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.

Contrast-enhanced mammography for the assessment of screening recalls: a two-centre study.

OBJECTIVES: To evaluate the potential of contrast-enhanced mammography (CEM) for reducing the biopsy rate of screening recalls. METHODS: Recalled women were prospectively enrolled to undergo CEM alongside standard assessment (SA) through additional views, tomosynthesis, and/or ultrasound. Exclusion criteria were symptoms, implants, allergy to contrast agents, renal failure, and pregnancy. SA and CEM were independently evaluated by one of six radiologists, who recommended biopsy or 2-year follow-up. Biopsy rates according to SA or recombined CEM (rCEM) were compared with the McNemar's test. Diagnostic performance was calculated considering lesions with available final histopathology. RESULTS: Between January 2019 and July 2021, 220 women were enrolled, 207 of them (median age 56.6 years) with 225 suspicious findings analysed. Three of 207 patients (1.4%) developed mild self-limiting adverse reactions to iodinated contrast agent. Overall, 135/225 findings were referred for biopsy, 90/225 by both SA and rCEM, 41/225 by SA alone and 4/225 by rCEM alone (2/4 being one DCIS and one invasive carcinoma). The rCEM biopsy rate (94/225, 41.8%, 95% CI 35.5-48.3%) was 16.4% lower (p < 0.001) than the SA biopsy rate (131/225, 58.2%, 95% CI 51.7-64.5%). Considering the 124/135 biopsies with final histopathology (44 benign, 80 malignant), rCEM showed a 93.8% sensitivity (95% CI 86.2-97.3%) and a 65.9% specificity (95% CI 51.1-78.1%), all 5 false negatives being ductal carcinoma in situ detectable as suspicious calcifications on low-energy images. CONCLUSIONS: Compared to SA, the rCEM-based work-up would have avoided biopsy for 37/225 (16.4%) suspicious findings. Including low-energy images in interpretation provided optimal overall CEM sensitivity. KEY POINTS: • The work-up of suspicious findings detected at mammographic breast cancer screening still leads to a high rate of unnecessary biopsies, involving between 2 and 6% of screened women. • In 207 recalled women with 225 suspicious findings, recombined images of contrast-enhanced mammography (CEM) showed a 93.8% sensitivity and a 65.9% specificity, all 5 false negatives being ductal carcinoma in situ detectable on low-energy images as suspicious calcifications. • CEM could represent an easily available one-stop shop option for the morphofunctional assessment of screening recalls, potentially reducing the biopsy rate by 16.4%.

Semiquantitative score of breast arterial calcifications on mammography (BAC-SS): intra- and inter-reader reproducibility.

BACKGROUND: Breast arterial calcifications (BAC), representing Mönckeberg's sclerosis of the tunica media of breast arteries, are an imaging biomarker for cardiovascular risk stratification in the female population. Our aim was to estimate the intra- and inter-reader reproducibility of a semiquantitative score for BAC assessment (BAC-SS). METHODS: Consecutive women who underwent screening mammography at our center from January 1st to January 31st, 2018 were retrieved and included according to BAC presence. Two readers (R1 and R2) independently applied the BAC-SS to medio-lateral oblique views, obtaining a BAC score by summing: (I) number of calcified vessels (from 0 to n); (II) vessel opacification, i.e., the degree of artery coverage by calcium bright pixels (0 or 1); and (III) length class of calcified vessels (from 0 to 4). R1 repeated the assessment 2 weeks later. Scoring time was recorded. Cohen's κ statistics and Bland-Altman analysis were used. RESULTS: Among 408 women, 57 (14%) had BAC; 114 medio-lateral oblique views were assessed. Median BAC score was 4 [interquartile range (IQR): 3-6] for R1 and 4 (IQR: 2-6) for R2 (P=0.417) while median scoring time was 156 s (IQR: 99-314 s) for R1 and 191 s (IQR: 137-292 s) for R2 (P=0.743). Bland-Altman analysis showed a 77% intra-reader reproducibility [bias: 0.193, coefficient of repeatability (CoR): 0.955] and a 64% inter-reader reproducibility (bias: 0.211, CoR: 1.516). Cohen's κ for BAC presence was 0.968 for intra-reader agreement and 0.937 for inter-reader agreement. CONCLUSIONS: Our BAC-SS has a good intra- and inter-reader reproducibility, within acceptable scoring times. A large-scale study is warranted to test its ability to stratify cardiovascular risk in women.

MRI-Derived Tumour-to-Breast Volume Is Associated with the Extent of Breast Surgery.

