Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery.

Significance: Hyperspectral dark-field microscopy (HSDFM) and data cube analysis algorithms demonstrate successful detection and classification of various tissue types, including carcinoma regions in human post-lumpectomy breast tissues excised during breast-conserving surgeries. Aim: We expand the application of HSDFM to the classification of tissue types and tumor subtypes in pre-histopathology human breast lumpectomy samples. Approach: Breast tissues excised during breast-conserving surgeries were imaged by the HSDFM and analyzed. The performance of the HSDFM is evaluated by comparing the backscattering intensity spectra of polystyrene microbead solutions with the Monte Carlo simulation of the experimental data. For classification algorithms, two analysis approaches, a supervised technique based on the spectral angle mapper (SAM) algorithm and an unsupervised technique based on the K-means algorithm are applied to classify various tissue types including carcinoma subtypes. In the supervised technique, the SAM algorithm with manually extracted endmembers guided by H&E annotations is used as reference spectra, allowing for segmentation maps with classified tissue types including carcinoma subtypes. Results: The manually extracted endmembers of known tissue types and their corresponding threshold spectral correlation angles for classification make a good reference library that validates endmembers computed by the unsupervised K-means algorithm. The unsupervised K-means algorithm, with no a priori information, produces abundance maps with dominant endmembers of various tissue types, including carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma. The two carcinomas' unique endmembers produced by the two methods agree with each other within <2% residual error margin. Conclusions: Our report demonstrates a robust procedure for the validation of an unsupervised algorithm with the essential set of parameters based on the ground truth, histopathological information. We have demonstrated that a trained library of the histopathology-guided endmembers and associated threshold spectral correlation angles computed against well-defined reference data cubes serve such parameters. Two classification algorithms, supervised and unsupervised algorithms, are employed to identify regions with carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma present in the tissues. The two carcinomas' unique endmembers used by the two methods agree to <2% residual error margin. This library of high quality and collected under an environment with no ambient background may be instrumental to develop or validate more advanced unsupervised data cube analysis algorithms, such as effective neural networks for efficient subtype classification.

The Impact of Mammographic, Radiologist, and Patient Factors on the Likelihood of Probably Benign (BI-RADS 3) Assessment at Diagnostic Mammography.

OBJECTIVE: To evaluate the association of mammographic, radiologist, and patient factors on BI-RADS 3 assessment at diagnostic mammography in patients recalled from screening mammography. METHODS: This Institutional Review Board-approved retrospective study of consecutive unique diagnostic mammography examinations in asymptomatic patients recalled from screening mammography March 5, 2014, to December 31, 2019, was conducted in a single large United States health care institution. Mammographic features (mass, calcification, distortion, asymmetry), breast density, prior examination, and BI-RADS assessment were extracted from reports by natural language processing. Patient age, race, and ethnicity were extracted from the electronic health record. Radiologist years in practice, recall rate, and number of interpreted diagnostic mammograms were calculated. A mixed effect logistic regression model evaluated factors associated with likelihood of BI-RADS 3 compared with other BI-RADS assessments. RESULTS: A total of 12 080 diagnostic mammography examinations were performed during the study period, yielding 2010 (16.6%) BI-RADS 3 and 10 070 (83.4%) other BI-RADS assessments. Asymmetry (odds ratio [OR] = 6.49, P <.001) and calcification (OR = 5.59, P <.001) were associated with increased likelihood of BI-RADS 3 assessment; distortion (OR = 0.20, P <.001), dense breast parenchyma (OR = 0.82, P <.001), prior examination (OR = 0.63, P = .01), and increasing patient age (OR = 0.99, P <.001) were associated with decreased likelihood. Mass, patient race or ethnicity, and radiologist factors were not significantly associated with BI-RADS 3 assessment. Malignancy rate for BI-RADS 3 lesions was 1.6%. CONCLUSION: Asymmetry and calcifications had an increased likelihood of BI-RADS 3 assessment at diagnostic evaluation with low likelihood of malignancy, while radiologist features had no association.

