Accurate semiautomatic assessment of ligament length variations from MRI data. Issue 9 (15th August 2013)

• Record Type: Journal Article
• Authors: Honal, Matthias; Lovell‐Smith, Cris; Vicari, Marco; Weitzel, Elisabeth; Izadpanah, Kaywan; Weigel, Matthias
• Is Part Of: Medical physics. Volume 40:Issue 9(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-08-15
• Subjects: Magnetic resonance imaging -- Registration -- Spatial dimensions (e.g., position, lengths, volume, angles, and displacements); biomedical MRI -- bone -- image registration -- image segmentation -- length measurement -- medical image processing; ligament dynamics -- image registration -- magnetic resonance imaging -- distance measurement; Involving electronic [emr] or nuclear [nmr] magnetic resonance, e.g. magnetic resonance imaging -- Measuring length, thickness or similar linear dimensions; Measuring angles; Measuring areas; Measuring irregularities of surfaces or contours -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general; Magnetic resonance imaging -- Medical imaging -- Image registration -- Computed tomography -- Kinematics -- Spatial resolution -- Data sets -- Data analysis -- Image scanners -- Computer software; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4818058
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : A semiautomatic method for the assessment of ligament length variations during different joint positions based on MRI data is proposed. Methods: : Ligament lengths are represented as distances between points marking characteristic locations in the ligament insertion regions on the bones. These points are defined manually for one single reference joint position and for all other joint positions they are automatically mapped with high accuracy to the correct locations using image registration methods. The methodology is validated using data from 16 volunteers depicting the coracoclavicular ligaments in the left shoulder during different arm abductions. Results: : The method yielded a superior reproducibility of the point locations over different joint positions compared to manual point marking. Significant ligament length variations were found for different abductions which was not possible with manual measurements. Acquisition related geometric distortions and inaccuracies during the registration and segmentation process were small. Conclusions: : The proposed method provides superior accuracy for the in vivo analysis of ligament dynamics compared to manual measurements. This permits a better understanding of the ligament behavior during joint motion and offers new possibilities for presurgical planning which to date has not been possible with manual data analysis.