Underwent Breast Magnetic Resonance Imaging Research Articles

Abstract GS03-01: Magnetic Resonance Imaging and a 12-Gene Expression Assay to Optimize Local Therapy for Ductal Carcinoma In Situ: 5-year clinical outcomes of E4112

Abstract BACKGROUND. Advanced diagnostics such as magnetic resonance imaging (MRI) and gene-expression profiles are potentially useful to guide treatment in patients with ductal carcinoma in situ (DCIS). To evaluate these tests, we performed a prospective single arm multicenter study. We have previously reported the impact of MRI on surgical management of DCIS patients, and the effect of a 12-gene DCIS Score (DS) on radiotherapy (RT) use after wide local excision (WLE). We now report a pre-planned analysis of ipsilateral breast events (IBE) at 5-years. METHODS. Adult women with a core needle biopsy diagnosis of DCIS and eligible for WLE based on conventional imaging were registered following consent. All registered patients underwent breast MRI. Those still eligible, and willing, to receive WLE after appropriate follow-up biopsies underwent resection to free margins. DCIS sections were submitted to Exact Sciences for DS. Those with a low DS (< 39) were advised to omit RT; those with intermediate/high (inter/hi) DS (≥39) were advised to receive RT. All participants were monitored at 6-month intervals for any breast cancer event, and for survival. An IBE was defined as the first DCIS or invasive recurrence in the ipsilateral breast following the final WLE. Participants without IBE were censored by date of last contact or date of death for those who died. Follow-up was truncated at 5 years from WLE. Using data available as of 07-06-2023, Kaplan-Meier (K-M) curves were constructed to estimate the time-to-event distributions for subjects who received RT and for those who did not. The 5-year IBE rates and 95% confidence intervals (CIs) were estimated from K-M curves for all subjects with a DS (analogue of Intention to Treat [ITT] analysis), and for the subset who were compliant with their DS-based RT recommendation (Per Protocol analysis). The analyses were repeated for subgroups based on age at DCIS diagnosis (< 50 vs. ≥ 50). RESULTS. Of 339 women evaluable for the previously reported primary analysis (PMID 30653209), 171 (50.4%) underwent WLE with free surgical margins and had DS available for RT recommendations (ITT population). Of these, 7/82 low DS patients underwent RT, and 5/89 inter/hi DS patients declined RT; thus, the adherence to DS-based RT recommendations was 93%. At a median of 5 years of follow-up from final WLE, the ITT population experienced a total of eight IBE events (4.8%, 95% CI 2.4, 9.4) with 5-year IBE rates that were similar for participants with a low DS and for those with a inter/hi DS: 5.1% (95% CI: 1.9, 12.9) and 4.5% (95% CI 1.7, 11.7), respectively. Stratification by age did not alter these results: among women aged < 50 years (n=33), the IBE rate was 6.7% (95% CI 1.0, 38.7) for low DS and 5.6% (95% CI 0.8, 33.4) for inter/hi DS. Among women aged ≥ 50 years (n=138), the IBE rate was 4.7% (95% CI 1.5, 13.8) for low DS and 4.3% (95% CI 1.4, 12.7) for inter/hi DS. In the per-protocol analysis (N=159 adherent to RT recommendations), IBE rates were also similar for participants who had a low DS and no RT [5.5% (95% CI 2.1, 14.1)] and for those with inter/hi DS who received RT [4.8% (95% CI: 1.8% to 12.3%)]. Again, there was no discernible influence by age as categorized above. CONCLUSION. We report the first prospective data on use of DCIS Score for RT decisions, and 5-year IBE rates. We find that DS-based recommendations are followed by >90% of patients. Although the sample size is limited, the data are reassuring in that the IBE rate is similar between the low DS group treated with WLE alone and the inter/hi DS group treated with WLE and radiation, whereas prior studies have shown a marked difference in IBE rates by DS with excision alone. Therefore, this prospective trial provides strong evidence to support the omission of RT after surgery in DCIS patients with low DS, and its use in patients with intermediate/high DS. Citation Format: Seema Khan, Justin Romanoff, Constantine Gatsonis, Habib Rahbar, Ruth Carlos, Sunil Badve, Jean Wright, Constance Lehman, Worta McCaskill-Stevens, Ralph Corsetti, Derrick Spell, Kenneth Blankstein, Linda Han, Jennifer Sabol, John Bumberry, Ilana Gareen, Bradley Snyder, Lynne Wagner, Kathy Miller, Joseph Sparano, Christopher Comstock. Magnetic Resonance Imaging and a 12-Gene Expression Assay to Optimize Local Therapy for Ductal Carcinoma In Situ: 5-year clinical outcomes of E4112 [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr GS03-01.

