Ultrasound Radiomics Features to Identify Patients With Triple-Negative Breast Cancer: A Retrospective, Single-Center Study.

OBJECTIVES: Patients with triple-negative breast cancer (TNBC) exhibit a fast tumor growth rate and poor survival outcomes. In this study, we aimed to develop and compare intelligent algorithms using ultrasound radiomics features in addition to clinical variables to identify patients with TNBC prior to histopathologic diagnosis. METHODS: We used single-center, retrospective data of patients who underwent ultrasound before histopathologic verification and subsequent neoadjuvant systemic treatment (NAST). We developed a logistic regression with an elastic net penalty algorithm using pretreatment ultrasound radiomics features in addition to patient and tumor variables to identify patients with TNBC. Findings were compared to the histopathologic evaluation of the biopsy specimen. The main outcome measure was the area under the curve (AUC). RESULTS: We included 1161 patients, 813 in the development set and 348 in the validation set. Median age was 50.1 years and 24.4% (283 of 1161) had TNBC. The integrative model using radiomics and clinical information showed significantly better performance in identifying TNBC compared to the radiomics model (AUC: 0.71, 95% confidence interval [CI]: 0.65-0.76 versus 0.64, 95% CI: 0.57-0.71, P = .004). The five most important variables were cN status, shape surface volume ratio (SA:V), gray level co-occurrence matrix (GLCM) correlation, gray level dependence matrix (GLDM) dependence nonuniformity normalized, and age. Patients with TNBC were more often categorized as BI-RADS 4 than BI-RADS 5 compared to non-TNBC patients (P = .002). CONCLUSION: A machine learning algorithm showed promising potential to identify patients with TNBC using ultrasound radiomics features and clinical information prior to histopathologic evaluation.

Minimally Invasive Breast Biopsy After Neoadjuvant Systemic Treatment to Identify Breast Cancer Patients with Residual Disease for Extended Neoadjuvant Treatment: A New Concept.

BACKGROUND: Breast cancer patients with residual disease after neoadjuvant systemic treatment (NAST) have a worse prognosis compared with those achieving a pathologic complete response (pCR). Earlier identification of these patients might allow timely, extended neoadjuvant treatment strategies. We explored the feasibility of a vacuum-assisted biopsy (VAB) after NAST to identify patients with residual disease (ypT+ or ypN+) prior to surgery. METHODS: We used data from a multicenter trial, collected at 21 study sites (NCT02948764). The trial included women with cT1-3, cN0/+ breast cancer undergoing routine post-neoadjuvant imaging (ultrasound, MRI, mammography) and VAB prior to surgery. We compared the findings of VAB and routine imaging with the histopathologic evaluation of the surgical specimen. RESULTS: Of 398 patients, 34 patients with missing ypN status and 127 patients with luminal tumors were excluded. Among the remaining 237 patients, tumor cells in the VAB indicated a surgical non-pCR in all patients (73/73, positive predictive value [PPV] 100%), whereas PPV of routine imaging after NAST was 56.0% (75/134). Sensitivity of the VAB was 72.3% (73/101), and 74.3% for sensitivity of imaging (75/101). CONCLUSION: Residual cancer found in a VAB specimen after NAST always corresponds to non-pCR. Residual cancer assumed on routine imaging after NAST corresponds to actual residual cancer in about half of patients. Response assessment by VAB is not safe for the exclusion of residual cancer. Response assessment by biopsies after NAST may allow studying the new concept of extended neoadjuvant treatment for patients with residual disease in future trials.

Intelligent multi-modal shear wave elastography to reduce unnecessary biopsies in breast cancer diagnosis (INSPiRED 002): a retrospective, international, multicentre analysis.

