Prospective multicenter cohort study to refine management recommendations for women at elevated familial risk of breast cancer: the EVA trial

Deep Learning k-Space-to-Image Reconstruction Facilitates High Spatial Resolution and Scan Time Reduction in Diffusion-Weighted Imaging Breast MRI

BACKGROUND

For time-consuming diffusion-weighted imaging (DWI) of the breast, deep learning-based imaging acceleration appears particularly promising.

PURPOSE

To investigate a combined k-space-to-image reconstruction approach for scan time reduction and improved spatial resolution in breast DWI.

STUDY TYPE

Retrospective.

POPULATION

133 women (age 49.7 ± 12.1 years) underwent multiparametric breast MRI.

FIELD STRENGTH/SEQUENCE

3.0T/T2 turbo spin echo, T1 3D gradient echo, DWI (800 and 1600 sec/mm2).

ASSESSMENT

DWI data were retrospectively processed using deep learning-based k-space-to-image reconstruction (DL-DWI) and an additional super-resolution algorithm (SRDL-DWI). In addition to signal-to-noise ratio and apparent diffusion coefficient (ADC) comparisons among standard, DL- and SRDL-DWI, a range of quantitative similarity (e.g., structural similarity index [SSIM]) and error metrics (e.g., normalized root mean square error [NRMSE], symmetric mean absolute percent error [SMAPE], log accuracy error [LOGAC]) was calculated to analyze structural variations. Subjective image evaluation was performed independently by three radiologists on a seven-point rating scale.

STATISTICAL TESTS

Friedman's rank-based analysis of variance with Bonferroni-corrected pairwise post-hoc tests. P < 0.05 was considered significant.

RESULTS

Both DL- and SRDL-DWI allowed for a 39% reduction in simulated scan time over standard DWI (5 vs. 3 minutes). The highest image quality ratings were assigned to SRDL-DWI with good interreader agreement (ICC 0.834; 95% confidence interval 0.818-0.848). Irrespective of b-value, both standard and DL-DWI produced superior SNR compared to SRDL-DWI. ADC values were slightly higher in SRDL-DWI (+0.5%) and DL-DWI (+3.4%) than in standard DWI. Structural similarity was excellent between DL-/SRDL-DWI and standard DWI for either b value (SSIM ≥ 0.86). Calculation of error metrics (NRMSE ≤ 0.05, SMAPE ≤ 0.02, and LOGAC ≤ 0.04) supported the assumption of low voxel-wise error.

DATA CONCLUSION

Deep learning-based k-space-to-image reconstruction reduces simulated scan time of breast DWI by 39% without influencing structural similarity. Additionally, super-resolution interpolation allows for substantial improvement of subjective image quality.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 1.

The impact of preoperative breast MRI on the therapeutic management of breast cancer patients

BACKGROUND

The role of preoperative breast MRI to evaluate the extent of disease in breast cancer patients is considered controversial. We aimed at assessing the effect of breast MRI on the management of newly diagnosed breast cancer.

MATERIALS

A retrospective review of 202 consecutively seen patients who were newly diagnosed with breast cancer and who underwent preoperative breast MRIs at Assuta Ashdod between June 1, 2017, and June 1, 2020. Data included discovering suspicious lesions by conventional imaging, MRI findings, and surgical pathology results. This was analyzed to determine whether the MRI changed the management and whether it had a justified or unjustified effect on the treatment.

RESULTS

The mean age was 54.51 (standard deviation, 11.34 years). Breast MRI revealed additional findings in 56 % of patients and modified therapeutic management in 32 % of the cases evaluated, having a justified effect in 87.6 %. Patients with changed management had a statistically significantly higher mastectomy rate (36 %) than those who did not (14 %). No statistically significant association was found between independent variables such as breast density, tumor location on the breast, type of tumor, patient's demographic information, etc. And whether MRI findings changed the initial treatment plan.

CONCLUSIONS

MRI played an essential role in the preoperative staging of breast cancer in our study, modifying therapeutic planning in approximately one-third of the cases and having a justified effect on most of them. We, therefore, support preoperative breast MRI in newly diagnosed breast cancer patients.

Prospective Study of Supplemental Screening With Contrast-Enhanced Mammography in Women With Elevated Risk of Breast Cancer: Results of the Prevalence Round

PURPOSE

Contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) have shown similar diagnostic performance in detection of breast cancer. Limited CEM data are available for high-risk breast cancer screening. The purpose of the study was to prospectively investigate the efficacy of supplemental screening CEM in elevated risk patients.

MATERIALS AND METHODS

A prospective, single-institution, institutional review board-approved observational study was conducted in asymptomatic elevated risk women age 35 years or older who had a negative conventional two-dimensional digital breast tomosynthesis screening mammography (MG) and no additional supplemental screening within the prior 12 months.

RESULTS

Four hundred sixty women were enrolled from February 2019 to April 2021. The median age was 56.8 (range, 35.0-79.2) years; 408 of 460 (88.7%) were mammographically dense. Biopsy revealed benign changes in 22 women (22/37, 59%), high-risk lesions in four women (4/37, 11%), and breast cancer in 11 women (11/37, 30%). Fourteen cancers (10 invasive, tumor size range 4-15 mm, median 9 mm) were diagnosed in 11 women. The overall supplemental cancer detection rate was 23.9 per 1,000 patients, 95% CI (12.0 to 42.4). All cancers were grade 1 or 2, ER+ ERBB2-, and node negative. CEM imaging screening offered high specificity (0.875 [95% CI, 0.844 to 0.906]), high NPV (0.998 [95% CI, 0.993 to 1.000), moderate PPV1 (0.164 [95% CI, 0.076 to 0.253), moderate PPV3 (0.275 [95% CI, 0.137 to 0.413]), and high sensitivity (0.917 [95% CI, 0.760 to 1.000]). At least 1 year of imaging follow-up was available on all patients, and one interval cancer was detected on breast MRI 4 months after negative screening CEM.

CONCLUSION

A pilot trial demonstrates a supplemental cancer detection rate of 23.9 per 1,000 in women at an elevated risk for breast cancer. Larger, multi-institutional, multiyear CEM trials in patients at elevated risk are needed for validation.

Case report: Possible role of low-dose PEM for avoiding unneeded procedures associated with false-positive or equivocal breast MRI results

Contrast-enhanced breast magnetic resonance imaging (MRI) is currently recommended as a screening tool for high-risk women and has been advocated for women with radiologically dense breast tissue. While breast MRI is acknowledged for its high sensitivity (with an exception for lower-grade ductal carcinoma in situ (DCIS) where emerging techniques like diffusion-weighted imaging offer improvement), its limitations include sensitivity to hormonal changes and a relatively high false-positive rate, potentially leading to overdiagnosis, increased imaging uncertainty, and unnecessary biopsies. These factors can exacerbate patient anxiety and impose additional costs. Molecular imaging with breast-targeted Positron Emission Tomography (PET) has shown the capability to detect malignancy independent of breast density and hormonal changes. Furthermore, breast-targeted PET has shown higher specificity when compared with MRI. However, traditional PET technology is associated with high radiation dose, which can limit its widespread use particularly in repeated studies or for undiagnosed patients. In this case report, we present a clinical application of low-dose breast imaging utilizing a breast-targeted PET camera (Radialis PET imager, Radialis Inc). The case involves a 33-year-old female patient who had multiple enhanced lesions detected on breast MRI after surgical removal of a malignant phyllodes tumor from the right breast. A benign core biopsy was obtained from the largest lesion seen in the left breast. One month after the MRI, 18F-fluorodeoxyglucose (18F-FDG) PET imaging session was performed using the Radialis PET Imager. Although the Radialis PET Imager has proven high count sensitivity and the capability to detect breast lesions with low metabolic activity (at a dose similar to mammography), no areas of increased 18F-FDG uptake were visualized in this particular case. The patient underwent a right-sided nipple-sparing mastectomy and left-sided lumpectomy, with bilateral reconstruction. The excised left breast tissue was completely benign, as suggested by both core biopsy and the PET results. The case presented highlights a promising clinical application of low-dose breast-targeted PET imaging to mitigate the uncertainty associated with MRI while keeping radiation doses within the safe range typically used in X-ray mammography.

Cancer detection rate of breast-MR in supplemental screening after negative mammography in women with dense breasts. Preliminary results of the MA-DETECT-Study after 200 participants

BACKGROUND

Due to increased cancer detection rates (CDR), breast MR (breast MRI) can reduce underdiagnosis of breast cancer compared to conventional imaging techniques, particularly in women with dense breasts. The purpose of this study is to report the additional breast cancer yield by breast MRI in women with dense breasts after receiving a negative screening mammogram.

METHODS

For this study we invited consecutive participants of the national German breast cancer Screening program with breast density categories ACR C & D and a negative mammogram to undergo additional screening by breast MRI. Endpoints were CDR and recall rates. This study reports interim results in the first 200 patients. At a power of 80% and considering an alpha error of 5%, this preliminary population size is sufficient to demonstrate a 4/1000 improvement in CDR.

