Face, Content, and Construct Validity of Brain Tumor Microsurgery Simulation Using a Human Placenta Model

2015 ◽  
Vol 12 (1) ◽  
pp. 61-67 ◽  
Author(s):  
Marcelo Magaldi Oliveira ◽  
Audrey Beatriz Araujo ◽  
Arthur Nicolato ◽  
Andre Prosdocimi ◽  
Joao Victor Godinho ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Construct Validity ◽  
Content Validity ◽  
Ex Vivo ◽  
Subjective Evaluation ◽  
Surgical Instruments ◽  
Surgical Performance ◽  
Human Brain Tumor ◽  
Microsurgical Techniques

Abstract BACKGROUND Brain tumors are complex 3-dimensional lesions. Their resection involves training and the use of the multiple microsurgical techniques available for removal. Simulation models, with haptic and visual realism, may be useful for improving the bimanual technical skills of neurosurgical residents and neurosurgeons, potentially decreasing surgical errors and thus improving patient outcomes. OBJECTIVE To describe and assess an ex vivo placental model for brain tumor microsurgery using a simulation tool in neurosurgical psychomotor teaching and assessment. METHODS Sixteen human placentas were used in this research project. Intravascular blood remnants were removed by continuous saline solution irrigation of the 2 placental arteries and placental vein. Brain tumors were simulated using silicone injections in the placental stroma. Eight neurosurgeons and 8 neurosurgical residents carried out the resection of simulated tumors using the same surgical instruments and bimanual microsurgical techniques used to perform human brain tumor operations. Face and content validity was assessed using a subjective evaluation based on a 5-point Likert scale. Construct validity was assessed by analyzing the surgical performance of the neurosurgeon and resident groups. RESULTS The placenta model simulated brain tumor surgical procedures with high fidelity. Results showed face and content validity. Construct validity was demonstrated by statistically different surgical performances among the evaluated groups. CONCLUSION Human placentas are useful haptic models to simulate brain tumor microsurgical removal. Results using this model demonstrate face, content, and construct validity.

Production of matrix metalloproteinases and tissue inhibitor of metalloproteinases-1 by human brain tumors

1994 ◽  
Vol 81 (1) ◽  
pp. 69-77 ◽  
Author(s):  
Takao Nakagawa ◽  
Toshihiko Kubota ◽  
Masanori Kabuto ◽  
Kazufumi Sato ◽  
Hirokazu Kawano ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Matrix Metalloproteinases ◽  
Brain Tumors ◽  
Human Brain ◽  
Tumor Cells ◽  
Tumor Invasion ◽  
Gelatinolytic Activity ◽  
Normal Brain ◽  
Tissue Inhibitor Of Metalloproteinases ◽  
Human Brain Tumor

✓ The role of matrix metalloproteinases (MMP's) and their inhibitor, tissue inhibitor of metalloproteinases-1 (TIMP-1), in human brain tumor invasion was investigated. Gelatinolytic activity was assayed via gelatin zymography, and four MMP's (MMP-1, MMP-2, MMP-3, and MMP-9) and TIMP-1 were immunolocalized in human brain tumors and in normal brain tissues using monoclonal antibodies. The tissue was surgically removed from 44 patients: glioblastoma (five cases), anaplastic astrocytoma (six cases), astrocytoma (four cases), metastatic tumor (six cases), neurinoma (10 cases), meningioma (10 cases), and normal brain tissue (three cases). Glioblastomas, anaplastic astrocytomas, and metastatic tumors showed high gelatinolytic activity and positive immunostaining for MMP's; TIMP-1 was also expressed in these tumors, but some tumor cells were negative for the antibody. Astrocytomas had low gelatinolytic activity and the tumor cells showed no immunoreactivity for MMP's and TIMP-1. Although neurinomas and meningiomas had only moderate proteinase activity and exhibited positive immunoreactivity for MMP-9, intense expression of TIMP-1 was simultaneously observed in these tumor cells. These findings suggest that MMP's play an important role in human brain tumor invasion, probably due to an imbalance between the production of MMP's and TIMP-1 by the tumor cells.

scholarly journals Hybrid Surgical Simulator: A Temporal Bone Simulator Validation Study of the Stryker Surgical Simulator (S3)