BACKGROUND: Breast ultrasound identifies additional carcinomas not detected in mammography but has a higher rate of false-positive findings. We evaluated whether use of intelligent multi-modal shear wave elastography (SWE) can reduce the number of unnecessary biopsies without impairing the breast cancer detection rate. METHODS: We trained, tested, and validated machine learning algorithms using SWE, clinical, and patient information to classify breast masses. We used data from 857 women who underwent B-mode breast ultrasound, SWE, and subsequent histopathologic evaluation at 12 study sites in seven countries from 2016 to 2019. Algorithms were trained and tested on data from 11 of the 12 sites and externally validated using the additional site's data. We compared findings to the histopathologic evaluation and compared the diagnostic performance between B-mode breast ultrasound, traditional SWE, and intelligent multi-modal SWE. RESULTS: In the external validation set (n = 285), intelligent multi-modal SWE showed a sensitivity of 100% (95% CI, 97.1-100%, 126 of 126), a specificity of 50.3% (95% CI, 42.3-58.3%, 80 of 159), and an area under the curve of 0.93 (95% CI, 0.90-0.96). Diagnostic performance was significantly higher compared to traditional SWE and B-mode breast ultrasound (P < 0.001). Unlike traditional SWE, positive-predictive values of intelligent multi-modal SWE were significantly higher compared to B-mode breast ultrasound. Unnecessary biopsies were reduced by 50.3% (79 versus 159, P < 0.001) without missing cancer compared to B-mode ultrasound. CONCLUSION: The majority of unnecessary breast biopsies might be safely avoided by using intelligent multi-modal SWE. These results may be helpful to reduce diagnostic burden for patients, providers, and healthcare systems.

The importance of multi-modal imaging and clinical information for humans and AI-based algorithms to classify breast masses (INSPiRED 003): an international, multicenter analysis.

OBJECTIVES: AI-based algorithms for medical image analysis showed comparable performance to human image readers. However, in practice, diagnoses are made using multiple imaging modalities alongside other data sources. We determined the importance of this multi-modal information and compared the diagnostic performance of routine breast cancer diagnosis to breast ultrasound interpretations by humans or AI-based algorithms. METHODS: Patients were recruited as part of a multicenter trial (NCT02638935). The trial enrolled 1288 women undergoing routine breast cancer diagnosis (multi-modal imaging, demographic, and clinical information). Three physicians specialized in ultrasound diagnosis performed a second read of all ultrasound images. We used data from 11 of 12 study sites to develop two machine learning (ML) algorithms using unimodal information (ultrasound features generated by the ultrasound experts) to classify breast masses which were validated on the remaining study site. The same ML algorithms were subsequently developed and validated on multi-modal information (clinical and demographic information plus ultrasound features). We assessed performance using area under the curve (AUC). RESULTS: Of 1288 breast masses, 368 (28.6%) were histopathologically malignant. In the external validation set (n = 373), the performance of the two unimodal ultrasound ML algorithms (AUC 0.83 and 0.82) was commensurate with performance of the human ultrasound experts (AUC 0.82 to 0.84; p for all comparisons > 0.05). The multi-modal ultrasound ML algorithms performed significantly better (AUC 0.90 and 0.89) but were statistically inferior to routine breast cancer diagnosis (AUC 0.95, p for all comparisons ≤ 0.05). CONCLUSIONS: The performance of humans and AI-based algorithms improves with multi-modal information. KEY POINTS: • The performance of humans and AI-based algorithms improves with multi-modal information. • Multimodal AI-based algorithms do not necessarily outperform expert humans. • Unimodal AI-based algorithms do not represent optimal performance to classify breast masses.

Intelligent Vacuum-Assisted Biopsy to Identify Breast Cancer Patients With Pathologic Complete Response (ypT0 and ypN0) After Neoadjuvant Systemic Treatment for Omission of Breast and Axillary Surgery.

