ArticleMedical physics2021
H-scan trajectories indicate the progression of specific diseases.
Article in Medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Multiparametric quantification and visualization of liver fat using ultrasound.WFUMB ultrasound open · 2024Article
- Multiparametric ultrasound imaging for early-stage steatosis: Comparison with magnetic resonance imaging-based proton density fat fraction.Medical physics · 2024Article
- H-Scan Discrimination for Tumor Microenvironmental Heterogeneity in Melanoma.Ultrasound in medicine & biology · 2024Article
- Improving breast cancer diagnosis by incorporating raw ultrasound parameters into machine learning.Machine learning: science and technology · 2022Article
- Power laws prevail in medical ultrasound.Physics in medicine and biology · 2022Review
- Disease-Specific Imaging Utilizing Support Vector Machine Classification of H-Scan Parameters: Assessment of Steatosis in a Rat Model.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2022Article
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Authors and funding
2 authors.
Funding
Abstract
purposeThe ability of ultrasound to assess pathology is increasing with the development of quantitative parameters. Among these are a set of parameters derived from the recent H-scan analysis of subresolvable scattering. The emergence of these quantitative measures of tissue/ultrasound interactions now enables a study of the unique trajectories of multiparametric features in multidimensional space, representing the progression of specific diseases over time. We develop the mathematical and visual tools that are effective for classifying, quantifying, and visualizing the steady progression of several diseases from independent studies, all within a uniform framework.
methodsAfter applying the H-scan analysis of ultrasound echoes, we trained a support vector machine (SVM) to classify the unique trajectories of progressive liver disease from fibrosis, steatosis, and pancreatic ductal adenocarcinoma (PDAC) metastasis. Our approaches include the development of trajectory maps and disease-specific color imaging stains.
resultsThe multidimensional SVM image classification reached 100% accuracy across the three different studies.
conclusionH-scan trajectories can be useful to track the progression of multiple classes of diseases, improving diagnosis, staging, and assessing the response to therapy.
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Registered trials
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