To evaluate the diagnostic performance of radiomic signatures extracted from contrast-enhanced magnetic resonance imaging (CE-MRI) for the assessment of breast cancer receptor status and molecular ...subtypes.
One hundred and forty-three patients with biopsy-proven breast cancer who underwent CE-MRI at 3 T were included in this IRB-approved HIPAA-compliant retrospective study. The training dataset comprised 91 patients (luminal A, n = 49; luminal B, n = 8; HER2-enriched, n = 11; triple negative, n = 23), while the validation dataset comprised 52 patients from a second institution (luminal A, n = 17; luminal B, n = 17; triple negative, n = 18). Radiomic analysis of manually segmented tumors included calculation of features derived from the first-order histogram (HIS), co-occurrence matrix (COM), run-length matrix (RLM), absolute gradient (GRA), autoregressive model (ARM), discrete Haar wavelet transform (WAV), and lesion geometry (GEO). Fisher, probability of error and average correlation (POE + ACC), and mutual information coefficients were used for feature selection. Linear discriminant analysis followed by k-nearest neighbor classification (with leave-one-out cross-validation) was used for pairwise radiomic-based separation of receptor status and molecular subtypes. Histopathology served as the standard of reference.
In the training dataset, radiomic signatures yielded the following accuracies > 80%: luminal B vs. luminal A, 84.2% (mainly based on COM features); luminal B vs. triple negative, 83.9% (mainly based on GEO features); luminal B vs. all others, 89% (mainly based on COM features); and HER2-enriched vs. all others, 81.3% (mainly based on COM features). Radiomic signatures were successfully validated in the separate validation dataset for luminal A vs. luminal B (79.4%) and luminal B vs. triple negative (77.1%).
In this preliminary study, radiomic signatures with CE-MRI enable the assessment of breast cancer receptor status and molecular subtypes with high diagnostic accuracy. These results need to be confirmed in future larger studies.
Full-field digital mammography (FFDM), the standard of care for breast cancer screening, has some limitations. With the advent of digital breast tomosynthesis (DBT), improvements including decreased ...recall rates and increased cancer detection rates have been observed. The quasi-three-dimensional capability of DBT reduces breast tissue overlap, a significant limitation of FFDM. However, early studies demonstrate that a few cancers detected at FFDM may not be diagnosed at DBT-only screening, and lesions with calcifications as the dominant feature may look less suspicious at DBT or not be visible at all. These findings support the use of combined FFDM and DBT protocols to optimize screening performance. However, this combination would approximately double the patient's radiation exposure. The development of computer algorithms that generate two-dimensional synthesized mammography (SM) views from DBT has improved calcification conspicuity and sensitivity. Therefore, SM may substitute for FFDM in screening protocols, reducing radiation exposure. DBT plus SM demonstrates significantly better performance than that of FFDM alone, although there are reports of missed malignant calcifications. Thus, some centers continue to perform FFDM with DBT. Use of DBT in breast imaging has also necessitated the development of DBT-guided biopsy. DBT-guided biopsy may have a higher success rate than that of stereotactic biopsy, with a shorter procedure time. While DBT brings substantial improvements to breast cancer imaging, it is important to be aware of its strengths and limitations regarding detection of calcifications. This article reviews the imaging appearance of breast calcifications at DBT, discusses calcification biopsy techniques, and provides an overview of the current literature. Online supplemental material is available for this article.
RSNA, 2019 An earlier incorrect version of this article appeared online. This article was corrected on February 13, 2019.
Objectives
To assess the frequency of ipsilateral axillary adenopathy on breast MRI after COVID-19 vaccination. To investigate the duration, outcomes, and associated variables of vaccine-related ...adenopathy.
Methods
In this retrospective cohort study, our database was queried for patients who underwent breast MRI following COVID-19 vaccination from January 22, 2021, to March 21, 2021. The frequency of ipsilateral axillary adenopathy and possible associated variables were evaluated, including age, personal history of ipsilateral breast cancer, clinical indication for breast MRI, type of vaccine, side of vaccination, number of doses, and number of days between the vaccine and the MRI exam. The outcomes of the adenopathy were investigated, including the duration of adenopathy and biopsy results.
