Detection and quantification of breast arterial calcifications on mammograms: a deep learning approach.

OBJECTIVE: Breast arterial calcifications (BAC) are a sex-specific cardiovascular disease biomarker that might improve cardiovascular risk stratification in women. We implemented a deep convolutional neural network for automatic BAC detection and quantification. METHODS: In this retrospective study, four readers labelled four-view mammograms as BAC positive (BAC+) or BAC negative (BAC-) at image level. Starting from a pretrained VGG16 model, we trained a convolutional neural network to discriminate BAC+ and BAC- mammograms. Accuracy, F1 score, and area under the receiver operating characteristic curve (AUC-ROC) were used to assess the diagnostic performance. Predictions of calcified areas were generated using the generalized gradient-weighted class activation mapping (Grad-CAM++) method, and their correlation with manual measurement of BAC length in a subset of cases was assessed using Spearman ρ. RESULTS: A total 1493 women (198 BAC+) with a median age of 59 years (interquartile range 52-68) were included and partitioned in a training set of 410 cases (1640 views, 398 BAC+), validation set of 222 cases (888 views, 89 BAC+), and test set of 229 cases (916 views, 94 BAC+). The accuracy, F1 score, and AUC-ROC were 0.94, 0.86, and 0.98 in the training set; 0.96, 0.74, and 0.96 in the validation set; and 0.97, 0.80, and 0.95 in the test set, respectively. In 112 analyzed views, the Grad-CAM++ predictions displayed a strong correlation with BAC measured length (ρ = 0.88, p < 0.001). CONCLUSION: Our model showed promising performances in BAC detection and in quantification of BAC burden, showing a strong correlation with manual measurements. CLINICAL RELEVANCE STATEMENT: Integrating our model to clinical practice could improve BAC reporting without increasing clinical workload, facilitating large-scale studies on the impact of BAC as a biomarker of cardiovascular risk, raising awareness on women's cardiovascular health, and leveraging mammographic screening. KEY POINTS: • We implemented a deep convolutional neural network (CNN) for BAC detection and quantification. • Our CNN had an area under the receiving operator curve of 0.95 for BAC detection in the test set composed of 916 views, 94 of which were BAC+ . • Furthermore, our CNN showed a strong correlation with manual BAC measurements (ρ = 0.88) in a set of 112 views.

Utility of detection of breast calcifications with integrated real-time radiography system (IRRS) during digital breast tomosynthesis (DBT)-guided vacuum assisted biopsy (VAB): initial single-center experience.

PURPOSE: To determine whether the presence of calcifications in specimens collected during stereotactic-guided vacuum-assisted breast biopsies (VABB) is sufficient to ascertain their adequacy for final diagnosis at pathology. MATERIALS AND METHODS: Digital breast tomosynthesis (DBT)-guided VABBs were performed on 74 patients with calcifications as target. Each biopsy consisted of the collection of 12 samplings with a 9-gauge needle. This technique was integrated with a real-time radiography system (IRRS) which allowed the operator to determine whether calcifications were included in the specimens at the end of each of the 12 tissue collections through the acquisition of a radiograph of every sampling. Calcified and non-calcified specimens were separately sent to pathology and evaluated. RESULTS: A total of 888 specimens were retrieved, 471 containing calcifications and 417 without. In 105 (22.2%) samples out of 471 with calcifications cancer was detected, while the remaining 366 (77.7%) were non-cancerous. Out of 417 specimens without calcifications 56 (13.4%) were cancerous, whereas 361 (86.5%) were non-cancerous. Seven hundred and twenty-seven specimens out of all 888 were cancer-free (81.8%, 95%CI 79-84%). CONCLUSION: Although there is a statistical significative difference between calcified and non-calcified samples and the detection of cancer (p < 0.001), our study shows that the sole presence of calcifications in the specimens is not sufficient to determine their adequacy for final diagnosis at pathology because non-calcified samples can be cancerous and vice-versa. Ending biopsies when calcifications are first detected through IRRS could lead to false negative results.

