ArticleScientific reports2020
A nomogram for estimating intracranial pressure using acute subdural hematoma thickness and midline shift.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Surgical decision-making in traumatic acute subdural hematoma: A scoping review of current evidence, knowledge gaps, and future directions.Surgical neurology international · 2026Review
- Computational Modeling of Bridging Vein Rupture and Acute Subdural Hematoma Growth.Annals of biomedical engineering · 2025Article
- Simulating Cerebral Edema and Ischemia After Traumatic Acute Subdural Hematoma Using Triphasic Swelling Biomechanics.Annals of biomedical engineering · 2024Article
- A Spherical Cap Model of Epidural Hematomas.Cureus · 2024Article
- Mismatch between midline shift and hematoma thickness as a prognostic factor of mortality in patients sustaining acute subdural hematoma.Trauma surgery & acute care open · 2021Article
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although criteria for surgical treatment of acute subdural hematoma (SDH) have been proposed, interaction exists between SDH, midline shift (MLS), and intracranial pressure (ICP). Based on our half sphere finite-element model (FEM) of the supratentorial brain parenchyma, tools for ICP estimation using SDH thickness (SDHx) and MLS were developed. We performed 60 single load step, structural static analyses, simulating a left-sided SDH compressing the cerebral hemispheres. The Young's modulus was taken as 10,000 Pa. The ICP loads ranged from 10 to 80 mmHg with Poisson's ratios between 0.25 and 0.49. The SDHx and the MLS results were stored in a lookup table. An ICP estimation equation was derived from these data and then was converted into a nomogram. Numerical convergence was achieved in 49 model analyses. Their SDHx ranged from 0.79 to 28.3 mm, and the MLS ranged from 1.5 to 16.9 mm. The estimation formula was log(ICP) = 0.614-0.520 log(SDHx) + 1.584 log(MLS). Good correlations were observed between invasive ICP measurements and those estimated from preoperative SDHx and MLS data on images using our model. These tools can be used to estimate ICP noninvasively, providing additional information for selecting the treatment strategy in patients with SDH.
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