MR imaging of the breast for the detection, diagnosis, and staging of breast cancer

The p53/miRNA Axis in Breast Cancer

One of the main health issues in the modern world is cancer, with breast cancer (BC) as one of the most common types of malignancies. Different environmental and genetic risk factors are involved in the development of BC. One of the primary genes implicated in cancer development is the p53 gene, which is also known as the "gatekeeper" gene. p53 is involved in cancer development by interacting with numerous pathways and signaling factors, including microRNAs (miRNAs). miRNAs are small noncoding RNA molecules that regulate gene expression by binding to the 3' untranslated region of target mRNAs, resulting in their translational inhibition or degradation. If the p53 gene is mutated or degraded, it can contribute to the risk of BC by disrupting the expression of miRNAs. Similarly, the disruption of miRNAs causes the negative regulation of p53. Therefore, the p53/miRNA axis is a crucial pathway in the progression or prevention of BC, and understanding the regulation and function of this pathway may contribute to the development of new therapeutic strategies to help treat BC.

The Utility of Second-Look US to Evaluate Abnormal Molecular Breast Imaging Findings: A Retrospective Study

OBJECTIVE

The purpose of this study was to evaluate the utility of US for identifying and characterizing lesions detected on molecular breast imaging (MBI).

METHODS

A retrospective single-institution review was performed of patients with MBI studies with subsequent US for abnormal MBI findings between January 1, 2015, and September 30, 2021. Medical records, imaging, and histopathology were reviewed. The reference standard was histopathology and/or imaging follow-up. Associations among MBI findings, the presence of an US correlate, and histopathology were evaluated by Fisher exact tests.

RESULTS

The 32 lesions detected on MBI in 25 patients were evaluated by US, and 19 lesions had an US correlate (19/32, 59%). Mass uptake was more likely to have an US correlate (11/13, 85%; P = .02) than nonmass uptake (7/19, 37%), and mass uptake was more likely to be malignant (5/13, 38%; P = .01). Of the 13 lesions without an US correlate, 5 were evaluated and subsequently biopsied by MRI (2 high-risk lesions and 3 benign lesions). Follow-up MBIs demonstrated stability/resolution for 5 lesions in 4 patients at 6 months or longer. Three patients had no further imaging.

CONCLUSION

Mass lesions identified on MBI were more likely to have an US correlate and were more likely to be malignant than nonmass lesions.

Abbreviated Breast MRI as a Supplement to Mammography in Family Risk History of Breast Cancer within the Croatian National Breast Screening Program

OBJECTIVE

To evaluate the diagnostic performance of abbreviated breast MRI compared with mammography in women with a family history of breast cancer included in the Croatian National Breast Screening Program.

METHODS

178 women with a family history of breast cancer aged 50 to 69 underwent abbreviated breast MRI and mammography. Radiological findings for each method were categorized according to the BI-RADS classification. The gold standard for assessing the diagnostic accuracy of breast MRI and mammography, in terms of suspicious BI-RADS 4 and BI-RADS 5 findings, was the histopathological diagnosis. Performance measures, including cancer detection rates, specificity, sensitivity, and positive and negative predictive values, were calculated for both imaging methods.

RESULTS

Twelve new cases of breast cancer were detected, with seven (58.3%) identified only by abbreviated breast MRI, four (33.3%) detected by both mammography and breast MRI, and one (8.3%) diagnosed only by mammography. Diagnostic accuracy parameters for abbreviated breast MRI were 91.67% sensitivity, 94.58% specificity, 55.0% positive predictive value (PPV), and 99.37% negative predictive value (NPV), while for mammography, the corresponding values were 41.67%, 96.39%, 45.46%, and 95.81%, respectively.

CONCLUSIONS

Abbreviated breast MRI is a useful supplement to screening mammography in women with a family history of breast cancer. Considering the results of the conducted research, it is recommended to assess whether women with a family history of breast cancer have an increased risk and subsequently provide annual abbreviated breast MRI in addition to mammography for early detection of breast cancer.

Breast imaging with an ultra-low field MRI scanner: a pilot study

Breast cancer screening is necessary to reduce mortality due to undetected breast cancer. Current methods have limitations, and as a result many women forego regular screening. Magnetic resonance imaging (MRI) can overcome most of these limitations, but access to conventional MRI is not widely available for routine annual screening. Here, we used an MRI scanner operating at ultra-low field (ULF) to image the left breasts of 11 women (mean age, 35 years ±13 years) in the prone position. Three breast radiologists reviewed the imaging and were able to discern the breast outline and distinguish fibroglandular tissue (FGT) from intramammary adipose tissue. Additionally, the expert readers agreed on their assessment of the breast tissue pattern including fatty, scattered FGT, heterogeneous FGT, and extreme FGT. This preliminary work demonstrates that ULF breast MRI is feasible and may be a potential option for comfortable, widely deployable, and low-cost breast cancer diagnosis and screening.

Radiologic-Pathologic Correlation of Nonmass Enhancement Contiguous with Malignant Index Breast Cancer Masses at Preoperative Breast MRI

Purpose To determine the pathologic features of nonmass enhancement (NME) directly adjacent to biopsy-proven malignant masses (index masses) at preoperative MRI and determine imaging characteristics that are associated with a malignant pathologic condition. Materials and Methods This retrospective study involved the review of breast MRI and mammography examinations performed for evaluating disease extent in patients newly diagnosed with breast cancer from July 1, 2016, to September 30, 2019. Inclusion criteria were limited to patients with an index mass and the presence of NME extending directly from the mass margins. Wilcoxon rank sum test, Fisher exact test, and χ2 test were used to analyze cancer, patient, and imaging characteristics associated with the NME diagnosis. Results Fifty-eight patients (mean age, 58 years ± 12 [SD]; all women) were included. Malignant pathologic findings for mass-associated NME occurred in 64% (37 of 58) of patients, 43% (16 of 37) with ductal carcinoma in situ and 57% (21 of 37) with invasive carcinoma. NME was more likely to be malignant when associated with an index cancer that had a low Ki-67 index (<20%) (P = .04). The presence of calcifications at mammography correlating with mass-associated NME was not significantly associated with malignant pathologic conditions (P = .19). The span of suspicious enhancement measured at MRI overestimated the true span of disease at histologic evaluation (P < .001), while there was no evidence of a difference between span of calcifications at mammography and true span of disease at histologic evaluation (P = .27). Conclusion Mass-associated NME at preoperative MRI was malignant in most patients with newly diagnosed breast cancer. The span of suspicious enhancement measured at MRI overestimated the true span of disease found at histologic evaluation. Keywords: Breast, Mammography © RSNA, 2024 See also the commentary by Newell in this issue.

The Role of Contrast-Enhanced Mammography After Cryoablation of Breast Cancer

Image-guided cryoablation is an emerging therapeutic technique for the treatment of breast cancer and is a treatment strategy that is an effective alternate to surgery in select patients. Tumor features impacting the efficacy of cryoablation include size, location in relation to skin, and histology (e.g., extent of intraductal component), underscoring the importance of imaging for staging and workup in this patient population. Contrast-enhanced mammography (CEM) utilization is increasing in both the screening and diagnostic settings and may be useful for follow-up imaging after breast cancer cryoablation, given its high sensitivity for cancer detection and its advantages in terms of PPV, time, cost, eligibility, and accessibility compared with contrast-enhanced MRI. This Clinical Perspective describes the novel use of CEM after breast cancer cryoablation, highlighting the advantages and disadvantages of CEM compared with alternate imaging modalities, expected benign postablation CEM findings, and CEM findings suggestive of residual or recurrent tumor.

Breast intervention device for low-field MRI with a customized unilateral coil

With the incidence of breast cancer rising to the top among female malignant tumors, magnetic resonance images guided breast biopsy intervention and minimally invasive treatment have developed as a clinically practical research issue. High field studies have shown the diagnostic value of breast MRI, but the examination costs greatly exceed those of competing conventional mammography. In this case, low-field MRI cannot merely provide typical MRI contrast, but also significantly reduce the cost of diagnosis and treatment for breast cancer patients. This work describes a unilateral breast coil and prototype intervention device, which provides a customized solution for low-field MRI-guided breast intervention. Results demonstrate that the low-field MRI breast intervention device facilitates medical intervention procedures. And the designed positioning device can locate the target lesion within 2-3 mm accuracy. Phantom tests with the customized unilateral coil indicate that the open loops perform as well as the 4-channel commercial closed breast coil, presenting a relatively good SNR (signal-to-noise ratio) and uniformity characteristics. MR scanning images of the volunteer breast using the breast intervention coil also show high SNR, which lays a foundation for further implementation of image-guided breast interventional minimally invasive surgery with the low-field MRI system.

Utility of positron emission tomography for determination of axillary metastasis of breast cancer

Objectives

The involvement of axillary lymph nodes plays a key role in breast cancer staging. Positron emission tomography is a promising modality for detecting axillary lymph node metastasis. In addition, nomograms are used to predict the status of axillary lymph nodes. In this study, the role of positron emission tomography in determining axillary metastasis and its correlation with the nomogram was evaluated.

Material and Methods

The axillary maximum standard uptake value (SUVmax) values of the patients in the preoperative period, the features in the perioperative and postoperative specimen and Memorial Sloan Kettering Cancer Center nomogram data were evaluated.

Results

As axillary SUVmax detected by Positron emission tomography in the preoperative period increased, so did the likelihood of lymph node involvement. Axillary SUVmax value were compared with Memorial Sloan Kettering Cancer Center nomogram data but no correlation was found. Age, lymph node number, histopathology results, mass diameter, presence or absence of lymphovascular invasion and/or perineural invasion, tumor type, estrogen receptor status, Ki67 and Cerb-B2 statuses were not correlated. However, axillary SUVmax was inversely correlated with grade and progesterone receptor status.

