scholarly journals Altered relaxation times in MRI indicate bronchopulmonary dysplasia

Thorax ◽  
2019 ◽  
Vol 75 (2) ◽  
pp. 184-187 ◽  
Author(s):  
Kai Förster ◽  
Birgit Ertl-Wagner ◽  
Harald Ehrhardt ◽  
Hannah Busen ◽  
Steffen Sass ◽  
...  
Keyword(s):  
Relaxation Time ◽  
Bronchopulmonary Dysplasia ◽  
Structural Changes ◽  
Relaxation Times ◽  
Area Under The Curve ◽  
Independent Study ◽  
Study Cohort ◽  
Lasso Regression ◽  
Quiet Sleep ◽  
Mri Protocol

We developed a MRI protocol using transverse (T2) and longitudinal (T1) mapping sequences to characterise lung structural changes in preterm infants with bronchopulmonary dysplasia (BPD). We prospectively enrolled 61 infants to perform 3-Tesla MRI of the lung in quiet sleep. Statistical analysis was performed using logistic Group Lasso regression and logistic regression. Increased lung T2 relaxation time and decreased lung T1 relaxation time indicated BPD yielding an area under the curve (AUC) of 0.80. Results were confirmed in an independent study cohort (AUC 0.75) and mirrored by lung function testing, indicating the high potential for MRI in future BPD diagnostics.Trial registrationDRKS00004600.

scholarly journals T2 mapping of the peritumoral infiltration zone of glioblastoma and anaplastic astrocytoma

2021 ◽  
pp. 197140092198932
Author(s):  
Timo Alexander Auer ◽  
Maike Kern ◽  
Uli Fehrenbach ◽  
Yasemin Tanyldizi ◽  
Martin Misch ◽  
...  
Keyword(s):  
Relaxation Time ◽  
Isocitrate Dehydrogenase ◽  
Anaplastic Astrocytoma ◽  
T2 Mapping ◽  
Relaxation Times ◽  
Region Of Interest ◽  
World Health ◽  
High Grade ◽  
High Grade Gliomas ◽  
Health Organization

Purpose To characterise peritumoral zones in glioblastoma and anaplastic astrocytoma evaluating T2 values using T2 mapping sequences. Materials and methods In this study, 41 patients with histopathologically confirmed World Health Organization high grade gliomas and preoperative magnetic resonance imaging examinations were retrospectively identified and enrolled. High grade gliomas were differentiated: (a) by grade, glioblastoma versus anaplastic astrocytoma; and (b) by isocitrate dehydrogenase mutational state, mutated versus wildtype. T2 map relaxation times were assessed from the tumour centre to peritumoral zones by means of a region of interest and calculated pixelwise by using a fit model. Results Significant differences between T2 values evaluated from the tumour centre to the peritumoral zone were found between glioblastoma and anaplastic astrocytoma, showing a higher decrease in signal intensity (T2 value) from tumour centre to periphery for glioblastoma ( P = 0.0049 – fit-model: glioblastoma –25.02± 19.89 (–54–10); anaplastic astrocytoma –5.57±22.94 (–51–47)). Similar results were found when the cohort was subdivided by their isocitrate dehydrogenase profile, showing an increased drawdown from tumour centre to periphery for wildtype in comparison to mutated isocitrate dehydrogenase ( P = 0.0430 – fit model: isocitrate dehydrogenase wildtype –10.35±16.20 (–51) – 0; isocitrate dehydrogenase mutated 12.14±21.24 (–15–47)). A strong statistical proof for both subgroup analyses ( P = 0.9987 – glioblastoma R2 0.93±0.08; anaplastic astrocytoma R2 0.94±0.15) was found. Conclusion Peritumoral T2 mapping relaxation time tissue behaviour of glioblastoma differs from anaplastic astrocytoma. Significant differences in T2 values, using T2 mapping relaxation time, were found between glioblastoma and anaplastic astrocytoma, capturing the tumour centre to the peritumoral zone. A similar curve progression from tumour centre to peritumoral zone was found for isocitrate dehydrogenase wildtype high grade gliomas in comparison to isocitrate dehydrogenase mutated high grade gliomas. This finding is in accordance with the biologically more aggressive behaviour of isocitrate dehydrogenase wildtype in comparison to isocitrate dehydrogenase mutated high grade gliomas. These results emphasize the potential of mapping techniques to reflect the tissue composition of high grade gliomas.

