Construction contingency determination : a review of processes and techniques

Abstract

Critical success factors (CSFs) for motivating end-user stakeholder’s support for ensuring sustainability of PPP projects in Nigerian host communities

This is an accepted manuscript of an article published by Emerald in Journal of Engineering, Design and Technology on 06/09/2021, available online: https://doi.org/10.1108/JEDT-04-2021-0202 The accepted version of the publication may differ from the final published version.Purpose: This study aims to investigate two public private partnership (PPP) road projects in Nigeria for exploring factors that can motivate end-user stakeholders for contributing towards sustaining a PPP project in the long-term. Design/methodology/approach: Using a case study methodology approach, this study adopts two-way data collection strategies via in-depth interviews with PPP experts and end-user stakeholders in Nigeria host communities and a questionnaire survey to relevant stakeholders. Findings: The study identifies an eight-factor structure indicating critical success factors for ensuring end-user stakeholders support PPP projects on a long-term basis in their host communities. Originality/value: Results of the study have huge implications for policymakers and project companies by encouraging the early integration of far-sighted measures that will promote long-term support and sustainability for PPP projects amongst the end-user stakeholders.Published versio

Sustainability Barriers in Nigeria Construction Practice

© 2022 IOP Publishing. Content from this work may be used under the terms of the Creative Commons Attribution 3.0. licence. https://creativecommons.org/licenses/by/3.0/The struggles to practise sustainable construction are not gaining the desired traction in Nigeria. This study established the likely barriers to successful application of sustainable construction in the Nigeria construction industry and factors to overcome the possible barriers. A quantitative approach was used for the study and a questionnaire survey was conducted among the professionals and other stakeholders. A descriptive method was used in analysing the collected data. Among the highly ranked sustainability barriers to construction practice are poor sustainability education in academic institutions, lack of incentives for designers to facilitate sustainable design, ignorance of lifecycle cost benefits, sustainable construction regarded as low priority and other issues take priority, and resistance to cultural change in the industry. The research recommends adequate sustainability education in academic institutions to positively impact the required cultural change in the industry. There is call for proper government policies that support implementation of sustainable construction practices. The study also advances the need for construction professionals and stakeholders to embrace the concept of sustainability education through continuing professional development and or postgraduate studies to improve the thinking and practicability of sustainable practice of construction in Nigeria.Peer reviewedFinal Published versio

Timing of glioblastoma surgery and patient outcomes: a multicenter cohort study.

BACKGROUND: The impact of time-to-surgery on clinical outcome for patients with glioblastoma has not been determined. Any delay in treatment is perceived as detrimental, but guidelines do not specify acceptable timings. In this study, we relate the time to glioblastoma surgery with the extent of resection and residual tumor volume, performance change, and survival, and we explore the identification of patients for urgent surgery. METHODS: Adults with first-time surgery in 2012–2013 treated by 12 neuro-oncological teams were included in this study. We defined time-to-surgery as the number of days between the diagnostic MR scan and surgery. The relation between time-to-surgery and patient and tumor characteristics was explored in time-to-event analysis and proportional hazard models. Outcome according to time-to-surgery was analyzed by volumetric measurements, changes in performance status, and survival analysis with patient and tumor characteristics as modifiers. RESULTS: Included were 1033 patients of whom 729 had a resection and 304 a biopsy. The overall median time-to-surgery was 13 days. Surgery was within 3 days for 235 (23%) patients, and within a month for 889 (86%). The median volumetric doubling time was 22 days. Lower performance status (hazard ratio [HR] 0.942, 95% confidence interval [CI] 0.893–0.994) and larger tumor volume (HR 1.012, 95% CI 1.010–1.014) were independently associated with a shorter time-to-surgery. Extent of resection, residual tumor volume, postoperative performance change, and overall survival were not associated with time-to-surgery. CONCLUSIONS: With current decision-making for urgent surgery in selected patients with glioblastoma and surgery typically within 1 month, we found equal extent of resection, residual tumor volume, performance status, and survival after longer times-to-surgery

Glioblastoma Surgery Imaging-Reporting and Data System: Validation and Performance of the Automated Segmentation Task

For patients with presumed glioblastoma, essential tumor characteristics are determined from preoperative MR images to optimize the treatment strategy. This procedure is time-consuming and subjective, if performed by crude eyeballing or manually. The standardized GSI-RADS aims to provide neurosurgeons with automatic tumor segmentations to extract tumor features rapidly and objectively. In this study, we improved automatic tumor segmentation and compared the agreement with manual raters, describe the technical details of the different components of GSI-RADS, and determined their speed. Two recent neural network architectures were considered for the segmentation task: nnU-Net and AGU-Net. Two preprocessing schemes were introduced to investigate the tradeoff between performance and processing speed. A summarized description of the tumor feature extraction and standardized reporting process is included. The trained architectures for automatic segmentation and the code for computing the standardized report are distributed as open-source and as open-access software. Validation studies were performed on a dataset of 1594 gadolinium-enhanced T1-weighted MRI volumes from 13 hospitals and 293 T1-weighted MRI volumes from the BraTS challenge. The glioblastoma tumor core segmentation reached a Dice score slightly below 90%, a patientwise F1-score close to 99%, and a 95th percentile Hausdorff distance slightly below 4.0 mm on average with either architecture and the heavy preprocessing scheme. A patient MRI volume can be segmented in less than one minute, and a standardized report can be generated in up to five minutes. The proposed GSI-RADS software showed robust performance on a large collection of MRI volumes from various hospitals and generated results within a reasonable runtime