Conclusion

Results from positron emission tomography of axillary lymph nodes in breasts cancer patients showed that SUVmax was only inversely related to cancer grade and progesterone receptor status while not correlating with other accepted parameters for tumor assessment. Thus there is insufficient reliability for the use of axillary SUVmax alone for accurate assessment of tumor characteristics at present.

Fluoropolymer Nanoparticles Synthesized via Reversible-Deactivation Radical Polymerizations and Their Applications

Fluorinated polymeric nanoparticles (FPNPs) combine unique properties of fluorocarbon and polymeric nanoparticles, which has stimulated massive interest for decades. However, fluoropolymers are not readily available from nature, resulting in synthetic developments to obtain FPNPs via free radical polymerizations. Recently, while increasing cutting-edge directions demand tailored FPNPs, such materials have been difficult to access via conventional approaches. Reversible-deactivation radical polymerizations (RDRPs) are powerful methods to afford well-defined polymers. Researchers have applied RDRPs to the fabrication of FPNPs, enabling the construction of particles with improved complexity in terms of structure, composition, morphology, and functionality. Related examples can be classified into three categories. First, well-defined fluoropolymers synthesized via RDRPs have been utilized as precursors to form FPNPs through self-folding and solution self-assembly. Second, thermally and photoinitiated RDRPs have been explored to realize in situ preparations of FPNPs with varied morphologies via polymerization-induced self-assembly and cross-linking copolymerization. Third, grafting from inorganic nanoparticles has been investigated based on RDRPs. Importantly, those advancements have promoted studies toward promising applications, including magnetic resonance imaging, biomedical delivery, energy storage, adsorption of perfluorinated alkyl substances, photosensitizers, and so on. This Review should present useful knowledge to researchers in polymer science and nanomaterials and inspire innovative ideas for the synthesis and applications of FPNPs.

Radiomic Signatures Based on Mammography and Magnetic Resonance Imaging as New Markers for Estimation of Ki-67 and HER-2 Status in Breast Cancer

OBJECTIVE

The aim of the study is to investigate the values of intratumoral and peritumoral regions based on mammography and magnetic resonance imaging for the prediction of Ki-67 and human epidermal growth factor (HER-2) status in breast cancer (BC).

METHODS

Two hundred BC patients were consecutively enrolled between January 2017 and March 2021 and divided into training (n = 133) and validation (n = 67) groups. All the patients underwent breast mammography and magnetic resonance imaging screening. Features were derived from intratumoral and peritumoral regions of the tumor and selected using the least absolute shrinkage and selection operator regression to build radiomic signatures (RSs). Receiver operating characteristic curve analysis and the DeLong test were performed to assess and compare each RS.

RESULTS

For each modality, the combined RSs integrating features from intratumoral and peritumoral regions always showed better prediction performance for predicting Ki-67 and HER-2 status compared with the RSs derived from intratumoral or peritumoral regions separately. The multimodality and multiregional combined RSs achieved the best prediction performance for predicting the Ki-67 and HER-2 status with an area under the receiver operating characteristic curve of 0.888 and 0.868 in the training cohort and 0.800 and 0.848 in the validation cohort, respectively.

CONCLUSIONS

Peritumoral areas provide complementary information to intratumoral regions of BC. The developed multimodality and multiregional combined RSs have good potential for noninvasive evaluation of Ki-67 and HER-2 status in BC.

Review of microwave imaging algorithms for stroke detection

Microwave imaging is one of the rapidly developing frontier disciplines in the field of modern medical imaging. The development of microwave imaging algorithms for reconstructing stroke images is discussed in this paper. Compared with traditional stroke detection and diagnosis techniques, microwave imaging has the advantages of low price and no ionizing radiation hazards. The research hotspots of microwave imaging algorithms in the field of stroke are mainly reflected in the design and improvement of microwave tomography, radar imaging, and deep learning imaging. However, the current research lacks the analysis and combing of microwave imaging algorithms. In this paper, the development of common microwave imaging algorithms is reviewed. The concept, research status, current research hotspots and difficulties, and future development trends of microwave imaging algorithms are systematically expounded. The microwave antenna is used to collect scattered signals, and a series of microwave imaging algorithms are used to reconstruct the stroke image. The classification diagram and flow chart of the algorithms are shown in this Figure. (The classification diagram and flow chart are based on the microwave imaging algorithms.).

Prognostic Implication of Focal Breast Edema on Preoperative Breast Magnetic Resonance Imaging in Breast Cancer Patients

PURPOSE

In this study, we investigated the prognostic implications of focal breast edema on preoperative breast magnetic resonance imaging (MRI) in patients with breast cancer.

METHODS

Data of 899 patients with breast cancer at a single institution were retrospectively analyzed. The patients were divided into an edema-positive group (EPG) and an edema-negative group (ENG) based on the presence of peritumoral, prepectoral, or subcutaneous edema. Two radiologists evaluated the presence or absence of focal edema and its subtypes on preoperative breast MRI. Clinicopathologic characteristics and survival outcomes were compared between the two groups and among the three subtypes using Pearson's χ² test, Kaplan-Meier estimator, and Cox proportional hazards model.

RESULTS

There were 399 (44.4%) and 500 (55.6%) patients in the EPG and ENG, respectively. The EPG showed significantly higher rates of axillary lymph node metastasis (55.6% vs. 19.2%, p < 0.001) and lymphovascular invasion (LVI) (57.9% vs. 12.6%, p < 0.001) than the ENG. Patients in the EPG showed significantly worse overall survival (OS) rate (log-rank p < 0.001; hazard ratio [HR], 4.83; 95% confidence interval [CI], 2.56-9.11) and recurrence-free survival rate (log-rank p < 0.001; HR, 3.00; 95% CI, 1.94-4.63) than those in the ENG. After adjusting for other variables, focal breast edema remained a significant factor affecting the OS rate, regardless of the edema type. Specifically, the presence of subcutaneous edema emerged as the strongest predictor for OS with the highest HR (p < 0.001; HR, 9.10; 95% CI, 3.05-27.15).

CONCLUSION

Focal breast edema on preoperative breast MRI implies a higher possibility of LVI and axillary lymph node metastasis, which can lead to a poor prognosis. A detailed description of focal breast edema, especially subcutaneous edema, on preoperative breast MRI may provide prognostic predictions. More intensive surveillance is required for patients with breast cancer and focal preoperative breast edema.

Preoperative Breast Magnetic Resonance Imaging: An Ontario Health (Cancer Care Ontario) Clinical Practice Guideline

BACKGROUND

The use of preoperative breast magnetic resonance imaging (MRI) after the diagnosis of breast cancer by mammography and/or ultrasound is inconsistent.

METHODS

After conducting a systematic review and meta-analysis comparing preoperative breast MRI versus no MRI, we reconvened to prepare a clinical practice guideline on this topic.

RESULTS

Based on the evidence that MRI improved recurrence, decreased the rates of reoperations (re-excisions or conversion mastectomy), and increased detection of synchronous contralateral breast cancer, we recommend that preoperative breast MRI should be considered on a case-by-case basis in patients diagnosed with breast cancer for whom additional information about disease extent could influence treatment. Based on stronger evidence, preoperative breast MRI is recommended in patients diagnosed with invasive lobular carcinoma for whom additional information about disease extent could influence treatment. For both recommendations, the decision to proceed with MRI would be conditional on shared decision-making between care providers and the patient, taking into account the benefits and risks of MRI as well as patient preferences. Based on the opinion of the Working Group, preoperative breast MRI is also recommended in the following more specific situations: (a) to aid in surgical planning of breast conserving surgery in patients with suspected or known multicentric or multifocal disease; (b) to identify additional lesions in patients with dense breasts; (c) to determine the presence of pectoralis major muscle/chest wall invasion in patients with posteriorly located tumours or when invasion of the pectoralis major muscle or chest wall is suspected; (d) to aid in surgical planning for skin/nipple-sparing mastectomies, autologous reconstruction, oncoplastic surgery, and breast conserving surgery with suspected nipple/areolar involvement; and (e) in patients with familial/hereditary breast cancer but who have not had recent breast MRI as part of screening or diagnosis.

Image quality assessment using deep learning in high b-value diffusion-weighted breast MRI

The objective of this IRB approved retrospective study was to apply deep learning to identify magnetic resonance imaging (MRI) artifacts on maximum intensity projections (MIP) of the breast, which were derived from diffusion weighted imaging (DWI) protocols. The dataset consisted of 1309 clinically indicated breast MRI examinations of 1158 individuals (median age [IQR]: 50 years [16.75 years]) acquired between March 2017 and June 2020, in which a DWI sequence with a high b-value equal to 1500 s/mm2 was acquired. From these, 2D MIP images were computed and the left and right breast were cropped out as regions of interest (ROI). The presence of MRI image artifacts on the ROIs was rated by three independent observers. Artifact prevalence in the dataset was 37% (961 out of 2618 images). A DenseNet was trained with a fivefold cross-validation to identify artifacts on these images. In an independent holdout test dataset (n = 350 images) artifacts were detected by the neural network with an area under the precision-recall curve of 0.921 and a positive predictive value of 0.981. Our results show that a deep learning algorithm is capable to identify MRI artifacts in breast DWI-derived MIPs, which could help to improve quality assurance approaches for DWI sequences of breast examinations in the future.

