Water-content calculation in growth plate and cartilage using MR T1-mapping design and validation of a new method in a porcine model.
Skeletal Radiol 2013;
42:1413-9. [PMID:
23842573 DOI:
10.1007/s00256-013-1674-8]
[Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2013] [Revised: 05/22/2013] [Accepted: 06/09/2013] [Indexed: 02/02/2023]
Abstract
OBJECTIVE
There is a close relation between cartilage health and its hydration state. Current magnetic resonance methods allow visualizing this tissue. However, a quantitative analysis is more useful when studying disease. The purpose of this study was to quantify water content in cartilage using magnetic resonance without contrast agents.
MATERIALS AND METHODS
Water-content estimations using T1 magnetic resonance mapping were done first in eight gelatin samples where the water content was previously known. The same method was used in the physeal areas of eight skeletally immature 30-kg pigs. To calculate accuracy, T1 calculations were compared to dry-freeze, which is considered the gold standard because it can remove the total water content form a tissue. Four fresh cartilage and seven gelatin samples were dry-frozen. Water content obtained from dry-freeze was compared to the one calculated from T1 map values. A mathematical model and statistical analysis were used to calculate the predictive value of the method and its significance.
RESULTS
T1-map-based magnetic resonance method can calculate water content in cartilage with an accuracy of 97.3 %. We calculated a coefficient of variance for this method against dry-frozen sample of 3.68 (SD = 1.2) in gelatin samples, and 2.73 (SD = 1.3) in in vivo samples. Between two independent observers, the coefficient of variance was 0.053, which suggests it can be easily reproduced.
CONCLUSIONS
Magnetic resonance was able to calculate, with high accuracy, the cartilage water content using T1 mapping sequences.
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