scholarly journals 3D volume reconstruction of brain tissues using nonlinear filters, k-means clustering, and Bland-Altman analysis

2021 ◽  
Vol 44 (1) ◽  
pp. 75-87
Author(s):  
Lenuța Pană ◽  
Simona Moldoveanu ◽  
Luminița Moraru
Keyword(s):  
3D Reconstruction ◽  
Brain Tissue ◽  
Anisotropic Diffusion ◽  
Nonlinear Filters ◽  
Altman Analysis ◽  
Volume Reconstruction ◽  
Bland Altman Analysis ◽  
True Value ◽  
3D Volume ◽  
Brain Tissues

This paper aims to provide a sound estimation of the true value and proportion of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) of the brain DTI images for a proper 3D volume reconstruction. During the pre-processing stage, two nonlinear filters are operated, i.e. bilateral and anisotropic diffusion. The segmentation of each brain tissue is performed using the k-means clustering algorithm. To minimize filters bias and for obtaining the best reproducible results, a statistical analysis has been performed. Thus, the skewness and kurtosis statistics features were computed for each segmented brain tissue and filter. The fuzzy k-means method allows for clustering analysis and the Bland-Altman analysis investigates the agreement between two filtering techniques of the same statistics feature and brain tissue. Then the 3D reconstruction method is presented using ImageJ and the image stacks for raw and processed data. We conclude that anisotropic diffusion filter offers the best results and 3D reconstruction of brain tissues is feasible.

Reply: Bland-Altman analysis for pupillometer comparison

2010 ◽  
Vol 36 (10) ◽  
pp. 1803-1804
Author(s):  
Magdalena Scheffel ◽  
Christoph Kuehne ◽  
Thomas Kohnen
Keyword(s):  
Altman Analysis ◽  
Bland Altman Analysis

scholarly journals Population-based input function for TSPO quantification and kinetic modeling with [11C]-DPA-713

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mercy I. Akerele ◽  
Sara A. Zein ◽  
Sneha Pandya ◽  
Anastasia Nikolopoulou ◽  
Susan A. Gauthier ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Kinetic Analysis ◽  
Kinetic Modeling ◽  
Input Function ◽  
Brain Regions ◽  
Population Based ◽  
Patient Specific ◽  
Systematic Bias ◽  
Altman Analysis ◽  
Bland Altman Analysis

Abstract Introduction Quantitative positron emission tomography (PET) studies of neurodegenerative diseases typically require the measurement of arterial input functions (AIF), an invasive and risky procedure. This study aims to assess the reproducibility of [11C]DPA-713 PET kinetic analysis using population-based input function (PBIF). The final goal is to possibly eliminate the need for AIF. Materials and methods Eighteen subjects including six healthy volunteers (HV) and twelve Parkinson disease (PD) subjects from two [11C]-DPA-713 PET studies were included. Each subject underwent 90 min of dynamic PET imaging. Five healthy volunteers underwent a test-retest scan within the same day to assess the repeatability of the kinetic parameters. Kinetic modeling was carried out using the Logan total volume of distribution (VT) model. For each data set, kinetic analysis was performed using a patient-specific AIF (PSAIF, ground-truth standard) and then repeated using the PBIF. PBIF was generated using the leave-one-out method for each subject from the remaining 17 subjects and after normalizing the PSAIFs by 3 techniques: (a) Weightsubject×DoseInjected, (b) area under AIF curve (AUC), and (c) Weightsubject×AUC. The variability in the VT measured with PSAIF, in the test-retest study, was determined for selected brain regions (white matter, cerebellum, thalamus, caudate, putamen, pallidum, brainstem, hippocampus, and amygdala) using the Bland-Altman analysis and for each of the 3 normalization techniques. Similarly, for all subjects, the variabilities due to the use of PBIF were assessed. Results Bland-Altman analysis showed systematic bias between test and retest studies. The corresponding mean bias and 95% limits of agreement (LOA) for the studied brain regions were 30% and ± 70%. Comparing PBIF- and PSAIF-based VT estimate for all subjects and all brain regions, a significant difference between the results generated by the three normalization techniques existed for all brain structures except for the brainstem (P-value = 0.095). The mean % difference and 95% LOA is −10% and ±45% for Weightsubject×DoseInjected; +8% and ±50% for AUC; and +2% and ± 38% for Weightsubject×AUC. In all cases, normalizing by Weightsubject×AUC yielded the smallest % bias and variability (% bias = ±2%; LOA = ±38% for all brain regions). Estimating the reproducibility of PBIF-kinetics to PSAIF based on disease groups (HV/PD) and genotype (MAB/HAB), the average VT values for all regions obtained from PBIF is insignificantly higher than PSAIF (%difference = 4.53%, P-value = 0.73 for HAB; and %difference = 0.73%, P-value = 0.96 for MAB). PBIF also tends to overestimate the difference between PD and HV for HAB (% difference = 32.33% versus 13.28%) and underestimate it in MAB (%difference = 6.84% versus 20.92%). Conclusions PSAIF kinetic results are reproducible with PBIF, with variability in VT within that obtained for the test-retest studies. Therefore, VT assessed using PBIF-based kinetic modeling is clinically feasible and can be an alternative to PSAIF.