RESULTS

In 200 screening participants, 8 women (40/1000, 17.4-77.3/1000) were recalled due to positive breast MRI findings. Image-guided biopsy revealed 5 cancers in 4 patients (one bilateral), comprising four invasive cancers and one case of DCIS. 3 patients revealed 4 invasive cancers presenting with ACR C breast density and one patient non-calcifying DCIS in a woman with ACR D breast density, resulting in a CDR of 20/1000 (95%-CI 5.5-50.4/1000) and a PPV of 50% (95%-CI 15.7-84.3%).

CONCLUSION

Our initial results demonstrate that supplemental screening using breast MRI in women with heterogeneously dense and very dense breasts yields an additional cancer detection rate in line with a prior randomized trial on breast MRI screening of women with extremely dense breasts. These findings are highly important as the population investigated constitutes a much higher proportion of women and yielded cancers particularly in women with heterogeneously dense breasts.

ACR Appropriateness Criteria® Female Breast Cancer Screening: 2023 Update

Early detection of breast cancer from regular screening substantially reduces breast cancer mortality and morbidity. Multiple different imaging modalities may be used to screen for breast cancer. Screening recommendations differ based on an individual's risk of developing breast cancer. Numerous factors contribute to breast cancer risk, which is frequently divided into three major categories: average, intermediate, and high risk. For patients assigned female at birth with native breast tissue, mammography and digital breast tomosynthesis are the recommended method for breast cancer screening in all risk categories. In addition to the recommendation of mammography and digital breast tomosynthesis in high-risk patients, screening with breast MRI is recommended. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

The Role of MRI in Breast Cancer and Breast Conservation Therapy

Contrast-enhanced breast MRI has an established role in aiding in the detection, evaluation, and management of breast cancer. This article discusses MRI sequences, the clinical utility of MRI, and how MRI has been evaluated for use in breast radiotherapy treatment planning. We highlight the contribution of MRI in the decision-making regarding selecting appropriate candidates for breast conservation therapy and review the emerging role of MRI-guided breast radiotherapy.

Awareness, Knowledge, and Current Practice of Breast Cancer Among Surgeons in Jordan

PURPOSE

Breast cancer (BC) is the most prevalent cancer in Jordan. De-escalation in treatment reflects a paradigm shift in BC treatment. More tailored strategies and the adoption of a multidisciplinary approach are essential to apply recent changes in management. In the era of breast surgery fellowship, adopting well-structured training is essential to apply recent therapeutic guidelines and meet patients' expectations.

METHODS

A cross-sectional study using a customized, self-reported questionnaire was used. Data collection occurred anonymously using a link via WhatsApp in the period between February 2023 and April 2023.

RESULTS

A total of 89 surgeons were involved in this study, and only 14 (15.7%) completed a subspecialty in breast surgery. About 58.4% considered the age of 40 years as the starting point for screening, and 84.3% reported that mammogram screening is associated with improved BC survival. Only 10.1% and 28.1% acknowledged the applicability of both tomosynthesis and breast magnetic resonance imaging in screening, respectively. A significant difference in the mean knowledge score about BC is observed between general surgeon and those with subspecialty. Varying levels of awareness concerning different risk factors and their correlation with the likelihood of BC occurrence observed. Although 56.2% of participants could offer breast conserving surgery and consider it oncological safe, only 48.3% defined it correctly. Of the participants, 61.8% and 76.4% stated that sentinel lymph node biopsy can be safely applied in clinically negative or suspicious axillary nodes, respectively, with <50% of surgeon performing it in their practice.

CONCLUSION

More efforts are required to enhance the knowledge and practice of surgeons in the field of breast surgery. Adopting national guidelines can facilitate the acceptance and improvement of current practices among surgeons in Jordan.

Decoding the Prevalent High-Risk Breast Cancers: Demographics, Pathological, Imaging Insights, and Long-Term Outcome

Objective: To investigate the features and outcomes of breast cancer in high-risk subgroups. Materials and Methods: REB approved an observational study of women diagnosed with breast cancer from 2010 to 2019. Three radiologists, using the BI-RADS lexicon, blindly reviewed mammogram and MRI screenings without a washout period. Consensus was reached with 2 additional reviewers. Inter-rater agreement was measured by Fleiss Kappa. Statistical analysis included Mann-Whitney U, Chi-square tests for cohort analysis, and Kaplan-Meier for survival rates, with a Cox model for comparative analysis using gene mutation as a reference. Results: The study included 140 high-risk women, finding 155 malignant lesions. Significant age differences noted: chest radiation therapy (median age 44, IQR: 37.0-46.2), gene mutation (median age 49, IQR: 39.8-58.0), and familial risk (median age 51, IQR: 44.5-56.0) (P = .007). Gene mutation carriers had smaller (P = .01), higher-grade tumours (P = .002), and more triple-negative ER- (P = .02), PR- (P = .002), and HER2- (P = .02) cases. MRI outperformed mammography in all subgroups. Substantial to near-perfect inter-rater agreement observed. Over 10 years, no deaths occurred in chest radiation group, with no significant survival difference between gene mutation and familial risk groups, HR = 0.93 (95% CI: 0.27, 3.26), P = .92. Conclusion: The study highlights the importance of age and specific tumour characteristics in identifying high-risk breast cancer subgroups. MRI is confirmed as an effective screening tool. Despite the aggressive nature of cancers in gene mutation carriers, early detection is crucial for survival outcomes. These insights, while necessitating further validation with larger studies, advocate for a move toward personalized medical care, strengthening the existing healthcare guidelines.

Clinical Significance of Background Parenchymal Enhancement in Breast Cancer Risk Stratification

BACKGROUND

Background parenchymal enhancement (BPE) is an established breast cancer risk factor. However, the relationship between BPE levels and breast cancer risk stratification remains unclear.

PURPOSE

To evaluate the clinical relationship between BPE levels and breast cancer risk with covariate adjustments for age, ethnicity, and hormonal status.

STUDY TYPE

Retrospective.

POPULATION

954 screening breast MRI datasets representing 721 women divided into four cohorts: women with pathogenic germline breast cancer (BRCA) mutations (Group 1, N = 211), women with non-BRCA germline mutations (Group 2, N = 60), women without high-risk germline mutations but with a lifetime breast cancer risk of ≥20% using the Tyrer-Cuzick model (Group 3, N = 362), and women with <20% lifetime risk (Group 4, N = 88).

FIELD STRENGTH/SEQUENCE

3 T/axial non-fat-saturated T1, short tau inversion recovery, fat-saturated pre-contrast, and post-contrast T1-weighted images.

ASSESSMENT

Data on age, body mass index, ethnicity, menopausal status, genetic predisposition, and hormonal therapy use were collected. BPE levels were evaluated by two breast fellowship-trained radiologists independently in accordance with BI-RADS, with a third breast fellowship-trained radiologist resolving any discordance.

STATISTICAL TESTS

Propensity score matching (PSM) was utilized to adjust covariates, including age, ethnicity, menopausal status, hormonal treatments, and prior bilateral oophorectomy. The Mann-Whitney U test, chi-squared test, and univariate and multiple logistic regression analysis were performed, with an odds ratio (OR) and corresponding 95% confidence interval. Weighted Kappa statistic was used to assess inter-reader variation. A P value <0.05 indicated a significant result.

RESULTS

In the assessment of BPE, there was substantial agreement between the two interpreting radiologists (κ = 0.74). Patient demographics were not significantly different between patient groups after PSM. The BPE of Group 1 was significantly lower than that of Group 4 and Group 3 among premenopausal women. In estimating the BPE level, the OR of gene mutations was 0.35.

DATA CONCLUSION

Adjusting for potential confounders, the BPE level of premenopausal women with BRCA mutations was significantly lower than that of non-high-risk women.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 3.

MRI Surveillance and Breast Cancer Mortality in Women With BRCA1 and BRCA2 Sequence Variations

Importance

Magnetic resonance imaging (MRI) surveillance is offered to women with a pathogenic variant in the BRCA1 or BRCA2 gene who face a high lifetime risk of breast cancer. Surveillance with MRI is effective in downstaging breast cancers, but the association of MRI surveillance with mortality risk has not been well defined.

Objective

To compare breast cancer mortality rates in women with a BRCA1 or BRCA2 sequence variation who entered an MRI surveillance program with those who did not.

Design, Setting, and Participants

Women with a BRCA1 or BRCA2 sequence variation were identified from 59 participating centers in 11 countries. Participants completed a baseline questionnaire between 1995 and 2015 and a follow-up questionnaire every 2 years to document screening histories, incident cancers, and vital status. Women who had breast cancer, a screening MRI examination, or bilateral mastectomy prior to enrollment were excluded. Participants were followed up from age 30 years (or the date of the baseline questionnaire, whichever was later) until age 75 years, the last follow-up, or death from breast cancer. Data were analyzed from January 1 to July 31, 2023.

Exposures

Entrance into an MRI surveillance program.

Main Outcomes and Measures

Cox proportional hazards modeling was used to estimate the hazard ratios (HRs) and 95% CIs for breast cancer mortality associated with MRI surveillance compared with no MRI surveillance using a time-dependent analysis.

