Preliminary assessment of the effectiveness of neoadjuvant chemotherapy in breast cancer with the use of ultrasound image quality indexes

Neoadjuvant chemotherapy (NAC) in breast cancer requires non-invasive methods of monitoring its effects after each dose of drug therapy. The aim is to isolate responding and non-responding tumors prior to surgery in order to increase patient safety and select the optimal medical follow-up. A new met...

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Published inBiomedical signal processing and control Vol. 80; p. 104393
Main Authors Pawłowska, Anna, Żołek, Norbert, Leśniak-Plewińska, Beata, Dobruch-Sobczak, Katarzyna, Klimonda, Ziemowit, Piotrzkowska-Wróblewska, Hanna, Litniewski, Jerzy
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LanguageEnglish
Published Elsevier Ltd 01.02.2023
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Abstract Neoadjuvant chemotherapy (NAC) in breast cancer requires non-invasive methods of monitoring its effects after each dose of drug therapy. The aim is to isolate responding and non-responding tumors prior to surgery in order to increase patient safety and select the optimal medical follow-up. A new method of monitoring NAC therapy has been proposed. The method is based on image quality indexes (IQI) calculated from ultrasound data obtained from breast tumors and surrounding tissue. Four different tissue regions from the preliminary set of 38 tumors and three data pre-processing techniques are considered. Postoperative histopathology results were used as a benchmark in evaluating the effectiveness of the IQI classification. Out of ten parameters considered, the best results were obtained for the Gray Relational Coefficient. Responding and non-responding tumors were predicted after the first dose of NAC with an area under the receiver operating characteristics curve of 0.88 and 0.75, respectively. When considering subsequent doses of NAC, other IQI parameters also proved usefulness in evaluating NAC therapy. The image quality parameters derived from the ultrasound data are well suited for assessing the effects of NAC therapy, in particular on breast tumors. •A method of the analysis of ultrasound data of the lesion and surrounding tissue•A method of monitoring NAC therapy based on ultrasound data of breast tumors•Subjects responding to NAC can be detected already after the first stage of treatment•Prediction of responding and non-responding tumors with AUC of 0.88 and 0.75•The image quality parameters are well-suited for assessing the effects of NAC therapy
AbstractList Neoadjuvant chemotherapy (NAC) in breast cancer requires non-invasive methods of monitoring its effects after each dose of drug therapy. The aim is to isolate responding and non-responding tumors prior to surgery in order to increase patient safety and select the optimal medical follow-up. A new method of monitoring NAC therapy has been proposed. The method is based on image quality indexes (IQI) calculated from ultrasound data obtained from breast tumors and surrounding tissue. Four different tissue regions from the preliminary set of 38 tumors and three data pre-processing techniques are considered. Postoperative histopathology results were used as a benchmark in evaluating the effectiveness of the IQI classification. Out of ten parameters considered, the best results were obtained for the Gray Relational Coefficient. Responding and non-responding tumors were predicted after the first dose of NAC with an area under the receiver operating characteristics curve of 0.88 and 0.75, respectively. When considering subsequent doses of NAC, other IQI