Characterization of breast lesions using multi-parametric diffusion MRI and machine learning

Objective. To investigate quantitative imaging markers based on parameters from two diffusion-weighted imaging (DWI) models, continuous-time random-walk (CTRW) and intravoxel incoherent motion (IVIM) models, for characterizing malignant and benign breast lesions by using a machine learning algorithm.Approach. With IRB approval, 40 women with histologically confirmed breast lesions (16 benign, 24 malignant) underwent DWI with 11b-values (50 to 3000 s/mm2) at 3T. Three CTRW parameters,Dm,α, andβand three IVIM parametersDdiff,Dperf, andfwere estimated from the lesions. A histogram was generated and histogram features of skewness, variance, mean, median, interquartile range; and the value of the 10%, 25% and 75% quantiles were extracted for each parameter from the regions-of-interest. Iterative feature selection was performed using the Boruta algorithm that uses the Benjamin Hochberg False Discover Rate to first determine significant features and then to apply the Bonferroni correction to further control for false positives across multiple comparisons during the iterative procedure. Predictive performance of the significant features was evaluated using Support Vector Machine, Random Forest, Naïve Bayes, Gradient Boosted Classifier (GB), Decision Trees, AdaBoost and Gaussian Process machine learning classifiers.Main Results. The 75% quantile, and median ofDm; 75% quantile off;mean, median, and skewness ofβ;kurtosis ofDperf; and 75% quantile ofDdiffwere the most significant features. The GB differentiated malignant and benign lesions with an accuracy of 0.833, an area-under-the-curve of 0.942, and an F1 score of 0.87 providing the best statistical performance (p-value < 0.05) compared to the other classifiers.Significance. Our study has demonstrated that GB with a set of histogram features from the CTRW and IVIM model parameters can effectively differentiate malignant and benign breast lesions.

Synthetic MRI, multiplexed sensitivity encoding, and BI-RADS for benign and malignant breast cancer discrimination

Objective

To assess the diagnostic value of predictive models based on synthetic magnetic resonance imaging (syMRI), multiplexed sensitivity encoding (MUSE) sequences, and Breast Imaging Reporting and Data System (BI-RADS) in the differentiation of benign and malignant breast lesions.

Methods

Clinical and MRI data of 158 patients with breast lesions who underwent dynamic contrast-enhanced MRI (DCE-MRI), syMRI, and MUSE sequences between September 2019 and December 2020 were retrospectively collected. The apparent diffusion coefficient (ADC) values of MUSE and quantitative relaxation parameters (longitudinal and transverse relaxation times [T1, T2], and proton density [PD] values) of syMRI were measured, and the parameter variation values and change in their ratios were calculated. The patients were randomly divided into training (n = 111) and validation (n = 47) groups at a ratio of 7:3. A nomogram was built based on univariate and multivariate logistic regression analyses in the training group and was verified in the validation group. The discriminatory and predictive capacities of the nomogram were assessed by the receiver operating characteristic curve and area under the curve (AUC). The AUC was compared by DeLong test.

Results

In the training group, univariate analysis showed that age, lesion diameter, menopausal status, ADC, T2_pre, PD_pre, PD_Gd, T2_Delta, and T2_ratio were significantly different between benign and malignant breast lesions (P < 0.05). Multivariate logistic regression analysis showed that ADC and T2_pre were significant variables (all P < 0.05) in breast cancer diagnosis. The quantitative model (model A: ADC, T2_pre), BI-RADS model (model B), and multi-parameter model (model C: ADC, T2_pre, BI-RADS) were established by combining the above independent variables, among which model C had the highest diagnostic performance, with AUC of 0.965 and 0.986 in the training and validation groups, respectively.

Conclusions

The prediction model established based on syMRI, MUSE sequence, and BI-RADS is helpful for clinical differentiation of breast tumors and provides more accurate information for individualized diagnosis.

Clinical value of contralateral breast cancers detected by pre-operative MRI in patients diagnosed with DCIS: a population-based cohort study

OBJECTIVES

For patients with ductal carcinoma in situ (DCIS), data about the impact of breast MRI at primary diagnosis on the incidence and characteristics of contralateral breast cancers are scarce.

METHODS

We selected all 8486 women diagnosed with primary DCIS in the Netherlands in 2011-2015 from the Netherlands Cancer Registry. The synchronous and metachronous detection of contralateral DCIS (cDCIS) and contralateral invasive breast cancer (cIBC) was assessed for patients who received an MRI upon diagnosis (MRI group) and for an age-matched control group without MRI.

RESULTS

Nineteen percent of patients received an MRI, of which 0.8% was diagnosed with synchronous cDCIS and 1.3% with synchronous cIBC not found by mammography. The 5-year cumulative incidence of synchronous plus metachronous cDCIS was higher for the MRI versus age-matched control group (2.0% versus 0.9%, p = 0.02) and similar for cIBC (3.5% versus 2.3%, p = 0.17). The increased incidence of cDCIS was observed in patients aged < 50 years (sHR = 4.22, 95% CI: 1.19-14.99), but not in patients aged 50-74 years (sHR = 0.89, 95% CI: 0.41-1.93).

CONCLUSIONS

MRI at primary DCIS diagnosis detected additional synchronous cDCIS and cIBC, and was associated with a higher rate of metachronous cDCIS without decreasing the rate of metachronous cIBC. This finding was most evident in younger patients.

KEY POINTS

• Magnetic resonance imaging at primary diagnosis of ductal carcinoma in situ detected an additional synchronous breast lesion in 2.1% of patients. • In patients aged younger than 50 years, the use of pre-operative MRI was associated with a fourfold increase in the incidence of a second contralateral DCIS without decreasing the incidence of metachronous invasive breast cancers up to 5 years after diagnosis. • In patients aged over 50 years, the use of pre-operative MRI did not result in a difference in the incidence of a second contralateral DCIS or metachronous invasive breast cancer.

Intra- and peri-tumoral radiomics for predicting the sentinel lymph node metastasis in breast cancer based on preoperative mammography and MRI

Purpose

This study aims to investigate values of intra- and peri-tumoral regions in the mammography and magnetic resonance imaging (MRI) image for prediction of sentinel lymph node metastasis (SLNM) in invasive breast cancer (BC).

Methods

This study included 208 patients with invasive BC between Spe. 2017 and Apr. 2021. All patients underwent preoperative digital mammography (DM), digital breast tomosynthesis (DBT), dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DWI) scans. Radiomics features were extracted from manually outlined intratumoral regions, and automatically dilated peritumoral tumor regions in each modality. The least absolute shrinkage and selection operator (LASSO) regression was used to select key features from each region to develop radiomics signatures (RSs). Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity and negative predictive value (NPV) were calculated to evaluate performance of the RSs.

Results

Intra- and peri-tumoral regions of BC can provide complementary information on the SLN status. In each modality, the Com-RSs derived from combined intra- and peri-tumoral regions always yielded higher AUCs than the Intra-RSs or Peri-RSs. A total of 10 and 11 features were identified as the most important predictors from mammography (DM plus DBT) and MRI (DCE-MRI plus DWI), respectively. The DCE-MRI plus DWI generated higher AUCs compared with DM plus DBT in the training (AUCs, DCE-MRI plus DWI vs. DM plus DBT, 0.897 vs. 0.846) and validation (AUCs, DCE-MRI plus DWI vs. DM plus DBT, 0.826 vs. 0.786) cohort.

Conclusions

Radiomics features from intra- and peri-tumoral regions can provide complementary information to identify the SLNM in both mammography and MRI. The DCE-MRI plus DWI generated lower specificity, but higher AUC, accuracy, sensitivity and negative predictive value compared with DM plus DBT.

Motion-based microwave tomographic measurement device for three-dimensional coverage in a magnetic resonance system

PURPOSE

We have developed a fully 3D data acquisition system for microwave breast imaging which can operate simultaneously inside a magnetic resonance imaging (MRI). MRI is used regularly for breast imaging to distinguish tumors from normal tissue. It generally has poor specificity unless used with a gadolinium contrast agent. Microwave imaging could fill this need because of the good endogenous tumor:normal tissue property contrast, especially in light of safety concerns for gadolinium. The antenna array consists of 16 monopole antennas positioned in a horizontal circle surrounding the breast which can then be moved vertically for 3D coverage of the breast. The tank system materials were chosen to minimize artifacts in the MR image within the specific shared imaging zone. The support rods are stainless steel, albeit positioned sufficiently far from the imaging target to have little effect. The mechanical motion parts are all 3D printed plastic. Unlike many conventional antennas, the monopoles consist of just the center conductor and insulator of the coaxial cable, making it one of the least possible metallic structures.

METHODS

Data were acquired both inside and outside of the MR bore to confirm that the MR bore did not have adverse effects on the microwave imaging process. The imaging tank was filled with a mixture of glycerin and water to both provide a reasonable property match to the phantom and to highly attenuate the fields which also acted to suppress multi-path signals. Microwave images were reconstructed using our Gauss-Newton scheme combined with a log transformation for a more linear convergence. MR images were also acquired to assess the effects of the microwave tank structures on the imaging.

RESULTS

The microwave measurement data were acquired in log magnitude and phase format at 200 MHz increments from 700-1900 MHz. Each antenna acted sequentially as a transmitter while the complement of 15 acted as a receiver. The single frequency images were reconstructed using a Gauss-Newton iterative technique with a standard log transformation to linearize the process. The data showed that the signal strengths were between 7-10 dB lower for the case when the array was inside the MRI versus when not. Notwithstanding, the image quality was still high because of the significant signal to noise ratio. The reconstructed images in both situations demonstrated good 3D object recovery of the vertically size and shaped varying object. The MR images were not adversely affected by the presence of antennas or feed structures.

