Leiden University Scholary Publications
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Deep learning image enhancement algorithms in PET/CT imaging: a phantom and sarcoma patient radiomic evaluation
Get PDFPurposePET/CT imaging data contains a wealth of quantitative information that can provide valuable contributions to characterising tumours. A growing body of work focuses on the use of deep-learning (DL) techniques for denoising PET data. These models are clinically evaluated prior to use, however, quantitative image assessment provides potential for further evaluation. This work uses radiomic features to compare two manufacturer deep-learning (DL) image enhancement algorithms, one of which has been commercialised, against ‘gold-standard’ image reconstruction techniques in phantom data and a sarcoma patient data set (N=20).MethodsAll studies in the retrospective sarcoma clinical [18F]FDG dataset were acquired on either a GE Discovery 690 or 710 PET/CT scanner with volumes segmented by an experienced nuclear medicine radiologist. The modular heterogeneous imaging phantom used in this work was filled with [18F]FDG, and five repeat acquisitions of the phantom were acquired on a GE Discovery 710 PET/CT scanner. The DL-enhanced images were compared to ‘gold-standard’ images the algorithms were trained to emulate and input images. The difference between image sets was tested for significance in 93 international biomarker standardisation initiative (IBSI) standardised radiomic features.ResultsComparing DL-enhanced images to the ‘gold-standard’, 4.0% and 9.7% radiomic features measured significantly different (pcritical ConclusionDL-enhanced images were found to be similar to images generated using the ‘gold-standard’ target image reconstruction method with more than 80% of radiomic features not significantly different in all comparisons across unseen phantom and sarcoma patient data. This result offers insight into the performance of the DL algorithms, and demonstrate potential applications for DL algorithms in harmonisation for radiomics and for radiomic features in quantitative evaluation of DL algorithms.</p
Fc proteoforms of ACPA IgG discriminate autoimmune responses in plasma and synovial fluid of rheumatoid arthritis patients and associate with disease activity
Get PDFAutoantibodies and their post-translational modifications (PTMs) are insightful markers of autoimmune diseases providing diagnostic and prognostic clues, thereby informing clinical decisions. However, current autoantibody analyses focus mostly on IgG1 glycosylation representing only a subpopulation of the actual IgG proteome. Here, by taking rheumatoid arthritis (RA) as prototypic autoimmune disease, we sought to circumvent these shortcomings and illuminate the importance of (auto)antibody proteoforms employing a novel comprehensive mass spectrometry (MS)-based analytical workflow. Profiling of anti-citrullinated protein antibodies (ACPA) IgG and total IgG in paired samples of plasma and synovial fluid revealed a clear distinction of autoantibodies from total IgG and between biofluids. This discrimination relied on comprehensive subclass-specific PTM profiles including previously neglected features such as IgG3 CH3 domain glycosylation, allotype ratios, and non-glycosylated IgG. Intriguingly, specific proteoforms were found to correlate with markers of inflammation and disease accentuating the need of such approaches in clinical investigations and calling for further mechanistic studies to comprehend the role of autoantibody proteoforms in defining autoimmune responses.Pathophysiology and treatment of rheumatic disease
(BONUS) Hardlopers en doodlopers: de paradoxen van Zeno
No full textClassics and Classical Civilizatio
Psychological distress and quality of life in families with a germline CDKN2A pathogenic variant
Get PDFBackgroundIndividuals with a germline CDKN2A pathogenic variant (PV) have an increased lifetime risk of melanoma and pancreatic cancer. It is unknown whether the CDKN2A PV impacts quality of life (QoL). Therefore we aimed to assess QoL and psychological distress in families affected by the PV.MethodsThis cross-sectional study included confirmed carriers and those with a 50% likelihood of carrying the PV (at-risk carriers) under cancer surveillance who were invited to complete a one-time questionnaire. Both confirmed and at-risk carriers are offered skin surveillance, whereas only confirmed carriers aged 40 years or older can participate in pancreatic surveillance.ResultsIn total, 59/247 (24%) individuals under skin surveillance only (skin surveillance group) and 188/290 (65%) individuals under both skin and pancreatic cancer surveillance (pancreatic surveillance group) responded. In both surveillance groups, health-related QoL and general distress levels were within the general population norms. However, more than 40% of all study participants reported melanoma-related distress. Pancreatic cancer-related distress was experienced by 45% of the pancreatic surveillance group. Determinants of cancer-related distress were a first-degree relative with melanoma or pancreatic cancer, increased cancer risk perception, and poor general health perception. Over 80% of the participants felt that the benefits of cancer surveillance outweigh the disadvantages.ConclusionIn conclusion, confirmed and at-risk carriers of the CDKN2A PV under cancer surveillance experienced similar levels of QoL and general distress compared to the general population. However, cancer-related worry was substantial in this population. These findings can help identify individuals who may benefit from psychological support.Cellular mechanisms in basic and clinical gastroenterology and hepatolog
Do local parties only mind their own business?: Explaining the deployment of large-scale solar energy projects in Germany
Get PDFInstitutions, Decisions and Collective Behaviou
