Evaluating The Relation Between Apparent Diffusion Coefficient, Lesion Enhancement Pattern And Severity Of Disease In Patient With Brain Stroke


1 (Medical Imaging MSc Candidate, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.)

2 (Radiology Technology Department, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran )

3 (MSc Student of Medical Physics, Students Research Committee, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran.)

4 Shahid Beheshti University of Medical Sciences

5 (Associate Professor of Medical Imaging. Clinical MRI Physicist, PhD in Medical Physics-Emphasis: Medical Imaging-Fellow of fMRI and Diffusion from Italy.)

6 (Neurology Ward, Shohada Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.)


The stroke disease leads to some problems in normal brain diffusion. Thus, DWI can be used in the early diagnosis of this disease, especially in acute phase. Acquired ADC maps from DWI show the water molecule diffusion. These maps are used as a biomarker to detect different types of stroke. We investigated the relationship between signal amplification pattern of lesion and stroke intensity according to the size of the lesion in patients with ischemic stroke in the middle cerebral artery.
Materials and Methods:
We included 30 patients (12 females and 18 males) in our study. By using the Onis software, patients were divided into three groups (<5cm3, 5-15cm3 and 15cm3<), based on the lesion volume. The mean ADC was determined by using ADC maps. The relationship between the mean ADC and the NIHHS score, and NIHHS score with the volume of the lesion was determined. A quantitative model and a qualitative-visual model were used to determine the intralesional patterns in the ADC maps. Also, we used the ROC curve for analyzing the diagnostic value of ADC mean and determining the quantitative threshold to define the intralesional pattern.
There was a strong correlation between stroke intensity and lesion size in patients with large lesion size (P = 0.001, r =0.753). There was no significant relationship between the severity of stroke (NIHSS score) and mean ADC (P = 0.724, r = -0.067). Also, the ROC curve indicates that if the standard deviation of ADC of an individual is greater than 1.82*10-3 s /mm2, it is a heterogeneous lesion. We also found a weak agreement (k = 0.03) between two quantitative and qualitative-visual model. 
This study showed that ADC maps and stroke intensity can be used to predict stroke volume. Additionally, we could specify intralesional pattern by ADC maps.