Glioblastoma surgery imaging—reporting and data system: Standardized reporting of tumor volume, location, and resectability based on automated segmentations

Treatment decisions for patients with presumed glioblastoma are based on tumor characteristics available from a preoperative MR scan. Tumor characteristics, including volume, location, and resectability, are often estimated or manually delineated. This process is time consuming and subjective. Hence, comparison across cohorts, trials, or registries are subject to assessment bias. In this study, we propose a standardized Glioblastoma Surgery Imaging Reporting and Data System (GSI-RADS) based on an automated method of tumor segmentation that provides standard reports on tumor features that are potentially relevant for glioblastoma surgery. As clinical validation, we determine the agreement in extracted tumor features between the automated method and the current standard of manual segmentations from routine clinical MR scans before treatment. In an observational consecutive cohort of 1596 adult patients with a first time surgery of a glioblastoma from 13 institutions, we segmented gadolinium-enhanced tumor parts both by a human rater and by an automated algorithm. Tumor features were extracted from segmentations of both methods and compared to assess differences, concordance, and equivalence. The laterality, contralateral infiltration, and the laterality indices were in excellent agreement. The native and normalized tumor volumes had excellent agreement, consistency, and equivalence. Multifocality, but not the number of foci, had good agreement and equivalence. The location profiles of cortical and subcortical structures were in excellent agreement. The expected residual tumor volumes and resectability indices had excellent agreement, consistency, and equivalence. Tumor probability maps were in good agreement. In conclusion, automated segmentations are in excellent agreement with manual segmentations and practically equivalent regarding tumor features that are potentially relevant for neurosurgical purposes. Standard GSI-RADS reports can be generated by open access software

Multi-class glioma segmentation on real-world data with missing MRI sequences: comparison of three deep learning algorithms

This study tests the generalisability of three Brain Tumor Segmentation (BraTS) challenge models using a multi-center dataset of varying image quality and incomplete MRI datasets. In this retrospective study, DeepMedic, no-new-Unet (nn-Unet), and NVIDIA-net (nv-Net) were trained and tested using manual segmentations from preoperative MRI of glioblastoma (GBM) and low-grade gliomas (LGG) from the BraTS 2021 dataset (1251 in total), in addition to 275 GBM and 205 LGG acquired clinically across 12 hospitals worldwide. Data was split into 80% training, 5% validation, and 15% internal test data. An additional external test-set of 158 GBM and 69 LGG was used to assess generalisability to other hospitals’ data. All models’ median Dice similarity coefficient (DSC) for both test sets were within, or higher than, previously reported human inter-rater agreement (range of 0.74–0.85). For both test sets, nn-Unet achieved the highest DSC (internal = 0.86, external = 0.93) and the lowest Hausdorff distances (10.07, 13.87 mm, respectively) for all tumor classes (p < 0.001). By applying Sparsified training, missing MRI sequences did not statistically affect the performance. nn-Unet achieves accurate segmentations in clinical settings even in the presence of incomplete MRI datasets. This facilitates future clinical adoption of automated glioma segmentation, which could help inform treatment planning and glioma monitoring

Living Alone, Patient Sex and Mortality After Acute Myocardial Infarction

BACKGROUND: Psychosocial factors, including social support, affect outcomes of cardiovascular disease, but can be difficult to measure. Whether these factors have different effects on mortality post-acute myocardial infarction (AMI) in men and women is not clear. OBJECTIVE: To examine the association between living alone, a proxy for social support, and mortality postdischarge AMI and to explore whether this association is modified by patient sex. DESIGN: Historical cohort study. PARTICIPANTS/SETTING: All patients discharged with a primary diagnosis of AMI in a major urban center during the 1998–1999 fiscal year. MEASUREMENTS: Patients’ sociodemographic and clinical characteristics were obtained by standardized chart review and linked to vital statistics data through December 2001. RESULTS: Of 880 patients, 164 (18.6%) were living alone at admission and they were significantly more likely to be older and female than those living with others. Living alone was independently associated with mortality [adjusted hazard ratio (HR) 1.6, 95% confidence interval (CI) 1.0–2.5], but interacted with patient sex. Men living alone had the highest mortality risk (adjusted HR 2.0, 95% CI 1.1–3.7), followed by women living alone (adjusted HR 1.2, 95% CI 0.7–2.2), men living with others (reference, HR 1.0), and women living with others (adjusted HR 0.9, 95% CI 0.5–1.5). CONCLUSIONS: Living alone, an easily measured psychosocial factor, is associated with significantly increased longer-term mortality for men following AMI. Further prospective studies are needed to confirm the usefulness of living alone as a prognostic factor and to identify the potentially modifiable mechanisms underlying this increased risk