A color-based tumor segmentation method for clinical ex vivo breast tissue assessment utilizing a multi-contrast brightfield imaging strategy.

We demonstrate an automated two-step tumor segmentation method leveraging color information from brightfield images of fresh core needle biopsies of breast tissue. Three different color spaces (HSV, CIELAB, YCbCr) were explored for the segmentation task. By leveraging white-light and green-light images, we identified two different types of color transformations that could separate adipose from benign and tumor or cancerous tissue. We leveraged these two distinct color transformation methods in a two-step process where adipose tissue segmentation was followed by benign tissue segmentation thereby isolating the malignant region of the biopsy. Our tumor segmentation algorithm and imaging probe could highlight suspicious regions on unprocessed biopsy tissue to guide selection of areas most similar to malignant tissues for tissue pathology whether it be formalin fixed or frozen sections, expedite tissue selection for molecular testing, detect positive tumor margins, or serve an alternative to tissue pathology, in countries where these services are lacking.

Biopathologic Characterization and Grade Assessment of Breast Cancer With 3-D Multiparametric Ultrasound Combining Shear Wave Elastography and Backscatter Tensor Imaging.

OBJECTIVE: Despite recent improvements in medical imaging, the final diagnosis and biopathologic characterization of breast cancers currently still requires biopsies. Ultrasound is commonly used for clinical examination of breast masses. B-Mode and shear wave elastography (SWE) are already widely used to detect suspicious masses and differentiate benign lesions from cancers. But additional ultrasound modalities such as backscatter tensor imaging (BTI) could provide relevant biomarkers related to tissue organization. Here we describe a 3-D multiparametric ultrasound approach applied to breast carcinomas in the aims of (i) validating the ability of BTI to reveal the underlying organization of collagen fibers and (ii) assessing the complementarity of SWE and BTI to reveal biopathologic features of diagnostic interest. METHODS: Three-dimensional SWE and BTI were performed ex vivo on 64 human breast carcinoma samples using a linear ultrasound probe moved by a set of motors. Here we describe a 3-D multiparametric representation of the breast masses and quantitative measurements combining B-mode, SWE and BTI. RESULTS: Our results reveal for the first time that BTI can capture the orientation of the collagen fibers around tumors. BTI was found to be a relevant marker for assessing cancer stages, revealing a more tangent tissue orientation for in situ carcinomas than for invasive cancers. In invasive cases, the combination of BTI and SWE parameters allowed for classification of invasive tumors with respect to their grade with an accuracy of 95.7%. CONCLUSION: Our results highlight the potential of 3-D multiparametric ultrasound imaging for biopathologic characterization of breast tumors.

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.

Artificial Intelligence-Enhanced Breast MRI: Applications in Breast Cancer Primary Treatment Response Assessment and Prediction.

ABSTRACT: Primary systemic therapy (PST) is the treatment of choice in patients with locally advanced breast cancer and is nowadays also often used in patients with early-stage breast cancer. Although imaging remains pivotal to assess response to PST accurately, the use of imaging to predict response to PST has the potential to not only better prognostication but also allow the de-escalation or omission of potentially toxic treatment with undesirable adverse effects, the accelerated implementation of new targeted therapies, and the mitigation of surgical delays in selected patients. In response to the limited ability of radiologists to predict response to PST via qualitative, subjective assessments of tumors on magnetic resonance imaging (MRI), artificial intelligence-enhanced MRI with classical machine learning, and in more recent times, deep learning, have been used with promising results to predict response, both before the start of PST and in the early stages of treatment. This review provides an overview of the current applications of artificial intelligence to MRI in assessing and predicting response to PST, and discusses the challenges and limitations of their clinical implementation.

Triple assessment breast clinics: The value of clinical core biopsies.

