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In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 4_Supplement ( 2021-02-15), p. OT-04-03-OT-04-03

Abstract: Background Main weaknesses of neoadjuvant chemotherapy (NACT) to avoid axillary dissection (ALND) in patients with clinically node-positive breast cancer are frequent failure of achieving nodal pathologic complete response (pCR) and administration of chemotherapy even though not indicated otherwise in many cases. Tailored axillary surgery (TAS) was designed to selectively remove positive nodes and omit ALND in patients with clinically node-positive breast cancer either in the upfront surgery setting or in case of residual nodal disease after neoadjuvant therapy, which distinguishes this trial from all others ongoing and published. Trial design In this international, multi-center, phase-III, non-inferiority randomized controlled trial, including 61 study sites from six countries, we plan to randomize 1500 patients to either receive TAS followed by ALND and regional nodal irradiation excluding the dissected axilla, or receive TAS only followed by regional nodal irradiation including the full axilla. TAS consists of selective removal of the sentinel lymph nodes (SLNs) and all palpably suspicious findings, thereby tailoring the extent of axillary surgery to the extent of axillary disease, followed by specimen radiography to document removal of the clip placed in the sampled node. Imaging-guided localization is encouraged to increase the chances of clip removal. All patients undergo adjuvant whole-breast irradiation after breast conserving surgery and chest wall irradiation after mastectomy. Inclusion of internal mammary nodes is recommended irrespective of treatment arm. ClinicalTrials.gov Identifier: NCT03513614. Inclusion criteria - Clinically node-positive breast cancer (all molecular subtypes allowed) - Node-positivity palpable or detectable only by imaging at time of initial diagnosis - Newly diagnosed or isolated in-breast recurrence or second ipsilateral breast cancer after previous breast conserving surgery and sentinel procedure and at least 3 years disease free and no prior axillary dissection or axillary RT. - In case of prior neoadjuvant treatment: residual disease (including residual ITCs) confirmed by pathology at the time of surgery - Clipping of sampled axillary lymph node Exclusion criteria - Absence of clip in the specimen radiography - Palpable disease left behind in the axilla after TAS - No SLN identified in the axilla Specific aims To test the hypothesis that treatment with TAS and axillary radiotherapy is non-inferior to ALND in terms of disease-free survival (DFS) of clinically node-positive breast cancer patients. Secondary objective is to test if quality of life is significantly better with TAS and axillary radiotherapy compared to ALND. Statistical methods With type I error 5% and power 80%, 385 events will be needed to show non-inferiority of TAS and axillary RT in comparison to ALND with a non-inferiority hazard ratio (HR) of 1.289 (corresponding to a DFS at 5 years of 80% in the ALND arm and 75% in the TAS and axillary RT arm), including one interim analysis for efficacy/futility after 20% of the required events have occurred. The sample size needed is 1500 patients (750 per arm). The HR and one-sided 95% confidence interval will be calculated using a Cox regression model based on the per-protocol set. Present accrual and target accrual The trial was activated on 31 July 2018 and the first patient was randomized on 07 August 2018. As of 03 July 2020, 291 patients have been randomized. Accrual is currently running according to protocol and is planned until end of 2023 with the primary endpoint analysis expected in 2029. Contact information Prof. Dr. Walter Paul Weber, University Hospital Basel; Tel: +41 61 328 61 49; Walter.Weber@usb.ch Citation Format: Walter Paul Weber, Guido Henke, Stefanie Hayoz, Karin Ribi, Stefanie Seiler, Charlotte Maddox, Thomas Ruhstaller, Daniel Rudolf Zwahlen, Simone Muenst, Markus Ackerknecht, Florian Fitzal, Mihály Újhelyi, Christian Kurzeder, Loïc Lelièvre, Christoph Tausch, Daniel Egle, Jörg Heil, Zoltan Matrai, Michael Knauer. Tailored axillary surgery with or without axillary lymph node dissection followed by radiotherapy in patients with clinically node-positive breast cancer (SAKK 23/16 / IBCSG 57-18 / ABCSG-53 / GBG 101 - TAXIS): A multicenter randomized phase III trial [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr OT-04-03.

Type of Medium: Online Resource

ISSN: 0008-5472 , 1538-7445

URL: Article

DOI: 10.1158/1538-7445.SABCS20-OT-04-03

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2021

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detail.hit.zdb_id: 410466-3

In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 4_Supplement ( 2022-02-15), p. P2-12-08-P2-12-08