Results

A total of 2488 women (mean [range] age at study entry 41.2 [30-69] years), with a sequence variation in the BRCA1 (n = 2004) or BRCA2 (n = 484) genes were included in the analysis. Of these participants, 1756 (70.6%) had at least 1 screening MRI examination and 732 women (29.4%) did not. After a mean follow-up of 9.2 years, 344 women (13.8%) developed breast cancer and 35 women (1.4%) died of breast cancer. The age-adjusted HRs for breast cancer mortality associated with entering an MRI surveillance program were 0.20 (95% CI, 0.10-0.43; P < .001) for women with BRCA1 sequence variations and 0.87 (95% CI, 0.10-17.25; P = .93) for women with BRCA2 sequence variations.

Conclusion and Relevance

Results of this cohort study suggest that among women with a BRCA1 sequence variation, MRI surveillance was associated with a significant reduction in breast cancer mortality compared with no MRI surveillance. Further studies of women with BRCA2 sequence variations are needed to ascertain these women obtain the same benefits associated with MRI surveillance.

Breast lesion morphology assessment with high and standard b values in diffusion-weighted imaging at 3 Tesla

INTRODUCTION

With increasing spatial resolution, diffusion-weighted imaging (DWI) may be suitable for morphologic lesion characterization in breast MRI - an area that has traditionally been occupied by dynamic contrast-enhanced imaging (DCE). This investigation compared DWI with b values of 800 and 1600 s/mm2 to DCE for lesion morphology assessment in high-resolution breast MRI at 3 Tesla.

MATERIAL AND METHODS

Multiparametric breast MRI was performed in 91 patients with 93 histopathologically proven lesions (31 benign, 62 malignant). Two radiologists independently evaluated three datasets per patient (DWIb800; DWIb1600; DCE) and assessed lesion visibility and BIRADS morphology criteria. Diagnostic accuracy was compared among readers and datasets using Cochran's Q test and pairwise post-hoc McNemar tests. Bland-Altman analyses were conducted for lesion size comparisons.

RESULTS

Discrimination of carcinomas was superior compared to benign findings in both DWIb800 and DWIb1600 (p < 0.001) with no b value-dependent difference. Similarly, assessability of mass lesions was better than of non-mass lesions, irrespective of b value (p < 0.001). Intra-reader reliability for the analysis of morphologic BIRADS criteria among DCE and DWI datasets was at least moderate (Fleiss κ≥0.557), while at least substantial inter-reader agreement was ascertained over all assessed categories (κ≥0.776). In pairwise Bland-Altman analyses, the measurement bias between DCE and DWIb800 was 0.7 mm, whereas the difference between DCE and DWIb1600 was 2.8 mm. DWIb1600 allowed for higher specificity than DCE (p = 0.007/0.062).

CONCLUSIONS

DWI can be employed for reliable morphologic lesion characterization in high-resolution breast MRI. High b values increase diagnostic specificity, while lesion size assessment is more precise with standard 800 s/mm2 images.

Utilizing large language models in breast cancer management: systematic review

PURPOSE

Despite advanced technologies in breast cancer management, challenges remain in efficiently interpreting vast clinical data for patient-specific insights. We reviewed the literature on how large language models (LLMs) such as ChatGPT might offer solutions in this field.

METHODS

We searched MEDLINE for relevant studies published before December 22, 2023. Keywords included: "large language models", "LLM", "GPT", "ChatGPT", "OpenAI", and "breast". The risk bias was evaluated using the QUADAS-2 tool.

RESULTS

Six studies evaluating either ChatGPT-3.5 or GPT-4, met our inclusion criteria. They explored clinical notes analysis, guideline-based question-answering, and patient management recommendations. Accuracy varied between studies, ranging from 50 to 98%. Higher accuracy was seen in structured tasks like information retrieval. Half of the studies used real patient data, adding practical clinical value. Challenges included inconsistent accuracy, dependency on the way questions are posed (prompt-dependency), and in some cases, missing critical clinical information.

CONCLUSION

LLMs hold potential in breast cancer care, especially in textual information extraction and guideline-driven clinical question-answering. Yet, their inconsistent accuracy underscores the need for careful validation of these models, and the importance of ongoing supervision.

Breast Cancer Detection Using a Low-Dose Positron Emission Digital Mammography System

Purpose To investigate the feasibility of low-dose positron emission mammography (PEM) concurrently to MRI to identify breast cancer and determine its local extent. Materials and Methods In this research ethics board-approved prospective study, participants newly diagnosed with breast cancer with concurrent breast MRI acquisitions were assigned independently of breast density, tumor size, and histopathologic cancer subtype to undergo low-dose PEM with up to 185 MBq of fluorine 18-labeled fluorodeoxyglucose (18F-FDG). Two breast radiologists, unaware of the cancer location, reviewed PEM images taken 1 and 4 hours following 18F-FDG injection. Findings were correlated with histopathologic results. Detection accuracy and participant details were examined using logistic regression and summary statistics, and a comparative analysis assessed the efficacy of PEM and MRI additional lesions detection (ClinicalTrials.gov: NCT03520218). Results Twenty-five female participants (median age, 52 years; range, 32-85 years) comprised the cohort. Twenty-four of 25 (96%) cancers (19 invasive cancers and five in situ diseases) were identified with PEM from 100 sets of bilateral images, showcasing comparable performance even after 3 hours of radiotracer uptake. The median invasive cancer size was 31 mm (range, 10-120). Three additional in situ grade 2 lesions were missed at PEM. While not significant, PEM detected fewer false-positive additional lesions compared with MRI (one of six [16%] vs eight of 13 [62%]; P = .14). Conclusion This study suggests the feasibility of a low-dose PEM system in helping to detect invasive breast cancer. Though large-scale clinical trials are essential to confirm these preliminary results, this study underscores the potential of this low-dose PEM system as a promising imaging tool in breast cancer diagnosis. ClinicalTrials.gov registration no. NCT03520218 Keywords: Positron Emission Digital Mammography, Invasive Breast Cancer, Oncology, MRI Supplemental material is available for this article. © RSNA, 2024 See also commentary by Barreto and Rapelyea in this issue.

Outcomes of High-Risk Breast MRI Screening in Women Without Prior History of Breast Cancer: Effectiveness Data from a Tertiary Care Center

OBJECTIVE

To evaluate the diagnostic performance outcomes of a breast MRI screening program in high-risk women without prior history of breast cancer.

METHODS

Retrospective cohort study of 1 405 consecutive screening breast MRI examinations in 681 asymptomatic women with high risk of breast cancer without prior history of breast cancer from January 1, 2015, to December 31, 2019. Outcomes (sensitivity, specificity, positive predictive value, negative predictive value, false-negative rate [FNR], cancer detection rate [CDR]) and characteristics of cancers were determined based on histopathology or 12-month follow-up. MRI examinations performed, BI-RADS assessments, pathology outcomes, and CDRs were analyzed overall and by age decade. Results in incidence screening round (MRI in last 18 months) and nonincidence round were compared.

RESULTS

Breast MRI achieved CDR 20/1000, sensitivity 93.3% (28/30), and specificity 83.4% (1 147/1375). Twenty-eight (28/1 405, CDR 20/1000) screen-detected cancers were identified: 18 (64.3%, 18/28) invasive and 10 (35.7%, 10/28) ductal carcinoma in situ. Overall, 92.9% (26/28) of all cancers were stage 0 or 1 and 89.3% (25/28) were node negative. All 14 incidence screening round malignancies were stage 0 or 1 with N0 disease. Median size for invasive carcinoma was 8.0 mm and for ductal carcinoma in situ was 9.0 mm. There were two false-negative exams for an FNR 0.1% (2/1 405).

CONCLUSION

High-risk screening breast MRI was effective at detecting early breast cancer and associated with favorable outcomes.

Screening in Women With BRCA Mutations Revisited

Patients with BRCA1 or BRCA2 gene mutations are at high risk for the development of breast cancer. This article reviews the current evidence for breast cancer screening of patients with BRCA1 or BRCA2 pathogenic gene mutations if they have not undergone prophylactic mastectomy. It will review the current evidence-based imaging recommendations for different modalities and ages of screening initiation in screening this patient population at high risk. Special considerations in transgender BRCA1 and BRCA2 mutation carriers are also discussed.

Psychosocial outcomes after varying risk management strategies in women at increased familial breast cancer risk: a mixed methods study of patient and partner outcomes

INTRODUCTION

Female carriers of BRCA1/2 genes have an increased lifetime risk of breast cancer. Options for managing risk include imaging surveillance or risk-reducing surgery (RRS). This mixed methods study aimed to identify factors affecting risk-management decisions and the psychosocial outcomes of these decisions for high-risk women and their partners.

METHODS

Semi-structured qualitative interviews were performed with women at high breast cancer risk who had faced these choices. Partners were also interviewed. Analysis used a framework approach. A bespoke questionnaire was developed to quantify and explore associations.

RESULTS

A total of 32 women were interviewed. Of these, 27 had partners of whom 7 (26%) agreed to be interviewed. Four main themes arose: perception of risk and impact of increased risk; risk-management strategy decision-making; impact of risk-management strategy; support needs and partner relationship issues. The questionnaire response rate was 36/157 (23%). Decision satisfaction was high in both surveillance and RRS groups. Relationship changes were common but not universal. Common causes of distress following RRS included adverse body image changes. Both groups experienced generalised and cancer-specific anxiety. Drivers for surgery included having children, deaths of close family from breast cancer and higher levels of cancer anxiety.

