Evaluation of the HD-GLIO Deep Learning Algorithm for Brain Tumour Segmentation on Postoperative MRI

In the context of brain tumour response assessment, deep learning-based three-dimensional (3D) tumour segmentation has shown potential to enter the routine radiological workflow. The purpose of the present study was to perform an external evaluation of a state-of-the-art deep learning 3D brain tumour segmentation algorithm (HD-GLIO) on an independent cohort of consecutive, post-operative patients. For 66 consecutive magnetic resonance imaging examinations, we compared delineations of contrast-enhancing (CE) tumour lesions and non-enhancing T2/FLAIR hyperintense abnormality (NE) lesions by the HD-GLIO algorithm and radiologists using Dice similarity coefficients (Dice). Volume agreement was assessed using concordance correlation coefficients (CCCs) and Bland–Altman plots. The algorithm performed very well regarding the segmentation of NE volumes (median Dice = 0.79) and CE tumour volumes larger than 1.0 cm3 (median Dice = 0.86). If considering all cases with CE tumour lesions, the performance dropped significantly (median Dice = 0.40). Volume agreement was excellent with CCCs of 0.997 (CE tumour volumes) and 0.922 (NE volumes). The findings have implications for the application of the HD-GLIO algorithm in the routine radiological workflow where small contrast-enhancing tumours will constitute a considerable share of the follow-up cases. Our study underlines that independent validations on clinical datasets are key to asserting the robustness of deep learning algorithms

Evaluation of the HD-GLIO Deep Learning Algorithm for Brain Tumour Segmentation on Postoperative MRI

In the context of brain tumour response assessment, deep learning-based three-dimensional (3D) tumour segmentation has shown potential to enter the routine radiological workflow. The purpose of the present study was to perform an external evaluation of a state-of-the-art deep learning 3D brain tumour segmentation algorithm (HD-GLIO) on an independent cohort of consecutive, post-operative patients. For 66 consecutive magnetic resonance imaging examinations, we compared delineations of contrast-enhancing (CE) tumour lesions and non-enhancing T2/FLAIR hyperintense abnormality (NE) lesions by the HD-GLIO algorithm and radiologists using Dice similarity coefficients (Dice). Volume agreement was assessed using concordance correlation coefficients (CCCs) and Bland–Altman plots. The algorithm performed very well regarding the segmentation of NE volumes (median Dice = 0.79) and CE tumour volumes larger than 1.0 cm3 (median Dice = 0.86). If considering all cases with CE tumour lesions, the performance dropped significantly (median Dice = 0.40). Volume agreement was excellent with CCCs of 0.997 (CE tumour volumes) and 0.922 (NE volumes). The findings have implications for the application of the HD-GLIO algorithm in the routine radiological workflow where small contrast-enhancing tumours will constitute a considerable share of the follow-up cases. Our study underlines that independent validations on clinical datasets are key to asserting the robustness of deep learning algorithms

Improving work for the body - a participatory ergonomic intervention aiming at reducing physical exertion and musculoskeletal pain among childcare workers (the TOY-project): Study protocol for a wait-list cluster-randomized controlled trial

Background: The prevalence of musculoskeletal pain (MSP) is persistently high throughout the world. Work-related factors such as high physical workload (lifting, bending and twisting of the back) are considered to be among the main causes of MSP. Work in childcare includes the need to lift, carry, and support children in a range of activities, requiring several demanding postures and movements, such as bending forward and twisting of the back and sitting on the floor. Participatory ergonomics may represent a solution for decreasing the physical workload to reduce MSP. We present the protocol of a study aiming to evaluate the effect and process of a participatory ergonomics intervention designed to reduce physical exertion during work and MSP (including MSP interfering with work) among childcare workers. Methods/design: This study will use a two-arm cluster-randomized design employing a wait-list control, with childcare institutions forming the clusters. Three workshops will be conducted during the 4-month intervention period. Participants will identify risk factors for strenuous work and MSP, develop solutions for reducing the identified risk factors, and implement them in their team. An ergonomic consultant will guide the process. The data collection will consist of questionnaires and objective measures of heart rate and physical activity, observations of physical workload, and information on sickness absence based on company records. Primary outcomes are physical exertion during work and MSP (including pain-related work interference) measured at 4 months. Secondary outcomes measured at 4months are sickness absence due to MSP; objectively measured occupational physical activity and heart rate; and self-reported self-efficacy, employee involvement, and need for recovery. Alongside the trial, a process evaluation and an economic evaluation will be conducted. Discussion: The study will evaluate the effect and process of a participatory ergonomics intervention to reduce physical exertion at work and MSP among childcare workers. By performing a cluster-randomized controlled trial with an effect evaluation based on both objective and self-reported measures with the addition of a process evaluation and economic evaluation, this study will contribute to the evidence for prevention of MSP among a less studied occupational group. Results are expected in 2018-2019

Inter- and Intra-Observer Agreement When Using a Diagnostic Labeling Scheme for Annotating Findings on Chest X-rays—An Early Step in the Development of a Deep Learning-Based Decision Support System