Breast arterial calcifications as a biomarker of cardiovascular risk: radiologists' awareness, reporting, and action. A survey among the EUSOBI members.

OBJECTIVES: To investigate the knowledge of radiologists on breast arterial calcifications (BAC) and attitude about BAC reporting, communication to women, and subsequent action. METHODS: An online survey was offered to EUSOBI members, with 17 questions focused on demographics, level of experience, clinical setting, awareness of BAC association with cardiovascular risk, mammographic reporting, modality of BAC assessment, and action habits. Descriptive statistics were used. RESULTS: Among 1084 EUSOBI members, 378 (34.9%) responded to the survey, 361/378 (95.5%) radiologists, 263 females (69.6%), 112 males (29.6%), and 3 (0.8%) who did not specify their gender. Of 378 respondents, 305 (80.7%) declared to be aware of BAC meaning in terms of cardiovascular risk and 234 (61.9%) to routinely include BAC in mammogram reports, when detected. Excluding one inconsistent answer, simple annotation of BAC presence was declared by 151/233 (64.8%), distinction between low versus extensive BAC burden by 59/233 (25.3%), and usage of an ordinal scale by 22/233 (9.5%) and of a cardinal scale by 1/233 (0.4%). Among these 233 radiologists reporting BAC, 106 (45.5%) declared to orally inform the woman and, in case of severe BAC burden, 103 (44.2%) to investigate cardiovascular history, and 92 (39.5%) to refer the woman to a cardiologist. CONCLUSION: Among EUSOBI respondents, over 80% declared to be aware of BAC cardiovascular meaning and over 60% to include BAC in the report. Qualitative BAC assessment predominates. About 40% of respondents who report on BAC, in the case of severe BAC burden, investigate cardiovascular history and/or refer the woman to a cardiologist. KEY POINTS: • Of 1084 EUSOBI members, 378 (35%) participated: 81% of respondents are aware of breast arterial calcification (BAC) cardiovascular meaning and 62% include BAC in the mammogram report. • Of those reporting BAC, description of presence was declared by 65%, low versus extensive burden distinction by 25%, usage of an ordinal scale by 10%, and of a cardinal scale by 0.4%; 46% inform the woman and, in case of severe BAC burden, 44% examine cardiovascular history, and 40% refer her to a cardiologist. • European breast radiologists may be ready for large-scale studies to ascertain the role of BAC assessment in the comprehensive framework of female cardiovascular disease prevention.

Biennial screening mammography: How many women ask for more? Estimate of the interval mammogram rate in an organised population-based screening programme.

OBJECTIVES: To estimate the interval mammogram rate, i.e. the undertaking of an additional mammography between scheduled screening rounds, and identify factors influencing this phenomenon. METHODS: Data from our screening programme for the year 2014, excluding prevalent rounds, were analysed. Information about the number of women who underwent  interval mammograms was obtained reviewing the questionnaires and searching the department database. Data on age, breast density, family history of breast cancer, number of screening rounds, previous recalls, general practitioner, and city of residence (used as a proxy of local socio-economic differences) were evaluated using chi-square test. RESULTS: Of 2780 screened women (incident rounds), 2566 had complete data (92%). The interval mammogram rate was 384/2566 (15%, 95% confidence interval 14-17%). Women classified with American College of Radiology c or d breast density categories showed a higher interval mammography probability than those with a and b density (p < 0.001); women in their second round showed a higher probability of interval mammogram compared to women in their fifth, sixth, or seventh round (p ≤ 0.004). No significant differences were found between women with and without an interval mammogram when considering previous recalls for a negative work-up (p = 0.241), positive breast cancer family history (p = 0.538), and city of residence (p = 0.177). CONCLUSIONS: The interval mammogram rate was relatively low (15%). Higher breast density and first of years of adherence to the programme were associated with higher interval mammogram rate.

Double reading of diffusion-weighted magnetic resonance imaging for breast cancer detection.