CONCLUSIONS

Levels of psychosocial and decision satisfaction were high for women choosing both RRS and surveillance but, for a minority, risk-reducing measures result in long-term psychosocial morbidity. Efforts to recognise women at increased risk of psychological morbidity may allow targeted support.

Economic evaluation of breast MRI in screening - a systematic review and basic approach to cost-effectiveness analyses

Background

Economic evaluations have become an accepted methodology for decision makers to allocate resources in healthcare systems. Particularly in screening, where short-term costs are associated with long-term benefits, and adverse effects of screening intermingle, cost-effectiveness analyses provide a means to estimate the economic value of screening.

Purpose

To introduce the methodology of economic evaluations and to review the existing evidence on cost-effectiveness of MR-based breast cancer screening.

Materials and methods

The various concepts and techniques of economic evaluations critical to the interpretation of cost-effectiveness analyses are briefly introduced. In a systematic review of the literature, economic evaluations from the years 2000-2022 are reviewed.

Results

Despite a considerable heterogeneity in the reported input variables, outcome categories and methodological approaches, cost-effectiveness analyses report favorably on the economic value of breast MRI screening for different risk groups, including both short- and long-term costs and outcomes.

Conclusion

Economic evaluations indicate a strongly favorable economic value of breast MRI screening for women at high risk and for women with dense breast tissue.

[Use of contrast-enhanced mammography for diagnosis of breast cancer]

BACKGROUND

Contrast-enhanced mammography (CEM) is an imaging method that is able to improve visualization of intramammary tumors after peripheral venous administration of an iodine-containing contrast medium (ICM).

OBJECTIVES AND METHODS

The current significance of CEM is discussed.

RESULTS

Studies were able to show an advantage of CEM in the diagnosis of breast cancer compared to mammography, especially for women with dense breasts. Indications for CEM currently depend on the availability of magnetic resonance imaging (MRI). If MRI is available, CEM is indicated in those cases when MRI cannot be performed. Use of CEM for breast cancer screening is currently viewed critically. This view can change when results and updated assessments of large CEM studies in Europe and USA become available. Patients must be informed about the use of an ICM. As ICM administration for CEM is carried out in a similar manner to established imaging methods, the authors expect the use of ICM for CEM to be unproblematic as long as general contraindications are adhered to.

CONCLUSIONS

In the future, CEM could have greater importance for the diagnosis of breast cancer, as this imaging method has diagnostic advantages compared to conventional mammography. A great advantage of CEM is its availability. For those who use breast MRI, CEM is helpful when MRI is not feasible due to contraindications or other reasons.

Revisiting Screening in Women With a Family History of Breast Cancer

Women with a family history (FH) of breast cancer and without known genetic susceptibility represent a unique population whose lifetime probability of developing breast cancer varies widely depending on familial factors, breast density, and the risk assessment tool used. Recently updated guidelines from the American College of Radiology recommend supplemental annual screening with contrast-enhanced MRI or contrast-enhanced mammography for women with an FH who are high risk (≥20% lifetime risk) or have dense breasts. To date, most screening studies addressing outcomes in women with FH have largely included those also with confirmed or suspected gene mutations, in whom the lifetime risk is highest, with limited data for women at average to intermediate risk who are not known to be genetically susceptible and may not benefit as much from the same screening approaches. Further research focusing specifically on women with FH as the only breast cancer risk factor is warranted to refine risk assessment and optimize a multimodality personalized screening approach.

High-Temporal/High-Spatial Resolution Breast Magnetic Resonance Imaging Improves Diagnostic Accuracy Compared With Standard Breast Magnetic Resonance Imaging in Patients With High Background Parenchymal Enhancement

PURPOSE

To compare breast magnetic resonance imaging (MRI) diagnostic performance using a standard high-spatial resolution protocol versus a simultaneous high-temporal/high-spatial resolution (HTHS) protocol in women with high levels of background parenchymal enhancement (BPE).

MATERIALS AND METHODS

We conducted a retrospective study of contrast-enhanced breast MRIs performed at our institution before and after the introduction of the HTHS protocol. We compared diagnostic performance of the HTHS and standard protocol by comparing cancer detection rate (CDR) and positive predictive value of biopsy (PPV3) among women with high BPE (ie, marked or moderate).

RESULTS

Among women with high BPE, the HTHS protocol demonstrated increased CDR (23.6 per 1,000 patients v 7.9 per 1,000 patients; P = 0. 013) and increased PPV3 (16.0% v 6.3%; P = .021) compared with the standard protocol. This corresponded to a 9.8% (95% CI, 1.29 to 18.3) decrease in the proportion of unnecessary biopsies among high-BPE patients and an additional cancer yield of 15.7 per 1,000 patients (95% CI, 1.3 to 18.3).

CONCLUSION

Among women with high BPE, HTHS MRI improved diagnostic performance, leading to an additional cancer yield of 15.7 cancers per 1,000 women and concomitantly decreasing unnecessary biopsies by 9.8%. A multisite prospective trial is warranted to confirm these findings and to pave the way for more widespread clinical implementation.

Clinical and imaging modality factors impacting radiological interpretation of breast screening in young women with neurofibromatosis type 1

Young women with Neurofibromatosis type 1 (NF1) have a high risk of developing breast cancer and poorer survival following breast cancer diagnosis. International guidelines recommend commencing breast screening between 30 and 35 years; however, the optimal screening modality is unestablished, and previous reports suggest that breast imaging may be complicated by the presence of intramammary and cutaneous neurofibromas (cNFs). The aim of this study was to explore potential barriers to implementation of breast screening for young women with NF1.Twenty-seven women (30-47 years) with NF1 completed breast screening with breast MRI, mammogram and breast ultrasound. Nineteen probably benign/suspicious lesions were detected across 14 women. Despite the presence of breast cNFs, initial biopsy rate for participants with NF1 (37%), were comparable to a BRCA pathogenic variant (PV) cohort (25%) (P = 0.311). No cancers or intramammary neurofibromas were identified. Most participants (89%) returned for second round screening.The presence of cNF did not affect clinician confidence in 3D mammogram interpretation, although increasing breast density, frequently seen in young women, impeded confidence for 2D and 3D mammogram. Moderate or marked background parenchymal enhancement on MRI was higher in the NF1 cohort (70.4%) than BRCA PV carriers (47.3%), which is an independent risk factor for breast cancer.Breast MRI was the preferred mode of screening over mammogram, as the majority (85%) with NF1 demonstrated breast density (BI-RADS 3C/4D), which hinders mammogram interpretation. For those with high breast density and high cNF breast coverage, 3D rather than 2D mammogram is preferred, if MRI is unavailable.

Breast MRI - The champion in the millimeter league: MIO breast MRI - The method of choice in women with dense breasts

We perform MRI of the breast as a first pass technique. We successfully established 10-minute-protocols (including T2 images) with a fixed dosage of 5 ml 1 M CM. A high spatial resolution of 526 × 526, better 672 × 672 or maximum (1.024 × 1.024, MIO MRI) is vital to achieve best results. We use fixation tools to avoid motion artifacts. Motion correction algorithms can, however, often eliminate such artifacts when they are present. In initial breast MRI exams, morphologic features are the most important criteria for lesion evaluation. If previous exams are available for comparison, the main criteria indicating a suspicious lesion are an increase in lesion size or the depiction of new lesions. High quality HR MRI of the breast is the method of choice in women with dense or extremely dense breasts in all cases (screening, assessment, follow up). In density type A or B, MRI can be helpful in defined constellations, e.g. when MX and US are limited or contraindicated. According to our experience, 95% or more of all carcinomas of the breast are detectable on MRI. The remaining 5% of MRI-occult lesions are intraductal tumors or very small invasive carcinomas depicted with mammography due to associated microcalcifications. MRI is, however, superior to all other imaging modalities in the detection of the clinically relevant DCIS (high risk DCIS, intermediate type). Consecutive MRI examinations in intervals of 12 to 24 months allow a reliable detection of invasive breast cancer with an average size of 7-8 mm. This corresponds to a rate of metastasis-free locoregional lymph nodes in >95% of cases. The rate of interval cancers is <2%. In conclusion, this strategy may increase the overall-lifetime survival of breast cancer patients to more than 95%. Inversely, mortality may be reduced to <5%. Taking these improvements in early breast cancer detection and survival that can be achieved through the implementation of QA HR MRI of the breast into account, it should be discussed to modify oncologic guidelines for the treatment of breast cancer. MRI is the best diagnostic tool we have and according to our experience, a first pass, quality-assured high-resolution breast MRI protocol provides best diagnostic results at minimal procedural effort.

Lymph Node Positivity: Indication for Preoperative MRI?

BACKGROUND

The purpose was to determine what factors help predict benefit from preoperative MRI.

METHODS

We conducted an IRB approved retrospective review of patients with breast cancer who underwent preoperative MRI (2018-2021). Patients were divided into a cohort of no new disease detected on MRI versus new disease detected.