Diffusion tensor imaging: survival analysis prediction in breast cancer patients.

We aimed to explore the performance of diffusion-tensor imaging (DTI) and apparent diffusion coefficient (ADC) parameters in evaluating disease-free survival (DFS) and overall survival (OS) in patients with invasive breast cancer. Atotal of 49women with invasive breast cancer who were diagnosed between 2017 and 2022 were included. All patients underwent breast magnetic resonance imaging (MRI) with DTI and diffusion-weighted imaging (DWI) features, with examiners blinded to the clinical data. Volume anisotropy (VA), fractional anisotropy (FA), and ADC values were measured to assess intratumoral measured heterogeneity. Correlations and differences in diffusion metrics according to OS and DFS status of the cases were analyzed. The discriminative ability of the quantitative findings was assessed by receiver operating characteristic (ROC) curve analyses and validated in the independent cohort. We evaluated patients with metastases (n = 13, 36.5%) and those without metastases (n = 36, 73.5%). Differences in the ADC, FA, and VA values were observed. The results of Cox regression survival analysis for all the patients included in the survival analysis revealed that DTI metrics contributed to the prediction of overall survival (OS) in the emerging models (p < 0.05). Both FA and VA were associated with OS (p = 0.037 and p = 0.038, respectively). However, ADC was not associated with OS (p = 0.177) or DFS (p = 0.252). To the best of our knowledge, this is the first study to assess the prognostic value of DTI-MRI in breast cancer with statistical survival analysis techniques. We believe that DTI measurements can be used as abiomarker for OS analysis in breast cancer given the available data.

Arterial Supply of the Breast and Nipple-areola Complex: A MRI and Cadaveric Study

Introduction: Preservation of the Nipple-areola Complex (NAC) is currently being attempted for a better aesthetic and functional outcome, necessitating precise knowledge of its vascular supply to minimise postoperative necrosis. Aim: To determine the source, branches, and pattern of arterial supply to breast parenchyma and the NAC using Magnetic Resonance Imaging (MRI) and cadaver. Materials and Methods: The present retrospective observational study was conducted in the Department of Anatomy, AIIMS, New Delhi, India, from March 2015 to October 2016. Total of 50 MRI scan images of female patients who underwent breast MRI as part of their preoperative assessment were collected and retrospectively reviewed. Cadaveric dissection was performed on 11 breasts (5 left and 6 right) obtained from 10 female cadavers with no breast pathology. Radiographic and cadaveric data pertaining to the source, branches, and pattern of arterial supply to breast parenchyma and the NAC were collected. Data was studied using statistical tests like Dunn test followed by Bonferroni correction and Signed-rank test. Results: The MRI scans revealed that most vessels bilaterally supplying the medial half of the breast originate from the Internal Mammary Artery (IMA), while those supplying the lateral half arise from the Lateral Thoracic Artery (LTA), and the branches of IMA were found to be consistently supplying the NAC. Cadaveric dissection confirmed, in all cases except one, that the principal parenchymal and NAC supply on either side arises from the IMA. Conclusion: IMA perforators supply the NAC most consistently and the major part of the breast parenchyma, as well. MRI breast is the most precise modality currently available for the preoperative evaluation of breast vascularity during conservative mastectomies.

Evaluations of the diagnostic performance of ZOOMit diffusion-weighted imaging and conventional diffusion-weighted imaging for breast lesions.

Diffusion-weighted imaging (DWI) is valuable in the screening, diagnosis, and grading of breast lesions. However, conventional DWI (C-DWI) is prone to chemical shift and distortion. ZOOMit DWI (Z-DWI), as an advanced magnetic resonance imaging (MRI) technique, applies two spatially selective parallel excitation pulses to focus sampling in the hope of obtaining more valuable information. This study aimed to evaluate and compare the image quality and feasibility of Z-DWI with those of C-DWI in breast lesions. The study included 51 patients with breast lesions who underwent breast MRI from May 2021 to February 2022. All patients received Z-DWI and C-DWI sequences, with b values selected as 50 and 800 s/mm2 (Z-DWIb50, Z-DWIb800, C-DWIb50, and C-DWIb800). Apparent diffusion coefficient (ADC) values based on Z-DWI and C-DWI were calculated. For qualitative analysis, four image quality parameters were selected and assessed on a 4-point Likert scale (1 = poor and 4 = excellent). For quantitative analysis, ADC, relative ADC (rADC), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and tumor-to-parenchymal contrast (TPC) values were selected for comparison. Z-DWI had higher scores compared to C-DWI in terms of lesion conspicuity, anatomical details, distortion and artifacts, and overall image quality (P<0.05). Meanwhile, the agreement between the two readers was reasonably good [intraclass correlation coefficient (ICC) range, 0.360-0.881]. The SNR of Z-DWIb800 was better than that of C-DWIb800 (P<0.001). The Z-DWI ADC and rADC values of breast lesions were statistically significantly lower than those of C-DWI (mean ADC: P<0.001; rADC; P=0.005). Z-DWI sequences were shown to have superior image quality. The ADC map of Z-DWI is more conducive to the imaging evaluation of breast lesions.

