Gaussian mixture model-based cluster analysis of apparent diffusion coefficient values: a novel approach to evaluate uterine endometrioid carcinoma grade

2020 ◽  
Vol 31 (1) ◽  
pp. 55-64
Author(s):  
Sakiko Kageyama ◽  
Naoko Mori ◽  
Shunji Mugikura ◽  
Hideki Tokunaga ◽  
Kei Takase
Keyword(s):  
Cluster Analysis ◽  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture ◽  
Endometrioid Carcinoma ◽  
Apparent Diffusion Coefficient Values ◽  
Novel Approach ◽  
Apparent Diffusion

Added Value of Quantitative Apparent Diffusion Coefficient Values for Neuroprognostication After Cardiac Arrest

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000011991
Author(s):  
Anke Wouters ◽  
Lauranne Scheldeman ◽  
Sam Plessers ◽  
Ronald Peeters ◽  
Sarah Cappelle ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Brain Mri ◽  
Multivariate Model ◽  
Added Value ◽  
Neurological Recovery ◽  
Adc Value ◽  
Apparent Diffusion Coefficient Values ◽  
Apparent Diffusion

ObjectiveTo test the prognostic value of brain MRI in addition to clinical and electrophysiological variables in post-cardiac arrest (CA) patients, we explored data from the randomized Neuroprotect post-CA trial (NCT02541591).MethodsIn this trial brain MRI’s were prospectively obtained. We calculated receiver operating characteristic curves for the average Apparent Diffusion Coefficient (ADC) value and percentage of brain voxels with an ADC value < 650 x 10-6 mm2/s and < 450 x 10-6 mm2/s. We constructed multivariable logistic regression models with clinical characteristics, electroencephalogram (EEG), somatosensory evoked potentials (SSEP) and ADC value as independent variables, to predict good neurological recovery.ResultsIn 79/102 patients MRI data were available and in 58/79 patients all other data were available. At 180 days post-CA, 25/58 (43%) patients had good neurological recovery. In univariable analysis of all tested MRI parameters, average ADC value in the postcentral cortex had the highest accuracy to predict good neurological recovery with an AUC of 0.78. In the most optimal multivariate model which also included corneal reflexes and EEG, this parameter remained an independent predictor of good neurological recovery (AUC = 0.96, false positive = 27%). This model provided a more accurate prediction compared to the most optimal combination of EEG, corneal reflexes and SSEP (p=0.03).ConclusionAdding information on brain MRI in a multivariate model may improve the prediction of good neurological recovery in post-CA patients.Classification of Evidence:"This study provides Class III evidence that MRI ADC features predict neurological recovery in post-cardiac arrest patients."

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