RESULTS

Of 420 patients with a new diagnosis of breast cancer who underwent preoperative MRI, 17% had new multicentric, multifocal, or contralateral disease detected. There was no difference between the two cohorts for age (p = 0.23), race (p = 0.45), family history (p = 0.47), breast density (p = 0.14), or hormone status (p = 0.90). In multivariate analysis, age (p = 0.61, OR 0.99), race (p = 0.58, OR 1.26), family history (p = 0.54, OR 0.82), breast density (p = 0.83, OR 0.87), grade (p = 0.87, OR 1.09), tumor size (p = 0.37, OR 0.92), and use of neoadjuvant therapy (p = 0.41, OR 0.72) were not predictive of detection of additional new disease. Presence of positive nodes on ultrasound or mammogram was associated with new or multifocal disease on MRI (p = 0.0005, OR 3.48). Pre-MRI positive nodes increased the likelihood of detection of new disease (p = 0.0002, OR 3.04). Preoperative MRI resulted in more extensive surgery than indicated for 22.2% of the no new disease detected cohort and 6.9% of the new multicentric disease cohort (p < 0.001).

CONCLUSIONS

Patients with nodal disease detected in their evaluation are more likely to have new multifocal, multicentric, or contralateral disease detected on MRI. The use of preoperative MRI may be particularly helpful in patients with node-positive disease in identifying additional disease that would alter surgical management.

Defining features of hereditary lobular breast cancer due to CDH1 with magnetic resonance imaging and tumor characteristics

Women with germline pathogenic variants in CDH1, which encodes E-cadherin protein, are at increased lifetime risk of invasive lobular carcinoma (ILC). The associated tumor characteristics of hereditary lobular breast carcinoma (HLBC) in this high-risk population are not well-known. A single-center prospective cohort study was conducted to determine the imaging and pathologic features of HLBC compared to population-based ILC using Surveillance, Epidemiology, and End Results (SEER) data. One hundred fifty-eight women with CDH1 variants were evaluated, of whom 48 (30%) also had an ILC diagnosis. The median age at CDH1 diagnosis was 45 years [interquartile range, IQR 34-57 years] whereas the median age at diagnosis of CDH1 with concomitant ILC (HLBC) was 53 [IQR 45-62] years. Among women with HLBC, 83% (40/48) were identified with CDH1 mutation after diagnosis of ILC. Among 76 women (48%, 76/158) undergoing surveillance for ILC with breast magnetic resonance imaging (MRI), 29% (22/76) had an abnormal MRI result with available biopsy data for comparison. MRI detected ILC in 7 out of 8 biopsy-confirmed cases, corresponding with high sensitivity (88%), specificity (75%), and negative predictive value (98%); however, false-positive and false-discovery rates were elevated also (25% and 68%, respectively). HLBC was most frequently diagnosed at age 40-49 years (44%, 21/48), significantly younger than the common age of diagnosis of ILC in SEER general population data (most frequent age range 60-69 years, 28%; p < 0.001). HLBC tumors were smaller than SEER-documented ILC tumors (median 1.40 vs. 2.00 cm; p = 0.002) and had a higher incidence of background lobular carcinoma in situ (88% vs. 1%; p < 0.001) as well as progesterone receptor positivity (95% vs. 81%, p = 0.032). These findings suggest that HLBC is often detected via conventional screening methods as an early-stage hormone receptor-positive tumor, thus the clinical benefit of intensive screening with MRI may be limited to a subset of women with germline CDH1 variants.

Diffusion-weighted Breast MRI at 3 Tesla: Improved Lesion Visibility and Image Quality with a Combination of Water-excitation and Spectral Fat Saturation

RATIONALE AND OBJECTIVES

In breast MRI with diffusion-weighted imaging (DWI), fat suppression is essential for eliminating the dominant lipid signal. This investigation evaluates a combined water-excitation-spectral-fatsat method (WEXfs) versus standard spectral attenuated inversion recovery (SPAIR) in high-resolution 3-Tesla breast MRI.

MATERIALS AND METHODS

Multiparametric breast MRI with 2 echo-planar DWI sequences was performed in 83 patients (50.1 ± 12.6 years) employing either WEXfs or SPAIR for fat signal suppression. Three radiologists assessed overall DWI quality and delineability of 88 focal lesions (28 malignant, 60 benign) on images with b values of 800 and 1600 s/mm2, as well as apparent diffusion coefficient (ADC) maps. For each fat suppression method and b value, the longest lesion diameter was determined in addition to measuring the signal intensity in DWI and ADC value in standardized regions of interest.

RESULTS

Regardless of b values, image quality (all p < 0.001) and lesion delineability (all p ≤ 0.003) with WEXfs-DWI were deemed superior compared to SPAIR-DWI in benign and malignant lesions. Irrespective of lesion characterization, WEXfs-DWI provided superior signal-to-noise, contrast-to-noise and signal-intensity ratios with 1600 s/mm2 (all p ≤ 0.05). The lesion size difference between contrast-enhanced T1 subtraction images and DWI was smaller for WEXfs compared to SPAIR fat suppression (all p ≤ 0.007). The mean ADC value in malignant lesions was lower for WEXfs-DWI (p < 0.001), while no significant ADC difference was ascertained between both techniques in benign lesions (p = 0.947).

CONCLUSION

WEXfs-DWI provides better subjective and objective image quality than standard SPAIR-DWI, resulting in a more accurate estimation of benign and malignant lesion size.

Comparison of the Diagnostic Accuracy of Mammogram-based Deep Learning and Traditional Breast Cancer Risk Models in Patients Who Underwent Supplemental Screening with MRI

Background Access to supplemental screening breast MRI is determined using traditional risk models, which are limited by modest predictive accuracy. Purpose To compare the diagnostic accuracy of a mammogram-based deep learning (DL) risk assessment model to that of traditional breast cancer risk models in patients who underwent supplemental screening with MRI. Materials and Methods This retrospective study included consecutive patients undergoing breast cancer screening MRI from September 2017 to September 2020 at four facilities. Risk was assessed using the Tyrer-Cuzick (TC) and National Cancer Institute Breast Cancer Risk Assessment Tool (BCRAT) 5-year and lifetime models as well as a DL 5-year model that generated a risk score based on the most recent screening mammogram. A risk score of 1.67% or higher defined increased risk for traditional 5-year models, a risk score of 20% or higher defined high risk for traditional lifetime models, and absolute scores of 2.3 or higher and 6.6 or higher defined increased and high risk, respectively, for the DL model. Model accuracy metrics including cancer detection rate (CDR) and positive predictive values (PPVs) (PPV of abnormal findings at screening [PPV1], PPV of biopsies recommended [PPV2], and PPV of biopsies performed [PPV3]) were compared using logistic regression models. Results This study included 2168 women who underwent 4247 high-risk screening MRI examinations (median age, 54 years [IQR, 48-60 years]). CDR (per 1000 examinations) was higher in patients at high risk according to the DL model (20.6 [95% CI: 11.8, 35.6]) than according to the TC (6.0 [95% CI: 2.9, 12.3]; P < .01) and BCRAT (6.8 [95% CI: 2.9, 15.8]; P = .04) lifetime models. PPV1, PPV2, and PPV3 were higher in patients identified as high risk by the DL model (PPV1, 14.6%; PPV2, 32.4%; PPV3, 36.4%) than those identified as high risk with the TC (PPV1, 5.0%; PPV2, 12.7%; PPV3, 13.5%; P value range, .02-.03) and BCRAT (PPV1, 5.5%; PPV2, 11.1%; PPV3, 12.5%; P value range, .02-.05) lifetime models. Conclusion Patients identified as high risk by a mammogram-based DL risk assessment model showed higher CDR at breast screening MRI than patients identified as high risk with traditional risk models. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bae in this issue.

Breast Cancer Screening for Women at Higher-Than-Average Risk: Updated Recommendations From the ACR

Early detection decreases breast cancer death. The ACR recommends annual screening beginning at age 40 for women of average risk and earlier and/or more intensive screening for women at higher-than-average risk. For most women at higher-than-average risk, the supplemental screening method of choice is breast MRI. Women with genetics-based increased risk, those with a calculated lifetime risk of 20% or more, and those exposed to chest radiation at young ages are recommended to undergo MRI surveillance starting at ages 25 to 30 and annual mammography (with a variable starting age between 25 and 40, depending on the type of risk). Mutation carriers can delay mammographic screening until age 40 if annual screening breast MRI is performed as recommended. Women diagnosed with breast cancer before age 50 or with personal histories of breast cancer and dense breasts should undergo annual supplemental breast MRI. Others with personal histories, and those with atypia at biopsy, should strongly consider MRI screening, especially if other risk factors are present. For women with dense breasts who desire supplemental screening, breast MRI is recommended. For those who qualify for but cannot undergo breast MRI, contrast-enhanced mammography or ultrasound could be considered. All women should undergo risk assessment by age 25, especially Black women and women of Ashkenazi Jewish heritage, so that those at higher-than-average risk can be identified and appropriate screening initiated.

