ArticleBreast cancer research : BCR2017
Addition of T2-guided optical tomography improves noncontrast breast magnetic resonance imaging diagnosis.
Article in Breast cancer research : BCR, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 33 citations in OpenAlex.
- Deep Learning Enables Fast and Accurate Quantification of MRI-Guided Near-Infrared Spectral Tomography for Breast Cancer Diagnosis.IEEE transactions on medical imaging · 2025Article
- Model-Based Convolution Neural Network for 3D Near-Infrared Spectral Tomography.IEEE transactions on medical imaging · 2025Article
- MRI-Guided Near-Infrared Spectroscopic Tomography (MRg-NIRST) Imaging System With Wearable Breast Optical Interface for Breast Cancer Imaging.IEEE transactions on bio-medical engineering · 2025Article
- In vivo optimization of the experimental conditions for the non-invasive optical assessment of breast density.Scientific reports · 2024Article
- FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image Reconstruction.IEEE transactions on medical imaging · 2023Article
- Stable tissue-mimicking phantoms for longitudinal multimodality imaging studies that incorporate optical, CT, and MRI contrast.Journal of biomedical optics · 2023Article
- Fusion deep learning approach combining diffuse optical tomography and ultrasound for improving breast cancer classification.Biomedical optics express · 2023Article
- Method to improve the localization accuracy and contrast recovery of lesions in separately acquired X-ray and diffuse optical tomographic breast imaging.Biomedical optics express · 2022Article
- Prospective assessment of adjunctive ultrasound-guided diffuse optical tomography in women undergoing breast biopsy: Impact on BI-RADS assessments.European journal of radiology · 2021Article
- Performance assessment of MRI guided continuous wave near-infrared spectral tomography for breast imaging.Biomedical optics express · 2021Article
- A review of optical breast imaging: Multi-modality systems for breast cancer diagnosis.European journal of radiology · 2020Review
- Target depth-regularized reconstruction in diffuse optical tomography using ultrasound segmentation as prior information.Biomedical optics express · 2020Article
- Back-propagation neural network-based reconstruction algorithm for diffuse optical tomography.Journal of biomedical optics · 2018Article
- Weighting function effects in a direct regularization method for image-guided near-infrared spectral tomography of breast cancer.Biomedical optics express · 2018Article
- Optical Breast Imaging: A Review of Physical Principles, Technologies, and Clinical Applications.Journal of breast imagingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundWhile dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) is recognized as the most sensitive examination for breast cancer detection, it has a substantial false positive rate and gadolinium (Gd) contrast agents are not universally well tolerated. As a result, alternatives to diagnosing breast cancer based on endogenous contrast are of growing interest. In this study, endogenous near-infrared spectral tomography (NIRST) guided by T2 MRI was evaluated to explore whether the combined imaging modality, which does not require contrast injection or involve ionizing radiation, can achieve acceptable diagnostic performance.
methodsTwenty-four subjects-16 with pathologically confirmed malignancy and 8 with benign abnormalities-were simultaneously imaged with MRI and NIRST prior to definitive pathological diagnosis. MRIs were evaluated independently by three breast radiologists blinded to the pathological results. Optical image reconstructions were constrained by grayscale values in the T2 MRI. MRI and NIRST images were used, alone and in combination, to estimate the diagnostic performance of the data. Outcomes were compared to DCE results.
resultsSensitivity, specificity, accuracy, and area under the curve (AUC) of noncontrast MRI when combined with T2-guided NIRST were 94%, 100%, 96%, and 0.95, respectively, whereas these values were 94%, 63%, 88%, and 0.81 for DCE MRI alone, and 88%, 88%, 88%, and 0.94 when DCE-guided NIRST was added.
conclusionIn this study, the overall accuracy of imaging diagnosis improved to 96% when T2-guided NIRST was added to noncontrast MRI alone, relative to 88% for DCE MRI, suggesting that similar or better diagnostic accuracy can be achieved without requiring a contrast agent.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.