scholarly journals Evaluation of automated microvascular flow analysis software AVA 4: a validation study

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Christian S. Guay ◽  
Mariam Khebir ◽  
T. Shiva Shahiri ◽  
Ariana Szilagyi ◽  
Erin Elizabeth Cole ◽  
...  
Keyword(s):  
General Anesthesia ◽  
Validation Study ◽  
Validation Studies ◽  
Gold Standard ◽  
Flow Analysis ◽  
Automated Analysis ◽  
Altman Analysis ◽  
Analysis Software ◽  
Bland Altman Analysis ◽  
Microvascular Flow

Abstract Background Real-time automated analysis of videos of the microvasculature is an essential step in the development of research protocols and clinical algorithms that incorporate point-of-care microvascular analysis. In response to the call for validation studies of available automated analysis software by the European Society of Intensive Care Medicine, and building on a previous validation study in sheep, we report the first human validation study of AVA 4. Methods Two retrospective perioperative datasets of human microcirculation videos (P1 and P2) and one prospective healthy volunteer dataset (V1) were used in this validation study. Video quality was assessed using the modified Microcirculation Image Quality Selection (MIQS) score. Videos were initially analyzed with (1) AVA software 3.2 by two experienced investigators using the gold standard semi-automated method, followed by an analysis with (2) AVA automated software 4.1. Microvascular variables measured were perfused vessel density (PVD), total vessel density (TVD), and proportion of perfused vessels (PPV). Bland–Altman analysis and intraclass correlation coefficients (ICC) were used to measure agreement between the two methods. Each method’s ability to discriminate between microcirculatory states before and after induction of general anesthesia was assessed using paired t-tests. Results Fifty-two videos from P1, 128 videos from P2 and 26 videos from V1 met inclusion criteria for analysis. Correlational analysis and Bland–Altman analysis revealed poor agreement and no correlation between AVA 4.1 and AVA 3.2. Following the induction of general anesthesia, TVD and PVD measured using AVA 3.2 increased significantly for P1 (p < 0.05) and P2 (p < 0.05). However, these changes could not be replicated with the data generated by AVA 4.1. Conclusions AVA 4.1 is not a suitable tool for research or clinical purposes at this time. Future validation studies of automated microvascular flow analysis software should aim to measure the new software’s agreement with the gold standard, its ability to discriminate between clinical states and the quality thresholds at which its performance becomes unacceptable.

scholarly journals Comparison of IOP Measurement by Goldmann Applanation Tonometer, ICare Rebound Tonometer, and Tono-Pen in Keratoconus Patients after MyoRing Implantation

