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Cancers
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Application of Imaging in Breast Cancer
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Application of Imaging in Breast Cancer

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 10974

Special Issue Editors

Prof. Dr. Yun-Chung Cheung

E-Mail Website
Guest Editor
Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Medical College of Chang Gung University, 5 Fuxing St., Guishan, Taoyuan 333, Taiwan
Interests: breast cancer; breast imaging, breast biopsy; breast screening; surgical planning; image-pathologic correlation
Special Issues, Collections and Topics in MDPI journals
Dr. Yao Melissa Min-Szu

E-Mail Website
Guest Editor
Department of Radiology, Koo Foundation Sun Yat-Sen Cancer Center, Taipei, Taiwan
Interests: breast cancer
Dr. Chung Wai-Shan

E-Mail Website
Guest Editor
Department of Breast Surgery, Chang Gung Memorial Hospital, Taipei, Taiwan
Interests: breast cancer

Special Issue Information

Dear Colleagues,

Breast cancer is the most common female cancer and the second leading cause of death worldwide. Imaging plays an important role in cancer detection and assessment. Breast screening has been recognized as the best way to detect early breast cancer and reduce the mortality of this disease. Early detection has a major impact on survival. For women with clinical symptoms, the features of imaging can help distinguish the benign from malignant, helping in the decision of whether the essential procedure of a biopsy should be carried out. Currently, different kinds of imaging methods have been clinically applied. Mammographic, sonographic and magnetic resonance and PET/CT images are the main examinations in clinical practice, as well as other techniques such as tomosynthesis, contrast-enhanced mammography and sonography, optical imaging and molecular imaging. The purposes of application are wide within diagnosis, pre-operative assessment, therapeutic evaluation or cancer investigation. The data of using single or combined imaging methods and the advanced artificial intelligence/deep learning can provide valuable information for oncology medicine. Although their advantages and limitations have been discussed, the idea and technology of using imaging in breast cancer is still developing.

The aim of this Special Issue is to provide room to share or exchange the clinician/researcher experiences of using imaging in breast cancer, so that the fruitful results and complexity can be available globally. We encourage clinicians/researchers to submit original research papers or reviews. All kinds of clinical-use imaging, either for diagnosis, surgical and oncologic assessment, artificial intelligence, prediction analysis or multimodality observation, are welcome.

We look forward to receiving your contributions.

Prof. Dr. Yun-Chung Cheung
Dr. Yao Melissa Min-Szu
Dr. Chung Wai-Shan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • breast cancer
  • mammography/tomosynthesis/contrast-enhanced mammography
  • sonography/contrast-enhanced sonography
  • magnetic resonance imaging
  • PET/CT
  • quantitative imaging
  • elastography
  • optical imaging
  • artificial intelligence
  • image-guided biopsy

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Published Papers (6 papers)