Abstract: Background: Pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is associated with beneficial long-term outcome in early breast cancer (EBC). pCR is defined as ypT0/is, ypN0. It is well known that pCR rates depend on tumor subtype. However, the impact of different therapy regimens, dose delays and dose reductions on pCR rates is still unclear. This retrospective study analyzed the therapy dose of patients with pCR and non-pCR after NACT for EBC using referenced and delivered summation dose intensity product (SDIP) and relative dose intensity (RDI) calculations. Methods: SDIP of different therapy regimens were calculated by defining a unit dose intensity (UDI) for each therapy (Hryniuk et al. JCO 1998). The UDI is defined as the dose in mg/m2/week that produces a 30% complete or partial remission rate as a single agent in first-line therapy for metastatic breast cancer. For each regimen, the planned dose intensities (PDI) were divided by the UDI for every single drug. The summation dose intensity (SDI) is the addition of the resulting decimal fractions. Multiplying the SDI by the treatment intervals and number of cycles gives the SDIP. SDIP can be divided into referenced SDIP (rSDIP) and delivered SDIP (dSDIP). RDI is the ratio of dSDIP in comparison to rSDIP. Therapy dose calculations were performed for patients who received NACT for EBC at the National Center for Tumor Diseases (NCT) Heidelberg, Germany, between 01/2015 and 08/2019. Results: 590 patients (median age 51 years) were included, median follow up was 38 months, 225 patients (38.1%) achieved pCR. 65 patients (11.0%) were hormone receptor positive HER2 negative (HR+HER2-), 164 (27.8%) were HR-HER2-, 133 (22.5%) were HR+HER2+, 97 (16.4%) were HR-HER2+. Significant difference between the pCR and non-pCR group was observed for HR-status (p & lt;0.001), HER2-status (p & lt;0.001), tumor grading (p & lt;0.001) and Ki-67 (p & lt;0.001). Age of diagnosis (p=0.611), menopause-status (p=0.769), tumor size (p=0.183) and nodal status (p=0.163) did not significantly vary between patients with pCR versus non-pCR. Patients with pCR had significantly higher rates of anemia II° (p=0.006). No significant difference was seen for anemia ≥III°, neutropenia ≥II°, deviation of liver enzymes ≥II°, nephrotoxicity ≥II°, polyneuropathy ≥II° or the administration of red cell and platelet concentrate as well as the use of Granulocyte-Colony Stimulating Factor (G-CSF). 3 year overall survival (OS), metastasis-free survival (MFS) and recurrence-free survival (RFS) were found to be significantly better in patients with pCR (OS: 98.0% vs. 90.2%, p & lt;0.001; MFS: 94.5% vs. 84.6%, p & lt;0.001; RFS: 97.7% vs. 94.0 %, p=0.029). Patients with pCR had a significantly higher mean rSDIP (69.8 vs. 58.9, p=0.001) and dSDIP (59.5 vs. 49.1, p=0.001). Mean RDI did not significantly vary between pCR and non-pCR (0.853 vs. 0.840, p=0.350). Mean rSDIP and dSDIP significantly vary between the tumor subtypes HR+HER2-, HR-HER2-, HR+HER2+, and HR-HER2+ (rSDIP: 47.4, 54.5, 74.3, 76.7; p & lt;0.001; dSDIP: 39.5, 43.3, 62.0, 67.0; p & lt;0.001). Mean rSDIP and dSDIP did not significantly vary between patients with pCR and non-pCR within the tumor subtypes. Conclusion: Outcomes for NACT are consistent with published data concerning pCR rates. It is notable that the pCR group had significantly higher rSDIP and dSDIP than the non-pCR group whereas RDI and toxicity did not significantly vary between the two groups. rSDIP and dSDIP were mainly depending on the tumor subtype. This data confirms that the tumor subtype has a major impact on pCR rate. Whilst this retrospective analysis must be interpreted with caution, the results show that SDIP is an integral parameter for assessing the efficacy and adequate application of combination therapy and is associated with pCR rate and overall survival. Citation Format: Thomas M Deutsch, Michelle Kobel, Manuel Feisst, Fabian Riedel, Katharina Smetanay, Carlo Fremd, Laura Michel, Michael Golatta, Joerg Heil, Markus Wallwiener, Andreas Schneeweiss. Impact of summation dose intensity product on pathologic response in patients receiving neoadjuvant chemotherapy for early breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-12-08.

Type of Medium: Online Resource

ISSN: 0008-5472 , 1538-7445

URL: Article

DOI: 10.1158/1538-7445.SABCS21-P2-12-08

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2022

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detail.hit.zdb_id: 1432-1

detail.hit.zdb_id: 410466-3

In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 4_Supplement ( 2022-02-15), p. PD7-02-PD7-02

