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Gd-EOB-DTPA dynamic contrast-enhanced magnetic resonance imaging is more effective than enhanced 64-slice CT for the detection of small lesions in patients with hepatocellular carcinoma.
Li, J, Li, X, Weng, J, Lei, L, Gong, J, Wang, J, Li, Z, Zhang, L, He, S
Medicine. 2018;(52):e13964
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Abstract
This study aimed to compare the sensitivity and accuracy for the detection of small lesions in patients with hepatocellular carcinoma (HCC) using gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and 64-slice computed tomography (CT) enhanced scanning, and to evaluate the necessity to perform MRI in patients diagnosed with HCC by CT.The clinical data from 209 patients with HCC diagnosed prior to surgery in the Affiliated Hospital of Guilin Medical University, China were retrospectively analyzed. The 64-slice dynamic contrast-enhanced multi-detector CT (MDCT) and 3.0 T Gd-EOB-DTPA DCE MRI procedures were successively carried out on all patients who were enrolled in a self-controlled study including detection and diagnosis of HCC lesions by MRI and CT, respectively.A total of 243 lesions were detected and both imaging methods could accurately detect lesions of diameter >2 cm. For lesions <2 cm, MRI detected 47, while CT detected 25 lesions indicating that the detection rate of MRI was 88% higher than that of CT. In addition, MRI detected lesions in 15 cases (7.81% in the total of 209 cases) that were not diagnosed by CT. Among these cases, 2 patients were diagnosed to have no lesion by CT.Gd-EOB-DTPA DCE-MRI performed as a routine check prior to surgery in HCC patients can improve the detection of small HCC lesions.
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Prestructural cartilage assessment using MRI.
Link, TM, Neumann, J, Li, X
Journal of magnetic resonance imaging : JMRI. 2017;(4):949-965
Abstract
UNLABELLED Cartilage loss is irreversible, and to date, no effective pharmacotherapies are available to protect or regenerate cartilage. Quantitative prestructural/compositional MR imaging techniques have been developed to characterize the cartilage matrix quality at a stage where abnormal findings are early and potentially reversible, allowing intervention to halt disease progression. The goal of this article is to critically review currently available technologies, present the basic concept behind these techniques, but also to investigate their suitability as imaging biomarkers including their validity, reproducibility, risk prediction and monitoring of therapy. Moreover, we highlighted important clinical applications. This review article focuses on the currently most relevant and clinically applicable technologies, such as T2 mapping, T2*, T1ρ, delayed gadolinium enhanced MRI of cartilage (dGEMRIC), sodium imaging and glycosaminoglycan chemical exchange saturation transfer (gagCEST). To date, most information is available for T2 and T1ρ mapping. dGEMRIC has also been used in multiple clinical studies, although it requires Gd contrast administration. Sodium imaging and gagCEST are promising technologies but are dependent on high field strength and sophisticated software and hardware. LEVEL OF EVIDENCE 5 J. Magn. Reson. Imaging 2017;45:949-965.
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Cartilage repair surgery: outcome evaluation by using noninvasive cartilage biomarkers based on quantitative MRI techniques?
Jungmann, PM, Baum, T, Bauer, JS, Karampinos, DC, Erdle, B, Link, TM, Li, X, Trattnig, S, Rummeny, EJ, Woertler, K, et al
BioMed research international. 2014;:840170
Abstract
BACKGROUND New quantitative magnetic resonance imaging (MRI) techniques are increasingly applied as outcome measures after cartilage repair. OBJECTIVE To review the current literature on the use of quantitative MRI biomarkers for evaluation of cartilage repair at the knee and ankle. METHODS Using PubMed literature research, studies on biochemical, quantitative MR imaging of cartilage repair were identified and reviewed. RESULTS Quantitative MR biomarkers detect early degeneration of articular cartilage, mainly represented by an increasing water content, collagen disruption, and proteoglycan loss. Recently, feasibility of biochemical MR imaging of cartilage repair tissue and surrounding cartilage was demonstrated. Ultrastructural properties of the tissue after different repair procedures resulted in differences in imaging characteristics. T2 mapping, T1rho mapping, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), and diffusion weighted imaging (DWI) are applicable on most clinical 1.5 T and 3 T MR scanners. Currently, a standard of reference is difficult to define and knowledge is limited concerning correlation of clinical and MR findings. The lack of histological correlations complicates the identification of the exact tissue composition. CONCLUSIONS A multimodal approach combining several quantitative MRI techniques in addition to morphological and clinical evaluation might be promising. Further investigations are required to demonstrate the potential for outcome evaluation after cartilage repair.
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Identification of MRI and 1H MRSI parameters that may predict survival for patients with malignant gliomas.
Li, X, Jin, H, Lu, Y, Oh, J, Chang, S, Nelson, SJ
NMR in biomedicine. 2004;(1):10-20
Abstract
Although MR imaging (MRI) and MR spectroscopic imaging (MRSI) have been applied in the diagnosis and treatment planning for brain tumors, their prognostic significance has not yet been determined. The goal of this study was to identify pre-treatment MRI and MRSI parameters for patients with malignant glioma that may be useful in predicting survival. Two populations of patients with newly-diagnosed malignant glioma were examined with MRI and three-dimensional proton ((1)H) MRSI. Thirty-nine patients (22 grade 3 and 17 glioblastoma multiforme, GBM) were studied prior to surgery, and 33 GBM patients were studied after surgery but prior to treatment with radiation and chemotherapy. Signal intensities of choline (Cho), creatine (Cr), N-acetyl aspartate (NAA), and lactate/lipid (LL) were estimated from the spectra. Recursive partitioning methods were applied to parameters that included age, histological grade, MRI and MRSI variables to generate survival trees. Patients were grouped into high and low risk categories and the corresponding Kaplan-Meier curves were plotted for comparison between groups. The parameters that were selected by recursive partitioning as being predictive of poor outcome were older age, larger contrast enhancement, higher Cho-to-Cr, higher Cho-to-NAA, higher LL and lower Cr-to-NAA abnormalities. The survival functions were significantly different between the sub-groups of patients obtained from the survival tree for both pre-surgery and post-surgery data. The results of this study suggest that pre-treatment MRI and three-dimensional (1)H-MRSI provide information that predicts outcome for patients with malignant gliomas and have drawn attention to variables that should be examined prospectively in future studies using these techniques.