Retrospective Cohort Study of Practical Applications of Paramagnetic Seed Localisation in Breast Carcinoma and Other Malignancies.

(1) Background: Paramagnetic seeds are a safe alternative for the wire-guided localisation of non-palpable breast lesions, but can also be applied for non-breast lesions. This study presents the experience with a paramagnetic seed, MagSeed® (Endomagnetics Ltd., Cambridge, UK, CE-registered and FDA-cleared), in an academic and non-academic breast centre. (2) Methods: Multicentre, retrospective analysis of 374 consecutive patients who underwent surgery after paramagnetic seed localisation (MSL) between 2018 and 2020. Indications for localisation included non-palpable breast lesions (n = 356), lymph nodes (n = 15) or soft tissue lesions (n = 3). The primary outcome was feasibility and the rate of positive section margins. The secondary outcome was predictive factors for positive section margins. (3) Results: The accurate excision of high-risk breast lesions, lymph nodes and soft tissue lesions was seen in 91.07% (n = 56). Positive section margins were observed in 7.86% (n = 25) after breast conserving surgery for invasive or ductal carcinoma in situ (DCIS) (n = 318). Invasive breast cancer associated with DCIS (p = 0.043) and the size of DCIS (p < 0.001) were significantly correlated with the positive section margins. (4) Conclusion: This study confirms the feasibility of MSL, as well as the higher risk for positive margins in cases of breast carcinoma with associated DCIS. Soft tissue lesions and lymph nodes associated with other malignancies, e.g., melanoma, can also be localised with paramagnetic seeds. This offers perspectives for future applications, such as the de-escalation of axillary treatment in breast cancer.

Cancer Surveillance in Healthy Carriers of Germline Pathogenic Variants in BRCA1/2: A Review of Secondary Prevention Guidelines.

Germline pathogenic alterations in the breast cancer susceptibility genes 1 (BRCA1) and 2 (BRCA2) are the most prevalent causes of hereditary breast and ovarian cancer. The increasing trend in proportion of cancer patients undergoing genetic testing, followed by predictive testing in families of new index patients, results in a significant increase of healthy germline BRCA1/2 mutation carriers who are at increased risk for breast, ovarian, and other BRCA-related cancers. This review aims to give an overview of available screening guidelines for female and male carriers of pathogenic or likely pathogenic germline BRCA1/2 variants per cancer type, incorporating malignancies that are more or less recently well correlated with BRCA1/2. We selected guidelines from national/international organizations and/or professional associations that were published or updated between January 1, 2015, and February 1, 2020. In total, 12 guidelines were included. This review reveals several significant discordances between the different guidelines. Optimal surveillance strategies depend on accurate age-specific cancer risk estimates, which are not reliably available for all BRCA-related cancers. Up-to-date national or international consensus guidelines are of utmost importance to harmonize counseling and proposed surveillance strategies for BRCA1/2 carriers.

Correlation of free-response and receiver-operating-characteristic area-under-the-curve estimates: results from independently conducted FROC∕ROC studies in mammography.

PURPOSE: From independently conducted free-response receiver operating characteristic (FROC) and receiver operating characteristic (ROC) experiments, to study fixed-reader associations between three estimators: the area under the alternative FROC (AFROC) curve computed from FROC data, the area under the ROC curve computed from FROC highest rating data, and the area under the ROC curve computed from confidence-of-disease ratings. METHODS: Two hundred mammograms, 100 of which were abnormal, were processed by two image-processing algorithms and interpreted by four radiologists under the FROC paradigm. From the FROC data, inferred-ROC data were derived, using the highest rating assumption. Eighteen months afterwards, the images were interpreted by the same radiologists under the conventional ROC paradigm; conventional-ROC data (in contrast to inferred-ROC data) were obtained. FROC and ROC (inferred, conventional) data were analyzed using the nonparametric area-under-the-curve (AUC), (AFROC and ROC curve, respectively). Pearson correlation was used to quantify the degree of association between the modality-specific AUC indices and standard errors were computed using the bootstrap-after-bootstrap method. The magnitude of the correlations was assessed by comparison with computed Obuchowski-Rockette fixed reader correlations. RESULTS: Average Pearson correlations (with 95% confidence intervals in square brackets) were: Corr(FROC, inferred ROC) = 0.76[0.64, 0.84] > Corr(inferred ROC, conventional ROC) = 0.40[0.18, 0.58] > Corr (FROC, conventional ROC) = 0.32[0.16, 0.46]. CONCLUSIONS: Correlation between FROC and inferred-ROC data AUC estimates was high. Correlation between inferred- and conventional-ROC AUC was similar to the correlation between two modalities for a single reader using one estimation method, suggesting that the highest rating assumption might be questionable.

Evaluation of clinical image processing algorithms used in digital mammography.

Screening is the only proven approach to reduce the mortality of breast cancer, but significant numbers of breast cancers remain undetected even when all quality assurance guidelines are implemented. With the increasing adoption of digital mammography systems, image processing may be a key factor in the imaging chain. Although to our knowledge statistically significant effects of manufacturer-recommended image processings have not been previously demonstrated, the subjective experience of our radiologists, that the apparent image quality can vary considerably between different algorithms, motivated this study. This article addresses the impact of five such algorithms on the detection of clusters of microcalcifications. A database of unprocessed (raw) images of 200 normal digital mammograms, acquired with the Siemens Novation DR, was collected retrospectively. Realistic simulated microcalcification clusters were inserted in half of the unprocessed images. All unprocessed images were subsequently processed with five manufacturer-recommended image processing algorithms (Agfa Musica 1, IMS Raffaello Mammo 1.2, Sectra Mamea AB Sigmoid, Siemens OPVIEW v2, and Siemens OPVIEW v1). Four breast imaging radiologists were asked to locate and score the clusters in each image on a five point rating scale. The free-response data were analyzed by the jackknife free-response receiver operating characteristic (JAFROC) method and, for comparison, also with the receiver operating characteristic (ROC) method. JAFROC analysis revealed highly significant differences between the image processings (F = 8.51, p < 0.0001), suggesting that image processing strongly impacts the detectability of clusters. Siemens OPVIEW2 and Siemens OPVIEW1 yielded the highest and lowest performances, respectively. ROC analysis of the data also revealed significant differences between the processing but at lower significance (F = 3.47, p = 0.0305) than JAFROC. Both statistical analysis methods revealed that the same six pairs of modalities were significantly different, but the JAFROC confidence intervals were about 32% smaller than ROC confidence intervals. This study shows that image processing has a significant impact on the detection of microcalcifications in digital mammograms. Objective measurements, such as described here, should be used by the manufacturers to select the optimal image processing algorithm.