Characterizing COPD phenotypes with a targeted signaling lipids metabolomics approach
Get PDFAnalytical BioScience
Performance and mechanisms of heterotrophic nitrification aerobic denitrifying bacteria in utilizing photogenerated electrons from magnetite for efficient denitrification
Get PDFHeterotrophic nitrification-aerobic denitrification bacteria (HN-AD) have been demonstrated to possess denitrification potential. The limited effectiveness of HN-AD in remediating nitrogen-polluted surface waters is attributed to its low C/N ratio. In this study, a magnetite photogenerated electrons coupled HN-AD bacteria system was constructed and its nitrogen removal mechanisms were revealed. The results demonstrated the electrons photo-generated by magnetite can effectively stimulate the growth of the HN-AD (Delftia sp., Y19).The coupled system of the ammonium and nitrate reached removal rates of 80.1 % and 71.3 %, which were 4 times higher than the strain Y19 alone (20.3 %, 15.2 %). Compared with dark conditions, the activity of enzymes (AMO, HAO, NAR and NIR) related to nitrogen removal in Y19 was increased by 4.81, 4.75, 6.45 and 4.78 times under sunlight irradiation, respectively. This suggests that the electrons photo-generated from magnetite can enhance the metabolic activities of the Y19 strain. Furthermore, the concentration of ferric ions dissolved from magnetite has been detected as equaling 0.13 mg/L, which plays a crucial role in the reduction of nitrate. The denitrification mechanisms of the coupled system can be incorporated: heterotrophic nitrification and aerobic denitrification by strain Y19, photogenerated electrons reduction of magnetite, the reduction of ferric ions, and the adsorption of magnetite. After 9 days of running the simulator, the magnetite-Y19 coupled system achieved removal rates of 100 % for nitrate and chemical oxygen demand, and 36 % for ammonium. This study offers novel insights into the utilization of photogenerated electrons by microorganisms for remediating the low C/N ratio wastewater.Environmental Biolog
Validation of left ventricular high frame rate echo-particle image velocimetry against 4D flow MRI in patients
Get PDFObjectiveAccurately measuring intracardiac flow patterns could provide insights into cardiac disease pathophysiology, potentially enhancing diagnostic and prognostic capabilities. This study aims to validate Echo-Particle Image Velocimetry (echoPIV) for in vivo left ventricular intracardiac flow imaging against 4D flow MRI.MethodsWe acquired high frame rate contrast-enhanced ultrasound images from three standard apical views of 26 patients who required cardiac MRI. 4D flow MRI was obtained for each patient. Only echo image planes with sufficient quality and alignment with MRI were included for validation. Regional velocity, kinetic energy (KE) and viscous energy loss (EL˙) were compared between modalities using normalized mean absolute error (NMAE), cosine similarity and Bland–Altman analysis.ResultsAmong 24 included apical view acquisitions, we observed good correspondence between echoPIV and MRI regarding spatial flow patterns and vortex traces. The velocity profile at base-level (mitral valve) cross-section had cosine similarity of 0.92 ± 0.06 and NMAE of (14 ± 5)%. Peak spatial mean velocity differed by (3 ± 6) cm/s in systole and (6 ± 10) cm/s in diastole. The KE and rate of EL˙ also revealed a high level of cosine similarity (0.89 ± 0.09 and 0.91 ± 0.06) with NMAE of (23 ± 7)% and (52 ± 16)%.ConclusionGiven good B-mode image quality, echoPIV provides a reliable estimation of left ventricular flow, exhibiting spatial-temporal velocity distributions comparable to 4D flow MRI. Both modalities present respective strengths and limitations: echoPIV captured inter-beat variability and had higher temporal resolution, while MRI was more robust to patient BMI and anatomy.</p
Cognitive impairment predicts medication discrepancies in Huntington's Disease: patient self-report compared to pharmacy records
Get PDFBackgroundProper medication reconciliation (= comparing the accuracy of patient-reported medication use with pharmacy records) could prevent potentially dangerous situations such as drug–drug interactions and hospitalization. This is particularly important when patients rely on multiple medications, such as in neurodegenerative disorders like Huntington’s Disease (HD). Currently, it is unknown how often medication discrepancies occur in HD patients and which factors contribute to the discrepancies.ObjectiveIdentify prognostic factors of medication discrepancies in HD, using patient-reported medication use and local pharmacy records.MethodsWith 134 pre- and manifest HD patients, we performed a multivariable logistic regression analysis with medication discrepancy as dependent variable (pharmacy records as reference value) and sex, CAP score, disease status (pre- or manifest HD), number of concomitant medications taken, presence of an informal caregiver, Unified Huntington’s Disease Rating Scale-Total Functioning Capacity, unified cognitive Z-score and Problem Behaviors Assessment-short characteristic scores for depression, anxiety, and apathy as independent variables.ResultsMedication discrepancies were reported frequently, both in premanifest (43.2%) and manifest HD subjects (36.7%). Impaired cognition significantly predicted medication discrepancies (beta = −0.688, SE 0.27, p = 0.011). All other variables were non-significant.ConclusionsRegardless of HD disease status and stage, patient self-reported medication use is not a reliable source, especially in those with impaired cognitive function. The presence of an informal caregiver and the absence of polypharmacy, depression, anxiety and apathy do not influence self-reported medication accuracy. Objective verification of medication use with HD patients’ local pharmacy is recommended.Neurological Motor Disorder