BACKGROUND: Triple Assessment Breast Clinics are designed for rapid diagnosis of symptomatic patients. When there is no concordance between clinical and radiological assessment, clinicians perform clinical core biopsies. In patients with a clinically suspicious examination (S4, S5) and normal imaging, clinically guided core biopsy should be performed as per NCCP guidelines. However, substantial research does not exist on the diagnostic value or use of clinical core biopsies in non-suspicious palpable (S3) lesions and practices differ in each health system. AIMS: The aim of this research was to assess the diagnostic value of clinical core biopsies in nonsuspicious, probably benign palpable breast lesions (S3) where image guided cores were not indicated (R1/R2). METHODS: The cohort consisted of patients undergoing clinical core biopsies at a Symptomatic Breast Unit from January 2014 to 2019. Data regarding patient demographics, outcome of triple-assessment and incidence of malignancy were obtained from a prospectively maintained database and results were analysed using Minitab 2018. RESULTS: Three hundred and sixty patients had a clinical core biopsy performed in this period. Clinical examination scores for these patients were S1/S2 (66), S3 (277), S4 (15), and S5 (2). Radiology Scores were R1/R2 (355) and R3(5). Two patients with clinical score S3 (0.6%) were diagnosed with breast cancer due to their clinical cores. Both patients had normal mass imaging. There was no association between uncertain palpable breast lesions (S3), and atypia or malignancy on biopsy results when breast imaging was normal (P = 0.43, χ2 test). CONCLUSION: Despite clinical core biopsies being used in triple assessment, there is no certainty in their value except that there is high clinical suspicion. Imaging modalities are constantly improving and are already well established. When the patient is assigned a clinical score of S3 and has normal radiology, a clinical core biopsy is not required in most cases.

The value of Demetics ultrasound-assisted diagnosis system in diagnosis of breast lesions and in assessment Ki-67 status of breast cancer.

PURPOSE: This study aims to explore the diagnostic efficiency of the Demetics for breast lesions and assessment of Ki-67 status. MATERIAL: This retrospective study included 291 patients. Three combined methods (method 1: upgraded BI-RADS when Demetics classified the breast lesion as malignant; method 2: downgraded BI-RADS when Demetics classified the breast lesion as benign; method 3: BI-RADS was upgraded or downgraded according to Demetrics' diagnosis) were used to compare the diagnostic efficiency of two radiologists with different seniority before and after using Demetics. The correlation between the visual heatmap by Demetics and the Ki-67 expression level of breast cancer was explored. RESULTS: The sensitivity, specificity, and area under curve (AUC) of diagnosis by Demetics, junior radiologist and senior radiologist were 89.5%, 83.1%, 0.863; 76.9%, 82.4%, 0.797 and 81.1%, 89.9%, 0.855, respectively. Method 1 was the best for senior radiologist, which increased AUC from 0.855 to 0.884. For junior radiologist, Method 3 was the best method, improving sensitivity (88.8% vs. 76.9%) and specificity (87.2% vs. 82.4%). Demetics paid more attention to the peripheral area of breast cancer with high expression of Ki-67. CONCLUSION: Demetics has shown good diagnostic efficiency in the assisted diagnosis of breast lesions and is expected to further distinguish Ki-67 status of breast cancer.

The Effect of Intraoperative Margin Assessment During Breast Conserving Surgery for Breast Cancer in a Dutch Cohort.

INTRODUCTION: Intraoperative specimen radiography is a routinely used procedure to ensure adequate resection of non-palpable breast tumors. Intraoperative digital specimen mammography (IDSM) is an alternative to conventional specimen radiography (CSR) which provides immediate specimen evaluation and can potentially decrease operation time. IDSM may also result in lower positive margin and re-excision rates. IDSM was implemented in our hospital in 2018. The objective of this study was to evaluate the effect of using IDSM versus CSR on operation time, margin status and re-excision rates in breast conserving surgery. METHODS: The present study is a single-center retrospective cohort study with 2 patient cohorts: one which underwent CSR (n = 532) and one which underwent IDSM (n = 475). The primary outcome was the operation time. Secondary outcomes were the margin status of the primary surgery, the cavity shaving rate, and the re-excision rate. Differences between cohorts were compared using univariate statistics and multiple regression analyses to adjust for variables that were significantly different between the groups. RESULTS: IDSM use was associated with an 8-minute reduction in surgery time (B = -8.034, 95% CI [-11.6, -4.5]; P < .001). Treatment variables independently associated with the operation time included use of IDSM, type of surgery, and performance of cavity shaving. Cavity shaves were more often performed when IDSM was used (24% for IDSM vs. 14% for CSR, P < .001), while the proportion of negative margin rates (93% for IDSM vs. 96% for CSR, P = .070) was comparable. CONCLUSION: IDSM was associated with a modest reduction in operation time. Surgeons performed more cavity shaves since the introduction of IDSM, but this increase was not reflected by difference in negative margin rates.

