磁共振弥散加权成像(DWI)在急性脑缺血中的诊断价值

目的：探讨磁共振弥散加权成像（DWI）在急性脑缺血中的诊断价值．方法：对50例急性脑缺血患者的常规的MRI、液体衰减翻转恢复（Flair）和DWI图像进行比较研究分析．结果：50例患者经DWI扫描，均可发现梗塞灶，病灶检出率为100％，而15例发病在6h以内的超急性脑梗塞患者中，常规MR扫描T2WI上只有1例有轻微改变，而DWI均可显影；在35例发病在6～24h以内的急性脑梗塞患者中，T2WI上可逐渐显示病灶，但DWI显影更为清晰，显示病灶的范围也大于T2WI上的病灶．结论：DWI对诊断急性脑缺血十分敏感，能对急性脑缺血做出明确诊断．     

Diffusion-weighted MRI: influence of intravoxel fat signal and breast density on breast tumor conspicuity and apparent diffusion coefficient measurements

Promising recent investigations have shown that breast malignancies exhibit restricted diffusion on diffusion-weighted imaging (DWI) and may be distinguished from normal tissue and benign lesions in the breast based on differences in apparent diffusion coefficient (ADC) values. In this study, we assessed the influence of intravoxel fat signal on breast diffusion measures by comparing ADC values obtained using a diffusion-weighted single shot fast spin-echo sequence with and without fat suppression. The influence of breast density on ADC measures was also evaluated. ADC values were calculated for both tumor and normal fibroglandular tissue in a group of 21 women with diagnosed breast cancer. There were systematic underestimations of ADC for both tumor and normal breast tissue due to intravoxel contribution from fat signal on non–fat-suppressed DWI. This ADC underestimation was more pronounced for normal tissue values (mean difference=40%) than for tumors (mean difference=27%, P<.001) and was worse in women with low breast tissue density vs. those with extremely dense breasts (P<.05 for both tumor and normal tissue). Tumor conspicuity measured by contrast-to-noise ratio was significantly higher on ADC maps created with fat suppression and was not significantly associated with breast density. In summary, robust fat suppression is important for accurate breast ADC measures and optimal lesion conspicuity on DWI.     

An efficient non-iterative algorithm to estimate the apparent diffusion coefficient of water molecules in the magnetic resonance diffusion imaging experiments

Many studies have shown that the magnetic resonance signal decay with an extend range of diffusion weighting(b-factor)is a bi-exponential attenuation in the diffusion-weighted magnetic resonance imaging experiments in vivo.Based on this feature and the two-compartmental model,we propose a twice-linear-fitting(TLF)algorithm to estimate the apparent diffusion coefficient(ADC)of the water molecules instead of the commonly used iterative Levenberg–Marquardt(LM)method.The TLF algorithm consists of two liner fitting steps to estimate the fast and the slow apparent diffusion coefficients and their sizes,respectively.It is unnecessary to guess the initial values in the whole fitting process.The time consumption of the TLF algorithm is much less than that of the iterative LM method.Moreover,the TLF algorithm may avoid the extraneous solutions,which often deteriorates the results of the LM method.Compared with the iterative fitting method,the TLF algorithm is a reliable and timeefficient approach to estimate the ADC of water molecules in vivo in magnetic resonance diffusion-weighted imaging experiments.     

Intravoxel incoherent motion imaging of the kidney: alterations in diffusion and perfusion in patients with renal dysfunction

Purpose

To investigate the relationship between estimated glomerular filtration rate (eGFR) and parameters calculated using intravoxel incoherent motion (IVIM) imaging of the kidneys.

Materials and Methods

We studied 365 patients, divided into 4 groups based on eGFR levels (mL/min/1.73 m²): group 1, eGFR ≥ 80(n = 80); group 2, eGFR 60–80 (n = 156); group 3, eGFR 30–60 (n = 114); and group 4 ,eGFR < 30 (n = 15). IVIM imaging was used to acquire diffusion-weighted images at 12 b values. The diffusion coefficient of pure molecular diffusion (D), the diffusion coefficient of microcirculation or perfusion (D*), and perfusion fraction (f) were compared among the groups using group 1 as control.

