Literature DB >> 31407967

Predicting Axillary Response to Neoadjuvant Chemotherapy: Breast MRI and US in Patients with Node-Positive Breast Cancer.

Rihyeon Kim1, Jung Min Chang1, Han-Byoel Lee1, Su Hyun Lee1, Soo-Yeon Kim1, Eun Sil Kim1, Nariya Cho1, Woo Kyung Moon1.   

Abstract

Background In patients who are expected to achieve axillary pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC), omission of axillary lymph node (LN) dissection could prevent morbidity and complications. Purpose To develop a clinical model to predict residual axillary LN metastasis in patients with clinically node-positive breast cancer after NAC by using MRI and US. Materials and Methods In this retrospective study, women with clinically node-positive breast cancer who were treated with NAC following surgery between January 2015 and September 2017 were included. The patients were randomly assigned to a test and validation set (7:3 ratio). Univariable and multivariable logistic regression analyses were performed to evaluate the independent predictors of residual axillary LN metastasis in the test set. A prediction risk score was developed based on the odds ratios from the multivariable analysis and validated in both sets. Results A total of 408 women were included (mean age ± standard deviation, 47.9 years ± 9.6). The axillary pCR rate was 56.6% (231 of 408). Independent predictors of residual axillary LN metastasis were clinical stage N2 or N3, presence of axillary lymphadenopathy at US after NAC, tumor size reduction less than 50% at MRI, Ki-67 negativity, hormone receptor positivity, and human epidermal growth factor receptor 2 negativity (all, P < .05). In a model using these predictors, the area under the receiver operating characteristic curve in the test and validation sets was 0.84 (95% confidence interval: 0.79, 0.88) and 0.78 (95% confidence interval: 0.70, 0.87), respectively. When the patients had a simplified risk score of 1, the false-negative rates ranged between 5%-10%. Conclusion A prediction model incorporating nodal status stage, US finding, MRI response, and molecular receptor status shows good diagnostic performance for residual axillary lymph node metastasis after neoadjuvant chemotherapy in patients with clinically node-positive breast cancer. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Whitman in this issue.

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Year:  2019        PMID: 31407967     DOI: 10.1148/radiol.2019190014

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  15 in total

1.  Can We Use MRI and US to Predict Axillary Node Response in Breast Cancer?

Authors:  Gary J Whitman
Journal:  Radiology       Date:  2019-08-13       Impact factor: 11.105

2.  Can we avoid axillary lymph node dissection in N2 breast cancer patients with chemo-sensitive tumours such as HER2 and TNBC?

Authors:  Amparo Garcia-Tejedor; Sergi Fernandez-Gonzalez; Raul Ortega; Miguel Gil-Gil; Hector Perez-Montero; Eulalia Fernandez-Montolí; Agostina Stradella; Sabela Recalde; Teresa Soler; Anna Petit; Maria Teresa Bajen; Ana Benitez; Anna Guma; Miriam Campos; Maria J Pla; Evelyn Martinez; Maria Laplana; Sonia Pernas; Diana Perez-Sildekova; Isabel Catala; Jordi Ponce; Catalina Falo
Journal:  Breast Cancer Res Treat       Date:  2020-10-17       Impact factor: 4.872

3.  Prediction of axillary response by monitoring with ultrasound and MRI during and after neoadjuvant chemotherapy in breast cancer patients.

Authors:  Na Lae Eun; Eun Ju Son; Hye Mi Gweon; Jeong-Ah Kim; Ji Hyun Youk
Journal:  Eur Radiol       Date:  2019-12-04       Impact factor: 5.315

4.  Predicting axillary response to neoadjuvant chemotherapy: the role of diffusion weighted imaging.

Authors:  Lucia Graña-López; Tania Pérez-Ramos; Fiz Andrés Maciñeira; Ángeles Villares; Manuel Vázquez-Caruncho
Journal:  Br J Radiol       Date:  2021-11-10       Impact factor: 3.039

5.  Assessment of preoperative axillary nodal disease burden: breast MRI in locally advanced breast cancer before, during and after neoadjuvant endocrine therapy.

Authors:  Jürgen Geisler; Jonn Terje Geitung; Joana Reis; Joao Boavida; Hang T Tran; Marianne Lyngra; Laurens Cornelus Reitsma; Hossein Schandiz; Woldegabriel A Melles; Kjell-Inge Gjesdal
Journal:  BMC Cancer       Date:  2022-06-25       Impact factor: 4.638

6.  Development and Validation of an MRI Radiomics-Based Signature to Predict Histological Grade in Patients with Invasive Breast Cancer.

Authors:  Shihui Wang; Yi Wei; Zhouli Li; Jingya Xu; Yunfeng Zhou
Journal:  Breast Cancer (Dove Med Press)       Date:  2022-10-14

7.  Combining conventional ultrasound and sonoelastography to predict axillary status after neoadjuvant chemotherapy for breast cancer.

Authors:  Jia-Xin Huang; Shi-Yang Lin; Yan Ou; Cai-Gou Shi; Yuan Zhong; Ming-Jie Wei; Xiao-Qing Pei
Journal:  Eur Radiol       Date:  2022-04-02       Impact factor: 7.034

8.  Criteria for identifying residual tumours after neoadjuvant chemotherapy of breast cancers: a magnetic resonance imaging study.

Authors:  Yunju Kim; Sung Hoon Sim; Boram Park; In Hye Chae; Jai Hong Han; So-Youn Jung; Seeyoun Lee; Youngmi Kwon; In Hae Park; Kyounglan Ko; Chan Wha Lee; Keun Seok Lee; Han-Sung Kang; Eun Sook Lee
Journal:  Sci Rep       Date:  2021-01-12       Impact factor: 4.379

9.  Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer.

Authors:  Signe Borgquist; Lisa Rydén; Ida Skarping; Daniel Förnvik; Sophia Zackrisson
Journal:  Breast Cancer Res Treat       Date:  2021-06-12       Impact factor: 4.872

10.  Artificial Intelligence Algorithm-Based Ultrasound Image Segmentation Technology in the Diagnosis of Breast Cancer Axillary Lymph Node Metastasis.

Authors:  Lianhua Zhang; Zhiying Jia; Xiaoling Leng; Fucheng Ma
Journal:  J Healthc Eng       Date:  2021-07-22       Impact factor: 2.682

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