Results
A total of 357 patients were included. The frequency of adenopathy on breast MRI was 29% (104/357 patients). Younger patients and shorter time intervals from the second dose of the vaccine were significantly associated with the development of adenopathy (
p
= 0.002 for both). Most adenopathy resolved or decreased on follow-up, with 11% of patients presenting persistence of adenopathy up to 64 days after the second dose of the vaccine. Metastatic axillary carcinoma was diagnosed in three patients; all three had a current ipsilateral breast cancer diagnosis.
Conclusions
Vaccine-related adenopathy is a frequent event after COVID-19 vaccination; short-term follow-up is an appropriate clinical approach, except in patients with current ipsilateral breast cancer. Adenopathy may often persist 4–8 weeks after the second dose of the vaccine, thus favoring longer follow-up periods.
Key Points
• MRI-detected ipsilateral axillary adenopathy is a frequent benign finding after mRNA COVID-19 vaccination.
• Axillary adenopathy following COVID-19 vaccination often persists > 4 weeks after vaccination, favoring longer follow-up periods.
• In patients with concurrent ipsilateral breast cancer, axillary adenopathy can represent metastatic carcinoma and follow-up is not appropriate.
Vaccine-related lymphadenopathy is a frequent finding following initial coronavirus disease 2019 (COVID-19) vaccination, but the frequency after COVID-19 booster vaccination is still unknown. In this ...study we compare axillary lymph node morphology on breast MRI before and after COVID-19 booster vaccination.
This retrospective, single-center, IRB-approved study included patients who underwent breast MRI between October 2021 and December 2021 after the COVID-19 booster vaccination. The axillary lymph node with the greatest cortical thickness ipsilateral to the side of vaccination was measured on MRI after booster vaccination and before initial COVID-19 vaccination. Comparisons were made between patients with and without increase in cortical thickness of ≥ 0.2 cm. Continuous covariates were compared using Wilcoxon rank-sum test and categorical covariates were compared using Fisher's exact test. Multiple comparison adjustment was made using the Benjamini-Hochberg procedure.
All 128 patients were included. Twenty-four of 128 (19%) displayed an increase in lymph node cortical thickness of ≥ 0.2 cm. Patients who received the booster more recently were more likely to present cortical thickening, with a median of 9 days (IQR 5, 20) vs. 36 days (IQR 18, 59) (p < 0.001). Age (p = 0.5) and type of vaccine (p = 0.7) were not associated with thickening. No ipsilateral breast cancer or malignant lymphadenopathy were diagnosed on follow-up.
Axillary lymphadenopathy on breast MRI following COVID-19 booster vaccination is a frequent finding, especially in the first 3 weeks after vaccination. Additional evaluation or follow-up may be omitted in patients with low concern for malignancy.
Purpose
To compare annotation segmentation approaches and to assess the value of radiomics analysis applied to diffusion-weighted imaging (DWI) for evaluation of breast cancer receptor status and ...molecular subtyping.
Procedures
In this IRB-approved HIPAA-compliant retrospective study, 91 patients with treatment-naïve breast malignancies proven by image-guided breast biopsy, (luminal A,
n
= 49; luminal B,
n
= 8; human epidermal growth factor receptor 2 HER2-enriched,
n
= 11; triple negative TN,
n
= 23) underwent multiparametric magnetic resonance imaging (MRI) of the breast at 3 T with dynamic contrast-enhanced MRI, T2-weighted and DW imaging. Lesions were manually segmented on high b-value DW images and segmentation ROIS were propagated to apparent diffusion coefficient (ADC) maps. In addition in a subgroup (
n
= 79) where lesions were discernable on ADC maps alone, these were also directly segmented there. To derive radiomics signatures, the following features were extracted and analyzed: first-order histogram (HIS), co-occurrence matrix (COM), run-length matrix (RLM), absolute gradient, autoregressive model (ARM), discrete Haar wavelet transform (WAV), and lesion geometry. Fisher, probability of error and average correlation, and mutual information coefficients were used for feature selection. Linear discriminant analysis followed by k-nearest neighbor classification with leave-one-out cross-validation was applied for pairwise differentiation of receptor status and molecular subtyping. Histopathologic results were considered the gold standard.