parameters also proved usefulness in evaluating NAC therapy. The image quality parameters derived from the ultrasound data are well suited for assessing the effects of NAC therapy, in particular on breast tumors. •A method of the analysis of ultrasound data of the lesion and surrounding tissue•A method of monitoring NAC therapy based on ultrasound data of breast tumors•Subjects responding to NAC can be detected already after the first stage of treatment•Prediction of responding and non-responding tumors with AUC of 0.88 and 0.75•The image quality parameters are well-suited for assessing the effects of NAC therapy
ArticleNumber 104393
Author Klimonda, Ziemowit
Litniewski, Jerzy
Dobruch-Sobczak, Katarzyna
Piotrzkowska-Wróblewska, Hanna
Pawłowska, Anna
Żołek, Norbert
Leśniak-Plewińska, Beata
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Cites_doi 10.1016/j.tranon.2019.06.004
10.3389/fonc.2021.718531
10.1186/s40644-019-0248-y
10.1038/s41598-019-44376-z
10.1634/theoncologist.8-6-521
10.1007/s10278-010-9353-y
10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3
10.15557/JoU.2019.0013
10.4103/0019-509X.112301
10.1038/s41598-021-82141-3
10.21037/gs-20-836
10.1093/jnci/djs528
10.1007/s00330-021-08293-y
10.1155/2016/6740956
10.1245/s10434-011-2108-2
10.1109/97.995823
10.1016/S0959-8049(00)00197-0
10.1007/s10916-011-9724-z
10.1016/S0960-9776(03)00106-1
10.1371/journal.pone.0213749
10.1109/TIP.2003.819861
10.1016/j.clbc.2017.08.003
10.1016/j.media.2014.11.009
10.1200/JCO.2014.55.2836
10.1158/1538-7445.AM2016-1439
10.1016/j.tranon.2019.05.004
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Keywords Image quality
Neoadjuvant chemotherapy
Breast cancer
Treatment response
Quantitative ultrasound
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References Sethi, Sen, Parshad, Khetarpal, Garg, Sen (b10) 2013; 50
Tadayyon, Sannachi, Gangeh (b30) 2017; 7
Kaufmann, von Minckwitz, Mamounas, Cameron, Carey, Cristofanili (b7) 2012; 19
Ogston, Miller, Payne, Hutcheon, Sarkar, Smith, Schofield, Heys (b21) 2003; 12
Youden (b29) 1950; 3
Marinovich, Houssami, Macaskill, Sardanelli, Irwig, Mamounas (b28) 2013; 105
Dobruch-Sobczak, Piotrzkowska-Wróblewska, Klimonda, Karwat, Roszkowska-Purska, Clauser (b36) 2021; 11
Sheng-Chieh, You-Chen, Weng-Song, Jia-Ming, Tzong-Jer (b18) 2011; 24
Sannachi, Gangeh, Tadayyon, Gandhi, Wright, Slodkowska, Curpen, Sadeghi-Naini, Tran, Czarnota (b16) 2019; 12
Daoud, Bdair, Al-Najar, Alazrai (b27) 2016
Li, Huang, Wang, Lin, Li, Zheng, Wang, Cao, Zhou (b3) 2019; 19
Feng (b2) 2019; 7
Al-Ghazal, Fallowfield, Blamey (b11) 2000; 36
Fernandes, Sannachi, Tran, Koven, Watkins, Hadizad (b32) 2019; 12
Piotrzkowska-Wróblewska, Dobruch-Sobczak, Klimonda, Karwat, Roszkowska-Purska, Gumowska, Litniewski (b15) 2019; 14
Wang, Bovik, Sheikh, Simoncelli (b25) 2004; 13
Oelze (b26) 2013
Klimonda, Karwat, Dobruch-Sobczak (b31) 2019; 9
Choi, Kim, Shin, Cha, Chae, Kim (b12) 2018; 18
Loizou, Pattichis (b22) 2008
Dobruch-Sobczak, Piotrzkowska-Wróblewska, Klimoda, Secomski, Karwat, Markiewicz-Grodzicka, Kolasińska-Ćwikła, Roszkowska-Purska, Litniewski (b6) 2019; 19
Huang, Le, Miao, Zhi, Wang, Chen (b34) 2021; 10
Morigi (b4) 2017; 11
Giordano (b5) 2003; 8
Yao, Zhang, Wu, Li, He, Fengyue (b14) 2022; 75
Cui, Zhao, Han, Zhang, Fan, Zuo (b33) 2021; 11
Deng (b23) 1989; 1
(b1) 2019
Sannachi, Tadayyon, Sadeghi-Naini, Tran, Gandhi, Wright, Oelze, Czarnota (b13) 2015; 20
Mendelson, Böhm-Vélez, Berg (b20) 2013
Spring, Greenup, Reynolds, Smith, Moy, Bardia (b9) 2016; 76
Içer, Coskun, Ikizceli (b19) 2011; 36
Berruti, Amoroso, Gallo, Bertaglia, Simoncini (b8) 2014; 32
Gu, Tong, He, Xu, Yang, Tian (b35) 2022; 32