Abstract: Background: Neoadjuvant systemic treatment (NST) elicits a pathologic complete response (pCR, ypT0, ypN0) in 40-70% of women with HER2 positive, triple-negative, and high-proliferative Luminal B breast cancer. These patients may not need surgery as all local tumor has already been eradicated by NST. However, their safe identification prior to surgery is a major challenge: imaging after NST, minimally-invasive biopsies, or combinations of both using narrow patient selection criteria are not accurate enough either because they showed high rates of missed cancer or high rates of missed pCR. Recently, the concept of an intelligent, minimally-invasive, vacuum-assisted biopsy (intelligent VAB) was introduced to identify exceptional responders to NST. The intelligent VAB is a multivariate risk algorithm that uses artificial intelligence techniques to analyze conventional VAB results alongside contextualizing patient, imaging, and tumor information. It showed great potential to reliably identify patients with a pCR in the breast (ypT0). However, the absent integration of the axillary status impairs clinical applicability. In this study, we evaluated the feasibility of an intelligent VAB to identify exceptional responders to NST in the breast and axilla. Methods: We trained, tested, and validated a machine learning algorithm (Extreme Gradient Boosting Tree) using patient, imaging, tumor, and conventional VAB variables to detect residual cancer after NST (ypT+/is or ypN+) prior to surgery. We used data from 318 women with cT1-3, cN0/+, HER2 positive, triple-negative breast or high-proliferative Luminal B breast cancer who underwent VAB before surgery (NCT02948764). We used 10-fold cross-validation to train and test the algorithm which was externally validated using data of an independent, similar trial (NCT02575612). Findings were compared to the histopathologic evaluation of the surgical specimen. False-negative rate (FNR), specificity, and area under the ROC curve (AUROC) were the main outcome measures. Results: In the development set (n=318), mean patient age was 52.5 years and 45.3% (144 of 318) achieved a pCR (ypT0 and ypN0). Using resampling methods, the intelligent VAB showed an FNR of 5.2% (9 of 174, 95% CI 2.4-9.5), a specificity of 37.5% (54 of 144, 95% CI 29.6-45.9), and an AUROC of 0.92 (95% CI 0.90-0.94) in the development set to detect residual cancer (ypT+/is or ypN+) after NST. In the external validation set (n=45), mean patient age was 48.1 years and 44.4% (20 of 45) achieved a pCR. The intelligent VAB showed an FNR of 0% (0 of 25, 95% CI 0.0-13.7), a specificity of 40.0% (8 of 20, 95% CI 19.1-63.9) and an AUROC of 0.91 (95% CI 0.82-0.97). Spiegelhalter’s Z confirmed a well-calibrated model (z score -0.746, P 0.228). FNR of the intelligent VAB was lower compared to imaging after NST, conventional VAB, or combinations of both using narrow patient selection criteria. Conclusion: An intelligent VAB can reliably exclude residual cancer after NST for women with cT1-3, cN0/+, HER2 positive, triple-negative breast or high-proliferative Luminal B breast cancer. The omission of breast and axillary surgery for these exceptional responders may be evaluated in future trials. Trial registration: NCT02948764 and NCT02575612. Funding: German Research Foundation (DFG) Diagnostic Performance ComparisonFalse-negative rate - % (95% CI); no.Specificity - % (95% CI); no.Negative predictive value - % (95% CI); no.Positive predictive value - % (95% CI); no.AUROC - value (95% CI)Development set (n=318)Imaging after NST24.4% (18.0-13.7); 40 of 16452.2% (43.4-61.0); 69 of 13263.3% (53.5-72.3); 69 of 10966.3% (59.1-73.0); 124 of 187-Conventional VAB32.8% (25.8-40.3); 57 of 174100% (97.5-100); 144 of 14471.6% (64.9-77.8); 144 of 201100% (96.9-100); 117 of 117-Imaging after NST + VAB16.7% (11.4-23.2); 28 of 16832.1% (24.4-40.6); 44 of 13761.1% (48.9-72.4); 44 of 7260.1% (56.1-69.1); 140 of 223-VAB + patient selection9.1% (5.0-14.1) 15 of 17036.3% (28.2-45.0); 49 of 13576.6% (64.3-86.2); 49 of 6464.3% (57.9-70.4); 155 of 241-Intelligent VAB (Extreme Gradient Boosting tree)5.2% (2.4-9.6); 9 of 17437.5% (29.6-45.9); 54 of 14485.7% (74.6-93.3); 54 of 6364.7% (58.5-70.6); 165 of 2550.92 (0.90-0.94)External validation (n=45)Imaging after NST24.0% (9.4-45.1%);6 of 2565.0% (40.8-84.6%);13 of 2068.4% (43.4-87.4%);13 of 1973.1% (52.2-88.4%);19 of 26-Conventional VAB28.0% (12.1-49.4%);7 of 25100% (83.2-100%);20 of 2074.1% (53.7-88.9%);20 of 27100% (81.5-100%);18 of 18-Imaging after NST + VAB12.0% (2.5-31.2); 3 of 2565.0% (40.8-84.6%);13 of 2081.3% (54.4-96.0%); 13 of 1675.9% (56.5-89.7%); 22 of 29-VAB + patient selection4.0% (1.0-2.4); 1 of 2530.0% (9.4-45.1%); 6 of 2085.7% (69.8-99.8); 6 of 763.2% (46.0-78.2); 24 of 38-Intelligent VAB (Extreme Gradient Boosting tree)0.0% (0.0-13.7%);0 of 2540.0% (19.1-63.9%);8 of 20100% (63.1-100%);8 of 867.8% (50.2-82.0%);25 of 370.91 (0.82 - 0.97)AUROC = Area under the receiver operating characteristic curve; CI = confidence interval Citation Format: André Pfob, Chris Sidey-Gibbons, Geraldine Rauch, Bettina Thomas, Benedikt Schaefgen, Sherko Kuemmel, Toralf Reimer, Markus Hahn, Marc Thill, Jens-Uwe Blohmer, John Hackmann, Wolfram Malter, Inga Bekes, Kay Friedrichs, Sebastian Wojcinski, Sylvie Joos, Stefan Paepke, Tom Degenhardt, Joachim Rom, Achim Rody, Regina Große, Marion van Mackelenbergh, Mattea Reinisch, Maria Karsten, Michael Golatta, Joerg Heil. Intelligent vacuum-assisted breast biopsy to identify breast cancer patients with pathologic complete response after neoadjuvant systemic treatment for omission of breast and axillary surgery [abstract] . In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD7-02.

Type of Medium: Online Resource

ISSN: 0008-5472 , 1538-7445

URL: Article

DOI: 10.1158/1538-7445.SABCS21-PD7-02

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2022

detail.hit.zdb_id: 2036785-5

detail.hit.zdb_id: 1432-1

detail.hit.zdb_id: 410466-3

In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 5_Supplement ( 2023-03-01), p. PD15-11-PD15-11