PURPOSE: Neoadjuvant systemic treatment (NST) elicits a pathologic complete response in 40%-70% of women with breast cancer. These patients may not need surgery as all local tumor has already been eradicated by NST. However, nonsurgical approaches, including imaging or vacuum-assisted biopsy (VAB), were not able to accurately identify patients without residual cancer in the breast or axilla. We evaluated the feasibility of a machine learning algorithm (intelligent VAB) to identify exceptional responders to NST. METHODS: We trained, tested, and validated a machine learning algorithm using patient, imaging, tumor, and VAB variables to detect residual cancer after NST (ypT+ or in situ or ypN+) before surgery. We used data from 318 women with cT1-3, cN0 or +, human epidermal growth factor receptor 2-positive, triple-negative, or high-proliferative Luminal B-like breast cancer who underwent VAB before surgery (ClinicalTrials.gov identifier: NCT02948764, RESPONDER trial). We used 10-fold cross-validation to train and test the algorithm, which was then externally validated using data of an independent trial (ClinicalTrials.gov identifier: NCT02575612). We compared findings with the histopathologic evaluation of the surgical specimen. We considered false-negative rate (FNR) and specificity to be the main outcomes. RESULTS: In the development set (n = 318) and external validation set (n = 45), the intelligent VAB showed an FNR of 0.0%-5.2%, a specificity of 37.5%-40.0%, and an area under the receiver operating characteristic curve of 0.91-0.92 to detect residual cancer (ypT+ or in situ or ypN+) after NST. Spiegelhalter's Z confirmed a well-calibrated model (z score -0.746, P = .228). FNR of the intelligent VAB was lower compared with imaging after NST, VAB alone, or combinations of both. CONCLUSION: An intelligent VAB algorithm can reliably exclude residual cancer after NST. The omission of breast and axillary surgery for these exceptional responders may be evaluated in future trials.

Diagnosing Pathologic Complete Response in the Breast After Neoadjuvant Systemic Treatment of Breast Cancer Patients by Minimal Invasive Biopsy: Oral Presentation at the San Antonio Breast Cancer Symposium on Friday, December 13, 2019, Program Number GS5-03.

OBJECTIVE: We evaluated the ability of minimally invasive, image-guided vacuum-assisted biopsy (VAB) to reliably diagnose a pathologic complete response in the breast (pCR-B). SUMMARY BACKGROUND DATA: Neoadjuvant systemic treatment (NST) elicits a pathologic complete response in up to 80% of women with breast cancer. In such cases, breast surgery, the gold standard for confirming pCR-B, may be considered overtreatment. METHODS: This multicenter, prospective trial enrolled 452 women presenting with initial stage 1-3 breast cancer of all biological subtypes. Fifty-four women dropped out; 398 were included in the full analysis. All participants had an imaging-confirmed partial or complete response to NST and underwent study-specific image-guided VAB before guideline-adherent breast surgery. The primary endpoint was the false-negative rate (FNR) of VAB-confirmed pCR-B. RESULTS: Image-guided VAB alone did not detect surgically confirmed residual tumor in 37 of 208 women [FNR, 17.8%; 95% confidence interval (CI), 12.8-23.7%]. Of these 37 women, 12 (32.4%) had residual DCIS only, 20 (54.1%) had minimal residual tumor (<5 mm), and 19 of 25 (76.0%) exhibited invasive cancer cellularity of ≤10%. In 19 of the 37 cases (51.4%), the false-negative result was potentially avoidable. Exploratory analysis showed that performing VAB with the largest needle by volume (7-gauge) resulted in no false-negative results and that combining imaging and image-guided VAB into a single diagnostic test lowered the FNR to 6.2% (95% CI, 3.4%-10.5%). CONCLUSIONS: Image-guided VAB missed residual disease more often than expected. Refinements in procedure and patient selection seem possible and necessary before omitting breast surgery.

A New Practical Decision Rule to Better Differentiate BI-RADS 3 or 4 Breast Masses on Breast Ultrasound.