Texture Analysis Using Machine Learning-Based 3-T Magnetic Resonance Imaging for Predicting Pathological Response in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy

Neoadjuvant chemotherapy (NAC) is the standard treatment for large operable or locally advanced breast cancer. Magnetic resonance imaging (MRI) is an important tool to evaluate tumor extent and response to treatment. In the future, surgery may not be required for patients showing pathologic complete response (pCR) after NAC. Therefore, early identification of such patients is crucial for improving and personalizing patient treatment. A total of 90 patients were identified who were diagnosed with invasive breast carcinoma and underwent breast MRI before and after NAC between August 2014 and May 2018. The patients were divided into training group (72 cases) and test group (18 cases). Immunohistochemical data were used to classify breast carcinomas into five molecular subtypes: Luminal A; Luminal B; Her-2 negative; Her-2 positive; or triple-negative and the corresponding surgical specimens were evaluated according to Residual Cancer Burden (RCB) criteria for pathological response. Statistical analyses were conducted using statistical software and statistical significance was defined as P < 0.05. A total of 90 patients with invasive breast carcinoma were enrolled in our study, including 72 patients in training group and 18 patients in test group. The accuracy of molecular subtypes is Luminal A (0.77); Luminal B (0.78); Her-2 negative (0.72); Her-2 positive (0.79); or triple-negative (0.87). Compared with other molecular subtypes, triple-negative show better prediction results (P= 0.028). The accuracy of pathological response is Grade 1 chemotherapy response (0.73); Grade 2 chemotherapy response (0.84); Grade 3 chemotherapy response (0.78); Grade 4 chemotherapy response (0.79); Grade 5 chemotherapy response (0.77). There was no significant difference in chemotherapy response between five groups. The results of this analysis suggested that three negative breast cancer has better prediction effect in magnetic resonance texture analysis for breast cancer patients receiving NAC. However, magnetic resonance texture analysis did not show statistical differences in chemotherapy response. A multicenter randomized controlled prospective trial may be needed.

Evaluation of malignant breast masses with abbreviated breast magnetic resonance imaging

Objectives: Our study aimed to investigate the sensitivity of the abbreviated magnetic resonance imaging (MRI) in the detection of tumors in breast cancer patients. Methods: Patients who underwent breast MRI between March 2018 and October 2021 were reviewed retrospectively. Patients with a histologic diagnosis of breast malignancy were included in the study. Patients who underwent a biopsy or an interventional procedure before the MRI examination and who received neoadjuvant chemotherapy were excluded from the study. Abbreviated MR protocol included a pre-contrast T1-weighted, 1st minute contrast-enhanced T1-weighted, and 1st minute subtracted series. Additionally, 2nd minute post-contrast series were evaluated. Results: A total of 83 lesions with a histologic diagnosis of breast cancer were evaluated in 81 patients. The mean age of the patients included in the study was 51.08 years (range: 27-79 years). Seventy-four of the 83 breast lesions showed contrast enhancement in the 1st minute contrast-enhanced images and subtraction images (sensitivity 89.1%). When missed cases were re-evaluated all of them were visible in the second-minute contrast-enhanced series. Conclusions: In this study, malignant lesions could be detected with high-sensitivity abbreviated MRI protocol and the addition of second-minute contrast-enhanced series to the protocol significantly improve lesion detection. We believe that MRI with the abbreviated MRI protocol can be used for screening purposes in high-risk women with dense breasts.

Triple-negative breast cancer: predictive model of early recurrence based on MRI features

To develop an integrated model based on preoperative magnetic resonance imaging (MRI) features for predicting early recurrence in patients with triple-negative breast cancer (TNBC). Women with TNBC who underwent breast MRI and surgery between 2009 and 2019 were evaluated retrospectively. Two breast radiologists reviewed MRI images independently based on the Breast Imaging Reporting and Data System Lexicon (BI-RADS), and classified the breast oedema scores on T2-weighted imaging (WI) as no oedema, peritumoural oedema, prepectoral oedema, or subcutaneous oedema. The relationship between disease-free survival (DFS) and MRI features was analysed by Cox regression, and a nomogram model was generated based on the results. 150 patients with TNBC were included and divided into a training cohort (n=78) and validation cohort (n=72). MRI features including subcutaneous oedema and rim enhancement showed a tendency to worsen DFS in univariate analysis. Multivariate analysis showed that subcutaneous oedema (p=0.049, HR [95% confidence interval {CI}=8.24 [1.01-67.52]) and rim enhancement (p=0.016, HR [95% CI]=4.38 [1.32-14.54]) were independent predictors for DFS. In the nomogram, the areas under the curves (AUCs) of the training cohort was 0.808, and that of the validation cohort was 0.875. The presence of subcutaneous oedema or rim enhancement on preoperative breast MRI was shown to be a good predictor of poor survival outcomes in patients with TNBC.

