An MRI derived articular cartilage visualization framework.

Abstract:

OBJECTIVE:We present a multi-dimensional framework for the visualization of femoral articular cartilage. The framework comprises methods for visualizing and quantifying changes in cartilage thickness and surface morphology derived from MRI based cartilage segmentation. Adequate visualization of cartilage allows accurate and clinically meaningful assessment of cartilage surface morphology and thickness. In current practice the routine use of conventional 2D MR images provides limited qualitative information and is inconvenient because the imaged volume has to be reviewed slice by slice. METHOD:A Graphical User Interface (GUI) that encapsulates the framework described above was developed. In the first stage of the analysis MR images of the knee are segmented to delineate cartilage boundaries. Cartilage thicknesses are subsequently measured. The detected points and corresponding thickness data are utilized to produce a visualization framework. RESULTS:The system was tested using data from six example patients. The spatial distribution of cartilage on the articular surface was visualized using a 3D WearMap. The 2D WearMap allowed the entire cartilage surface to be studied at once. Quantitative interaction with the 2D WearMap was assisted by the ability to ascertain cartilage surface dimensions and TrackBack from a point of interest to the original MR image. As a result, the detection of wear patterns and lesions was efficiently carried out. CONCLUSION:A means of quantitatively visualizing cartilage defects non-invasively is presented. This stands to reduce clinician reporting times, as well as allowing quantitative follow-up that facilitates osteoarthritis (OA) screening and planning/evaluating interventions.

authors

Akhtar S,Poh CL,Kitney RI

doi

10.1016/j.joca.2007.03.009

subject

Has Abstract

pub_date

2007-09-01 00:00:00

pages

1070-85

issue

9

eissn

1063-4584

issn

1522-9653

pii

S1063-4584(07)00113-6

journal_volume

15

pub_type

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