OBJECTIVES: The BI-RADS classification provides a standardized way to describe ultrasound findings in breast cancer diagnostics. However, there is little information regarding which BI-RADS descriptors are most strongly associated with malignancy, to better distinguish BI-RADS 3 (follow-up imaging) and 4 (diagnostic biopsy) breast masses. METHODS: Patients were recruited as part of an international, multicenter trial (NCT02638935). The trial enrolled 1294 women (6 excluded) categorized as BI-RADS 3 or 4 upon routine B-mode ultrasound examination. Ultrasound images were evaluated by three expert physicians according to BI-RADS. All patients underwent histopathological confirmation (reference standard). We performed univariate and multivariate analyses (chi-square test, logistic regression, and Krippendorff's alpha). RESULTS: Histopathologic evaluation showed malignancy in 368 of 1288 masses (28.6%). Upon performing multivariate analysis, the following descriptors were significantly associated with malignancy (P < .05): age ≥50 years (OR 8.99), non-circumscribed indistinct (OR 4.05) and microlobulated margin (OR 2.95), nonparallel orientation (OR 2.69), and calcification (OR 2.64). A clinical decision rule informed by these results demonstrated a 97% sensitivity and missed fewer cancers compared to three physician experts (range of sensitivity 79-95%) and a previous decision rule (sensitivity 59%). Specificity was 44% versus 22-83%, respectively. The inter-reader reliability of the BI-RADS descriptors and of the final BI-RADS score was fair-moderate. CONCLUSIONS: A patient should undergo a diagnostic biopsy (BI-RADS 4) instead of follow-up imaging (BI-RADS 3) if the patient is 50 years or older or exhibits at least one of the following features: calcification, nonparallel orientation of mass, non-circumscribed margin, or posterior shadowing.

Vacuum-Assisted Breast Biopsy After Neoadjuvant Systemic Treatment for Reliable Exclusion of Residual Cancer in Breast Cancer Patients.

BACKGROUND: About 40 % of women with breast cancer achieve a pathologic complete response in the breast after neoadjuvant systemic treatment (NST). To identify these women, vacuum-assisted biopsy (VAB) was evaluated to facilitate risk-adaptive surgery. In confirmatory trials, the rates of missed residual cancer [false-negative rates (FNRs)] were unacceptably high (> 10%). This analysis aimed to improve the ability of VAB to exclude residual cancer in the breast reliably by identifying key characteristics of false-negative cases. METHODS: Uni- and multivariable logistic regressions were performed using data of a prospective multicenter trial (n = 398) to identify patient and VAB characteristics associated with false-negative cases (no residual cancer in the VAB but in the surgical specimen). Based on these findings FNR was exploratively re-calculated. RESULTS: In the multivariable analysis, a false-negative VAB result was significantly associated with accompanying ductal carcinoma in situ (DCIS) in the initial diagnostic biopsy [odds ratio (OR), 3.94; p < 0.001], multicentric disease on imaging before NST (OR, 2.74; p = 0.066), and age (OR, 1.03; p = 0.034). Exclusion of women with DCIS or multicentric disease (n = 114) and classication of VABs that did not remove the clip marker as uncertain representative VABs decreased the FNR to 2.9% (3/104). CONCLUSION: For patients without accompanying DCIS or multicentric disease, performing a distinct representative VAB (i.e., removing a well-placed clip marker) after NST suggests that VAB might reliably exclude residual cancer in the breast without surgery. This evidence will inform the design of future trials evaluating risk-adaptive surgery for exceptional responders to NST.

Does conventional specimen radiography after neoadjuvant chemotherapy of breast cancer help to reduce the rate of second surgeries?

PURPOSE: This is the first study to systematically evaluate the diagnostic accuracy of intraoperative specimen radiography on margin level and its potential to reduce second surgeries in patients treated with neoadjuvant chemotherapy. METHODS: This retrospective study included 174 cases receiving breast conserving surgery (BCS) after neoadjuvant chemotherapy (NACT) of primary breast cancer. Conventional specimen radiography (CSR) was performed to assess potential margin infiltration and recommend an intraoperative re-excision of any radiologically positive margin. The histological workup of the specimen served as gold standard for the evaluation of the accuracy of CSR and the potential reduction of second surgeries by CSR-guided re-excisions. RESULTS: 1044 margins were assessed. Of 47 (4.5%) histopathological positive margins, CSR identified 9 correctly (true positive). 38 infiltrated margins were missed (false negative). This resulted in a sensitivity of 19.2%, a specificity of 89.2%, a positive predictive value (PPV) of 7.7%, and a negative predictive value (NPV) of 95.9%. The rate of secondary procedures was reduced from 23 to 16 with a number needed to treat (NNT) of CSR-guided intraoperative re-excisions of 25. In the subgroup of patients with cCR, the prevalence of positive margins was 10/510 (2.0%), PPV was 1.9%, and the NNT was 85. CONCLUSION: Positive margins after NACT are rare and CSR has only a low sensitivity to detect them. Thus, the rate of secondary surgeries cannot be significantly reduced by recommending targeted re-excisions, especially in cases with cCR. In summary, CSR after NACT is inadequate for intraoperative margin assessment but remains useful to document removal of the biopsy site clip.