Diagnostic efficiency of multi-modal MRI based deep learning with Sobel operator in differentiating benign and malignant breast mass lesions-a retrospective study.

To compare the diagnostic efficiencies of deep learning single-modal and multi-modal for the classification of benign and malignant breast mass lesions. We retrospectively collected data from 203 patients (207 lesions, 101 benign and 106 malignant) with breast tumors who underwent breast magnetic resonance imaging (MRI) before surgery or biopsy between January 2014 and October 2020. Mass segmentation was performed based on the three dimensions-region of interest (3D-ROI) minimum bounding cube at the edge of the lesion. We established single-modal models based on a convolutional neural network (CNN) including T2WI and non-fs T1WI, the dynamic contrast-enhanced (DCE-MRI) first phase was pre-contrast T1WI (d1), and Phases 2, 4, and 6 were post-contrast T1WI (d2, d4, d6); and Multi-modal fusion models with a Sobel operator (four_mods:T2WI, non-fs-T1WI, d1, d2). Training set (n=145), validation set (n=22), and test set (n=40). Five-fold cross validation was performed. Accuracy, sensitivity, specificity, negative predictive value, positive predictive value, and area under the ROC curve (AUC) were used as evaluation indicators. Delong's test compared the diagnostic performance of the multi-modal and single-modal models. All models showed good performance, and the AUC values were all greater than 0.750. Among the single-modal models, T2WI, non-fs-T1WI, d1, and d2 had specificities of 77.1%, 77.2%, 80.2%, and 78.2%, respectively. d2 had the highest accuracy of 78.5% and showed the best diagnostic performance with an AUC of 0.827. The multi-modal model with the Sobel operator performed better than single-modal models, with an AUC of 0.887, sensitivity of 79.8%, specificity of 86.1%, and positive prediction value of 85.6%. Delong's test showed that the diagnostic performance of the multi-modal fusion models was higher than that of the six single-modal models (T2WI, non-fs-T1WI, d1, d2, d4, d6); the difference was statistically significant (p = 0.043, 0.017, 0.006, 0.017, 0.020, 0.004, all were greater than 0.05). Multi-modal fusion deep learning models with a Sobel operator had excellent diagnostic value in the classification of breast masses, and further increase the efficiency of diagnosis.

Correlation of background parenchymal enhancement on breast MRI with breast cancer

To evaluate the prognostic value of background parenchymal enhancement (BPE) in breast magnetic resonance imaging (MRI) in women referred to radiological department as a high risk for breast cancer. A retrospective, cross-sectional study included 327 consecutive patients (mean age: 60 years, age range: 30-90 years) who underwent breast MRI and tissue biopsy between 2007 and 2016. All MRI images (T1, T2, and subtraction images) were evaluated visually. The relationship of BPE with patient age, fibroglandular tissue (FGT), Breast Imaging Reporting and Data System (BIRADS) categories, presence of breast cancer, and expression of human epidermal growth factor receptor 2 (HER2), progesterone receptor (PR), oestrogen receptor (ER), and Ki67 were analysed. Furthermore, all variables were correlated with pre- and postmenopausal status. BPE of bilateral breast showed a weak correlation with FGT (right BPE: r=-0.14, p=0.004; left BPE: r=0.16, p=0.003), a weak negative correlation with patient age (right BPE: r=-0.14, p=0.007; left BPE: r=-0.15, p=0.006), and significant correlation with HER2 (right BPE, p=0.02), left BPE with HER2 was not significant. Among the correlations between BPE and BIRADS, only between right BPE and right BIRADS was significant (p=0.031). No clear evidence of an association between breast MRI BPE and breast cancer in premenopausal and postmenopausal status was observed, and no difference was found between the right and left breasts. The results of the present study showed no significant correlations between BPE and breast cancer. In addition, there was no significant difference between the right and left breast. Hence, BPE of MRI may not be a reliable biomarker of breast cancer development.

