Breast magnetic resonance imaging as a problem-solving modality?

Mammography is the primary imaging modality for the early detection of breast cancer. Because of the low predictive value of mammography, a large majority of patient referred for biopsy have benign disease. The question is whether magnetic resonance imaging (MRI) is a diagnostic alternative to biopsy for women with inconclusive findings at mammography or mammographic (Breast Imaging Reporting And Data System (BIRADS) 3 lesions. In this article the breast MRI and indications will be described. An overview will be given of MRI as a problem-solving modality in mammographic BIRADS 3 lesions and inconclusive mammographic findings with and without microcalcifications. The negative predictive value of breast MRI must be sufficiently high to definitively indicate a lack of need for biopsy and thus to be an effective addition to the work-up of mammographic BIRADS 3 lesions or inconclusive findings on mammography. Therefore, breast MRI should only be used for cases with proven diagnostic value.</p

Breast magnetic resonance imaging as a problem-solving modality?

Mammography is the primary imaging modality for the early detection of breast cancer. Because of the low predictive value of mammography, a large majority of patient referred for biopsy have benign disease. The question is whether magnetic resonance imaging (MRI) is a diagnostic alternative to biopsy for women with inconclusive findings at mammography or mammographic (Breast Imaging Reporting And Data System (BIRADS) 3 lesions. In this article the breast MRI and indications will be described. An overview will be given of MRI as a problem-solving modality in mammographic BIRADS 3 lesions and inconclusive mammographic findings with and without microcalcifications. The negative predictive value of breast MRI must be sufficiently high to definitively indicate a lack of need for biopsy and thus to be an effective addition to the work-up of mammographic BIRADS 3 lesions or inconclusive findings on mammography. Therefore, breast MRI should only be used for cases with proven diagnostic value.</p

Breast magnetic resonance imaging as a problem-solving modality in mammographic BI-RADS 3 lesions

The probability of a mammographic Breast Imaging Reporting and Data System (BI-RADS) 3 lesion being cancer is considered to be less than 2%. Therefore, the work-up of a mammographic BI-RADS 3 lesion should be biopsy or follow-up mammography after 6 months. However, most patients referred for biopsy have benign disease. Although the negative predictive value (NPV) of magnetic resonance imaging (MRI) is highest of all imaging techniques, it is not yet common practice to use breast MRI as a problem-solving modality to exclude patients for further diagnostic work-up. Therefore, in this meta-analysis the usefulness of breast MRI as a problem-solving modality in mammographic BI-RADS 3 lesions is investigated. After a systematic search only 5 out of 61 studies met the inclusion criteria. The NPV in 2 of those studies was reported to be 100%. It was concluded that MRI can be used as an adjunctive tool to mammographic BI-RADS 3 findings to exclude patients for further diagnostic work-up. The other 3 studies assessed the accuracy of MRI in mammographic BI-RADS 3 microcalcifications. These studies reported an NPV of MRI between 76% and 97%. Therefore, MRI cannot be implemented as a diagnostic tool to evaluate mammographic microcalcifications at this time. The first solid data indicate that breast MRI might be useful as a problem-solving modality to exclude patients with non-calcified mammographic BI-RADS 3 lesions for further diagnostic work-up. However, further research is needed to verify these results.</p

Breast magnetic resonance imaging as a problem-solving modality in mammographic BI-RADS 3 lesions

The probability of a mammographic Breast Imaging Reporting and Data System (BI-RADS) 3 lesion being cancer is considered to be less than 2%. Therefore, the work-up of a mammographic BI-RADS 3 lesion should be biopsy or follow-up mammography after 6 months. However, most patients referred for biopsy have benign disease. Although the negative predictive value (NPV) of magnetic resonance imaging (MRI) is highest of all imaging techniques, it is not yet common practice to use breast MRI as a problem-solving modality to exclude patients for further diagnostic work-up. Therefore, in this meta-analysis the usefulness of breast MRI as a problem-solving modality in mammographic BI-RADS 3 lesions is investigated. After a systematic search only 5 out of 61 studies met the inclusion criteria. The NPV in 2 of those studies was reported to be 100%. It was concluded that MRI can be used as an adjunctive tool to mammographic BI-RADS 3 findings to exclude patients for further diagnostic work-up. The other 3 studies assessed the accuracy of MRI in mammographic BI-RADS 3 microcalcifications. These studies reported an NPV of MRI between 76% and 97%. Therefore, MRI cannot be implemented as a diagnostic tool to evaluate mammographic microcalcifications at this time. The first solid data indicate that breast MRI might be useful as a problem-solving modality to exclude patients with non-calcified mammographic BI-RADS 3 lesions for further diagnostic work-up. However, further research is needed to verify these results.</p

Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging:A systematic review and meta-analysis