Cytomorphological Assessment in Aspirates of Ductal Carcinoma in situ: Correlations with Histopathologic Grade, Architectural Pattern, and Invasion.

INTRODUCTION: Fine-needle aspiration biopsy (FNAB) of the breast is an effective and widely adopted diagnostic technique. Histopathologic grading of ductal carcinoma in situ (DCIS) has prognostic significance. In this current study, FNAB of DCIS was reviewed to identify parameters that predict grading, histopathologic architecture, and presence of invasion in DCIS. METHODS: Aspirates from histopathology-proven cases of DCIS were retrieved and reviewed for cytomorphologic parameters including cellularity, composition, epithelial fragment architecture cellular/nuclear features. RESULTS: In total 104 aspirates were reviewed. Cytopathologic cellular features - large nuclear size (p = 0.005), prominent nucleoli (p = 0.011), increased nuclear membrane irregularity (p = 0.043), high variation in nuclear size (p = 0.025), and presence of apoptotic figures in epithelial structures (p < 0.001); and background debris (p = 0.033) correlated with a high-grade diagnosis. Cytoplasmic vacuolation (p = 0.034) was seen exclusively in non-high-grade aspirates. Epithelial fragment architecture did not correlate with grading. A predominance (≥50%) of solid aggregates and papillary fragments on FNAB correlated with histopathologically solid (p = 0.039, p = 0.005) and papillary (p = 0.029, < p = 0.001) patterns. No parameter showed correlation with invasion. CONCLUSION: FNAB is effective in predicting DCIS grading. Epithelial fragment architecture assessment is limited to papillary or solid types, and FNAB cannot predict focal invasion in DCIS.

High Peritumoral and Intratumoral T2 Signal Intensity in HER2-Positive Breast Cancers on Preneoadjuvant Breast MRI: Assessment of Associations With Histopathologic Characteristics.

BACKGROUND. Intratumoral necrosis and peritumoral edema are features of aggressive breast cancer that may present as high T2 signal intensity (T2 SI). Implications of high T2 SI in HER2-positive cancers are unclear. OBJECTIVE. The purpose of this study was to assess associations with histopathologic characteristics of high peritumoral T2 SI and intratumoral T2 SI of HER2-positive breast cancer on MRI performed before initiation of neoadjuvant therapy. METHODS. This retrospective study included 210 patients (age, 24-82 years) with 211 HER2 breast cancers who, from January 1, 2015, to July 30, 2022, underwent breast MRI before receiving neoadjuvant therapy. Two radiologists independently assessed cancers for high peritumoral T2 SI and high intratumoral T2 SI on fat-suppressed T2-weighted imaging and classified patterns of high peritumoral T2 SI (adjacent to tumor vs prepectoral extension). A third radiologist resolved discrepancies. Multivariable logistic regression analyses were performed to identify associations of high peritumoral and intratumoral T2 SI with histopathologic characteristics (associated ductal carcinoma in situ, hormone receptor status, histologic grade, lymphovascular invasion, and axillary lymph node metastasis). RESULTS. Of 211 HER2-positive cancers, 81 (38.4%) had high peritumoral T2 SI, and 95 (45.0%) had high intratumoral T2 SI. A histologic grade of 3 was independently associated with high peritumoral T2 SI (OR = 1.90; p = .04). Otherwise, none of the five assessed histopathologic characteristics were independently associated with high intratumoral T2 SI or high peritumoral T2 SI (p > .05). Cancers with high T2 SI adjacent to the tumor (n = 29) and cancers with high T2 SI with prepectoral extension (n = 52) showed no significant difference in frequency for any of the histopathologic characteristics (p > .05). Sensitivities and specificities for predicting the histopathologic characteristics ranged from 35.6% to 43.7% and from 59.7% to 70.7%, respectively, for high peritumoral T2 SI, and from 37.3% to 49.6% and from 49.3% to 62.7%, respectively, for high intratumoral T2 SI. Interreader agreement was almost perfect for high peritumoral T2 SI (Gwet agreement coefficient [AC] = 0.93), high intratumoral T2 SI (Gwet AC = 0.89), and a pattern of high peritumoral T2 SI (Gwet AC = 0.95). CONCLUSION. The only independent association between histopathologic characteristics and high T2 SI of HER2-positive breast cancer was observed between a histologic grade of 3 and high peritumoral T2 SI. CLINICAL IMPACT. In contrast with previously reported findings in broader breast cancer subtypes, peritumoral and intratumoral T2 SI had overall limited utility as prognostic markers of HER2-positive breast cancer.