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Research

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11 pages, 1142 KiB  
Article
Development of an MRI Radiomic Machine-Learning Model to Predict Triple-Negative Breast Cancer Based on Fibroglandular Tissue of the Contralateral Unaffected Breast in Breast Cancer Patients
by Roberto Lo Gullo, Rosa Elena Ochoa-Albiztegui, Jayasree Chakraborty, Sunitha B. Thakur, Mark Robson, Maxine S. Jochelson, Keitha Varela, Daphne Resch, Sarah Eskreis-Winkler and Katja Pinker
Cancers 2024, 16(20), 3480; https://doi.org/10.3390/cancers16203480 - 14 Oct 2024
Viewed by 1315
Abstract
Aim: The purpose of this study was to develop a radiomic-based machine-learning model to predict triple-negative breast cancer (TNBC) based on the contralateral unaffected breast’s fibroglandular tissue (FGT) in breast cancer patients. Materials and methods: This study retrospectively included 541 patients (mean age, [...] Read more.
Aim: The purpose of this study was to develop a radiomic-based machine-learning model to predict triple-negative breast cancer (TNBC) based on the contralateral unaffected breast’s fibroglandular tissue (FGT) in breast cancer patients. Materials and methods: This study retrospectively included 541 patients (mean age, 51 years; range, 26–82) who underwent a screening breast MRI between November 2016 and September 2018 and who were subsequently diagnosed with biopsy-confirmed, treatment-naïve breast cancer. Patients were divided into training (n = 250) and validation (n = 291) sets. In the training set, 132 radiomic features were extracted using the open-source CERR platform. Following feature selection, the final prediction model was created, based on a support vector machine with a polynomial kernel of order 2. Results: In the validation set, the final prediction model, which included four radiomic features, achieved an F1 score of 0.66, an area under the curve of 0.71, a sensitivity of 54% [47–60%], a specificity of 74% [65–84%], a positive predictive value of 84% [78–90%], and a negative predictive value of 39% [31–47%]. Conclusions: TNBC can be predicted based on radiomic features extracted from the FGT of the contralateral unaffected breast of patients, suggesting the potential for risk prediction specific to TNBC. Full article
(This article belongs to the Special Issue Application of Imaging in Breast Cancer)
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16 pages, 8326 KiB  
Article
Cytoarchitecture of Breast Cancer Cells under Diabetic Conditions: Role of Regulatory Kinases—Rho Kinase and Focal Adhesion Kinase
by Diganta Dutta, Matthew Ziemke, Payton Sindelar, Hernan Vargas, Jung Yul Lim and Surabhi Chandra
Cancers 2024, 16(18), 3166; https://doi.org/10.3390/cancers16183166 - 15 Sep 2024
Cited by 1 | Viewed by 1240
Abstract
Diabetes greatly reduces the survival rates in breast cancer patients due to chemoresistance and metastasis. Reorganization of the cytoskeleton is crucial to cell migration and metastasis. Regulatory cytoskeletal protein kinases such as the Rho kinase (ROCK) and focal adhesion kinase (FAK) play a [...] Read more.
Diabetes greatly reduces the survival rates in breast cancer patients due to chemoresistance and metastasis. Reorganization of the cytoskeleton is crucial to cell migration and metastasis. Regulatory cytoskeletal protein kinases such as the Rho kinase (ROCK) and focal adhesion kinase (FAK) play a key role in cell mobility and have been shown to be affected in cancer. It is hypothesized that diabetes/high-glucose conditions alter the cytoskeletal structure and, thus, the elasticity of breast cancer cells through the ROCK and FAK pathway, which can cause rapid metastasis of cancer. The aim of the study was to investigate the role of potential mediators that affect the morphology of cancer cells in diabetes, thus leading to aggressive cancer. Breast cancer cells (MDA-MB-231 and MCF-7) were treated with 5 mM glucose (low glucose) or 25 mM glucose (high glucose) in the presence of Rho kinase inhibitor (Y-27632, 10 mM) or FAK inhibitor (10 mM). Cell morphology and elasticity were monitored using atomic force microscopy (AFM), and actin staining was performed by fluorescence microscopy. For comparative study, normal mammary breast epithelial cells (MCF-10A) were used. It was observed that high-glucose treatments modified the cytoskeleton of the cells, as observed through AFM and fluorescence microscopy, and significantly reduced the elasticity of the cells. Blocking the ROCK or FAK pathway diminished the high-glucose effects. These changes were more evident in the breast cancer cells as compared to the normal cells. This study improves the knowledge on the cytoarchitecture properties of diabetic breast cancer cells and provides potential pathways that can be targeted to prevent such effects. Full article