Wang, Bovik (b24) 2002; 9
Byra, Dobruch-Sobczak, Klimonda, Piotrzkowska-Wroblewska, Litniewski (b17) 2020
Deng (10.1016/j.bspc.2022.104393_b23) 1989; 1
Al-Ghazal (10.1016/j.bspc.2022.104393_b11) 2000; 36
Oelze (10.1016/j.bspc.2022.104393_b26) 2013
Huang (10.1016/j.bspc.2022.104393_b34) 2021; 10
Li (10.1016/j.bspc.2022.104393_b3) 2019; 19
Sethi (10.1016/j.bspc.2022.104393_b10) 2013; 50
Mendelson (10.1016/j.bspc.2022.104393_b20) 2013
Feng (10.1016/j.bspc.2022.104393_b2) 2019; 7
Berruti (10.1016/j.bspc.2022.104393_b8) 2014; 32
Cui (10.1016/j.bspc.2022.104393_b33) 2021; 11
Sannachi (10.1016/j.bspc.2022.104393_b13) 2015; 20
Piotrzkowska-Wróblewska (10.1016/j.bspc.2022.104393_b15) 2019; 14
Kaufmann (10.1016/j.bspc.2022.104393_b7) 2012; 19
Klimonda (10.1016/j.bspc.2022.104393_b31) 2019; 9
Loizou (10.1016/j.bspc.2022.104393_b22) 2008
Daoud (10.1016/j.bspc.2022.104393_b27) 2016
Sannachi (10.1016/j.bspc.2022.104393_b16) 2019; 12
Byra (10.1016/j.bspc.2022.104393_b17) 2020
(10.1016/j.bspc.2022.104393_b1) 2019
Youden (10.1016/j.bspc.2022.104393_b29) 1950; 3
Dobruch-Sobczak (10.1016/j.bspc.2022.104393_b36) 2021; 11
Wang (10.1016/j.bspc.2022.104393_b24) 2002; 9
Spring (10.1016/j.bspc.2022.104393_b9) 2016; 76
Wang (10.1016/j.bspc.2022.104393_b25) 2004; 13
Fernandes (10.1016/j.bspc.2022.104393_b32) 2019; 12
Yao (10.1016/j.bspc.2022.104393_b14) 2022; 75
Içer (10.1016/j.bspc.2022.104393_b19) 2011; 36
Gu (10.1016/j.bspc.2022.104393_b35) 2022; 32
Giordano (10.1016/j.bspc.2022.104393_b5) 2003; 8
Ogston (10.1016/j.bspc.2022.104393_b21) 2003; 12
Tadayyon (10.1016/j.bspc.2022.104393_b30) 2017; 7
Dobruch-Sobczak (10.1016/j.bspc.2022.104393_b6) 2019; 19
Choi (10.1016/j.bspc.2022.104393_b12) 2018; 18
Sheng-Chieh (10.1016/j.bspc.2022.104393_b18) 2011; 24
Morigi (10.1016/j.bspc.2022.104393_b4) 2017; 11
Marinovich (10.1016/j.bspc.2022.104393_b28) 2013; 105
References_xml – volume: 50
  start-page: 58
  year: 2013
  end-page: 64
  ident: b10
  article-title: Histopathologic changes following neoadjuvant chemotherapy in locally advanced breast cancer
  publication-title: Indian J. Cancer
– volume: 76
  start-page: 1439
  year: 2016
  ident: b9
  article-title: Pathological complete response after neoadjuvant chemotherapy predicts improved survival in all major subtypes of breast cancer: systematic review and meta-analyses of over 18, 000 patients
  publication-title: Cancer Res.
– year: 2013
  ident: b20
  article-title: ACR BI-rads® ultrasound
  publication-title: ACR BI-RADS® Atlas, Breast Imaging Reporting and Data System
– volume: 9
  start-page: 81
  year: 2002
  end-page: 84
  ident: b24
  article-title: A universal image quality index
  publication-title: IEEE Signal Process. Lett.
– volume: 12
  start-page: 1177
  year: 2019
  end-page: 1184
  ident: b32
  article-title: Monitoring breast cancer response to neoadjuvant chemotherapy using ultrasound strain elastography
  publication-title: Transl. Oncol.
– volume: 14
  start-page: 1
  year: 2019
  end-page: 15
  ident: b15
  article-title: Monitoring breast cancer response to neoadjuvant chemotherapy with ultrasound signal statistics and integrated backscatter
  publication-title: PLoS ONE
– volume: 12
  start-page: 1271
  year: 2019
  end-page: 1281
  ident: b16
  article-title: Breast cancer treatment response monitoring using quantitative ultrasound and texture analysis: comparative analysis of analytical models
  publication-title: Transl. Oncol.
– year: 2020
  ident: b17
  article-title: Early prediction of response to neoadjuvant chemotherapy in breast cancer sonography using Siamese convolutional neural networks
  publication-title: IEEE J. Biomed. Health Inform.
