scholarly journals Test–Retest Reproducibility Analysis of Bone Mineral Densitometry Radiomics Features

2020 ◽  
Author(s):  
Younes Qasempour ◽  
Mohammad Rashid Akhash ◽  
Isaac Shiri ◽  
Ghasem Hajianfar ◽  
Neda Abdalvand ◽  
...  
Keyword(s):  
Bone Mineral ◽  
Biomarker Discovery ◽  
Research Work ◽  
Critical Issue ◽  
Imaging Biomarker ◽  
Imaging Biomarkers ◽  
First Line ◽  
Intra Class Correlation ◽  
Bone Mineral Densitometry ◽  
Intra Class Correlation Coefficient

Abstract Background Radiomics features reproducibility assessment is a critical issue in imaging biomarker development era. In the present study, we aimed to assess test–retest reproducibility analysis of bone mineral densitometry (BMD) image radiomics features. Methods In this prospective research work, eighteen patients were included and were subjected to DXA BMD scans acquired within 10 min of each other under an approved protocol. Seven regions of interest (ROIs) including four lumbar spine regions (L1-L4) and three hip regions (trochanteric, inter trochanteric and neck) in both test and re-test images were segmented and 107 radiomics features from seven different feature sets were extracted. Intra-class correlation coefficient (ICC) were initially used to estimate radiomics features reproducibility. Results We showed that there is no radiomics feature with 90% < ICC < 100% in all ROIs, but there are three feature including Strength (from NGTDM feature set), SALGLE (Small Area Low Gray Level Emphasis) (from GLSZM feature set) and Busyness (from NGTDM feature set) with ICC < 70% in all eight ROIs. Shape features has features with ICC < 70%. Conclusion Our study on test–retest reproducibility analysis of bone mineral densitometry radiomics features shows radiomics features have several variations against changes of time of image acquisition. The reproducible features may be used as imaging biomarkers in the field of clinical densitometry. The results of this study may be repeated by more radiomics features and more BMD scanners as first line for bone mineral biomarker discovery.

scholarly journals The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics

2021 ◽  
Vol 7 (8) ◽  
pp. 124
Author(s):  
Kostas Marias
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Medical Image ◽  
Biomarker Discovery ◽  
Medical Image Processing ◽  
Machine Learning Techniques ◽  
Imaging Biomarker ◽  
Imaging Biomarkers ◽  
Precision Oncology

The role of medical image computing in oncology is growing stronger, not least due to the unprecedented advancement of computational AI techniques, providing a technological bridge between radiology and oncology, which could significantly accelerate the advancement of precision medicine throughout the cancer care continuum. Medical image processing has been an active field of research for more than three decades, focusing initially on traditional image analysis tasks such as registration segmentation, fusion, and contrast optimization. However, with the advancement of model-based medical image processing, the field of imaging biomarker discovery has focused on transforming functional imaging data into meaningful biomarkers that are able to provide insight into a tumor’s pathophysiology. More recently, the advancement of high-performance computing, in conjunction with the availability of large medical imaging datasets, has enabled the deployment of sophisticated machine learning techniques in the context of radiomics and deep learning modeling. This paper reviews and discusses the evolving role of image analysis and processing through the lens of the abovementioned developments, which hold promise for accelerating precision oncology, in the sense of improved diagnosis, prognosis, and treatment planning of cancer.

The reporting of reproducibility of cardiac imaging biomarkers

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
S Sangha ◽  
A Gupta ◽  
K Negishi ◽  
F Pathan
Keyword(s):  
Total Population ◽  
Case Reports ◽  
Meta Analysis ◽  
Cardiovascular Imaging ◽  
Imaging Biomarkers ◽  
Original Research ◽  
Altman Analysis ◽  
Intra Class Correlation ◽  
Bland Altman Analysis ◽  
Intra Class Correlation Coefficient