scholarly journals POS1439 A MULTI-PREDICTOR MODEL TO PREDICT RISK OF SCLERODERMA RENAL CRISIS IN SYSTEMIC SCLEROSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1004.1-1004
Author(s):  
D. Xu ◽  
R. Mu
Keyword(s):  
Systemic Sclerosis ◽  
Prediction Model ◽  
Renal Involvement ◽  
Area Under The Curve ◽  
Individual Risk ◽  
Multivariable Logistic Regression Analysis ◽  
Scleroderma Renal Crisis ◽  
Lasso Regression ◽  
Patients At Risk ◽  
Renal Crisis

Background:Scleroderma renal crisis (SRC) is a life-threatening syndrome. The early identification of patients at risk is essential for timely treatment to improve the outcome[1].Objectives:We aimed to provide a personalized tool to predict risk of SRC in systemic sclerosis (SSc).Methods:We tried to set up a SRC prediction model based on the PKUPH-SSc cohort of 302 SSc patients. The least absolute shrinkage and selection operator (Lasso) regression was used to optimize disease features. Multivariable logistic regression analysis was applied to build a SRC prediction model incorporating the features of SSc selected in the Lasso regression. Then, a multi-predictor nomogram combining clinical characteristics was constructed and evaluated by discrimination and calibration.Results:A multi-predictor nomogram for evaluating the risk of SRC was successfully developed. In the nomogram, four easily available predictors were contained including disease duration <2 years, cardiac involvement, anemia and corticosteroid >15mg/d exposure. The nomogram displayed good discrimination with an area under the curve (AUC) of 0.843 (95% CI: 0.797-0.882) and good calibration.Conclusion:The multi-predictor nomogram for SRC could be reliably and conveniently used to predict the individual risk of SRC in SSc patients, and be a step towards more personalized medicine.References:[1]Woodworth TG, Suliman YA, Li W, Furst DE, Clements P (2016) Scleroderma renal crisis and renal involvement in systemic sclerosis. Nat Rev Nephrol 12 (11):678-91.Disclosure of Interests:None declared

scholarly journals Prediction of COVID-19 severity using laboratory findings on admission: informative values, thresholds, ML model performance

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e044500
Author(s):  
Yauhen Statsenko ◽  
Fatmah Al Zahmi ◽  
Tetiana Habuza ◽  
Klaus Neidl-Van Gorkom ◽  
Nazar Zaki
Keyword(s):  
Lymphocyte Count ◽  
Prediction Models ◽  
Model Performance ◽  
Area Under The Curve ◽  
Predictive Biomarkers ◽  
Supervised Machine Learning ◽  
Study Cohort ◽  
Threshold Values ◽  
Laboratory Findings ◽  
Study Results

BackgroundDespite the necessity, there is no reliable biomarker to predict disease severity and prognosis of patients with COVID-19. The currently published prediction models are not fully applicable to clinical use.ObjectivesTo identify predictive biomarkers of COVID-19 severity and to justify their threshold values for the stratification of the risk of deterioration that would require transferring to the intensive care unit (ICU).MethodsThe study cohort (560 subjects) included all consecutive patients admitted to Dubai Mediclinic Parkview Hospital from February to May 2020 with COVID-19 confirmed by the PCR. The challenge of finding the cut-off thresholds was the unbalanced dataset (eg, the disproportion in the number of 72 patients admitted to ICU vs 488 non-severe cases). Therefore, we customised supervised machine learning (ML) algorithm in terms of threshold value used to predict worsening.ResultsWith the default thresholds returned by the ML estimator, the performance of the models was low. It was improved by setting the cut-off level to the 25th percentile for lymphocyte count and the 75th percentile for other features. The study justified the following threshold values of the laboratory tests done on admission: lymphocyte count <2.59×109/L, and the upper levels for total bilirubin 11.9 μmol/L, alanine aminotransferase 43 U/L, aspartate aminotransferase 32 U/L, D-dimer 0.7 mg/L, activated partial thromboplastin time (aPTT) 39.9 s, creatine kinase 247 U/L, C reactive protein (CRP) 14.3 mg/L, lactate dehydrogenase 246 U/L, troponin 0.037 ng/mL, ferritin 498 ng/mL and fibrinogen 446 mg/dL.ConclusionThe performance of the neural network trained with top valuable tests (aPTT, CRP and fibrinogen) is admissible (area under the curve (AUC) 0.86; 95% CI 0.486 to 0.884; p<0.001) and comparable with the model trained with all the tests (AUC 0.90; 95% CI 0.812 to 0.902; p<0.001). Free online tool at https://med-predict.com illustrates the study results.

