Automated Microsurgical Tool Segmentation and Characterization in Intra-Operative Neurosurgical Videos.

Checklist based routine evaluation of surgical skills in any medical school demands quality time and effort from the supervising expert and is highly influenced by assessor bias. Alternatively, automated video based surgical skill assessment is a simple and viable method to analyse surgical dexterity offline without the need for acute presence of an expert surgeon throughout the surgery. In this paper, a novel approach and results for the automated segmentation of microsurgical instruments from the real-world neurosurgical video dataset was presented. The proposed tool segmentation model showcased mean average precision of 96.7% in detecting, and localizing five surgical instruments from the real-world neurosurgical videos. Accurate detection and characterization of motion features of the microsurgical tool from the novel annotated neurosurgical video dataset forms the key step towards automated surgical skill evaluation. Clinical Relevance- Tool segmentation, localization, and characterization in neurosurgical video, has several applications including assessing surgeons skills, training novice surgeons, understanding critical operating procedures post surgery, characterizing any critical anatomical response to the tool that leads to the success or failure of the surgery, and building models for conducting autonomous robotic surgery. Semantic segmentation, and characterization of the microsurgical tools forms the basis of the modern neurosurgery.

A flexible implantable microelectrode array for recording electrocorticography signals from rodents.

Electrocorticography signals, the intracranial recording of electrical signatures of the brain, are recorded by non-penetrating planar electrode arrays placed on the cortical surface. Flexible electrode arrays minimize the tissue damage upon implantation. This work shows the design and development of a 32-channel flexible microelectrode array to record electrocorticography signals from the rat's brain. The array was fabricated on a biocompatible flexible polyimide substrate. A titanium/gold layer was patterned as electrodes, and a thin polyimide layer was used for insulation. The fabricated microelectrode array was mounted on the exposed somatosensory cortex of the right hemisphere of a rat after craniotomy and incision of the dura. The signals were recorded using OpenBCI Cyton Daisy Biosensing Boards. The array faithfully recorded the baseline electrocorticography signals, the induced epileptic activities after applying a convulsant, and the recovered baseline signals after applying an antiepileptic drug. The signals recorded by such fabricated microelectrode array from anesthetized rats demonstrate its potential to monitor electrical signatures corresponding to epilepsy. Finally, the time-frequency analyses highlight the difference in spatiotemporal features of baseline and evoked epileptic discharges.

Electromechanical Characterization of Human Brain Tissues: A Potential Biomarker for Tumor Delineation.

OBJECTIVE: Accurate identification of surgical margins in brain tumors is of significant prognostic importance. Despite the availability of methods such as 5-ALA and image guidance, recognizing tumor boundary is highly subjective, dependant on recognizing subtle changes in tissue characteristics including texture and color to aid distinction. METHOD: Design and development of a semi-automated system integrated with MEMS-based electromechanical sensors to enable an objective and reliable method of distinguishing tumors from normal brain tissue. Simultaneous electrical impedance and viscoelastic characterization of three types of freshly excised gliomas (glioblastoma (GBM), astrocytoma (AST), and oligodendroglioma (OLI)) (N = 8 each) and seventeen different normal brain regions (N = 6 each) obtained postmortem. RESULTS: The electrical impedance of gliomas (462±56Ω) was found to be significantly lower than corresponding normal (1267±515Ω) regions at 100kHz (p = 7.46e-11). The difference in the impedance between individual tumor types and corresponding normal regions was also statistically significant (p = 1e-8), suggesting accurate tumor delineation. There were distinct differences in the viscoelastic relaxation responses of high-grade and low-grade gliomas. White matter regions demonstrated higher impedance and faster stress relaxation compared to grey matter regions as a characteristic of their structural composition. CONCLUSION: We demonstrate that simultaneous electromechanical characterization of brain tumors and normal brain tissues can be an effective biomarker for tumor delineation, grading, and studying heterogeneity between the brain regions. SIGNIFICANCE: The observations suggest the potential use of the technology in a clinical setting to achieve gross total resection and improve treatment outcomes by helping surgeons perform real-time risk evaluation during surgery.

Microsurgical Tool Detection and Characterization in Intra-operative Neurosurgical Videos.

