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Generation of synthetic CT from MRI for MRI-based attenuation correction of brain PET images using radiomics and machine learning
No full textBackground: Accurate quantitative PET imaging in neurological studies requires proper attenuation correction. MRI-guided attenuation correction in PET/MRI remains challenging owing to the lack of direct relationship between MRI intensities and linear attenuation coefficients. Purpose: This study aims at generating accurate patient-specific synthetic CT volumes, attenuation maps, and attenuation correction factor (ACF) sinograms with continuous values utilizing a combination of machine learning algorithms, image processing techniques, and voxel-based radiomics feature extraction approaches. Methods: Brain MR images of ten healthy volunteers were acquired using IR-pointwise encoding time reduction with radial acquisition (IR-PETRA) and VIBE-Dixon techniques. synthetic CT (SCT) images, attenuation maps, and attenuation correction factors (ACFs) were generated using the LightGBM, a fast and accurate machine learning algorithm, from the radiomics-based and image processing-based feature maps of MR images. Additionally, ultra-low-dose CT images of the same volunteers were acquired and served as the standard of reference for evaluation. The SCT images, attenuation maps, and ACF sinograms were assessed using qualitative and quantitative evaluation metrics and compared against their corresponding reference images, attenuation maps, and ACF sinograms. Results: The voxel-wise and volume-wise comparison between synthetic and reference CT images yielded an average mean absolute error of 60.75 ± 8.8 HUs, an average structural similarity index of 0.88 ± 0.02, and an average peak signal-to-noise ratio of 32.83 ± 2.74 dB. Additionally, we compared MRI-based attenuation maps and ACF sinograms with their CT-based counterparts, revealing average normalized mean absolute errors of 1.48% and 1.33%, respectively. Conclusion: Quantitative assessments indicated higher correlations and similarities between LightGBM-synthesized CT and Reference CT images. Moreover, the cross-validation results showed the possibility of producing accurate SCT images, MRI-based attenuation maps, and ACF sinograms. This might spur the implementation of MRI-based attenuation correction on PET/MRI and dedicated brain PET scanners with lower computational time using CPU-based processors.</p
Generation of synthetic CT from MRI for MRI-based attenuation correction of brain PET images using radiomics and machine learning
No full textBackground: Accurate quantitative PET imaging in neurological studies requires proper attenuation correction. MRI-guided attenuation correction in PET/MRI remains challenging owing to the lack of direct relationship between MRI intensities and linear attenuation coefficients. Purpose: This study aims at generating accurate patient-specific synthetic CT volumes, attenuation maps, and attenuation correction factor (ACF) sinograms with continuous values utilizing a combination of machine learning algorithms, image processing techniques, and voxel-based radiomics feature extraction approaches. Methods: Brain MR images of ten healthy volunteers were acquired using IR-pointwise encoding time reduction with radial acquisition (IR-PETRA) and VIBE-Dixon techniques. synthetic CT (SCT) images, attenuation maps, and attenuation correction factors (ACFs) were generated using the LightGBM, a fast and accurate machine learning algorithm, from the radiomics-based and image processing-based feature maps of MR images. Additionally, ultra-low-dose CT images of the same volunteers were acquired and served as the standard of reference for evaluation. The SCT images, attenuation maps, and ACF sinograms were assessed using qualitative and quantitative evaluation metrics and compared against their corresponding reference images, attenuation maps, and ACF sinograms. Results: The voxel-wise and volume-wise comparison between synthetic and reference CT images yielded an average mean absolute error of 60.75 ± 8.8 HUs, an average structural similarity index of 0.88 ± 0.02, and an average peak signal-to-noise ratio of 32.83 ± 2.74 dB. Additionally, we compared MRI-based attenuation maps and ACF sinograms with their CT-based counterparts, revealing average normalized mean absolute errors of 1.48% and 1.33%, respectively. Conclusion: Quantitative assessments indicated higher correlations and similarities between LightGBM-synthesized CT and Reference CT images. Moreover, the cross-validation results showed the possibility of producing accurate SCT images, MRI-based attenuation maps, and ACF sinograms. This might spur the implementation of MRI-based attenuation correction on PET/MRI and dedicated brain PET scanners with lower computational time using CPU-based processors.</p
“I cannot let this happen to other people”:on menopause advocacy, marketing and consumption with Kate Muir
No full textWe present an interview with Kate Muir, a UK-based women’s health activist, documentary maker and author of books on the menopause and the contraceptive pill. In this exchange, we talk about her menopause documentaries Davina McCall: Sex, Myths and the Menopause and Davina McCall: Sex, Mind and the Menopause. Both documentaries have made the menopause transition achieve a new distinction, aided by celebrity association and vociferation against the traditional invisibility associated with mid-life change and its overlooked health and economic implications. This paper goes on to discuss embodied health activism, ‘The New Menopause Movement’, biographical disruption, reproductive health misinformation and calling out spurious marketing messages
