Investigating MRI-Associated Biological Aspects of Racial Disparities in Prostate Cancer for African American and White Men.

BACKGROUND: Understanding the characteristics of multiparametric MRI (mpMRI) in patients from different racial/ethnic backgrounds is important for reducing the observed gaps in clinical outcomes. PURPOSE: To investigate the diagnostic performance of mpMRI and quantitative MRI parameters of prostate cancer (PCa) in African American (AA) and matched White (W) men. STUDY TYPE: Retrospective. SUBJECTS: One hundred twenty-nine patients (43 AA, 86 W) with histologically proven PCa who underwent mpMRI before radical prostatectomy. FIELD STRENGTH/SEQUENCE: 3.0 T, T2-weighted turbo spin echo imaging, a single-shot spin-echo EPI sequence diffusion-weighted imaging, and a gradient echo sequence dynamic contrast-enhanced MRI with an ultrafast 3D spoiled gradient-echo sequence. ASSESSMENT: The diagnostic performance of mpMRI in AA and W men was assessed using detection rates (DRs) and positive predictive values (PPVs) in zones defined by the PI-RADS v2.1 prostate sector map. Quantitative MRI parameters, including Ktrans and ve of clinically significant (cs) PCa (Gleason score ≥ 7) tumors were compared between AA and W sub-cohorts after matching age, prostate-specific antigen (PSA), and prostate volume. STATISTICAL TESTS: Weighted Pearson's chi-square and Mann-Whitney U tests with a statistically significant level of 0.05 were used to examine differences in DR and PPV and to compare parameters between AA and matched W men, respectively. RESULTS: A total number of 264 PCa lesions were identified in the study cohort. The PPVs in the peripheral zone (PZ) and posterior prostate of mpMRI for csPCa lesions were significantly higher in AA men than in matched W men (87.8% vs. 68.1% in PZ, and 89.3% vs. 69.6% in posterior prostate). The Ktrans of index csPCa lesions in AA men was significantly higher than in W men (0.25 ± 0.12 vs. 0.20 ± 0.08 min-1; P < 0.01). DATA CONCLUSION: This study demonstrated race-related differences in the diagnostic performances and quantitative MRI measures of csPCa that were not reflected in age, PSA, and prostate volume. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

nnUNet for Automatic Kidney and Cyst Segmentation in Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND: Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a genetic disorder that causes uncontrolled kidney cyst growth, leading to kidney volume enlargement and renal function loss over time. Total kidney volume (TKV) and cyst burdens have been used as prognostic imaging biomarkers for ADPKD. OBJECTIVE: This study aimed to evaluate nnUNet for automatic kidney and cyst segmentation in T2-weighted (T2W) MRI images of ADPKD patients. METHODS: 756 kidney images were retrieved from 95 patients in the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) cohort (95 patients × 2 kidneys × 4 follow-up scans). The nnUNet model was trained, validated, and tested on 604, 76, and 76 images, respectively. In contrast, all images of each patient were exclusively assigned to either the training, validation, or test sets to minimize evaluation bias. The kidney and cyst regions defined using a semi-automatic method were employed as ground truth. The model performance was assessed using the Dice Similarity Coefficient (DSC), the intersection over union (IoU) score, and the Hausdorff distance (HD). RESULTS: The test DSC values were 0.96±0.01 (mean±SD) and 0.90±0.05 for kidney and cysts, respectively. Similarly, the IoU scores were 0.91± 0.09 and 0.81±0.06, and the HD values were 12.49±8.71 mm and 12.04±10.41 mm, respectively, for kidney and cyst segmentation. CONCLUSION: The nnUNet model is a reliable tool to automatically determine kidney and cyst volumes in T2W MRI images for ADPKD prognosis and therapy monitoring.

Deep learning-based automated kidney and cyst segmentation of autosomal dominant polycystic kidney disease using single vs. multi-institutional data.