– year: 2016
  ident: b27
  article-title: A fusion-based approach for breast ultrasound image classification using multiple-ROI texture and morphological analyses
  publication-title: Comput. Math. Methods Med.
– volume: 32
  start-page: 2099
  year: 2022
  end-page: 2109
  ident: b35
  article-title: Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study
  publication-title: Eur. Radiol.
– volume: 75
  year: 2022
  ident: b14
  article-title: Quantitative assessment for characterization of breast lesion tissues using adaptively decomposed ultrasound RF images
  publication-title: Biomed. Signal Process. Control
– volume: 8
  start-page: 521
  year: 2003
  end-page: 530
  ident: b5
  article-title: Update on locally advanced breast cancer
  publication-title: Oncologist
– volume: 19
  start-page: 1508
  year: 2012
  end-page: 1516
  ident: b7
  article-title: Recommendations from an international consensus conference on the current status and future of neoadjuvant systemic therapy in primary breast cancer
  publication-title: Ann. Surg. Oncol.
– volume: 11
  year: 2017
  ident: b4
  article-title: Highlights from the 15th St Gallen international breast cancer conference 15-18 march, 2017, vienna: tailored treatments for patients with early breast cancer
  publication-title: Ecancermedicalscience
– volume: 36
  start-page: 2521
  year: 2011
  end-page: 2528
  ident: b19
  article-title: Quantitative grading using grey relational analysis on ultrasonographic images of a Fatty Liver
  publication-title: J. Med. Syst.
– volume: 105
  start-page: 321
  year: 2013
  end-page: 333
  ident: b28
  article-title: Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after Neoadjuvant therapy
  publication-title: JNCI: J. Natl. Cancer Inst.
– volume: 3
  start-page: 32
  year: 1950
  end-page: 35
  ident: b29
  article-title: Index for rating diagnostic tests
  publication-title: Cancer
– volume: 19
  start-page: 89
  year: 2019
  end-page: 97
  ident: b6
  article-title: Monitoring the response to neoadjuvant chemotherapy in patients with breast cancer using ultrasound scattering coefficient: A preliminary report
  publication-title: J. Ultrason.
– volume: 7
  year: 2019
  ident: b2
  article-title: Accurate prediction of neoadjuvant chemotherapy pathological complete remission (pCR) for the four sub-types of breast cancer
  publication-title: IEEE Access
– volume: 7
  year: 2017
  ident: b30
  article-title: A priori prediction of neoadjuvant chemotherapy response and survival in breast cancer patients using quantitative ultrasound
  publication-title: Sci. Rep.
– volume: 36
  start-page: 1938
  year: 2000
  end-page: 1943
  ident: b11
  article-title: Comparison of psychological aspects and patient satisfaction following breast conserving surgery, simple mastectomy and breast reconstruction
  publication-title: Eur. J. Cancer
– volume: 32
  start-page: 3883
  year: 2014
  end-page: 3891
  ident: b8
  article-title: Pathologic complete response as a potential surrogate for the clinical outcome in patients with breast cancer after neoadjuvant therapy: A meta-regression of 29 randomized prospective studies
  publication-title: J. Clin. Oncol.
– volume: 1
  start-page: 1
  year: 1989
  end-page: 24
  ident: b23
  article-title: Introduction to grey system theory
  publication-title: J. Grey Syst.
– volume: 10
  start-page: 1280
  year: 2021
  end-page: 1290
  ident: b34
  article-title: Prediction of treatment responses to neoadjuvant chemotherapy in breast cancer using contrast-enhanced ultrasound
  publication-title: Gland Surg.
– volume: 12
  start-page: 320
  year: 2003
  end-page: 327
  ident: b21
  article-title: A new histological grading system to assess response of breast cancers to primary chemotherapy: prognostic significance and survival
  publication-title: Breast
– year: 2013
  ident: b26
  article-title: Quantitative Ultrasound in Soft Tissues: Statistics of Scatterer Property Estimates
– volume: 20
  start-page: 224
  year: 2015
  end-page: 236
  ident: b13
  article-title: Non-invasive evaluation of breast cancer response to chemotherapy using quantitative ultrasonic backscatter parameters
  publication-title: Med. Image Anal.
