The diagnostic utility of size and apparent diffusion coefficient values for cervical lymph nodes in patients with osteomyelitis of the jaw bone

2021 ◽  
Author(s):  
Hirotaka Muraoka ◽  
Kotaro Ito ◽  
Naohisa Hirahara ◽  
Tomohiro Komatsu ◽  
Takumi Kondo ◽  
...  
Author(s):  
Alexey Surov ◽  
Hans-Jonas Meyer ◽  
Maciej Pech ◽  
Maciej Powerski ◽  
Jasan Omari ◽  
...  

Abstract Background Our aim was to provide data regarding use of diffusion-weighted imaging (DWI) for distinguishing metastatic and non-metastatic lymph nodes (LN) in rectal cancer. Methods MEDLINE library, EMBASE, and SCOPUS database were screened for associations between DWI and metastatic and non-metastatic LN in rectal cancer up to February 2021. Overall, 9 studies were included into the analysis. Number, mean value, and standard deviation of DWI parameters including apparent diffusion coefficient (ADC) values of metastatic and non-metastatic LN were extracted from the literature. The methodological quality of the studies was investigated according to the QUADAS-2 assessment. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian, and Laird random-effects models with inverse-variance weights were used to account the heterogeneity between the studies. Mean DWI values including 95% confidence intervals were calculated for metastatic and non-metastatic LN. Results ADC values were reported for 1376 LN, 623 (45.3%) metastatic LN, and 754 (54.7%) non-metastatic LN. The calculated mean ADC value (× 10−3 mm2/s) of metastatic LN was 1.05, 95%CI (0.94, 1.15). The calculated mean ADC value of the non-metastatic LN was 1.17, 95%CI (1.01, 1.33). The calculated sensitivity and specificity were 0.81, 95%CI (0.74, 0.89) and 0.67, 95%CI (0.54, 0.79). Conclusion No reliable ADC threshold can be recommended for distinguishing of metastatic and non-metastatic LN in rectal cancer.


Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000011991
Author(s):  
Anke Wouters ◽  
Lauranne Scheldeman ◽  
Sam Plessers ◽  
Ronald Peeters ◽  
Sarah Cappelle ◽  
...  

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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