First proof-of-concept evaluation of the FUSION-X-US-II prototype for the performance of automated breast ultrasound in healthy volunteers.

PURPOSE: The FUSION-X-US-II prototype was developed to combine 3D-automated breast ultrasound (ABUS) and digital breast tomosynthesis in a single device without decompressing the breast. We evaluated the technical function, feasibility of the examination workflow, image quality, breast tissue coverage and patient comfort of the ABUS device of the new prototype. METHODS: In this prospective feasibility study, the FUSION-X-US-II prototype was used to perform ABUS in 30 healthy volunteers without history of breast cancer. The ABUS images of the prototype were interpreted by a physician with specialization in breast diagnostics. Any detected lesions were measured and classified using BI-RADS® scores. Image quality was rated subjectively by the physician and coverage of the breast was measured. Patient comfort was evaluated by a questionnaire after the examination. RESULTS: One hundred and six scans were performed (61 × CC, 23 × ML, 22 × MLO) in 60 breasts. Image acquisition and processing by the prototype was fast and accurate. Breast coverage by ABUS was approximately 90.8%. Sixteen breast lesions (all benign, classified as BIRADS® 2) were identified. The examination was tolerated by all patients. CONCLUSION: The FUSION-X-US-II prototype allows a rapid ABUS scan with mostly high patient comfort. Technical developments resulted in an improvement of quality and coverage compared to previous prototype versions. The results are encouraging for a test of the prototype in a clinical setting in combination with tomosynthesis.

Diagnostic accuracy of axillary staging by ultrasound in early breast cancer patients.

BACKGROUND: Axillary ultrasound (AUS) is a standard procedure in the preoperative clinical identification of axillary metastatic lymph node (LN) involvement. It guides decisions about local and systemic therapy for patients with early breast cancer (EBC). But there is only weak evidence on the diagnostic criteria and standard interpretation. The aim of this study was to assess the performance of AUS in the detection and exclusion of LN metastases. METHODS: In a retrospective single-center study, 611 consecutive EBC patients with 622 axillae underwent AUS +/- core needle biopsy (CNB) plus axillary surgery, i.e. sentinel lymph node biopsy and/or axillary lymph node dissection. For all patients, AUS image documentation of at least the most suspicious LN was saved during the initial diagnostic work-up. The diagnostic outcome measures were sensitivity, specificity, accuracy, Youden-index (YI), and diagnostic odds ratio (DOR) on the basis of the daily routine interpretation and on the basis of previously recommended diagnostic criteria by two blinded examiners. RESULTS: On the basis of the daily routine interpretation, AUS had a sensitivity (95 % CI) of 53.3 % (46.4-60.1), a specificity (95 % CI) of 93.6 % (90.8-95.8), an accuracy (95 % CI) of 79.7 % (76.4-82.8), a YI (95 % CI) of 0.47 (0.40 - 0.54), and a DOR (95 % CI) of 16.75 (10.37-27.05). Systematic application of previously recommended diagnostic criteria did not improve the diagnostic accuracy of routinely interpreted AUS. CONCLUSION: AUS performance alone is not sufficient to accurately identify or exclude axillary metastatic disease in unselected patients with EBC.

Analyzing non-sentinel axillary metastases in patients with T3-T4 cN0 early breast cancer and tumor-involved sentinel lymph nodes undergoing breast-conserving therapy or mastectomy.

