). Tumors assigned a BI-RADS 3 category had a low rate of malignancy. The relatively high rate of noncompliance with short-interval follow-up recommendations (323 of 1114, or 29%) supports prior recommendations that radiologists thoroughly evaluate lesions before placing them in this category.

Project description:To evaluate the positive predictive values (PPVs) of Breast Imaging and Reporting Data Systems (BI-RADS) assessment categories for breast magnetic resonance (MR) imaging and to identify the BI-RADS MR imaging lesion features most predictive of cancer.This institutional review board-approved HIPAA-compliant prospective multicenter study was performed with written informed consent. Breast MR imaging studies of the contralateral breast in women with a recent diagnosis of breast cancer were prospectively evaluated. Contralateral breast MR imaging BI-RADS assessment categories, morphologic descriptors for foci, masses, non-masslike enhancement (NMLE), and kinetic features were assessed for predictive values for malignancy. PPV of each imaging characteristic of interest was estimated, and logistic regression analysis was used to examine the predictive ability of combinations of characteristics.Of 969 participants, 71.3% had a BI-RADS category 1 or 2 assessment; 10.9%, a BI-RADS category 3 assessment; 10.0%, a BI-RADS category 4 or 5 assessment; and 7.7%, a BI-RADS category 0 assessment on the basis of initial MR images. Thirty-one cancers were detected with MR imaging. Overall PPV for BI-RADS category 4 and 5 lesions was 0.278, with 17 cancers in patients with a BI-RADS category 4 lesion (PPV, 0.205) and 10 cancers in patients with a BI-RADS category 5 lesion (PPV, 0.714). Of the cancers, one was a focus, 17 were masses, and 13 were NMLEs. For masses, irregular shape, irregular margins, spiculated margins, and marked internal enhancement were most predictive of malignancy. For NMLEs, ductal, clumped, and reticular or dendritic enhancement were the features most frequently seen with malignancy. Kinetic enhancement features were less predictive of malignancy than were morphologic features.Standardized terminology of the BI-RADS lexicon enables quantification of the likelihood of malignancy for MR imaging-detected lesions through careful evaluation of lesion features. In particular, BI-RADS assessment categories and morphologic descriptors for masses and NMLE were useful in estimating the probability of cancer.

Project description:PurposeSclerosing adenosis (SA) is a benign lesion that could mimic breast carcinoma and be evaluated as malignancy by Breast Imaging-Reporting and Data System (BI-RADS) analysis. We aimed to construct and validate the performance of radiomic model based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) compared to BI-RADS analysis to identify SA.MethodsSixty-seven patients with invasive ductal carcinoma (IDC) and 58 patients with SA were included in this retrospective study from two institutions. The 125 patients were divided into a training cohort (n= 88) from institution I and a validation cohort from institution II (n=37). Dynamic contrast-enhanced sequences including one pre-contrast and five dynamic post-contrast series were obtained for all cases with different 3T scanners. Single-phase enhancement, multi-phase enhancement, and dynamic radiomic features were extracted from DCE-MRI. The least absolute shrinkage and selection operator (LASSO) logistic regression and cross-validation was performed to build the radscore of each single-phase enhancement and the final model combined multi-phase and dynamic radiomic features. The diagnostic performance of radiomics was evaluated by receiver operating characteristic (ROC) analysis and compared to the performance of BI-RADS analysis. The classification performance was tested using external validation.ResultsIn the training cohort, the AUCs of BI-RADS analysis were 0.71 (95%CI [0.60, 0.80]), 0.78 (95%CI [0.67, 0.86]), and 0.80 (95%CI [0.70, 0.88]), respectively. In single-phase analysis, the second enhanced phase radiomic signature achieved the highest AUC of 0.88 (95%CI [0.79, 0.94]) in distinguishing SA from IDC. Nine multi-phase radiomic features and two dynamic radiomic features showed the best predictive ability for final model building. The final model improved the AUC to 0.92 (95%CI [0.84, 0.97]), and showed statistically significant differences with BI-RADS analysis (p<0.05 for all). In the validation cohort, the AUC of the final model was 0.90 (95%CI [0.75, 0.97]), which was higher than all BI-RADS analyses and showed statistically significant differences with one of the BI-RADS analysis observers (p = 0.03).ConclusionsRadiomics based on DCE-MRI could show better diagnostic performance compared to BI-RADS analysis in differentiating SA from IDC, which may contribute to clinical diagnosis and treatment.

Project description:Purpose To determine the utilization and positive predictive value (PPV) of the American College of Radiology (ACR) Breast Imaging Data and Reporting System (BI-RADS) category 4 subdivisions in diagnostic mammography in the National Mammography Database (NMD). Materials and Methods This study involved retrospective review of diagnostic mammography data submitted to the NMD from January 1, 2008 to December 30, 2014. Utilization rates of BI-RADS category 4 subdivisions were compared by year, facility (type, location, census region), and examination (indication, finding type) characteristics. PPV3 (positive predictive value for biopsies performed) was calculated overall and according to category 4 subdivision. The χ2 test was used to test for significant associations. Results Of 1 309 950 diagnostic mammograms, 125 447 (9.6%) were category 4, of which 33.3% (41 841 of 125 447) were subdivided. Subdivision utilization rates were higher (P < .001) in practices that were community, suburban, or in the West; for examination indication of prior history of breast cancer; and for the imaging finding of architectural distortion. Of 41 841 category 4 subdivided examinations, 4A constituted 55.6% (23 258 of 41 841) of the examinations; 4B, 31.8% (13 302 of 41 841) of the examinations; and 4C, 12.6% (5281 of 41 841) of the examinations. Pathologic outcomes were available in 91 563 examinations, and overall category 4 PPV3 was 21.1% (19 285 of 91 563). There was a statistically significant difference in PPV3 according to category 4 subdivision (P < .001): The PPV of 4A was 7.6% (1274 of 16 784), that of 4B was 22% (2317 of 10 408), and that of 4C was 69.3% (2839 of 4099). Conclusion Although BI-RADS suggests their use, subdivisions were utilized in the minority (33.3% [41 841 of 125 447]) of category 4 diagnostic mammograms, with variability based on facility and examination characteristics. When subdivisions were used, PPV3s were in BI-RADS-specified malignancy ranges. This analysis supports the use of subdivisions in broad practice and, given benefits for patient care, should motivate increased utilization. © RSNA, 2018 Online supplemental material is available for this article.

Dataset Information

MRI for the assessment of malignancy in BI-RADS 4 mammographic microcalcifications.

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MRI for the assessment of malignancy in BI-RADS 4 mammographic microcalcifications.

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