Impact of tracer uptake rate on quantification accuracy of myocardial blood flow in PET:A simulation study
No full textBackground: Cardiac perfusion PET is commonly used to assess ischemia and cardiovascular risk, which enables quantitative measurements of myocardial blood flow (MBF) through kinetic modeling. However, the estimation of kinetic parameters is challenging due to the noisy nature of short dynamic frames and limited sample data points. Purpose: This work aimed to investigate the errors in MBF estimation in PET through a simulation study and to evaluate different parameter estimation approaches, including a deep learning (DL) method. Materials and Methods: Simulated studies were generated using digital phantoms based on cardiac segmentations from 55 clinical CT images. We employed the irreversible 2-tissue compartmental model and simulated dynamic 13N-ammonia PET scans under both rest and stress conditions (220 cases each). The simulations covered a rest K1 range of 0.6 to 1.2 and a stress K1 range of 1.2 to 3.6 (unit: mL/min/g) in the myocardium. A transformer-based DL model was trained on the simulated dataset to predict parametric images (PIMs) from noisy PET image frames and was validated using 5-fold cross-validation. We compared the DL method with the voxel-wise nonlinear least squares (NLS) fitting applied to the dynamic images, using either Gaussian filter (GF) smoothing (GF-NLS) or a dynamic nonlocal means (DNLM) algorithm for denoising (DNLM-NLS). Two patients with coronary CT angiography (CTA) and fractional flow reserve (FFR) were enrolled to test the feasibility of applying DL models on clinical PET data. Results: The DL method showed clearer image structures with reduced noise compared to the traditional NLS-based methods. In terms of mean absolute relative error (MARE), as the rest K1 values increased from 0.6 to 1.2 mL/min/g, the overall bias in myocardium K1 estimates decreased from approximately 58% to 45% for the NLS-based methods while the DL method showed a reduction in MARE from 42% to 18%. For stress data, as the stress K1 decreased from 3.6 to 1.2 mL/min/g, the MARE increased from 30% to 70% for the GF-NLS method. In contrast, both the DNLM-NLS (average: 42%) and the DL methods (average: 20%) demonstrated significantly smaller MARE changes as stress K1 varied. Regarding the regional mean bias (±standard deviation), the GF-NLS method had a bias of 6.30% (±8.35%) of rest K1, compared to 1.10% (±8.21%) for DNLM-NLS and 6.28% (±14.05%) for the DL method. For the stress K1, the GF-NLS showed a mean bias of 10.72% (±9.34%) compared to 1.69% (±8.82%) for DNLM-NLS and −10.55% (±9.81%) for the DL method. Significance: This study showed that an increase in the tracer uptake rate (K1) corresponded to improved accuracy and precision in MBF quantification, whereas lower tracer uptake resulted in higher noise in dynamic PET and poorer parameter estimates. Utilizing denoising techniques or DL approaches can mitigate noise-induced bias in PET parametric imaging.</p
Invasive mechanical ventilation strategies, adjuvants treatments and adverse events among ICU patients with COVID-19 in Denmark
No full textAim: To describe the use of invasive mechanical ventilation core strategies, adjuvant treatments and the occurrence of barotrauma and prolonged ventilation in ICU patients with COVID-19 in Denmark, retrospectively.Methods: All ICUs admitting COVID-19 patients in Denmark from 10 March 2020 to 2 April 2021 were invited to participate. All patients with COVID-19 who received invasive mechanical ventilation were included and data was retrospectively collected from electronic patient records.Results: A total of 774 patients were invasively ventilated during the first two waves and included; 70% were males and the median age was 69 years. 340 (51.5%) of patients never exceeded tidal volumes of 8 mL/kg. For all patients, tidal volumes under 8 mL/kg were applied in 77.6% (IQR 54.5%-96.2%) of the time on ventilator in the ICU; plateau pressure was below 30 cm H2O in 125 (80.6%) patients; prone positioning was used in 44.7% of patients. In ICU, 169 of 774 (21.8%) patients experienced barotrauma and 220 (28.4%) prolonged ventilation. At 90 days, 306 (39.5%) had died.Conclusions: Lung protective ventilation and prone positioning were used in many of the Danish ICU patients with COVID-19, but barotrauma, prolonged ventilation and death occurred frequently.AIM: To describe the use of invasive mechanical ventilation core strategies, adjuvant treatments and the occurrence of barotrauma and prolonged ventilation in ICU patients with COVID-19 in Denmark, retrospectively.METHODS: All ICUs admitting COVID-19 patients in Denmark from 10 March 2020 to 2 April 2021 were invited to participate. All patients with COVID-19 who received invasive mechanical ventilation were included and data was retrospectively collected from electronic patient records.RESULTS: A total of 774 patients were invasively ventilated during the first two waves and included; 70% were males and the median age was 69 years. 340 (51.5%) of patients never exceeded tidal volumes of 8 mL/kg. For all patients, tidal volumes under 8 mL/kg were applied in 77.6% (IQR 54.5%-96.2%) of the time on ventilator in the ICU; plateau pressure was below 30 cm H2O in 125 (80.6%) patients; prone positioning was used in 44.7% of patients. In ICU, 169 of 774 (21.8%) patients experienced barotrauma and 220 (28.4%) prolonged ventilation. At 90 days, 306 (39.5%) had died.CONCLUSIONS: Lung protective ventilation and prone positioning were used in many of the Danish ICU patients with COVID-19, but barotrauma, prolonged ventilation and death occurred frequently
