Explainable artificial intelligence for human-machine interaction in brain tumor localization

Primary malignancies in adult brains are globally fatal. Computer vision, especially recent developments in artificial intelligence (AI), have created opportunities to automatically characterize and diagnose tumor lesions in the brain. AI approaches have provided scores of unprecedented accuracy in different image analysis tasks, including differentiating tumor-containing brains from healthy brains. AI models, however, perform as a black box, concealing the rational interpretations that are an essential step towards translating AI imaging tools into clinical routine. An explainable AI approach aims to visualize the high-level features of trained models or integrate into the training process. This study aims to evaluate the performance of selected deep-learning algorithms on localizing tumor lesions and distinguishing the lesion from healthy regions in magnetic resonance imaging contrasts. Despite a significant correlation between classification and lesion localization accuracy (R = 0.46, p = 0.005), the known AI algorithms, examined in this study, classify some tumor brains based on other non-relevant features. The results suggest that explainable AI approaches can develop an intuition for model interpretability and may play an important role in the performance evaluation of deep learning models. Developing explainable AI approaches will be an essential tool to improve human–machine interactions and assist in the selection of optimal training methods.publishedVersio

Impact of Freezing Delay Time on Tissue Samples for Metabolomic Studies

Introduction: Metabolic profiling of intact tumor tissue by high resolution magic angle spinning (HR MAS) MR spectroscopy (MRS) provides important biological information possibly useful for clinical diagnosis and development of novel treatment strategies. However, generation of high-quality data requires that sample handling from surgical resection until analysis is performed using systematically validated procedures. In this study, we investigated the effect of postsurgical freezing delay time on global metabolic profiles and stability of individual metabolites in intact tumor tissue.Materials and methods: Tumor tissue samples collected from two patient-derived breast cancer xenograft models (n = 3 for each model) were divided into pieces that were snap-frozen in liquid nitrogen at 0, 15, 30, 60, 90, and 120 min after surgical removal. In addition, one sample was analyzed immediately, representing the metabolic profile of fresh tissue exposed neither to liquid nitrogen nor to room temperature. We also evaluated the metabolic effect of prolonged spinning during the HR MAS experiments in biopsies from breast cancer patients (n = 14). All samples were analyzed by proton HR MAS MRS on a Bruker Avance DRX600 spectrometer, and changes in metabolic profiles were evaluated using multivariate analysis and linear mixed modeling.Results: Multivariate analysis showed that the metabolic differences between the two breast cancer models were more prominent than variation caused by freezing delay time. No significant changes in levels of individual metabolites were observed in samples frozen within 30 min of resection. After this time point, levels of choline increased, whereas ascorbate, creatine, and glutathione (GS) levels decreased. Freezing had a significant effect on several metabolites but is an essential procedure for research and biobank purposes. Furthermore, four metabolites (glucose, glycine, glycerophosphocholine, and choline) were affected by prolonged HR MAS experiment time possibly caused by physical release of metabolites caused by spinning or due to structural degradation processes.Conclusion: The MR metabolic profiles of tumor samples are reproducible and robust to variation in postsurgical freezing delay up to 30 min

Filaggrin mutations in relation to skin barrier and atopic dermatitis in early infancy

Background Loss-of-function mutations in the skin barrier gene filaggrin (FLG) increase the risk of atopic dermatitis (AD), but their role in skin barrier function, dry skin and eczema in infancy is unclear. Objectives To determine the role of FLG mutations in impaired skin barrier function, dry skin, eczema and AD at 3 months of age and throughout infancy. Methods FLG mutations were analysed in 1836 infants in the Scandinavian population-based PreventADALL study. Transepidermal water loss (TEWL), dry skin, eczema and AD were assessed at 3, 6 and 12 months of age. Results FLG mutations were observed in 166 (9%) infants. At 3 months, carrying FLG mutations was not associated with impaired skin barrier function (TEWL > 11 center dot 3 g m(-2) h(-1)) or dry skin, but was associated with eczema [odds ratio (OR) 2 center dot 89, 95% confidence interval (CI) 1 center dot 95-4 center dot 28; P < 0 center dot 001]. At 6 months, mutation carriers had significantly higher TEWL than nonmutation carriers [mean 9 center dot 68 (95% CI 8 center dot 69-10 center dot 68) vs. 8 center dot 24 (95% CI 7 center dot 97-8 center dot 15), P < 0 center dot 01], and at 3 and 6 months mutation carriers had an increased risk of dry skin on the trunk (OR 1 center dot 87, 95% CI 1 center dot 25-2 center dot 80; P = 0 center dot 002 and OR 2 center dot 44, 95% CI 1 center dot 51-3 center dot 95; P < 0 center dot 001) or extensor limb surfaces (OR 1 center dot 52, 95% CI 1 center dot 04-2 center dot 22; P = 0 center dot 028 and OR 1 center dot 74, 95% CI 1 center dot 17-2 center dot 57; P = 0 center dot 005). FLG mutations were associated with eczema and AD in infancy. Conclusions FLG mutations were not associated with impaired skin barrier function or dry skin in general at 3 months of age, but increased the risk for eczema, and for dry skin on the trunk and extensor limb surfaces at 3 and 6 months.Peer reviewe

