Literature DB >> 28934812

Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy for Primary Breast Cancer Comparing Interim Ultrasound, Shear Wave Elastography and MRI.

Andrew Evans1, Patsy Whelehan2, Alastair Thompson3, Colin Purdie4, Lee Jordan4, Jane Macaskill5, Shelley Waugh6, Frances Fuller-Pace7, Katrin Brauer2, Sarah Vinnicombe1.   

Abstract

BACKGROUND: Prediction of pathological complete response (pCR) of primary breast cancer to neoadjuvant chemotherapy (NACT) may influence planned surgical approaches in the breast and axilla. The aim of this project is to assess the value of interim shear wave elastography (SWE), ultrasound (US) and magnetic resonance imaging (MRI) after 3 cycles in predicting pCR.
METHODS: 64 patients receiving NACT had baseline and interim US, SWE and MRI examinations. The mean lesion stiffness at SWE, US and MRI diameter was measured at both time points. We compared four parameters with pCR status: a) Interim mean stiffness ≤ or > 50 kPa; b) Percentage stiffness reduction; c) Percentage US diameter reduction and d) Interim MRI response using RECIST criteria. The Chi square test was used to assess significance.
RESULTS: Interim stiffness of ≤ or > 50 kPa gave the best prediction of pCR with pCR seen in 10 of 14 (71 %) cancers with an interim stiffness of ≤ 50 kPa, compared to 7 of 50 (14 %) of cancers with an interim stiffness of > 50 kPa, (p < 0.0001) (sensitivity 59 %, specificity 91 %, PPV 71 %, NPV 86 % and diagnostic accuracy 83 %). Percentage reduction in stiffness was the next best parameter (sensitivity 59 %, specificity 85 %, p < 0.0004) followed by reduction in MRI diameter of > 30 % (sensitivity 50 % and specificity 79 %, p = 0.03) and % reduction in US diameter (sensitivity 47 %, specificity 81 %, p = 0.03). Similar results were obtained from ROC analysis.
CONCLUSION: SWE stiffness of breast cancers after 3 cycles of NACT and changes in stiffness from baseline are strongly associated with pCR after 6 cycles. © Georg Thieme Verlag KG Stuttgart · New York.

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Year:  2017        PMID: 28934812     DOI: 10.1055/s-0043-111589

Source DB:  PubMed          Journal:  Ultraschall Med        ISSN: 0172-4614            Impact factor:   6.548


  12 in total

1.  Spatial Attention-Based Deep Learning System for Breast Cancer Pathological Complete Response Prediction with Serial Histopathology Images in Multiple Stains.

Authors:  Hongyi Duanmu; Shristi Bhattarai; Hongxiao Li; Chia Cheng Cheng; Fusheng Wang; George Teodoro; Emiel A M Janssen; Keerthi Gogineni; Preeti Subhedar; Ritu Aneja; Jun Kong
Journal:  Med Image Comput Comput Assist Interv       Date:  2021-09-21

2.  Evaluation of the Property of Axillary Lymph Nodes and Analysis of Lymph Node Metastasis Factors in Breast Cancer by Ultrasound Elastography.

Authors:  Jia Zhou; Qingyu Zhang; Qi Zhang; Lei Yan; Qing Gao
Journal:  Comput Math Methods Med       Date:  2022-06-03       Impact factor: 2.809

3.  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

4.  Early ultrasound evaluation identifies excellent responders to neoadjuvant systemic therapy among patients with triple-negative breast cancer.

Authors:  Beatriz E Adrada; Rosalind Candelaria; Stacy Moulder; Alastair Thompson; Peng Wei; Gary J Whitman; Vicente Valero; Jennifer K Litton; Lumarie Santiago; Marion E Scoggins; Tanya W Moseley; Jason B White; Elizabeth E Ravenberg; Wei T Yang; Gaiane M Rauch
Journal:  Cancer       Date:  2021-04-20       Impact factor: 6.921

Review 5.  Evaluation of the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer.

Authors:  Huan Wang; Xiaoyun Mao
Journal:  Drug Des Devel Ther       Date:  2020-06-18       Impact factor: 4.162

6.  Monitoring breast cancer response to neoadjuvant chemotherapy with ultrasound signal statistics and integrated backscatter.

Authors:  Hanna Piotrzkowska-Wróblewska; Katarzyna Dobruch-Sobczak; Ziemowit Klimonda; Piotr Karwat; Katarzyna Roszkowska-Purska; Magdalena Gumowska; Jerzy Litniewski
Journal:  PLoS One       Date:  2019-03-14       Impact factor: 3.240

7.  Early assessment of shear wave elastography parameters foresees the response to neoadjuvant chemotherapy in patients with invasive breast cancer.

Authors:  Juanjuan Gu; Eric C Polley; Max Denis; Jodi M Carter; Sandhya Pruthi; Adriana V Gregory; Judy C Boughey; Robert T Fazzio; Mostafa Fatemi; Azra Alizad
Journal:  Breast Cancer Res       Date:  2021-04-29       Impact factor: 8.408

Review 8.  A Narrative Review of Ultrasound Technologies for the Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer.

Authors:  Jing Wang; Yanhua Chu; Baohua Wang; Tianan Jiang
Journal:  Cancer Manag Res       Date:  2021-10-14       Impact factor: 3.989

9.  Study on association between shear wave elastography parameters and clinicopathological characteristics in breast cancer: A protocol for systematic review.

Authors:  Hong-Hong Xue; Yuan-Yuan Wang
Journal:  Medicine (Baltimore)       Date:  2020-11-20       Impact factor: 1.817

Review 10.  Assessment and Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer: A Comparison of Imaging Modalities and Future Perspectives.

Authors:  Valeria Romeo; Giuseppe Accardo; Teresa Perillo; Luca Basso; Nunzia Garbino; Emanuele Nicolai; Simone Maurea; Marco Salvatore
Journal:  Cancers (Basel)       Date:  2021-07-14       Impact factor: 6.639

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