PURPOSE: In the ACOSOG Z0011 trial, completing axillary lymph node dissection (cALND) did not benefit patients with T1-T2 cN0 early breast cancer and 1-2 positive sentinel lymph nodes (SLN) undergoing breast-conserving surgery (BCT). This paper reports cALND rates in the clinical routine for patients who had higher (T3-T4) tumor stages and/or underwent mastectomy but otherwise met the ACOSOG Z0011 eligibility criteria. Aim of this study is to determine cALND time trends and non-sentinel axillary metastases (NSAM) rates to estimate occult axillary tumor burden. METHODS: Data were included from patients treated in 179 German breast cancer centers between 2008 and 2015. Time-trend rates were analyzed for cALND of patients with T3-T4 tumors separated for BCT and mastectomy and regarding presence of axillary macrometastases or micrometastases. RESULTS: Data were available for 188,909 patients, of whom 19,009 were identified with 1-2 positive SLN. Those 19,009 patients were separated into 4 cohorts: (1) Patients with T1-T2 tumors receiving BCT (ACOSOG Z0011 eligible; n = 13,741), (2) T1-T2 with mastectomy (n = 4093), (3) T3-T4 with BCT (n = 269), (4) T3-T4 with mastectomy (n = 906). Among patients with T3-T4 tumors, cALND rates declined from 2008 to 2015: from 88.2 to 62.6% for patients receiving mastectomy and from 96.6 to 58.1% in patients receiving BCT. Overall rates for any NSAM after cALND for cohorts 1-4 were 33.4%, 42.3%, 46.9%, 58.8%, respectively. CONCLUSIONS: The cALND rates have decreased substantially in routine care in patients with 'extended' ACOSOG Z0011 eligibility criteria. Axillary tumor burden is higher in these patients than in the ACOSOG Z0011 trial.

Heterogeneous Responses of Axillary Lymph Node Metastases to Neoadjuvant Chemotherapy are Common and Depend on Breast Cancer Subtype.

BACKGROUND: The objective of this study was to analyze heterogeneous responses of axillary lymph node metastasis to neoadjuvant chemotherapy and to determine to what extent they differ between tumor subtypes (TN, HER2+, HR+/HER2-). METHODS: This retrospective, monocenter study included 72 consecutive, histologically node-positive breast cancers (cT1-4 cN1-3 cM0) diagnosed in the period from January 2015 to December 2016, who had received axillary lymph node dissection following neoadjuvant chemotherapy. All individual lymph node specimens were re-evaluated for the presence of tumor cells and chemotherapy effects to assess their response to neoadjuvant chemotherapy on an individual lymph node level according to the Sataloff classification. RESULTS: Heterogeneous axillary responses to neoadjuvant chemotherapy occurred in 47.2% of the included 72 patients. The partial response rate was significantly higher in HR+/HER2- tumors (74.2%) than in TN (28.6%) and HER2+ tumors (25.0%) (p < 0.001). The presence of at least one negative, completely responding lymph node in the axillary lymph node dissection specimen had a false-negative rate of 48.8% in predicting ypN0. It dropped below 10% if at least four completely responding negative lymph nodes were identified. CONCLUSIONS: Our study shows that axillary heterogeneous response rates differ significantly between tumor subtypes.

RESPONDER - diagnosis of pathological complete response by vacuum-assisted biopsy after neoadjuvant chemotherapy in breast Cancer - a multicenter, confirmative, one-armed, intra-individually-controlled, open, diagnostic trial.