Changing the Menu:Humpback Whale (Megaptera novaeangliae) Diet Switching in Senyavin Strait, Chukotka
No full textHumpback whales have the most diverse diet of all rorquals. Their ability to use different prey depending on local availability makes them a promising indicator species for ecosystem dynamics. During five summer–fall seasons in 2017–2021, regular observations of humpback whale feeding aggregations were conducted as part of multi-year cetacean monitoring in Senyavin Strait, on the eastern Chukotka Peninsula. The study included assessing the trophic level of the whales using stable isotope analysis, as well as collateral observations of feeding behavior, spatial distribution, and surface activity records. We found that the spatial distribution, daytime activity patterns, and trophic levels of the whales differed significantly between 2017 and 2018–2021. These differences, combined with some additional observations of whale feeding activity, suggest that the whales fed on fish, most likely polar cod, in 2017 and switched to preferentially krill in later years. We suggest that our observations in 2017 coincided with a sporadic schooling event of polar cod. We show that a single humpback whale population can abruptly change its feeding habits and switch from one prey type to another under optimal conditions. The high degree of behavioral plasticity may be one of the keys to the evolutionary success of this species.</p
Serverless Computing in Cloud-Edge Scenarios
No full textDenne afhandling undersøger udvidelser til serverless computing, med fokus på Function-as a-Service (FaaS), ved at udvide anvendelsesområdet ud over rent offentlige, cloudbaserede arkitekturer til edge-systemer og hybride cloud-edge-implementeringer. Inkluderingen af disse miljøer medfører flere fordele, såsom reduktion af behovet for datatransmission og oprettelsen af et cloud-edge-continuum, således at arbejdsbelastninger kan flyttes på en transparent måde. Understøttelse af disse miljøer skaber også mulighed, for at integrere Internet of Things (IoT)-enheder på en sikker og transparent måde.Inkorporering af edge-systemer medfører imidlertid nye udfordringer, der stammer fra heterogene netværkstopologier og enheder med begrænsede ressourcer. For at imødegå disse udfordringer introducerer dette arbejde flere nye planlægningsmetoder, der udtrykkes gennem udvidelser af APP (Application Priority Policies), et konfigurationssprog for FaaS-schedulers. Disse udvidelser, dvs. topology-aware APP (tAPP), affinity-aware APP (aAPP) og cost-aware APP (cAPP), forbedrer henholdsvis schedulers ved at fokusere på den geografiske fordeling af senheder, affiniteten mellem funktioner og minimering af den forventede ventetid ved kommunikation med eksterne tjenester.Med samme formål præsenterer afhandlingen også FunLess, en open-source serverless platform, der er rettet mod edge- og cloud-edge-implementeringer. Platformen bruger WebAssemblytil at eksekvere funktioner og udnytter dens cross-platform natur og de små binære filestørelser til bedre at målrette enheder med begrænsede ressourcer.Endelig undersøger arbejdet et anvendelsesscenarie, hvor droner fungerer som mobile beregningsenheder inden for platformen. Dette system demonstrerer udførelse og aflastning af opgaver i realtid under upålidelige og mobile netværksforhold, valideret gennem en simuleret katastrofesituation.This thesis investigates extensions to serverless computing, and specifically Function-as-a-Service (FaaS), by broadening its scope beyond purely public, cloud-based architectures, towards edge systems and hybrid cloud-edge deployments. The inclusion of such environments brings several benefits, such as the reduction of data transmission needs and the creation of a cloud-edge continuum across which workloads can be transparently moved. Supporting these environments also creates the possibility to integrate Internet of Things(IoT) devices in a secure, transparent way.Incorporating edge systems, however, brings new challenges stemming from heterogeneous network topologies and resource-constrained devices. To address these, this work introduces several novel scheduling approaches, expressed through extensions of APP(Application Priority Policies), a configuration language for FaaS schedulers. These extensions, i.e., topology-aware APP (tAPP), affinity-aware APP (aAPP), and cost-aware APP(cAPP), respectively improve schedulers by focusing on the geographical distribution ofworkers, the affinity between functions, and the minimisation of the expected latency when communicating with external services.To the same end, the thesis also presents FunLess, an open-source serverless platform geared towards edge and cloud-edge deployments. The platform makes use of WebAssembly for function execution, leveraging its cross-architecture nature and the small size of its binaries to better target resource-constrained devices.Finally, the work explores an application scenario where drones act as mobile computational nodes within the platform. This system demonstrates real-time task execution and offloading in unreliable and mobile network conditions, validated through a simulated emergency response use case