(This article belongs to the Special Issue Application of Imaging in Breast Cancer)
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13 pages, 1540 KiB  
Article
Tumor-Infiltrating Lymphocyte Level Consistently Correlates with Lower Stiffness Measured by Shear-Wave Elastography: Subtype-Specific Analysis of Its Implication in Breast Cancer
by Na Lae Eun, Soong June Bae, Ji Hyun Youk, Eun Ju Son, Sung Gwe Ahn, Joon Jeong, Jee Hung Kim, Yangkyu Lee and Yoon Jin Cha
Cancers 2024, 16(7), 1254; https://doi.org/10.3390/cancers16071254 - 22 Mar 2024
Viewed by 1358
Abstract
Background: We aimed to elucidate the clinical significance of tumor stiffness across breast cancer subtypes and establish its correlation with the tumor-infiltrating lymphocyte (TIL) levels using shear-wave elastography (SWE). Methods: SWE was used to measure tumor stiffness in breast cancer patients from January [...] Read more.
Background: We aimed to elucidate the clinical significance of tumor stiffness across breast cancer subtypes and establish its correlation with the tumor-infiltrating lymphocyte (TIL) levels using shear-wave elastography (SWE). Methods: SWE was used to measure tumor stiffness in breast cancer patients from January 2016 to August 2020. The association of tumor stiffness and clinicopathologic parameters, including the TIL levels, was analyzed in three breast cancer subtypes. Results: A total of 803 patients were evaluated. Maximal elasticity (Emax) showed a consistent positive association with an invasive size and the pT stage in all cases, while it negatively correlated with the TIL level. A subgroup-specific analysis revealed that the already known parameters for high stiffness (lymphovascular invasion, lymph node metastasis, Ki67 levels) were significant only in hormone receptor-positive and HER2-negative breast cancer (HR + HER2-BC). In the multivariate logistic regression, an invasive size and low TIL levels were significantly associated with Emax in HR + HER2-BC and HER2 + BC. In triple-negative breast cancer, only TIL levels were significantly associated with low Emax. Linear regression confirmed a consistent negative correlation between TIL and Emax in all subtypes. Conclusions: Breast cancer stiffness presents varying clinical implications dependent on the tumor subtype. Elevated stiffness indicates a more aggressive tumor biology in HR + HER2-BC, but is less significant in other subtypes. High TIL levels consistently correlate with lower tumor stiffness across all subtypes. Full article
(This article belongs to the Special Issue Application of Imaging in Breast Cancer)
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13 pages, 29510 KiB  
Article
Magnetic Resonance Imaging Features Associated with a High and Low Expression of Tumor-Infiltrating Lymphocytes: A Stratified Analysis According to Molecular Subtypes
by Jiejie Zhou, Yi Jin, Haiwei Miao, Shanshan Lu, Xinmiao Liu, Yun He, Huiru Liu, Youfan Zhao, Yang Zhang, Yan-Lin Liu, Zhifang Pan, Jeon-Hor Chen, Meihao Wang and Min-Ying Su
Cancers 2023, 15(23), 5672; https://doi.org/10.3390/cancers15235672 - 30 Nov 2023
Cited by 2 | Viewed by 1550
Abstract
A total of 457 patients, including 241 HR+/HER2− patients, 134 HER2+ patients, and 82 TN patients, were studied. The percentage of TILs in the stroma adjacent to the tumor cells was assessed using a 10% cutoff. The low TIL percentages were 82% in [...] Read more.
A total of 457 patients, including 241 HR+/HER2− patients, 134 HER2+ patients, and 82 TN patients, were studied. The percentage of TILs in the stroma adjacent to the tumor cells was assessed using a 10% cutoff. The low TIL percentages were 82% in the HR+ patients, 63% in the HER2+ patients, and 56% in the TN patients (p < 0.001). MRI features such as morphology as mass or non-mass enhancement (NME), shape, margin, internal enhancement, presence of peritumoral edema, and the DCE kinetic pattern were assessed. Tumor sizes were smaller in the HR+/HER2− group (p < 0.001); HER2+ was more likely to present as NME (p = 0.031); homogeneous enhancement was mostly seen in HR+ (p < 0.001); and the peritumoral edema was present in 45% HR+, 71% HER2+, and 80% TN (p < 0.001). In each subtype, the MR features between the high- vs. low-TIL groups were compared. In HR+/HER2−, peritumoral edema was more likely to be present in those with high TILs (70%) than in those with low TILs (40%, p < 0.001). In TN, those with high TILs were more likely to present a regular shape (33%) than those with low TILs (13%, p = 0.029) and more likely to present the circumscribed margin (19%) than those with low TILs (2%, p = 0.009). Full article
(This article belongs to the Special Issue Application of Imaging in Breast Cancer)
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Review

