Experimental model to evaluate in vivo and in vitro cartilage MR imaging by means of histological analyses

Bittersohl, Bernd; Mamisch, T.C.; Welsch, Goetz H.; Stratmann, J.; Forst, Raimund; Swoboda, B.; Bautz, W.; Rechenberg, Brigitte von; Cavallaro, A.

doi:10.1016/j.ejrad.2008.02.031

Cited by 13 publications

(7 citation statements)

References 35 publications

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“…In several other studies different MRI sequences were used to detect cartilage degeneration [15,116,117]. It was confirmed that even after MRI examinations with FLASH and DESS sequences low correlation in terms of sensitivity and specificity was found for both sequences in normal to mild Mankin grades [112]. Only moderate to severe changes were diagnosed with higher significance and specificity.…”

Section: Discussionmentioning

confidence: 84%

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Osteoarthritis in the Knee Joints of Göttingen Minipigs after Resection of the Anterior Cruciate Ligament? Missing Correlation of MRI, Gene and Protein Expression with Histological Scoring

et al. 2016

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IntroductionThe Göttingen Minipig (GM) is used as large animal model in articular cartilage research. The aim of the study was to introduce osteoarthritis (OA) in the GM by resecting the anterior cruciate ligament (ACLR) according to Pond and Nuki, verified by histological and magnetic resonance imaging (MRI) scoring as well as analysis of gene and protein expression.Materials and MethodsThe eight included skeletally mature female GM were assessed after ACLR in the left and a sham operation in the right knee, which served as control. 26 weeks after surgery the knee joints were scanned using a 3-Tesla high-field MR tomography unit with a 3 T CP Large Flex Coil. Standard proton-density weighted fat saturated sequences in coronal and sagittal direction with a slice thickness of 3 mm were used. The MRI scans were assessed by two radiologists according to a modified WORMS-score, the X-rays of the knee joints by two evaluators. Osteochondral plugs with a diameter of 4mm were taken for histological examination from either the main loading zone or the macroscopic most degenerated parts of the tibia plateau or condyle respectively. The histological sections were blinded and scored by three experts according to Little et al. Gene expression analysis was performed from surrounding cartilage. Expression of adamts4, adamts5, acan, col1A1, col2, il-1ß, mmp1, mmp3, mmp13, vegf was determined by qRT-PCR. Immunohistochemical staining (IH) of Col I and II was performed. IH was scored using a 4 point grading (0—no staining; 3-intense staining).Results and DiscussionSimilar signs of OA were evident both in ACLR and sham operated knee joints with the histological scoring result of the ACLR joints with 6.48 ± 5.67 points and the sham joints with 6.86 ± 5.84 points (p = 0.7953) The MRI scoring yielded 0.34 ± 0.89 points for the ACLR and 0.03 ± 0.17 for the sham knee joints. There was no correlation between the histological and MRI scores (r = 0.10021). The gene expression profiles as well as the immunohistochemical findings showed no significant differences between ACLR and sham knee joints. In conclusion, both knee joints showed histological signs of OA after 26 weeks irrespective of whether the ACL was resected or not. As MRI results did not match the histological findings, MRI was obviously unsuitable to diagnose the OA in GM. The analysis of the expression patterns of the 10 genes could not shed light on the question, whether sham operation also induced cartilage erosion or if the degeneration was spontaneous. The modified Pond-Nuki model may be used with reservation in the adult minipig to induce an isolated osteoarthritis.

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Section: Discussionmentioning

confidence: 84%

“…For the detection of OA with MRI, lots of different sequences are available and used [1,111,112,113]. There is general agreement that cartilage damage evaluation with standard MRI examination remains problematic.…”

Section: Discussionmentioning

confidence: 99%

Osteoarthritis in the Knee Joints of Göttingen Minipigs after Resection of the Anterior Cruciate Ligament? Missing Correlation of MRI, Gene and Protein Expression with Histological Scoring

et al. 2016

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“…42 However, the work by Bittersohl et al reports poor classification accuracy for detecting early histological stages of OA in humans, suggesting a need for more sensitive quantitative measures. 43 Building upon earlier methods, the OARSI histopathology assessment system was developed specifically to increase dynamic range over the disease process and improve stratification within early and mild OA states 18 , thereby improving detection of matrix-level changes that precede development of structural OA identifiable by morphological imaging. 26 Further, the OARSI assessment has demonstrated higher reliability and reproducibility compared to earlier methods.…”

