Article
Optics
Shanshan Guo, Junshan Xiu, Lingnan Kong, Xin Kong, Hanqiu Wang, Zhiwei Lu, Famei Xu, Jing Li, Te Ji, Fuli Wang, Huiqiang Liu
Summary: This study introduces a multidimensional data mining method using XPCT and FTIR for breast cancer diagnosis. The results show that this method can accurately visualize the micromorphology of tumor lesions and provide valuable information about the distribution and variation of biomacromolecules in breast tumors. The spectral data of blood samples also demonstrate potential clinical applications for breast cancer diagnosis.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Oncology
Jing Chen, Ji Ma, Chunxiao Li, Sihui Shao, Yijin Su, Rong Wu, Minghua Yao
Summary: This study developed and validated a multi-parameter ultrasound model for breast cancer diagnosis, showing good performance with improved specificity and maintained sensitivity. Using this model could help reduce unnecessary biopsies and guide clinical diagnosis and treatment.
FRONTIERS IN ONCOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Marion Olubunmi Adebiyi, Micheal Olaolu Arowolo, Moses Damilola Mshelia, Oludayo O. Olugbara
Summary: Although breast cancer is the most common malignancy among women globally, routine mammography for diagnosis is not available at all hospitals. In order to improve the accuracy of breast cancer diagnosis, researchers have developed a computerized method based on machine learning. This study demonstrates the effectiveness of machine learning algorithms in classifying and predicting breast cancer.
APPLIED SCIENCES-BASEL
(2022)
Article
Oncology
Catherine Duggan, Dario Trapani, Andre M. Ilbawi, Elena Fidarova, Mathieu Laversanne, Giuseppe Curigliano, Freddie Bray, Benjamin O. Anderson
Summary: Some countries have seen significant reduction in breast cancer mortality rates through increased coverage of essential health services and higher number of public cancer centers. Early diagnosis programs are crucial for improving breast cancer outcomes.
Article
Chemistry, Multidisciplinary
Ya Cao, Xiaomeng Yu, Tianyu Zeng, Ziyi Fu, Yingyan Zhao, Beibei Nie, Jing Zhao, Yongmei Yin, Genxi Li
Summary: The study developed biomimetic vesicles for molecular classification of breast cancer exosomes. These vesicles specifically recognized and fused with breast cancer exosomes, amplifying electrochemical signaling using DNA machinery. Application to clinical samples demonstrated the feasibility and reliability of this method for diagnosis and treatment of breast cancer patients.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2022)
Article
Computer Science, Artificial Intelligence
Bhavannarayanna Kolla, P. Venugopal
Summary: This article introduces two Swin transformer-based models, the teacher model and the student model, for diagnosing breast cancer. The models are trained using transfer learning and knowledge distillation, and the SARSA algorithm is used to improve accuracy and training efficiency. The student model shows promising performance in WSI analysis.
MACHINE LEARNING-SCIENCE AND TECHNOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Masaki Ogawa, Hirohito Kan, Misugi Urano, Tatsuya Kawai, Haruna Nakajima, Kazuma Murai, Hirotaka Miyaji, Tatsuya Toyama, Akio Hiwatashi
Summary: The three-compartment diffusion model using magnetic resonance spectral diffusion analysis accurately differentiated IDC from DCIS, but it was not superior to ADC and D-IVIM.
MAGNETIC RESONANCE IMAGING
(2023)
Article
Biochemistry & Molecular Biology
Sara D. Alharthi, Hemalatha Kanniyappan, Soundarya Prithweeraj, Divya Bijukumar, Mathew T. Mathew
Summary: Breast cancer is the second leading cause of cancer-related mortality in women worldwide and in the United States. Early detection using a cost-effective, rapid, and highly sensitive approach such as an electrochemical biosensor is crucial for better treatment outcomes. Our research focuses on using the ECM1 biomarker with higher expression in synthetic urine to develop such a biosensor for breast cancer detection.
INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
(2023)
Article
Geriatrics & Gerontology
Ruoning Yang, Yunhao Wu, Yana Qi, Weijing Liu, Ya Huang, Xin Zhao, Ruixian Chen, Tao He, Xiaorong Zhong, Qintong Li, Li Zhou, Jie Chen
Summary: The treatment decisions for elderly patients with breast cancer are highly variable, and researchers have developed a predictive model to estimate the breast cancer-specific death risk, which can assist clinicians in decision-making.