The efficiency of volumetric apparent diffusion coefficient histogram analysis in breast papillary neoplasms

Background/Aim: Papillary neoplasia encompasses both malignant and benign lesions, and core needle biopsy (CNB) is crucial in their diagnosis. Histological findings determine their management. Here we compare volumetric apparent diffusion coefficient (ADC) histogram analysis of carcinomas and benign pathologies identified by histopathology from excisional biopsies. Methods: This retrospective study included 524 patients who underwent breast magnetic resonance imaging (MRI) for a suspicious breast mass from January 2018 to October 2022. Patients with benign lesions, incompatible ultrasound-guided CNB results with papillary neoplasia, and those with MRI exams insufficient for diagnosis due to motion artifacts were excluded. After applying the exclusion criteria, the study included 48 patients (average aged 61.5 (14.8) years; range, 31 to 72 years). After excisional biopsies, 30 benign lesions and 18 carcinomas were identified. MRI was acquired at 1.5 T (Verio; Siemens Medical Solutions, Erlangen, Germany), and the b-values for diffusion-weighted imaging were calculated at 1000 s/mm2. Histogram parameters were computed. Receiver operating characteristic (ROC) curve analysis was performed to investigate diagnostic accuracy, evaluate histogram analysis performance, and determine threshold values. Results: The ADCmin, ADCmean, ADCmax, and all ADC value percentiles were significantly lower in the carcinoma group than in the benign group (P&lt;0.001). The variance, skewness, and kurtosis were higher in the carcinoma group. ADCmax had the highest area under the curve (AUC: 0.985; cut-off 1.247 × 10-3 mm2/s; sensitivity 86%, and specificity 92%), followed by ADCmean (AUC: 0.950; cut-off 0.903 × 10-3 mm2/s; sensitivity 94%, and specificity 96%). Conclusion: Volumetric ADC histogram analysis of papillary neoplasia at higher b-values can be an imaging marker to detect carcinoma and quantitatively reveal the lesions’ diffusion characteristics.

Diagnostic value of combined use of abbreviated breast MRI and diffusion-weighted MRI in the prediction of breast cancer

Purpose: The aim of this study was to compare the diagnostic performances of abbreviated protocol (AP) magnetic resonance imaging (MRI), AP combined with diffusion-weighted imaging (DWI), and full dynamic protocol (FDP) in the differentiation of breast cancers from benign breast diseases.&#x0D; Materials and Methods: The total study population consisted of 68 patients who underwent breast MRI (1.5 Tesla) between January 2016 and December 2021 for the evaluation of suspicious findings on mammography or ultrasonography. All lesions were evaluated by 2 radiologists using AP, AP+DWI, and FDP. The reader sensitivity, specificity, and accuracy were analyzed using the “Chi-squared” test. The inter-observer agreement (IOA) between the Breast Imaging Reporting and Data System (BI-RADS) category assessments of the two readers was evaluated by using the “Kappa statistics”.&#x0D; Results: Sixty-eight patients with 72 lesions (31 malignant and 41 benign) were analyzed. The sensitivity/specificity for AP and AP+DWI for reader 1 was 67.7/90.2% and 80.6/87.8%, respectively, and for reader 2 was 67.7/92.6% and 70.9/90.2%, respectively. The sensitivity/specificity for FDP for reader 1 was 83.7/85.3% and for reader 2 was 80.6/90.2%. The IOA in the BI-RADS category assessment was almost perfect in all models between two readers (the kappa value was 0.907, 0.825, and 0.858 in AP, AP+DWI, and FDP, respectively).&#x0D; Conclusion: FDP showed greater diagnostic efficiency in the characterization of tumor biology as compared to AP and AP +DWI. Combining AP with DWI improved the diagnostic performance of MRI for the determination of malignancy.

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.

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. 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. 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 2.9cm (± 1,7cm), with all having additional findings on breast MRI (100% of the mastectomies group vs 28.2% of the OP, p<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. 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.

Abstract PD16-01: Racial Disparities in the Use of Preoperative Breast MRI after Breast Cancer Diagnosis

