Multimodality Imaging Review of HER2-positive Breast Cancer and                     Response to Neoadjuvant Chemotherapy

Portnow, Leah H.; Kochkodan-Self, Jeanne; Maduram, Amy; Barrios, Mirelys; Onken, Allison; Hong, Xuefei; Mittendorf, Elizabeth A.; Giess, Catherine S.; Chikarmane, Sona A.

doi:10.1148/rg.220103

Cited by 9 publications

(11 citation statements)

References 58 publications

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“…They claim to, by using radiomics, have “achieved non‐invasive and effective prediction of HER2‐low breast cancer.” The material is small, but it is still an important addition to the literature. The literature so far has concentrated on multiparametric approaches more than on radiomics 2,4,5 . However, I did a short search on PubMed and found 222,898 articles on radiomics, but only 10 concerning breast cancer HER2 or subdivision of breast cancers.…”

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confidence: 99%

“…It gives a comprehensive overview of the present state of imaging diagnostics. 2 The article published in the present journal is a study using radiomics in order to identify HER2-low (IHC 1+) cancers. 3 They claim to, by using radiomics, have "achieved non-invasive and effective prediction of HER2-low breast cancer."…”

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confidence: 99%

“…The literature so far has concentrated on multiparametric approaches more than on radiomics. 2,4,5 However, I did a short search on PubMed and found 222,898 articles on radiomics, but only 10 concerning breast cancer HER2 or subdivision of breast cancers. The most relevant of those are listed in the presented article.…”

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confidence: 99%

“…1 Different imaging modalities and approaches have been used for describing breast cancer, and in a recent article in RadioGraphics, imaging of HER2-positive cancer is described. 2 This article discusses diagnoses of HER2-positive breast cancer toward HER2-negative and the different treatment options. It gives a comprehensive overview of the present state of imaging diagnostics.…”

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confidence: 99%

“…To achieve targeted therapy, one relies on immunohistochemical (IHC) analyses 1 . Different imaging modalities and approaches have been used for describing breast cancer, and in a recent article in RadioGraphics, imaging of HER2‐positive cancer is described 2 . This article discusses diagnoses of HER2‐positive breast cancer toward HER2‐negative and the different treatment options.…”

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confidence: 99%

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Editorial for “Potential Antihuman Epidermal Growth Factor Receptor 2 Target Therapy Beneficiaries: The Role of MRI‐Based Radiomics in Distinguishing Human Epidermal Growth Factor Receptor 2‐Low Status of Breast Cancer”

Geitung

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Magnetic Resonance Imaging

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confidence: 99%

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confidence: 99%

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confidence: 99%

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Editorial for “Potential Antihuman Epidermal Growth Factor Receptor 2 Target Therapy Beneficiaries: The Role of MRI‐Based Radiomics in Distinguishing Human Epidermal Growth Factor Receptor 2‐Low Status of Breast Cancer”

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Improving Neoadjuvant Therapy Response Prediction by Integrating Longitudinal Mammogram Generation with Cross-Modal Radiological Reports: A Vision-Language Alignment-Guided Model

Gao,

Zhou,

Wang

et al. 2024

Lecture Notes in Computer Science

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Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case–control study

Sui,

Yan,

Jiang

et al. 2023

Breast Cancer Res Treat

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Background The objective of this study was to develop a model combining ultrasound (US) and clinicopathological characteristics to predict the pathologic response to neoadjuvant chemotherapy (NACT) in human epidermal growth factor receptor 2 (HER2)-positive breast cancer. Materials and methods This is a retrospective study that included 248 patients with HER2-positive breast cancer who underwent NACT from March 2018 to March 2022. US and clinicopathological characteristics were collected from all patients in this study, and characteristics obtained using univariate analysis at p < 0.1 were subjected to multivariate analysis and then the conventional US and clinicopathological characteristics independently associated with pathologic complete response (pCR) from the analysis were used to develop US models, clinicopathological models, and their combined models by the area under the receiver operating characteristic (ROC) curve (AUC), accuracy, sensitivity, and specificity to assess their predictive efficacy. Results The combined model had an AUC of 0.808, a sensitivity of 88.72%, a specificity of 60.87%, and an accuracy of 75.81% in predicting pCR of HER2-positive breast cancer after NACT, which was significantly better than the clinicopathological model (AUC = 0.656) and the US model (AUC = 0.769). In addition, six characteristics were screened as independent predictors, namely the Clinical T stage, Clinical N stage, PR status, posterior acoustic, margin, and calcification. Conclusion The conventional US combined with clinicopathological characteristics to construct a combined model has a good diagnostic effect in predicting pCR in HER2-positive breast cancer and is expected to be a useful tool to assist clinicians in effectively determining the efficacy of NACT in HER2-positive breast cancer patients.

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Multimodality Imaging Review of HER2-positive Breast Cancer and Response to Neoadjuvant Chemotherapy

Cited by 9 publications

References 58 publications

Editorial for “Potential Antihuman Epidermal Growth Factor Receptor 2 Target Therapy Beneficiaries: The Role of MRI‐Based Radiomics in Distinguishing Human Epidermal Growth Factor Receptor 2‐Low Status of Breast Cancer”

Editorial for “Potential Antihuman Epidermal Growth Factor Receptor 2 Target Therapy Beneficiaries: The Role of MRI‐Based Radiomics in Distinguishing Human Epidermal Growth Factor Receptor 2‐Low Status of Breast Cancer”

Improving Neoadjuvant Therapy Response Prediction by Integrating Longitudinal Mammogram Generation with Cross-Modal Radiological Reports: A Vision-Language Alignment-Guided Model

Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case–control study

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