Constantinos Loukas

The relationship between oscillatory activity and motor reaction time in the parkinsonian subthalamic nucleus.

Averaging techniques have demonstrated that movement preparatory cues and movement itself are associated with marked reductions in the oscillatory synchrony of local neuronal populations in the area of the human parkinsonian subthalamic nucleus (STN), as indexed by 8–30 Hz local field potential (LFP) activity. In order to examine the detailed nature and strength of the relationship between reductions in oscillatory activity and movement we examined single‐trial LFP activity recorded from the STN area of parkinsonian subjects engaged in a choice reaction task. In this task an initial warning cue was either fully predictive or non‐predictive of the hand required to make a later motor response. This motor response was elicited by a second go cue to which data were aligned. We observed a significant linear relationship between the onset time of oscillation reduction after go cues and subsequent motor response time across single trials within subjects. Consistent with this observation we also found a positive correlation of power with response time following go cues. In addition, we observed shorter durations of suppression in fully predictive trials where selection of the response could precede go cue presentation. The results are consistent with the hypothesis that reductions in 8–30 Hz population synchrony in the STN area are related to the processing required for motor preparation, particularly response selection.

An image analysis-based approach for automated counting of cancer cell nuclei in tissue sections.

Semiquantitative evaluation and manual cell counting are the commonly used procedures to assess positive staining of molecular markers in tissue sections. Manual counting is also a laborious task in which consistent objectivity is difficult to achieve. Recently, image analysis has been explored, but the studies reported were limited to histological images acquired at high magnification and containing uniformly stained cells.

Corticocortical coupling in chronic stroke: Its relevance to recovery

Background: The mechanisms behind motor recovery from stroke are not clearly understood. Functional imaging studies have demonstrated task-related brain activation in several motor areas, but few studies have attempted to correlate this with stroke outcome. Moreover, these studies have focused on how motor areas may individually contribute to compensation. Here, the authors investigate whether different cortical areas interact to form dynamic assemblies that may then compensate for disability. Methods: The authors investigated corticocortical coherence in 16 healthy subjects and 25 patients with chronic stroke involving one cerebral hemisphere and having varying degrees of motor recovery. Scalp EEG was recorded at rest and while right-handed subjects performed a unimanual grip task. The degree of functional recovery after stroke was assessed using a range of outcome measures. Results: Compared with healthy subjects, hand-related asymmetries in task-related EEG-EEG coherence were increased between mesial and lateral frontal regions of the affected hemisphere, over mesial frontal regions, and over lateral frontal areas of the unaffected hemisphere when patients with stroke gripped with their affected hand. Mesial hand-related asymmetries in task-related power and coherence were negatively correlated with recovery. Conclusion: Increases in task-related coupling between cortical areas may dynamically compensate for brain damage after stroke. Some of this increased coupling, particularly that over mesial frontal areas, decreases as patients make a functional recovery.

A survey on histological image analysis-based assessment of three major biological factors influencing radiotherapy: proliferation, hypoxia and vasculature

Image analysis is a rapidly evolving field with growing applications in science and engineering. In cancer research, it has played a key role in advancing techniques of major diagnostic importance, minimising human intervention and providing vital clinical information. Especially in the field of tissue microscopy, the use of computers for the automated analysis of histological sections is becoming increasingly important. This paper presents an overview of various image analysis methodologies and summarises developments in this field, with great emphasis given on the assessment of three major biological factors known to influence the outcome of radiotherapy: proliferation, vasculature and hypoxia. A brief introduction followed by a survey is provided in each of these areas.

Breast Cancer Characterization Based on Image Classification of Tissue Sections Visualized under Low Magnification

Rapid assessment of tissue biopsies is a critical issue in modern histopathology. For breast cancer diagnosis, the shape of the nuclei and the architectural pattern of the tissue are evaluated under high and low magnifications, respectively. In this study, we focus on the development of a pattern classification system for the assessment of breast cancer images captured under low magnification (×10). Sixty-five regions of interest were selected from 60 images of breast cancer tissue sections. Texture analysis provided 30 textural features per image. Three different pattern recognition algorithms were employed (kNN, SVM, and PNN) for classifying the images into three malignancy grades: I–III. The classifiers were validated with leave-one-out (training) and cross-validation (testing) modes. The average discrimination efficiency of the kNN, SVM, and PNN classifiers in the training mode was close to 97%, 95%, and 97%, respectively, whereas in the test mode, the average classification accuracy achieved was 86%, 85%, and 90%, respectively. Assessment of breast cancer tissue sections could be applied in complex large-scale images using textural features and pattern classifiers. The proposed technique provides several benefits, such as speed of analysis and automation, and could potentially replace the laborious task of visual examination.

Multivariate Autoregressive Modeling of Hand Kinematics for Laparoscopic Skills Assessment of Surgical Trainees

Virtual reality (VR) simulators aim to enhance surgical education by allowing trainees to optimize their skills without patient risk. To achieve this quality, an objective analysis of surgical dexterity is crucial. The application of hidden Markov models (HMMs) has offered important insights in the evaluation of surgical skills (e.g., task decomposition), but there are still issues that need standardization, especially when constructing the hand motion vocabulary. In this paper, we investigate an alternative approach based on multivariate autoregressive (MAR) models. Kinematic signals from orientation sensors attached to the instruments of a VR simulator were used to study the laparoscopic skills of surgical residents. Two different tasks were performed: knot tying and needle driving. A variational Bayesian (VB) approximation was employed to calculate the MAR coefficients, which after data reduction were fed to a classifier. The MAR weights also provided the opportunity to study the hand motion connections. Specificity (Spec) and sensitivity (Sens) analysis was used to evaluate and compare the classification performance between MAR models and HMMs. Our results demonstrate the strength of the proposed approach in recognizing surgical maneuvers of residents with limited experience in laparoscopic suturing. The MAR approach yielded the best performance (Sens/Spec: 86%-96%), significantly outperforming the well-established approach of statistical similarity between different HMMs (Sens/Spec: 64%-87%). Subjects at the end of residency training demonstrated more and greater hand motion couplings compared to beginners. The methodological aspects of the proposed approach may be easily embedded in the assessment module of modern laparoscopic simulators.