PURPOSE: To estimate the performance of diffusion-weighted imaging (DWI) for breast cancer detection. METHODS: Consecutive breast magnetic resonance imaging examinations performed from January to September 2016 were retrospectively evaluated. Examinations performed before/after neoadjuvant therapy, lacking DWI sequences or reference standard were excluded; breasts after mastectomy were also excluded. Two experienced breast radiologists (R1, R2) independently evaluated only DWI. Final pathology or > 1-year follow-up served as reference standard. Mc Nemar, χ2, and κ statistics were applied. RESULTS: Of 1,131 examinations, 672 (59.4%) lacked DWI sequence, 41 (3.6%) had no reference standard, 30 (2.7%) were performed before/after neoadjuvant therapy, and 10 (0.9%) had undergone bilateral mastectomy. Thus, 378 women aged 49 ± 11 years (mean ± standard deviation) were included, 51 (13%) with unilateral mastectomy, totaling 705 breasts. Per-breast cancer prevalence was 96/705 (13.6%). Per-breast sensitivity was 83/96 (87%, 95% confidence interval 78-93%) for both R1 and R2, 89/96 (93%, 86-97%) for double reading (DR) (p = 0.031); per-lesion DR sensitivity for cancers ≤ 10 mm was 22/31 (71%, 52-86%). Per-breast specificity was 562/609 (93%, 90-94%) for R1, 538/609 (88%, 86-91%) for R2, and 526/609 (86%¸ 83-89%) for DR (p < 0.001). Inter-observer agreement was substantial (κ = 0.736). Acquisition time varied from 3:00 to 6:22 min:s. Per-patient median interpretation time was 46 s (R1) and 51 s (R2). CONCLUSIONS: DR DWI showed a 93% sensitivity and 88% specificity, with 71% sensitivity for cancers ≤ 10 mm, pointing out a potential for DWI as stand-alone screening method.

Upgrade Rate of Percutaneously Diagnosed Pure Atypical Ductal Hyperplasia: Systematic Review and Meta-Analysis of 6458 Lesions.

Background Management of percutaneously diagnosed pure atypical ductal hyperplasia (ADH) is an unresolved clinical issue. Purpose To calculate the pooled upgrade rate of percutaneously diagnosed pure ADH. Materials and Methods A search of MEDLINE and EMBASE databases was performed in October 2018. Preferred Reporting Items for Systematic Reviews and Meta-Analyses, or PRISMA, guidelines were followed. A fixed- or random-effects model was used, along with subgroup and meta-regression analyses. The Newcastle-Ottawa scale was used for study quality, and the Egger test was used for publication bias. Results Of 521 articles, 93 were analyzed, providing data for 6458 ADHs (5911 were managed with surgical excision and 547 with follow-up). Twenty-four studies used core-needle biopsy; 44, vacuum-assisted biopsy; 21, both core-needle and vacuum-assisted biopsy; and four, unspecified techniques. Biopsy was performed with stereotactic guidance in 29 studies; with US guidance in nine, with MRI guidance in nine, and with mixed guidance in eight. Overall heterogeneity was high (I2 = 80%). Subgroup analysis according to management yielded a pooled upgrade rate of 29% (95% confidence interval [CI]: 26%, 32%) for surgically excised lesions and 5% (95% CI: 4%, 8%) for lesions managed with follow-up (P < .001). Heterogeneity was entirely associated with surgically excised lesions (I2 = 78%) rather than those managed with follow-up (I2 = 0%). Most variability was explained by guidance and needle caliper (P = .15). At subgroup analysis of surgically excised lesions, the pooled upgrade rate was 42% (95% CI: 31%, 53%) for US guidance, 23% (95% CI: 19%, 27%) for stereotactic biopsy, and 32% (95% CI: 22%, 43%) for MRI guidance, with heterogeneity (52%, 63%, and 56%, respectively) still showing the effect of needle caliper. When the authors considered patients with apparent complete lesion removal after biopsy (subgroups in 14 studies), the pooled upgrade rate was 14% (95% CI: 8%, 23%). Study quality was low to medium; the risk of publication bias was low (P = .10). Conclusion Because of a pooled upgrade rate higher than 2% (independent of biopsy technique, needle size, imaging guidance, and apparent complete lesion removal), atypical ductal hyperplasia diagnosed with percutaneous needle biopsy should be managed with surgical excision. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Brem in this issue.

