Ability of dGEMRIC and T2 mapping to evaluate cartilage repair after microfracture: a goat study

OBJECTIVE: To investigate the ability of delayed gadolinium-enhanced magnetic resonance (MR) imaging of cartilage (dGEMRIC) and T2 mapping to evaluate the quality of repair tissue after microfracture. DESIGN: Twelve knees from 12 goats were studied. An osteochondral defect (diameter, 6mm; depth, 3mm) with microfracture was created in the weight-bearing aspect of both the medial and lateral femoral condyles. Goats were euthanized at 24 weeks (n=6) and 48 weeks (n=6) postsurgery. Pre-contrast R1 (R1pre) and post-contrast R1 (R1post) measurements for dGEMRIC and a pre-contrast T2 measurement for T2 mapping were performed with a 3T MR imaging system. MR imaging findings were compared with histological and biochemical assessments. RESULTS: In native cartilage, significant correlations were observed between the R1post and the glycosaminoglycan (GAG) concentration, as well as DeltaR1 (difference between the R1pre and R1post) and the GAG concentration (P<0.05). In repair tissue, a significant correlation was observed between DeltaR1 and the GAG concentration (P<0.05), but not between the R1post and the GAG concentration. In both repair tissue and native cartilage, no correlation was observed between T2 and the water concentration or between T2 and the hydroxyproline (HP) concentration. A zonal variation of T2 and a clear dependence of T2 on the angles relative to B0 were observed in native cartilage, but not in repair tissue. CONCLUSION: dGEMRIC with DeltaR1 measurement might be useful for the evaluation of the GAG concentration in repair tissue after microfracture. T2 mapping might be useful for the differentiation of repair tissue after microfracture from native cartilage; however, its potential to assess the specific biochemical markers in native cartilage as well as repair tissue may be limited.

Multimodal approach in the use of clinical scoring, morphological MRI and biochemical T2-mapping and diffusion-weighted imaging in their ability to assess differences between cartilage repair tissue after microfracture therapy and matrix-associated autologous chondrocyte transplantation: a pilot study

OBJECTIVE: The aim of the present pilot study is to show initial results of a multimodal approach using clinical scoring, morphological magnetic resonance imaging (MRI) and biochemical T2-relaxation and diffusion-weighted imaging (DWI) in their ability to assess differences between cartilage repair tissue after microfracture therapy (MFX) and matrix-associated autologous chondrocyte transplantation (MACT). METHOD: Twenty patients were cross-sectionally evaluated at different post-operative intervals from 12 to 63 months after MFX and 12-59 months after MACT. The two groups were matched by age (MFX: 36.0+/-10.4 years; MACT: 35.1+/-7.7 years) and post-operative interval (MFX: 32.6+/-16.7 months; MACT: 31.7+/-18.3 months). After clinical evaluation using the Lysholm score, 3T-MRI was performed obtaining the MR observation of cartilage repair tissue (MOCART) score as well as T2-mapping and DWI for multi-parametric MRI. Quantitative T2-relaxation was achieved using a multi-echo spin-echo sequence; semi-quantitative diffusion-quotient (signal intensity without diffusion-weighting divided by signal intensity with diffusion weighting) was prepared by a partially balanced, steady-state gradient-echo pulse sequence. RESULTS: No differences in Lysholm (P=0.420) or MOCART (P=0.209) score were observed between MFX and MACT. T2-mapping showed lower T2 values after MFX compared to MACT (P=0.039). DWI distinguished between healthy cartilage and cartilage repair tissue in both procedures (MFX: P=0.001; MACT: P=0.007). Correlations were found between the Lysholm and the MOCART score (Pearson: 0.484; P=0.031), between the Lysholm score and DWI (Pearson:-0.557; P=0.011) and a trend between the Lysholm score and T2 (Person: 0.304; P=0.193). CONCLUSION: Using T2-mapping and DWI, additional information could be gained compared to clinical scoring or morphological MRI. In combination clinical, MR-morphological and MR-biochemical parameters can be seen as a promising multimodal tool in the follow-up of cartilage repair.

Validation of the estimation of physiologic ability and surgical stress (E-PASS) score in liver surgery

BACKGROUND: The estimation of physiologic ability and surgical stress (E-PASS) has been used to produce a numerical estimate of expected mortality and morbidity after elective gastrointestinal surgery. The aim of this study was to validate E-PASS in a selected cohort of patients requiring liver resections (LR). METHODS: In this retrospective study, E-PASS predictor equations for morbidity and mortality were applied to the prospective data from 243 patients requiring LR. The observed rates were compared with predicted rates using Fisher's exact test. The discriminative capability of E-PASS was evaluated using receiver-operating characteristic (ROC) curve analysis. RESULTS: The observed and predicted overall mortality rates were both 3.3% and the morbidity rates were 31.3 and 26.9%, respectively. There was a significant difference in the comprehensive risk scores for deceased and surviving patients (p = 0.043). However, the scores for patients with or without complications were not significantly different (p = 0.120). Subsequent ROC curve analysis revealed a poor predictive accuracy for morbidity. CONCLUSIONS: The E-PASS score seems to effectively predict mortality in this specific group of patients but is a poor predictor of complications. A new modified logistic regression might be required for LR in order to better predict the postoperative outcome.