Fetal thoracic circumference and lung volume and their rlation to fetal size and pulmonary artery blood flow

Objective: Research on early origins of lung disease suggests the need for studying the relationships of thoracic and lung size with fetal size and pulmonary circulation. The primary aim of this study is therefore to explore the associations between fetal thoracic circumference, lung volume, and fetal size. We also aim to assess if lung volume and thoracic circumference are associated with fetal pulmonary artery blood flow velocity measures. Methods: Cross-sectional assessment of singleton pregnancies from the general population (n = 447) at 30 gestational weeks (GW) was performed using ultrasound measurement of fetal thoracic circumference, lung volume, head and abdominal circumference, and femur length. We obtained Doppler blood flow velocity measures from the proximal branches of the fetal pulmonary artery. Associations between variables were studied using Pearson's correlation and multiple linear regression analyses. Results: Both thoracic circumference and lung volume correlated with fetal size measures, ranging from r = 0.64 between thoracic circumference and abdominal circumference, to r = 0.28 between lung volume and femur length. Adjustment for gestational age, maternal nicotine use, pre-pregnancy body mass index, and fetal sex marginally influenced the associations with abdominal circumference. The correlations of thoracic circumference and lung volume with pulmonary artery blood flow velocity measures were weak (r ≤ 0.17). Conclusion: We found moderate to low correlation between thoracic circumference, lung volume, and fetal size at 30 GW. The closest relationship was with the abdominal circumference. We found low correlations of thoracic circumference and lung volume with pulmonary artery blood flow velocity measures.publishedVersio

Maternal human papillomavirus infection during pregnancy and preterm delivery, a mother–child cohort study in Norway and Sweden

Introduction: Human papillomavirus (HPV) infection is common in women of reproductive age. Infection and inflammation are leading causes for preterm delivery (PTD), but the role of HPV infection in PTD and prelabor rupture of membranes (PROM) is unclear. We aimed to explore whether HPV infection during pregnancy in general, and high-risk-HPV (HR-HPV) infection specifically, increased the risk of PTD, preterm prelabor rupture of membranes (PPROM), PROM at term, and/or chorioamnionitis. Material and Methods: In pregnant women, who were participating in a prospective multicenter cohort study from a general population in Norway and Sweden (PreventADALL, ClinicalTrials.gov NCT02449850), HPV DNA was analyzed in available urine samples at mid-gestation (16–22 weeks) and at delivery, and in the placenta after delivery with Seegene Anyplex II HPV28 PCR assay. The risk of PTD, PPROM, PROM, and chorioamnionitis was analyzed using unadjusted and adjusted logistic regression analyses for any 28 HPV genotypes, including 12 HR-HPV genotypes, compared with HPV-negative women. Further, subgroups of HPV (low-risk/possibly HR-HPV, HR-HPV-non-16 and HR-HPV-16), persistence of HR-HPV from mid-gestation to delivery, HR-HPV-viral load, and presence of multiple HPV infections were analyzed for the obstetric outcomes. Samples for HPV analyses were available from 950 women with singleton pregnancies (mean age 32 years) at mid-gestation and in 753 also at delivery. Results: At mid-gestation, 40% of women were positive for any HPV and 24% for HR-HPV. Of the 950 included women, 23 had PTD (2.4%), nine had PPROM (0.9%), and six had chorioamnionitis (0.6%). Of the term pregnancies, 25% involved PROM. The frequency of PTD was higher in HR-HPV-positive women (8/231, 3.5%) than in HPV-negative women (13/573, 2.3%) at mid-gestation, but the association was not statistically significant (odds ratio 1.55; 95% confidence interval 0.63–3.78). Neither any HPV nor subgroups of HPV at mid-gestation or delivery, nor persistence of HR-HPV was significantly associated with increased risk for PTD, PPROM, PROM, or chorioamnionitis. No HPV DNA was detected in placentas of women with PTD, PPROM or chorioamnionitis. Conclusions: HPV infection during pregnancy was not significantly associated with increased risk for PTD, PPROM, PROM, or chorioamnionitis among women from a general population with a low incidence of adverse obstetric outcomes