Gadolinium Retention and Breast MRI Screening: More Harm Than Good?

OBJECTIVE. The purpose of this article is to describe the risk-benefit balance of contrast-enhanced breast MRI (CE-BMRI) screening. CONCLUSION. CE-BMRI confers risk of effects associated with administration of gadolinium-based contrast agents (GBCAs), including nephrogenic systemic fibrosis and gadolinium retention. The risk-benefit balance of CE-BMRI screening is favorable for carriers of BRCA, TP53, or other deleterious mutations women who have undergone thoracic irradiation; and women at 20% or greater lifetime risk of breast cancer. The balance is uncertain, however, for women at intermediate to average risk. Women must always receive detailed information regarding possible GBCA-associated effects.

Artificial Intelligence for Breast MRI in 2008-2018: A Systematic Mapping Review.

OBJECTIVE: The purpose of this study is to review literature from the past decade on applications of artificial intelligence (AI) to breast MRI. MATERIALS AND METHODS: In June 2018, a systematic search of the literature was performed to identify articles on the use of AI in breast MRI. For each article identified, the surname of the first author, year of publication, journal of publication, Web of Science Core Collection journal category, country of affiliation of the first author, study design, dataset, study aim(s), AI methods used, and, when available, diagnostic performance were recorded. RESULTS: Sixty-seven studies, 58 (87%) of which had a retrospective design, were analyzed. When journal categories were considered, 36% of articles were identified as being included in the radiology and imaging journal category. Contrast-enhanced sequences were used for most AI applications (n = 50; 75%) and, on occasion, were combined with other MRI sequences (n = 8; 12%). Four main clinical aims were addressed: breast lesion classification (n = 36; 54%), image processing (n = 14; 21%), prognostic imaging (n = 9; 13%), and response to neoadjuvant therapy (n = 8; 12%). Artificial neural networks, support vector machines, and clustering were the most frequently used algorithms, accounting for 66%. The performance achieved and the most frequently used techniques were then analyzed according to specific clinical aims. Supervised learning algorithms were primarily used for lesion characterization, with the AUC value from ROC analysis ranging from 0.74 to 0.98 (median, 0.87) and with that from prognostic imaging ranging from 0.62 to 0.88 (median, 0.80), whereas unsupervised learning was mainly used for image processing purposes. CONCLUSION: Interest in the application of advanced AI methods to breast MRI is growing worldwide. Although this growth is encouraging, the current performance of AI applications in breast MRI means that such applications are still far from being incorporated into clinical practice.

Correlation between voxel-wise enhancement parameters on DCE-MRI and pathological prognostic factors in invasive breast cancers.

PURPOSE: To investigate the correlation between enhancement parameters on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and pathologic prognostic factors in invasive breast cancers (BCs). MATERIALS AND METHODS: A total of 25 invasive BCs were included: 22 invasive ductal, 2 invasive lobular and 1 invasive mucinous. The tumor volume was segmented using a semi-automatic software (Olea Sphere). The following voxel-wise enhancement parameters were extracted: (1) time to peak enhancement; (2) signal intensity at peak (SIP); (3) peak enhancement percentage (PEP); (4) post-initial enhancement percentage (PIEP). The following pathological prognostic factors were considered for potential correlation: tumor (pT) and nodal (pN) stage, grading, perivascular/perineural invasion, estrogen/progesterone receptor status, Ki-67 proliferation, and HER2 expression. Spearman and Pearson correlation coefficients were calculated according with type of variable and data distribution. RESULTS: Tumor volume was 2.8 ± 2.0 cm3 (mean ± standard deviation [SD]). Mean SIP correlated with pT (ρ = 0.424, p = 0.035); mean PEP correlated with HER2 overexpression (ϕ = 0.471, p = 0.017) and pT (ρ = 0.449, p = 0.024). The percentage of voxels with fast PEP directly correlated with pT (ρ = 0.482, p = 0.015) and pN (ρ = 0.446, p = 0.026), while the percentage of voxels with slow PEP inversely correlated with pT (ρ = -0.421, p = 0.039) and pN (ρ = -0.481, p = 0.015). Segmentation time was 14.6 ± 1.3 min (mean ± SD). CONCLUSION: In invasive BCs, DCE-MRI voxel-wise enhancement parameters correlated with HER2, pT, and pN.

