Prediction of Infarct Lesion Volumes by Processing Magnetic Resonance Apparent Diffusion Coefficient Maps in Patients with Acute Ischemic Stroke.
OBJECTIVE
We aimed to investigate the diagnostic value of apparent diffusion coefficient (ADC) maps in magnetic resonance imaging (MRI) in the volume of acute cerebral infarction (ACI).


METHODS
A total of 207 ACI patients were selected in our study. The cerebral infarction (CI) volume in the initial diffusion-weighted imaging examination, minimum ADC value, relative apparent diffusion coefficient (rADC) value, and mean ADC value were measured. The correlations between age, smoking, drinking, hypertension, diabetes, coronary heart disease, clinical stage, the lowest ADC value, the mean ADC value, and the mean rADC value with CI volume were analyzed by logistic regression analysis. A receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of the ADC value in the ACI volume.


RESULTS
There was a significant difference in the distribution of the CI volume in ACI patients (P <.05). A significant difference was found in the signal intensity and percentage distribution of ADC map in patients of different CI groups with different CI volumes (P <.05). The signal of the ADC map was positively correlated with the CI volume. The mean ADC and rADC values had significant differences between different CI volumes (all P <.05). Logistic regression analysis revealed that the mean ADC value was significantly correlated with the CI volume (P <.05). Analysis of the ROC curve showed that the quantitative value of ADC has a diagnostic value for the ACI volume.


CONCLUSIONS
This study has shown that the signal intensity change on the ADC map in MRI and quantitative analysis of the ADC value can be used as a reference for predicting the ACI volume.
Department of Radiology, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Qi
Q
Qian
Department of Radiology, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Hai-Tao
HT
Huang
Department of Radiology, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Li
L
Xu
Department of Radiology, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Ping
P
Jin
Department of Radiology, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China. Electronic address: Linmin_2@126.com.
Min
M
Lin
D000368:Aged; D019540:Area Under Curve; D001921:Brain / Q000000981:diagnostic imaging*; D020520:Brain Infarction / Q000000981:diagnostic imaging* / Q000209:etiology; D002545:Brain Ischemia / Q000000981:diagnostic imaging* / Q000209:etiology; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D012372:ROC Curve; D015203:Reproducibility of Results; D012307:Risk Factors; D012720:Severity of Illness Index
Acute cerebral infarction; T1-weighted imaging; T2-weighted imaging; apparent diffusion coefficient; diffusion-weighted imaging; infarct volume; magnetic resonance imaging; region of interest