Smart and low-cost fluorometer for identifying breast cancer malignancy based on lipid droplets accumulation.

The most common cause of breast cancer-related death is tumor recurrence. To develop more effective treatments, the identification of cancer cell specific malignancy indicators is therefore critical. Lipid droplets are known as an emerging hallmark in aggressive breast tumors. A common technique that can be used for observing molecules in cancer microenvironment is fluorescence microscopy. We describe the design, development and applicability of a smart fluorometer to detect lipid droplet accumulation based on the emitted fluorescence signals from highly malignant (MDA-MB-231) and mildly malignant (MCF7) breast cancer cell lines, that are stained with BODIPY dye. This device uses a visible-range light source as an excitation source and a spectral sensor as the detector. A commercial imaging system was used to examine the fluorescent cancer cell lines before being validated in a preclinical setting with the developed prototype. The outcomes indicate that this low-cost fluorometer can effectively detect the alterations levels of lipid droplets and hence distinguish between "moderately malignant" and "highly malignant" cancer cells. In comparison to prior research that used fluorescence spectroscopy techniques to detect cancer biomarkers, this study revealed enhanced capability in classifying mildly and highly malignant cancer cell lines.

Assessment of Use and Impact of Chemotherapy in Lymph Node-Negative, T1a Triple-Negative Breast Cancer.

BACKGROUND: Current treatment guidelines suggest considering adjuvant chemotherapy in high-risk patients with T1a, node-negative triple-negative breast cancer (TNBC); however, limited quality data support this statement. Our population-based study assessed the efficacy of adjuvant chemotherapy and factors associated with its administration in node-negative, T1a TNBC. MATERIALS AND METHODS: We obtained data from the Surveillance, Epidemiology, and End Results database for patients with T1aN0 TNBC diagnosed between 2010 and 2019. We utilized the Kaplan-Meier method and Cox regression model to analyze the overall survival (OS) and breast cancer-specific survival (BCSS) in chemotherapy benefit. We performed stratified models to identify differences in OS and BCSS between those who received chemotherapy and those who did not across subgroups. Competing risk analysis was conducted to assess differences in risk of breast cancer death in patients with chemotherapy administration versus no chemotherapy. Additionally, propensity score matching was executed to assess survival analysis in a matched cohort. RESULTS: We included 1739 patients with T1a TNBC. Patients who received chemotherapy were younger, had higher histological grade and ductal histology subtype, were more likely to be married and undergo mastectomy. Our study did not show improvement in OS (HR, 0.63; 95% CI, 0.35-1.13; P = .122) or BCSS (HR, 0.95; 95% CI, 0.37-2.43; P = .908) after chemotherapy use. We did not identify any subgroup of patients that may benefit from chemotherapy. Without chemotherapy, 8-year risk of breast cancer death is 2.75% for these patients. CONCLUSION: Adjuvant chemotherapy is not associated with benefit on OS or BCSS in node-negative, T1a TNBC.