PURPOSE: This study aimed to investigate if a deep learning model trained with a single institution's data has comparable accuracy to that trained with multi-institutional data for segmenting kidney and cyst regions in magnetic resonance (MR) images of patients affected by autosomal dominant polycystic kidney disease (ADPKD). METHODS: We used TensorFlow with a Keras custom UNet on 2D slices of 756 MRI images of kidneys with ADPKD obtained from four institutions in the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study. The ground truth was determined via a manual plus global thresholding method. Five models were trained with 80 % of all institutional data (n = 604) and each institutional data (n = 232, 172, 148, or 52), respectively, and validated with 10 % and tested on an unseen 10 % of the data. The model's performance was evaluated using the Dice Similarity Coefficient (DSC). RESULTS: The DSCs by the model trained with all institutional data ranged from 0.92 to 0.95 for kidney image segmentation, only 1-2 % higher than those by the models trained with single institutional data (0.90-0.93).In cyst segmentation, however, the DSCs by the model trained with all institutional data ranged from 0.83 to 0.89, which were 2-20 % higher than those by the models trained with single institutional data (0.66-0.86). CONCLUSION: The UNet performance, when trained with a single institutional dataset, exhibited similar accuracy to the model trained on a multi-institutional dataset. Segmentation accuracy increases with models trained on larger sample sizes, especially in more complex cyst segmentation.

The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge.

PURPOSE: K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for K trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize K trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS: A framework was created to evaluate K trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.

Technical note: 3D-printed MRI-compatible syringe pump.

BACKGROUND: A power injector is typically employed to deliver a contrast agent to a subject (e.g., humans, animals, phantoms) during MRI, but it is costly and cannot inject more than one subject at a time. Conventional syringe pumps housing multiple syringes are typically non-MRI compatible and, thus, should be placed outside the MRI room. PURPOSE: To develop the prototype of a cost-effective, easy-to-use, reliable syringe pump that could be deployed inside a clinical MRI bore and operated on during a scan. METHODS: The MRI-compatible syringe pump (MSP) was designed using Solidworks 3D modeling software and fabricated using a Raise3D Pro2 Printer. The MSP was designed to infuse up to three syringes simultaneously. The injection speed was mainly controlled with different gear sets in the escapement unit and further adjusted by changing the effective hairspring length via a pinch pin. The MSP was evaluated with three gear sets (gear ratios: 0.20:1, 0.56:1, and 1.09:1) and 10 different effective hairspring lengths at each gear ratio. A video was recorded while operating MSP at each injection speed to calculate the volume injection rate of a 5-mL syringe (mL/s). The MSP was operated five times repeatedly at each injection speed, and the mean and standard deviation of the volume injection rate were calculated. RESULTS: The volume injection rates produced by three gear ratios (0.20:1, 0.56:1, and 1.09:1) were 0.209 ± 0.003 mL/s, 0.411 ± 0.002 mL/s, and 0.625 ± 0.006 mL/s, respectively, at the full hairspring length. The injection rates of gear set 1 (gear ratio: 0.20:1) decreased from 0.273 ± 0.001 mL/s to 0.245 ± 0.001 mL/s with a decrement of 0.003 mL/s for 10 different effective hairspring lengths (r = 0.997, p < 0.001). The injection rates of gear set 2 (gear ratio: 0.56:1) decreased from 0.519 ± 0.003 mL/s to 0.469 ± 0.003 mL/s with a decrement of 0.006 mL/s (r = 0.987, p < 0.001), and that of gear set 3 (gear ratio: 1.09:1) decreased from 0.779 ± 0.012 mL/s to 0.709 ± 0.005 mL/s with a decrement of 0.007 mL/s (r = 0.963, p < 0.001). The coefficient of variation in the injection rate measurement was 0.727 ± 0.346%. CONCLUSIONS: The MSP is a portable device that can reliably deliver a liquid agent to multiple subjects inside a clinical MRI bore during a scan.

Mucociliary Clearance Augmenting Drugs Block SARS-Cov-2 Replication in Human Airway Epithelial Cells.

