A method for quantifying time dependent changes in MR signal intensity of articular cartilage as a function of tissue deformation in intact joints

Stammberger, Tobias; Herberhold, C.; Faber, Svea; Englmeier, Karl-Hans; Reiser, Maximilian; Eckstein, F.

doi:10.1016/s1350-4533(98)00082-4

Cited by 19 publications

(15 citation statements)

References 32 publications

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“…w͑, x, p j ͒ [4] where N A and N B are the number of vertices of the surfaces A and B, respectively. By varying , the effect of the weighting function can be controlled.…”

Section: Force Fieldmentioning

confidence: 99%

“…Equation [4] describes the interpolation and smoothing of the distance vectors that are applied iteratively during the registration. In each iteration k, the smoothing effect characterized by the constant is diminished: k ϭ 0 / 2 k .…”

Section: Force Fieldmentioning

confidence: 99%

“…Another popular approach for registering segmented objects is chamfer matching (4,30,35). Drawbacks of this method are that chamfer matching requires isotropic image data, and that a high-dimensional space has to be searched for the global minimum to find the best transformation parameters.…”

Section: Rigid Registrationmentioning

confidence: 99%

“…Particular interest is currently directed at evaluating the success of new types of chondroprotective therapy (1), in patients as well as in animal models of osteoarthritis, in which drug effects can be tested on a much smaller time scale. Other applications of MR-based analyses of articular cartilage morphology include the study of functional adaption to the specific mechanical demands (2) and the compression of the cartilage upon mechanical joint loading (3)(4)(5)(6). Quantitative data on cartilage morphology can also be used for the design and validation of numerical simulations of load transmission in human joints (7,8).…”

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confidence: 99%

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Elastic registration of 3D cartilage surfaces from MR image data for detecting local changes in cartilage thickness

et al. 2000

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“…w͑, x, p j ͒ [4] where N A and N B are the number of vertices of the surfaces A and B, respectively. By varying , the effect of the weighting function can be controlled.…”

Section: Force Fieldmentioning

confidence: 99%

Section: Force Fieldmentioning

confidence: 99%

Section: Rigid Registrationmentioning

confidence: 99%

mentioning

confidence: 99%

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Elastic registration of 3D cartilage surfaces from MR image data for detecting local changes in cartilage thickness

et al. 2000

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“…Recent advances in MRI technology have led to significant improvements in spatial resolution and contrast, enabling researchers to evaluate anatomic damage of all these joint structures in the axial, coronal, and sagittal planes (14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24). Recently, we and other investigators have developed a system for quantifying cartilage volume using MRI acquisitions combined with sophisticated software (25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41); however, to date, few studies have used MRI technology to evaluate cartilage volume changes over time (42)(43)(44)(45)(46). Some clinical parameters, such as age, weight, body mass index (BMI), trauma, and baseline radiologic JSW, have already been identified as predictors of rapid radiologic progression of knee OA (47,48).…”

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confidence: 99%

Quantitative magnetic resonance imaging evaluation of knee osteoarthritis progression over two years and correlation with clinical symptoms and radiologic changes

Raynauld¹,

Martel‐Pelletier²,

Berthiaume³

et al. 2004

Arthritis & Rheumatism

239

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Objective. To evaluate the change in osteoarthritic (OA) knee cartilage volume over a two-year period with the use of magnetic resonance imaging (MRI) and to correlate the MRI changes with radiologic changes.Methods. Thirty-two patients with symptomatic knee OA underwent MRI of the knee at baseline and at 6, 12, 18, and 24 months. Loss of cartilage volumes were computed and contrasted with changes in clinical variables for OA and with standardized semiflexed knee radiographs at baseline at 1 and 2 years.Results. Progression of cartilage loss at all followup points was statistically significant (P < 0.0001), with a mean ؎ SD of 3.8 ؎ 5.1% for global cartilage loss and 4.3 ؎ 6.5% for medial compartment cartilage loss at 6 months, 3.6 ؎ 5.1% and 4.2 ؎ 7.5% at 12 months, and 6.1 ؎ 7.2% and 7.6 ؎ 8.6% at 24 months. Discriminant function analysis identified 2 groups of patients, those who progressed slowly (<2% of global cartilage loss; n ‫؍‬ 21) and those who progressed rapidly (>15% of global cartilage loss; n ‫؍‬ 11) over the 2 years of study. At baseline, there was a greater proportion of women (P ‫؍‬ 0.001), a lower range of motion (P ‫؍‬ 0.01), a greater circumference and higher level of pain (P ‫؍‬ 0.05) and stiffness in the study knee, and a higher body mass index in the fast progressor group compared with the slow progressor group. No statistical correlation between loss of cartilage volume and radiographic changes was seen.Conclusion. Quantitative MRI can measure the progression of knee OA precisely and can help to identify patients with rapidly progressing disease. These findings indicate that MRI could be helpful in assessing the effects of treatment with structure-modifying agents in OA.In people over the age of 60 years, osteoarthritis (OA) is a common cause of disability. Assessment of cartilage damage is important for monitoring disease progression and evaluating therapeutic response in OA. For many years, clinical studies of drug interventions in symptomatic knee OA have focused specifically on clinical parameters, such as pain and joint function, without assessing the effect of treatment on structural changes caused by the disease or the role of treatment in preventing cartilage degradation. Serial radiographs of affected joints appear to be a logical means of documenting the progression of OA over time (1), provided that a validated, reliable, and easily reproducible technique is used (2-5).

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Volumen und Dicke des Gelenkknorpels

Gläser¹,

Burgkart²,

Englmeier³

et al. 2000

Das Patellofemorale Schmerzsyndrom

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A method for quantifying time dependent changes in MR signal intensity of articular cartilage as a function of tissue deformation in intact joints

Cited by 19 publications

References 32 publications

Elastic registration of 3D cartilage surfaces from MR image data for detecting local changes in cartilage thickness

Elastic registration of 3D cartilage surfaces from MR image data for detecting local changes in cartilage thickness

Quantitative magnetic resonance imaging evaluation of knee osteoarthritis progression over two years and correlation with clinical symptoms and radiologic changes

Volumen und Dicke des Gelenkknorpels

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