Data mining MR image features of select structures for lateralization of mesial temporal lobe epilepsy

PURPOSE: This study systematically investigates the predictive power of volumetric imaging feature sets extracted from select neuroanatomical sites in lateralizing the epileptogenic focus in mesial temporal lobe epilepsy (mTLE) patients. METHODS: A cohort of 68 unilateral mTLE patients who had achieved an Engel class I outcome postsurgically was studied retrospectively. The volumes of multiple brain structures were extracted from preoperative magnetic resonance (MR) images in each. The MR image data set consisted of 54 patients with imaging evidence for hippocampal sclerosis (HS-P) and 14 patients without (HS-N). Data mining techniques (i.e., feature extraction, feature selection, machine learning classifiers) were applied to provide measures of the relative contributions of structures and their correlations with one another. After removing redundant correlated structures, a minimum set of structures was determined as a marker for mTLE lateralization. RESULTS: Using a logistic regression classifier, the volumes of both hippocampus and amygdala showed correct lateralization rates of 94.1%. This reflected about 11.7% improvement in accuracy relative to using hippocampal volume alone. The addition of thalamic volume increased the lateralization rate to 98.5%. This ternary-structural marker provided a 100% and 92.9% mTLE lateralization accuracy, respectively, for the HS-P and HS-N groups. CONCLUSIONS: The proposed tristructural MR imaging biomarker provides greater lateralization accuracy relative to single- and double-structural biomarkers and thus, may play a more effective role in the surgical decision-making process. Also, lateralization of the patients with insignificant atrophy of hippocampus by the proposed method supports the notion of associated structural changes involving the amygdala and thalamus

Segmentation of corpus callosum using diffusion tensor imaging: validation in patients with glioblastoma

Abstract Background This paper presents a three-dimensional (3D) method for segmenting corpus callosum in normal subjects and brain cancer patients with glioblastoma. Methods Nineteen patients with histologically confirmed treatment naïve glioblastoma and eleven normal control subjects underwent DTI on a 3T scanner. Based on the information inherent in diffusion tensors, a similarity measure was proposed and used in the proposed algorithm. In this algorithm, diffusion pattern of corpus callosum was used as prior information. Subsequently, corpus callosum was automatically divided into Witelson subdivisions. We simulated the potential rotation of corpus callosum under tumor pressure and studied the reproducibility of the proposed segmentation method in such cases. Results Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations. Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results. Conclusions The proposed method and similarity measure segment corpus callosum by propagating a hyper-surface inside the structure (resulting in high sensitivity), without penetrating into neighboring fiber bundles (resulting in high specificity)

A neuroimaging model based on MRI, DTI, and spect findings for lateralization of temporal lobe epilepsy

Purpose: Temporal lobe epilepsy (TLE) is the most widespread type of epilepsy with the most successful resection outcome. Interhemispheric variations detected in the images of T1-weighted and fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI), and ictal and interictal single photon emission computed tomography (SPECT), and in the indices of mean diffusivity (MD) and fractional anisotropy (FA) of diffusion tensor imaging (DTI), are within the established markers ofTLE laterality. However, current non-quantitative imaging evaluations may not optimally incorporate the imaging information into the decision-making process prior to resection of mesial temporalstructures. We hypothesize that quantitative TLE lateralization response models of MRI, DTI, and SPECTneuroimaging attributes will optimize the selection ofsurgical candidates and reduce, in some cases, the need for extraoperative electrocorticography (eECoG). Method: Neuroimaging features of 138 retrospective TLE patients with Engel class l surgical outcomes were extracted, including the hippocampal volumes, normalized ictal-interictal SPECT and FLAIR intensities, and mean diffusivity, along with the cingulate and forniceal fractional anisotropy (FA). Using logistic function regression, univariate and multivariate models were developed. Results: The model incorporating all multivariate attributes for138 TLE cases that had at least one imaging attribute and imputing the missing attributes with the mean values of the corresponding attributes measured oncontrol cohort reached the probability of detection and false alarm of 0.83 and 0.17 for all cases, and 0.90 and 0.10 for the patients who underwent eECoG. Conclusion: Increased reliability in lateralizing TLE cases using the proposed response model involving the incorporation of the multivariate attributes reinforces the notion that eECoG in a number ofcases may be circumvented. The proposed response model can be further generalized by integrating attributes of additional neuroclinical, neurophysiological, neuropsychological, and neuroimaging attributes into the presurgical decision making process

HIGH TIBIAL OSTEOTOMYWITHOUT FIXATION: TREATMENT OF KNEE OSTEOARTHRITIS

Introduction. Considering the high frequency of osteoarthritis of the knee and varus and valgus deformities in this disorder, there are several methods of treatment to reduce patients symptoms. Hight tibial osteotomy and arthroplasty are knowm surgical methods for these patients. Because of socioeconomic problems (about arthroplasty) in our country and unfavorable long term results of it, osteotomy has found a specific position in the treatment of these patients. Osteotomy, itself can be performed in different ways. High tibial osteotomy without internal fixation and secure the osteotomy site on the basis of inherent stability and cast application (external support); reduce the complications and cast of operation and the surgen is able to recorrect the deformity after operation. Also, there is no need for implant removal by the second surgery.
 Methods. This quasiexperimental study was performed on 42 patients with osteoarthritis of the knee who refered to Al- zahra hospital orthopedic clinic from October 1997 to October 1999. Their age, physical and radiographic conditions were acceptable for osteotomy (on the basis of texts ). Therefore, the osteotomy was performed and 30 patients were followed for 4 months for probable complications and outcomes. Complications which had been cheked in every visit by physical examination and radiographic imaging, included: loss of reduction, maluniun, nonunion, infection, knee stiffness.
 Results. Non of the before mentioned complications were seen. Also no nervous (proneal nerve palsy) and vascular complications were seen in patients in the following period.
 Discussion. It can be said that with meticulus operation technique, osteotomy without internal fixation resulted in less complications and costs, ability to recorrect the deformity and no need for implement removal