scholarly journals Head-to-Head Comparison of Two Nomograms Predicting Probability of Lymph Node Invasion in Prostate Cancer and the Therapeutic Impact of Higher Nomogram Threshold

2021 ◽  
Vol 10 (5) ◽  
pp. 999
Author(s):  
Zilvinas Venclovas ◽  
Tim Muilwijk ◽  
Aivaras J. Matjosaitis ◽  
Mindaugas Jievaltas ◽  
Steven Joniau ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Lymph Node ◽  
Area Under The Curve ◽  
Pelvic Lymph Node ◽  
Cancer Center ◽  
Study Cohort ◽  
Net Benefit ◽  
Characteristic Analysis ◽  
Therapeutic Impact ◽  
Mskcc Nomogram

Introduction: The aim of the study was to compare the performance of the 2012 Briganti and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms as a predictor for pelvic lymph node invasion (LNI) in men who underwent radical prostatectomy (RP) with pelvic lymph node dissection (PLND), to examine their performance and to analyse the therapeutic impact of using 7% nomogram cut-off. Materials and Methods: The study cohort consisted of 807 men with clinically localised prostate cancer (PCa) who underwent open RP with PLND between 2001 and 2019. The area under the curve (AUC) of the receiver operator characteristic analysis was used to quantify the accuracy of the 2012 Briganti and MSKCC nomograms to predict LNI. Calibration plots were used to visualise over or underestimation by the models and a decision curve analysis (DCA) was performed to evaluate the net benefit associated with the used nomograms. Results: A total of 97 of 807 patients had LNI (12%). The AUC of 2012 Briganti and MSKCC nomogram was 80.6 and 79.2, respectively. For the Briganti nomogram using the cut-off value of 7% would lead to reduce PLND in 47% (379/807), while missing 3.96% (15/379) cases with LNI. For the MSKCC nomogram using the cut-off value of 7% a PLND would be omitted in 44.5% (359/807), while missing 3.62% (13/359) of cases with LNI. Conclusions: Both analysed nomograms demonstrated high accuracy for prediction of LNI. Using a 7% nomogram cut-off would allow the avoidance up to 47% of PLNDs, while missing less than 4% of patients with LNI.

scholarly journals Red cell distribution width as a predictor for bronchopulmonary dysplasia in premature infants

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hayato Go ◽  
Hitoshi Ohto ◽  
Kenneth E. Nollet ◽  
Kenichi Sato ◽  
Hirotaka Ichikawa ◽  
...  
Keyword(s):  
Blood Cell ◽  
Bronchopulmonary Dysplasia ◽  
Gestational Age ◽  
Red Blood Cell ◽  
Area Under The Curve ◽  
Cell Distribution ◽  
Characteristic Analysis ◽  
Distribution Width ◽  
Potential Biomarker ◽  
Rbc Transfusion

AbstractBronchopulmonary dysplasia (BPD) is the most common morbidity complicating preterm birth. Red blood cell distribution width (RDW), a measure of the variation red blood cell size, could reflect oxidative stress and chronic inflammation in many diseases such as cardiovascular, pulmonary, and other diseases. The objectives of the present study were to evaluate perinatal factors affecting RDW and to validate whether RDW could be a potential biomarker for BPD. A total of 176 preterm infants born at < 30 weeks were included in this study. They were categorized into BPD (n = 85) and non-BPD (n = 91) infants. RDW at birth and 14 days and 28 days of life (DOL 14, DOL 28) were measured. Clinical data were obtained from all subjects at Fukushima Medical University (Fukushima, Japan). The mean RDW at birth, DOL 14 and DOL 28 were 16.1%, 18.6%, 20.1%, respectively. Small for gestational age (SGA), chorioamnionitis (CAM), hypertensive disorders of pregnancy (HDP), gestational age and birth weight were significantly associated with RDW at birth. SGA, BPD and red blood cell (RBC) transfusion before DOL 14 were associated with RDW at DOL 14. BPD and RBC transfusion before DOL 14 were associated with RDW at DOL 28. Compared with non-BPD infants, mean RDW at birth DOL 14 (21.1% vs. 17.6%, P < 0.001) and DOL 28 (22.2% vs. 18.2%, P < 0.001) were significantly higher in BPD infants. Multivariate analysis revealed that RDW at DOL 28 was significantly higher in BPD infants (P = 0.001, odds ratio 1.63; 95% CI 1.22–2.19). Receiver operating characteristic analysis for RDW at DOL 28 in infants with and without BPD yielded an area under the curve of 0.87 (95% CI 0.78–0.91, P < 0.001). RDW at DOL 28 with mild BPD (18.3% vs. 21.2%, P < 0.001), moderate BPD (18.3% vs. 21.2%, P < 0.001), and severe BPD (18.3% vs. 23.9%, P < 0.001) were significantly higher than those with non-BPD, respectively. Furthermore, there are significant differences of RDW at DOL 28 between mild, moderate, and severe BPD. In summary, we conclude that RDW at DOL 28 could serve as a biomarker for predicting BPD and its severity. The mechanism by which RDW at DOL 28 is associated with the pathogenesis of BPD needs further elucidation.