Background Several methods for tumor delineation are used in literature on breast diffusion weighted imaging (DWI) to measure the apparent diffusion coefficient (ADC). However, in the process of reaching consensus on breast DWI scanning protocol, image analysis and interpretation, still no standardized optimal breast tumor tissue selection (BTTS) method exists. Therefore, the purpose of this study is to assess the impact of BTTS methods on ADC in the discrimination of benign from malignant breast lesions in DWI in terms of sensitivity, specificity and area under the curve (AUC). Methods and findings In this systematic review and meta-analysis, adhering to the PRISMA statement, 61 studies, with 65 study subsets, in females with benign or malignant primary breast lesions (6291 lesions) were assessed. Studies on DWI, quantified by ADC, scanned on 1.5 and 3.0 Tesla and using b-values 0/50 and >= 800 s/mm(2) were included. PubMed and EMBASE were searched for studies up to 23-10-2019 (n = 2897). Data were pooled based on four BTTS methods (by definition of measured region of interest, ROI): BTTS1: whole breast tumor tissue selection, BTTS2: subtracted whole breast tumor tissue selection, BTTS3: circular breast tumor tissue selection and BTTS4: lowest diffusion breast tumor tissue selection. BTTS methods 2 and 3 excluded necrotic, cystic and hemorrhagic areas. Pooled sensitivity, specificity and AUC of the BTTS methods were calculated. Heterogeneity was explored using the inconsistency index (I-2) and considering covariables: field strength, lowest b-value, image of BTTS selection, pre-or post-contrast DWI, slice thickness and ADC threshold. Pooled sensitivity, specificity and AUC were: 0.82 (0.72-0.89), 0.79 (0.65-0.89), 0.88 (0.85-0.90) for BTTS1; 0.91 (0.89-0.93), 0.84 (0.80-0.87), 0.94 (0.91-0.96) for BTTS2; 0.89 (0.86-0.92), 0.90 (0.85-0.93), 0.95 (0.93-0.96) for BTTS3 and 0.90 (0.86-0.93), 0.84 (0.81-0.87), 0.86 (0.82-0.88) for BTTS4, respectively. Significant heterogeneity was found between studies (I-2 = 95). Conclusions None of the breast tissue selection (BTTS) methodologies outperformed in differentiating benign from malignant breast lesions. The high heterogeneity of ADC data acquisition demands further standardization, such as DWI acquisition parameters and tumor tissue selection to substantially increase the reliability of DWI of the breast

Diffusion weighted imaging of the breast:Performance of standardized breast tumor tissue selection methods in clinical decision making

Objectives In breast diffusion weighted imaging (DWI) protocol standardization, it is recently shown that no breast tumor tissue selection (BTTS) method outperformed the others. The purpose of this study is to analyze the feasibility of three fixed-size breast tumor tissue selection (BTTS) methods based on the reproducibility, accuracy and time-measurement in comparison to the largest oval and manual delineation in breast diffusion weighted imaging data. Methods This study is performed with a consecutive dataset of 116 breast lesions (98 malignant) of at least 1.0 cm, scanned in accordance with the EUSOBI breast DWI working group recommendations. Reproducibility of the maximum size manual (BTTS1) and of the maximal size round/oval (BTTS2) methods were compared with three smaller fixed-size circular BTTS methods in the middle of each lesion (BTTS3, 0.12 cm(3) volume) and at lowest apparent diffusion coefficient (ADC) (BTTS4, 0.12 cm(3); BTTS5, 0.24 cm(3)). Mean ADC values, intraclass-correlation-coefficients (ICCs), area under the curve (AUC) and measurement times (sec) of the 5 BTTS methods were assessed by two observers. Results Excellent inter- and intra-observer agreement was found for any BTTS (with ICC 0.88-0.92 and 0.92-0.94, respectively). Significant difference in ADCmean between any pair of BTTS methods was shown (p = Conclusion The performance of fixed-size BTTS methods, as a potential tool for clinical decision making, shows equal AUC but shorter ADC measurement time compared to manual or oval whole lesion measurements. The advantage of a fixed size BTTS method is the excellent reproducibility. A central fixed breast tumor tissue volume of 0.12 cm(3) is the most feasible method for use in clinical practice

Cost-effectiveness of abbreviated-protocol MRI screening for women with mammographically dense breasts in a national breast cancer screening program