Article
Engineering, Biomedical
Jingqi Song, Yuanjie Zheng, Muhammad Zakir Ullah, Junxia Wang, Yanyun Jiang, Chenxi Xu, Zhenxing Zou, Guocheng Ding
Summary: The study proposed a deep learning classification model that combines multiple features of CESM. The experimental results indicate that our method is more precise than the state-of-the-art methods and produces accurate results for the classification of CESM images.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
(2021)
Article
Biochemistry & Molecular Biology
Qing Ye, Jiajia Wang, Barbara Ducatman, Rebecca A. Raese, Jillian L. Rogers, Ying-Wooi Wan, Chunlin Dong, Lindsay Padden, Elena N. Pugacheva, Yong Qian, Nancy Lan Guo
Summary: Currently, there is no gene expression assay available to determine whether premalignant lesions will progress to invasive breast cancer. This study aimed to identify biomarkers that can predict the development of invasive carcinoma in patients with normal breast tissue, benign lesions, or premalignant lesions. A set of 26-gene mRNA expression profiles successfully identified invasive ductal carcinomas and selected those with a higher likelihood of developing cancer in breast tissue associated with atypical ductal hyperplasia (ADH). The gene signature showed high accuracy in classifying invasive ductal carcinomas from normal tissue and benign lesions, and accurately predicted cancer development in ADH tissues. Furthermore, this gene signature had prognostic value, demonstrated associations with drug sensitivity/resistance, and led to the discovery of a potential new drug for breast cancer treatment.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Biochemistry & Molecular Biology
Qian Zhao, Lei Shen, Jinhui Lue, Heying Xie, Danni Li, Yuanyuan Shang, Liqun Huang, Lingyu Meng, Xuefeng An, Jieru Zhou, Jing Han, Zuoren Yu
Summary: A miRNA model for the diagnosis of breast cancer using blood samples was developed, showing high sensitivity and specificity.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Article
Biochemical Research Methods
Mei-Huan Wang, Xiao Liu, Qian Wang, Hua-Wei Zhang
Summary: This study investigated the diagnostic efficiency of Raman spectroscopy for breast cancer. The meta-analysis results showed that Raman spectroscopy has high sensitivity and specificity for breast cancer diagnosis and may be an effective and accurate tool.
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2022)
Review
Pharmacology & Pharmacy
Yue Wang, Haroon Iqbal, Uzair Ur-Rehman, Lina Zhai, Ziyin Yuan, Anam Razzaq, Man Lv, Huiying Wei, Xin Ning, Jun Xin, Run Xiao
Summary: Since the approval of Abraxane, an albumin-based nanodrug, by the FDA in 2005, protein-based nanoparticles have gained considerable interest in the field of nanomedicine for cancer therapy. Serum albumin-based nanodevices, loaded with various diagnostic and therapeutic agents, offer several advantages such as biocompatibility, prolonged blood circulation, and targeted delivery to breast cancer cells. This mini-review provides an overview of albumin and its properties, tumor targeting mechanisms, designed formulations, and their applications in breast cancer diagnosis and therapy.