CONCLUSIONS

We have demonstrated that our technique can recover high-quality images of a 3D varying object within an MRI system. Compatibility issues have been addressed for both the microwave and MRI systems. The reduced SNR for the case operating in the MRI did not adversely affect the images. To the best of our knowledge, this is the first example of a microwave imaging system operating in an MRI with full 3D volumetric capability.

Addressing Disparities Related to Access of Multimodality Breast Imaging Services Before and During the COVID-19 Pandemic

Despite technological advancements focused on reducing breast cancer mortality through early detection, there have been reported disparities in the access to these imaging services with underserved patient populations (including racial minority groups and patients of low socioeconomic status) showing underutilization compared to other patient groups. These underserved populations tend to have more advanced breast cancer presentations, in part due to delays in diagnosis resulting in later stage of disease presentation. To make matters worse, the COVID-19 pandemic declared in March 2020 has resulted in significant healthcare disruptions leading to extensive delays in breast imaging services which are expected to negatively impact breast cancer mortality long-term. Given the worsening disparity in breast cancer mortality among racial/ethnic minorities and financially disadvantaged groups, it is vital to address these disparity gaps with the goal of reducing the barriers to timely breast cancer diagnosis and addressing breast cancer mortality differences among breast cancer patients. Therefore, this review aims to provide a discussion highlighting the disparities related to breast imaging access, the effects of the COVID-19 pandemic on these disparities, current targeted interventions implemented in breast imaging practices to reduce these disparities, and future directions on the journey to reducing disparity gaps for breast imaging patients. Tackling the root cause factors of the persistent breast cancer-related disparities is critical to meeting the needs of patients who are disadvantaged and can lead to continued improvement in the quality of individualized care for patients who have higher breast cancer morbidity and mortality risks.

Digital Breast Tomosynthesis versus MRI as an Adjunct to Full-Field Digital Mammography for Preoperative Evaluation of Breast Cancer according to Mammographic Density

OBJECTIVE

To compare digital breast tomosynthesis (DBT) and MRI as an adjunct to full-field digital mammography (FFDM) for the preoperative evaluation of women with breast cancer based on mammographic density.

MATERIALS AND METHODS

This retrospective study enrolled 280 patients with breast cancer who had undergone FFDM, DBT, and MRI for preoperative local tumor staging. Three radiologists independently sought the index cancer and additional ipsilateral and contralateral breast cancers using either FFDM alone, DBT plus FFDM, or MRI plus FFDM. Diagnostic performances across the three radiologists were compared among the reading modes in all patients and subgroups with dense (n = 186) and non-dense breasts (n = 94) according to mammographic density.

RESULTS

Of 280 patients, 46 (16.4%) had 48 additional (39 ipsilateral and nine contralateral) cancers in addition to the index cancer. For index cancers, both DBT plus FFDM and MRI plus FFDM showed sensitivities of 100% in the non-dense group. In the dense group, DBT plus FFDM showed lower sensitivity than that of MRI plus FFDM (94.6% vs. 99.6%, p < 0.001). For additional ipsilateral cancers, DBT plus FFDM showed specificity and positive predictive value (PPV) of 100% in the non-dense group, but sensitivity and negative predictive value (NPV) were not statistically different from those of MRI plus FFDM (p > 0.05). In the dense group, DBT plus FFDM showed higher specificity (98.2% vs. 94.1%, p = 0.005) and PPV (83.1% vs. 65.4%; p = 0.036) than those of MRI plus FFDM, but lower sensitivity (59.9% vs. 75.3%; p = 0.049). For contralateral cancers, DBT plus FFDM showed higher specificity than that of MRI plus FFDM (99.0% vs. 96.7%, p = 0.014), however, the other values did not differ (all p > 0.05) in the dense group.

CONCLUSION

DBT plus FFDM showed an overall higher specificity than that of MRI plus FFDM regardless of breast density, perhaps without substantial loss in sensitivity and NPV in the diagnosis of additional cancers. Thus, DBT may have the potential to be used as a preoperative breast cancer staging tool.

Type 2 dynamic curves: A diagnostic dilemma

BACKGROUND

Magnetic resonance imaging (MRI) with multiparametric dynamic contrast plays a critical role in the assessment of breast lesions. Dynamic curves are a critical parameter in determining the benign or malignant nature of lesions. Dynamic curves of type 1 are known to represent benign masses, while dynamic curves of type 3 are known to identify malignant masses. Type 2 dynamic curves have a sensitivity of 42.6% and specificity of 75% for malignancy detection.

AIM

To investigate the pathological diagnosis of lesions with type 2 dynamic curves.

METHODS

We evaluated breast MRI examinations performed between 2020 and 2021 retrospectively and included lesions with type 2 dynamic curves. We included 38 lesions from 33 patients. The lesions were evaluated for their pathological diagnosis and morphological characteristics.

RESULTS

Twenty-six lesions were malignant, while twelve were benign. The most frequently encountered benign lesion (7/12, 58.3%) was sclerosing adenosis, while the most frequently encountered malignant diagnosis was invasive ductal cancer. The presence of a type 2 dynamic curve had a sensitivity of 40.2% and specificity of 73.4% for predicting malignancy. By combining type 2 curves and morphological features, the sensitivity and specificity were increased.

CONCLUSION

The high rates of malignancy detected histopathologically among patients with type 2 dynamic curves in our study are remarkable. Type 2 dynamic curves can be detected in benign breast masses, especially in sclerosing adenosis cases. Considering morphological features can increase the diagnostic accuracy in cases with type 2 dynamic curves.

Case Report: Mucocele-Like Tumor of the Breast Associated With Ductal Carcinoma In Situ

Mucocele-like tumor of the breast is histologically characterized as mucin-containing cysts with mucin leaking to the stroma. It could be associated with atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC). We report a case of mucocele-like tumor of the breast associated with DCIS confirmed by paraffin section. We review the literature and discuss the imaging features, pathology, and clinical management of the lesion. These lesions demonstrate characteristic imaging features, and we especially highlight the MR characteristics, as they have not been well documented. Performing a diagnostic fine-needle aspiration cytology (FNAC) of mucocele-like tumor carries a risk of tumor underestimation; therefore, excision for all mucocele-like tumors is suggested to be the best approach. However, some recent reports recommend close follow-up for patients with low-risk factors who have mucocele-like tumor without atypia on FNAC.

Additional Workups Recommended During Preoperative Breast MRI: Methods to Gain Efficiency and Limit Confusion

BACKGROUND

Preoperative breast MRI is indicated for staging but can lead to complex imaging workups. This study reviewed imaging recommendations made on preoperative MRI exams, to simplify management approaches for patients with newly diagnosed breast cancer.

METHODS

This retrospective single-institution review was restricted to women with breast cancer who underwent staging MRI. Additional breast lesions, separate from index tumors, recommended for additional workup or surveillance were assessed to see which were detected and which characteristics predicted success in detection. Univariate mixed-effects logistic modeling predicted the likelihood of finding lesions using MRI-directed ultrasound (US), with odds ratios reported. Tests were two-sided, with a p value lower than 0.05 considered significant.

RESULTS

In this study, 534 (39.6%) patients had recommendations for additional workup after preoperative MRI. MRI detected additional malignancy in 178 patients (33.3%). Half of the 66 patients who refused an additional workup and opted for mastectomy had additional malignancies at mastectomy. MRI-directed US was 14 times more likely to detect masses than nonmass enhancement (NME) (p < 0.001). NME was detected on US in only 16% of cases, with one third of subsequent biopsy results considered discordant. Probably benign assessments were given to 35 patients, with 23% not returning for follow-up evaluation and 7% returning at least 6 months later than recommended.

CONCLUSION

Use of preoperative breast MRI has increased. Although it can add value, institutions should establish indications and expectations to prevent unnecessary workups. Limiting MRI-directed US to masses, avoiding probably benign assessments, and consulting with patients after MRI but prior to workups can prevent unnecessary exams and confusion.

Comparative Study of Digital Breast Tomosynthesis (DBT) with and without Ultrasound versus Breast Magnetic Resonance Imaging (MRI) in Detecting Breast Lesion

Digital breast tomosynthesis (DBT) is a fairly recent breast imaging technique invented to overcome the challenges of overlapping breast tissue. Ultrasonography (USG) was used as a complementary tool to DBT for the purpose of this study. Nonetheless, breast magnetic resonance imaging (MRI) remains the most sensitive tool to detect breast lesion. The purpose of this study was to evaluate diagnostic performance of DBT, with and without USG, versus breast MRI in correlation to histopathological examination (HPE). This was a retrospective study in a university hospital over a duration of 24 months. Findings were acquired from a formal report and were correlated with HPE. The sensitivity of DBT with or without USG was lower than MRI. However, the accuracy, specificity and PPV were raised with the aid of USG to equivalent or better than MRI. These three modalities showed statistically significant in correlation with HPE (p < 0.005, chi-squared). Generally, DBT alone has lower sensitivity as compared to MRI. However, it is reassuring that DBT + USG could significantly improve diagnostic performance to that comparable to MRI. In conclusion, results of this study are vital to centers which do not have MRI, as complementary ultrasound can accentuate diagnostic performance of DBT.

Characterization of the diffusion signal of breast tissues using multi-exponential models

PURPOSE

Restriction spectrum imaging (RSI) decomposes the diffusion-weighted MRI signal into separate components of known apparent diffusion coefficients (ADCs). The number of diffusion components and optimal ADCs for RSI are organ-specific and determined empirically. The purpose of this work was to determine the RSI model for breast tissues.