Abstract: Introduction: Chemotherapy is recommended for patients with luminal breast cancer and more than three positive nodes. In addition, recent landmark trials raised the question if the exact number of positive nodes is required to indicate genomic testing. In the neoadjuvant setting, response-driven therapy is increasingly used and may be influenced by surgical staging of the axilla. The present study addressed the role of axillary lymph node dissection (ALND) as decision aid for systemic therapy in a contemporary cohort of patients with clinically node-positive breast cancer in the adjuvant and neoadjuvant setting. Methods: The study was preplanned in the international multicenter phase-III OPBC-03/TAXIS trial (ClinicalTrials.gov Identifier: NCT03513614). The first 500 patients with clinically node-positive breast cancer who were randomized after tailored axillary surgery (TAS) to undergo ALND or axillary radiotherapy (ART) without ALND in the context of extended regional irradiation were included from August 2018 to June 2022. Clinically node-positive breast cancer was defined by confirmed nodal disease at the time of initial diagnosis; in case of neoadjuvant therapy, the finding of residual nodal disease was mandatory for randomization. TAS consisted of removal of palpably suspicious findings and the sentinel nodes with the option of image guidance. In the ART arm, the total number of positive nodes was not known. We analyzed the impact of ALND on rate and type of systemic therapy. Results: A total of 500 patients with a median age of 57 years (IQR: 48-69 years) were included at 44 breast centers from six European countries. Subtype was hormone receptor (HR) positive (+) and human epidermal growth factor receptor 2 (HER2) negative (-) in 393 (80.0%), HR+/HER2+ in 52 (10.6%), HR-/HER2+ in 5 (1.0%) and HR-/HER2- in 34 (6.9%) patients. Of 343 patients (68.6%) who were treated in the adjuvant setting, 297 had HR+/HER2- disease. Of these 297 patients, 145 (48.8%) underwent ART without ALND and 152 (51.2%) underwent ALND after TAS. In the ART arm, the median number of lymph nodes removed was five (IQR 4-8), three (IQR 1-4) of which were positive and in the ALND arm, the number was 19 (IQR 14-26), four (IQR 2-9) of which were positive (p & lt; 0.001). The use of ALND had no significant impact on the rate of patients with HR+/HER2- disease undergoing adjuvant chemotherapy (51.0% in the ART and 57.9% in the ALND arm, p=0.2), and there were no significant differences in type of systemic therapy with the exception of tamoxifen, which was 18.4% with ALND versus 9.0% without (p=0.018). A total of 143 patients (28.6%) underwent neoadjuvant chemotherapy, 13 had neoadjuvant antihormonal treatment and one had neoadjuvant double HER2-blockade without chemotherapy. Of the 143 patients who received neoadjuvant chemotherapy, 71 (49.7%) underwent ART without ALND and 72 (50.3%) underwent ALND. In the ART arm, the median number of lymph nodes removed was four (IQR 3-6), one (IQR 1-3) of which was positive and in the ALND arm, the number was 16 (IQR 12-19), two (IQR 1-5) of which were positive (p & lt; 0.001). The use of ALND in patients after neoadjuvant treatment had no significant impact on the rate of adjuvant systemic therapy (71.8% in the ART and 65.3% in the ALND arm, p=0.4), with no significant differences in type of chemotherapy (e.g., capecitabine: 11.3% vs 12.5%, p=0.8; T-DM1: 11.3% vs. 11.1%, p & gt;0.9) or antihormonal therapy (e.g., aromatase inhibitors: 49.3% vs. 41.7%, p=0.4; tamoxifen: 11.3% vs. 5.6%, p=0.2). Discussion: This study showed that although ALND significantly increased the number of positive nodes removed in the adjuvant and neoadjuvant setting, it had no relevant impact on rate and type of adjuvant systemic therapy. Citation Format: Walter P. Weber, Zoltan Matrai, Stefanie Hayoz, Christoph Tausch, Guido Henke, Daniel R. Zwahlen, Günther Gruber, Frank Zimmermann, Thomas Ruhstaller, Simone Muenst, Markus Ackerknecht, Sherko Küemmel, Vesna Bjelic-Radisic, Viktor Smanykó, Conny Vrieling, Rok Satler, Inna Meyer, Charles Becciolini, Susanne Bucher, Colin Simonson, Peter M. Fehr, Natalie Gabriel, Robert Maráz, Dimitri Sarlos, Konstantin J. Dedes, Cornelia Leo, Gilles Berclaz, Hisham Fansa, Christopher Hager, Klaus Reisenberger, Ákos Sávolt, Christian F. Singer, Roland Reitsamer, Jelena Winkler, Giang Thanh Lam Lam, Mathias K. Fehr, Tatiana Naydina, Magdalena Kohlik, Karine Clerc, Valerijus Ostapenko, Florian Fitzal, Martin Heidinger, Nadia Maggi, Alexandra Schulz, Pagona Markellou, Loïc Lelièvre, Daniel Egle, Jörg Heil, Michael Knauer, Christian Kurzeder. PD15-11 Axillary dissection to determine nodal burden to inform systemic therapy recommendations in patients with clinically node-positive breast cancer: Pre-planned substudy of TAXIS (OPBC-03, SAKK 23/16, IBCSG 57-18, ABCSG-53, GBG 101) [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 PD15-11.

Type of Medium: Online Resource

ISSN: 1538-7445

URL: Article

DOI: 10.1158/1538-7445.SABCS22-PD15-11

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2023

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detail.hit.zdb_id: 1432-1

detail.hit.zdb_id: 410466-3

In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 4_Supplement ( 2022-02-15), p. PD11-05-PD11-05