Brain surgery is complex and has evolved as a separate surgical specialty. Surgical procedures on the brain are performed using dedicated micro-instruments which are designed specifically for the requirements of operating with finesse in a confined space. The usage of these microsurgical tools in an operating environment defines the surgical skill of a surgeon. Video recordings of micro-surgical procedures are a rich source of information to develop automated surgical assessment tools that can offer continuous feedback for surgeons to improve their skills, effectively increase the outcome of the surgery, and make a positive impact on their patients. This work presents a novel deep learning system based on the Yolov5 algorithm to automatically detect, localize and characterize microsurgical tools from recorded intra-operative neurosurgical videos. The tool detection achieves a high 93.2% mean average precision. The detected tools are then characterized by their on-off time, motion trajectory and usage time. Tool characterization from neurosurgical videos offers useful insight into the surgical methods employed by a surgeon and can aid in their improvement. Additionally, a new dataset of annotated neurosurgical videos is used to develop the robust model and is made available for the research community.Clinical relevance- Tool detection and characterization in neurosurgery has several online and offline applications including skill assessment and outcome of the surgery. The development of automated tool characterization systems for intra-operative neurosurgery is expected to not only improve the surgical skills of the surgeon, but also leverage in training the neurosurgical workforce. Additionally, dedicated neurosurgical video based datasets will, in general, aid the research community to explore more automation in this field.

Psychometric validation of a knowledge questionnaire on micronutrients among adolescents and its relationship to micronutrient status of 15-19-year-old adolescent boys, Hyderabad, India.

OBJECTIVE: To develop a psychometrically valid questionnaire for testing knowledge on micronutrients and to assess the relationship between knowledge and biomarkers of micronutrient status among adolescents. DESIGN: Cross-sectional, institution-based, validity and reliability study. SETTING: Seven higher secondary schools were covered in the limits of Greater Hyderabad Municipal Corporation, Hyderabad, India. SUBJECTS: Students aged 15-19 years, n 92 for the pre-test, n 108 for test-retest and n 109 for studying the relationship between knowledge and biomarkers of Fe, retinol, ascorbic acid, α-tocopherol, folic acid and vitamin B12 status. RESULTS: From an item pool of 106, thirty-one items were selected based on content validity. Statistical tools to obtain a valid and reliable questionnaire among adolescent boys and girls resulted in eighteen items with a difficulty index of 0·11-0·86, discrimination index of 0·20-0·72 and validity index (point bi-serial correlation) of 0·10-0·62. Reliability as measured by Cronbach's α was 0·71 and the intra-class correlation coefficient was 0·80. A Bland-Altman plot showed good agreement between test and retest scores. The mean response score to the eighteen-item questionnaire was 5·2 (sd 2·68). The mean values of serum retinol were significantly different (P = 0·022) between groups below (24·8 (sd 6·64) µg/dl) and above (28·0 (sd 7·67) µg/dl) the 50th percentile of knowledge score. The relationship persisted after controlling for economic status as a covariate using analysis of covariance (P = 0·018). Other micronutrients did not show any significant relationship. CONCLUSIONS: A valid and reliable eighteen-item knowledge questionnaire was constructed and found to have a significant positive relationship with plasma retinol status alone.

Prevalence of vitamin A deficiency and its determinants among the rural pre-school children of Madhya Pradesh, India.

BACKGROUND: Vitamin A deficiency (VAD) continues to be a major public health nutritional problem in India, even though the National Vitamin A Prophylaxis Programme has been in operation for more than three decades. AIM: To assess the prevalence of vitamin A deficiency among rural pre-school children. SUBJECTS AND METHODS: A community-based cross-sectional study was carried out in rural Madhya Pradesh. A total of 8777 pre-school children were clinically examined for VAD and blood vitamin A levels were estimated in a sub-sample by dried blood spot method. RESULTS: Prevalence of night blindness and Bitot's spot, an objective sign of VAD, was 0.8% and 1.4%, respectively, and prevalence increased significantly (p < 0.001) with age. The proportion of children with blood vitamin A deficiency ( < 20 µg/dL) was 88% (95% CI: 84.8-91.2).The prevalence of Bitot's spot was significantly (p < 0.001) higher among children of lower socio-economic communities, 3-5-year age group and those of illiterate mothers. CONCLUSIONS: VAD is a major public health problem among rural children of Madhya Pradesh. Children of 3-5 years and those belonging to lower socio-economic communities are at high risk of VAD. Therefore, appropriate intervention measures are to be initiated to improve the vitamin A status of children.