METHODS

The diffusion-weighted MRI signal was described using a linear combination of multiple exponential components. A set of ADC values was estimated to fit voxels in cancer and control ROIs. Later, the signal contributions of each diffusion component were estimated using these fixed ADC values. Relative-fitting residuals and Bayesian information criterion were assessed. Contrast-to-noise ratio between cancer and fibroglandular tissue in RSI-derived signal contribution maps was compared to DCE imaging.

RESULTS

A total of 74 women with breast cancer were scanned at 3.0 Tesla MRI. The fitting residuals of conventional ADC and Bayesian information criterion suggest that a 3-component model improves the characterization of the diffusion signal over a biexponential model. Estimated ADCs of triexponential model were D_1,3 = 0, D_2,3 = 1.5 × 10^-3 , and D_3,3 = 10.8 × 10^-3 mm² /s. The RSI-derived signal contributions of the slower diffusion components were larger in tumors than in fibroglandular tissues. Further, the contrast-to-noise and specificity at 80% sensitivity of DCE and a subset of RSI-derived maps were equivalent.

CONCLUSION

Breast diffusion-weighted MRI signal was best described using a triexponential model. Tumor conspicuity in breast RSI model is comparable to that of DCE without the use of exogenous contrast. These data may be used as differential features between healthy and malignant breast tissues.

Association between lesion enhancement and breast cancer in contrast-enhanced spectral mammography

BACKGROUND

Contrast-enhanced spectral mammography (CESM) may help to determine the malignancy potential of lesions according to the degree of enhancement.

PURPOSE

To investigate the correlation between the degree of contrast enhancement of the lesions in contrast-enhanced spectral mammography (CESM) and the final histopathological diagnosis in patients with BI-RADS 4 and 5 lesions.

MATERIAL AND METHODS

CESM was performed in 128 patients who had BI-RADS 4 and 5 lesions on mammography and underwent histopathological examination. A total of 128 index lesions were scored using a 4-point scale regarding the degree of contrast enhancement (0 = no contrast enhancement, 1 = minimal, 2 = moderate, 3 = marked), a score of 2 and 3 was accepted as suggestive of malignancy. The study was approved in our institutional scientific committee.

RESULTS

In total, 76 (59.4%) of the lesions had benign histopathological results, whereas 52 of them had malignant results. Contrast enhancement was not observed in 22.7% of the lesions while 24.2% had minimal enhancement, 18.8% had moderate enhancement, and 34.4% had marked enhancement in CESM. The sensitivity of the degree of contrast enhancement in CESM was 98.1%, when the specificity was 77.6%, positive predictive value was 75%, negative predictive value was 98.3%, and accuracy was 85.9%.

CONCLUSION

This study demonstrated that the degree of contrast enhancement of the lesions in CESM may be used in daily practice with easily performing a visual scale in predicting the malignancy potential of the lesions.

Clinical and MRI Evaluation of Silicone Gel Implants with RFID-M Traceability System: A Prospective Controlled Cohort Study Related to Safety and Image Quality in MRI Follow-Up

BACKGROUND

SmoothSilk implants (SSI) are the first generation of implants to incorporate a radio-frequency identification device (RFID-M), a non-invasive traceability system. Although the RFID-M is considered compatible with magnetic resonance imaging (MRI), the size of the artifact and its influence on breast tissue vary. This prospective study assessed safety and MRI issues in a cohort of breast reconstruction patients.

METHODS

Forty-four SSI were used for breast reconstruction in patients undergoing treatment for breast cancer. All patients were evaluated for magnetic field interactions, MRI-related heating and artifacts in a 1.5-T MRI unit using standard T1/T2-weighted sequences utilized in clinical assessment of breast tissue/implants.

RESULTS

Mean patient age was 41.5 years (27-53ys) and body mass index was 28+-6.44 kg/m². In 18/22 patients (81.8%), mastectomies were unilateral. No patients reported local heat/discomfort. All implants showed RFID-M-related artifacts with an estimated mean volume in T1 of 42.9cm³ (26.2-63.6cm³; SD±8.6 and 95% CI, 40.37-45.45) and in T2 of 60.5cm³ (35.4-97.2cm³; SD±14.7 and 95% CI, 56.29-65.01). Artifact volume was smaller in T1 than in T2, to a statistically significant degree (p <0.001). There were no statistically significant differences in artifact volume according to surgical indication, breast side or implant volume. There were 4/44 (9%) cases of minor rotation (<45°). In all cases, adequate analysis of the breast tissue was performed.

CONCLUSIONS

The results demonstrate that SSI with RFID-M technology presented an artifact volume of 42.9cm³ and 60.5cm³ in T1 and T2 images, respectively. Our findings provide detailed information on the quality and location of MRI artifacts in a reconstructed cohort which can help guide clinical decision-making for patients. To our knowledge, this is the first time RFID-M breast implants have been prospectively evaluated for clinical and MRI issues in a cohort of reconstructive patients.

LEVEL OF EVIDENCE IV

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MRI-Based Machine Learning in Differentiation Between Benign and Malignant Breast Lesions

Background

Differential diagnosis between benign and malignant breast lesions is of crucial importance relating to follow-up treatment. Recent development in texture analysis and machine learning may lead to a new solution to this problem.

Method

This current study enrolled a total number of 265 patients (benign breast lesions:malignant breast lesions = 71:194) diagnosed in our hospital and received magnetic resonance imaging between January 2014 and August 2017. Patients were randomly divided into the training group and validation group (4:1), and two radiologists extracted their texture features from the contrast-enhanced T1-weighted images. We performed five different feature selection methods including Distance correlation, Gradient Boosting Decision Tree (GBDT), least absolute shrinkage and selection operator (LASSO), random forest (RF), eXtreme gradient boosting (Xgboost) and five independent classification models were built based on Linear discriminant analysis (LDA) algorithm.

Results

All five models showed promising results to discriminate malignant breast lesions from benign breast lesions, and the areas under the curve (AUCs) of receiver operating characteristic (ROC) were all above 0.830 in both training and validation groups. The model with a better discriminating ability was the combination of LDA + gradient boosting decision tree (GBDT). The sensitivity, specificity, AUC, and accuracy in the training group were 0.814, 0.883, 0.922, and 0.868, respectively; LDA + random forest (RF) also suggests promising results with the AUC of 0.906 in the training group.

Conclusion

The evidence of this study, while preliminary, suggested that a combination of MRI texture analysis and LDA algorithm could discriminate benign breast lesions from malignant breast lesions. Further multicenter researches in this field would be of great help in the validation of the result.

Intra- and peritumoral radiomics on assessment of breast cancer molecular subtypes based on mammography and MRI

PURPOSE

This study aimed to investigate the efficacy of digital mammography (DM), digital breast tomosynthesis (DBT), diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI separately and combined in the prediction of molecular subtypes of breast cancer.

METHODS

A total of 241 patients were enrolled and underwent breast MD, DBT, DW and DCE scans. Radiomics features were calculated from intra- and peritumoral regions, and selected with least absolute shrinkage and selection operator (LASSO) regression to develop radiomics signatures (RSs). Prediction performance of intra- and peritumoral regions in the four modalities were evaluated and compared with area under the receiver-operating characteristic (ROC) curve (AUC), specificity and sensitivity as comparison metrics.

RESULTS

The RSs derived from combined intra- and peritumoral regions improved prediction AUCs compared with those from intra- or peritumoral regions alone. DM plus DBT generated better AUCs than the DW plus DCE on predicting Luminal A and Luminal B in the training (Luminal A: 0.859 and 0.805; Luminal B: 0.773 and 0.747) and validation (Luminal A: 0.906 and 0.853; Luminal B: 0.807 and 0.784) cohort. For the prediction of HER2-enriched and TN, the DW plus DCE yielded better AUCs than the DM plus DBT in the training (HER2-enriched: 0.954 and 0.857; TN: 0.877 and 0.802) and validation (HER2-enriched: 0.974 and 0.907; TN: 0.938 and 0.874) cohort.

CONCLUSIONS

Peritumoral regions can provide complementary information to intratumoral regions for the prediction of molecular subtypes. Compared with MRI, the mammography showed higher AUCs for the prediction of Luminal A and B, but lower AUCs for the prediction of HER2-enriched and TN.

Radiomic Evaluations of the Diagnostic Performance of DM, DBT, DCE MRI, DWI, and Their Combination for the Diagnosisof Breast Cancer

Objectives

This study aims to evaluate digital mammography (DM), digital breast tomosynthesis (DBT), dynamic contrast-enhanced (DCE), and diffusion-weighted (DW) MRI, individually and combined, for the values in the diagnosis of breast cancer, and propose a visualized clinical-radiomics nomogram for potential clinical uses.

Methods

A total of 120 patients were enrolled between September 2017 and July 2018, all underwent preoperative DM, DBT, DCE, and DWI scans. Radiomics features were extracted and selected using the least absolute shrinkage and selection operator (LASSO) regression. A radiomics nomogram was constructed integrating the radiomics signature and important clinical predictors, and assessed with the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

Results

The radiomics signature derived from DBT plus DM generated a lower area under the ROC curve (AUC) and sensitivity, but a higher specificity compared with that from DCE plus DWI. The nomogram integrating the combined radiomics signature, age, and menstruation status achieved the best diagnostic performance in the training (AUCs, nomogram vs. combined radiomics signature vs. clinical model, 0.975 vs. 0.964 vs. 0.782) and validation (AUCs, nomogram vs. combined radiomics signature vs. clinical model, 0.983 vs. 0.978 vs. 0.680) cohorts. DCA confirmed the potential clinical usefulness of the nomogram.