Weakly supervised breast lesion detection in DCE-MRI using self-transfer learning

BACKGROUND

Breast cancer is a typically diagnosed and life-threatening cancer in women. Thus, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly used for breast lesion detection and diagnosis because of the high resolution of soft tissues. Moreover, supervised detection methods have been implemented for breast lesion detection. However, these methods require substantial time and specialized staff to develop the labeled training samples.

PURPOSE

To investigate the potential of weakly supervised deep learning models for breast lesion detection.

METHODS

A total of 1003 breast DCE-MRI studies were collected, including 603 abnormal cases with 770 breast lesions and 400 normal subjects. The proposed model was trained using breast DCE-MRI considering only the image-level labels (normal and abnormal) and optimized for classification and detection sub-tasks simultaneously. Ablation experiments were performed to evaluate different convolutional neural network (CNN) backbones (VGG19 and ResNet50) as shared convolutional layers, as well as to evaluate the effect of the preprocessing methods.

RESULTS

Our weakly supervised model performed better with VGG19 than with ResNet50 (p < 0.05). The average precision (AP) of the classification sub-task was 91.7% for abnormal cases and 88.0% for normal samples. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.939 (95% confidence interval [CI]: 0.920-0.941). The weakly supervised detection task AP was 85.7%, and the correct location (CorLoc) was 90.2%. A sensitivity of 84.0% at two-false positives per image was assessed based on free-response ROC (FROC) curve.

CONCLUSIONS

The results confirm that a weakly supervised CNN based on self-transfer learning is an effective and promising auxiliary tool for detecting breast lesions.

Delayed Sentinel Lymph Node Dissection in Patients with a Preoperative Diagnosis of Ductal Cancer In Situ by Preoperative Injection with Superparamagnetic Iron Oxide (SPIO) Nanoparticles: The SentiNot Study

BACKGROUND

Difficulty in preoperatively assessing the risk for occult invasion or surgery that precludes future accurate axillary mapping in patients with ductal cancer in situ (DCIS) account for overutilization of SLND.

METHODS

Prospective, multicenter, cohort study, including women with any DCIS planned for mastectomy or DCIS grade 2 and > 20 mm, any DCIS grade 3, any mass-forming DCIS and any planned surgery. Patients received an interstitial SPIO injection during breast surgery, but no upfront SLND was performed. If invasion was identified on final pathology, delayed SLND (d-SLND) was performed separately with the coadministration of isotope ± blue dye (BD). Study outcomes were proportion of upfront SLNDs that were avoided, detection rates during d-SLND, and impact on healthcare costs.

RESULTS

In total, 78.7% of study participants (N = 254, mean age 60 years, mean DCIS size 37.8 mm) avoided upfront SLND. On d-SLND (median 28 days, range 9-46), SPIO outperformed Tc99 with (98.2% vs. 63.6%, p < 0.001) or without BD (92.7% vs. 50.9%, p < 0.001) and had higher nodal detection rate (86.9% vs. 32.3%, p < 0.001) and with BD (93.9% vs. 41.4%, p < 0.001). Only 27.9% of all SLNs retrieved were concordant for Tc99 and SPIO. Type of breast procedure (WLE vs. oncoplastic BCT vs. mastectomy) affected these outcomes and accounted for the low performance of Tc99 (p < 0.001). d-SLND resulted in a 28.1% total cost containment for women with pure DCIS on final pathology (4190 vs. 5828 USD, p < 0.001).

CONCLUSIONS

Marking the SLN with SPIO may avoid overtreatment and allow for accurate d-SLND in patients with DCIS.

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.

Imaging of breast cancer-beyond the basics

Imaging of breast cancer is the backbone of breast cancer screening, diagnosis, preoperative/treatment assessment and follow-up. The main modalities are mammography, ultrasound and magnetic resonance imaging, each with its own advantages and disadvantages. New emerging technologies have also enabled each modality to improve on their weaknesses. Imaging-guided biopsies have allowed for accurate diagnosis of breast cancer, with low complication rates. The purpose of this article is to review the common modalities for breast cancer imaging in current practice with emphasis on the strengths and potential weaknesses, discuss the selection of the best imaging modality for the specific clinical question or patient population, and explore new technologies / future directions of breast cancer imaging.

CEST-MRI for body oncologic imaging: are we there yet?

Chemical exchange saturation transfer (CEST) MRI has gained recognition as a valuable addition to the molecular imaging and quantitative biomarker arsenal, especially for characterization of brain tumors. There is also increasing interest in the use of CEST-MRI for applications beyond the brain. However, its translation to body oncology applications lags behind those in neuro-oncology. The slower migration of CEST-MRI to non-neurologic applications reflects the technical challenges inherent to imaging of the torso. In this review, we discuss the application of CEST-MRI to oncologic conditions of the breast and torso (i.e., body imaging), emphasizing the challenges and potential solutions to address them. While data are still limited, reported studies suggest that CEST signal is associated with important histology markers such as tumor grade, receptor status, and proliferation index, some of which are often associated with prognosis and response to therapy. However, further technical development is still needed to make CEST a reliable clinical application for body imaging and establish its role as a predictive and prognostic biomarker.

Abbreviated Breast MRI: Our Two-Year Initial Experience

OBJECTIVE

The aim of this study was to retrospectively evaluate and present our two-year experience with abbreviated breast MRI at our academic institution as a screening tool to identify primary breast cancers.

METHODS

Employing eight specialty trained breast radiologists, studies were interpreted using the BI-RADS MRI lexicon in this IRB-approved retrospective study. The protocol utilized T1-weighted, fat-saturated, pre- and post-contrast, short  T1 inversion recovery images, and was completed within 10 minutes. Abbreviated breast MRI was offered to asymptomatic women of all breast densities, whose ages ranged from 24 to 90 years. Statistical analysis was performed for comparative data utilizing estimated odds ratios.

RESULTS

Of 1338 patients that met inclusion criteria, 83% (1111/1338) were BI-RADS 1 or 2, 9.0% (121/1338) were BI-RADS 3, and 8% (106/1338) were categorized as either BI-RADS 4 or 5 with recommended biopsy. Biopsy of BI-RADS 4 and 5 categorized patients yielded 15 cancers for a positive predictive value (PPV) 2 of 14.2% and a PPV3 of 18.5%, with 76% (81/106) of patients undergoing the recommended biopsy. An additional cancer was detected in a BI-RADS 3 finding. All cancers detected were in women with heterogeneously dense or extremely dense breasts. Therefore, 16 cancers were detected, yielding a cancer detection rate of 12.0 per 1000. Over the next 12 to 24 months, no interval cancers were detected.

CONCLUSION

Abbreviated breast MRI demonstrates a higher cancer detection rate compared with mammography only and may provide a supplemental screening method to detect breast cancers in patients with varying risk factors.

Prospective Multicenter Diagnostic Performance of Technologist-Performed Screening Breast Ultrasound After Tomosynthesis in Women With Dense Breasts (the DBTUST)

PURPOSE

To assess diagnostic performance of digital breast tomosynthesis (DBT) alone or combined with technologist-performed handheld screening ultrasound (US) in women with dense breasts.

METHODS

In an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant multicenter protocol in western Pennsylvania, 6,179 women consented to three rounds of annual screening, interpreted by two radiologist observers, and had appropriate follow-up. Primary analysis was based on first observer results.

RESULTS

Mean participant age was 54.8 years (range, 40-75 years). Across 17,552 screens, there were 126 cancer events in 125 women (7.2/1,000; 95% CI, 5.9 to 8.4). In year 1, DBT-alone cancer yield was 5.0/1,000, and of DBT+US, 6.3/1,000, difference 1.3/1,000 (95% CI, 0.3 to 2.1; P = .005). In years 2 + 3, DBT cancer yield was 4.9/1,000, and of DBT+US, 5.9/1,000, difference 1.0/1,000 (95% CI, 0.4 to 1.5; P < .001). False-positive rate increased from 7.0% for DBT in year 1 to 11.5% for DBT+US and from 5.9% for DBT in year 2 + 3 to 9.7% for DBT+US (P < .001 for both). Nine cancers were seen only by double reading DBT and one by double reading US. Ten interval cancers (0.6/1,000 [95% CI, 0.2 to 0.9]) were identified. Despite reduction in specificity, addition of US improved receiver operating characteristic curves, with area under receiver operating characteristic curve increasing from 0.83 for DBT alone to 0.92 for DBT+US in year 1 (P = .01), with smaller improvements in subsequent years. Of 6,179 women, across all 3 years, 172/6,179 (2.8%) unique women had a false-positive biopsy because of DBT as did another 230/6,179 (3.7%) women because of US (P < .001).

CONCLUSION

Overall added cancer detection rate of US screening after DBT was modest at 19/17,552 (1.1/1,000; CI, 0.5- to 1.6) screens but potentially overcomes substantial increases in false-positive recalls and benign biopsies.

False-positive incidental lesions detected on contrast-enhanced breast MRI: clinical and imaging features

PURPOSE

To identify demographic and imaging features of MRI-detected enhancing lesions without clinical, ultrasound, and mammographic correlation associated with false-positive outcomes, impacting patient care.