Abstract Introduction There is inconsistency in the reporting of reproducibility of imaging biomarkers in published literature. Purpose To assess the reporting of reproducibility of imaging biomarkers described in original articles across the top 3 multi-modality cardiovascular imaging journals. Methods We reviewed all published articles in 2018 in the 3 leading cardiovascular imaging journals: JACC cardiovascular Imaging (A), Circulation. Cardiovascular Imaging (B), and EHJ Cardiovascular Imaging (C). Articles were excluded if they were not original research or reproducibility reporting was not required: case reports, editorials, research supports, meta- analysis, reviews, miscellaneous. The remaining articles were assessed for the following reproducibility reporting parameters: 1) Discuss reproducibility; 2) Assess reproducibility in current study; 3) Reproducibility tools used: Intra-class correlation coefficient (ICC), coefficient of variance (COV), Bland Altman analysis (BA), etc and 5) Proportion of total population used in reproducibility analysis Results Among 951 articles published (Journal A/B/C 521/ 171/ 259), 692 were excluded due to above reasons. 259 articles were assessed for reproducibility data (Figure 1a). 122 of the 259 (47%) articles discussed reproducibility, including 26/122 (21%) referring to previous reproducibility data. Remaining 96/122 (79%) articles demonstrated reproducibility in the current manuscript- there was no difference in the frequency of articles discussing reproducibility across three journals (A 35/85 (41%); B 25/52 (48%); C 62/122 (51%), p=0.39). Modality differences between reporting of reproducibility were as follows: (Echo 66/122 (54%); CT 14/38 (37%); CMR 27/55 (49%); Nuclear 9/26 (35%) and others 6/18 (33%), p=0.04) Measures used to demonstrate reproducibility were as follows: (1.) ICC 64/96 (67%); 2.) BA 28/96 (29%); 3.) COV 16/96 (17%); 4.) Agreement 18/96 (19%); 5.) Correlation (Pearson's r) 3/96 (3%) p&lt;0.001) (Figure 1b). The proportion of the total population used for reproducibility analysis ranged from 0.8% to 100%, median 18.6% IQR (7.8%- 56.3%). Regression revealed proportion of total population used, was inversely related to population size (r=−0.32, p 0.002). Modality differences were as follows: (Echo 12.0% (5.7%- 36.1%); CT 17.1% (7.8%- 100%); CMR 25.0% (16.1%- 97.1%); Nuclear 68.9% (29.6% - 100%) and others 56.1% (32.6%- 62.3%), p=0.03). Conclusions Approximately half original research manuscripts published across 3 major multi-modality imaging journals discussed or demonstrated reproducibility. No differences across journals were identified. There are differences between modalities with respect to reporting reproducibility. The most common tool used to report reproducibility was ICC. There is marked heterogeneity in the proportion of the total population used to demonstrate reproducibility, this is partly determined by the size of population being examined. Figure 1. A Snapshot of reproducibility reporting Funding Acknowledgement Type of funding source: None

Development and Validation of an Instrument to Assess Horseback Mobility in Hippotherapy

2021 ◽  
pp. 003151252110365
Author(s):  
Alessandra V. Prieto ◽  
Kênnea Martins Almeida Ayupe ◽  
Ana C. A. Abreu ◽  
Paulo J. B. Gutierres Filho
Keyword(s):  
Correlation Coefficient ◽  
Factor Structure ◽  
Internal Consistency ◽  
Rater Reliability ◽  
Intra Class Correlation ◽  
Exploratory Factor Analyses ◽  
Excellent Internal Consistency ◽  
Development And Validation ◽  
Functional Gain ◽  
Intra Class Correlation Coefficient

Improvement in rider mobility represents an important functional gain for people with disabilities undergoing hippotherapy. However, there is no validated measuring instrument to track and document the rider's progress in riding activities. In this study, we aimed to develop and establish validity evidence for an instrument to assess hippotherapy participants’ mobility on horseback. We report on this development through the stages of: (a) content validation, (b) construct validation, (c) inter- and intra-rater reliability and (d) internal consistency analysis. We evaluated its factor structure with exploratory factor analyses, calculated values for inter- and intra-rater reliability using the intra-class correlation coefficient, and calculated its internal consistency using Cronbach's alpha. We followed recommendations by the Guidelines for Reporting Reliability and Agreement Studies. We found good inter-rater reliability (intra-class correlation coefficient – ICC = 0.991–0.999) and good intra-rater reliability (ICC = 0.997–1.0), and there was excellent internal consistency (Cronbach's α = 0.937–0.999). The instrument’s factor structure grouped its three domains into one factor. As this instrument is theoretically consistent and has been found to be appropriate and reliable for its intended use, it is now available for the measurement of horseback mobility among hippotherapy riders.