INTRODUCTION: Magnetic resonance imaging (MRI) has shown the potential to improve the screening effectiveness among women with dense breasts. The introduction of fast abbreviated protocols (AP) makes MRI more feasible to be used in a general population. We aimed to investigate the cost-effectiveness of AP-MRI in women with dense breasts (heterogeneously/extremely dense) in a population-based screening program. METHODS: A previously validated model (SiMRiSc) was applied, with parameters updated for women with dense breasts. Breast density was assumed to decrease with increased age. The base scenarios included six biennial AP-MRI strategies, with biennial mammography from age 50–74 as reference. Fourteen alternative scenarios were performed by varying screening interval (triennial and quadrennial) and by applying a combined strategy of mammography and AP-MRI. A 3% discount rate for both costs and life years gained (LYG) was applied. Model robustness was evaluated using univariate and probabilistic sensitivity analyses. RESULTS: The six biennial AP-MRI strategies ranged from 132 to 562 LYG per 10,000 women, where more frequent application of AP-MRI was related to higher LYG. The optimal strategy was biennial AP-MRI screening from age 50–65 for only women with extremely dense breasts, producing an incremental cost-effectiveness ratio of € 18,201/LYG. At a threshold of € 20,000/LYG, the probability that the optimal strategy was cost-effective was 79%. CONCLUSION: Population-based biennial breast cancer screening with AP-MRI from age 50–65 for women with extremely dense breasts might be a cost-effective alternative to mammography, but is not an option for women with heterogeneously dense breasts

Clinical characteristics and work-up of small to intermediate-sized pulmonary nodules in a Chinese dedicated cancer hospital

Objectives: To evaluate the characteristics and work-up of small to intermediate-sized pulmonary nodules in a Chinese dedicated cancer hospital. Methods: Patients with pulmonary nodules 4-25 mm in diameter detected via computed tomography (CT) in 2013 were consecutively included. The analysis was restricted to patients with a histological nodule diagnosis or a 2-year follow-up period without nodule growth confirming benign disease. Patient information was collected from hospital records. Results: Among the 314 nodules examined in 299 patients, 212 (67.5%) nodules in 206 (68.9%) patients were malignant. Compared to benign nodules, malignant nodules were larger (18.0 mm vs. 12.5 mm, P < 0.001), more often partly solid (16.0% vs. 4.7%, P < 0.001) and more often spiculated (72.2% vs. 41.2%, P < 0.001), with higher density in contrast-enhanced CT (67.0 HU vs. 57.5 HU, P = 0.015). Final diagnosis was based on surgery in 232 out of 314 (73.9%) nodules, 166 of which were identified as malignant [30 (18.1%) stage III or IV] and 66 as benign. In 36 nodules (11.5%), diagnosis was confirmed by biopsy and the remainder verified based on stability of nodule size at follow-up imaging (n = 46, 14.6%). Among 65 nodules subjected to gene (EGFR) mutation analyses, 28 (43.1%) cases (EGFR19 n = 13; EGFR21 n = 15) were identified as EGFR mutant and 37 (56.9%) as EGFR wild-type. Prior to surgery, the majority of patients [n = 194 (83.6%)] received a contrast-enhanced CT scan for staging of both malignant [n = 140 (84.3%)] and benign [n = 54 (81.8%)] nodules. Usage of positron emission tomography (PET)-CT was relatively uncommon [n = 38 (16.4%)]. Conclusions: CT-derived nodule assessment assists in diagnosis of small to intermediate- sized malignant pulmonary nodules. Currently, contrast-enhanced CT is commonly used as the sole diagnostic confirmation technique for pre-surgical staging, often resulting in surgery for late-stage disease and unnecessary surgery in cases of benign nodules

A contrast-enhanced-CT-based classification tree model for classifying malignancy of solid lung tumors in a Chinese clinical population

Background: To develop and validate a contrast-enhanced CT based classification tree model for classifying solid lung tumors in clinical patients into malignant or benign. Methods: Between January 2015 and October 2017, 827 pathologically confirmed solid lung tumors (487 malignant, 340 benign; median size, 27.0 mm, IQR 18.0-39.0 mm) from 827 patients from a dedicated Chinese cancer hospital were identified. Nodules were divided randomly into two groups, a training group (575 cases) and a testing group (252 cases). CT characteristics were collected by two radiologists, and analyzed using a classification and regression tree (CART) model. For validation, we used the decision analysis threshold to evaluate the classification performance of the CART model and radiologist's diagnosis (benign; malignant) in the testing group. Results: Three out of 19 characteristics [margin (smooth; slightly lobulated/lobulated/spiculated), and shape (round/oval; irregular), subjective enhancement (no/uniform enhancement; heterogeneous enhancement)] were automatically generated by the CART model for classifying solid lung tumors. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy of the CART model is 98.5%, 58.1%, 80.6%, 98.6%, 79.8%, and 90.4%, 54.7%, 82.4% 98.5%, 74.2% for the radiologist's diagnosis by using three-threshold decision analysis. Conclusions: Tumor margin and shape, and subjective tumor enhancement were the most important CT characteristics in the CART model for classifying solid lung tumors as malignant. The CART model had higher discriminatory power than radiologist's diagnosis. The CART model could help radiologists making recommendations regarding follow-up or surgery in clinical patients with a solid lung tumor