ArticleQuantitative imaging in medicine and surgery2022
Clinical experience of tensor-valued diffusion encoding for microstructure imaging by diffusional variance decomposition in patients with breast cancer.
Article in Quantitative imaging in medicine and surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 7 citations in OpenAlex.
- The role of diffusion-weighted MRI in biological image-guided radiation therapy: a roadmap.Physics in medicine and biology · 2026Review
- Spectral principal axis system (SPAS) and tuning of tensor-valued encoding for microscopic anisotropy and time-dependent diffusion in the rat brain.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Imaging evaluation focused on microstructural tissue changes using tensor-valued diffusion encoding in breast cancers after neoadjuvant chemotherapy: is it a promising way forward?Gland surgery · 2024Article
- Cardiac q-space trajectory imaging by motion-compensated tensor-valued diffusion encoding in human heart in vivo.Magnetic resonance in medicine · 2023Article
- Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging.Quantitative imaging in medicine and surgery · 2023Article
- Histogram analysis of breast diffusion kurtosis imaging: a comparison between readout-segmented and single-shot echo-planar imaging sequence.Quantitative imaging in medicine and surgery · 2023Article
- Advanced Magnetic Resonance Imaging Modalities for Breast Cancer Diagnosis: An Overview of Recent Findings and Perspectives.Diagnostics (Basel, Switzerland) · 2022Review
- The value of noncontrast MRI in evaluating breast imaging reporting and data system category 0 lesions on digital mammograms.Quantitative imaging in medicine and surgery · 2022Article
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
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Abstract
Background: Diffusion-weighted imaging plays a key role in magnetic resonance imaging (MRI) of breast tumors. However, it remains unclear how to interpret single diffusion encoding with respect to its link with tissue microstructure. The purpose of this retrospective cross-sectional study was to use tensor-valued diffusion encoding to investigate the underlying microstructure of invasive ductal carcinoma (IDC) and evaluate its potential value in a clinical setting. Methods: We retrospectively reviewed biopsy-proven breast cancer patients who underwent preoperative breast MRI examination from July 2020 to March 2021. We reviewed the MRI of 29 patients with 30 IDCs, including analysis by diffusional variance decomposition enabled by tensor-valued diffusion encoding. The diffusion parameters of mean diffusivity (MD), total mean kurtosis (MK Results: The mean value of MD in IDCs was significantly lower than that of normal FGBT (1.07±0.27 Conclusions: Tensor-valued diffusion encoding enables a useful non-invasive method for characterizing breast cancers with information on tissue microstructures. Particularly, µFA could be a potential imaging biomarker for evaluating breast cancers prior to surgery or chemotherapy.
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