Results

In the renal cortex, D* values were significantly lower in groups 2, 3, and 4 than in group 1. The D value of renal cortex was significantly low in only group 3. In the renal medulla, the D* and D values were significantly lower only in groups 2 and 3, respectively.

Conclusion

As renal dysfunction progresses, renal perfusion might be reduced earlier and affected more than molecular diffusion in the renal cortex. These changes are effectively detected by IVIM MR imaging.     

Investigating brain tumor differentiation with diffusion and perfusion metrics at 3T MRI using pattern recognition techniques

The aim of this study was to evaluate the contribution of diffusion and perfusion MR metrics in the discrimination of intracranial brain lesions at 3T MRI, and to investigate the potential diagnostic and predictive value that pattern recognition techniques may provide in tumor characterization using these metrics as classification features. Conventional MRI, diffusion weighted imaging (DWI), diffusion tensor imaging (DTI) and dynamic-susceptibility contrast imaging (DSCI) were performed on 115 patients with newly diagnosed intracranial tumors (low-and- high grade gliomas, meningiomas, solitary metastases). The Mann–Whitney U test was employed in order to identify statistical differences of the diffusion and perfusion parameters for different tumor comparisons in the intra-and peritumoral region. To assess the diagnostic contribution of these parameters, two different methods were used; the commonly used receiver operating characteristic (ROC) analysis and the more sophisticated SVM classification, and accuracy, sensitivity and specificity levels were obtained for both cases. The combination of all metrics provided the optimum diagnostic outcome. The highest predictive outcome was obtained using the SVM classification, although ROC analysis yielded high accuracies as well. It is evident that DWI/DTI and DSCI are useful techniques for tumor grading. Nevertheless, cellularity and vascularity are factors closely correlated in a non-linear way and thus difficult to evaluate and interpret through conventional methods of analysis. Hence, the combination of diffusion and perfusion metrics into a sophisticated classification scheme may provide the optimum diagnostic outcome. In conclusion, machine learning techniques may be used as an adjunctive diagnostic tool, which can be implemented into the clinical routine to optimize decision making.     

Fitting of two-tensor models without ad hoc assumptions to detect crossing fibers using clinical DWI data

Analysis of crossing fibers is a challenging topic in recent diffusion-weighted imaging (DWI). Resolving crossing fibers is expected to bring major changes to present tractography results based on the standard tensor model. Model free approaches, like Q-ball or diffusion spectrum imaging, as well as multi-tensor models are used to unfold the different diffusion directions mixed in a voxel of DWI data. Due to its seeming simplicity, the two-tensor model (TTM) is applied frequently to provide two positive-definite tensors and the relative population fraction modeling two crossing fiber branches. However, problems with uniqueness and noise instability are apparent. To stabilize the fit, several of the 13 physical parameters are fixed ad hoc, before fitting the model to the data. Our analysis of the TTM aims at fitting procedures where ad hoc parameters are avoided. Revealing sources of instability, we show that the model's inherent ambiguity can be reduced to one scalar parameter which only influences the fraction and the eigenvalues of the TTM, whereas the diffusion directions are not affected. Based on this, two fitting strategies are proposed: the parsimonious strategy detects the main diffusion directions without extra parameter fixation, to determine the eigenvalues and the population fraction an empirically motivated condition must be added. The expensive strategy determines all 13 physical parameters of the TTM by a fit to DWIs alone; no additional assumption is necessary. Ill-posedness of the model in case of noisy data is cured by denoising of the data and by L-curve regularization combined with global minimization performing a least-squares fit of the full model. By model simulations and real data applications, we demonstrate the feasibility of our fitting strategies and achieve convincing results. Using clinically affordable diffusion acquisition paradigms (encoding numbers: 21, 2*15, 2*21) and b values (b = 500–1500 s/mm²), this methodology can place the TTM parameters involved in crossing fibers on a more empirical basis than fitting procedures with technical assumptions.     