scholarly journals Theoretical Effect of Temperature on Threshold in the Hodgkin-Huxley Nerve Model

1966 ◽  
Vol 49 (5) ◽  
pp. 989-1005 ◽  
Author(s):  
Richard Fitzhugh
Keyword(s):  
Relaxation Time ◽  
Relaxation Times ◽  
Giant Axon ◽  
Temperature Curve ◽  
Effect Of Temperature ◽  
Threshold Temperature ◽  
Ionic Conductances ◽  
And Shifts ◽  
The Right ◽  
Increasing Temperature

In the squid giant axon, Sjodin and Mullins (1958), using 1 msec duration pulses, found a decrease of threshold with increasing temperature, while Guttman (1962), using 100 msec pulses, found an increase. Both results are qualitatively predicted by the Hodgkin-Huxley model. The threshold vs. temperature curve varies so much with the assumptions made regarding the temperature-dependence of the membrane ionic conductances that quantitative comparison between theory and experiment is not yet possible. For very short pulses, increasing temperature has two effects. (1) At lower temperatures the decrease of relaxation time of Na activation (m) relative to the electrical (RC) relaxation time favors excitation and decreases threshold. (2) For higher temperatures, effect (1) saturates, but the decreasing relaxation times of Na inactivation (h) and K activation (n) factor accommodation and increased threshold. The result is a U-shaped threshold temperature curve. R. Guttman has obtained such U-shaped curves for 50 µsec pulses. Assuming higher ionic conductances decreases the electrical relaxation time and shifts the curve to the right along the temperature axis. Making the conductances increase with temperature flattens the curve. Using very long pulses favors effect (2) over (1) and makes threshold increase monotonically with temperature.

scholarly journals Value of radiomics in differential diagnosis of chromophobe renal cell carcinoma and renal oncocytoma

2019 ◽  
Vol 45 (10) ◽  
pp. 3193-3201 ◽  
Author(s):  
Yajuan Li ◽  
Xialing Huang ◽  
Yuwei Xia ◽  
Liling Long
Keyword(s):  
Machine Learning ◽  
Differential Diagnosis ◽  
Cell Carcinoma ◽  
Area Under The Curve ◽  
Image Features ◽  
Renal Tumors ◽  
Support Vector ◽  
Svm Classifier ◽  
Renal Oncocytoma ◽  
Lasso Regression

Abstract Purpose To explore the value of CT-enhanced quantitative features combined with machine learning for differential diagnosis of renal chromophobe cell carcinoma (chRCC) and renal oncocytoma (RO). Methods Sixty-one cases of renal tumors (chRCC = 44; RO = 17) that were pathologically confirmed at our hospital between 2008 and 2018 were retrospectively analyzed. All patients had undergone preoperative enhanced CT scans including the corticomedullary (CMP), nephrographic (NP), and excretory phases (EP) of contrast enhancement. Volumes of interest (VOIs), including lesions on the images, were manually delineated using the RadCloud platform. A LASSO regression algorithm was used to screen the image features extracted from all VOIs. Five machine learning classifications were trained to distinguish chRCC from RO by using a fivefold cross-validation strategy. The performance of the classifier was mainly evaluated by areas under the receiver operating characteristic (ROC) curve and accuracy. Results In total, 1029 features were extracted from CMP, NP, and EP. The LASSO regression algorithm was used to screen out the four, four, and six best features, respectively, and eight features were selected when CMP and NP were combined. All five classifiers had good diagnostic performance, with area under the curve (AUC) values greater than 0.850, and support vector machine (SVM) classifier showed a diagnostic accuracy of 0.945 (AUC 0.964 ± 0.054; sensitivity 0.999; specificity 0.800), showing the best performance. Conclusions Accurate preoperative differential diagnosis of chRCC and RO can be facilitated by a combination of CT-enhanced quantitative features and machine learning.