The coronavirus disease (COVID-19) pandemic, caused by SARS-CoV-2 coronavirus, is devastatingly impacting human health. A prominent component of COVID-19 is the infection and destruction of the ciliated respiratory cells, which perpetuates dissemination and disrupts protective mucociliary transport (MCT) function, an innate defense of the respiratory tract. Thus, drugs that augment MCT could improve barrier function of the airway epithelium, reduce viral replication and, ultimately, COVID-19 outcomes. We tested five agents known to increase MCT through distinct mechanisms for activity against SARS-CoV-2 infection using a model of human respiratory epithelial cells terminally differentiated in an air/liquid interphase. Three of the five mucoactive compounds tested showed significant inhibitory activity against SARS-CoV-2 replication. An archetype mucoactive agent, ARINA-1, blocked viral replication and therefore epithelial cell injury, thus, it was further studied using biochemical, genetic and biophysical methods to ascertain mechanism of action via improvement of MCT. ARINA-1 antiviral activity was dependent on enhancing the MCT cellular response, since terminal differentiation, intact ciliary expression and motion was required for ARINA-1-mediated anti-SARS-CoV2 protection. Ultimately, we showed that improvement of cilia movement was caused by ARINA-1-mediated regulation of the redox state of the intracellular environment, which benefited MCT. Our study indicates that Intact MCT reduces SARS-CoV-2 infection, and its pharmacologic activation may be effective as an anti-COVID-19 treatment.

Cutaneous Exposure to Arsenicals Is Associated with Development of Constrictive Bronchiolitis in Mice.

Organoarsenicals, such as lewisite and related chloroarsine, diphenylchloroarsine (DPCA), are chemical warfare agents developed during World War I. Stockpiles in Eastern Europe remain a threat to humans. The well-documented effects of cutaneous exposure to these organoarsenicals include skin blisters, painful burns, and life-threatening conditions such as acute respiratory distress syndrome. In survivors, long-term effects such as the development of respiratory ailments are reported for the organoarsenical sulfur mustard; however, no long-term pulmonary effects are documented for lewisite and DPCA. No animal models exist to explore the relationship between skin exposure to vesicants and constrictive bronchiolitis. We developed and characterized a mouse model to study the long-term effects of cutaneous exposure on the lungs after exposure to a sublethal dose of organoarsenicals. We exposed mice to lewisite, DPCA, or a less toxic surrogate organoarsenic chemical, phenyl arsine oxide, on the skin. The surviving mice were followed for 20 weeks after skin exposure to arsenicals. Lung microcomputed tomography, lung function, and histology demonstrated increased airway resistance, increased thickness of the smooth muscle layer, increased collagen deposition in the subepithelium, and peribronchial lymphocyte infiltration in mice exposed to arsenical on skin.

Racial Disparities in Quantitative MRI for African American and White Men with Prostate Cancer.

The risk of prostate cancer (PCa) is strongly influenced by race and ethnicity. The purpose of this study is to investigate differences in the diagnostic performance of multiparametric MRI (mpMRI) in African American (AA) and white (W) men. 111 patients (37 AA and 74 W men) were selected from the study's initial cohort of 885 patients after matching age, prostate-specific antigen, and prostate volume. The diagnostic performance of mpMRI was assessed using detection rates (DRs) and positive predictive values (PPVs) with/without combining Ktrans (volume transfer constant) stratified by prostate zones for AA and W sub-cohorts. The DRs of mpMRI for clinically significant PCa (csPCa) lesions in AA and W sub-cohort with PI-RADS scores ≥ 3 were 67.3% vs. 80.3% in the transition zone (TZ; p=0.026) and 81.2% vs. 76.1% in the peripheral zone (PZ; p>0.9). The Ktrans of csPCa in AA men was significantly higher than in W men (0.23±0.08 min-1 vs. 0.19±0.07 min-1; p=0.022). This emphasizes that there are race-related differences in the performance of mpMRI and quantitative MRI measures that are not reflected in age, PSA, and prostate volume.

Accuracy and processing time of kidney volume measurement methods in rodents polycystic kidney disease models: superiority of semiautomated kidney segmentation.