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17 pages, 5539 KiB  
Review
Contrast-Enhanced Mammography: A Literature Review of Clinical Uses for Cancer Diagnosis and Surgical Oncology
by Wai-Shan Chung, Ya-Chun Tang and Yun-Chung Cheung
Cancers 2024, 16(24), 4143; https://doi.org/10.3390/cancers16244143 - 12 Dec 2024
Viewed by 1387
Abstract
Contrast-enhanced mammography (CEM) uses intermittent dual-energy (low- and high-energy) exposures to produce low-energy mammograms and recombine enhanced images after the administration of iodized contrast medium, which provides more detailed information to detect breast cancers by using the features of morphology and abnormal uptake. [...] Read more.
Contrast-enhanced mammography (CEM) uses intermittent dual-energy (low- and high-energy) exposures to produce low-energy mammograms and recombine enhanced images after the administration of iodized contrast medium, which provides more detailed information to detect breast cancers by using the features of morphology and abnormal uptake. In this article, we reviewed the literature to clarify the clinical applications of CEM, including (1) the fundamentals of CEM: the technique, radiation exposure, and image interpretation; (2) its clinical uses for cancer diagnosis, including problem-solving, palpable mass, suspicious microcalcification, architecture distortion, screening, and CEM-guided biopsy; and (3) the concerns of surgical oncology in pre-operative and neoadjuvant chemotherapy assessments. CEM undoubtedly plays an important role in clinical practice. Full article
(This article belongs to the Special Issue Application of Imaging in Breast Cancer)
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21 pages, 333 KiB  
Review
An Updated Review on the Emerging Role of Indocyanine Green (ICG) as a Sentinel Lymph Node Tracer in Breast Cancer
by Ioanna Akrida, Nikolaos V. Michalopoulos, Maria Lagadinou, Maria Papadoliopoulou, Ioannis Maroulis and Francesk Mulita
Cancers 2023, 15(24), 5755; https://doi.org/10.3390/cancers15245755 - 8 Dec 2023
Cited by 12 | Viewed by 3381
Abstract
Sentinel lymph node biopsy (SLNB) has become the standard of care for clinically node-negative breast cancer and has recently been shown by clinical trials to be also feasible for clinically node-positive patients treated with primary systemic therapy. The dual technique using both radioisotope [...] Read more.
Sentinel lymph node biopsy (SLNB) has become the standard of care for clinically node-negative breast cancer and has recently been shown by clinical trials to be also feasible for clinically node-positive patients treated with primary systemic therapy. The dual technique using both radioisotope (RI) and blue dye (BD) as tracers for the identification of sentinel lymph nodes is considered the gold standard. However, allergic reactions to blue dye as well as logistics issues related to the use of radioactive agents, have led to research on new sentinel lymph node (SLN) tracers and to the development and introduction of novel techniques in the clinical practice. Indocyanine green (ICG) is a water-soluble dye with fluorescent properties in the near-infrared (NIR) spectrum. ICG has been shown to be safe and effective as a tracer during SLNB for breast cancer and accumulating evidence suggests that ICG is superior to BD and at least comparable to RI alone and to RI combined with BD. Thus, ICG was recently proposed as a reliable SLN tracer in some breast cancer clinical practice guidelines. Nevertheless, there is lack of consensus regarding the optimal role of ICG for SLN mapping. Specifically, it is yet to be determined whether ICG should be used in addition to BD and/or RI, or if ICG could potentially replace these long-established traditional SLN tracers. This article is an updated overview of somerecent studies that compared ICG with BD and/or RI regarding their accuracy and effectiveness during SLNB for breast cancer. Full article
(This article belongs to the Special Issue Application of Imaging in Breast Cancer)
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