Importance of incorporating quantitative imaging biomarker technical performance characteristics when estimating treatment effects

2021 ◽  
pp. 174077452098193
Author(s):  
Nancy A Obuchowski ◽  
Erick M Remer ◽  
Ken Sakaie ◽  
Erika Schneider ◽  
Robert J Fox ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Confidence Intervals ◽  
Treatment Effect ◽  
Quantitative Imaging ◽  
Imaging Biomarker ◽  
Imaging Biomarkers ◽  
Measurement Bias ◽  
Technical Performance ◽  
Quantitative Imaging Biomarker ◽  
Performance Validation

Background/aims Quantitative imaging biomarkers have the potential to detect change in disease early and noninvasively, providing information about the diagnosis and prognosis of a patient, aiding in monitoring disease, and informing when therapy is effective. In clinical trials testing new therapies, there has been a tendency to ignore the variability and bias in quantitative imaging biomarker measurements. Unfortunately, this can lead to underpowered studies and incorrect estimates of the treatment effect. We illustrate the problem when non-constant measurement bias is ignored and show how treatment effect estimates can be corrected. Methods Monte Carlo simulation was used to assess the coverage of 95% confidence intervals for the treatment effect when non-constant bias is ignored versus when the bias is corrected for. Three examples are presented to illustrate the methods: doubling times of lung nodules, rates of change in brain atrophy in progressive multiple sclerosis clinical trials, and changes in proton-density fat fraction in trials for patients with nonalcoholic fatty liver disease. Results Incorrectly assuming that the measurement bias is constant leads to 95% confidence intervals for the treatment effect with reduced coverage (<95%); the coverage is especially reduced when the quantitative imaging biomarker measurements have good precision and/or there is a large treatment effect. Estimates of the measurement bias from technical performance validation studies can be used to correct the confidence intervals for the treatment effect. Conclusion Technical performance validation studies of quantitative imaging biomarkers are needed to supplement clinical trial data to provide unbiased estimates of the treatment effect.

Evaluation of Osteopathy in Thalassemia by Bone Mineral Densitometry and Biochemical Indices

2010 ◽  
Vol 77 (9) ◽  
pp. 987-991 ◽  
Author(s):  
Rashid Merchant ◽  
Amish Udani ◽  
Vipla Puri ◽  
Valentina D’cruz ◽  
Deepak Patkar ◽  
...  
Keyword(s):  
Bone Mineral ◽  
Bone Mineral Densitometry ◽  
Biochemical Indices

KATZ AND STIRRAT HAND DIAGRAM REVISITED

Hand Surgery ◽  
2010 ◽  
Vol 15 (02) ◽  
pp. 71-73 ◽  
Author(s):  
Rouin Amirfeyz ◽  
Sanchit Mehendale ◽  
Sarah Tyrrell ◽  
Raj Bhatia ◽  
Ian Leslie ◽  
...  
Keyword(s):  
Carpal Tunnel Syndrome ◽  
Correlation Coefficient ◽  
Carpal Tunnel ◽  
Observer Agreement ◽  
Healthy Individuals ◽  
Intra Class Correlation ◽  
Hand Surgeon ◽  
Observer Reliability ◽  
Tunnel Syndrome ◽  
Intra Class Correlation Coefficient