Results
For lesion that were segmented on DWI and segmentation ROIs were propagated to ADC maps the following classification accuracies > 90% were obtained: luminal B
vs.
HER2-enriched, 94.7 % (based on COM features); luminal B
vs.
others, 92.3 % (COM, HIS); and HER2-enriched
vs.
others, 90.1 % (RLM, COM). For lesions that were segmented directly on ADC maps, better results were achieved yielding the following classification accuracies: luminal B
vs.
HER2-enriched, 100 % (COM, WAV); luminal A
vs.
luminal B, 91.5 % (COM, WAV); and luminal B
vs.
others, 91.1 % (WAV, ARM, COM).
Conclusions
Radiomic signatures from DWI with ADC mapping allows evaluation of breast cancer receptor status and molecular subtyping with high diagnostic accuracy. Better classification accuracies were obtained when breast tumor segmentations could be performed on ADC maps.
•Distinction of charge storage mechanisms at carbon electrodes in redox electrolyte.•Electrochemical impedance applied in distinguishing charge storage mechanisms.•Essential role of capacitive ...impedance changes predicted by impedance modelling.•Significant capacitive impedance changes verified experimentally.
Different charge storage mechanisms at some carbon electrodes in redox active electrolyte are distinguished by electrochemical impedance spectroscopy technique. Significance of monitoring capacitive impedance contribution(s) in distinguishing battery-like and pseudocapacitive charge storage mechanisms is predicted by impedance modelling and verified experimentally. Experimental verification is made by comparison of capacitive impedance contributions in impedance spectra of graphite vs. glassy carbon electrodes. Impedance measurements are made at the same potential values in the supporting H2SO4 electrolyte and H2SO4/K4Fe(CN)6 redox active electrolyte, respectively.
Activities of hydrogen evolution reaction, HER, on two differently modified metal-free GC electrodes and on the same electrodes supplied with ruthenium catalyst, have been studied in H2SO4 ...electrolyte solution. GC electrodes were gradually modified by electrochemical oxidation/reduction procedure, changing morphology properties and forming spatially heterogeneous surfaces. Ruthenium was deposited on the top of two differently modified GC electrodes in nearly the same specific mass of ∼25μgcm−2 of active ruthenium, showing almost uniform dispersion of ruthenium particle clusters on less modified electrode and pronounced agglomeration on more modified electrode surface. Results of cyclic voltammetry and polarization experiments, aiding mostly in adjustments of the specific masses of active ruthenium on two GC electrodes and characteristic potential regions of “double-layer” vs. HER responses, were found strongly correlated with electrochemical impedance data. Evaluations of impedance data were done using standard regression procedure based on strictly postulated statistical criteria, in conditions of complex interfacial impedance/frequency functions accounting for: a) spatial surface heterogeneity, b) diffusion controlled hydrogen absorption and c) hydrogen evolution involving hydrogen adsorption. Activities for HER on bare GC electrodes were found much lower than on the corresponding Ru/GC electrodes, but increased with stage of surface modification. At Ru/GC electrodes, HER is proceeding exclusively on ruthenium particles with activity related to the mass of active ruthenium and total ruthenium utilization of ∼25%. Not any effect of the supporting GC electrode morphology has been observed for HER on Ru/GC electrodes.