Conclusions

The DBT plus DM provided a lower AUC and sensitivity, but a higher specificity than DCE plus DWI for detecting breast cancer. The proposed clinical-radiomics nomogram has diagnostic advantages over each modality, and can be considered as an efficient tool for breast cancer screening.

Recalibrating the decision for MRI-directed breast ultrasound in patients with newly diagnosed breast cancer, factors predicting sonographic success

OBJECTIVE

Evaluate utilization of MRI-directed breast ultrasound (US) in patients with newly diagnosed breast cancer and refine practices to increase success of sonographic lesion detection.

METHODS

This retrospective single-institution review was restricted to women with breast cancer who underwent MRI from November 2006 to January 2017. Enhancing breast lesions, separate from the index tumor, recommended for MRI-directed US were assessed to see which were detected and which characteristics predicted success in detection. Univariate mixed-effects logistic modeling predicted likelihood of finding breast lesions with US, with odds ratios reported. All tests were two-sided with p < 0.05 considered significant.

RESULTS

A total of 275 patients underwent MRI-directed US for 361 breast lesions, of which 187 (51.8%) were found on US. Of those detected, 171 (91.4%) were masses and 16 (8.6%) were nonmass enhancement (NME), with masses 14 times more likely to be seen (p < 0.001). Size alone was not a significant predictor but achieved significance when associated with lesion type (mass size, p < 0.001). Masses with irregular shapes or margins and invasive carcinomas were more frequently detected. Patient age, internal enhancement pattern, and distribution of NME were not significant predictors in sonographic detection. A presumed sonographic correlate for NME was found for 16 (16.2%) of 99 attempted lesions.

CONCLUSION

As MRI access expands, utilization of MRI-directed US should be scrutinized to avoid downstream practice inefficiencies. Sonographic detection rates for NME remain low for women undergoing MRI for disease extent, with NME often better suited for MRI-guided biopsy.

Improved value of whole-lesion histogram analysis on DCE parametric maps for diagnosing small breast cancer (≤ 1 cm)

OBJECTIVES

To determine if whole-lesion histogram analysis on dynamic contrast-enhanced (DCE) parametric maps help to improve the diagnostic accuracy of small suspicious breast lesions (≤ 1 cm).

METHODS

This retrospective study included 99 female patients with 114 lesions (40 malignant and 74 benign lesions) suspicious on magnetic resonance imaging (MRI).Two radiologists reviewed all lesions and descripted the morphologic and kinetic characteristics according to BI-RADS by consensus. Whole lesions were segmented on DCE parametric maps (washin and washout), and quantitative histogram features were extracted. Univariate analysis and multivariate logistic regression analysis with forward stepwise covariate selection were performed to identify significant variables. Diagnostic performance was assessed and compared with that of qualitative BI-RADS assessment and quantitative histogram analysis by ROC analysis.

RESULTS

For malignancy defined as a washout or plateau pattern, the qualitative kinetic pattern showed a significant difference between the two groups (p = 0.023), yielding an AUC of 0.603 (95% confidence interval [CI]: 0.507, 0.694). The mean and median of washout were independent quantitative predictors of malignancy (p = 0.002, 0.010), achieving an AUC of 0.796 (95% CI: 0. 709, 0.865). The AUC of the quantitative model was better than that of the qualitative model (p < 0.001).

CONCLUSIONS

Compared with the qualitative BI-RADS assessment, quantitative whole-lesion histogram analysis on DCE parametric maps was better to discriminate between small benign and malignant breast lesions (≤ 1 cm) initially defined as suspicious on DCE-MRI.

KEY POINTS

• For malignancy defined as a washout or plateau, the kinetic pattern may provide information to diagnose small breast cancer. • The mean and median of washout map were significantly lower for small malignant breast lesions than for benign lesions. • Quantitative histogram analysis on MRI parametric maps improves diagnostic accuracy for small breast cancer, which may obviate unnecessary biopsy.

Diagnostic performance of mammography and magnetic resonance imaging for evaluating mammographically visible breast masses

OBJECTIVE

We compared the diagnostic values of mammography and magnetic resonance imaging (MRI) for evaluating breast masses.

METHODS

We retrospectively analyzed mammography, MRI, and histopathological data for 377 patients with breast masses on mammography, including 73 benign and 304 malignant masses.

RESULTS

The sensitivities and negative predictive values (NPVs) were significantly higher for MRI compared with mammography for detecting breast cancer (98.4% vs. 89.8% and 87.8% vs. 46.6%, respectively). The specificity and positive predictive values (PPV) were similar for both techniques. Compared with mammography alone, mammography plus MRI improved the specificity (67.1% vs. 37.0%) and PPV (91.8% vs. 85.6%), but there was no significant difference in sensitivity or NPV. Compared with MRI alone, the combination significantly improved the specificity (67.1% vs. 49.3%), but the sensitivity (88.5% vs. 98.4%) and NPV (58.3% vs. 87.8%) were reduced, and the PPV was similar in both groups. There was no significant difference between mammography and MRI in terms of sensitivity or specificity among 81 patients with breast masses with calcification.

CONCLUSION

Breast MRI improved the sensitivity and NPV for breast cancer detection. Combining MRI and mammography improved the specificity and PPV, but MRI offered no advantage in patients with breast masses with calcification.

Low-Field NMR Relaxometry for Intraoperative Tumour Margin Assessment in Breast-Conserving Surgery

Simple Summary

Breast cancer is the most diagnosed cancer for women, and clear surgical margins in breast-conserving surgery (BCS) are essential for preventing recurrence. In this study, the potential of fast field-cycling ¹H-NMR relaxometry as a new tool for intraoperative margin assessment was evaluated. The technique allows the determination of the tissue proton relaxation rates as a function of the applied magnetic field on small tissue samples excised from surgical specimens, at the margins of tumour resection, prior to histopathological analysis. It was found that a good accuracy in margin assessment, i.e., a sensitivity of 92% and a specificity of 85%, can be achieved. The discriminating ability shown by the relaxometric assay relies mainly on the difference of fat/water content between healthy and tumour cells. The information obtained has the potential to support the surgeon in real-time margin assessment during BCS.

Abstract

As conserving surgery is routinely applied for the treatment of early-stage breast cancer, the need for new technology to improve intraoperative margin assessment has become increasingly important. In this study, the potential of fast field-cycling ¹H-NMR relaxometry as a new diagnostic tool was evaluated. The technique allows the determination of the tissue proton relaxation rates (R₁), as a function of the applied magnetic field, which are affected by the changes in the composition of the mammary gland tissue occurring during the development of neoplasia. The study involved 104 small tissue samples obtained from surgical specimens destined for histopathology. It was found that a good accuracy in margin assessment, i.e., a sensitivity of 92% and a specificity of 85%, can be achieved by using two quantifiers, namely (i) the slope of the line joining the R₁ values measured at 0.02 and 1 MHz and (ii) the sum of the R₁ values measured at 0.39 and 1 MHz. The method is fast, and it does not rely on the expertise of a pathologist or cytologist. The obtained results suggest that a simplified, low-cost, automated instrument might compete well with the currently available tools in margin assessment.

Added value of abbreviated breast magnetic resonance imaging for assessing suspicious microcalcification on screening mammography-a prospective study

OBJECTIVES

To investigate the added diagnostic value of abbreviated breast magnetic resonance imaging (MRI) for suspicious microcalcifications on screening mammography.

METHODS

This prospective study included 80 patients with suspicious calcifications on screening mammography who underwent abbreviated MRI before undergoing breast biopsy between August 2017 and September 2020. The abbreviated protocol included one pre-contrast and the first post-contrast T1-weighted series. MRI examinations were interpreted as either positive or negative based on the visibility of any significant enhancement. The positive predictive value (PPV) was compared before and after the MRI.

RESULTS

Of the 80 suspicious microcalcifications, 33.8% (27/80) were malignant and 66.2% (53/80) were false positives. Abbreviated MRI revealed 33 positive enhancement lesions, and 25 and two lesions showed true-positive and false-negative findings, respectively. Abbreviated MRI increased PPV from 33.8 (27 of 80 cases; 95% CI: 26.2%, 40.8%) to 75.8% (25 of 33 cases; 95% CI: 62.1%, 85.7%). A total of 85% (45 of 53) false-positive diagnoses were reduced after abbreviated MRI assessment.

CONCLUSIONS

Abbreviated MRI added significant diagnostic value in patients with suspicious microcalcifications on screening mammography, as demonstrated by a significant increase in PPV with a potential reduction in unnecessary biopsy.

KEY POINTS

• Abbreviated breast magnetic resonance imaging increased the positive predictive value of suspicious microcalcifications on screening mammography from 33.8 (27/80 cases) to 75.8% (25/33 cases) (p < .01). • Abbreviated magnetic resonance imaging helped avoid unnecessary benign biopsies in 85% (45/53 cases) of lesions without missing invasive cancer.

Volume reduction for ≥2 cm benign breast lesions after ultrasound-guided microwave ablation with a minimum 12-month follow-up

OBJECTIVE

To prospectively evaluate the efficacy of microwave ablation (MWA) for benign breast lesions (BBLs) ≥2 cm and explore the possible factors associated with the volume reduction rate (VRR) of ablated lesions.

MATERIALS AND METHODS

From November 2013 to December 2017, a total of 80 patients with 104 biopsy-proved BBLs larger than 2 cm in size underwent MWA. After the procedure, patients were followed up via physical and imaging examination consisting of contrast-enhanced ultrasound (CEUS) and magnetic resonance imaging (MRI). Possible factors associated with 12-month VRR were assessed, including basic patient characteristics, index lesions and parameters of ablation technique.