Classification and assessment techniques of breast ptosis: A systematic review.

BACKGROUND: Breast ptosis is characterized by the inferolateral descent of the glandular area and nipple-areola complex. A high degree of ptosis may negatively impact a woman's attractiveness and self-confidence. There are various classifications and measurement techniques for breast ptosis used as references in the medical and garment industry. A practical and comprehensive classification will provide accurate standardized definitions of the degrees of ptosis to facilitate the development of corrective surgeries and well-fitting undergarments for women in need. METHODS: A systematic review on the classification and assessment techniques to measure breast ptosis was carried out based on the Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) guidelines. The risk of bias was assessed using the modified Newcastle-Ottawa scale for observational studies, whereas the Revised Cochrane risk-of-bias tool for randomized trials (RoB2) was used to evaluate randomized studies. RESULTS: Of 2550 articles identified in the literature search, 16 observational and 2 randomized studies describing the classification and assessment techniques of breast ptosis were included in the review. A total of 2033 subjects were involved. Half of the total observational studies had a Newcastle-Ottawa scale score of 5 and above. In addition, all randomized trials recorded a low overall bias. CONCLUSION: A total of 7 classifications and 4 measurement techniques for breast ptosis were identified. However, most studies did not demonstrate a clear derivation of sample size beside lacking robust statistical analysis. Hence, further studies that apply the latest technology to combine the strength of previous assessment techniques are needed to develop better classification system that is applicable to all affected women.

Simulation-Based Breast Biopsy Training Using a Low-Cost Gelatin-Based Breast Model in Rwanda.

BACKGROUND: An interdisciplinary team of healthcare providers and simulation specialists adopted and modified a protocol for the creation of a low-cost, gelatin-based breast model for teaching ultrasound-guided breast biopsy and assessed first-time user experience. METHODS: An interdisciplinary team of healthcare providers and simulation specialists adopted and modified a protocol for the creation of a low-cost, gelatin-based breast model for teaching ultrasound-guided breast biopsy for approximately $4.40 USD. Components include medical-grade gelatin, Jell-O™, water, olives, and surgical gloves. The model was used to train two cohorts comprising 30 students total during their junior surgical clerkship. The learners' experience and perceptions on the first Kirkpatrick level were evaluated using pre- and post-training surveys. RESULTS: Response rate was 93.3% (n = 28). Only three students had previously completed an ultrasound-guided breast biopsy, and none had prior exposure to simulation-based breast biopsy training. Learners that were confident in performing biopsies under minimal supervision rose from 4 to 75% following the session. All students indicated the session increased their knowledge, and 71% agreed that the model was an anatomically accurate and appropriate substitute to a real human breast. CONCLUSIONS: The use of a low-cost gelatin-based breast model was able to increase student confidence and knowledge in performing ultrasound-guided breast biopsies. This innovative simulation model provides a cost-effective and more accessible means of simulation-based training especially for low- and middle-income settings.

Increased breast cancer mortality due to treatment delay and needle biopsy type: a retrospective analysis of SEER-medicare.

BACKGROUND: Substantial evidence indicates that delay of first treatment after diagnosis is associated with poorer survival outcomes in breast cancer. Accordingly, the Commission on Cancer introduced a quality measure for receipt of therapeutic surgery within 60 days of diagnostic biopsy for stage I-III breast cancer patients in the non-neoadjuvant setting. It is unknown, however, what may contribute to mortality associated with treatment delay. Therefore, we investigated whether biopsy type moderates the effect of the mortality risk posed by treatment delay. METHODS: Retrospective analysis of 31,306 women with stage I-III breast cancer diagnosed between 2003 and 2013 selected from the SEER-Medicare database was performed to determine whether needle biopsy type [core needle biopsy (CNB) or vacuum-assisted biopsy (VAB)] impacts time to treatment (TTT)-associated survival outcomes. Multivariable Fine-Gray competing risk survival models, adjusted for inverse propensity score weights, were used to determine the association between biopsy type, TTT, and breast cancer-specific mortality (BCSM). RESULTS: TTT ≥ 60 days was associated with 45% higher risk of BCSM (sHR = 1.45, 95% CI 1.24-1.69) compared to those with TTT < 60 days in stage I-III cases. Independent of TTT, CNB was associated with 28% higher risk of BCSM compared to VAB in stage II-III cases (sHR = 1.28, 95% CI 1.11-1.36), translating to a 2.7% and 4.0% absolute difference in BCSM at 5 and 10 years, respectively. However, in stage I cases, the BCSM risk was not associated with type of biopsy. CONCLUSIONS: Our results suggest that treatment delay ≥ 60 days is independently associated with poorer survival outcomes in breast cancer patients. In stage II-III, CNB is associated with higher BCSM than VAB. However, type of biopsy does not underlie TTT-associated breast cancer mortality risk.