LIMB LENGTHENING USING WAGNER'S TECHNIQUE

Introduction. Limb length discrepancy is a disabling anomaly that has many causes including congential, traumatic and paralytic. This study was designed to evaluate results and complications of Wagner's technique in lower limb lenghtening.
 Methods. In this retrospective study results of the Wagner's technique in seventy paiteints during ten years were studied. Patients were followed for 1 to 9 years after operation with mean of 6 years. Results of operation, complications and paitients statisfaction were recorded.
 Results. Among the 70 paitents 71% were male and 29% were female. The average time of paitients hospitalization was 6 days for each of first and second satges. The tibial and femoral lengthening were performed in the 84% and 16% respectively. Limb lengthening achieved minimally 4 - 5 cm and maximally 10 cm (mean=6.6cm). In 73%, the cause of discrepancy was paralytic and the other causes were traumatic and congenital anomalies. Complications rate were 47% totally. The most common complication was pin tract infection that was threated conservatively. Results of operation and satisfaction of the patients were good in 85% and fair in 15%.
 Discussion. The Wagner's method of limb lengthening is a safe and simple method, with low complications and we recommend it for the treatment of lower limb discrepancy yet

Lateralization of temporal lobe epilepsy by multimodal multinomial hippocampal response-driven models

PURPOSE: Multiple modalities are used in determining laterality in mesial temporal lobe epilepsy (mTLE). It is unclear how much different imaging modalities should be weighted in decision-making. The purpose of this study is to develop response-driven multimodal multinomial models for lateralization of epileptogenicity in mTLE patients based upon imaging features in order to maximize the accuracy of noninvasive studies. METHODS AND MATERIALS: The volumes, means and standard deviations of FLAIR intensity and means of normalized ictal-interictal SPECT intensity of the left and right hippocampi were extracted from preoperative images of a retrospective cohort of 45 mTLE patients with Engel class I surgical outcomes, as well as images of a cohort of 20 control, nonepileptic subjects. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Based on the Bayesian model averaging (BMA) theorem, response models were developed as compositions of independent univariate models. RESULTS: A BMA model composed of posterior probabilities of univariate response models of hippocampal volumes, means and standard deviations of FLAIR intensity, and means of SPECT intensity with the estimated weighting coefficients of 0.28, 0.32, 0.09, and 0.31, respectively, as well as a multivariate response model incorporating all mentioned attributes, demonstrated complete reliability by achieving a probability of detection of one with no false alarms to establish proper laterality in all mTLE patients. CONCLUSION: The proposed multinomial multivariate response-driven model provides a reliable lateralization of mesial temporal epileptogenicity including those patients who require phase II assessment

A Combination of Particle Swarm Optimization and Minkowski Weighted K-Means Clustering: Application in Lateralization of Temporal Lobe Epilepsy

K-Means is one of the most popular clustering algorithms that partitions observations into nonoverlapping subgroups based on a predefined similarity metric. Its drawbacks include a sensitivity to noisy features and a dependency of its resulting clusters upon the initial selection of cluster centroids resulting in the algorithm converging to local optima. Minkowski weighted K-Means (MWK-Means) addresses the issue of sensitivity to noisy features, but is sensitive to the initialization of clusters, and so the algorithm may similarly converge to local optima. Particle Swarm Optimization (PSO) uses a globalized search method to solve this issue. We present a hybrid Particle Swarm Optimization (PSO) + MWK-Means clustering algorithm to address all the above problems in a single framework, while maintaining benefits of PSO and MWK Means methods. This study investigated the utility of this approach in lateralizing the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Using MEG-CSI, we analyzed preoperative resting state MEG data from 17 adults TLE patients with Engel class I outcomes to determine coherence at 54 anatomical sites and compared the results with 17 age- and gender-matched controls. Fiber-tracking was performed through the same anatomical sites using DTI data. Indices of both MEG coherence and DTI nodal degree were calculated. A PSO + MWK-Means clustering algorithm was applied to identify the side of temporal lobe epileptogenicity and distinguish between normal and TLE cases. The PSO module was aimed at identifying initial cluster centroids and assigning initial feature weights to cluster centroids and, hence, transferring to the MWK-Means module for the final optimal clustering solution. We demonstrated improvements with the use of the PSO + MWK-Means clustering algorithm compared to that of K-Means and MWK-Means independently. PSO + MWK-Means was able to successfully distinguish between normal and TLE in 97.2% and 82.3% of cases for DTI and MEG data, respectively. It also lateralized left and right TLE in 82.3% and 93.6% of cases for DTI and MEG data, respectively. The proposed optimization and clustering methodology for MEG and DTI features, as they relate to focal epileptogenicity, would enhance the identification of the TLE laterality in cases of unilateral epileptogenicity