Parent and Therapist Perceptions of Early Therapy for Infants With or at Risk of Cerebral Palsy:A Scoping Review
No full textBACKGROUND: Currently, the early detection of cerebral palsy (CP) or risk of CP is recommended to enable targeted and specific intervention. The provision of early therapy is a complex practice that places high demands on both parents and therapists. More knowledge about the perceptions of parents and therapists is needed to help the implementation of family-centred early therapy interventions that are based on recent evidence in clinical practice. This scoping review aims to identify the extent of literature and summarize the evidence exploring parents' and therapists' experiences of early occupational and physical therapy for infants with or at risk of CP.METHOD: The scoping review was conducted in accordance with the JBI methodology for scoping reviews and reported following the PRISMA Extension for Scoping Reviews checklist. The experiences of parents and therapists were categorized using qualitative content analysis.RESULTS: In total, 16 studies published between 2018 and 2024 were included. Parent-reported experiences were included in 15 studies and therapist-reported experiences in three. The content analysis resulted in five categories reflecting perceptions of valued and challenging aspects of early therapy. Four categories concerned parents' perceptions: parental commitment, parent-therapist collaboration, parents as training providers and parental education. One category concerned therapists' perceptions: providing guidance and educating parents.CONCLUSION: Insight into perceptions of early therapy highlights the importance of professional coordination of intervention, specific training of therapists, managing parents' feelings of uncertainty and balancing parents' engagement in their role as treatment providers and the pressure they may experience from the responsibility this role entails. This finding contributes important knowledge for the successful implementation of family-centred and evidence-based early therapy interventions in clinical practice for infants with or at risk of CP. A limited number of studies exploring therapists' perceptions were identified, which indicates a knowledge gap and a need for further research.</p
Quantifying physical activity during active commuting to school: A comparison of methodologies
No full textThe current study aims to detect walking trips to/from school with different methodologies (GPS, self-reported, fixed windows [w30 and w60], and distance-based time), and to compare the start/end times for the trips, and the time accumulated in sedentary time, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). A total of 93 Spanish adolescents wore an accelerometer and GPS during school days, and the start/end times of walking trips to/from school were determined using five different methodologies. Mixed-effects limits of agreement analyses were used to determine the level of agreement between the start/end times of the walking trips identified by the five methodologies mentioned. Moreover, methodologies were determined to be equivalent if the mean difference with the GPS was within the proposed equivalence zone of ± 5.0 min. Self-reported measures showed a good level of agreement for estimating start times of walking trips to school compared to GPS, 0.0 (LoA95%:-0.3–0.2) hours. Self-reported measures were deemed equivalent to GPS for measuring sedentary time, LPA, and MVPA. W30 and distance-based time were equivalent to GPS for LPA and MVPA, but not for sedentary time. W60 was only deemed equivalent to GPS for MVPA accumulated during walking trips to and from school. Self-reported measures showed the most precise approach for estimating start times to school, as well as it deemed equivalent to GPS for quantifying sedentary time, LPA, and MVPA. Moreover, estimating the time to complete the trip based on the distance between home and school could be more appropriate than fixed windows
“I cannot let this happen to other people”:on menopause advocacy, marketing and consumption with Kate Muir
No full textWe present an interview with Kate Muir, a UK-based women’s health activist, documentary maker and author of books on the menopause and the contraceptive pill. In this exchange, we talk about her menopause documentaries Davina McCall: Sex, Myths and the Menopause and Davina McCall: Sex, Mind and the Menopause. Both documentaries have made the menopause transition achieve a new distinction, aided by celebrity association and vociferation against the traditional invisibility associated with mid-life change and its overlooked health and economic implications. This paper goes on to discuss embodied health activism, ‘The New Menopause Movement’, biographical disruption, reproductive health misinformation and calling out spurious marketing messages