2020 ◽  
Vol 185 (11-12) ◽  
pp. e2026-e2031
Author(s):  
Charles Meyer ◽  
Francine Noda ◽  
Craig R Folsom
Keyword(s):  
Temporal Bone ◽  
Content Validity ◽  
Haptic Feedback ◽  
Surgical Simulation ◽  
Subjective Evaluation ◽  
Face Validity ◽  
Task Completion ◽  
Surgical Simulator ◽  
Surgical Performance ◽  
Training Tool

ABSTRACT Introduction The Stryker Surgical Simulator is a hybrid, temporal bone simulator that uses both tactile and haptic feedback combined with a computer interface. We sought to validate this simulator as an otolaryngology resident training tool for performing tympanomastoidectomy. Materials and Methods 15 residents and staff performed five basic cortical mastoidectomies. Staff surgeons comprised the “expert” cohort and resident surgeons comprised the “trainee” cohort. Subjective evaluation of the face validity and content validity was assessed via pre- and postquestionnaires. Objective evaluation of content validity was assessed through grading of each temporal bone dissection specimen, comparing time to task completion, and calculating the rate of injury to critical structures. Study approved by the Institutional Review Board (2013.0001). Results Post hoc questionnaires showed that both staff and residents subjectively rated the simulator favorably on face validity, content validity, and all global assessment categories, though there were no significant distinctions between groups (P > 0.05). The resident group had a significantly longer drilling time compared with the staff group throughout the series of tympanomastoidectomies (P = 0.008), and both groups showed a decrease in time to task completion with repetitive drilling. However, there were no significant differences in surgical performance as evaluated by a blinded senior neurotologist (P = 0.52). There were also no critical injuries recorded by the simulator in any of the 75 trials, preventing any evaluation on this measure. Conclusions Despite favorable subjective evaluations by both staff and residents, objective discrimination between experienced and novice participants was not achieved. This was likely in part due to inherent design flaws of the simulator. This emphasizes the potential shortcomings of surgical simulation models for highly technical procedures and points to the importance of intensive study and validation prior to incorporation of commercial training models into surgical training programs.

scholarly journals Automatic Human Brain Tumor Detection in MRI Image Using Template-Based K Means and Improved Fuzzy C Means Clustering Algorithm

2019 ◽  
Vol 3 (2) ◽  
pp. 27 ◽  
Author(s):  
Md Shahariar Alam ◽  
Md Mahbubur Rahman ◽  
Mohammad Amazad Hossain ◽  
Md Khairul Islam ◽  
Kazi Mowdud Ahmed ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Human Brain ◽  
Clustering Algorithm ◽  
Tumor Detection ◽  
Gray Level ◽  
Human Brain Tumor ◽  
Human Brain Tumors ◽  
Fuzzy C Means ◽  
Mri Image

In recent decades, human brain tumor detection has become one of the most challenging issues in medical science. In this paper, we propose a model that includes the template-based K means and improved fuzzy C means (TKFCM) algorithm for detecting human brain tumors in a magnetic resonance imaging (MRI) image. In this proposed algorithm, firstly, the template-based K-means algorithm is used to initialize segmentation significantly through the perfect selection of a template, based on gray-level intensity of image; secondly, the updated membership is determined by the distances from cluster centroid to cluster data points using the fuzzy C-means (FCM) algorithm while it contacts its best result, and finally, the improved FCM clustering algorithm is used for detecting tumor position by updating membership function that is obtained based on the different features of tumor image including Contrast, Energy, Dissimilarity, Homogeneity, Entropy, and Correlation. Simulation results show that the proposed algorithm achieves better detection of abnormal and normal tissues in the human brain under small detachment of gray-level intensity. In addition, this algorithm detects human brain tumors within a very short time—in seconds compared to minutes with other algorithms.

The distribution of nuclear DNA from human brain-tumor cells

1978 ◽  
Vol 49 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Takao Hoshino ◽  
Kazuhiro Nomura ◽  
Charles B. Wilson ◽  
Kathy D. Knebel ◽  
Joe W. Gray
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Human Brain ◽  
Dna Synthesis ◽  
Tumor Cells ◽  
Malignant Gliomas ◽  
Benign Tumors ◽  
Low Grade ◽  
Human Brain Tumor ◽  
Large Variability