– volume: 24
  start-page: 874
  year: 2011
  end-page: 882
  ident: b18
  article-title: A novel medical image quality index
  publication-title: J. Digit. Imaging
– volume: 18
  start-page: e115
  year: 2018
  end-page: e121
  ident: b12
  article-title: Evaluation of the tumor response after neoadjuvant chemotherapy in breast cancer patients: correlation between dynamic contrast-enhanced magnetic resonance imaging and pathologic tumor cellularity
  publication-title: Clin. Breast Cancer
– volume: 11
  start-page: 1
  year: 2021
  end-page: 12
  ident: b33
  article-title: Predicting pathological complete response after neoadjuvant chemotherapy in advanced breast cancer by ultrasound and clinicopathological features using a nomogram
  publication-title: Front. Oncol.
– year: 2019
  ident: b1
  article-title: National comprehensive cancer network (NCCN)
  publication-title: NCCN Clinical Practice Guidelines in Oncology: Breast Cancer V.1.2019
– volume: 11
  start-page: 1
  year: 2021
  end-page: 9
  ident: b36
  article-title: Multiparametric ultrasound examination for response assessment in breast cancer patients undergoing neoadjuvant therapy
  publication-title: Sci. Rep.
– year: 2008
  ident: b22
  article-title: Despeckle Filtering Algorithms and Software for Ultrasound Imaging
– volume: 9
  start-page: 7963
  year: 2019
  ident: b31
  article-title: Breast-lesions characterization using quantitative ultrasound features of peritumoral tissue
  publication-title: Sci. Rep.
– volume: 13
  start-page: 600
  year: 2004
  end-page: 612
  ident: b25
  article-title: Image quality qssessment: from error visibility to structural similarity
  publication-title: IEEE Trans. Image Process.
– volume: 19
  start-page: 61
  year: 2019
  end-page: 71
  ident: b3
  article-title: Early differentiating between the chemotherapy responders and nonresponders: preliminary results with ultrasonic spectrum analysis of the RF time series in preclinical breast cancer models
  publication-title: Cancer Imaging
– volume: 12
  start-page: 1271
  issue: 10
  year: 2019
  ident: 10.1016/j.bspc.2022.104393_b16
  article-title: Breast cancer treatment response monitoring using quantitative ultrasound and texture analysis: comparative analysis of analytical models
  publication-title: Transl. Oncol.
  doi: 10.1016/j.tranon.2019.06.004
– volume: 75
  issue: 103559
  year: 2022
  ident: 10.1016/j.bspc.2022.104393_b14
  article-title: Quantitative assessment for characterization of breast lesion tissues using adaptively decomposed ultrasound RF images
  publication-title: Biomed. Signal Process. Control
– volume: 11
  start-page: 1
  year: 2021
  ident: 10.1016/j.bspc.2022.104393_b33
  article-title: Predicting pathological complete response after neoadjuvant chemotherapy in advanced breast cancer by ultrasound and clinicopathological features using a nomogram
  publication-title: Front. Oncol.
  doi: 10.3389/fonc.2021.718531
– volume: 19
  start-page: 61
  issue: 1
  year: 2019
  ident: 10.1016/j.bspc.2022.104393_b3
  article-title: Early differentiating between the chemotherapy responders and nonresponders: preliminary results with ultrasonic spectrum analysis of the RF time series in preclinical breast cancer models
  publication-title: Cancer Imaging
  doi: 10.1186/s40644-019-0248-y
– volume: 9
  start-page: 7963
  year: 2019
  ident: 10.1016/j.bspc.2022.104393_b31
  article-title: Breast-lesions characterization using quantitative ultrasound features of peritumoral tissue
  publication-title: Sci. Rep.
  doi: 10.1038/s41598-019-44376-z
– volume: 8
  start-page: 521
  issue: 6
  year: 2003
  ident: 10.1016/j.bspc.2022.104393_b5
  article-title: Update on locally advanced breast cancer
  publication-title: Oncologist
  doi: 10.1634/theoncologist.8-6-521
– volume: 24
  start-page: 874
  issue: 5
  year: 2011
  ident: 10.1016/j.bspc.2022.104393_b18
  article-title: A novel medical image quality index
  publication-title: J. Digit. Imaging
  doi: 10.1007/s10278-010-9353-y
– volume: 3
  start-page: 32
  issue: 1
  year: 1950
  ident: 10.1016/j.bspc.2022.104393_b29
  article-title: Index for rating diagnostic tests
  publication-title: Cancer
  doi: 10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3
– year: 2020
  ident: 10.1016/j.bspc.2022.104393_b17
  article-title: Early prediction of response to neoadjuvant chemotherapy in breast cancer sonography using Siamese convolutional neural networks
  publication-title: IEEE J. Biomed. Health Inform.
