Neurosurgery videos on online video sharing sites: The next best teacher?

BACKGROUND: E-learning platforms, especially the online neurosurgical video sharing sites, are playing a key role in the dissemination of knowledge related to the essential steps of operative neurosurgery. AIM: A national survey was undertaken to assess the utility of neurosurgical operative videos exhibited on the online video-sharing sites. MATERIALS AND METHODS: Resident trainees in neurosurgery, as well as junior and senior consultant neurosurgeons practicing in India were provided, on the Google platform, a questionnaire consisting of nine multiple-choice questions and a space for remarks. 520 people were contacted using e mail and/or whattsapp modalities, out which 98 responses were considered valid. RESULTS: Majority (n = 87, 88.8%) of the responders voted that internet videos have helped them in improving their surgical skills. There was no statistically significant difference between people working in rural and urban areas in this regard (P = 0.517). Both senior and junior neurosurgeons were utilizing these online videos for enhancing their surgical skills, and there was no statistically significant difference regarding the perception of the usefulness of these online video channels between the two groups (P = 0.660). However, the response rate to the questionnaires sent was only 18.84%. CONCLUSIONS: Online video-sharing platforms are useful, especially in a country like India with diverse neurosurgical infrastructure. The need for the development and maintenance of a dedicated, high-quality, structured video bank through collaboration and cooperation of high volume centers and institutes of repute in India is strongly advocated.

State-of-the-art review on automated lumen and adventitial border delineation and its measurements in carotid ultrasound.

BACKGROUND AND OBJECTIVE: Accurate, reliable, efficient, and precise measurements of the lumen geometry of the common carotid artery (CCA) are important for (a) managing the progression/regression of atherosclerotic build-up and (b) the risk of stroke. The image-based degree of stenosis in the carotid artery and the plaque burden can be predicted using the automated carotid lumen diameter (LD)/inter-adventitial diameter (IAD) measurements from B-mode ultrasound images. The objective of this review is to present the state-of-the-art methods and systems for the measurement of LD/IAD in CCA based on automated or semi-automated strategies. Further, the performance of these systems is compared based on various metrics for its measurements. METHODS: The automated algorithms proposed for the segmentation of carotid lumen are broadly classified into two different categories as: region-based and boundary-based. These techniques are discussed in detail specifying their pros and cons. Further, we discuss the challenges encountered in the segmentation process along with its quantitative assessment. Lastly, we present stenosis quantification and risk stratification strategies. RESULTS: Even though, we have found more boundary-based approaches compared to region-based approaches in the literature, however, the region-based strategy yield more satisfactory performance. Novel risk stratification strategies are presented. On a patient database containing 203 patients, 9 patients are identified as high risk patients, whereas 27 patients are identified as medium risk patients. CONCLUSIONS: We have presented different techniques for the lumen segmentation of the common carotid artery from B-mode ultrasound images and measurement of lumen diameter and inter-adventitial diameter. We believe that the issue regarding boundary-based techniques can be compensated by taking regional statistics embedded with boundary-based information.

Antero posterior elongation of midbrain in traumatic brain injury- significant sign yet a mistaken entity.

BACKGROUND: Antero posterior elongation of the midbrain is observed occasionally in severe traumatic brain injury and generally implies a bad outcome. The objective of the study was to document midbrain elongation and identify the implications of this finding. METHODS: This prospective study included 100 patients with traumatic intracranial haematoma of more than 20 cc in volume. Key measurements were taken in the midbrain and pontine regions and the status of perimesencephalic basal cisterns was noted. All the predictors were analyzed for the outcome. RESULTS: In twenty-nine patients the distorted midbrain appeared to be elongated in the antero posterior direction on visual inspection of CT head images. However, on statistical analysis, it was made out that there is no demonstrable anteroposterior lengthening of the midbrain. The factors influencing the appearance and outcome were discussed. CONCLUSIONS: Although not a true sign, the finding of the elongated appearance of the midbrain in traumatic brain injury still holds significance as a predictor of mortality. Hence, this finding should alert neurosurgeons or intensivists to expedite the administration of suitable interventions in a salvageable patient.

Formulation of a Three-Tier Cisternal Grade as a Predictor of In-Hospital Outcome from a Prospective Study of Patients with Traumatic Intracranial Hematoma.