The aim of this study was to determine the range of apparent diffusion coefficient (ADC) values for benign axillary lymph nodes in contrast to malignant axillary lymph nodes, and to define the ...optimal ADC thresholds for three different ADC parameters (minimum, maximum, and mean ADC) in differentiating between benign and malignant lymph nodes. This retrospective study included consecutive patients who underwent breast MRI from January 2017-December 2020. Two-year follow-up breast imaging or histopathology served as the reference standard for axillary lymph node status. Area under the receiver operating characteristic curve (AUC) values for minimum, maximum, and mean ADC (min ADC, max ADC, and mean ADC) for benign
malignant axillary lymph nodes were determined using the Wilcoxon rank sum test, and optimal ADC thresholds were determined using Youden's Index. The final study sample consisted of 217 patients (100% female, median age of 52 years (range, 22-81), 110 with benign axillary lymph nodes and 107 with malignant axillary lymph nodes. For benign axillary lymph nodes, ADC values (×10
mm
/s) ranged from 0.522-2.712 for mean ADC, 0.774-3.382 for max ADC, and 0.071-2.409 for min ADC; for malignant axillary lymph nodes, ADC values (×10
mm
/s) ranged from 0.796-1.080 for mean ADC, 1.168-1.592 for max ADC, and 0.351-0.688 for min ADC for malignant axillary lymph nodes. While there was a statistically difference in all ADC parameters (p<0.001) between benign and malignant axillary lymph nodes, boxplots illustrate overlaps in ADC values, with the least overlap occurring with mean ADC, suggesting that this is the most useful ADC parameter for differentiating between benign and malignant axillary lymph nodes. The mean ADC threshold that resulted in the highest diagnostic accuracy for differentiating between benign and malignant lymph nodes was 1.004×10
mm
/s, yielding an accuracy of 75%, sensitivity of 71%, specificity of 79%, positive predictive value of 77%, and negative predictive value of 74%. This mean ADC threshold is lower than the European Society of Breast Imaging (EUSOBI) mean ADC threshold of 1.300×10
mm
/s, therefore suggesting that the EUSOBI threshold which was recently recommended for breast tumors should not be extrapolated to evaluate the axillary lymph nodes.
High-Risk Lesion Management Horvat, Joao V.
Seminars in ultrasound, CT, and MRI,
February 2023, 2023-Feb, 2023-02-00, 20230201, Letnik:
44, Številka:
1
Journal Article
Recenzirano
High-risk lesions or lesions of uncertain malignant potential are frequent findings on image-guided needle biopsy of the breast and comprise a number of distinct entities. These lesions are known for ...having risk of underlying malignancy and are usually associated with an increased lifetime risk for breast cancer. Surgical excision was traditionally recommended for all high-risk lesions but recent studies have demonstrated that vacuum-assisted excision or surveillance may be adequate for some lesions. While management of high-risk lesion varies among institutions, this chapter describes the management recommendations based on recent literature of the most frequent types of lesions.
The purpose of this study was to investigate whether ultra-high-field dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast at 7T using quantitative pharmacokinetic (PK) ...analysis can differentiate between benign and malignant breast tumors for improved breast cancer diagnosis and to predict molecular subtypes, histologic grade, and proliferation rate in breast cancer. In this prospective study, 37 patients with 43 lesions suspicious on mammography or ultrasound underwent bilateral DCE-MRI of the breast at 7T. PK parameters (K
, k
, V
) were evaluated with two region of interest (ROI) approaches (2D whole-tumor ROI or 2D 10 mm standardized ROI) manually drawn by two readers (senior reader, R1, and R2) independently. Histopathology served as the reference standard. PK parameters differentiated benign and malignant lesions (n = 16, 27, respectively) with good accuracy (AUCs = 0.655-0.762). The addition of quantitative PK analysis to subjective BI-RADS classification improved breast cancer detection from 88.4% to 97.7% for R1 and 86.04% to 97.67% for R2. Different ROI approaches did not influence diagnostic accuracy for both readers. Except for K
for whole-tumor ROI for R2, none of the PK parameters were valuable to predict molecular subtypes, histologic grade, or proliferation rate in breast cancer. In conclusion, PK-enhanced BI-RADS is promising for the noninvasive differentiation of benign and malignant breast tumors.
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