The tumour-to-breast volume ratio (TBVR) is a metric that may help surgical decision making. In this retrospective Ethics-Committee-approved study, we assessed the correlation between magnetic resonance imaging (MRI)-derived TBVR and the performed surgery. The TBVR was obtained using a fully manual method for the segmentation of the tumour volume (TV) and a growing region semiautomatic method for the segmentation of the whole breast volume (WBV). Two specifically-trained residents (R1 and R2) independently segmented T1-weighted datasets of 51 cancer cases in 51 patients (median age 57 years). The intraobserver and interobserver TBVR reproducibility were calculated. Mann-Whitney U, Spearman correlations, and Bland-Altman statistics were used. Breast-conserving surgery (BCS) was performed in 31/51 cases (61%); mastectomy was performed in 20/51 cases (39%). The median TBVR was 2.08‰ (interquartile range 0.70-9.13‰) for Reader 1, and 2.28‰ (interquartile range 0.71-9.61‰) for Reader 2, with an 84% inter-reader reproducibility. The median segmentation times were 54 s for the WBV and 141 s for the TV. Significantly-lower TBVR values were observed in the breast-conserving surgery group (median 1.14‰, interquartile range 0.49-2.55‰) than in the mastectomy group (median 10.52‰, interquartile range 2.42-14.73‰) for both readers (p < 0.001). Large scale prospective studies are needed in order to validate MRI-derived TBVR as a predictor of the type of breast surgery.

Accuracy and inter-reader agreement of breast MRI for cancer staging using 0.08 mmol/kg of gadobutrol.

BACKGROUND: Evidence on gadolinium brain accumulation after contrast-enhanced MRI prompted research in dose reduction. PURPOSE: To estimate accuracy and inter-reader reproducibility of tumor size measurement in breast MRI using 0.08 mmol/kg of gadobutrol. METHODS: We retrospectively analyzed all women who underwent 1.5-T breast MRI for cancer staging at our department with 0.08 mmol/kg of gadobutrol. Two readers (R1 and R2, 12 and 3 years-experience) measured the largest lesion diameter. Accuracy was estimated both as correlation with pathology and rate of absolute (>5 mm) overestimation and underestimation, inter-reader reproducibility using the Bland-Altman method. Data are given as median and interquartile range. RESULTS: Thirty-six patients were analyzed (median age 56 years, 49-66) for a total of 38 lesions, 24 (63%) mass enhancement, 14 (37%) non-mass enhancement. Histopathological median size (mm) of all lesions was 15 (9-25): 13 (9-19) for mass lesions, 19 (11-39) for non-mass lesions. On MRI, R1 measured (mm) 14 (10-22) for all lesions, 13 (10-19) for mass lesions, 19 (11-49) for non-mass lesions. MRI-pathology correlation was very high for all lesion categories (ρ ≥ 0.766). On MRI, R1 overestimated lesion size in 6 cases (16%), and underestimated in 3 (8%); R2, overestimated 7 cases (18%) and underestimated 3 cases (8%). At inter-reader reproducibility analysis (mm): bias 0.9, coefficient of reproducibility 13 for all lesions; -0.1 and 6 for mass lesions; 2.5 and 20 for non-mass lesions. CONCLUSIONS: Breast MRI may be performed using 0.08 mmol/kg of gadobutrol with high accuracy and acceptable inter-reader agreement.

Waxy casts in the urinary sediment of patients with different types of glomerular diseases: results of a prospective study.

BACKGROUND: Casts are well known components of the urinary sediment. For most casts, the clinical associations are known and demonstrated, while for waxy casts they are totally unknown. METHODS: Prospective study for the search and count of waxy casts in the urinary sediment of patients with different types of glomerular diseases. RESULTS: Waxy casts were found in 39 out of 287 patients (13.6%), mostly in low number (1 to 9 out of 100 casts evaluated/sample). They were frequent in postinfectious glomerulonephritis and renal amyloidosis (5/9 patients, 44.5%, p=0.02 for each condition), while they were rare in membranous nephropathy (4/67 patients, 6.0%, 0.04) and absent in focal segmental glomerulosclerosis (0/23 patients, p=0.05). Waxy casts were associated significantly with higher serum creatinine levels (p<0.0001), with the presence of >1 leukocyte/HPF, granular casts and leukocytic casts (p=0.001 to 0.008) and with higher numbers of erythrocytes, leukocytes, renal tubular epithelial cells, granular casts, epithelial casts, and leukocytic casts (p<0.0001 to=0.03). CONCLUSIONS: Waxy casts are uncommon and few in patients with glomerular diseases and are associated with impaired renal function and with several other structures of the urinary sediment.