Breast tumor characteristics of BRCA1 and BRCA2 gene mutation carriers on MRI

The appearance of malignant lesions in BRCA1 and BRCA2 mutation carriers (BRCA-MCs) on mammography and magnetic resonance imaging (MRI) was evaluated. Thus, 29 BRCA-MCs with breast cancer were retrospectively evaluated and the results compared with an age, tumor size and tumor type matched control group of 29 sporadic breast cancer cases. Detection rates on both modalities were evaluated. Tumors were analyzed on morphology, density (mammography), enhancement pattern and kinetics (MRI). Overall detection was significantly better with MRI than with mammography (55/58 vs 44/57, P = 0.021). On mammography, lesions in the BRCA-MC group were significantly more described as rounded (12//19 vs 3/13, P = 0.036) and with sharp margins (9/19 vs 1/13, P = 0.024). On MRI lesions in the BRCA-MC group were significantly more described as rounded (16/27 vs 7/28, P = 0.010), with sharp margins (20/27 vs 7/28, P < 0.001) and with rim enhancement (7/27 vs 1/28, P = 0.025). No significant difference was found for enhancement kinetics (P = 0.667). Malignant lesions in BRCA-MC frequently have morphological characteristics commonly seen in benign lesions, like a rounded shape or sharp margins. This applies for both mammography and MRI. However the possibility of MRI to evaluate the enhancement pattern and kinetics enables the detection of characteristics suggestive for a malignancy

Selection of diagnostic features on breast MRI to differentiate between malignant and benign lesions using computer-aided diagnosis: differences in lesions presenting as mass and non-mass-like enhancement

Purpose: To investigate methods developed for the characterisation of the morphology and enhancement kinetic features of both mass and non-mass lesions, and to determine their diagnostic performance to differentiate between malignant and benign lesions that present as mass versus non-mass types. Methods: Quantitative analysis of morphological features and enhancement kinetic parameters of breast lesions were used to differentiate among four groups of lesions: 88 malignant (43 mass, 45 non-mass) and 28 benign (19 mass, 9 non-mass). The enhancement kinetics was measured and analysed to obtain transfer constant (Ktrans) and rate constant (kep). For each mass eight shape/margin parameters and 10 enhancement texture features were obtained. For the lesions presenting as nonmass-like enhancement, only the texture parameters were obtained. An artificial neural network (ANN) was used to build the diagnostic model. Results: For lesions presenting as mass, the four selected morphological features could reach an area under the ROC curve (AUC) of 0.87 in differentiating between malignant and benign lesions. The kinetic parameter (kep) analysed from the hot spot of the tumour reached a comparable AUC of 0.88. The combined morphological and kinetic features improved the AUC to 0.93, with a sensitivity of 0.97 and a specificity of 0.80. For lesions presenting as non-mass-like enhancement, four texture features were selected by the ANN and achieved an AUC of 0.76. The kinetic parameter kepfrom the hot spot only achieved an AUC of 0.59, with a low added diagnostic value. Conclusion: The results suggest that the quantitative diagnostic features can be used for developing automated breast CAD (computer-aided diagnosis) for mass lesions to achieve a high diagnostic performance, but more advanced algorithms are needed for diagnosis of lesions presenting as non-mass-like enhancement. © The Author(s) 2009

Quantitative breast MRI: 2D histogram analysis of diffusion tensor parameters in normal tissue

OBJECT: Diffusion tensor imaging (DTI) of the breast may provide a powerful new approach for the detection of intraductal processes. The aim of this investigation was to characterize the relation between diffusion tensor parameters [fractional anisotropy (FA), mean diffusivity (MD)] in normal breast tissue to obtain information on the microenvironment of the diffusing water molecules and to provide a systematic approach for DTI analysis. MATERIALS AND METHODS: Seven female, healthy volunteers underwent prospective double-spin-echo prepared echo-planar diffusion-weighted sequence (TR/TE 8,250 ms/74 ms, b values 0 and 500 s/mm (2), six encoding directions, 12 averages, 35 slices) in 4 consecutive weeks (3.0 T). Quantitative maps of diffusion tensor parameters were computed offline with custom routines. The interdependence of MD and FA in different voxels was analysed by linear and exponential regression. RESULTS: All MD and FA maps were of excellent quality. A consistent pattern was observed in that lower fractional anisotropy values were more likely associated with higher mean diffusivity values. The dependence exhibited an exponential behavior with a correlation coefficient R = 0.60 (R linear = 0.57). CONCLUSION: The likelihood with which FA and MD values are observed in a voxel within normal breast tissue is characterized by a specific pattern, which can be described by an exponential model. Moreover, we could show that the proposed technique does not depend on the menstrual cycle