scholarly journals Texture-Based Analysis of 18F-Labeled Amyloid PET Brain Images

2021 ◽  
Vol 11 (5) ◽  
pp. 1991
Author(s):  
Alexander P. Seiffert ◽  
Adolfo Gómez-Grande ◽  
Eva Milara ◽  
Sara Llamas-Velasco ◽  
Alberto Villarejo-Galende ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Standardized Uptake Value ◽  
Texture Features ◽  
Roc Curves ◽  
Significant Feature ◽  
Study Cohort ◽  
Amyloid Pet ◽  
Reference Region ◽  
Brain Images ◽  
Positron Emission

Amyloid positron emission tomography (PET) brain imaging with radiotracers like [18F]florbetapir (FBP) or [18F]flutemetamol (FMM) is frequently used for the diagnosis of Alzheimer’s disease. Quantitative analysis is usually performed with standardized uptake value ratios (SUVR), which are calculated by normalizing to a reference region. However, the reference region could present high variability in longitudinal studies. Texture features based on the grey-level co-occurrence matrix, also called Haralick features (HF), are evaluated in this study to discriminate between amyloid-positive and negative cases. A retrospective study cohort of 66 patients with amyloid PET images (30 [18F]FBP and 36 [18F]FMM) was selected and SUVRs and 6 HFs were extracted from 13 cortical volumes of interest. Mann–Whitney U-tests were performed to analyze differences of the features between amyloid positive and negative cases. Receiver operating characteristic (ROC) curves were computed and their area under the curve (AUC) was calculated to study the discriminatory capability of the features. SUVR proved to be the most significant feature among all tests with AUCs between 0.692 and 0.989. All HFs except correlation also showed good performance. AUCs of up to 0.949 were obtained with the HFs. These results suggest the potential use of texture features for the classification of amyloid PET images.

scholarly journals Longer T2relaxation time is a marker of hypothalamic gliosis in mice with diet-induced obesity

2013 ◽  
Vol 304 (11) ◽  
pp. E1245-E1250 ◽  
Author(s):  
Donghoon Lee ◽  
Joshua P. Thaler ◽  
Kathryn E. Berkseth ◽  
Susan J. Melhorn ◽  
Michael W. Schwartz ◽  
...  
Keyword(s):  
Relaxation Time ◽  
High Field ◽  
Relaxation Times ◽  
Quantitative Mri ◽  
Human Studies ◽  
Mri Findings ◽  
Diet Induced Obesity ◽  
Magnetic Resonance Imaging Mri ◽  
The Right ◽  
Mr Brain

A hallmark of brain injury from infection, vascular, neurodegenerative, and other disorders is the development of gliosis, which can be detected by magnetic resonance imaging (MRI). In rodent models of diet-induced obesity (DIO), high-fat diet (HFD) consumption rapidly induces inflammation and gliosis in energy-regulating regions of the mediobasal hypothalamus (MBH), and recently we reported MRI findings suggestive of MBH gliosis in obese humans. Thus, noninvasive imaging may obviate the need to assess MBH gliosis using histopathological end points, an obvious limitation to human studies. To investigate whether quantitative MRI is a valid tool with which to measure MBH gliosis, we performed analyses, including measurement of T2relaxation time from high-field MR brain imaging of mice fed HFD and chow-fed controls. Mean bilateral T2relaxation time was prolonged significantly in the MBH, but not in the thalamus or cortex, of HFD-fed mice compared with chow-fed controls. Histological analysis confirmed evidence of increased astrocytosis and microglial accumulation in the MBH of HFD-fed mice compared with controls, and T2relaxation times in the right MBH correlated positively with mean intensity of glial fibrillary acidic protein staining (a marker of astrocytes) in HFD-fed animals. Our findings indicate that T2relaxation time obtained from high-field MRI is a useful noninvasive measurement of HFD-induced gliosis in the mouse hypothalamus with potential for translation to human studies.

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