Abstract: Background: Breast ultrasound identifies additional carcinomas not detected in mammography, but has a higher rate of false-positive findings which result in more unnecessary breast biopsies. Shear-Wave Elastography (SWE), an ultrasound technique used to quantify the stiffness of a lesion, showed promising results to improve the diagnostic performance of B-mode breast ultrasound but also to miss some cancers. As the stiffness of a lesion is found to be influenced by individual patient characteristics, incorporation of lesion stiffness in more individualized assessments may be key to the problem of reducing unnecessary breast biopsies without impairing the breast cancer detection rate. Thus, in this study, we evaluated whether an intelligent algorithm incorporating traditional SWE values as well as other patient and clinical variables (hereafter “intelligent SWE”) could reduce the number of unnecessary breast biopsies without impairing the breast cancer detection rate compared to traditional SWE and B-mode breast ultrasound for patients with suspicious breast lesions. Methods: We trained, tested, and validated machine learning algorithms using patient, clinical, ultrasound, and SWE information to classify breast masses. We used international, multicenter data from 857 women with BI-RADS 4 breast masses at 12 study sites in 7 countries. Patients underwent B-mode breast ultrasound, SWE, and subsequent histopathologic evaluation. 10-fold cross-validation was used to train and test the algorithms on data from 11 of the 12 sites which were further validated using the additional site’s data. The results of B-mode breast ultrasound, traditional SWE, and intelligent SWE were compared to the gold standard of histopathologic evaluation. We calculated sensitivity, specificity, and AUROC and used McNemar tests to test for significant differences in diagnostic performance. Results: The mean age was 49.5 years (SD 16.3) and 42.2% breast masses (n=362 of 857) were found to be malignant as confirmed by histopathology. In the external validation set (n=285), traditional SWE showed a significantly higher diagnostic performance compared to B-mode breast ultrasound (P & lt; 0.001), whereas intelligent SWE outperformed both B-mode breast ultrasound and traditional SWE (P & lt; 0.001). The neural network algorithm showed a significantly higher diagnostic performance compared to the Logistic Regression with Elastic Net Penalty (P = 0.004). The neural network algorithm achieved a sensitivity of 100% (95% CI 97.1 to 100%, 126 of 126) and a specificity of 50.3% (95% CI 42.3 to 58.3%, 80 of 159); the number of unnecessary biopsies were reduced by 50.3% (79 vs. 159) without missing any cancer compared to B-mode breast ultrasound. Model-agnostic variable importance plots to provide insights into the model predictions showed that the three most important variables for intelligent SWE were patient age followed by Shear-Wave velocity and orientation of the lesion (parallel vs. not parallel) in B-mode ultrasound. Conclusion: This is the first evidence which suggests that the majority of false-positive breast biopsies could be safely avoided by using intelligent SWE without impairing breast cancer detection rates. These results may be helpful in their ability to reduce treatment burden for patients, providers, and healthcare systems. Trial registration: NCT02638935. Funding: Siemens Medical Solutions USA, Inc Diagnostic Performance ComparisonB-mode Breast UltrasoundTraditional Shear-Wave ElastographyIntelligent Shear-Wave Elastography – Logistic Regression with Elastic Net PenaltyIntelligent Shear-Wave Elastography – neural networkAUROC – value (95% CI)–0.84 (0.79-0.89)0.93 (0.90-0.95)0.93 (0.90-0.96)Sensitivity – % (95% CI); no.100% (97.1-100%); 126 of 12697.6% (93.2-99.5%); 123 of 126100% (97.1-100%); 126 of 126100% (97.1-100%); 126 of 126Specificity – % (95% CI); no.0% (0.0-2.3%); 0 of 15923.9% (17.5-31.3%); 38 of 15936.5% (29.0-44.5%); 58 of 15950.3% (42.3-58.3%); 80 of 159Negative predictive value – % (95% CI); no.–92.7% (80.1-98.5%); 38 of 41100% (93.8-100%); 58 of 58100% (95.5-100%); 80 of 80Positive predictive value – % (95% CI); no.44.2% (38.4-50.2); 126 of 28550.4% (44.0-56.8%); 123 of 24455.5% (48.8-62.1%); 126 of 22761.5% (54.4-68.2%); 126 of 205 Citation Format: André Pfob, Chris Sidey-Gibbons, Richard G. Barr, Volker Duda, Zaher Alwafai, Corinne Balleyguier, Dirk-André Clevert, Sarah Fastner, Christina Gomez, Manuela Goncalo, Ines Gruber, Markus Hahn, André Hennigs, Chi Ho, Panagiotis Kapetas, Sheng-Chieh Lu, Juliane Nees, Ralf Ohlinger, Fabian Riedel, Matthieu Rutten, Benedikt Schaefgen, Anne Stieber, Riku Togawa, Mitsuhiro Tozaki, Sebastian Wojcinski, Cai Xu, Geraldine Rauch, Joerg Heil, Michael Golatta. Intelligent shear-wave elastography to reduce unnecessary biopsies in breast cancer diagnosis (INSPiRED 002): An international, multicenter analysis [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD11-05.

Type of Medium: Online Resource

ISSN: 0008-5472 , 1538-7445

URL: Article

DOI: 10.1158/1538-7445.SABCS21-PD11-05

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2022

detail.hit.zdb_id: 2036785-5

detail.hit.zdb_id: 1432-1

detail.hit.zdb_id: 410466-3

In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 20, No. 10 ( 2011-10-01), p. 2222-2231

Abstract: Background: The single-nucleotide polymorphism (SNP) 5p12-rs10941679 has been found to be associated with risk of breast cancer, particularly estrogen receptor (ER)-positive disease. We aimed to further explore this association overall, and by tumor histopathology, in the Breast Cancer Association Consortium. Methods: Data were combined from 37 studies, including 40,972 invasive cases, 1,398 cases of ductal carcinoma in situ (DCIS), and 46,334 controls, all of white European ancestry, as well as 3,007 invasive cases and 2,337 controls of Asian ancestry. Associations overall and by tumor invasiveness and histopathology were assessed using logistic regression. Results: For white Europeans, the per-allele OR associated with 5p12-rs10941679 was 1.11 (95% CI = 1.08–1.14, P = 7 × 10−18) for invasive breast cancer and 1.10 (95% CI = 1.01–1.21, P = 0.03) for DCIS. For Asian women, the estimated OR for invasive disease was similar (OR = 1.07, 95%CI = 0.99–1.15, P = 0.09). Further analyses suggested that the association in white Europeans was largely limited to progesterone receptor (PR)-positive disease (per-allele OR = 1.16, 95% CI = 1.12–1.20, P = 1 × 10−18 vs. OR = 1.03, 95% CI = 0.99–1.07, P = 0.2 for PR-negative disease; Pheterogeneity = 2 × 10−7); heterogeneity by ER status was not observed (P = 0.2) once PR status was accounted for. The association was also stronger for lower grade tumors [per-allele OR (95% CI) = 1.20 (1.14–1.25), 1.13 (1.09–1.16), and 1.04 (0.99–1.08) for grade 1, 2, and 3/4, respectively; Ptrend = 5 × 10−7]. Conclusion: 5p12 is a breast cancer susceptibility locus for PR-positive, lower grade breast cancer. Impact: Multicenter fine-mapping studies of this region are needed as a first step to identifying the causal variant or variants. Cancer Epidemiol Biomarkers Prev; 20(10); 2222–31. ©2011 AACR.

