ArticleBreast cancer research : BCR2014
Pathologic response prediction to neoadjuvant chemotherapy utilizing pretreatment near-infrared imaging parameters and tumor pathologic criteria.
Article in Breast cancer research : BCR, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00908609 (3-D Simultaneous Ultrasound and NIR Imaging for Breast Cancer Detection), which is not on this map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
3-D Simultaneous Ultrasound and NIR Imaging for Breast Cancer Detection
Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.
- Diffuse optical spectroscopy for monitoring the responses of patients with breast cancer to neoadjuvant chemotherapy: A meta-analysis.Medicine · 2018Pooled it
- Role of vascular density and normalization in response to neoadjuvant bevacizumab and chemotherapy in breast cancer patients.Proceedings of the National Academy of Sciences of the United States of America · 2015Trial
- The Predictive Value of the Tumor-Stroma Ratio for Neoadjuvant Endocrine Therapy in Hormone Receptor-Positive Breast Cancer.International journal of cancer · 2026Article
- Joint synthesis of longitudinal MRI and enhanced prediction of neoadjuvant chemotherapy response in breast cancer: a multicohort study.BMC cancer · 2026Article
- Monitoring of neoadjuvant chemotherapy through time domain diffuse optics: breast tissue composition changes and collagen discriminative potential.Biomedical optics express · 2024Article
- Ultrasound and diffuse optical tomography-transformer model for assessing pathological complete response to neoadjuvant chemotherapy in breast cancer.Journal of biomedical optics · 2024Article
- Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy.Journal of biomedical optics · 2024Article
- Deep learning model improves tumor-infiltrating lymphocyte evaluation and therapeutic response prediction in breast cancer.NPJ breast cancer · 2023Article
- Predicting dynamic response to neoadjuvant chemotherapy in breast cancer: a novel metabolomics approach.Molecular oncology · 2022Article
- Deep Learning Mechanism for Predicting the Axillary Lymph Node Metastasis in Patients with Primary Breast Cancer.BioMed research international · 2022Article
- Enhanced diffuse optical tomographic reconstruction using concurrent ultrasound information.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Article
- Evaluation of SLE arthritis using frequency domain optical imaging.Lupus science & medicine · 2021Article
- Early Assessment Window for Predicting Breast Cancer Neoadjuvant Therapy using Biomarkers, Ultrasound, and Diffuse Optical Tomography.Breast cancer research and treatment · 2021Article
- Changes in Diffuse Optical Tomography Images During Early Stages of Neoadjuvant Chemotherapy Correlate with Tumor Response in Different Breast Cancer Subtypes.Clinical cancer research : an official journal of the American Association for Cancer Research · 2021Article
- Radiomics of Tumor Heterogeneity in Longitudinal Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer.Frontiers in molecular biosciences · 2021Article
- HIF-1α, TWIST-1 and ITGB-1, associated with Tumor Stiffness, as Novel Predictive Markers for the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer.Cancer management and research · 2020Article
- Identifying an early treatment window for predicting breast cancer response to neoadjuvant chemotherapy using immunohistopathology and hemoglobin parameters.Breast cancer research : BCR · 2018Article
- Dynamic Diffuse Optical Tomography for Monitoring Neoadjuvant Chemotherapy in Patients with Breast Cancer.Radiology · 2018Article
- Predicting Treatment Response of Breast Cancer to Neoadjuvant Chemotherapy Using Ultrasound-Guided Diffuse Optical Tomography.Translational oncology · 2018Article
- High throughput detection chain for time domain optical mammography.Biomedical optics express · 2018Article
Corrections and comments
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Authors and funding
6 authors at 5 institutions in 2 countries.
Funding
Abstract
introductionThe purpose of this study is to develop a prediction model utilizing tumor hemoglobin parameters measured by ultrasound-guided near-infrared optical tomography (US-NIR) in conjunction with standard pathologic tumor characteristics to predict pathologic response before neoadjuvant chemotherapy (NAC) is given.
methodsThirty-four patients' data were retrospectively analyzed using a multiple logistic regression model to predict response. These patients were split into 30 groups of training (24 tumors) and testing (12 tumors) for cross validation. Tumor vascularity was assessed using US-NIR measurements of total hemoglobin (tHb), oxygenated (oxyHb) and deoxygenated hemoglobin (deoxyHb) concentrations acquired before treatment. Tumor pathologic variables of tumor type, Nottingham score, mitotic index, the estrogen and progesterone receptors and human epidermal growth factor receptor 2 acquired before NAC in biopsy specimens were also used in the prediction model. The patients' pathologic response was graded based on the Miller-Payne system. The overall performance of the prediction models was evaluated using receiver operating characteristic (ROC) curves. The quantitative measures were sensitivity, specificity, positive and negative predictive values (PPV and NPV) and the area under the ROC curve (AUC).
resultsUtilizing tumor pathologic variables alone, average sensitivity of 56.8%, average specificity of 88.9%, average PPV of 84.8%, average NPV of 70.9% and average AUC of 84.0% were obtained from the testing data. Among the hemoglobin predictors with and without tumor pathological variables, the best predictor was tHb combined with tumor pathological variables, followed by oxyHb with pathological variables. When tHb was included with tumor pathological variables as an additional predictor, the corresponding measures improved to 79%, 94%, 90%, 86% and 92.4%, respectively. When oxyHb was included with tumor variables as an additional predictor, these measures improved to 77%, 85%, 83%, 83% and 90.6%, respectively. The addition of tHb or oxyHb significantly improved the prediction sensitivity, NPV and AUC compared with using tumor pathological variables alone.
conclusionsThese initial findings indicate that combining widely used tumor pathologic variables with hemoglobin parameters determined by US-NIR may provide a powerful tool for predicting patient pathologic response to NAC before the start of treatment.
trial registrationClincalTrials.gov ID: NCT00908609 (registered 22 May 2009).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.