MATERIALS AND METHODS

A retrospective multi-institutional study of imaging studies and patient's chart review of consecutive women with MRI-detected enhancing lesions without clinical, mammogram, or ultrasound correlation between January and December 2018, who underwent MRI-guided biopsy. According to the BI-RADS lexicon, lesions' frequency and imaging features were recorded. The demographic and imaging characteristics variables were correlated with histopathology as the gold standard and an uneventful follow-up of at least one year. Univariate logistic regression analysis was used to explore the correlation between the baseline variables such as age, genetic mutation, family history of breast cancer, personal history of breast cancer, MRI indication, background parenchymal enhancement, and MRI characteristic of the lesion with the false-positive results in main data and subgroup analysis.

RESULTS

Two hundred nineteen women (median age 49 years; range 26-85 years) with 219 MRI-detected enhancing lesions that underwent MRI-guided vacuum-assisted biopsy during the study period fulfilled the study criteria and formed the study cohort. Out of 219, 180 lesions (82.2%) yielded benign pathology results, including 137 benign outcomes (76%) and 43 high-risk lesions (24%). Most demographic and imaging characteristics variables did not help to differentiate malignant from benign lesions. The variables that showed statistically significant association with true-positive results in univariate analyses were age (OR 1.05; 95% CI 1.02-1.08; p = 0.0015), irregular mass-lesion shape when compared with oval/round mass lesion (OR 11.2; 95% CI 1.6-78.4; p = 0.015), and clumped and clustered ring of enhancement when compared with homogeneous (OR 3.22, 95% CI 1.40-7.40; p = 0.0058). For participants with mass breast lesion, the hyperintense signal on the T2-weighted sequence (compared to the normal fibroglandular signal) was significantly related to the false-positive result (OR 0.13; 95% CI 0.02-0.76; p = 0.024).

CONCLUSION

Young patients, oval/round mass-lesion shape, and homogeneous pattern of non-mass enhancement showed the strongest association with false-positive results of enhancing lesions depicted by MRI. For participants with mass breast lesion, T2-bright mass lesion showed significant association with false-positive result. It may impact the patient's management with a suggestion of follow-up rather than interventional procedure when these demographic and imaging parameters are present, consequently decreasing the patient's anxiety and health care costs.

An untrained deep learning method for reconstructing dynamic MR images from accelerated model-based data

PURPOSE

To implement physics-based regularization as a stopping condition in tuning an untrained deep neural network for reconstructing MR images from accelerated data.

METHODS

The ConvDecoder (CD) neural network was trained with a physics-based regularization term incorporating the spoiled gradient echo equation that describes variable-flip angle data. Fully-sampled variable-flip angle k-space data were retrospectively accelerated by factors of R = {8, 12, 18, 36} and reconstructed with CD, CD with the proposed regularization (CD + r), locally low-rank (LR) reconstruction, and compressed sensing with L1-wavelet regularization (L1). Final images from CD + r training were evaluated at the "argmin" of the regularization loss; whereas the CD, LR, and L1 reconstructions were chosen optimally based on ground truth data. The performance measures used were the normalized RMS error, the concordance correlation coefficient, and the structural similarity index.

RESULTS

The CD + r reconstructions, chosen using the stopping condition, yielded structural similarity indexs that were similar to the CD (p = 0.47) and LR structural similarity indexs (p = 0.95) across R and that were significantly higher than the L1 structural similarity indexs (p = 0.04). The concordance correlation coefficient values for the CD + r T1 maps across all R and subjects were greater than those corresponding to the L1 (p = 0.15) and LR (p = 0.13) T1 maps, respectively. For R ≥ 12 (≤4.2 min scan time), L1 and LR T1 maps exhibit a loss of spatially refined details compared to CD + r.

CONCLUSION

The use of an untrained neural network together with a physics-based regularization loss shows promise as a measure for determining the optimal stopping point in training without relying on fully-sampled ground truth data.

Prospective study: Impact of breast magnetic resonance imaging on oncoplastic surgery and on indications of mastectomy in patients who were previously candidates to breast conserving surgery

Background

Routine use of magnetic resonance imaging (MRI) in the staging of patients with early breast cancer is still controversial. Oncoplastic surgery (OP) allows for wider resections without compromising the aesthetic results. This study aimed to assess the impact of preoperative MRI on surgical planning and on indications of mastectomy.

Methods

Prospective study including T1-T2 breast cancer patients treated between January 2019 and December 2020 in the Breast Unit of the Hospital Nossa Senhora das Graças in Curitiba, Brazil. All patients had indication for breast conserving surgery (BCS) with OP and did a breast MRI after conventional imaging.

Results

131 patients were selected. Indication for BCS was based on clinical examination and conventional imaging (mammography and ultrasound) findings. After undergoing breast MRI, 110 patients (84.0%) underwent BCS with OP and 21 (16.0%) had their surgical procedure changed to mastectomy. Breast MRI revealed additional findings in 52 of 131 patients (38%). Of these additional findings, 47 (90.4%) were confirmed as invasive carcinoma. Of the 21 patients who underwent mastectomies, the mean tumor size was 2.9 cm (± 1,7cm), with all having additional findings on breast MRI (100% of the mastectomies group vs 28.2% of the OP, p&lt;0.01). Of the 110 patients submitted to OP, the mean tumor size was 1,6cm (± 0,8cm), with only 6 (5.4%) presenting positive margins at the final pathology assessment.

Conclusion

Preoperative breast MRI has an impact on the OP scenario, bringing additional information that may help surgical planning. It allowed selecting the group with additional tumor foci or greater extension to convert to mastectomy, with a consequent low reoperation rate of 5.4% in the BCS group. This is the first study to assess the impact of breast MRI in the preoperative planning of patients undergoing OP for the treatment of breast cancer.

Magnetic resonance imaging in screening women at high risk of breast cancer: A meta-analysis

BACKGROUND

Magnetic resonance imaging (MRI) is more accurate than mammography in screening for breast cancer. Exposure to ionizing radiation from repeated diagnostic X-rays may be a cause of breast cancer.

METHODS

We conducted systematic searches on PubMed, Cochrane and Embase to identify studies on women who underwent mammography or MRI screening. A meta-analysis was performed to compare the detection rate of breast cancer by mammography, MRI or both.

RESULTS

A total of 18 diagnostic publications were identified and included in the meta-analysis. Among the 1000 screened women, MRI alone increased the detection rate of breast cancer by 8 compared with mammography alone (RR 0.48, 95% CI 0.42-0.54), and MRI plus mammography increased the detection rate of breast cancer by 1 compared with MRI alone (RR 0.86, 95% CI 0.78-0.96). Subgroup analysis demonstrated that the diagnostic efficacy of MRI plus mammography in breast was obviously better than that of MRI alone or mammography alone.

CONCLUSIONS

Screening with MRI alone might be the best choice for women at high risk of breast cancer.

Beyond Breast Density: Risk Measures for Breast Cancer in Multiple Imaging Modalities

Breast density is an independent risk factor for breast cancer. In digital mammography and digital breast tomosynthesis, breast density is assessed visually using the four-category scale developed by the American College of Radiology Breast Imaging Reporting and Data System (5th edition as of November 2022). Epidemiologically based risk models, such as the Tyrer-Cuzick model (version 8), demonstrate superior modeling performance when mammographic density is incorporated. Beyond just density, a separate mammographic measure of breast cancer risk is parenchymal textural complexity. With advancements in radiomics and deep learning, mammographic textural patterns can be assessed quantitatively and incorporated into risk models. Other supplemental screening modalities, such as breast US and MRI, offer independent risk measures complementary to those derived from mammography. Breast US allows the two components of fibroglandular tissue (stromal and glandular) to be visualized separately in a manner that is not possible with mammography. A higher glandular component at screening breast US is associated with higher risk. With MRI, a higher background parenchymal enhancement of the fibroglandular tissue has also emerged as an imaging marker for risk assessment. Imaging markers observed at mammography, US, and MRI are powerful tools in refining breast cancer risk prediction, beyond mammographic density alone.

[MRI-Guided Breast Intervention: Biopsy and Needle Localization]

In Korea, the number of institutions providing breast MRI, as well as the number of breast MRIs, has recently increased. However, MRI-guided procedures, including biopsy and needle localization, are rarely performed compared to ultrasound-guided or stereotactic biopsy. As breast MRI has high sensitivity but limited specificity, lesions detected only on MRI require pathologic confirmation through MRI-guided biopsy or surgical excision with MRI-guided needle localization. Thus, we aimed to review MRI-guided procedures, including their indications, techniques, procedural considerations, and limitations.

Challenges and Changes of the Breast Cancer Screening Paradigm

Since four decades mammography is used for early breast cancer detection in asymptomatic women and still remains the gold standard imaging modality. However, population screening programs can be personalized and women can be divided into different groups based on risk factors and personal preferences. The availability of new and evolving imaging modalities, for example, digital breast tomosynthesis, dynamic-contrast-enhanced magnetic resonance imaging (MRI), abbreviated MRI protocols, diffusion-weighted MRI, and contrast-enhanced mammography leads to new challenges and perspectives regarding the feasibility and potential harms of breast cancer screening. The aim of this review is to discuss the current guidelines for different risk groups, to analyze the recent published studies about the diagnostic performance of the imaging modalities and to discuss new developments and future perspectives. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 6.