Type of Medium: Online Resource

ISSN: 1055-9965 , 1538-7755

URL: Article

DOI: 10.1158/1055-9965.EPI-11-0569

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2011

detail.hit.zdb_id: 2036781-8

detail.hit.zdb_id: 1153420-5

In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 4_Supplement ( 2021-02-15), p. PS3-18-PS3-18

Abstract: Background and objectives: The Breast Imaging Reporting and Data System (BI-RADS) has helped to standardize radiologic reports and assessment in breast cancer diagnostics. So far, BI-RADS consists of the sole, standardized description of images. Individual patient characteristics like disease and family history or age are no part of the current BI-RADS classification system but are often subjectively considered to evaluate the risk of breast cancer in the clinical setting. It is however unclear how and to which extent such additional patient information influence the evaluation of risk of malignancy. Thus, we compared the performance in the detection of breast cancer between the sole analysis of ultrasound images by physician experts and a physician actually examining and counseling a patient in the clinical setting. Methods: This multicenter, prospective trial took place at 11 trial sites in Austria, France, Germany, Japan, Netherlands, Portugal, and the US from February 2016 to March 2019. The trial enrolled 1288 women presenting with a lesion ≥0.5 and ≤5 cm in 2D B-mode ultrasound. In the clinical setting, the examiner conducted a routine 2D B-mode ultrasound examination and had additional standard information about the patients’ disease history and family history. The final ultrasound images made in the clinical routine (annotated with size measurements) but not any other information about the patient was given to three physician experts ( & gt;15 years of experience in breast cancer diagnostics). The examiner in the clinical setting and each of the three experts evaluated the ultrasound images according to BI-RADS and gave a likelihood score for malignancy according to ACR (American College of Radiology). Following the BI-RADS definition by ACR, malignancy was assumed for a likelihood of malignancy & gt;2% (BI-RADS 4 or higher). All patients underwent histopathological confirmation which was the gold standard against which the clinical examiner and the three experts were compared. AUC, sensitivity, specificity, negative-predictive value (NPV), and positive-predictive value (PPV) were the performance measures. Results: Histopathologic evaluation showed malignancy in 368 of 1288 lesions (28.6%). AUC of the examiner in the clinical setting (AUC=0.94; 95% CI 0.92-0.95) was significantly better as for all three experts evaluating images only: expert one AUC=0.78 (95% CI 0.75-0.81); expert two AUC=0.81 (95% CI 0.78-0.84); expert three AUC=0.83 (95% CI 0.80-0.86). Sensitivity, specificity, NPV, and PPV of the examiner in the clinical setting were better as for all three experts evaluating images only. NPV of the examiner in the clinical setting was 98.6% (425 of 431), for expert one 87.8% (381 of 434), for expert two 91.2% (198 of 217), and for expert 3 84.1% (413 of 491). Conclusion: Our findings suggest that information about individual patient characteristics (e.g. age, disease and family history) has great influence to accurately evaluate the risk of breast cancer. Future research may look into incorporating not only a standardized description of images into the BI-RADS classification system but also a standardized description of these individual patient characteristics to further standardize and objectify the risk evaluation in breast cancer diagnostics. Trial registration: NCT02638935 Performance of the examiner in the clinical setting and the three experts evaluating images onlyExaminer clinical settingImages only – Expert 1Images only – Expert 2Images only – Expert 3AUC (95% CI)0.94 (0.92-0.95)0.78 (0.75-0.81)0.81 (0.78-0.84)0.83 (0.80-0.86)Sensitivity –% (no.)98.4% (362 of 368)85.6% (315 of 368)94.8% (349 of 368)78.8% (290 of 368)Specificity –% (no.)46.2% (425 of 920)41.4% (381 of 920)21.5% (198 of 920)44.9% (413 of 920)Negative Predictive Value –% (no.)98.6% (425 of 431)87.8% (381 of 434)91.2% (198 of 217)84.1% (413 of 491)Positive Predictive Value –% (no.)42.2% (362 of 857)36.9% (315 of 854)32.6% (349 of 1071)36.4% (290 of 797) Citation Format: André Pfob, Richard G. Barr, Volker Duda, Christopher Buesch, Joerg Heil, Michael Golatta. Differences in the diagnostic performance of breast ultrasound with or without additional patient information: A secondary analysis of an international multicenter trial [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-18.

Type of Medium: Online Resource

ISSN: 0008-5472 , 1538-7445

URL: Article

DOI: 10.1158/1538-7445.SABCS20-PS3-18

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2021

detail.hit.zdb_id: 2036785-5

detail.hit.zdb_id: 1432-1

detail.hit.zdb_id: 410466-3

In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 4_Supplement ( 2021-02-15), p. PS3-16-PS3-16