The epidemiological and clinicopathological characteristics of multifocal/multicentric breast cancer in the Egyptian Delta and its impact on management strategies.

BACKGROUND: Multifocal (MFBC)/multicentric (MCBC) breast cancer is being more recognized due to the improved imaging modalities and the greater orientation with this form of breast cancer, however, optimal surgical treatment, still poses a challenge. The standard surgical treatment is mastectomy, however, breast-conserving surgeries (BCS) may be appropriate in certain situations. METHODS: A total of 464 cases of MF/MCBC out of 4798 cases of breast cancer were retrospectively analyzed from the database of the Oncology Center, Mansoura University (OCMU), between January 2008 and December 2019. RESULTS: Radiologic involvement of multiple quadrants was reported in 27.9% by ultrasonography, 19% by mammography, and 59.1% by magnetic resonance imaging. BCS was performed in 32 cases (6.9%) while 432 cases underwent a mastectomy. Postoperative pathology revealed infiltration of other quadrants grossly in 23.5%, and under the microscope in 63.6% of the examined cases. Mean disease-free and overall survival were 95.5 and 164.6 months, respectively. When compared with MFBC, MCBC showed higher pathologic tumor size (p < 0.001), higher stages (p < 0.001), higher recurrence rates (p = 0.006), and lower DFS (P = 0.009) but with similar OS (P = 0.8). CONCLUSION: Mastectomy is still the primary treatment option for MCBC with higher recurrence rates compared with MFBC. However, BCS for properly selected MFBC is considered oncologically safe, following the same rules of breast conservation for unifocal disease.

High-temporal resolution DCE-MRI improves assessment of intra- and peri-breast lesions categorized as BI-RADS 4.