Evaluation of texture features in hepatic tissue characterization from non-enhanced CT images

Aim of this paper is to evaluate the diagnostic contribution of various types of texture features in discrimination of hepatic tissue in abdominal non-enhanced Computed Tomography (CT) images. Regions of Interest (ROIs) corresponding to the classes: normal liver, cyst, hemangioma, and hepatocellular carcinoma were drawn by an experienced radiologist. For each ROI, five distinct sets of texture features are extracted using First Order Statistics (FOS), Spatial Gray Level Dependence Matrix (SGLDM), Gray Level Difference Method (GLDM), Laws' Texture Energy Measures (TEM), and Fractal Dimension Measurements (FDM). In order to evaluate the ability of the texture features to discriminate the various types of hepatic tissue, each set of texture features, or its reduced version after genetic algorithm based feature selection, was fed to a feed-forward Neural Network (NN) classifier. For each NN, the area under Receiver Operating Characteristic (ROC) curves (Az) was calculated for all one-vs-all discriminations of hepatic tissue. Additionally, the total Az for the multi-class discrimination task was estimated. The results show that features derived from FOS perform better than other texture features (total Az: 0.802+/-0.083) in the discrimination of hepatic tissue.

Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws' texture and neural networks

Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Direct and indirect associations between plant species richness and productivity in grasslands: regional differences preclude simple generalization of productivity-biodiversity relationships

Plant species richness of permanent grasslands has often been found to be significantly associated with productivity. Concentrations of nutrients in biomass can give further insight into these productivity- plant species richness relationships, e.g. by reflecting land use or soil characteristics. However, the consistency of such relationships across different regions has rarely been taken into account, which might significantly compromise our potential for generalization. We recorded plant species richness and measured above-ground biomass and concentrations of nutrients in biomass in 295 grasslands in three regions in Germany that differ in soil and climatic conditions. Structural equation modelling revealed that nutrient concentrations were mostly indirectly associated with plant species richness via biomass production. However, negative associations between the concentrations of different nutrients and biomass and plant species richness differed considerably among regions. While in two regions, more than 40% of the variation in plant species richness could be attributed to variation in biomass, K, P, and to some degree also N concentrations, in the third region only 15% of the variation could be explained in this way. Generally, highest plant species richness was recorded in grasslands where N and P were co-limiting plant growth, in contrast to N or K (co-) limitation. But again, this pattern was not recorded in the third region. While for two regions land-use intensity and especially the application of fertilizers are suggested to be the main drivers causing the observed negative associations with productivity, in the third region the little variance accounted for, low species richness and weak relationships implied that former intensive grassland management, ongoing mineralization of peat and fluctuating water levels in fen grasslands have overruled effects of current land-use intensity and productivity. Finally, we conclude that regional replication is of major importance for studies seeking general insights into productivity-diversity relationships.

Ranking of tests for pain hypersensitivity according to their discriminative ability in chronic neck pain

BACKGROUND AND OBJECTIVES Quantitative sensory testing (QST) is widely used to investigate peripheral and central sensitization. However, the comparative performance of different QST for diagnostic or prognostic purposes is unclear. We explored the discriminative ability of different quantitative sensory tests in distinguishing between patients with chronic neck pain and pain-free control subjects and ranked these tests according to the extent of their association with pain hypersensitivity. METHODS We performed a case-control study in 40 patients and 300 control subjects. Twenty-six tests, including different modalities of pressure, heat, cold, and electrical stimulation, were used. As measures of discrimination, we estimated receiver operating characteristic curves and likelihood ratios. RESULTS The following quantitative sensory tests displayed the best discriminative value: (1) pressure pain threshold at the site of the most severe neck pain (fitted area under the receiver operating characteristic curve, 0.92), (2) reflex threshold to single electrical stimulation (0.90), (3) pain threshold to single electrical stimulation (0.89), (4) pain threshold to repeated electrical stimulation (0.87), and (5) pressure pain tolerance threshold at the site of the most severe neck pain (0.86). Only the first 3 could be used for both ruling in and out pain hypersensitivity. CONCLUSIONS Pressure stimulation at the site of the most severe pain and parameters of electrical stimulation were the most appropriate QST to distinguish between patients with chronic neck pain and asymptomatic control subjects. These findings may be used to select the tests in future diagnostic and longitudinal prognostic studies on patients with neck pain and to optimize the assessment of localized and spreading sensitization in chronic pain patients.