Abstract Introduction: The use of magnetic resonance imaging (MRI) prior to surgical treatment for breast cancer has greatly increased over the past decade. As MRI more accurately defines disease extent vs mammography and sonography, it is frequently utilized for staging women at elevated risk of occult disease due to young age, dense breast tissue, and/or lobular histology. However, it is not known whether women from different racial backgrounds and socioeconomic statuses have equal access to preoperative breast MRI. The goal of this study was to assess whether the use of preoperative breast MRI varies by race and insurance type. Methods: We identified adult women who were diagnosed with Stage 0-III breast cancer within our mixed academic/community health system between 2016-2019 and were subsequently treated with surgical resection. We limited our analysis to non-Hispanic Black and non-Hispanic White women, as they comprised 93% of the eligible cohort. Patients who underwent breast MRI between their date of diagnosis and date of surgery were considered to have had a “preoperative MRI.” We used multivariable logistic regression to quantify the association between patient factors and receipt of preoperative MRI. Covariates included patient race, insurance type, age, year of diagnosis, clinical stage, histology, breast density, receptor subtype, and receipt of neoadjuvant systemic therapy. Results: 1,268 women met inclusion criteria and had complete clinical information available for analysis. 362 (29%) were Black, and 906 (71%) were White. 718 (57%) had private insurance, 460 (36%) had Medicare, and 72 (6%) had Medicaid. Compared to White patients, a larger proportion of Black patients had Medicaid (15% vs. 2.0%), fatty or scattered density (i.e., level 1 or 2) breasts (69% vs 48%), and regional disease (26% vs 19%) (Table). Patients with Medicare had the highest proportion of fatty or scattered density breasts (67% vs private=46% vs Medicaid=56%), while patients with Medicaid had the highest proportion of regional disease (35% vs private=23% vs Medicare=15%). The proportion of patients who received preoperative MRI was higher for White (49%) vs Black women (37%, p&amp;lt; 0.001). After adjustment, Black patients were 52% less likely to undergo preoperative MRI compared to White patients (OR 0.48, 95% CI 0.35-0.66, p&amp;lt; 0.001). Compared to privately-insured patients, patients with Medicare had a similar likelihood of undergoing preoperative MRI (OR 0.81, 95% CI 0.54-1.22, p=0.309), while patients with Medicaid may have had a lower likelihood of undergoing preoperative MRI (OR 0.55, 95% CI 0.30-1.00, p=0.053). Conclusions: Black patients with newly diagnosed breast cancer were less likely than White patients to undergo preoperative breast MRI, a disparity that persisted after controlling for insurance and clinical factors. Algorithmic use of preoperative MRI may mitigate provider- and system-level biases and promote more equitable resource utilization. Table 1: Characteristics of patients with non-metastatic breast cancer, diagnosed and treated at our institution (2016-2019) *Biomarker data for 2019 cohort is pending Citation Format: Sara P. Ginzberg, Connor B. Grady, Oluwadamilola (Lola) Fayanju, Christine E. Edmonds. Racial Disparities in the Use of Preoperative Breast MRI after Breast Cancer Diagnosis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD16-01.

How to optimize breast MRI protocol? The value of combined analysis of ultrafast and diffusion-weighted MRI sequences

PurposeThe purpose of this retrospective study was to demonstrate the validity of early enhancement criteria on ultrafast magnetic resonance imaging (MRI) sequence to predict malignancy in a large population, and the benefit of diffusion-weighted imaging (DWI) to improve the performance of breast MRI. Material and methodsWomen who underwent breast MRI examination between April 2018 and September 2020 and further breast biopsy were retrospectively included. Two readers quoted the different conventional features and classified the lesion according to the BI-RADS classification based on the conventional protocol. Then, the readers checked for the presence of early enhancement (≤ 30 s) on ultrafast sequence and the presence of an apparent diffusion coefficient (ADC) ≥ 1.5 × 10−3 mm2/s to classify the lesions based on morphology and these two functional criteria only. ResultsTwo hundred fifty-seven women (median age: 51 years; range: 16–92 years) with 436 lesions (157 benign, 11 borderline and 268 malignant) were included. A MRI protocol plus two simple functional features, early enhancement (≤ 30 s) and an ADC value ≥ 1.5 × 10−3 mm2/s, had a greater accuracy than the conventional protocol to distinguish benign from malignant breast lesions with or without ADC value (P = 0.01 and P = 0.001, respectively) on MRI, mainly due to better classification of benign lesions (increased specificity) with increasing diagnostic confidence of 3.7% and 7.8% respectively. ConclusionBI-RADS analysis based on a simple short MRI protocol plus early enhancement on ultrafast sequence and ADC value has a greaterr diagnostic accuracy than a conventional protocol and may avoid unnecessary biopsy.

Genetic Counseling, Screening and Risk-Reducing Surgery in Patients with Primary Breast Cancer and Germline BRCA Mutations: Unmet Needs in Low- and Middle-Income Countries.