Measurement of total kidney volume (TKV) using magnetic resonance imaging (MRI) is a valuable approach for monitoring disease progression in autosomal dominant polycystic kidney disease (PKD) and is becoming more common in preclinical studies using animal models. Manual contouring of kidney MRI areas [i.e., manual method (MM)] is a conventional, but time-consuming, way to determine TKV. We developed a template-based semiautomatic image segmentation method (SAM) and validated it in three commonly used PKD models: Cys1cpk/cpk mice, Pkd1RC/RC mice, and Pkhd1pck/pck rats (n = 10 per model). We compared SAM-based TKV with that obtained by clinical alternatives including the ellipsoid formula-based method (EM) using three kidney dimensions, the longest kidney length method (LM), and MM, which is considered the gold standard. Both SAM and EM presented high accuracy in TKV assessment in Cys1cpk/cpk mice [interclass correlation coefficient (ICC) ≥ 0.94]. SAM was superior to EM and LM in Pkd1RC/RC mice (ICC = 0.87, 0.74, and <0.10 for SAM, EM, and LM, respectively) and Pkhd1pck/pck rats (ICC = 0.59, <0.10, and <0.10, respectively). Also, SAM outperformed EM in processing time in Cys1cpk/cpk mice (3.6 ± 0.6 vs. 4.4 ± 0.7 min/kidney) and Pkd1RC/RC mice (3.1 ± 0.4 vs. 7.1 ± 2.6 min/kidney, both P < 0.001) but not in Pkhd1PCK/PCK rats (3.7 ± 0.8 vs. 3.2 ± 0.5 min/kidney). LM was the fastest (∼1 min) but correlated most poorly with MM-based TKV in all studied models. Processing times by MM were longer for Cys1cpk/cpk mice, Pkd1RC/RC mice, and Pkhd1pck.pck rats (66.1 ± 7.3, 38.3 ± 7.5, and 29.2 ± 3.5 min). In summary, SAM is a fast and accurate method to determine TKV in mouse and rat PKD models.NEW & NOTEWORTHY Total kidney volume (TKV) is a valuable readout in preclinical studies for autosomal dominant and autosomal recessive polycystic kidney diseases (ADPKD and ARPKD). Since conventional TKV assessment by manual contouring of kidney areas in all images is time-consuming, we developed a template-based semiautomatic image segmentation method (SAM) and validated it in three commonly used ADPKD and ARPKD models. SAM-based TKV measurements were fast, highly reproducible, and accurate across mouse and rat ARPKD and ADPKD models.

Mucociliary clearance augmenting drugs block SARS-CoV-2 replication in human airway epithelial cells.

The coronavirus disease (COVID-19) pandemic, caused by SARS-CoV-2 coronavirus, is devastatingly impacting human health. A prominent component of COVID-19 is the infection and destruction of the ciliated respiratory cells, which perpetuates dissemination and disrupts protective mucociliary transport (MCT) function, an innate defense of the respiratory tract. Thus, drugs that augment MCT could improve the barrier function of the airway epithelium and reduce viral replication and, ultimately, COVID-19 outcomes. We tested five agents known to increase MCT through distinct mechanisms for activity against SARS-CoV-2 infection using a model of human respiratory epithelial cells terminally differentiated in an air/liquid interphase. Three of the five mucoactive compounds tested showed significant inhibitory activity against SARS-CoV-2 replication. An archetype mucoactive agent, ARINA-1, blocked viral replication and therefore epithelial cell injury; thus, it was further studied using biochemical, genetic, and biophysical methods to ascertain the mechanism of action via the improvement of MCT. ARINA-1 antiviral activity was dependent on enhancing the MCT cellular response, since terminal differentiation, intact ciliary expression, and motion were required for ARINA-1-mediated anti-SARS-CoV2 protection. Ultimately, we showed that the improvement of cilia movement was caused by ARINA-1-mediated regulation of the redox state of the intracellular environment, which benefited MCT. Our study indicates that intact MCT reduces SARS-CoV-2 infection, and its pharmacologic activation may be effective as an anti-COVID-19 treatment.

Mucociliary transport deficiency and disease progression in Syrian hamsters with SARS-CoV-2 infection.

Substantial clinical evidence supports the notion that ciliary function in the airways is important in COVID-19 pathogenesis. Although ciliary damage has been observed in both in vitro and in vivo models, the extent or nature of impairment of mucociliary transport (MCT) in in vivo models remains unknown. We hypothesize that SARS-CoV-2 infection results in MCT deficiency in the airways of golden Syrian hamsters that precedes pathological injury in lung parenchyma. Micro-optical coherence tomography was used to quantitate functional changes in the MCT apparatus. Both genomic and subgenomic viral RNA pathological and physiological changes were monitored in parallel. We show that SARS-CoV-2 infection caused a 67% decrease in MCT rate as early as 2 days postinfection (dpi) in hamsters, principally due to 79% diminished airway coverage of motile cilia. Correlating quantitation of physiological, virological, and pathological changes reveals steadily descending infection from the upper airways to lower airways to lung parenchyma within 7 dpi. Our results indicate that functional deficits of the MCT apparatus are a key aspect of COVID-19 pathogenesis, may extend viral retention, and could pose a risk factor for secondary infection. Clinically, monitoring abnormal ciliated cell function may indicate disease progression. Therapies directed toward the MCT apparatus deserve further investigation.