RESULTS

The mean tumor size was 2.6 ± 0.6 cm (ranging 2.0-6.3 cm). Of the 104 lesions, 70 were fibroadenomas, 27 adenosis and 7 fibrocystic changes. Post-procedure CEUS or contrast-enhanced MRI showed that all lesions were completely ablated. No immediate or delayed complications were observed. All patients were followed up for more than 12 months (median follow-up 12.5 months). After MWA, the ablated lesion volume decreased significantly by 12 months (p < 0.001), with a mean volume reduction of 80.2 ± 13.1%. Multiple linear regression analysis showed that location adjacent to areola (β = 7.5, 95%CI: 1.0-13.9, p = 0.025) and location adjacent to skin (β = -7.4, 95%CI: -12.7 to -13.9, p = 0.007) were independent factors respectively associated with the increased and decreased 12-month VRR.

CONCLUSION

For BBLs larger than 2 cm, US-guided MWA is a favorable treatment modality, with BBLs adjacent to the areola being associated with more significant 12-month VRR after MWA.

The diagnostic dilemma with the plateau pattern of the time-intensity curve: can the relative apparent diffusion coefficient (rADC) optimise the ADC parameter for differentiating breast lesions?

AIM

To assess the performance of the apparent diffusion coefficient (ADC) and relative ADC (rADC) to differentiate benign from malignant breast lesions using the plateau pattern of the time-intensity curve (Type II TIC), including the impact of lesions-enhancement subtypes and menopausal status of patients.

MATERIALS AND METHODS

Between September 2016 and December 2019, 408 patients with 169 benign and 239 malignant lesions with Type II TIC underwent magnetic resonance imaging (MRI), including diffusion-weighted imaging, with b-values of 50 and 800 s/mm². ADC and rADC values were calculated by placing regions of interest (ROIs) on the lesion, the parenchyma of the normal breast, and the pectoralis major muscle. A receiver operating characteristic (ROC) curve was generated to compare the diagnostic performance of each parameter in distinguishing between benign and malignant breast lesions. Further classification was undertaken to study the discriminatory performance of each parameter in the different lesions enhancement subtypes (mass-like enhancement [MLE] and non-MLE [NMLE]) and menopausal status of patients (pre-menopausal and post-menopausal).

RESULTS

There was a significant difference in the ADC and rADC values between benign and malignant lesions. The sensitivities of lesion ADC, gland rADC, and muscle rADC were 79.29%, 77.51%, and 79.29%, respectively, with specificities of 94.56%, 82.01%, and 94.98%, respectively. The area under the ROC curve (AUC) of muscle rADC was the highest (AUC=0.92), especially in the MLE subtype (AUC=0.96), and was not affected by the menopausal status.

CONCLUSION

Muscle rADC and lesion ADC assessment improved the diagnostic performance of breast MRI in distinguishing between benign and malignant breast lesions with Type II TIC, especially muscle rADC in the MLE subtype.

Ultrafast Dynamic Contrast-Enhanced MRI Using Compressed Sensing: Associations of Early Kinetic Parameters With Prognostic Factors of Breast Cancer

OBJECTIVE. The purpose of this study was to investigate whether early kinetic parameters derived from ultrafast dynamic contrast-enhanced MRI (DCE-MRI) using compressed sensing are associated with prognostic factors for breast cancer. MATERIALS AND METHODS. We evaluated 201 consecutive women (mean age, 54.6 years) with breast cancer (168 invasive, 33 ductal carcinoma in situ) who underwent both ultrafast DCE-MRI using compressed sensing (temporal resolution, 4.7 seconds; spatial resolution, 0.8 × 1.1 × 0.9 mm) and surgery between 2018 and 2019. Early kinetic parameters (time to enhancement [TTE] and maximum slope [MS]) were measured in breast lesions by two radiologists using a software program and were correlated with histopathologic prognostic factors. The Mann-Whitney U test and linear regression analysis were used. RESULTS. The median TTE and MS values for breast cancer were 11.9 seconds and 7.7%/s, respectively. The median MS was significantly larger in invasive cancer lesions than in ductal carcinoma in situ lesions (8.4%/s vs 4.7%/s, p < .001). In women with invasive cancer, multivariate linear regression analyses showed that a larger tumor size (> 2 cm) (p = .048) and estrogen receptor-negative status (p < .001) were significantly associated with a shorter TTE. A higher histologic grade (grade 3) (p = .01) was significantly associated with a larger MS. We observed excellent interobserver agreement between two readers in the measurements of TTE and MS (intraclass correlation coefficients, 0.943 and 0.890, respectively). CONCLUSION. Ultrafast MRI-derived early enhancement parameters, such as TTE and MS, are associated with histopathologic prognostic factors in women with breast cancer.

Correction of Artifacts Induced by B0 Inhomogeneities in Breast MRI Using Reduced-Field-of-View Echo-Planar Imaging and Enhanced Reversed Polarity Gradient Method

BACKGROUND

Diffusion-weighted (DW) echo-planar imaging (EPI) is prone to geometric distortions due to B₀ inhomogeneities. Both prospective and retrospective approaches have been developed to decrease and correct such distortions.

PURPOSE

The purpose of this work was to evaluate the performance of reduced-field-of-view (FOV) acquisition and retrospective distortion correction methods in decreasing distortion artifacts for breast imaging. Coverage of the axilla in reduced-FOV DW magnetic resonance imaging (MRI) and residual distortion were also assessed.

STUDY TYPE

Retrospective.

POPULATION/PHANTOM

Breast phantom and 169 women (52.4 ± 13.4 years old) undergoing clinical breast MRI.

FIELD STRENGTH/SEQUENCE

A 3.0 T/ full- and reduced-FOV DW gradient-echo EPI sequence.

ASSESSMENT

Performance of reversed polarity gradient (RPG) and FSL topup in correcting breast full- and reduced-FOV EPI data was evaluated using the mutual information (MI) metric between EPI and anatomical images. Two independent breast radiologists determined if coverage on both EPI data sets was adequate to evaluate axillary nodes and identified residual nipple distortion artifacts.

STATISTICAL TESTS

Two-way repeated-measures analyses of variance and post hoc tests were used to identify differences between EPI modality and distortion correction method. Generalized linear mixed effects models were used to evaluate differences in axillary coverage and residual nipple distortion.

RESULTS

In a breast phantom, residual distortions were 0.16 ± 0.07 cm and 0.22 ± 0.13 cm in reduced- and full-FOV EPI with both methods, respectively. In patients, MI significantly increased after distortion correction of full-FOV (11 ± 5% and 18 ± 9%, RPG and topup) and reduced-FOV (8 ± 4% both) EPI data. Axillary nodes were observed in 99% and 69% of the cases in full- and reduced-FOV EPI images. Residual distortion was observed in 93% and 0% of the cases in full- and reduced-FOV images.

DATA CONCLUSION

Minimal distortion was achieved with RPG applied to reduced-FOV EPI data. RPG improved distortions for full-FOV images but with more modest improvements and limited correction near the nipple.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 1.

The rate of breast fibroglandular enhancement during dynamic contrast-enhanced MRI reflects response to neoadjuvant therapy

PURPOSE

This study assesses the rate of enhancement of breast fibroglandular tissue after administration of a magnetic resonance imaging (MRI) gadolinium-based contrast agent and determines its relationship with response to neoadjuvant therapy (NAT) in women with breast cancer.

METHOD

Women with locally advanced breast cancer (N = 19) were imaged four times over the course of NAT. Dynamic contrast-enhanced (DCE) MRI was acquired after administration of a gadolinium-based contrast agent with a temporal resolution of 7.27 s. The tumor, fibroglandular tissue, and adipose tissue were semi-automatically segmented using a manually drawn region of interest encompassing the tumor followed by fuzzy c-means clustering. The rate and relative intensity of signal enhancement were calculated for each voxel within the tumor and fibroglandular tissue.

RESULTS

The rate of fibroglandular tissue enhancement after contrast agent injection declined by an average of 29 % over the course of NAT. This decline was present in 16 of the 19 patients in the study. The rate of enhancement is significantly higher in women who achieve pathological complete response (pCR) after both 1 cycle (68 % higher, p < 0.05) and after 3-5 cycles of NAT (58 % higher; p < 0.05). The relative intensity of fibroglandular enhancement correlates with the rate of enhancement (R2 = 0.64, p < 0.001) and is higher in women who achieve pCR after both 1 cycle and after 3-5 cycles of NAT (p < 0.05, both timepoints).

CONCLUSION

The rate of fibroglandular tissue enhancement declines over the course of therapy, provides novel information not reflected by tumoral measures, and may predict pathological response early in the course of therapy, with smaller declines in enhancement in women who achieve favorable response.

Magnetic resonance imaging findings of invasive breast cancer in different histological grades and different histopathological types

BACKGROUND

The aim of this study was to evaluate the magnetic resonance imaging (MRI) findings of invasive breast cancer in different histopathological types (invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC) and mixed ductal-lobular carcinoma (MDLC)) and different histological grades.

METHODS

A retrospective review was made of 1256 patients who underwent breast MRI at our hospital between January 2015 and December 2018. A total of 152 lesions (27 ILC, 102 IDC, 23 MDLC and 20 grade 1, 83 grade 2 and 49 grade 3) were included in the study. All the lesions were evaluated according to size, shape, margin, dynamic curve, ADC value and T2 signal intensity ratio (SIR).

