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Thin-Walled Hollow Shafts

Thin-Walled Hollow Shafts

In analyzing a thin-walled hollow shaft subjected to torsional loading, a segment with width dx is isolated for examination. Despite its equilibrium state, this segment faces torsional shearing forces at its ends. These forces are quantitatively described by the product of the longitudinal shearing stress on the segment's minor surface and the area of this surface, leading to the concept of shear flow. This shear flow is consistent throughout the structure, indicating a uniform distribution...

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Related Experiment Video

Updated: May 27, 2025

Ultrasound Imaging of the Thoracic and Abdominal Aorta in Mice to Determine Aneurysm Dimensions

Ultrasound Imaging of the Thoracic and Abdominal Aorta in Mice to Determine Aneurysm Dimensions

Published on: March 8, 2019

Thoracic Aortic Shape: A Data-Driven Scale Space Approach.

Joseph A Pugar¹, Junsung Kim¹, Kameel Khabaz¹

¹University of Chicago, Chicago, IL 60637 USA.

Medrxiv : the Preprint Server for Health Sciences

|February 20, 2025

Summary

This summary is machine-generated.

This study identifies optimal scales for analyzing aortic shape using medical imaging, improving predictions for cardiovascular surgery outcomes. Findings highlight a specific discretization step for robust signal detection.

Keywords:

Aorta Imaging Scale Space Shape

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Three-Dimensional Printing of a Complex Aortic Anomaly

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Published on: November 1, 2018

Related Experiment Videos

Last Updated: May 27, 2025

Ultrasound Imaging of the Thoracic and Abdominal Aorta in Mice to Determine Aneurysm Dimensions

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Published on: March 8, 2019

Four-Dimensional Computed Tomography-Guided Valve Sizing for Transcatheter Pulmonary Valve Replacement

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Published on: January 20, 2022

Three-Dimensional Printing of a Complex Aortic Anomaly

Three-Dimensional Printing of a Complex Aortic Anomaly

Published on: November 1, 2018

Area of Science:

Medical Imaging
Computational Anatomy
Cardiovascular Surgery

Background:

Traditional 1D metrics for aortic disease lack nuance.
Advanced imaging and computational methods offer richer geometric insights.
Scale-invariant measures of aortic shape show promise.

Purpose of the Study:

To identify optimal scale-space parameters for analyzing aortic shape from CT images.
To improve the correlation between geometric shape variations and surgical outcomes.
To develop robust models resilient to patient heterogeneity.

Main Methods:

Comprehensive analysis of over 1200 scale-space constructions.
Utilized a cohort of 185 aortic dissection patients.
Investigated normalized fluctuation in total integrated Gaussian curvature.

Main Results:

Pinpointed optimal resolution scales for shape variation analysis.
Found a secondary discretization step yields robust signals at ~1 cm.
Demonstrated improved correlation between shape and surgical outcomes.

Conclusions:

Optimal intermediate scales are crucial for precise medical imaging analysis.
A secondary discretization step enhances signal robustness.
This approach leads to more reliable clinical decision-making tools for cardiovascular surgery.