Section: Discussionmentioning

confidence: 99%

Classification of histologically scored human knee osteochondral plugs by quantitative analysis of magnetic resonance images at 3T

Lukas

Fishbein

Lin

et al. 2015

Journal Orthopaedic Research

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This work evaluates the ability of quantitative MRI to discriminate between normal and pathological human osteochondral plugs characterized by the Osteoarthritis Research Society International (OARSI) histological system. Normal and osteoarthritic human osteochondral plugs were scored using the OARSI histological system and imaged at 3 T using MRI sequences producing T1 and T2 contrast and measuring T1, T2, and T2* relaxation times, magnetization transfer, and diffusion. The classification accuracies of quantitative MRI parameters and corresponding weighted image intensities were evaluated. Classification models based on the Mahalanobis distance metric for each MRI measurement were trained and validated using leave-one-out cross-validation with plugs grouped according to OARSI histological grade and score. MRI measurements used for classification were performed using a region-of-interest analysis which included superficial, deep, and full-thickness cartilage. The best classifiers based on OARSI grade and score were T1- and T2-weighted image intensities, which yielded accuracies of 0.68 and 0.75, respectively. Classification accuracies using OARSI score-based group membership were generally higher when compared with grade-based group membership. MRI-based classification—either using quantitative MRI parameters or weighted image intensities—is able to detect early osteoarthritic tissue changes as classified by the OARSI histological system. These findings suggest the benefit of incorporating quantitative MRI acquisitions in a comprehensive clinical evaluation of OA.

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“…Histological scoring systems that assess the structural composition of cartilage matrix and determine the severity of degradation 31 can be used as a reference standard to establish a classification scheme using image features 32–34 . The OARSI histopathology assessment has been shown to be reliable and reproducible 35 and is an informative gold standard for cartilage classification using quantitative MR measurements 9 .…”

Section: Discussionmentioning

confidence: 99%

Machine learning classification of OARSI-scored human articular cartilage using magnetic resonance imaging

Ashinsky

Coletta

Bouhrara

et al. 2015

Osteoarthritis and Cartilage

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Objective The purpose of this study is to evaluate the ability of machine learning to discriminate between magnetic resonance images (MRI) of normal and pathological human articular cartilage obtained under standard clinical conditions. Method An approach to MRI classification of cartilage degradation is proposed using pattern recognition and multivariable regression in which image features from MRIs of histologically scored human articular cartilage plugs were computed using weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHRM). The WND-CHRM method was first applied to several clinically available MRI scan types to perform binary classification of normal and osteoarthritic osteochondral plugs based on the OARSI histological system. In addition, the image features computed from WND-CHRM were used to develop a multiple linear least-squares regression model for classification and prediction of an OARSI score for each cartilage plug. Results The binary classification of normal and osteoarthritic plugs yielded results of limited quality with accuracies between 36% and 70%. However, multiple linear least-squares regression successfully predicted OARSI scores and classified plugs with accuracies as high as 86%. The present results improve upon the previously-reported accuracy of classification using average MRI signal intensities and parameter values. Conclusion MRI features detected by WND-CHRM reflect cartilage degradation status as assessed by OARSI histologic grading. WND-CHRM is therefore of potential use in the clinical detection and grading of osteoarthritis.

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Experimental model to evaluate in vivo and in vitro cartilage MR imaging by means of histological analyses

Cited by 13 publications

References 35 publications

Osteoarthritis in the Knee Joints of Göttingen Minipigs after Resection of the Anterior Cruciate Ligament? Missing Correlation of MRI, Gene and Protein Expression with Histological Scoring

Osteoarthritis in the Knee Joints of Göttingen Minipigs after Resection of the Anterior Cruciate Ligament? Missing Correlation of MRI, Gene and Protein Expression with Histological Scoring

Classification of histologically scored human knee osteochondral plugs by quantitative analysis of magnetic resonance images at 3T

Machine learning classification of OARSI-scored human articular cartilage using magnetic resonance imaging

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