✓ Flow cytometry (FCM) is a technique that measures the quantity of DNA contained in individual nuclei and records a frequency distribution of the DNA content per nucleus in the sampled cell population. Nuclei from a variety of human brain-tumor types were isolated by means of tissue grinding, purified by centrifugation through 40% sucrose (15 minutes at 4000 rpm), fixed with 10% formalin, stained with acriflavin-Feulgen, and analyzed by FCM. Profiles of DNA distribution in histologically benign tumors, such as meningiomas, pituitary adenomas, neuroblastomas, and low-grade astrocytomas, revealed a large diploid population (2C) with a few nuclei in DNA synthesis, as well as a small premitotic population (G2 cells) that contains a 4C DNA complement. In contrast, malignant gliomas, including glioblastomas, consist of more cells in DNA synthesis; these tumor cells show a highly variable distribution of ploidy consisting not only of diploid, and/or aneuploid, but also of triploid, tetraploid, and possibly octaploid populations. Also, a large variability between different regions of each tumor was always observed. In contrast, metastatic brain tumors, despite the fact that they contain a considerable number of cells undergoing DNA synthesis, demonstrate little variability within each individual tumor. The ability to rapidly characterize the cell populations of human brain tumors with FCM may enhance the effectiveness of their clinical management.

Plasminogen activator activity and molecular weight patterns in human brain tumors

1988 ◽  
Vol 68 (1) ◽  
pp. 73-79 ◽  
Author(s):  
Raymond Sawaya ◽  
Robert Highsmith
Keyword(s):  
Molecular Weight ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Human Brain ◽  
Plasminogen Activator ◽  
Malignant Tumors ◽  
Benign Tumors ◽  
Normal Brain ◽  
Human Brain Tumor ◽  
Content Type

✓ Fresh human brain-tumor samples were assayed for their plasminogen activator (PA) content. Specific molecular weight patterns were identified for each of five common brain tumors and for normal brain, suggesting a cell-specific origin of the various PA forms. Malignant tumors contained higher PA activity and a larger number of molecular weight patterns than benign tumors, with the exception of acoustic neurinomas. Irradiated tumors contained lower PA activity than nonirradiated tumors. Finally, a slight but definite correlation between brain edema and PA activity was detected. The future role of brain-tumor PA's for diagnostic and therapeutic purposes is discussed.

Permeability of human brain tumor to 99mTc-glucoheptonate and 99mTc-albumin

1986 ◽  
Vol 65 (2) ◽  
pp. 194-198 ◽  
Author(s):  
Edward A. Neuwelt ◽  
H. David Specht ◽  
Suellen A. Hill
Keyword(s):  
Molecular Weight ◽  
Monoclonal Antibody ◽  
Brain Tumor ◽  
Brain Tumors ◽  
High Molecular Weight ◽  
Antibody Fragment ◽  
Lipid Solubility ◽  
Human Brain Tumor ◽  
Malignant Brain Tumors ◽  
Iodinated Contrast

✓ The variable penetration of chemotherapeutic drugs into brain and tumor is more dependent upon lipid solubility than upon size. In contrast, the molecular weight of virus- and tumor-specific monoclonal antibodies appears to limit uptake. The authors have studied eight patients with malignant brain tumors in order to compare tumor uptake of an iodinated contrast agent evaluated by computerized tomography scanning with uptake of the low and high molecular weight imaging agents technetium-99m (99mTc)-glucoheptonate and 99mTc-albumin, respectively, measured by radionuclide brain scanning. The agent 99mTc-labeled albumin was chosen for evaluation because its molecular weight (68,000) is similar to that of the most clinically promising monoclonal antibody fragment, the immunoglobulin (Ig) G Fab monomeric fragment. The radionuclide brain scans in the eight patients showed highly variable permeability of brain tumor to these markers, with uptake of the high molecular weight marker in the tumor being much less than that of the low molecular weight radionuclide. A clinical implication of these studies is that the success of monoclonal antibody therapy in the treatment of malignant brain tumors may require techniques to increase permeability of the blood-brain barrier and blood-tumor barrier to protein.

Prostaglandin E2 levels in human brain tumor tissues and arachidonic acid levels in the plasma membrane of human brain tumors

1998 ◽  
Vol 132 (1-2) ◽  
pp. 17-21 ◽  
Author(s):  
E Kökoğlu ◽  
Y Tüter ◽  
K.S Sandıkçı ◽  
Z Yazıcı ◽  
E.Z Ulakoğlu ◽  
...  
Keyword(s):  
Arachidonic Acid ◽  
Plasma Membrane ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Human Brain ◽  
Prostaglandin E2 ◽  
Human Brain Tumor ◽  
Human Brain Tumors ◽  
Tumor Tissues

scholarly journals Immediate Label-Free Ex Vivo Evaluation of Human Brain Tumor Biopsies With Confocal Reflectance Microscopy