– volume: 19
  start-page: 89
  issue: 77
  year: 2019
  ident: 10.1016/j.bspc.2022.104393_b6
  article-title: Monitoring the response to neoadjuvant chemotherapy in patients with breast cancer using ultrasound scattering coefficient: A preliminary report
  publication-title: J. Ultrason.
  doi: 10.15557/JoU.2019.0013
– volume: 50
  start-page: 58
  issue: 1
  year: 2013
  ident: 10.1016/j.bspc.2022.104393_b10
  article-title: Histopathologic changes following neoadjuvant chemotherapy in locally advanced breast cancer
  publication-title: Indian J. Cancer
  doi: 10.4103/0019-509X.112301
– year: 2019
  ident: 10.1016/j.bspc.2022.104393_b1
  article-title: National comprehensive cancer network (NCCN)
– volume: 11
  start-page: 1
  year: 2021
  ident: 10.1016/j.bspc.2022.104393_b36
  article-title: Multiparametric ultrasound examination for response assessment in breast cancer patients undergoing neoadjuvant therapy
  publication-title: Sci. Rep.
  doi: 10.1038/s41598-021-82141-3
– volume: 10
  start-page: 1280
  year: 2021
  ident: 10.1016/j.bspc.2022.104393_b34
  article-title: Prediction of treatment responses to neoadjuvant chemotherapy in breast cancer using contrast-enhanced ultrasound
  publication-title: Gland Surg.
  doi: 10.21037/gs-20-836
– volume: 105
  start-page: 321
  issue: 5
  year: 2013
  ident: 10.1016/j.bspc.2022.104393_b28
  article-title: Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after Neoadjuvant therapy
  publication-title: JNCI: J. Natl. Cancer Inst.
  doi: 10.1093/jnci/djs528
– volume: 32
  start-page: 2099
  year: 2022
  ident: 10.1016/j.bspc.2022.104393_b35
  article-title: Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study
  publication-title: Eur. Radiol.
  doi: 10.1007/s00330-021-08293-y
– year: 2016
  ident: 10.1016/j.bspc.2022.104393_b27
  article-title: A fusion-based approach for breast ultrasound image classification using multiple-ROI texture and morphological analyses
  publication-title: Comput. Math. Methods Med.
  doi: 10.1155/2016/6740956
– volume: 19
  start-page: 1508
  issue: 5
  year: 2012
  ident: 10.1016/j.bspc.2022.104393_b7
  article-title: Recommendations from an international consensus conference on the current status and future of neoadjuvant systemic therapy in primary breast cancer
  publication-title: Ann. Surg. Oncol.
  doi: 10.1245/s10434-011-2108-2
– volume: 11
  issue: 732
  year: 2017
  ident: 10.1016/j.bspc.2022.104393_b4
  article-title: Highlights from the 15th St Gallen international breast cancer conference 15-18 march, 2017, vienna: tailored treatments for patients with early breast cancer
  publication-title: Ecancermedicalscience
– volume: 9
  start-page: 81
  issue: 3
  year: 2002
  ident: 10.1016/j.bspc.2022.104393_b24
  article-title: A universal image quality index
  publication-title: IEEE Signal Process. Lett.
  doi: 10.1109/97.995823
– volume: 7
  issue: 45733
  year: 2017
  ident: 10.1016/j.bspc.2022.104393_b30
  article-title: A priori prediction of neoadjuvant chemotherapy response and survival in breast cancer patients using quantitative ultrasound
  publication-title: Sci. Rep.
– volume: 7
  year: 2019
  ident: 10.1016/j.bspc.2022.104393_b2
  article-title: Accurate prediction of neoadjuvant chemotherapy pathological complete remission (pCR) for the four sub-types of breast cancer
  publication-title: IEEE Access
– volume: 1
  start-page: 1
  issue: 1
  year: 1989
  ident: 10.1016/j.bspc.2022.104393_b23
  article-title: Introduction to grey system theory
  publication-title: J. Grey Syst.