An integrated approach to endoscopic instrument tracking for augmented reality applications in surgical simulation training.

Despite the popular use of virtual and physical reality simulators in laparoscopic training, the educational potential of augmented reality (AR) has not received much attention. A major challenge is the robust tracking and three‐dimensional (3D) pose estimation of the endoscopic instrument, which are essential for achieving interaction with the virtual world and for realistic rendering when the virtual scene is occluded by the instrument. In this paper we propose a method that addresses these issues, based solely on visual information obtained from the endoscopic camera.

Deconstructing laparoscopic competence in a virtual reality simulation environment.

BACKGROUND Virtual reality (VR) simulators play a substantial role in modern medical education and have generated several performance parameters that are not always standardized and open to clear and easy interpretation. Consequently, our study objective was to investigate how these parameters contribute to the enhancement of key competencies in laparoscopic surgical skills. METHODS We recruited 20 residents and 8 experienced surgeons to participate in this study. The residents were trained on 5 basic tasks (4 of them at two difficulty levels) using a commercially available VR simulator. Study participants also performed an additional 3 complex tasks before and after training for assessment purposes. The experienced surgeons served as controls and so only performed the assessment tasks. Performance parameters were grouped to reflect errors in dexterity, safety, and technical skill. These errors, as well as the parameters of time and instrument velocity, were analyzed during training and assessment. RESULTS Performance for training tasks demonstrated notable learning curves for most of the parameters that were measured (ie, plateaus varied between the second and seventh VR training session). Velocity was influenced least by the training (3 of the 5 tasks), while time and dexterity were influenced most (all 5 tasks and for both difficulty levels). In the assessment tasks, technical skill was improved (P < .05) for some study participants, but this improvement was not demonstrated in all of the complex procedures tested (eg, bowel suturing). There was a significant improvement in safety (all 3 tasks; P < .05), and time to completion and dexterity (both of them in 2 tasks; P < .05). Experienced surgeons scored at a greater level than VR-trained residents in terms of time (all tasks; P < .05), safety and technical skill (bowel suturing; P < .05), as well as dexterity (adhesiolysis and bowel suturing; P < .05). CONCLUSION VR simulation training contributed markedly to the enhancement of key surgical competencies of residents. The proposed mapping of the simulator parameters may help program directors and trainees evaluate important competency domains during VR-based surgical training.

A novel augmented reality simulator for skills assessment in minimal invasive surgery.

IntroductionOver the past decade, simulation-based training has come to the foreground as an efficient method for training and assessment of surgical skills in minimal invasive surgery. Box-trainers and virtual reality (VR) simulators have been introduced in the teaching curricula and have substituted to some extent the traditional model of training based on animals or cadavers. Augmented reality (AR) is a new technology that allows blending of VR elements and real objects within a real-world scene. In this paper, we present a novel AR simulator for assessment of basic laparoscopic skills.MethodsThe components of the proposed system include: a box-trainer, a camera and a set of laparoscopic tools equipped with custom-made sensors that allow interaction with VR training elements. Three AR tasks were developed, focusing on basic skills such as perception of depth of field, hand-eye coordination and bimanual operation. The construct validity of the system was evaluated via a comparison between two experience groups: novices with no experience in laparoscopic surgery and experienced surgeons. The observed metrics included task execution time, tool pathlength and two task-specific errors. The study also included a feedback questionnaire requiring participants to evaluate the face-validity of the system.ResultsBetween-group comparison demonstrated highly significant differences (<0.01) in all performance metrics and tasks denoting the simulator’s construct validity. Qualitative analysis on the instruments’ trajectories highlighted differences between novices and experts regarding smoothness and economy of motion. Subjects’ ratings on the feedback questionnaire highlighted the face-validity of the training system.ConclusionsThe results highlight the potential of the proposed simulator to discriminate groups with different expertise providing a proof of concept for the potential use of AR as a core technology for laparoscopic simulation training.

A common N400 EEG component reflecting contextual integration irrespective of symbolic form

OBJECTIVE Electroencephalographic (EEG) waves modulated by context have been identified about 400 ms after presentation of a new semantic stimulus, such as a word or a number, within a prior context. However, it is not known if any component of these waves arises from a common brain system activated by different symbolic forms. METHODS Multichannel EEG recordings were performed in 10 healthy subjects during the presentation of lexical and numerical series with congruent and incongruent endings. EEG was analysed using a combination of independent component and cluster analysis. RESULTS Contextual integration of semantic stimuli elicited a negative independent component at around 400 ms that shared the same pattern of spatio-temporal covariation across numerical series and sentences within single subjects. This independent component was bigger following incongruent endings. CONCLUSIONS These data provide evidence that one element of the activity contributing to the N400 is common to different symbolic forms. SIGNIFICANCE One component of the brain systems evaluating the semantic inter-relationship of new stimuli with prior context may be common to different symbolic forms.