Breast arterial calcifications on mammography: intra- and inter-observer reproducibility of a semi-automatic quantification tool.

PURPOSE: A strong association between breast arterial calcifications (BAC) and cardiovascular disease has been demonstrated. However, BAC quantification tools are lacking. We evaluated the intra- and inter-observer reproducibility of a semi-automatic tool for BAC quantification on digital mammograms. MATERIALS AND METHODS: A multivendor image dataset of 212 mammographic views, 106 cranio-caudal (CC) and 106 medio-lateral oblique (MLO), were retrospectively selected from 53 subjects if BAC were seen in at least one view. Images were segmented twice by two intensively trained residents in Radiodiagnostics with > 6-month experience in mammography using a semi-automatic software. The two observers (O1, O2) independently positioned rectangular ROIs where they recognized BAC on both CC and MLO views, separately. The adaptive thresholding algorithm automatically provided the BAC amount in mm2. Number, size, and position of the ROIs were observer-dependent. Total BAC amount was calculated for each patient. Bland-Altman analysis was used. RESULTS: Total BAC amount was 56.6 (IQR 18.1-91.1) and 41.0 (IQR 18.8-90.9) for O1 and O2, respectively. Intra-observer Bland-Altman analysis showed a bias of 11.9 mm2, a coefficient of repeatability of 32.7 mm2, an average measurement of 72.8 mm2, for a 55% reproducibility; the same data were - 7.0, 61.4, 63.4 mm2, and only 3%, respectively, for the inter-observer analysis. CONCLUSION: Our semi-automatic tool for BAC quantification showed a poor reproducibility. These results pointed out that the human identification of BAC represents the main source of variability. Further research is needed to translate BAC quantification into clinical practice.

Optical Imaging of the Breast: Basic Principles and Clinical Applications.

OBJECTIVE: The objective of this article is to summarize the physical principles, technology features, and first clinical applications of optical imaging techniques to the breast. CONCLUSION: Light-breast tissue interaction is expressed as absorption and scattering coefficients, allowing image reconstruction based on endogenous or exogenous contrast. Diffuse optical spectroscopy and imaging, fluorescence molecular tomography, photoacoustic imaging, and multiparametric infrared imaging show potential for clinical application, especially for lesion characterization, estimation of cancer probability, and monitoring the effect of neoadjuvant therapy.

Diagnostic Performance of MRI Versus Galactography in Women With Pathologic Nipple Discharge: A Systematic Review and Meta-Analysis.

OBJECTIVE: The objective of our study was to perform a systematic review of the literature of the diagnostic accuracy of MRI compared with galactography in women with pathologic nipple discharge. MATERIALS AND METHODS: A systematic literature search was performed (MEDLINE, Embase, Web of Science) for articles evaluating the diagnostic performance of MRI and galactography in patients with pathologic nipple discharge and with histologic verification or clinical follow-up. Distinction between any abnormality and cancer was made. Two independent readers selected eligible articles published until December 2015. The quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Data analyses were performed using the bivariate model. RESULTS: Ten articles were analyzed for a total of 921 patients. The study quality was high, with a low risk of bias and low concerns regarding applicability. The pooled sensitivity for any abnormality was significantly higher for MRI, with 92% (95% CI, 85-96%), than for galactography, with 69% (95% CI, 59-78%) (p < 0.001). The pooled specificity was 76% (95% CI, 49-92%) for MRI versus 39% (95% CI, 16-69%) for galactography (p < 0.001). The pooled sensitivity and specificity for cancer detection were calculated for MRI only and were 92% (95% CI, 74-98%) and 97% (95% CI, 80-100%), respectively. CONCLUSION: This meta-analysis shows a higher diagnostic performance of MRI compared with that of galactography in the detection of any kind of lesion in patients with pathologic nipple discharge. Moreover, high sensitivity and very high specificity for cancer by MRI could be confirmed in this clinical setting. If mammography and ultrasound are negative, MRI should be preferred over galactography for further evaluation.