MRI 结合 DWI诊断脑囊虫病103例临床分析

目的探讨MRI结合扩散加权成像(DWI)诊断脑囊虫病的临床价值.方法选取疑似脑囊虫病患者103例行MRI检查和DWI检查,分析MRI检查、DWI检查及MRI结合DWI检查的灵敏度、特异性、准确率,总结MRI结合DWI诊断脑囊虫病的相关性.结果 DWI检查的灵敏度、特异性、准确率均高于MRI检查,但差异无统计学意义(P>0.05);MRI结合DWI检查的灵敏度、特异性、准确率均明显高于MRI检查和DWI检查,差异有统计学意义(P<0.05);MRI检查、DWI检查、MRI结合DWI检查均与脑囊虫病存在一定程度的正相关性(P<0.05).结论 MRI结合DWI检查是脑囊虫病的有效诊断手段之一,可显著提高脑囊虫病的诊断准确率.     

Diffusion tensor imaging to study anisotropy in a particular porous system: the trabecular bone network

During the last decade, considerable effort has been invested into the development of diffusion tensor imaging (DTI) mainly used to investigate cerebral morphology. The aim of this paper is to review and to discuss our recent results about high magnetic field DTI application to study spongy bone tissue. Due to its peculiar properties, spongy bone represents a particular porous system sample. Strategies to perform DTI on porous systems and issues linked to DTI outcome interpretation are presented on the basis of our results concerning trabecular bone network characterization.     

Functional MRI for radiotherapy dose painting

Modern radiation therapy techniques are exceptionally flexible in the deposition of radiation dose in a target volume. Complex distributions of dose can be delivered reliably, so that the tumor is exposed to a high dose, whereas nearby healthy structures can be avoided. As a result, an increase in curative dose is no longer invariably associated with an increased level of toxicity. This modern technology can be exploited further by modulating the required dose in space so as to match the variation in radiation sensitivity in the tumor. This approach is called dose painting.     

Diffusion-weighted magnetic resonance imaging to evaluate microvascular density after transarterial embolization ablation in a rabbit VX2 liver tumor model

Objective

To evaluate the correlation between findings from diffusion weighted imaging (DWI) and microvascular density (MVD) measurements in VX2 liver tumors after transarterial embolization ablation (TEA).

Materials and Methods

Eighteen New Zealand white rabbits were used in this study. VX2 tumor cells were implanted in livers by percutaneous puncture under computed tomography (CT) guidance. Two weeks later, all rabbits underwent conventional magnetic resonance imaging (MRI) (T1 and T2 imaging), DWI, (b = 100, 600, and 1000 s/mm²) and TEA. MRI was performed again1 week after TEA. Liver tissue was then harvested and processed for hematoxylin and eosin (H&E) staining and immunohistochemical staining for CD31to determine MVD.

Results

VX2 liver tumors were successfully established in all 18 rabbits. Optimal contrast was achieved with a b value of 600 s/mm².The maximum pre-operative apparent diffusion coefficient (ADC)_difference value was 0.28 × 10^− 3 ± 0.10 × 10^− 3 mm²/s, and was significantly different (P < 0.001) from the maximum postoperative ADC_difference value of 0.47 × 10^− 3 ± 0.10 × 10^− 3 mm²/s. However, the mean ADC value for the entire tumor was not significantly correlated with MVD (r = 0.221, P = 0.379), nor was the ADC value for the regions of viable tumor (r = − 0.044, P = 0.862). However, the maximum postoperative ADC_difference value was positively correlated with MVD(r = 0.606, F = 12.247, P = 0.003).

Conclusion

DWI is effective to evaluate the therapeutic efficacy of TEA. The maximum ADC_difference offers a promising new method to noninvasively assess tumor angiogenesis.