Perfusion Change of Hepatocellular Carcinoma During Atezolizumab plus Bevacizumab Treatment: A Pilot Study.

PURPOSE: To investigate whether the early perfusion change in hepatocellular carcinoma (HCC) predicts the long-term therapeutic response to atezolizumab plus bevacizumab. METHODS: We retrospectively selected 19 subjects (median age: 62 years, 4 females, and 15 males) having advanced HCC and treated with atezolizumab alone (n = 3) or in combination with bevacizumab (n = 16). The 4-phased CT or MRI imaging was performed for each subject before and at 9 ± 2 and 21 ± 5 weeks after therapy initiation. The tumor-to-liver signal ratio in the arterial phase was used to estimate the tumor perfusion. The change in tumor perfusion from the baseline to the 1st follow-up exam was correlated with the tumor response evaluated using mRECIST at the 2nd follow-up exam. The difference between favorably responding and non-responding groups was statistically analyzed using one-way ANOVA. RESULTS: The mean tumor long axis in the baseline image was 59 ± 47 mm. The HCC perfusion changes were -26 ± 18% for complete (or partial) response (CR/PR, n = 8), -24 ± 12% for stable disease (SD, n = 8), and 9 ± 13% for progressive disease (PD, n = 3). The HCC perfusion change of the CR/PR groups was significantly lower than that of the PD group (p = 0.0040). The HCC perfusion changes between the SD and PD groups were also significantly different (p = 0.0135). The sensitivity and specificity of the early perfusion change to predict the long-term progression of the disease were 100 and 94%, respectively. CONCLUSION: The early change in HCC perfusion may predict the long-term therapeutic response to atezolizumab plus bevacizumab, promoting personalized treatment for HCC patients.

Mucociliary Transport Deficiency and Disease Progression in Syrian Hamsters with SARS-CoV-2 Infection.

Substantial clinical evidence supports the notion that ciliary function in the airways plays an important role in COVID-19 pathogenesis. Although ciliary damage has been observed in both in vitro and in vivo models, consequent impaired mucociliary transport (MCT) remains unknown for the intact MCT apparatus from an in vivo model of disease. Using golden Syrian hamsters, a common animal model that recapitulates human COVID-19, we quantitatively followed the time course of physiological, virological, and pathological changes upon SARS-CoV-2 infection, as well as the deficiency of the MCT apparatus using micro-optical coherence tomography, a novel method to visualize and simultaneously quantitate multiple aspects of the functional microanatomy of intact airways. Corresponding to progressive weight loss up to 7 days post-infection (dpi), viral detection and histopathological analysis in both the trachea and lung revealed steadily descending infection from the upper airways, as the main target of viral invasion, to lower airways and parenchymal lung, which are likely injured through indirect mechanisms. SARS-CoV-2 infection caused a 67% decrease in MCT rate as early as 2 dpi, largely due to diminished motile ciliation coverage, but not airway surface liquid depth, periciliary liquid depth, or cilia beat frequency of residual motile cilia. Further analysis indicated that the fewer motile cilia combined with abnormal ciliary motion of residual cilia contributed to the delayed MCT. The time course of physiological, virological, and pathological progression suggest that functional deficits of the MCT apparatus predispose to COVID-19 pathogenesis by extending viral retention and may be a risk factor for secondary infection. As a consequence, therapies directed towards the MCT apparatus deserve further investigation as a treatment modality.

Evaluation of a novel CFTR potentiator in COPD ferrets with acquired CFTR dysfunction.