RESULTS

Most of the lesions tended to show type 2 and type 3 dynamic curve, type 1 dynamic curve was more commonly seen in ILC and grade 1 groups. IDC showed higher T2 SIR than the other types and grade 3 showed higher T2 SIR than other grades (p< 0,05) There was no statistically significant difference between the groups according to morphological features and mean ADC values (p > 0,05).

CONCLUSION

T2 SIR and dynamic curve can help the radiologists predict histopathological findings while morphological features and ADC values were not helpful in distinguishing histological types and grades.

Relationship between MRI findings and invasive breast cancer with podoplanin-positive cancer-associated fibroblasts

OBJECTIVE

Purpose of our study is to assess the relationship between MRI findings and invasive breast cancer (IBC) with cancer-associated fibroblasts (CAFs) that are positive for podoplanin.

METHODS

We retrospectively analyzed the consecutive 109 IBCs. The IBCs were dichotomized as with (+) or without (-) podoplanin-positive CAFs. In MRI analyses, the dichotomized IBCs were compared the lesion to muscle ratio (L/M ratio) in STIR images, the ADC value, the distribution of kinetic parameters, and morphological findings.

RESULTS

Of the 109 IBCs, 28 (26%) IBCs had podoplanin(+) CAFs. Compared to the podoplanin(-) group, the podoplanin(+) group tended to have a more malignant pathological status. In the STIR images, the podoplanin(+) group had significantly higher L/M ratio (7.59 vs. 6.55, p = 0.040). In a dynamic study, the podoplanin(+) group had a significantly higher percentage of the washout pattern (42.21% vs. 29.43%, p = 0.045). There were 23 mass lesions and 5 non-mass enhancement (NME) lesions in the podoplanin(+) group, and 69 mass lesions and 12 NME lesions in the podoplanin(-) group. The mass lesions of the podoplanin(-) group had a significantly higher likelihood of showing an irregular shape (n = 47 vs. 8, p = 0.035). The podoplanin(+) group's lesions had a significantly higher likelihood of showing a circumscribed margin (n = 14 vs. 6, p < 0.001) and a rim enhancement (n = 10 vs. 13, p = 0.047). In multivariate analyses, only high nuclear grade was significant predictive value of podoplanin(+) CAFs.

CONCLUSION

Although not significant in multivariate analyses, MRI findings may be used to determine the podoplanin-positive CAF status of invasive breast cancer.

Assessment of Additional MRI-Detected Breast Lesions Using the Quantitative Analysis of Contrast-Enhanced Ultrasound Scans and Its Comparability with Dynamic Contrast-Enhanced MRI Findings of the Breast

Purpose

To assess the diagnostic performance of contrast-enhanced ultrasound (CEUS) for additional MR-detected enhancing lesions and to determine whether or not kinetic pattern results comparable to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast can be obtained using the quantitative analysis of CEUS.

Materials and Methods

In this single-center prospective study, a total of 71 additional MR-detected breast lesions were included. CEUS examination was performed, and lesions were categorized according to the Breast Imaging-Reporting and Data System (BI-RADS). The sensitivity, specificity, and diagnostic accuracy of CEUS were calculated by comparing the BI-RADS category to the final pathology results. The degree of agreement between CEUS and DCE-MRI kinetic patterns was evaluated using weighted kappa.

Results

On CEUS, 46 lesions were assigned as BI-RADS category 4B, 4C, or 5, while 25 lesions category 3 or 4A. The diagnostic performance of CEUS for enhancing lesions on DCE-MRI was excellent, with 84.9% sensitivity, 94.4% specificity, and 97.8% positive predictive value. A total of 57/71 (80%) lesions had correlating kinetic patterns and showed good agreement (weighted kappa = 0.66) between CEUS and DCE-MRI. Benign lesions showed excellent agreement (weighted kappa = 0.84), and invasive ductal carcinoma (IDC) showed good agreement (weighted kappa = 0.69).

Conclusion

The diagnostic performance of CEUS for additional MR-detected breast lesions was excellent. Accurate kinetic pattern assessment, fairly comparable to DCE-MRI, can be obtained for benign and IDC lesions using CEUS.

Side of contrast injection and breast size correlate with motion artifacts grade and image quality on breast MRI

BACKGROUND

Motion is a relevant cause of artifacts in breast magnetic resonance imaging (MRI), potentially degrading image quality, even with optimized protocols.

PURPOSE

To investigate the causes of motion artifacts (MA) impacting on image quality (IQ) of contrast-enhanced breast MRI.

MATERIAL AND METHODS

Retrospective two-center study on consecutive 1.5-T contrast-enhanced breast MRI, independently reviewed by two radiologists on first subtracted and maximum intensity projection images to define the side most affected by MA. IQ was scored as 1 (optimal), 2 (reduced, but without reduction of diagnostic power), or 3 (reduced, with reduced diagnostic power). Correlations with injection side, breast size (A/B vs. C/D cups), patient age, clinical indication, and MRI scanner/protocol were assessed using χ² and Fisher's exact statistics.

RESULTS

In total, 237 examinations were included, with right injection performed in 124 (52%) and left in 113 (48%). MA were more frequent on the side ipsilateral to the injection (144/237, 61%, 95% confidence interval [CI] 54-67%) than on the contralateral (93/237, 95% CI 33-46%) (P < 0.001); IQ was scored 1 in 154/237 (65%), 2 in 63/237 (27%), and 3 in 20/237 (8%) examinations; patients with A/B cups showed higher IQ score than patients with C/D cups (scores 1, 2, and 3: 54% vs. 70%; 29% vs. 25%; 17% vs. 5%, respectively, P = 0.002). No significant correlations were found for MA (P≥0.106) or IQ (P ≥ 0.318) between ipsi- or contralateral injection and right/left injection, breast size, age, indication, or scanner/protocol.

CONCLUSION

MA were more frequent in breasts ipsilateral to contrast injection and showed a reduced IQ for small breasts.

Ex Vivo Study of Artifacts Caused by Breast Tissue Markers with Different 1.5 Tesla and 3 Tesla MRI Scanners - A Bicentric Study

RATIONALE AND OBJECTIVES

The purpose of our study was to evaluate magnetic resonance (MR) artifacts related to breast tissue markers in breast imaging procedures.

MATERIALS AND METHODS

In this bicentric prospective ex vivo study 10 different commercially available markers were measured in self-made breast phantoms. Breast tissue markers varying in marker size, composition, and shape were evaluated. MR imaging (MRI) scans were performed on 1.5 Tesla (T) and 3 T scanners from 2 different vendors, using dedicated breast coils. Three different sequences (T1-weighted images with and without fat saturation, T2-weighted images) were acquired in axial and coronal view. Three blinded readers electronically measured the artifact length.

RESULTS

All markers caused artifacts in MRI. The largest median artifact length was 10.4 mm, interquartile range (IQR 9.4-11.0 mm), the smallest 4.8 mm (IQR 4.5-5.2 mm). Relative artifact length (quotient artifact length in mm/real physical length of the marker) ranged between 0.9 (IQR 0.9-1.2) and 3.0 (IQR 2.8-3.4). Mean artifact length was higher for metallic markers (10.2 mm; IQR 8.7-11.5 mm) compared to metallic markers with nonmetallic coating (7.7 mm; IQR 6.3-10.2 mm) and nonmetallic marker (7.6 mm; IQR 5.9-10.0 mm); all p < 0.0001. Artifact size was higher in coronal in comparison to axial view; p < 0.05. The results were comparable between the different field strengths, the sites and sequences; p > 0.05. Interobserver agreement was excellent (ntraclass correlation coefficient = 0.83).

CONCLUSION

Artifacts are necessary in the detection and localization of breast tissue markers, but could also limit the interpretation of MRI due to the possibility of masking the residual tumor after biopsy. This artifact size varies among the different clips evaluated. It depends on marker composition and scan direction but is not influenced by image sequence, field strength or scanner type.

Second Look Ultrasonography-Guided Breast Biopsy with Magnetic Resonance Imaging Confirmation by Intralesional Contrast Injection

Objective

This study aimed to introduce an alternative pre-biopsy confirmation technique that combines sonography-guided intra-lesional contrast injections and single non-enhanced magnetic resonance imaging (MRI) pulse sequence in order to identify sonographic correlates of incidentally detected breast MRI lesions which were occult on primary ultrasonography (USG) and mammography examination.

Materials and Methods

From May 2014 through May 2015, a total of 37 incidental breast lesions of 37 patients, which were detected by breast MRI, were evaluated with targeted second look ultrasound (SLUS). The suspected lesion on USG was marked with a gadolinium-based contrast agent under USG guidance. After a single non-enhanced T1 weighted control MR sequence, positively correlated lesions with initial MRI were sampled by USG guided core biopsy.

Results

Of the 37 lesions evaluated, 32 (86%) lesions showed a correlation between MRI and SLUS findings. On SLUS core biopsy, there were eight (25%) malignant and 11 (34.4%) high-risk lesions among these 32 cases with correlated MRI findings; while the remaining 13 (40.6%) cases had benign histopathology. Eleven (34.4%) of the SLUS-discovered lesions were focus, 11 (34.4%) were non-mass enhancements, and the remaining 10 (31.2%) were mass lesions. Of the five lesions (13.5%) that showed no correlations on MRI and SLUS examinations, four were non-mass enhancements and one was focus.

Conclusion

SLUS represents a method for identifying MRI-detected lesions and provides a bridge to ultrasound-guided biopsy for histopathological diagnosis. There is a need for confirmation of biopsies to avoid false negative results. We describe a cheap, safe, and easy-to-apply USG-guided pre-biopsy lesions marking method in order to ensure definite correlation.