Purpose: To suggest a quantitative method for assessing the temporal changes in the geometry of individual multiple sclerosis (MS) lesions in follow-up studies of MS patients.
Materials And Methods: Computer simulated and in vivo magnetic resonance (MR) imaged MS lesions were studied. Ten in vivo MS lesions were identified from sets of axial MR images acquired from a patient scanned consecutively for 24 times during a one-year period. Each of the lesions was segmented and its three-dimensional surface approximated using spherical harmonics (SH). From the obtained SH polynomial coefficients, indices of shape were defined, and analysis of the temporal changes in each lesion's geometry throughout the year was performed by determining the mean discrete total variation of the shape indices.
Results: The results demonstrate that most of the studied lesions undergo notable geometrical changes with time. These changes are not necessarily associated with similar changes in size/volume. Furthermore, it was found that indices corresponding to changes in lesion shape could be 1.4 to 8.0 times higher than those corresponding to changes in the lesion size/volume.
Conclusion: Quantitative three-dimensional shape analysis can serve as a new tool for monitoring MS lesion activity and study patterns of MS lesion evolution over time.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/jmri.10365 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Pulse-by-pulse treatment planning and its application to generic observations of ultra-high dose rate (FLASH) radiotherapy with photons and protons.
Phys Med Biol
January 2025
Joint Department of Physics, The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, London, SM2 5PT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.
The exact temporal characteristics of beam delivery affect the efficacy and outcome of ultra-high dose rate (UHDR or "FLASH") radiotherapy, mainly due to the influence of the beam pulse structure on mean dose rate. Single beams may also be delivered in separate treatment sessions to elevate mean dose rate. This paper therefore describes a model for pulse-by-pulse treatment planning and demonstrates its application by making some generic observations of the characteristics of FLASH radiotherapy with photons and protons.
View Article and Find Full Text PDFTractGraphFormer: Anatomically informed hybrid graph CNN-transformer network for interpretable sex and age prediction from diffusion MRI tractography.
Med Image Anal
January 2025
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address:
The relationship between brain connections and non-imaging phenotypes is increasingly studied using deep neural networks. However, the local and global properties of the brain's white matter networks are often overlooked in convolutional network design. We introduce TractGraphFormer, a hybrid Graph CNN-Transformer deep learning framework tailored for diffusion MRI tractography.
View Article and Find Full Text PDFBone mineral density (BMD) measured with dual-energy X-ray absorptiometry (DXA) is widely used in clinical practice to assess fracture risk and guide management. DXA can also assess hip geometry, including femoral neck width (FNW) and hip axis length (HAL), which have both been associated with increased risk for hip fracture independently from BMD. Our objective was to assess if FNW predicts hip fracture independently from other factors including HAL.
View Article and Find Full Text PDFMorphometric assessment of mandibles with complications resulting from temporomandibular joint ankylosis in children from 4 months to 3 years of age.
Acta Bioeng Biomech
September 2024
Laboratory of Physiotherapy and Physioprevention, Institute of Physiotherapy and Health Sciences, Academy of Physical Education, Katowice, Poland.
: The main aim of this paper was to perform the morphological assessment of children's mandibles of different etiology of dys-functions within the temporomandibular joint, from isolated idiopathic ankylosis to craniofacial malformations co-existing with genetic disorders. : The investigations encompassed seven patients at the age of 0-3. Measurements were conducted on the basis of data obtained from computed tomography.
View Article and Find Full Text PDFIntegrating deep learning and machine learning for improved CKD-related cortical bone assessment in HRpQCT images: A pilot study.
Bone Rep
March 2025
Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States of America.
High resolution peripheral quantitative computed tomography (HRpQCT) offers detailed bone geometry and microarchitecture assessment, including cortical porosity, but assessing chronic kidney disease (CKD) bone images remains challenging. This proof-of-concept study merges deep learning and machine learning to 1) improve automatic segmentation, particularly in cases with severe cortical porosity and trabeculated endosteal surfaces, and 2) maximize image information using machine learning feature extraction to classify CKD-related skeletal abnormalities, surpassing conventional DXA and CT measures. We included 30 individuals (20 non-CKD, 10 stage 3 to 5D CKD) who underwent HRpQCT of the distal and diaphyseal radius and tibia and contributed data to develop and validate four different AI models for each anatomical site.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!