Semi-quantitative assessment of brain maturation by conventional magnetic resonance imaging in neonates with clinically mild hypoxic-ischemic encephalopathy.

BACKGROUND: Mild hypoxic-ischemic encephalopathy (HIE) injury is becoming the major type in neonatal brain diseases. The aim of this study was to assess brain maturation in mild HIE neonatal brains using total maturation score (TMS) based on conventional magnetic resonance imaging (MRI). METHODS: Totally, 45 neonates with clinically mild HIE and 45 matched control neonates were enrolled. Gestated age, birth weight, age after birth and postmenstrual age at magnetic resonance (MR) scan were homogenous in the two groups. According to MR findings, mild HIE neonates were divided into three subgroups: Pattern I, neonates with normal MR appearance; Pattern II, preterm neonates with abnormal MR appearance; Pattern III, full-term neonates with abnormal MR appearance. TMS and its parameters, progressive myelination (M), cortical infolding (C), involution of germinal matrix tissue (G), and glial cell migration bands (B), were employed to assess brain maturation and compare difference between HIE and control groups. RESULTS: The mean of TMS was significantly lower in mild HIE group than it in the control group (mean ± standard deviation [SD] 11.62 ± 1.53 vs. 12.36 ± 1.26, P < 0.001). In four parameters of TMS scores, the M and C scores were significantly lower in mild HIE group. Of the three patterns of mild HIE, Pattern I (10 cases) showed no significant difference of TMS compared with control neonates, while Pattern II (22 cases), III (13 cases) all had significantly decreased TMS than control neonates (mean ± SD 10.56 ± 0.93 vs. 11.48 ± 0.55, P < 0.05; 12.59 ± 1.28 vs. 13.25 ± 1.29, P < 0.05). It was M, C, and GM scores that significantly decreased in Pattern II, while for Pattern III, only C score significantly decreased. CONCLUSIONS: The TMS system, based on conventional MRI, is an effective method to detect delayed brain maturation in clinically mild HIE. The conventional MRI can reveal the different retardations in subtle structures and development processes among the different patterns of mild HIE.

EADC Values in Diagnosis of Renal Lesions by 3.0 T Diffusion-Weighted Magnetic Resonance Imaging: Compared with the ADC Values.

Exponential apparent diffusion coefficient (EADC) is an indicator of diffusion-weighted imaging (DWI) and reflects the pathological changes of tissues quantitatively. However, no study has been investigated in the space-occupying kidney disease using EADC values. This study aims to evaluate the diagnostic role of EADC values at a high magnetic field strength (3.0 T) in kidney neoplastic lesions, compared with that of the ADC values. Ninety patients with suspected renal tumors (including 101 suspected renal lesions) and 20 healthy volunteers were performed MRI scanning. Diffusion-weighted imaging was performed with a single-shot spin-echo echo-planar imaging (SE-EPI) sequence at a diffusion gradient of b = 500 s/mm2. We found renal cell carcinoma (RCC) can be distinguished from angiomyolipoma, and clear cell carcinoma can be distinguished from non-clear cell carcinoma by EADC value. There was significant difference in overall EADC values between renal cell carcinoma (0.150 ± 0.059) and angiomyolipoma (0.270 ± 0.108) when b value was 500 s/mm2. When receiver operating characteristic (ROC) was higher than 0.192, the sensitivity and specificity of EADC value of renal cell carcinoma were 84.6 and 81.1 %, respectively. In conclusion, EADC map shows the internal structure of the kidney tumor more intuitively than the ADC map dose, and is also in line with the observation habits of the clinicians. EADC can be used as an effective imaging method for tumor diagnosis.

[Functional MRI study on thalamus activation induced by electrical stimulation of different intensities].

OBJECTIVE: To detect the activation pattern of the thalamus in human by the functional magnetic resonance imaging (fMRI) with the electrical stimulation of different intensities, and to explore the mechanism of this area in pain modulation. METHODS: Ten healthy right-handed volunteers were given different electrical stimulations of 1-, 2-, and 3- times pain threshold respectively. The whole-brain was scanned simultaneously by GE 1.5T magnetic resonance imaging system. The data were postprocessed by analysis of functional neuroimages (AFNI) to establish the regional activity maps of the thalamus. RESULTS: Patterns of functional activity showed a positive linear relationship between the activation signals and stimulation intensity in bilateral thalamus, whereas the BOLD signal of bilateral medial thalamus demonstrated that the curve was similar to the exponential function. Meanwhile, the activation in the contralateral lateral thalamus (cThl), but not the contralateral medial thalamus (cThm), was prominent compared with the corresponding ipsilateral subregions, and only the lateral thalamus displayed a contralateral biased representation while the medial thalamus lacked this property. CONCLUSION: Thalamus is one of the vital components in the pain modulation network, which can present spatial segregation activations with unique characteristics of stimulation intensity-response in each subregion. All the results are helpful to understand the crucial role of thalamus in processing the pain information.

[Anterior cingulate cortex involving in pain modulation-an functional magnetic resonance imaging study].

OBJECTIVE: To investigate the functional activation patterns of the subregions of anterior cingulate cortex (ACC) in human to electrical stimulation of different intensity with functional Magnetic Resonance Imaging (fMRI) and probe the contribution of this area in pain modulation network. METHODS: 10 healthy right-handed volunteers were studied with different electrical intensity stimulation of 1-, 2-, or 3-time pain threshold. The fMRI data were collected by GE signa 1.5T MRI system and postprocessed with software of Analysis of Functional Neuroimages (AFNI) to generate the regional activation maps of ACC, furthermore, the distinctive characteristics of stimulation-BOLD signal in ACC subregions were analyzed according to the fMRI maps from the average of the 10 subjects. RESULTS: The anterior portion of ACC (aACC) showed moderate pain-attention-related activation but not statistically related to the strength of stimulation (average activated pixels of P1, P2, P3 amounted to 324, 429, 562 respectively). The BOLD signal showed a positive linear relation with the increasing stimulation at the dorsal-posterior portion of ACC (average activated pixels of P1, P2, P3 were 311, 964, 1414), which indicated stimulus intensity-dependent responses. The ventral-posterior area of ACC (vpACC) demonstrated pain intensity encoding because the BOLD signal had no significant difference during innocuous condition but displayed remarkable distinction during noxious stimulation in this area (average activated pixels of P1, P2, P3 were 324, 429, 562). CONCLUSION: Subregions in ACC may play a varied role in the network of pain modulation. Each area of ACC displays segregated activation patterns in response to electrical stimulation with different strength.