MR Imaging for Selection of Patients for Partial Breast Irradiation: A Systematic Review and Meta-Analysis.

PURPOSE: To systematically review articles that estimated the ineligibility for partial breast irradiation (PBI) after magnetic resonance (MR) imaging. MATERIALS AND METHODS: No ethics committee approval was needed. A systematic search was performed by using MEDLINE and EMBASE. The rate of patients eligible at standard assessment (ie, clinical examination, mammography, and/or ultrasonography) but ineligible after MR imaging was a study outcome. Odds ratios (ORs) were calculated to identify predictors. Quality was appraised by using the Strengthening Reporting of Observational Studies in Epidemiology checklist. RESULTS: Of 93 retrieved articles, six were included (total, 3136 patients). For PBI eligibility, all studies applied National Surgical Adjuvant Breast and Bowel Project B-39 criteria. Ineligibility at standard assessment varied from 21% to 80%; MR imaging prompted ineligibility for PBI in 6%-25% of patients who were initially deemed eligible or in 2%-20% if calculated on the overall number of patients initially screened. Meta-regression showed a negative correlation between ineligibility at standard assessment and ineligibility after MR imaging (P < .001). The pooled percentage of patients eligible at standard assessment but ineligible after MR imaging was 11% (95% confidence interval [CI]: 6%, 19%). Predictors for ineligibility after MR imaging were cancers stage pT2 or greater versus less than stage pT2 (OR, 8.8 [95% CI: 4.7, 16.7]; P < .001), invasive lobular histopathologic results versus invasive ductal pathologic results (OR, 3.0 [95% CI: 1.6, 6.6]; P = .007), pre- versus postmenopausal status (OR, 1.9 [95% CI: 1.3, 2.6]; P < .001), invasive cancer versus ductal carcinoma in situ (OR, 1.6 [95% CI: 1.0, 2.4]; P = .031). Study quality ranged from 17 to 20 (maximum quality, 22). The risk of publication bias was moderate. CONCLUSION: One of nine women (11%), who on the sole basis of standard assessment were candidates to undergo PBI, was found to be ineligible after undergoing MR imaging. Breast MR imaging should be used to select patients for PBI.

Surgical impact of preoperative breast MRI in women below 40 years of age.

Our aim was to evaluate the surgical impact of preoperative MRI in young patients. We reviewed a single-institution database of 283 consecutive patients below 40 years of age and who were treated for breast cancer. Thirty-seven (13 %) patients who received neoadjuvant chemotherapy were excluded. The remaining 246 patients included 124 (50 %) who preoperatively underwent conventional imaging (CI), i.e., mammography/ultrasonography (CI-group), and 122 (50 %) who underwent CI and dynamic MRI (CI + MRI-group). Pathology of surgical specimens served as a reference standard. Mann-Whitney, χ (2), and McNemar statistics were used. There were no significant differences between groups in terms of age, tumor pathologic subtype, stage, receptor, or nodal status. The mastectomy rate was 111/246 (45 %) overall but was significantly different between groups (46/124, 37 %, for the CI group and 65/122, 53 %, for the CI + MRI group; p = 0.011). Of 122 CI + MRI patients, 46 (38 %) would have undergone mastectomy due to CI alone, while MRI determined 19 additional mastectomies, increasing the mastectomy rate from 38 % to 53 % (p < 0.001). The number of patients with multifocal, multicentric, synchronous, or bilateral cancers was significantly different between groups (10/124, 8 %, for the CI group and 33/122, 27 %, for the CI + MRI group; p < 0.001). In the CI + MRI group, multifocal, multicentric, or synchronous bilateral cancers were detected with mammography in 5/33 (15 %) patients, with ultrasonography in 15/33 (45 %) patients, and with MRI in 32/33 (97 %) patients (p < 0.005). Two mastectomies were due to false positives at both conventional tests in the CI group (2/124, 1.6 %) and two mastectomies were due to MRI false positives in the CI + MRI group (2/122, 1.6 %). In conclusion, breast cancer in young patients was treated with mastectomy in 37-38 % of cases on the basis of CI only and in these patients MRI was more sensitive than CI for multifocal, multicentric, or synchronous bilateral cancers, resulting in an additional mastectomy rate of 15 %. A low probability of inappropriate imaging-based decision-making for mastectomy exists for both CI alone and for CI + MRI, making presurgical needle biopsy mandatory for findings that suggest a need for mastectomy.