Feasibility of MRI-guided large-core-needle biopsy of suspiscious breast lesions at 3 T

The feasibility of large-core-needle magnetic resonance imaging (MRI)-guided breast biopsy at 3 T was assessed. Thirty-one suspicious breast lesions shown only by MRI were detected in 30 patients. Biopsy procedures were performed in a closed-bore 3-T clinical MR system on a dedicated phased-array breast coil with a commercially available add-on stereotactic biopsy device. Tissue sampling was technically successful in 29/31 (94%) lesions. Median lesion size (n = 29) was 9 mm. Histopathological analysis showed 19 benign lesions (66%) and one inconclusive biopsy result (3%). At follow-up of these lesions, 15 lesions showed no malignancy, no information was available in three patients and two lesions turned out to be malignant (one lesion at surgical excision 1 month after biopsy and one lesion at a second biopsy because of a more malignant enhancement curve at 12-months follow-up MRI). Nine biopsy results showed a malignant lesion (31%) which were all surgically removed. No complications occurred. MRI-guided biopsy at 3 T is a safe and effective method for breast biopsy in lesions that are occult on mammography and ultrasound. Follow-up MRI at 6 months after the biopsy should be performed in case of a benign biopsy result

Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification

Classification of malignancy for breast cancer and other cancer types is usually tackled as an object detection problem: Individual lesions are first localized and then classified with respect to malignancy. However, the drawback of this approach is that abstract features incorporating several lesions and areas that are not labelled as a lesion but contain global medically relevant information are thus disregarded: especially for dynamic contrast-enhanced breast MRI, criteria such as background parenchymal enhancement and location within the breast are important for diagnosis and cannot be captured by object detection approaches properly. In this work, we propose a 3D CNN and a multi scale curriculum learning strategy to classify malignancy globally based on an MRI of the whole breast. Thus, the global context of the whole breast rather than individual lesions is taken into account. Our proposed approach does not rely on lesion segmentations, which renders the annotation of training data much more effective than in current object detection approaches. Achieving an AUROC of 0.89, we compare the performance of our approach to Mask R-CNN and Retina U-Net as well as a radiologist. Our performance is on par with approaches that, in contrast to our method, rely on pixelwise segmentations of lesions.Comment: Accepted to MICCAI 201

Breast cancer screening in women at increased risk according to different family histories: an update of the Modena Study Group experience

BACKGROUND: Breast cancer (BC) detection in women with a genetic susceptibility or strong family history is considered mandatory compared with BC screening in the general population. However, screening modalities depend on the level of risk. Here we present an update of our screening programs based on risk classification. METHODS: We defined different risk categories and surveillance strategies to identify early BC in 1325 healthy women recruited by the Modena Study Group for familial breast and ovarian cancer. Four BC risk categories included BRCA1/2 carriers, increased, intermediate, and slightly increased risk. Women who developed BC from January 1, 1994, through December 31, 2005 (N = 44) were compared with the number of expected cases matched for age and period. BRCA1/2 carriers were identified by mutational analysis. Other risk groups were defined by different levels of family history for breast or ovarian cancer (OC). The standardized incidence ratio (SIR) was used to evaluate the observed and expected ratio among groups. All statistical tests were two-sided. RESULTS: After a median follow-up of 55 months, there was a statistically significant difference between observed and expected incidence [SIR = 4.9; 95% confidence interval (CI) = 1.6 to 7.6; p < 0.001]. The incidence observed among BRCA carriers (SIR = 20.3; 95% CI = 3.1 to 83.9; P < 0.001), women at increased (SIR = 4.5; 95% CI = 1.5 to 8.3; P < 0.001) or intermediate risk (SIR = 7.0, 95% CI = 2.0 to 17.1; P = 0.0018) was higher than expected, while the difference between observed and expected among women at slightly increased risk was not statistically significant (SIR = 2.4, 95% CI = 0.9 to 8.3; P = .74). CONCLUSION: The rate of cancers detected in women at high risk according to BRCA status or strong family history, as defined according to our operational criteria, was significantly higher than expected in an age-matched general population. However, we failed to identify a greater incidence of BC in the slightly increased risk group. These results support the effectiveness of the proposed program to identify and monitor individuals at high risk, whereas prospective trials are needed for women belonging to families with sporadic BC or OC