Supplemental Breast Cancer Screening in Women with Dense Breasts and Negative Mammography: A Systematic Review and Meta-Analysis

Background The best supplemental breast cancer screening modality in women at average risk or intermediate risk for breast cancer with dense breast and negative mammogram remains to be determined. Purpose To conduct systematic review and meta-analysis comparing clinical outcomes of the most common available supplemental screening modalities in women at average risk or intermediate risk for breast cancer in patients with dense breasts and mammography with negative findings. Materials and Methods A comprehensive search was conducted until March 12, 2020, in Medline, Epub Ahead of Print and In-Process and Other Non-Indexed Citations; Embase Classic and Embase; Cochrane Central Register of Controlled Trials; and Cochrane Database of Systematic Reviews, for Randomized Controlled Trials and Prospective Observational Studies. Incremental cancer detection rate (CDR); positive predictive value of recall (PPV1); positive predictive value of biopsies performed (PPV3); and interval CDRs of supplemental imaging modalities, digital breast tomosynthesis, handheld US, automated breast US, and MRI in non-high-risk patients with dense breasts and mammography negative for cancer were reviewed. Data metrics and risk of bias were assessed. Random-effects meta-analysis and two-sided metaregression analyses comparing each imaging modality metrics were performed (PROSPERO; CRD42018080402). Results Twenty-two studies reporting 261 233 screened patients were included. Of 132 166 screened patients with dense breast and mammography negative for cancer who met inclusion criteria, a total of 541 cancers missed at mammography were detected with these supplemental modalities. Metaregression models showed that MRI was superior to other supplemental modalities in CDR (incremental CDR, 1.52 per 1000 screenings; 95% CI: 0.74, 2.33; P < .001), including invasive CDR (invasive CDR, 1.31 per 1000 screenings; 95% CI: 0.57, 2.06; P < .001), and in situ disease (rate of ductal carcinoma in situ, 1.91 per 1000 screenings; 95% CI: 0.10, 3.72; P < .04). No differences in PPV1 and PPV3 were identified. The limited number of studies prevented assessment of interval cancer metrics. Excluding MRI, no statistically significant difference in any metrics were identified among the remaining imaging modalities. Conclusion The pooled data showed that MRI was the best supplemental imaging modality in women at average risk or intermediate risk for breast cancer with dense breasts and mammography negative for cancer. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Hooley and Butler in this issue.

Clinicopathological and imaging features of ductal carcinoma in situ in BRCA1/2 mutation carriers

BACKGROUND

BRCA1/2-associated invasive breast cancer has been extensively studied. However, there are few reports of ductal carcinoma in situ (DCIS).

OBJECTIVE

This study aimed to investigate the clinicopathological and imaging findings of DCIS in patients with BRCA1/2 mutations.

METHODS

This was a single-institution, retrospective study. We identified patients diagnosed with DCIS with BRCA mutations between September 2003 and December 2020. Clinicopathological data and mammography (MG), magnetic resonance imaging (MRI), and ultrasound (US) findings were reviewed.

RESULTS

We identified 30 cancers in 28 patients; 7 (25.0%) patients had BRCA1 mutations, and 21 (75.0%) had BRCA2 mutations. The median patient age was 42 years. Screening was the most common reason for the detection of DCIS (50.0%), followed by occult cancer diagnosed by pathological examination after risk-reducing mastectomy (26.7%). The nuclear grade was most often 1 (46.7%), and 93.3% were estrogen and/or progesterone receptor positive. The detection rates of MG, MRI, and US were 64.3%, 72.0%, and 64.0%, respectively. The most common imaging findings were calcification (100%) on MG, non-mass enhancement (88.9%) on MRI, and hypoechoic area (75.0%) on US.

CONCLUSION

BRCA-associated DCIS was more strongly associated with BRCA2, and imaging features were similar to those of sporadic DCIS. Our results are helpful in informing surveillance strategies based on genotypes in women with BRCA mutations.

How Radiomics Can Improve Breast Cancer Diagnosis and Treatment

Recent technological advances in the field of artificial intelligence hold promise in addressing medical challenges in breast cancer care, such as early diagnosis, cancer subtype determination and molecular profiling, prediction of lymph node metastases, and prognostication of treatment response and probability of recurrence. Radiomics is a quantitative approach to medical imaging, which aims to enhance the existing data available to clinicians by means of advanced mathematical analysis using artificial intelligence. Various published studies from different fields in imaging have highlighted the potential of radiomics to enhance clinical decision making. In this review, we describe the evolution of AI in breast imaging and its frontiers, focusing on handcrafted and deep learning radiomics. We present a typical workflow of a radiomics analysis and a practical "how-to" guide. Finally, we summarize the methodology and implementation of radiomics in breast cancer, based on the most recent scientific literature to help researchers and clinicians gain fundamental knowledge of this emerging technology. Alongside this, we discuss the current limitations of radiomics and challenges of integration into clinical practice with conceptual consistency, data curation, technical reproducibility, adequate accuracy, and clinical translation. The incorporation of radiomics with clinical, histopathological, and genomic information will enable physicians to move forward to a higher level of personalized management of patients with breast cancer.

MR imaging phenotypes and features associated with pathogenic mutation to predict recurrence or metastasis in breast cancer

OBJECTIVES

Distant metastasis remains the main cause of death in breast cancer. Breast cancer risk is strongly influenced by pathogenic mutation.This study was designed to develop a multiple-feature model using clinicopathological and imaging characteristics adding pathogenic mutations associated signs to predict recurrence or metastasis in breast cancers in high familial risk women.

METHODS

Genetic testing for breast-related gene mutations was performed in 54 patients with breast cancers. Breast MRI findings were retrospectively evaluated in 64 tumors of the 54 patients. The relationship between pathogenic mutation, clinicopathological and radiologic features was examined. The disease recurrence or metastasis were estimated. Multiple logistic regression analyses were performed to identify independent factors of pathogenic mutation and disease recurrence or metastasis. Based on significant factors from the regression models, a multivariate logistic regression was adopted to establish two models for predicting disease recurrence or metastasis in breast cancer using R software.

RESULTS

Of the 64 tumors in 54 patients, 17 tumors had pathogenic mutations and 47 tumors had no pathogenic mutations. The clinicopathogenic and imaging features associated with pathogenic mutation included six signs: biologic features (p = 0.000), nuclear grade (p = 0.045), breast density (p = 0.005), MRI lesion type (p = 0.000), internal enhancement pattern (p = 0.004), and spiculated margin (p = 0.049). Necrosis within the tumors was the only feature associated with increased disease recurrence or metastasis (p = 0.006). The developed modelIincluding clinico-pathologic and imaging factors showed good discrimination in predicting disease recurrence or metastasis. Comprehensive model II, which included parts of modelIand pathogenic mutations significantly associated signs, showed significantly more sensitivity and specificity for predicting disease recurrence or metastasis compared to Model I.

CONCLUSIONS

The incorporation of pathogenic mutations associated imaging and clinicopathological parameters significantly improved the sensitivity and specificity in predicting disease recurrence or metastasis. The constructed multi-feature fusion model may guide the implementation of prophylactic treatment for breast cancers at high familial risk women.

Machine learning analysis of breast ultrasound to classify triple negative and HER2+ breast cancer subtypes

OBJECTIVES

Early diagnosis of triple-negative (TN) and human epidermal growth factor receptor 2 positive (HER2+) breast cancer is important due to its increased risk of micrometastatic spread necessitating early treatment and for guiding targeted therapies. This study aimed to evaluate the diagnostic performance of machine learning (ML) classification of newly diagnosed breast masses into TN versus non-TN (NTN) and HER2+ versus HER2 negative (HER2-) breast cancer, using radiomic features extracted from grayscale ultrasound (US) b-mode images.

MATERIALS AND METHODS

A retrospective chart review identified 88 female patients who underwent diagnostic breast US imaging, had confirmation of invasive malignancy on pathology and receptor status determined on immunohistochemistry available. The patients were classified as TN, NTN, HER2+ or HER2- for ground-truth labelling. For image analysis, breast masses were manually segmented by a breast radiologist. Radiomic features were extracted per image and used for predictive modelling. Supervised ML classifiers included: logistic regression, k-nearest neighbour, and Naïve Bayes. Classification performance measures were calculated on an independent (unseen) test set. The area under the receiver operating characteristic curve (AUC), sensitivity (%), and specificity (%) were reported for each classifier.

RESULTS

The logistic regression classifier demonstrated the highest AUC: 0.824 (sensitivity: 81.8%, specificity: 74.2%) for the TN sub-group and 0.778 (sensitivity: 71.4%, specificity: 71.6%) for the HER2 sub-group.

CONCLUSION

ML classifiers demonstrate high diagnostic accuracy in classifying TN versus NTN and HER2+ versus HER2- breast cancers using US images. Identification of more aggressive breast cancer subtypes early in the diagnostic process could help achieve better prognoses by prioritizing clinical referral and prompting adequate early treatment.