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Mahmoud Rateb ◽  
Mahmoud Abdel-Radi ◽  
Zeiad Eldaly ◽  
Mohamed Nagy Elmohamady ◽  
Asaad Noor El Din
Keyword(s):  
Central Corneal Thickness ◽  
Pearson Correlation ◽  
Corneal Thickness ◽  
Altman Analysis ◽  
Bland Altman Analysis ◽  
Rebound Tonometer ◽  
Goldmann Applanation Tonometer ◽  
Significant Difference ◽  
Applanation Tonometer ◽  
Icare Rebound Tonometer

Purpose. To evaluate the different IOP readings by Goldmann applanation tonometer (GAT), ICare rebound tonometer, and Tono-Pen in keratoconus patients after MyoRing implantation. To assess the influence of central corneal thickness (CCT) and thinnest corneal location (TCL) on IOP measurements by different tonometers. Setting. Prospective observational study was conducted in two private centers in Egypt from February 2015 to November 2016. Methods. Seventeen eyes of 10 patients suffering from keratoconus and who underwent MyoRing implantation were recruited. All subjects underwent GAT, ICare, and Tono-Pen IOP measurements in random order. Central corneal thickness and thinnest corneal location were assessed by Pentacam. Difference in mean in IOP readings was assessed by T-test. Correlation between each pair of devices was evaluated by Pearson correlation coefficient. The Bland–Altman analysis was used to assess intertonometer agreement. Results. Seventeen eyes (10 patients) were evaluated. The mean IOP reading was 13.9 ± 3.68, 12.41 ± 2.87, and 14.29 ± 1.31 mmHg in GAT, ICare, and Tono-Pen group, respectively. There was a significant difference between IOP readings by GAT/ICare and Tono-Pen/ICare (p value: 0.032 and 0.002, respectively) with no significant difference between GAT/Tono-Pen (p value: 0.554). Mean difference in IOP measurements between GAT/ICare was 1.49 ± 2.61 mmHg, Tono-Pen/ICare was 1.89 ± 2.15 mmHg, and GAT/Tono-Pen was −0.39 ± 2.59 mmHg. There was no significant correlation between the difference in IOP readings among any pair of devices and CCC or TCL. The Bland–Altman analysis showed a reasonable agreement between any pair of tonometers.

3D RECONSTRUCTION OF BREAST CANCER FROM MAMMOGRAMS USING VOLUME RENDERING TECHNIQUES

2015 ◽  
Vol 75 (2) ◽  
Author(s):  
Ho Wei Yong ◽  
Abdullah Bade ◽  
Rajesh Kumar Muniandy
Keyword(s):  
Breast Cancer ◽  
3D Reconstruction ◽  
Computational Cost ◽  
Reconstruction Method ◽  
Cancer Model ◽  
Volume Reconstruction ◽  
The Past ◽  
Breast Cancer Model ◽  
Reconstruction Software ◽  
To Come

Over the past thirty years, a number of researchers have investigated on 3D organ reconstruction from medical images and there are a few 3D reconstruction software available on the market. However, not many researcheshave focused on3D reconstruction of breast cancer’s tumours. Due to the method complexity, most 3D breast cancer’s tumours reconstruction were done based on MRI slices dataeven though mammogram is the current clinical practice for breast cancer screening. Therefore, this research will investigate the process of creating a method that will be able to reconstruct 3D breast cancer’s tumours from mammograms effectively.  Several steps were proposed for this research which includes data acquisition, volume reconstruction, andvolume rendering. The expected output from this research is the 3D breast cancer’s tumours model that is generated from correctly registered mammograms. The main purpose of this research is to come up with a 3D reconstruction method that can produce good breast cancer model from mammograms while using minimal computational cost.