BACKGROUND: Neoadjuvant chemotherapy (NACT) is a standard approach of the multidisciplinary treatment of breast cancer. Depending on the biological subtype a pathological complete response in the breast (bpCR) can be achieved in up to 60% of the patients. However, only limited accuracy can be reached when using imaging for prediction of bpCR prior to surgery. Due to this diagnostic uncertainty, surgery after NACT is considered to be obligatory for all patients in order to either completely remove residual disease or to diagnose a bpCR histologically. The purpose of this trial is to evaluate the accuracy of a vacuum-assisted biopsy (VAB) to diagnose a bpCR after NACT prior to surgery. METHODS: This study is a multicenter, confirmative, one-armed, intra-individually-controlled, open, diagnostic trial. The study will take place at 21 trial sites in Germany. Six hundred female patients with breast cancer after completed NACT showing at least a partial response to NACT treatment will be enrolled. A vacuum-assisted biopsy (VAB) guided either by ultrasound or mammography will be performed followed by histopathological evaluation of the VAB specimen before standard, guideline-adherent breast surgery. The study is designed to prove that the false negative rate of the VAB is below 10%. DISCUSSION: As a bpCR is becoming a more frequent result after NACT, the question arises whether breast surgery is therapeutically necessary in such cases. To study this subject further, it will be crucial to develop a reliable test to diagnose a bpCR without surgery. During the study we anticipate possible problems in patient recruitment as the VAB intervention does not provide participating patients with any personal benefit. Hence, a proficient informed consent discussion with the patient and a detailed explanation of the study aim will be crucial for patient recruitment. Another critical issue is the histopathological VAB evaluation of a non-tumorous specimen as this may have been taken either from the former tumor region (bpCR) or outside of the (former) tumor region (non-representative VAB, sampling error). TRIAL REGISTRATION: The trial has been registered at clinicaltrials.gov with the identifier NCT02948764 on October 28, 2016 and at the German Clinical Trials Register ( DRKS00011761 ) on February 20, 2017. The date of enrolment of the first participant to the trial was on March 8, 2017.

Initial results of the FUSION-X-US prototype combining 3D automated breast ultrasound and digital breast tomosynthesis.

PURPOSE: To determine the feasibility of a prototype device combining 3D-automated breast ultrasound (ABVS) and digital breast tomosynthesis in a single device to detect and characterize breast lesions. METHODS: In this prospective feasibility study, the FUSION-X-US prototype was used to perform digital breast tomosynthesis and ABVS in 23 patients with an indication for tomosynthesis based on current guidelines after clinical examination and standard imaging. The ABVS and tomosynthesis images of the prototype were interpreted separately by two blinded experts. The study compares the detection and BI-RADS® scores of breast lesions using only the tomosynthesis and ABVS data from the FUSION-X-US prototype to the results of the complete diagnostic workup. RESULTS: Image acquisition and processing by the prototype was fast and accurate, with some limitations in ultrasound coverage and image quality. In the diagnostic workup, 29 solid lesions (23 benign, including three cases with microcalcifications, and six malignant lesions) were identified. Using the prototype, all malignant lesions were detected and classified as malignant or suspicious by both investigators. CONCLUSION: Solid breast lesions can be localized accurately and fast by the Fusion-X-US system. Technical improvements of the ultrasound image quality and ultrasound coverage are needed to further study this new device. KEY POINTS: The prototype combines tomosynthesis and automated 3D-ultrasound (ABVS) in one device. It allows accurate detection of malignant lesions, directly correlating tomosynthesis and ABVS data. The diagnostic evaluation of the prototype-acquired data was interpreter-independent. The prototype provides a time-efficient and technically reliable diagnostic procedure. The combination of tomosynthesis and ABVS is a promising diagnostic approach.

Is Breast Surgery Necessary for Breast Carcinoma in Complete Remission Following Neoadjuvant Chemotherapy?

The likelihood of pathological complete remission (pCR) of breast cancer following neoadjuvant chemotherapy (NACT) is increasing; most of all in the triple negative and HER2 positive tumour subgroups. The question thus arises whether or not breast surgery is necessary when there is complete remission after NACT, and whether it provides any improvement of the oncological treatment result when tumour is no longer detectable. Avoiding surgery and possibly even radiotherapy would only be conceivable on the basis of a reliable diagnosis of pCR without operating. Current imaging does not achieve the necessary sensitivity and specificity to assure the diagnosis of pathological complete remission. Further studies are therefore required to determine which methods are best able to evaluate tumour response to NACT. Studies on image-guided, minimally invasive biopsies after NACT have delivered first promising results towards diagnosing pCR before surgery and could provide the basis for further studies on the possibility of avoiding surgery in this specific patient collective.