mRNA Coronavirus Disease 2019 Vaccine-Associated Myopericarditis in Adolescents: A Survey Study

In this survey study of institutions across the US, marked variability in evaluation, treatment, and follow-up of adolescents 12 through 18 years of age with mRNA coronavirus disease 2019 (COVID-19) vaccine-associated myopericarditis was noted. Only one adolescent with life-threatening complications was reported, with no deaths at any of the participating institutions

Explainable artificial intelligence for human-machine interaction in brain tumor localization

Primary malignancies in adult brains are globally fatal. Computer vision, especially recent developments in artificial intelligence (AI), have created opportunities to automatically characterize and diagnose tumor lesions in the brain. AI approaches have provided scores of unprecedented accuracy in different image analysis tasks, including differentiating tumor-containing brains from healthy brains. AI models, however, perform as a black box, concealing the rational interpretations that are an essential step towards translating AI imaging tools into clinical routine. An explainable AI approach aims to visualize the high-level features of trained models or integrate into the training process. This study aims to evaluate the performance of selected deep-learning algorithms on localizing tumor lesions and distinguishing the lesion from healthy regions in magnetic resonance imaging contrasts. Despite a significant correlation between classification and lesion localization accuracy (R = 0.46, p = 0.005), the known AI algorithms, examined in this study, classify some tumor brains based on other non-relevant features. The results suggest that explainable AI approaches can develop an intuition for model interpretability and may play an important role in the performance evaluation of deep learning models. Developing explainable AI approaches will be an essential tool to improve human–machine interactions and assist in the selection of optimal training methods

Do trauma safety-net hospitals deliver truly safe trauma care? A multilevel analysis of the national trauma data bank

Background: Patients treated at safety-net hospitals, facilities that care for a high percentage of uninsured patients, are known to have worse outcomes. This study seeks to analyze whether care at trauma safety-net hospitals (TSNH) accounts for the known mortality disparity between uninsured and insured trauma patients. Methods: A retrospective analysis of trauma patients (age, 18-64 years) in the National Trauma Data Bank (6.2; 2001-2005) with moderate to severe injury (Injury Severity Score ≥9) was performed. TSNH were defined as facilities treating ≥47% uninsured trauma patients. The main outcome measure was adjusted mortality of patients treated at TSNH versus non-TSNH. A multilevel analysis using multiple logistic regression and generalized estimating equations was performed to control for both hospital and patient-level characteristics (age, gender, insurance, injury severity, shock, and type and mechanism of injury). Subset analyses by hospital trauma level designation and patient injury severity and type were also performed. Results: Collectively 343,053 trauma patients were treated at 46 TSNH and 413 non-TSNH. TSNH patients (n = 36,774) were more likely to be minorities (55% vs. 27%; p \u3c 0.05) compared with non-TSNH patients (n = 306,279). Unadjusted mortality was greater in TSNH versus non-TSNH patients (6.8% vs. 4.6%; *p \u3c 0.05). After controlling for patient- and hospital-level factors, patients at TSNH and non-TSNH facilities had equivalent odds ratio of death = 0.93 (95% confidence interval = 0.65-1.32). Similar results were obtained in all subset analyses. Conclusion: Patients treated at TSNH have equivalent mortality compared with those treated at non-TSNH. Disparate trauma outcomes due to insurance status are not explained by differences between trauma treating institution