ArticleTranslational stroke research2020
Clot Analog Attenuation in Non-contrast CT Predicts Histology: an Experimental Study Using Machine Learning.
Article in Translational stroke research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 22 citations in OpenAlex.
- Clinical image analysis to build patient-specific models of acute ischemic stroke patients.Physical and engineering sciences in medicine · 2026Article
- Experimental Characterisation of Differently Composed Thrombus Entities with Spectral-Detector-CT.Neurology international · 2026Article
- Dual-layer dual-energy CT characterization of thrombus composition in acute pulmonary embolism and chronic thromboembolic pulmonary hypertension.The international journal of cardiovascular imaging · 2025Article
- Ironing out differences in attenuation and blooming artifact in acute stroke thrombi.Scientific reports · 2025Article
- Deep learning prediction of stroke thrombus red blood cell content from multiparametric MRI.Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences · 2024Article
- Contribution of Red Blood Cells and Platelets to Blood Clot Computed Tomography Imaging and Compressive Mechanical Characteristics.Annals of biomedical engineering · 2024Article
- Making acute ischemic stroke thrombi visible in MRI imaging.Scientific reports · 2024Article
- Thrombus discrimination with electron density: potential implications for non-contrast computed tomography imaging.Cardiovascular diagnosis and therapy · 2024Article
- Article
- An Intermodal Correlation Study among Imaging, Histology, Procedural and Clinical Parameters in Cerebral Thrombi Retrieved from Anterior Circulation Ischemic Stroke Patients.Journal of clinical medicine · 2022Article
- Study of correlations between CT properties of retrieved cerebral thrombi with treatment outcome of stroke patients.Radiology and oncology · 2021Article
- Radiology-Pathology Correlations of Intracranial Clots: Current Theories, Clinical Applications, and Future Directions.AJNR. American journal of neuroradiology · 2021Review
- Novel Human Acute Ischemic Stroke Blood Clot Analogs for In Vitro Thrombectomy Testing.AJNR. American journal of neuroradiology · 2021Article
- Utility of Hounsfield unit in the diagnosis of tandem occlusion in acute ischemic stroke.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021Article
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14 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Exact histological clot composition remains unknown. The purpose of this study was to identify the best imaging variables to be extrapolated on clot composition and clarify variability in the imaging of thrombi by non-contrast CT. Using a CT-phantom and covering a wide range of histologies, we analyzed 80 clot analogs with respect to X-ray attenuation at 24 and 48 h after production. The mean, maximum, and minimum HU values for the axial and coronal reconstructions were recorded. Each thrombus underwent a corresponding histological analysis, together with a laboratory analysis of water and iron contents. Decision trees, a type of supervised machine learning, were used to select the primary variable altering attenuation and the best parameter for predicting histology. The decision trees selected red blood cells (RBCs) for correlation with all attenuation parameters (p < 0.001). Conversely, maximum attenuation on axial CT offered the greatest accuracy for discriminating up to four groups of clot histology (p < 0.001). Similar RBC-rich thrombi displayed variable imaging associated with different iron (p = 0.023) and white blood cell contents (p = 0.019). Water content varied among the different histologies but did not in itself account for the differences in attenuation. Independent factors determining clot attenuation were the RBCs (β = 0.33, CI = 0.219-0.441, p < 0.001) followed by the iron content (β = 0.005, CI = 0.0002-0.009, p = 0.042). Our findings suggest that it is possible to extract more and valuable information from NCCT that can be extrapolated to provide insights into clot histological and chemical composition.
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