OBJECTIVE: Outcome prediction is of paramount importance in traumatic brain injury. Our objective of conducting this prospective study was to identify the predictors needed to formulate a prognostic score. METHODS: Clinical and radiologic characteristics of 100 patients with traumatic intracranial hematoma were analyzed. Key measurements were taken in the midbrain and pontine regions and the status of each of the 9 basal cisterns was noted, by giving a score of 1 if they were visible and 0 if not. All the predictors were analyzed for outcome. RESULTS: Total cisternal score was found to be an independent predictor of outcome. A grade was formulated by dividing the score into 3 levels. CONCLUSIONS: The model based on cisternal status described in the study is technically simple and conveys the information regarding the outcome to the treating neurosurgeon. Because the score obtained seems to have low interobserver variation, we believe that it can be a useful tool not only in recording data in case files and interphysician communication but also in research into traumatic brain injury.

Two Automated Techniques for Carotid Lumen Diameter Measurement: Regional versus Boundary Approaches.

The degree of stenosis in the carotid artery can be predicted using automated carotid lumen diameter (LD) measured from B-mode ultrasound images. Systolic velocity-based methods for measurement of LD are subjective. With the advancement of high resolution imaging, image-based methods have started to emerge. However, they require robust image analysis for accurate LD measurement. This paper presents two different algorithms for automated segmentation of the lumen borders in carotid ultrasound images. Both algorithms are modeled as a two stage process. Stage one consists of a global-based model using scale-space framework for the extraction of the region of interest. This stage is common to both algorithms. Stage two is modeled using a local-based strategy that extracts the lumen interfaces. At this stage, the algorithm-1 is modeled as a region-based strategy using a classification framework, whereas the algorithm-2 is modeled as a boundary-based approach that uses the level set framework. Two sets of databases (DB), Japan DB (JDB) (202 patients, 404 images) and Hong Kong DB (HKDB) (50 patients, 300 images) were used in this study. Two trained neuroradiologists performed manual LD tracings. The mean automated LD measured was 6.35 ± 0.95 mm for JDB and 6.20 ± 1.35 mm for HKDB. The precision-of-merit was: 97.4 % and 98.0 % w.r.t to two manual tracings for JDB and 99.7 % and 97.9 % w.r.t to two manual tracings for HKDB. Statistical tests such as ANOVA, Chi-Squared, T-test, and Mann-Whitney test were conducted to show the stability and reliability of the automated techniques.

Carotid inter-adventitial diameter is more strongly related to plaque score than lumen diameter: An automated tool for stroke analysis.

PURPOSE: To compare the strength of correlation between automatically measured carotid lumen diameter (LD) and interadventitial diameter (IAD) with plaque score (PS). METHODS: Retrospective study on a database of 404 common carotid artery B-mode sonographic images from 202 diabetic patients. LD and IAD were computed automatically using an advanced computerized edge detection method and compared with two distinct manual measurements. PS was computed by adding the maximal thickness in millimeters of plaques in segments taken from the internal carotid artery, bulb, and common carotid artery on both sides. RESULTS: The coefficient of correlation was 0.19 (p < 0.007) between LD and PS, and 0.25 (p < 0.0006) between IAD and PS. After excluding 10 outliers, coefficient of correlation was 0.25 (p < 0.0001) between LD and PS, and 0.38 (p < 0.0001) between IAD and PS. The precision of merit of automated versus the two manual measurements was 96.6% and 97.2% for LD, and 97.7% and 98.1%, for IAD, respectively. CONCLUSIONS: Our automated measurement system gave satisfying results in comparison with manual measurements. Carotid IAD was more strongly correlated to PS than carotid LD in this population sample of Japanese diabetic patients.

A Review on Carotid Ultrasound Atherosclerotic Tissue Characterization and Stroke Risk Stratification in Machine Learning Framework.

Cardiovascular diseases (including stroke and heart attack) are identified as the leading cause of death in today's world. However, very little is understood about the arterial mechanics of plaque buildup, arterial fibrous cap rupture, and the role of abnormalities of the vasa vasorum. Recently, ultrasonic echogenicity characteristics and morphological characterization of carotid plaque types have been shown to have clinical utility in classification of stroke risks. Furthermore, this characterization supports aggressive and intensive medical therapy as well as procedures, including endarterectomy and stenting. This is the first state-of-the-art review to provide a comprehensive understanding of the field of ultrasonic vascular morphology tissue characterization. This paper presents fundamental and advanced ultrasonic tissue characterization and feature extraction methods for analyzing plaque. Additionally, the paper shows how the risk stratification is achieved using machine learning paradigms. More advanced methods need to be developed which can segment the carotid artery walls into multiple regions such as the bulb region and areas both proximal and distal to the bulb. Furthermore, multimodality imaging is needed for validation of such advanced methods for stroke and cardiovascular risk stratification.