BACKGROUND: BI-RADS 4 breast lesions are suspicious for malignancy with a range from 2 to 95%, indicating that numerous benign lesions are unnecessarily biopsied. Thus, we aimed to investigate whether high-temporal-resolution dynamic contrast-enhanced MRI (H_DCE-MRI) would be superior to conventional low-temporal-resolution DCE-MRI (L_DCE-MRI) in the diagnosis of BI-RADS 4 breast lesions. METHODS: This single-center study was approved by the IRB. From April 2015 to June 2017, patients with breast lesions were prospectively included and randomly assigned to undergo either H_DCE-MRI, including 27 phases, or L_DCE-MRI, including 7 phases. Patients with BI-RADS 4 lesions were diagnosed by the senior radiologist in this study. Using a two-compartment extended Tofts model and a three-dimensional volume of interest, several pharmacokinetic parameters reflecting hemodynamics, including Ktrans, Kep, Ve, and Vp, were obtained from the intralesional, perilesional and background parenchymal enhancement areas, which were labeled the Lesion, Peri and BPE areas, respectively. Models were developed based on hemodynamic parameters, and the performance of these models in discriminating between benign and malignant lesions was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 140 patients were included in the study and underwent H_DCE-MRI (n = 62) or L_DCE-MRI (n = 78) scans; 56 of these 140 patients had BI-RADS 4 lesions. Some pharmacokinetic parameters from H_DCE-MRI (Lesion_Ktrans, Kep, and Vp; Peri_Ktrans, Kep, and Vp) and from L_DCE-MRI (Lesion_Kep, Peri_Vp, BPE_Ktrans and BPE_Vp) were significantly different between benign and malignant breast lesions (P < 0.01). ROC analysis showed that Lesion_Ktrans (AUC = 0.866), Lesion_Kep (AUC = 0.929), Lesion_Vp (AUC = 0.872), Peri_Ktrans (AUC = 0.733), Peri_Kep (AUC = 0.810), and Peri_Vp (AUC = 0.857) in the H_DCE-MRI group had good discrimination performance. Parameters from the BPE area showed no differentiating ability in the H_DCE-MRI group. Lesion_Kep (AUC = 0.767), Peri_Vp (AUC = 0.726), and BPE_Ktrans and BPE_Vp (AUC = 0.687 and 0.707) could differentiate between benign and malignant breast lesions in the L_DCE-MRI group. The models were compared with the senior radiologist's assessment for the identification of BI-RADS 4 breast lesions. The AUC, sensitivity and specificity of Lesion_Kep (0.963, 100.0%, and 88.9%, respectively) in the H_DCE-MRI group were significantly higher than those of the same parameter in the L_DCE-MRI group (0.663, 69.6% and 75.0%, respectively) for the assessment of BI-RADS 4 breast lesions. The DeLong test was conducted, and there was a significant difference only between Lesion_Kep in the H_DCE-MRI group and the senior radiologist (P = 0.04). CONCLUSIONS: Pharmacokinetic parameters (Ktrans, Kep and Vp) from the intralesional and perilesional regions on high-temporal-resolution DCE-MRI, especially the intralesional Kep parameter, can improve the assessment of benign and malignant BI-RADS 4 breast lesions to avoid unnecessary biopsy.

Breast Cancer Growth on Serial MRI: Volume Doubling Time Based on 3-Dimensional Tumor Volume Assessment.

BACKGROUND: The volume doubling time (VDT) of breast cancer was most frequently calculated using the two-dimensional (2D) diameter, which is not reliable for irregular tumors. It was rarely investigated using three-dimensional (3D) imaging with tumor volume on serial magnetic resonance imaging (MRI). PURPOSE: To investigate the VDT of breast cancer using 3D tumor volume assessment on serial breast MRIs. STUDY TYPE: Retrospective. SUBJECTS: Sixty women (age at diagnosis: 57 ± 10 years) with breast cancer, assessed by two or more breast MRI examinations. The median interval time was 791 days (range: 70-3654 days). FIELD STRENGTH/SEQUENCE: 3-T, fast spin-echo T2-weighted imaging (T2WI), single-shot echo-planar diffusion-weighted imaging (DWI), and gradient echo dynamic contrast-enhanced imaging. ASSESSMENT: Three radiologists independently reviewed the morphological, DWI, and T2WI features of lesions. The whole tumor was segmented to measure the volume on contrast-enhanced images. The exponential growth model was fitted in the 11 patients with at least three MRI examinations. The VDT of breast cancer was calculated using the modified Schwartz equation. STATISTICAL TESTS: Mann-Whitney U test, Kruskal-Wallis test, Chi-squared test, intraclass correlation coefficients, and Fleiss kappa coefficients. A P-value <0.05 was considered statistically significant. The exponential growth model was evaluated using the adjusted R2 and root mean square error (RMSE). RESULTS: The median tumor diameter was 9.7 mm and 15.2 mm on the initial and final MRI, respectively. The median adjusted R2 and RMSE of the 11 exponential models were 0.97 and 15.8, respectively. The median VDT was 540 days (range: 68-2424 days). For invasive ductal carcinoma (N = 33), the median VDT of the non-luminal type was shorter than that of the luminal type (178 days vs. 478 days). On initial MRI, breast cancer manifesting as a focus or mass lesion showed a shorter VDT than that of a non-mass enhancement (NME) lesion (median VDT: 426 days vs. 665 days). DATA CONCLUSION: A shorter VDT was observed in breast cancer manifesting as focus or mass as compared to an NME lesion. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.