Worldwide genetic counseling practices are variable and often not reported in low- and middle-income countries (LMICs). We present the follow-up genetic counseling, breast screening, risk-reducing salpingo-oophorectomy (RRSO) and contralateral prophylactic mastectomy (CPM) in a cohort of study patients with either BRCA pathogenic mutations or BRCA variant of unknown significance (VUS). Chart review and phone calls for the collection of information. Out of a cohort of 250 patients, 14 had deleterious mutations and 31 had a VUS, of whom 19 had primary early breast cancer. We collected information about genetic counseling, screening, CPM and RRSO. Fourteen patients with deleterious mutations (7 BRCA1 and 7 BRCA2) and 19 patients with VUS mutations (20 VUS, 4 BRCA1, 16 BRCA2; 1 patient had both) were surveyed. Of 14 patients with deleterious BRCA mutations, 57.14% (8/14 patients) received genetic counseling from their oncologist. Subsequently 85.71% (12/14) are undergoing mammography screening and 35.71% (5/14) breast screening magnetic resonance imaging (MRI). Furthermore, 50% of them underwent CPM and 57.14% underwent RRSO. Of 19 patients with VUS mutations, 10.5% received genetic counseling from their oncologist; 78.9% were undergoing regular screening mammogram and 31.5% were undergoing breast MRI; one patient underwent CPM and two patients RRSO. Within three years from knowing they have a mutation, 50% of patients with germline BRCA mutations had undergone CPM and 60% RRSO, the majority of them had screening mammography surveillance but only 50% had screening MRI. Follow-up of patients with VUS with mammography was 78% but MRI was only 31%. Lack of MRI surveillance reflects both limited resources and insufficient counseling. Genetic counseling was done by medical oncologists, which reflects a trend in LMIC. Our Data shows the importance of the need for professional genetic counselors and optimal surveillance in Lebanon and other LMICs.

Modelling level I Axillary Lymph Nodes depth for Microwave Imaging

Purpose:Patient-specific information on the depth of Axillary Lymph Nodes (ALNs) is important for the development of new diagnostic imaging technologies, e.g. Microwave Imaging (MWI), aiming to assess the diagnosis of ALNs during breast cancer staging. Studies about ALNs depth have been presented for treatment planning, but they lack information on sample size and usability of the data to infer the depth of ALNs. The aim of this study was to create a mathematical model that can be used to predict a depth interval where level I ALNs are likely to be located. Methods:We extracted biometric features of 98 patients who underwent breast Magnetic Resonance Imaging (MRI) to train two types of regression models. We then tested different combination of features to predict ALNs depth and found the best predictor. The final prediction models were then implemented in an algorithm used for MWI and tested with anthropomorphic phantoms of the axillary region. Results:Body Mass Index (BMI) was the feature with best performance to predict ALNs depth with coefficient of determination (R2) ranging from 0.49 to 0.55 and Root Mean Squared Error (RMSE) ranging from 0.68 to 0.91 cm. The proposed model showed satisfactory results in microwave images of patients with different BMIs. Conclusions:The presented results contribute to the development of reconstruction algorithms for new imaging technologies and to the assessment of ALNs in other medical applications.

Application of the Kaiser score by MRI in patients with breast lesions by ultrasound and mammography.

PURPOSE This study aimed to verify whether the use of the Kaiser score can improve the diagnostic performance in breast magnetic resonance imaging (MRI) for suspicious lesions and avoid further invasive diagnostic approaches. METHODS This retrospective study enrolled 97 patients who underwent breast MRI before undergoing breast biopsy or surgery. Evaluations were conducted on all MRI images individually by 2 radiologists using the Kaiser score. Neither radiologist had the knowledge of the final histopathological diagnosis. The ability of the Kaiser score in diagnosis was established via a receiver performing characteristic (ROC) analysis, which was measured by the area under the ROC curve (AUC). Youden index was used to define the optimal cutoff value. Kaiser score categories were dichotomized into positive (cutoff score > 4) and negative scores (cutoff score ≤ 4). Cohen's kappa coefficient was used to analyze the inter-rater agreement. RESULTS Histopathology revealed 56 malignant and 41 benign lesions. The AUC for all lesions evaluated by the Kaiser score was 0.992 (95% CI: 0.981-1.0) and 0.958 (95% CI: 0.920-0.996) for 2 radiologists, respectively. Inter-rater agreement of the dichotomized Kaiser score was excellent (κ=0.894, P < .001). A total of 20 lesions (33.8%) previously categorized as BI-RADS 4 were reduced to BI-RADS 2/3 (19 benign lesions and 1 malignant lesion). CONCLUSION The Kaiser score is a valuable auxiliary diagnostic tool for improving the diagnostic ability of radiologists, whose experiences in breast MRI are diverse. In some cases, the application of the Kaiser score could possibly avoid unnecessary breast biopsies.

FAST breast magnetic resonance imaging: a new approach for breast cancer screening?