RATIONALE: The majority of chronic obstructive pulmonary disease (COPD) patients have chronic bronchitis, for which specific therapies are unavailable. Acquired cystic fibrosis transmembrane conductance regulator (CFTR) dysfunction is observed in chronic bronchitis, but has not been proven in a controlled animal model with airway disease. Furthermore, the potential of CFTR as a therapeutic target has not been tested in vivo, given limitations to rodent models of COPD. Ferrets exhibit cystic fibrosis-related lung pathology when CFTR is absent and COPD with bronchitis following cigarette smoke exposure. OBJECTIVES: To evaluate CFTR dysfunction induced by smoking and test its pharmacological reversal by a novel CFTR potentiator, GLPG2196, in a ferret model of COPD with chronic bronchitis. METHODS: Ferrets were exposed for 6 months to cigarette smoke to induce COPD and chronic bronchitis and then treated with enteral GLPG2196 once daily for 1 month. Electrophysiological measurements of ion transport and CFTR function, assessment of mucociliary function by one-micron optical coherence tomography imaging and particle-tracking microrheology, microcomputed tomography imaging, histopathological analysis and quantification of CFTR protein and mRNA expression were used to evaluate mechanistic and pathophysiological changes. MEASUREMENTS AND MAIN RESULTS: Following cigarette smoke exposure, ferrets exhibited CFTR dysfunction, increased mucus viscosity, delayed mucociliary clearance, airway wall thickening and airway epithelial hypertrophy. In COPD ferrets, GLPG2196 treatment reversed CFTR dysfunction, increased mucus transport by decreasing mucus viscosity, and reduced bronchial wall thickening and airway epithelial hypertrophy. CONCLUSIONS: The pharmacologic reversal of acquired CFTR dysfunction is beneficial against pathological features of chronic bronchitis in a COPD ferret model.

Disposable point-of-care portable perfusion phantom for quantitative DCE-MRI.

PURPOSE: To develop a disposable point-of-care portable perfusion phantom (DP4) and validate its clinical utility in a multi-institutional setting for quantitative dynamic contrast-enhanced magnetic resonance imaging (qDCE-MRI). METHODS: The DP4 phantom was designed for single-use and imaged concurrently with a human subject so that the phantom data can be utilized as the reference to detect errors in qDCE-MRI measurement of human tissues. The change of contrast-agent concentration in the phantom was measured using liquid chromatography-mass spectrometry. The repeatability of the contrast enhancement curve (CEC) was assessed with five phantoms in a single MRI scanner. Five healthy human subjects were recruited to evaluate the reproducibility of qDCE-MRI measurements. Each subject was imaged concurrently with the DP4 phantom at two institutes using three 3T MRI scanners from three different vendors. Pharmacokinetic (PK) parameters in the regions of liver, spleen, pancreas, and paravertebral muscle were calculated based on the Tofts model (TM), extended Tofts model (ETM), and shutter speed model (SSM). The reproducibility of each PK parameter over three measurements was evaluated with the intraclass correlation coefficient (ICC) and compared before and after DP4-based error correction. RESULTS: The contrast-agent concentration in the DP4 phantom was linearly increased over 10 min (0.17 mM/min, measurement accuracy: 96%) after injecting gadoteridol (100 mM) at a constant rate (0.24 ml/s, 4 ml). The repeatability of the CEC within the phantom was 0.997 when assessed by the ICC. The reproducibility of the volume transfer constant, Ktrans , was the highest of the PK parameters regardless of the PK models. The ICCs of Ktrans in the TM, ETM, and SSM before DP4-based error correction were 0.34, 0.39, and 0.72, respectively, while those increased to 0.93, 0.98, and 0.86, respectively, after correction. CONCLUSIONS: The DP4 phantom is reliable, portable, and capable of significantly improving the reproducibility of qDCE-MRI measurements.

Circular economy as a key for industrial value chain resilience in a post-COVID world: what do future engineers think?