Abstract: Background and objectives: The Breast Imaging Reporting and Data System (BI-RADS) provides a standardized way to describe ultrasound images in breast cancer diagnostics. However, there is little information which descriptors are most strongly associated with malignancy and to which extend the single descriptors (tissue composition, shape, orientation, margin of lesion, echo pattern, posterior features, and calcifications) should be considered for the final evaluation of risk of malignancy. Thus, we aimed to identify which BI-RADS descriptors are most strongly associated with malignancy when evaluating ultrasound images in breast cancer diagnostics. Methods: This multicenter, prospective trial took place at 11 trial sites in Austria, France, Germany, Japan, Netherlands, Portugal, and the US from February 2016 to March 2019. The trial enrolled 1288 women presenting with a lesion ≥0.5 and ≤5 cm in 2D B-mode ultrasound. The examiner conducted a routine 2D B-mode ultrasound examination and had additional standard information about the patients’ disease history and family history. The examiner described the ultrasound images according to BI-RADS. All patients underwent histopathological confirmation which was the gold standard against which the clinical examiner was compared. We performed univariate and multivariate analyses using descriptive statistics, Chi-Square test, and logistic regression to identify which image descriptors are associated with malignancy. Results: Histopathologic evaluation showed malignancy in 368 of 1288 lesions (28.6%). The descriptors most strongly associated with malignancy were spiculated margins (rate of malignancy 84.9%; 79 of 93), calcification (69.9%; 51 of 73), un-parallel orientation (65.9%; 187 of 284), angular margins (64.6%; 64 of 99), posterior shadowing (62.4%; 88 of 142), irregular shape (55.2%; 208 of 377), and indistinct margins (52.0%; 185 of 356). Different tissue compositions and echo patterns were least useful to distinguish between malign and benign lesions. Upon multivariate analysis, calcifications (OR 5.52; 95% CI 1.94-15.87) and posterior shadowing (OR 16.13; 95% CI 2.75-90.91) remained significantly (p & lt;0.05) associated with malignancy. Conclusion: We identified which BI-RADS descriptors are most strongly associated with malignancy when evaluating ultrasound images in breast cancer diagnostics. Future research may look into providing not only a standardized image description but also a standardized final evaluation for the rate of malignancy with respect to the different predictive usefulness of the single descriptors. This may further standardize and objectify the risk evaluation in breast cancer diagnostics. Trial registration: NCT02638935 Table 1: Association of BI-RADS descriptors with final histopathologic resultsbenign pathologymalignant pathologyp-valuetissue compositionp & lt;0.0001homogeneous background texture; fat —no. (%)185 (60.3)122 (39.74)homogeneous background texture; fibroglandular —no. (%)378 (77.3)111 (22.7)heterogeneous background texture —no. (%)356 (72.7)134 (27.4)shape of lesionp & lt;0.0001oval —no. (%)659 (86.1)106 (13.8)round —no. (%)89 (62.7)53 (37.3)irregular —no. (%)169 (44.8)208 (55.2)orientation of lesionp & lt;0.0001parallel —no. (%)806 (82.6)170 (17.42)not parallel —no. (%)97 (34.15)187 (65.9)margin of lesionp & lt;0.0001circumcised —no. (%)644 (89.0)80 (11.0)indistinct margin —no. (%)171 (48.0)185 (52.0)angular margin —no. (%)35 (35.4)64 (64.6)microlobulated margin —no. (%)117 (60.0)78 (40.0)spiculated margin —no. (%)14 (15.1)79 (84.9)echo patternp=0.02anechoic —no. (%)7 (100)0 (0.0)hyperechoic —no. (%)30 (79.0)8 (21.0)complex cystic and solid —no. (%)52 (82.5)11 (17.5)hypoechoic —no. (%)645 (71.0)264 (29.0)isoechoic —no. (%)40 (78.4)11 (21.6)heterogeneous —no. (%)136 (64.8)74 (35.2)posterior featuresp & lt;0.0001none —no. (%)590 (73.2)216 (26.8)enhancement —no. (%)249 (83.3)50 (16.7)shadowing —no. (%)53 (37.6)88 (62.4)combined pattern —no. (%)20 (58.8)14 (41.2)calcificationp & lt;0.0001no calcification —no. (%)894 (73.8)317 (26.2)calcification —no. (%)22 (30.1)51 (69.9) Citation Format: André Pfob, Richard G. Barr, Volker Duda, Christopher Buesch, Joerg Heil, Michael Golatta. Identifying the most relevant descriptors when evaluating ultrasound images in breast cancer diagnostics: A secondary analysis of an international multicenter trial [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-16.

Type of Medium: Online Resource

ISSN: 0008-5472 , 1538-7445

URL: Article

DOI: 10.1158/1538-7445.SABCS20-PS3-16

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2021

detail.hit.zdb_id: 2036785-5

detail.hit.zdb_id: 1432-1

detail.hit.zdb_id: 410466-3

In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 4_Supplement ( 2021-02-15), p. PS2-42-PS2-42

Abstract: Purpose: Neoadjuvant systemic treatment elicits a pathologic complete response (pCR) in an average of 35% of women with breast cancer. In such cases, breast surgery may be considered overtreatment. However, imaging and vacuum-assisted biopsy (VAB) alone showed high rates of missed cancer compared to standard breast surgery. We therefore evaluated multivariate algorithms using patient, tumor, and VAB variables to accurately identify patients with breast pCR. Methods: We developed and tested three multivariate approaches: elastic net regression, Support Vector Machines (SVM), and a deep neural network. We analyzed 452 patients, randomly partitioned into training and test samples (2:1 ratio), who participated in three prospective studies assessing the feasibility of VAB to accurately detect residual disease after neoadjuvant systemic treatment (NST). The studies were conducted at 23 sites in the United States, Germany, and South Korea. The trials enrolled women who presented with clinical stage I-III breast cancer of any biological subtype and a partial or complete response to NST confirmed by ultrasonography, mammography, or magnetic resonance imaging; all patients underwent guideline-adherent surgery. We compared the performance of the multivariate algorithms to the histopathologic evaluation of disease response in the surgical specimen (reference standard) - false-negative rate (FNR, missed residual cancer) and specificity (identification of breast pCR) were the main outcome measures. The best performing algorithm on the test set with respect to sensitivity and specificity was validated using data of an independent fourth trial. We compared the performance of the multivariate approaches to the performance of imaging and/or VAB. Results: In the test set (n=152), elastic net regression, SVM and the neural network revealed an FNR of 1.2% (1 of 85 patients with missed residual disease). Specificity of the elastic net regression was 46.3% (31 of 67 women with surgically confirmed breast pCR identified), of the SVM 62.7% (42 of 67) and of the neural network 67.2% (45 of 67). All multivariate algorithms performed better than imaging or VAB: FNR 25.9% (22 of 85) and 16.5% (14 of 85), respectively. Subsequent external validation (n=50) of the neural network algorithm showed a false-negative rate of 0% (0 of 27) and a specificity of 65.2% (15 of 23). The area under the ROC curve for the deep neural network was 0.97 (95% CI, 0.94 to 1.00). Analyzing the coefficients of the elastic net regression (regularized beta; ß) showed that the lesion diameter on imaging after NST (ß = 0.31) and VAB results (ß = 0.49) were the most important variables in the prediction of residual tumor. Other variables were also important: age (ß = 0.18), in-situ in the initial diagnostic (not VAB) biopsy (ß = 0.11), difficulties during the pathologic evaluation of the VAB specimen (ß = 0.11); needle size 7G (ß = -0.06, as opposed to 8G, 9G, 10G), multicentricity on imaging after NST (ß = 0.06), hormone-receptor positivity (ß = 0.01), and a clip marker positioned within the (former) lesion (ß = -0.01, as opposed to a clip marker positioned & lt;5mm or & gt;5mm from the lesion Conclusion: A multivariate algorithm can accurately select breast cancer patients without residual disease after neoadjuvant treatment. This finding may pave the way to study omission of breast surgery in these patients in the future. Performance of multivariate algorithms compared to imaging and vacuum-assisted biopsyFalse-negative rate - value (95% CI)Specificity - value (95% CI)Negative predictive value - value (95% CI)Positive predictive value - value (95% CI)Test set (n=152)Imaging25.9% (17.0-36.5%)61.2% (48.5-72.9%)65.1% (52.0-76.7%)70.8% (60.2-79.9%)VAB16.5% (9.3-26.1%)89.6% (79.7-95.7%)81.1% (70.3-89.3%)91.0% (82.4-96.3%)Imaging + VAB5.9% (1.9-13.2%)52.2% (39.7-64.6)87.5% (73.2-95.8%)71.4% (62.1-79.6%)Elastic net regression1.2% (0.0-6.4%)46.3% (34.0-58.9%)96.9% (83.8-99.9%)70.0% (61.0%-78.0%)Support Vector Machine1.2% (0.0-6.4%)62.7% (50.0 - 74.2%)97.7% (87.7-99.9%)77.1% (68.0-84.6%)Deep Neural Network1.2% (0.0-6.4%)67.2% (54.6-78.2%)97.8% (88.5-99.9%)79.3% (70.3-86.5%)Validation set (n=50)Deep Neural Network0.0% (0.0-12.8%)65.2% (42.7-83.6%)100% (78.2-100%)77.1% (59.9-89.6%) Citation Format: André Pfob, Chris Sidey-Gibbons, Han-Byoel Lee, Marios Konstantinos Tasoulis, Vivian Koelbel, Michael Golatta, Gaiane M. Rauch, Benjamin D. Smith, Vicente Valero, Fiona MacNeill, Wonshik Han, Walter Paul Weber, Geraldine Rauch, Henry Kuerer, Joerg Heil. Identify breast cancer patients with pathologic complete response in the breast after neoadjuvant systemic treatment - an international, multicenter analysis [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS2-42.