Consistent annotation of data is a prerequisite for the successful training and testing of artificial intelligence-based decision support systems in radiology. This can be obtained by standardizing terminology when annotating diagnostic images. The purpose of this study was to evaluate the annotation consistency among radiologists when using a novel diagnostic labeling scheme for chest X-rays. Six radiologists with experience ranging from one to sixteen years, annotated a set of 100 fully anonymized chest X-rays. The blinded radiologists annotated on two separate occasions. Statistical analyses were done using Randolph’s kappa and PABAK, and the proportions of specific agreements were calculated. Fair-to-excellent agreement was found for all labels among the annotators (Randolph’s Kappa, 0.40–0.99). The PABAK ranged from 0.12 to 1 for the two-reader inter-rater agreement and 0.26 to 1 for the intra-rater agreement. Descriptive and broad labels achieved the highest proportion of positive agreement in both the inter- and intra-reader analyses. Annotating findings with specific, interpretive labels were found to be difficult for less experienced radiologists. Annotating images with descriptive labels may increase agreement between radiologists with different experience levels compared to annotation with interpretive labels

Improving work for the body – a participatory ergonomic intervention aiming at reducing physical exertion and musculoskeletal pain among childcare workers (the TOY-project): study protocol for a wait-list cluster-randomized controlled trial

Abstract Background The prevalence of musculoskeletal pain (MSP) is persistently high throughout the world. Work-related factors such as high physical workload (lifting, bending and twisting of the back) are considered to be among the main causes of MSP. Work in childcare includes the need to lift, carry, and support children in a range of activities, requiring several demanding postures and movements, such as bending forward and twisting of the back and sitting on the floor. Participatory ergonomics may represent a solution for decreasing the physical workload to reduce MSP. We present the protocol of a study aiming to evaluate the effect and process of a participatory ergonomics intervention designed to reduce physical exertion during work and MSP (including MSP interfering with work) among childcare workers. Methods/design This study will use a two-arm cluster-randomized design employing a wait-list control, with childcare institutions forming the clusters. Three workshops will be conducted during the 4-month intervention period. Participants will identify risk factors for strenuous work and MSP, develop solutions for reducing the identified risk factors, and implement them in their team. An ergonomic consultant will guide the process. The data collection will consist of questionnaires and objective measures of heart rate and physical activity, observations of physical workload, and information on sickness absence based on company records. Primary outcomes are physical exertion during work and MSP (including pain-related work interference) measured at 4 months. Secondary outcomes measured at 4 months are sickness absence due to MSP; objectively measured occupational physical activity and heart rate; and self-reported self-efficacy, employee involvement, and need for recovery. Alongside the trial, a process evaluation and an economic evaluation will be conducted. Discussion The study will evaluate the effect and process of a participatory ergonomics intervention to reduce physical exertion at work and MSP among childcare workers. By performing a cluster-randomized controlled trial with an effect evaluation based on both objective and self-reported measures with the addition of a process evaluation and economic evaluation, this study will contribute to the evidence for prevention of MSP among a less studied occupational group. Results are expected in 2018–2019. Trial registration ISRCTN, ISRCTN10928313 . Registered on 11 January 2017

Improving work for the body – a participatory ergonomic intervention aiming at reducing physical exertion and musculoskeletal pain among childcare workers (the TOY-project): study protocol for a wait-list cluster-randomized controlled trial

Abstract Background The prevalence of musculoskeletal pain (MSP) is persistently high throughout the world. Work-related factors such as high physical workload (lifting, bending and twisting of the back) are considered to be among the main causes of MSP. Work in childcare includes the need to lift, carry, and support children in a range of activities, requiring several demanding postures and movements, such as bending forward and twisting of the back and sitting on the floor. Participatory ergonomics may represent a solution for decreasing the physical workload to reduce MSP. We present the protocol of a study aiming to evaluate the effect and process of a participatory ergonomics intervention designed to reduce physical exertion during work and MSP (including MSP interfering with work) among childcare workers. Methods/design This study will use a two-arm cluster-randomized design employing a wait-list control, with childcare institutions forming the clusters. Three workshops will be conducted during the 4-month intervention period. Participants will identify risk factors for strenuous work and MSP, develop solutions for reducing the identified risk factors, and implement them in their team. An ergonomic consultant will guide the process. The data collection will consist of questionnaires and objective measures of heart rate and physical activity, observations of physical workload, and information on sickness absence based on company records. Primary outcomes are physical exertion during work and MSP (including pain-related work interference) measured at 4 months. Secondary outcomes measured at 4 months are sickness absence due to MSP; objectively measured occupational physical activity and heart rate; and self-reported self-efficacy, employee involvement, and need for recovery. Alongside the trial, a process evaluation and an economic evaluation will be conducted. Discussion The study will evaluate the effect and process of a participatory ergonomics intervention to reduce physical exertion at work and MSP among childcare workers. By performing a cluster-randomized controlled trial with an effect evaluation based on both objective and self-reported measures with the addition of a process evaluation and economic evaluation, this study will contribute to the evidence for prevention of MSP among a less studied occupational group. Results are expected in 2018–2019. Trial registration ISRCTN, ISRCTN10928313 . Registered on 11 January 2017

Additional file 1: of Improving work for the body â a participatory ergonomic intervention aiming at reducing physical exertion and musculoskeletal pain among childcare workers (the TOY-project): study protocol for a wait-list cluster-randomized controlled trial

SPIRIT 2013 checklist: Recommended items to address in a clinical trial protocol and related documents. (DOC 121 kb