– year: 2008
  ident: 10.1016/j.bspc.2022.104393_b22
– volume: 36
  start-page: 1938
  issue: 15
  year: 2000
  ident: 10.1016/j.bspc.2022.104393_b11
  article-title: Comparison of psychological aspects and patient satisfaction following breast conserving surgery, simple mastectomy and breast reconstruction
  publication-title: Eur. J. Cancer
  doi: 10.1016/S0959-8049(00)00197-0
– volume: 36
  start-page: 2521
  issue: 4
  year: 2011
  ident: 10.1016/j.bspc.2022.104393_b19
  article-title: Quantitative grading using grey relational analysis on ultrasonographic images of a Fatty Liver
  publication-title: J. Med. Syst.
  doi: 10.1007/s10916-011-9724-z
– volume: 12
  start-page: 320
  issue: 5
  year: 2003
  ident: 10.1016/j.bspc.2022.104393_b21
  article-title: A new histological grading system to assess response of breast cancers to primary chemotherapy: prognostic significance and survival
  publication-title: Breast
  doi: 10.1016/S0960-9776(03)00106-1
– volume: 14
  start-page: 1
  issue: 3
  year: 2019
  ident: 10.1016/j.bspc.2022.104393_b15
  article-title: Monitoring breast cancer response to neoadjuvant chemotherapy with ultrasound signal statistics and integrated backscatter
  publication-title: PLoS ONE
  doi: 10.1371/journal.pone.0213749
– volume: 13
  start-page: 600
  issue: 4
  year: 2004
  ident: 10.1016/j.bspc.2022.104393_b25
  article-title: Image quality qssessment: from error visibility to structural similarity
  publication-title: IEEE Trans. Image Process.
  doi: 10.1109/TIP.2003.819861
– volume: 18
  start-page: e115
  issue: 1
  year: 2018
  ident: 10.1016/j.bspc.2022.104393_b12
  article-title: Evaluation of the tumor response after neoadjuvant chemotherapy in breast cancer patients: correlation between dynamic contrast-enhanced magnetic resonance imaging and pathologic tumor cellularity
  publication-title: Clin. Breast Cancer
  doi: 10.1016/j.clbc.2017.08.003
– volume: 20
  start-page: 224
  issue: 1
  year: 2015
  ident: 10.1016/j.bspc.2022.104393_b13
  article-title: Non-invasive evaluation of breast cancer response to chemotherapy using quantitative ultrasonic backscatter parameters
  publication-title: Med. Image Anal.
  doi: 10.1016/j.media.2014.11.009
– volume: 32
  start-page: 3883
  issue: 34
  year: 2014
  ident: 10.1016/j.bspc.2022.104393_b8
  article-title: Pathologic complete response as a potential surrogate for the clinical outcome in patients with breast cancer after neoadjuvant therapy: A meta-regression of 29 randomized prospective studies
  publication-title: J. Clin. Oncol.
  doi: 10.1200/JCO.2014.55.2836
– year: 2013
  ident: 10.1016/j.bspc.2022.104393_b26
– volume: 76
  start-page: 1439
  issue: 14
  year: 2016
  ident: 10.1016/j.bspc.2022.104393_b9
  article-title: Pathological complete response after neoadjuvant chemotherapy predicts improved survival in all major subtypes of breast cancer: systematic review and meta-analyses of over 18, 000 patients
  publication-title: Cancer Res.
  doi: 10.1158/1538-7445.AM2016-1439
– volume: 12
  start-page: 1177
  year: 2019
  ident: 10.1016/j.bspc.2022.104393_b32
  article-title: Monitoring breast cancer response to neoadjuvant chemotherapy using ultrasound strain elastography
  publication-title: Transl. Oncol.
  doi: 10.1016/j.tranon.2019.05.004
– year: 2013
  ident: 10.1016/j.bspc.2022.104393_b20
  article-title: ACR BI-rads® ultrasound
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Snippet Neoadjuvant chemotherapy (NAC) in breast cancer requires non-invasive methods of monitoring its effects after each dose of drug therapy. The aim is to isolate...
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StartPage 104393
SubjectTerms Breast cancer
Image quality
Neoadjuvant chemotherapy
Quantitative ultrasound
Treatment response
Title Preliminary assessment of the effectiveness of neoadjuvant chemotherapy in breast cancer with the use of ultrasound image quality indexes
URI https://dx.doi.org/10.1016/j.bspc.2022.104393
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