Type of Medium: Online Resource

ISSN: 0008-5472 , 1538-7445

URL: Article

DOI: 10.1158/1538-7445.SABCS20-PS2-42

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2021

detail.hit.zdb_id: 2036785-5

detail.hit.zdb_id: 1432-1

detail.hit.zdb_id: 410466-3

In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 5_Supplement ( 2023-03-01), p. P2-14-01-P2-14-01

Abstract: Introduction: The goal of breast conserving surgery (BCS) for early breast cancer (EBC) is to remove the tumor in toto and preserving as much of the normal breast tissue as possible. In 20-50% of cases a re-excision is necessary because of involved margins. Repeat surgeries are not only a burden to patients physically but also psychologically and can delay recommended adjuvant therapies. Accurate determination of tumor margins during surgery is therefore a critical need. Breast cancer tissue produces significantly higher amounts of VEGF-A than healthy tissue. VEGF-A stimulates tumor angiogenesis and is therefore a target for molecular imaging techniques. The fluorescence imaging agent bevacizumab-IRDye800CW (Beva800) is a conjugate of bevacizumab and IRDye800CW and binds specifically to VEGF-A. Beva800 provides a potentially efficacious approach to imaging specimen and cavity margins during BCS. We are presenting a phase II study that combined Beva800 with the SurgVision Explorer Air camera for intraoperative margin assessment during BCS for EBC. Methods: MARGIN II is a multicenter open-label single arm prospective clinical trial aimed at evaluating Beva800 for assessment of tumor margins in women with EBC scheduled for BCS. The study was a within-patient comparison of positive tumor margin rates using BCS standard of care margin assessment compared to intraoperative assessment with 4.5 mg Beva800 and fluorescence imaging with the SurgVision Explorer Air camera. All patients received an i.-v. bolus injection of 4.5 mg of Beva800 three days before surgery. The fluorescent signal was visualized during surgery using NIR fluorescence imaging (700–1000 nm). Standard of care margin assessment was defined as visual inspection, palpation and, in cases of pre-operative wire marking, specimen sonography or mammography. Beva800 efficacy was determined as the number of patients in which a pathology-confirmed positive margin was identified by fluorescence-guided surgery using Beva800 but not by standard of care BCS. Results: 49 patients were included in 5 centers. 4 training cases were only included in the safety analysis, 45 patients were evaluable for the efficacy analysis. 8 patients (17.8%) had involved margins after standard of care BCS, 4 of which were detected by molecular fluorescence intraoperatively resulting in the reduction of patients with positive margins by 50% (95% CI: 15.7%, 84.3%). 4 patients (8.9%; 95% CI: 2.5%, 21.1%) needed a re-excision because of involved margins. In 27 patients (60.0%) the additional molecular fluorescence guided cavity shaving did not change the resection status from positive to negative (false positive). Adverse events were reported by 16 of 49 patients (32.7%), but only 3 (6.1%) were related to Beva800 (syncope, hot flush, hypertensive crisis). One patient experienced a treatment related SAE (hypertensive crisis). No anti-Beva800 antibodies were detected. Conclusion: In our analysis the rate of necessary second operations was reduced by 50% using Beva800 and the SurgVision Explorer Air camera. The safety analysis confirmed the positive safety profile of Beva800 found in previous studies. Molecular fluorescence-guided surgery may have the potential to change the practice of breast conserving surgery by reducing unnecessary re-excisions. Future studies will have to address the high false positive rates. Citation Format: Hans-Christian Kolberg, Carmen Röhm, Angrit Stachs, Florian Schütz, Jens-Uwe Blohmer, Sarah Wetzig, Steffi Hartmann, Jörg Heil, Markus Hahn. MOLECULAR FLUORESCENCE-GUIDED SURGERY USING BEVA800 FOR THE ASSESSMENT OF TUMOR MARGINS DURING BREAST CONSERVING SURGERY OF PATIENTS WITH PRIMARY BREAST CANCER (MARGIN-II) [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 P2-14-01.

Type of Medium: Online Resource

ISSN: 1538-7445

URL: Article

DOI: 10.1158/1538-7445.SABCS22-P2-14-01

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2023

detail.hit.zdb_id: 2036785-5

detail.hit.zdb_id: 1432-1

detail.hit.zdb_id: 410466-3