Pathologic response and residual tumor cellularity after neo-adjuvant chemotherapy predict prognosis in breast cancer patients.

INTRODUCTION: Residual tumor cellularity (RTC) and pathologic complete response (pCR) after neo-adjuvant chemotherapy (NAC) are prognostic factors associated with improved outcomes in breast cancer (BC). However, the majority of patients achieve partial pathologic response (pPR) and no clear correlation between RTC patterns and outcomes was described. Our aims were to define predictive factors for pCR and compare different outcomes of patients with pCR or pPR and with different RTC patterns. MATERIALS AND METHODS: Baseline and post-NAC demographics, clinicopathological characteristics, post-operative data, survival and recurrence status were recorded from our institutional database. A multivariable analysis was performed using a logistic regression model to identify independent predictors of pCR. Disease-free survival (DFS), distant disease-free survival (DDFS), and overall survival (OS) analyses were performed using the Kaplan-Meier method. RESULTS: Overall, of the 495 patients analyzed, 148 (29.9%) achieved pCR, 347 (70.1%) had pPR, and the median RTC was 40%. Multivariable analysis identified 3 independent factors predictive of pCR: tumor stage before NAC (cT1-2 84.5% versus cT3-4 15.5%), BC sub-type (HER2-positive 54.7% versus triple-negative 29.8% versus luminal-like 15.5%), and vascular invasion (absence 98.0% versus presence 2.0%). We found statistically significant longer DFS, DDFS, and OS in patients with pCR and with RTC <40%; no difference was observed in terms of OS between RTC <40% and RTC ≥40% groups. CONCLUSIONS: Tumor stage before NAC, BC sub-type, and vascular invasion are significant and independent factors associated with pCR. Patients with pCR and with RTC <40% have longer DFS, DDFS, and OS compared with patients with pPR.

Washout of mass-like benign breast lesions at dynamic magnetic resonance imaging.

OBJECTIVE: This study aimed to estimate the frequency and timing of washout in a series of pathologically proven benign mass-like breast lesions at dynamic magnetic resonance imaging. METHODS: Institutional review board approval was obtained for this retrospective study. We evaluated enhancement kinetics of 33 pathologically confirmed benign breast lesions: fibroadenomas (n = 22), adenosis (n = 6), typical ductal hyperplasia (n = 2), fibroadenoma with ductal hyperplasia (n = 1), fibrosclerosis (n = 1), and inflammatory lesion (n = 1). Coronal 3-dimensional T1-weighted gradient-echo sequences were acquired before/after intravenous injection of 0.1 mmol/ kg gadoterate meglumine (time resolution, 111 seconds), 1 before and 5 after contrast injection. The time point at which the kinetic curve demonstrated a washout was recorded. Cumulative distribution of lesions showing washout was built. Paired comparisons of specificity for washout kinetics were performed using the McNemar test. RESULTS: Of 33 lesions, washout was never observed in 20 (61%), whereas 13 (39%) showed washout during the study. Of these 13 lesions, only 1 (inflammatory mass) exhibited washout within the first 3 minutes (specificity, 97%), 9 within 6 minutes (specificity, 73%), and 13 within 8 minutes (specificity, 61%). Specificity of washout kinetics within 3 minutes (97%) was significantly larger than that from the sixth minute (73%) and thereafter (P < 0.016). CONCLUSIONS: A prolonged observation for dynamic breast magnetic resonance imaging may result in false-positive washout, especially after 6 minutes. Late washout should not be considered a reliable marker of malignancy.