Katz and Stirrat devised a hand diagram, which uses subjective information from the patient for the diagnosis of carpal tunnel syndrome (CTS). They reported a good result. We tested the inter-observer and intra-observer reliability of this hand diagram. Twenty five consecutive patients with a diagnosis of CTS, 25 with other common hand and wrist problems but CTS and 25 healthy individuals were prospectively recruited. Each patient filled in a hand diagram. Two experienced hand surgeon scored the diagrams blindly on two different sittings four-week apart. The intra-class correlation coefficient (ICC) and Cohen's Kappa were used for intra and inter-observer reliability respectively. The intra-observer agreement was poor (ICC 95% 0.33–0.65) and inter-observer was fair (Kappa = 0.241). This study does not support the use of Katz and Stirrat Hand Diagram for the diagnosis of carpal tunnel syndrome in place if a thorough clinical examination.

scholarly journals Reliability, Stability and Validity of the Brazilian Adaptation of the Oliveira Questionnaire on Low Back Pain in Young People

2017 ◽  
Vol 30 (10) ◽  
pp. 691 ◽  
Author(s):  
Debora Soccal Schwertner ◽  
Raul Oliveira ◽  
Ana Paula Ramos Marinho ◽  
Magnus Benetti ◽  
Thais Silva Beltrame ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Young People ◽  
Correlation Coefficient ◽  
Internal Consistency ◽  
Low Back ◽  
Intra Class Correlation ◽  
Brazilian Version ◽  
Spearman’S Correlation ◽  
Intra Class Correlation Coefficient

Introduction: The objective of this study was to adapt the Brazilian version, and verify the validity, reliability and internal consistency of the Oliveira questionnaire on low back pain in young people.Material and Methods: The questionnaire was translated from European Portuguese into Brazilian Portuguese by means of translation and re-translation. The validity of the contents was determined by experts who analyzed the clarity and pertinence of the questions. Fifteen young people aged 15 to 18 took part in the pre-test step (qualitative analysis), 40 in the test-retest (reliability) and 679 in the evaluation of internal consistency. The intra-class correlation coefficient and Spearman’s correlation coefficient were used in the reliability analysis (test-retest), and Cronbach’s alpha to determine the internal consistency (stability).Results: In the translation phase the questionnaire was modified and considered suitable, observing similarity and equivalence of the two versions. After being corrected by the experts in the validation of the contents, the instrument was considered suitable and valid, and in the pre-test, the young people suggested some modifications to make the questionnaire more succinct. With respect to reliability, the values for the intra-class correlation coefficient were between 0.512 – acceptable and 1 – excellent and Spearman’s correlation coefficient varied between 0.525 and 1, classifying the instrument as reproducible. The internal consistency was considered acceptable with a 0.757 Cronbach’s alpha.Discussion: The Oliveira questionnaire was choosen since it has been used in several Portuguese studies; moreover, it addresses the need to raise data regarding low back pain and associated risk factors.Conclusions: The Brazilian version of the Oliveira questionnaire on low back pain in young people showed valid and reliable cultural adaptation, with good reliability and stability.

scholarly journals The Effect of Interactive Multiple Intelligences Activities Flip Module: Its Effects on Students’ Multiple Intelligences

2019 ◽  
Vol 8 (11) ◽  
pp. 342-348
Keyword(s):  
Multiple Intelligences ◽  
Test Analysis ◽  
Pedagogical Tool ◽  
Intra Class Correlation ◽  
Treatment Groups ◽  
Computer Based Learning ◽  
Intelligence Activity ◽  
Computer Based ◽  
High Degree ◽  
Intra Class Correlation Coefficient

This study aims to test an interactive pedagogical tool using a computer-based learning approach. The purpose of building Multiple Intelligences Activities Flip Module is to increase students’ potentials through their multiple intelligences. The true-experimental study design is used and the samples are randomly selected as control and treatment groups. Pre and post tests are used to measure the effectiveness of this interactive flip module in relations to multiple intelligences significant differences. The findings of the study reveal that the interactive Multiple Intelligences Activity flip module has a high degree of reliability whereby the average measure for Intra-class Correlation Coefficient is .771 with a 95% confidence interval from .520 to .931 (F(9,486)= 4.644, p<.000). Based on MANCOVA test analysis, the researchers have rejected the null hypothesis. The study has demonstrated that the Multiple Intelligence Activity flip module has increased the scores of multiple intelligences tests for treatment groups.

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