2017 ◽  
Vol 76 (12) ◽  
pp. 1008-1022 ◽  
Author(s):  
Jennifer M. Eschbacher ◽  
Joseph F. Georges ◽  
Evgenii Belykh ◽  
Mohammedhassan Izady Yazdanabadi ◽  
Nikolay L. Martirosyan ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Human Brain ◽  
Ex Vivo ◽  
Label Free ◽  
Human Brain Tumor ◽  
Confocal Reflectance Microscopy ◽  
Tumor Biopsies ◽  
Reflectance Microscopy

Recent advancements in Fuzzy C-means based techniques for brain MRI Segmentation

2021 ◽  
Vol 16 ◽  
Author(s):  
Ghazanfar Latif ◽  
Jaafar Alghazo ◽  
Fadi N. Sibai ◽  
D.N.F. Awang Iskandar ◽  
Adil H. Khan
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Brain Mri ◽  
Tumor Segmentation ◽  
Brain Anatomy ◽  
Mri Segmentation ◽  
Brain Tumor Segmentation ◽  
Brain Images ◽  
Low Contrast ◽  
Fuzzy C Means

Background: Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques. Objective: In this paper, a comprehensive review is presented on all thirteen variations of FCM segmentation techniques. In the review process, the concentration is on the use of FCM segmentation techniques for brain tumors. Brain tumor segmentation is a vital step in the process of automatically diagnosing brain tumors. Unlike segmentation of other types of images, brain tumor segmentation is a very challenging task due to the variations in brain anatomy. The low contrast of brain images further complicates this process. Early diagnosis of brain tumors is indeed beneficial to patients, doctors, and medical providers. Results: FCM segmentation works on images obtained from magnetic resonance imaging (MRI) scanners, requiring minor modifications to hospital operations to early diagnose tumors as most, if not all, hospitals rely on MRI machines for brain imaging. In this paper, we critically review and summarize FCM based techniques for brain MRI segmentation.

Brain Tumor Detection via Asymmetry Quantification across Mid Sagittal Plane

2020 ◽  
Vol 13 ◽  
Author(s):  
Shoaib Amin Banday ◽  
Mohammad Khalid Pandit
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Sagittal Plane ◽  
Early Stage ◽  
Imaging Techniques ◽  
Complex Structure ◽  
Magnetic Resonance Images ◽  
Absolute Difference ◽  
Brain Hemispheres ◽  
The Brain

Introduction: Brain tumor is among the major causes of morbidity and mortality rates worldwide. According to National Brain Tumor Foundation (NBTS), the death rate has nearly increased by as much as 300% over last couple of decades. Tumors can be categorized as benign (non-cancerous) and malignant (cancerous). The type of the brain tumor significantly depends on various factors like the site of its occurrence, its shape, the age of the subject etc. On the other hand, Computer Aided Detection (CAD) has been improving significantly in recent times. The concept, design and implementation of these systems ascend from fairly simple ones to computationally intense ones. For efficient and effective diagnosis and treatment plans in brain tumor studies, it is imperative that an abnormality is detected at an early stage as it provides a little more time for medical professionals to respond. The early detection of diseases has predominantly been possible because of medical imaging techniques developed from past many decades like CT, MRI, PET, SPECT, FMRI etc. The detection of brain tumors however, has always been a challenging task because of the complex structure of the brain, diverse tumor sizes and locations in the brain. Method: This paper proposes an algorithm that can detect the brain tumors in the presence of the Radio-Frequency (RF) inhomoginiety. The algorithm utilizes the Mid Sagittal Plane as a landmark point across which the asymmetry between the two brain hemispheres is estimated using various intensity and texture based parameters. Result: The results show the efficacy of the proposed method for the detection of the brain tumors with an acceptable detection rate. Conclusion: In this paper, we have calculated three textural features from the two hemispheres of the brain viz: Contrast (CON), Entropy (ENT) and Homogeneity (HOM) and three parameters viz: Root Mean Square Error (RMSE), Correlation Co-efficient (CC), and Integral of Absolute Difference (IAD) from the intensity distribution profiles of the two brain hemispheres to predict any presence of the pathology. First a Mid Sagittal Plane (MSP) is obtained on the Magnetic Resonance Images that virtually divides brain into two bilaterally symmetric hemispheres. The block wise texture asymmetry is estimated for these hemispheres using the above 6 parameters.

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