While the COVID-19 pandemic has led to many disruptions in industrial value chains, the adoption of circular economy (CE) principles appears to be a commendable solution for more robust, resilient, and sustainable industrial supply chains. In this study, the standpoints and visions of two consecutive classes of engineering students - following the course "Circular Economy & Industrial Systems" at the Université Paris-Saclay - are given on how they value CE strategies to mitigate the impact of COVID-19 on industrial practices. Capturing and understanding the viewpoints of the engineers of tomorrow on such a pressing issue is key to train and provide them with the suitable methods and tools to build a more circular and sustainable society. At the end of their eight-week training class, including theoretical background on industrial ecology tools, workshops, and a hands-on project, part of the final exam included a one-hour essay in which the students had to argue their position on the following questions: (i) "Circular Economy as an answer to the COVID-19 crisis?" for the class of 2020, and (ii) "Circular Economy as an answer for green recovery and value chain resiliency in the COVID-19 context?" for the class of 2021. Interestingly, the evolution of viewpoints between the beginning of the COVID-19 crisis (exam conducted in May 2020 for the first class) and one year after (exam conducted in Mars 2021 for the second class) is discussed and illustrated. Also, the answers and insights provided by engineering students on these questions are positioned within the state-of-the-art literature on the topic. Last but not least, key recommendations and challenges on how CE could alleviate COVID-related disruptions and production shortages are synthesized in a SWOT (strengths, weaknesses, threats, and opportunities) diagram.

Designing optimal COVID-19 testing stations locally: A discrete event simulation model applied on a university campus.

Providing sufficient testing capacities and accurate results in a time-efficient way are essential to prevent the spread and lower the curve of a health crisis, such as the COVID-19 pandemic. In line with recent research investigating how simulation-based models and tools could contribute to mitigating the impact of COVID-19, a discrete event simulation model is developed to design optimal saliva-based COVID-19 testing stations performing sensitive, non-invasive, and rapid-result RT-qPCR tests processing. This model aims to determine the adequate number of machines and operators required, as well as their allocation at different workstations, according to the resources available and the rate of samples to be tested per day. The model has been built and experienced using actual data and processes implemented on-campus at the University of Illinois at Urbana-Champaign, where an average of around 10,000 samples needed to be processed on a daily basis, representing at the end of August 2020 more than 2% of all the COVID-19 tests performed per day in the USA. It helped identify specific bottlenecks and associated areas of improvement in the process to save human resources and time. Practically, the overall approach, including the proposed modular discrete event simulation model, can easily be reused or modified to fit other contexts where local COVID-19 testing stations have to be implemented or optimized. It could notably support on-site managers and decision-makers in dimensioning testing stations by allocating the appropriate type and quantity of resources.

NETosis in the pathogenesis of acute lung injury following cutaneous chemical burns.

Despite the high morbidity and mortality among patients with extensive cutaneous burns in the intensive care unit due to the development of acute respiratory distress syndrome, effective therapeutics remain to be determined. This is primarily because the mechanisms leading to acute lung injury (ALI) in these patients remain unknown. We test the hypothesis that cutaneous chemical burns promote lung injury due to systemic activation of neutrophils, in particular, toxicity mediated by the deployment of neutrophil extracellular traps (NETs). We also demonstrate the potential benefit of a peptidyl arginine deiminase 4 (PAD4) inhibitor to prevent NETosis and to preserve microvascular endothelial barrier function, thus reducing the severity of ALI in mice. Our data demonstrated that phenylarsine oxide (PAO) treatment of neutrophils caused increased intracellular Ca2+-associated PAD4 activity. A dermal chemical burn by lewisite or PAO resulted in PAD4 activation, NETosis, and ALI. NETs disrupted the barrier function of endothelial cells in human lung microvascular endothelial cell spheroids. Citrullinated histone 3 alone caused ALI in mice. Pharmacologic or genetic abrogation of PAD4 inhibited lung injury following cutaneous chemical burns. Cutaneous burns by lewisite and PAO caused ALI by PAD4-mediated NETosis. PAD4 inhibitors may have potential as countermeasures to suppress detrimental lung injury after chemical burns.

A Discrete Event Simulation-Based Model to Optimally Design and Dimension Mobile COVID-19 Saliva-Based Testing Stations.

SUMMARY STATEMENT: The present COVID-19 brief report addresses: (1) the problem of optimal design and resource allocation to mobile testing stations to ensure rapid results to the persons getting tested; (2) the proposed solution through a newly developed discrete event simulation model, experienced in on-campus saliva-based testing stations at the University of Illinois at Urbana-Champaign; and (3) the lessons learned on how 10,000 samples (from noninvasive polymerase chain reaction COVID-19 tests) can be processed per day on campus, as well as how the model could be reused or adapted to other contexts by site managers and decision makers.