JOURNAL OF DRUG DELIVERY SCIENCE AND TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Mehedi Masud, Amr E. Eldin Rashed, M. Shamim Hossain
Summary: Breast cancer is a common and deadly disease affecting millions of women worldwide. Researchers have proposed various convolutional neural network models to assist in diagnostic process. However, the lack of standard models and large datasets for training and validation remains a challenge. This study explores the use of transfer learning and evaluates eight pre-trained models on ultrasound images of breast cancers, as well as introduces a custom convolutional neural network that outperforms the pre-trained models.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Oncology
Jenna L. Mueller, Henry L. Fu, Jeffrey K. Mito, Melodi J. Whitley, Rhea Chitalia, Alaattin Erkanli, Leslie Dodd, Diana M. Cardona, Joseph Geradts, Rebecca M. Willett, David G. Kirsch, Nimmi Ramanujam
INTERNATIONAL JOURNAL OF CANCER
(2015)
Editorial Material
Biochemical Research Methods
Rainer A. Leitgeb, Peter E. Andersen, Juergen Popp, Nimmi Ramanujam, Katarina Svanberg
JOURNAL OF BIOMEDICAL OPTICS
(2015)
Article
Biochemical Research Methods
Brandon S. Nichols, Antonio Llopis, Gregory M. Palmer, Samuel S. McCachren, Ozlem Senlik, David Miller, Martin A. Brooke, Nan M. Jokerst, Joseph Geradts, Rachel Greenup, Nimmi Ramanujam
JOURNAL OF BIOMEDICAL OPTICS
(2017)
Article
Multidisciplinary Sciences
Robert Morhard, Corrine Nief, Carlos Barrero Castedo, Fangyao Hu, Megan Madonna, Jenna L. Mueller, Mark W. Dewhirst, David F. Katz, Nirmala Ramanujam
SCIENTIFIC REPORTS
(2017)
Article
Biochemical Research Methods
Gregory M. Palmer, Hengtao Zhang, Chen-Ting Lee, Husam Mikati, Joseph A. Herbert, Marlee Krieger, Jesko von Windheim, Dave Koester, Daniel Stevenson, Daniel J. Rocke, Ramon Esclamado, Alaatin Erkanli, Nirmala Ramanujam, Mark W. Dewhirst, Walter T. Lee
JOURNAL OF BIOMEDICAL OPTICS
(2018)
Article
Multidisciplinary Sciences
Christopher T. Lam, Jenna Mueller, Betsy Asma, Mercy Asiedu, Marlee S. Krieger, Rhea Chitalia, Denali Dahl, Peyton Taylor, John W. Schmitt, Nimmi Ramanujam
Review
Biochemical Research Methods
Torre M. Bydlon, Rami Nachabe, Nimmi Ramanujam, Henricus J. C. M. Sterenborg, Benno H. W. Hendriks
JOURNAL OF BIOPHOTONICS
(2015)
Article
Multidisciplinary Sciences
Caigang Zhu, Amy F. Martinez, Hannah L. Martin, Martin Li, Brian T. Crouch, David A. Carlson, Timothy A. J. Haystead, Nimmi Ramanujam
SCIENTIFIC REPORTS
(2017)
Article
Multidisciplinary Sciences
Brian Crouch, Helen Murphy, Stella Belonwu, Amy Martinez, Jennifer Gallagher, Allison Hall, Mary Scott Soo, Marianne Lee, Philip Hughes, Timothy Haystead, Nirmala Ramanujam
SCIENTIFIC REPORTS
(2017)
Article
Multidisciplinary Sciences
Amy F. Martinez, Samuel S. McCachren, Marianne Lee, Helen A. Murphy, Caigang Zhu, Brian T. Crouch, Hannah L. Martin, Alaattin Erkanli, Narasimhan Rajaram, Kathleen A. Ashcraft, Andrew N. Fontanella, Mark W. Dewhirst, Nirmala Ramanujam
SCIENTIFIC REPORTS
(2018)
Article
Oncology
Megan C. Madonna, Douglas B. Fox, Brian T. Crouch, Jihong Lee, Caigang Zhu, Amy F. Martinez, James Alvarez, Nirmala Ramanujam
MOLECULAR CANCER RESEARCH
(2019)
Article
Engineering, Biomedical
Mercy Nyamewaa Asiedu, Anish Simhal, Usamah Chaudhary, Jenna L. Mueller, Christopher T. Lam, John W. Schmitt, Gino Venegas, Guillermo Sapiro, Nimmi Ramanujam
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2019)
Article
Multidisciplinary Sciences
Brian T. Crouch, Jennifer Gallagher, Roujia Wang, Joy Duer, Allison Hall, Mary Scott Soo, Philip Hughes, Timothy Haystead, Nirmala Ramanujam
SCIENTIFIC REPORTS
(2019)
Proceedings Paper
Engineering, Biomedical
Brian T. Crouch, Joy Duer, Roujia Wang, Jennifer Gallagher, Allison Hall, Mary Scott Soo, Philip Hughes, Timothy A. J. Haystead, Nirmala Ramanujam
MOLECULAR-GUIDED SURGERY: MOLECULES, DEVICES, AND APPLICATIONS IV
(2018)
Article
Oncology
Jessica L. Dobbs, Jenna L. Mueller, Savitri Krishnamurthy, Dongsuk Shin, Henry Kuerer, Wei Yang, Nirmala Ramanujam, Rebecca Richards-Kortum
BREAST CANCER RESEARCH
(2015)