MRI as a biomarker for breast cancer diagnosis and prognosis.

Breast cancer (BC) is the most frequently diagnosed female invasive cancer in Western countries and the leading cause of cancer-related death worldwide. Nowadays, tumor heterogeneity is a well-known characteristic of BC, since it includes several nosological entities characterized by different morphologic features, clinical course and response to treatment. Thus, with the spread of molecular biology technologies and the growing knowledge of the biological processes underlying the development of BC, the importance of imaging biomarkers as non-invasive information about tissue hallmarks has progressively grown. To date, breast magnetic resonance imaging (MRI) is considered indispensable in breast imaging practice, with widely recognized indications such as BC screening in females at increased risk, locoregional staging and neoadjuvant therapy (NAT) monitoring. Moreover, breast MRI is increasingly used to assess not only the morphologic features of the pathological process but also to characterize individual phenotypes for targeted therapies, building on developments in genomics and molecular biology features. The aim of this review is to explore the role of breast multiparametric MRI in providing imaging biomarkers, leading to an improved differentiation of benign and malignant breast lesions and to a customized management of BC patients in monitoring and predicting response to treatment. Finally, we discuss how breast MRI biomarkers offer one of the most fertile ground for artificial intelligence (AI) applications. In the era of personalized medicine, with the development of omics-technologies, machine learning and big data, the role of imaging biomarkers is embracing new opportunities for BC diagnosis and treatment.

The potential of predictive and prognostic breast MRI (P2-bMRI).

Magnetic resonance imaging (MRI) is an important part of breast cancer diagnosis and multimodal workup. It provides unsurpassed soft tissue contrast to analyse the underlying pathophysiology, and it is adopted for a variety of clinical indications. Predictive and prognostic breast MRI (P2-bMRI) is an emerging application next to these indications. The general objective of P2-bMRI is to provide predictive and/or prognostic biomarkers in order to support personalisation of breast cancer treatment. We believe P2-bMRI has a great clinical potential, thanks to the in vivo examination of the whole tumour and of the surrounding tissue, establishing a link between pathophysiology and response to therapy (prediction) as well as patient outcome (prognostication). The tools used for P2-bMRI cover a wide spectrum: standard and advanced multiparametric pulse sequences; structured reporting criteria (for instance BI-RADS descriptors); artificial intelligence methods, including machine learning (with emphasis on radiomics data analysis); and deep learning that have shown compelling potential for this purpose. P2-bMRI reuses the imaging data of examinations performed in the current practice. Accordingly, P2-bMRI could optimise clinical workflow, enabling cost savings and ultimately improving personalisation of treatment. This review introduces the concept of P2-bMRI, focusing on the clinical application of P2-bMRI by using semantic criteria.

Loco-Regional Treatment of the Primary Tumor in De Novo Metastatic Breast Cancer Patients Undergoing Front-Line Chemotherapy.

BACKGROUND: Loco-regional therapy (LRT) in de novo metastatic breast cancer (MBC) has been investigated in several clinical trials, with heterogeneous and conflicting results. METHODS: We conducted a retrospective study of de novo MBC patients treated with front-line chemotherapy (FLC) followed by LRT of the primary tumor. Our aims were to evaluate the characteristics, treatment, and oncological outcomes in terms of progression-free survival (PFS), distant progression-free survival (DPFS), and overall survival (OS) of de novo MBC. We also investigated possible subgroups of patients with better outcomes according to menopausal status, biological sub-type, location, number of metastases, and radiologic complete response after FLC. RESULTS: We included 61 patients in the study. After a median follow-up of 55 months, disease progression occurred in 60.7% of patients and 49.2% died. There were no significant differences in PFS, DPFS, and OS between different subgroups of de novo MBC patients. A trend toward better PFS and DPFS was observed in triple-positive tumors, without a statistically significant difference in OS. CONCLUSIONS: No specific subgroup of de novo MBC patients showed a statistically significant survival advantage after FLC followed by LRT of the primary tumor.