Inter-rater reliability and double reading analysis of an automated three-dimensional breast ultrasound system: comparison of two independent examiners.

PURPOSE: Breast ultrasound could be a valuable tool complementary to mammography in breast cancer screening. Automated 3D breast ultrasound (ABUS) addresses challenges of hand-held ultrasound and could allow double reading analysis of ultrasound images. This trial assesses the inter-rater reliability and double reading analysis of an ABUS system. METHODS: To assess the reproducibility and diagnostic validity of the ABUS system, SomoV™, a blinded double reading analysis, was performed in 1019 patients (2038 breasts) by two examiners (examiner A/B) and compared to single reading results, as well as to the reference standard regarding its diagnostic validity. Cohen's kappa coefficients were calculated to measure the inter-rater reliability and agreement of the different diagnostic modalities. Patient comfort and time consumption for image acquisition and reading were analyzed descriptively as secondary objectives. RESULTS: Analysis of inter-rater reliability yielded agreement in 81.6% (κ = 0.37; p < 0.0001) showing fair agreement. Single reading analysis of SomoV™ exams (examiner A/examiner B) compared to reference standard showed good specificity (examiner A: 88.3%/examiner B: 84.5%), fair inter-rater agreement (examiner A: κ = 0.31/examiner B: κ = 0.31), and adequate sensitivity (examiner A: 53.1%/examiner B: 64.2%). Double reading analysis yielded good sensitivity and specificity (73.7 and 77.7%). Mammography (n = 1911) alone detected 160 of 176 carcinomas (sensitivity 90.1%). Adding SomoV™ to mammography would have detected 12 additional carcinomas, resulting in a higher sensitivity of 97.7%. CONCLUSION: SomoV™ is a promising technique with good sensitivity, high patient comfort, and fair inter-examiner reliability. It allows double reading analysis that, in combination with mammography, could increase detection rates in breast cancer screening.

Pyruvate controls the checkpoint inhibitor PD-L1 and suppresses T cell immunity.

Patients with coronary artery disease (CAD) are at high risk for reactivation of the varicella zoster virus (VZV) and development of herpes zoster (HZ). Here, we found that macrophages from patients with CAD actively suppress T cell activation and expansion, leading to defective VZV-specific T cell immunity. Monocyte-derived and plaque-infiltrating macrophages from patients with CAD spontaneously expressed high surface density of the immunoinhibitory ligand programmed death ligand-1 (PD-L1), thereby providing negative signals to programmed death-1+ (PD-1+) T cells. We determined that aberrant PD-L1 expression in patient-derived macrophages was metabolically controlled. Oversupply of the glycolytic intermediate pyruvate in mitochondria from CAD macrophages promoted expression of PD-L1 via induction of the bone morphogenetic protein 4/phosphorylated SMAD1/5/IFN regulatory factor 1 (BMP4/p-SMAD1/5/IRF1) signaling pathway. Thus, CAD macrophages respond to nutrient excess by activating the immunoinhibitory PD-1/PD-L1 checkpoint, leading to impaired T cell immunity. This finding indicates that metabolite-based immunotherapy may be a potential strategy for restoring adaptive immunity in CAD.

Is Mastectomy Oncologically Safer than Breast-Conserving Treatment in Early Breast Cancer?

AIM: To describe and discuss the evidence for oncological safety of different procedures in oncological breast surgery, i.e. breast-conserving treatment versus mastectomy. METHODS: Literature review and discussion. RESULTS: Oncological safety in breast cancer surgery has many dimensions. Breast-conserving treatment has been established as the standard surgical procedure for primary breast cancer and fits to the preferences of most breast cancer patients concerning oncological safety and aesthetic outcome. CONCLUSIONS: Breast-conserving treatment is safe. Nonetheless, the preferences of the individual patients in their consideration of breast conservation versus mastectomy should be integrated into routine treatment decisions.