Relationship between morphological features and kinetic patterns of enhancement of the dynamic breast magnetic resonance imaging and clinico-pathological and biological factors in invasive breast cancer

<p>Abstract</p> <p>Background</p> <p>To investigate the relationship between the magnetic resonance imaging (MRI) features of breast cancer and its clinicopathological and biological factors.</p> <p>Methods</p> <p>Dynamic MRI parameters of 68 invasive breast carcinomas were investigated. We also analyzed microvessel density (MVD), estrogen and progesterone receptor status, and expression of p53, HER2, ki67, VEGFR-1 and 2.</p> <p>Results</p> <p>Homogeneous enhancement was significantly associated with smaller tumor size (T1: < 2 cm) (p = 0.015). Tumors with irregular or spiculated margins had a significantly higher MVD than tumors with smooth margins (p = 0.038). Tumors showing a maximum enhancement peak at two minutes, or longer, after injecting the contrast, had a significantly higher MVD count than those which reached this point sooner (p = 0.012). The percentage of tumors with vascular invasion or high mitotic index was significantly higher among those showing a low percentage (≤ 150%) of maximum enhancement before two minutes than among those ones showing a high percentage (>150%) of enhancement rate (p = 0.016 and p = 0.03, respectively). However, there was a significant and positive association between the mitotic index and the peak of maximum intensity (p = 0.036). Peritumor inflammation was significantly associated with washout curve type III (p = 0.042).</p> <p>Conclusions</p> <p>Variations in the early phase of dynamic MRI seem to be associated with parameters indicatives of tumor aggressiveness in breast cancer.</p

Breast MRI: guidelines from the European Society of Breast Imaging

The aim of breast MRI is to obtain a reliable evaluation of any lesion within the breast. It is currently always used as an adjunct to the standard diagnostic procedures of the breast, i.e., clinical examination, mammography and ultrasound. Whereas the sensitivity of breast MRI is usually very high, specificity—as in all breast imaging modalities—depends on many factors such as reader expertise, use of adequate techniques and composition of the patient cohorts. Since breast MRI will always yield MR-only visible questionable lesions that require an MR-guided intervention for clarification, MRI should only be offered by institutions that can also offer a MRI-guided breast biopsy or that are in close contact with a site that can perform this type of biopsy for them. Radiologists involved in breast imaging should ensure that they have a thorough knowledge of the MRI techniques that are necessary for breast imaging, that they know how to evaluate a breast MRI using the ACR BI-RADS MRI lexicon, and most important, when to perform breast MRI. This manuscript provides guidelines on the current best practice for the use of breast MRI, and the methods to be used, from the European Society of Breast Imaging (EUSOBI)

Computer-aided detection in breast MRI: a systematic review and meta-analysis

To evaluate the additional value of computer-aided detection (CAD) in breast MRI by assessing radiologists' accuracy in discriminating benign from malignant breast lesions. A literature search was performed with inclusion of relevant studies using a commercially available CAD system with automatic colour mapping. Two independent researchers assessed the quality of the studies. The accuracy of the radiologists' performance with and without CAD was presented as pooled sensitivity and specificity. Of 587 articles, 10 met the inclusion criteria, all of good methodological quality. Experienced radiologists reached comparable pooled sensitivity and specificity before and after using CAD (sensitivity: without CAD: 89%; 95% CI: 78-94%, with CAD: 89%; 95%CI: 81-94%) (specificity: without CAD: 86%; 95% CI: 79-91%, with CAD: 82%; 95% CI: 76-87%). For residents the pooled sensitivity increased from 72% (95% CI: 62-81%) without CAD to 89% (95% CI: 80-94%) with CAD, however, not significantly. Concerning specificity, the results were similar (without CAD: 79%; 95% CI: 69-86%, with CAD: 78%; 95% CI: 69-84%). CAD in breast MRI has little influence on the sensitivity and specificity of experienced radiologists and therefore their interpretation remains essential. However, residents or inexperienced radiologists seem to benefit from CAD concerning breast MRI evaluation