Performance of Automated Telemetry in Diagnosing QT Prolongation in Critically Ill Patients

2021 ◽  
Vol 30 (6) ◽  
pp. 466-470
Author(s):  
Enrique Calvo-Ayala ◽  
Vince Procopio ◽  
Hayk Papukhyan ◽  
Girish B. Nair
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Demographic Data ◽  
Area Under The Curve ◽  
Qt Prolongation ◽  
Altman Analysis ◽  
Poor Agreement ◽  
Bland Altman Analysis ◽  
Prolonged Qt ◽  
Definition Of

Background QT prolongation increases the risk of ventricular arrhythmia and is common among critically ill patients. The gold standard for QT measurement is electrocardiography. Automated measurement of corrected QT (QTc) by cardiac telemetry has been developed, but this method has not been compared with electrocardiography in critically ill patients. Objective To compare the diagnostic performance of QTc values obtained with cardiac telemetry versus electrocardiography. Methods This prospective observational study included patients admitted to intensive care who had an electrocardiogram ordered simultaneously with cardiac telemetry. Demographic data and QTc determined by electrocardiography and telemetry were recorded. Bland-Altman analysis was done, and correlation coefficient and receiver operating characteristic (ROC) coefficient were calculated. Results Fifty-one data points were obtained from 43 patients (65% men). Bland-Altman analysis revealed poor agreement between telemetry and electrocardiography and evidence of fixed and proportional bias. Area under the ROC curve for QTc determined by telemetry was 0.9 (P &lt; .001) for a definition of prolonged QT as QTc ≥ 450 milliseconds in electrocardiography (sensitivity, 88.89%; specificity, 83.33%; cutoff of 464 milliseconds used). Correlation between the 2 methods was only moderate (r = 0.6, P &lt; .001). Conclusions QTc determination by telemetry has poor agreement and moderate correlation with electrocardiography. However, telemetry has an acceptable area under the curve in ROC analysis with tolerable sensitivity and specificity depending on the cutoff used to define prolonged QT. Cardiac telemetry should be used with caution in critically ill patients.

scholarly journals Evidence for the use of the Alere Afinion™ AS100 for measuring the levels of C-reactive protein in an elderly South African population

2020 ◽  
pp. 71-76
Author(s):  
I Mpofana ◽  
M Nyirenda ◽  
N Abbai
Keyword(s):  
Linear Regression Analysis ◽  
Reference Method ◽  
Altman Analysis ◽  
Concordance Correlation ◽  
Excellent Correlation ◽  
C Reactive Protein ◽  
Serum Samples ◽  
Cvd Risk ◽  
Bland Altman Analysis ◽  
Reactive Protein

Introduction: This study evaluated the performance of the Alere Afinion™ AS100 analyser for the measurement of C-reactive protein (CRP) levels in a population of older adults from South Africa. Methods: This study was a sub-study of the Sexual Health, HIV infection and comorbidity with non-communicable diseases among Older Persons (SHIOP) study. The median age of SHIOP participants was 61 years (interquartile range 12). Serum samples collected through SHIOP were used to measure CRP levels on the Alere Afinion™ AS100 (Point-of-care) and ABX Pentra 400 (reference method), respectively. Bland–Altman analysis and Lin’s concordance correlation coefficients were used to assess the agreement between the two analysers. Results: A total of 183 serum samples were tested in the study. The Alere Afinion™ AS100 median values for CRP were 9.5 mg/L and 11.5 mg/L in women and men respectively (p = 0.275). The ABX Pentra 400 median levels were lower with 5.6 mg/L and 3.6 mg/L for women and men (p = 0.027), respectively. Bland–Altman analysis and linear regression analysis showed an excellent correlation between the Pentra and Afinion analysers, with a Lin’s concordance correlation coefficient of 0.971. The Alere Afinion™ AS100 was able to correctly classify > 90% (165/183) of the CRP results when compared to the ABX Pentra 400. Conclusion: This study showed that the Alere Afinion™ AS100 had an excellent correlation with a standard laboratory method. However, the Afinion™ AS100 did not correlate well at elevated CRP levels. This may not be clinically significant since the cut-points for CVD risk are at much lower levels.

Sign in / Sign up

Export Citation Format

Share Document