Publications by authors named "G E Gold"
Background: Post-traumatic osteoarthritis (PTOA) often follows anterior cruciate ligament reconstruction (ACLR), leading to early cartilage degradation. Change in mean T fails to capture subject-specific spatial-temporal variations, highlighting the need for robust quantitative methods for early PTOA detection and monitoring.
Purpose/hypothesis: Develop and apply 3D T cluster analysis to ACLR and healthy knees over 2.
Article Synopsis
- Analyzing the shapes of tissues and organs is crucial for diagnosing diseases like osteoarthritis, which affects many Americans; a new dataset called ShapeMed-Knee has been introduced to support this analysis.
- ShapeMed-Knee contains 9,376 high-resolution 3D shapes of femur bones and cartilage, along with benchmarks for accuracy and clinical prediction tasks, enhancing the understanding of osteoarthritis.
- The authors developed a cutting-edge hybrid neural shape model using ShapeMed-Knee that significantly improves reconstruction accuracy and accurately predicts localized osteoarthritis features, with plans to make the dataset, code, and benchmarks publicly available.
In computed tomography (CT) imaging, optimizing the balance between radiation dose and image quality is crucial due to the potentially harmful effects of radiation on patients. Although subjective assessments by radiologists are considered the gold standard in medical imaging, these evaluations can be time-consuming and costly. Thus, objective methods, such as the peak signal-to-noise ratio and structural similarity index measure, are often employed as alternatives.
View Article and Find Full Text PDFArticle Synopsis
- - The text discusses the importance of analyzing the shapes of tissues and organs for diagnosing diseases, focusing on osteoarthritis, which affects a significant number of people in the U.S.
- - A new 3D shape dataset called ShapeMed-Knee has been introduced, containing 9,376 high-resolution models of the femur bone and cartilage, along with benchmarks for accuracy and clinical prediction tasks.
- - The study presents a hybrid neural shape model that outperforms existing models in accuracy and the ability to predict features related to osteoarthritis, aiming to improve medical diagnostics while providing open access to the dataset and tools.
Reproducibility of Quantitative Double-Echo Steady-State T Mapping of Knee Cartilage.
J Magn Reson Imaging
February 2025
Article Synopsis
- - The study investigates the reproducibility of knee cartilage T mapping using a fast technique called qDESS, focusing on its ability to identify joints at risk for osteoarthritis.
- - Researchers evaluated two methods for analyzing cartilage: manual segmentation of specific regions and automatic segmentation through a deep-learning tool, assessing test-retest performance over different time intervals.
- - The analysis revealed that all cartilage regions demonstrated good reproducibility, allowing for better profiling of this biomarker's technical performance in clinical assessments.