ABSTRACTObjective To develop an abbreviated breast magnetic resonance imaging protocol (FAST) and to compare it with the complete protocol (FULL) to determine its diagnostic accuracy for detecting malignant or suspicious lesions (BI-RADS 4, 5 and 6) and the time required for image interpretation using BI-RADS categorization.Methods Retrospective study with 100 consecutive women who underwent breast magnetic resonance imaging between January and February 2014. All patients were submitted to a complete breast magnetic resonance imaging protocol, which was then compared with an abbreviated protocol (pre-contrast sequence, second post-contrast sequence and subtraction of pre- from post-contrast images).Results Of 100 patients, 4 were classified as BI-RADS 5 or 6 and 16 as BI-RADS 4. In these 20 patients, there was full agreement among readers regarding the final BI-RADS categorization in both (FAST and FULL) protocols.Conclusion The FAST protocol reduces interpretation time without compromising the accuracy of the method for detection of malignant or suspicious lesions.

Value of magnetic resonance diffusion combined with perfusion imaging techniques for diagnosing potentially malignant breast lesions.

BACKGROUNDLesions of breast imaging reporting and data system (BI-RADS) 4 at mammography vary from benign to malignant, leading to difficulties for clinicians to distinguish between them. The specificity of magnetic resonance imaging (MRI) in detecting breast is relatively low, leading to many false-positive results and high rates of re-examination or biopsy. Diffusion-weighted imaging (DWI), combined with perfusion-weighted imaging (PWI), might help to distinguish between benign and malignant BI-RADS 4 breast lesions at mammography.AIMTo evaluate the value of DWI and PWI in diagnosing BI-RADS 4 breast lesions.METHODSThis is a retrospective study which included patients who underwent breast MRI between May 2017 and May 2019 in the hospital. The lesions were divided into benign and malignant groups according to the classification of histopathological results. The diagnostic efficacy of DWI and PWI were analyzed respectively and combinedly. The 95 lesions were divided according to histopathological diagnosis, with 46 benign and 49 malignant. The main statistical methods used included the Student t-test, the Mann-Whitney U-test, the chi-square test or Fisher’s exact test. RESULTSThe mean apparent diffusion coefficient (ADC) values in the parenchyma and lesion area of the normal mammary gland were 1.82 ± 0.22 × 10-3 mm2/s and 1.24 ± 0.16 × 10-3 mm2/s, respectively (P = 0.021). The mean ADC value of the malignant group was 1.09 ± 0.23 × 10-3 mm2/s, which was lower than that of the benign group (1.42 ± 0.68 × 10-3 mm2/s) (P = 0.016). The volume transfer constant (Ktrans) and rate constant (Kep) values were higher in malignant lesions than in benign ones (all P < 0.001), but there were no significant statistical differences regarding volume fraction (Ve) (P = 0.866). The sensitivity and specificity of PWI combined with DWI (91.7% and 89.3%, respectively) were higher than that of PWI or DWI alone. The accuracy of PWI combined with DWI in predicting pathological results was significantly higher than that predicted by PWI or DWI alone.CONCLUSIONDWI, combined with PWI, might possibly distinguish between benign and malignant BI-RADS 4 breast lesions at mammography.

Association between contralateral background parenchymal enhancement on MRI and outcome in patients with unilateral invasive breast cancer receiving neoadjuvant chemotherapy

PurposeThe purpose of this study was to retrospectively investigate whether background parenchymal enhancement (BPE) of the contralateral breast on magnetic resonance imaging (MRI) is associated with clinical outcomes in patients with unilateral invasive breast cancer receiving neoadjuvant chemotherapy (NAC). Materials and methodsA total of 228 women (47.6 years ± 10 [SD]; range: 24–74 years) with invasive breast cancer who underwent NAC between 2005 and 2013 were included. All included patients underwent breast MRI before and after NAC. Quantitative semiautomated analysis of BPE of the contralateral healthy breast was performed. The enhancement level on baseline MRI (baseline BPE) and on MRI after chemotherapy (final BPE) and the change in enhancement rate between baseline MRI and final MRI were recorded. Cox regression was used to test associations between BPE variables, patient and tumor characteristics, overall survival (OS) and disease–free survival (DFS). Subgroup analyses based on menopausal status and immunohistochemical subtypes were performed. ResultsMedian follow-up was 92 months. Multivariable analysis revealed that Ki-67 level (P = 0.026) and receipt of mastectomy (P = 0.015) were independent variables associated with OS while Ki-67 level (P = 0.010) and post-NAC pathological node categorization (P = 0.027) were independent variables associated with DFS. BPE was not associated with OS (P = 0.500, 0.546 and 0.712 for baseline BPE, final BPE and BPE change, respectively) or with DFS (P = 0.568, 0.412 and 0.327, respectively). ConclusionBPE of the contralateral breast on MRI may have limited prognostic value in patients with breast cancer treated with NAC.