基于3D深度残差网络和多模态MRI的脑胶质瘤自动分级

目的:利用3D深度残差网络和多模态MRI实现对脑胶质瘤的自动分级。方法:利用BraTS2020公共数据集的293例高级别胶质瘤（HGG）和76例低级别胶质瘤（LGG）的多模态MRI数据训练和测试3D深度残差卷积网络模型。多模态MRI图像经过3D剪裁、重采样和归一化的预处理,随机分组为训练（64%）、验证（16%）和测试（20%）样本,将预处理后的多模态MRI图像和分级标注输入到网络模型进行训练、验证和测试。利用准确率（ACC）和受试者工作特征（ROC）曲线下面积（AUC）评价分级结果。结果:在59例（48例HGG和11例LGG）验证数据集上,ACC和AUC分别为0.93和0.97,在75例（62例HGG和13例LGG）测试数据集上,ACC和AUC分别为0.89和0.93。结论:3D深度残差网络在多模态MRI数据集上获得了较好的脑胶质瘤自动分级结果,可以为确定治疗方案和预测预后方面提供重要参考。     

Triggered intravoxel incoherent motion MRI for the assessment of calf muscle perfusion during isometric intermittent exercise

The main aim of this paper was to propose triggered intravoxel incoherent motion (IVIM) imaging sequences for the evaluation of perfusion changes in calf muscles before, during and after isometric intermittent exercise. Twelve healthy volunteers were involved in the study. The subjects were asked to perform intermittent isometric plantar flexions inside the MRI bore. MRI of the calf muscles was performed on a 3.0 T scanner and diffusion‐weighted (DW) images were obtained using eight different b values (0 to 500 s/mm²). Acquisitions were performed at rest, during exercise and in the subsequent recovery phase. A motion‐triggered echo‐planar imaging DW sequence was implemented to avoid movement artifacts. Image quality was evaluated using the average edge strength (AES) as a quantitative metric to assess the motion artifact effect. IVIM parameters (diffusion D, perfusion fraction f and pseudo‐diffusion D*) were estimated using a segmented fitting approach and evaluated in gastrocnemius and soleus muscles. No differences were observed in quality of IVIM images between resting state and triggered exercise, whereas the non‐triggered images acquired during exercise had a significantly lower value of AES (reduction of more than 20%). The isometric intermittent plantar‐flexion exercise induced an increase of all IVIM parameters (D by 10%; f by 90%; D* by 124%; fD* by 260%), in agreement with the increased muscle perfusion occurring during exercise. Finally, IVIM parameters reverted to the resting values within 3 min during the recovery phase. In conclusion, the IVIM approach, if properly adapted using motion‐triggered sequences, seems to be a promising method to investigate muscle perfusion during isometric exercise.     

Correlative assessment of tumor microcirculation using contrast‐enhanced perfusion MRI and intravoxel incoherent motion diffusion‐weighted MRI: is there a link between them?

The purpose of this study was to correlate intravoxel incoherent motion (IVIM) imaging with classical perfusion‐weighted MRI metrics in human gliomas. Parametric images for slow diffusion coefficient (D), fast diffusion coefficient (D*), and fractional perfusion‐related volume (f) in patients with high‐grade gliomas were generated. Maps of F_p (plasma flow), v_p (vascular plasma volume), PS (permeability surface–area product), v_e (extravascular, extracellular volume), E (extraction ratio), k_e (influx ratio into the interstitium), and t_c (vascular transit time) from dynamic contrast‐enhanced (DCE) and dynamic susceptibility contrast‐enhanced (DSC) MRI were also generated. A region‐of‐interest analysis on the contralateral healthy white matter and on the tumor areas was performed and the extracted parameter values were tested for any significant differences among tumor grades or any correlations. Only f could be significantly correlated to DSC‐derived v_p and t_c in healthy brain tissue. Concerning the tumor regions, F_p was significantly positively correlated with D* and inversely correlated with f in DSC measurements. The D*, f, and f × D* values in the WHO grade III gliomas were non‐significantly different from those in the grade IV gliomas. There was a trend to significant negative correlations between f and PS as well as between f × D* and k_e in DCE experiments. Presumably due to different theoretical background, tracer properties and modeling of the tumor vasculature in the IVIM theory, there is no clearly evident link between D*, f and DSC‐ and DCE‐derived metrics. Copyright © 2014 John Wiley & Sons, Ltd.     

Delineation of gliomas using radial metabolite indexing

¹H MRSI has demonstrated the ability to characterise and delineate brain tumours, but robust data analysis methods are still needed. In this study, we present an objective analysis method for MRSI data to delineate tumour abnormality regions. The presented method is a development of the choline‐to‐N‐acetylaspartate index (CNI), which uses perpendicular distances in a choline versus N‐acetylaspartate plot as a measure of abnormality. We propose a radial CNI (rCNI) method that uses the choline to N‐acetylaspartate ratio directly as an abnormality measure. To avoid problems with small or zero denominators, we perform an arctangent transformation. CNI abnormality contours were evaluated using a z‐score threshold of 2 (CNI2) and 2.5 (CNI2.5) and compared with rCNI2. Simulations modelling low‐grade (LGG) and high‐grade (HGG) gliomas with different tissue compartments and partial volume effects suggest improved specificity of rCNI2 (LGG 92%/HGG 91%) over CNI2 (LGG 69%/HGG 69%) and CNI2.5 (LGG 74%/HGG 75%), whilst retaining a similar sensitivity to both CNI2 and CNI2.5. Our simulation results also confirm a previously reported increase in specificity of CNI2.5 over CNI2 with little penalty in sensitivity. The analysis of MRSI data acquired from 10 patients with low‐grade glioma at 3 T suggests a more robust delineation of the lesions using rCNI with respect to conventional imaging compared with standard CNI. Further analysis of 29 glioma datasets acquired at 1.5 T, together with previously published estimated tumour proportions, suggests that rCNI has higher sensitivity and specificity for the identification of abnormal MRSI voxels. Copyright © 2014 John Wiley & Sons, Ltd.     

Relationship between diffusion parameters derived from intravoxel incoherent motion MRI and perfusion measured by dynamic contrast‐enhanced MRI of soft tissue tumors

Our aim was to evaluate the link between diffusion parameters measured by intravoxel incoherent motion (IVIM) diffusion‐weighted imaging (DWI) and the perfusion metrics obtained with dynamic contrast‐enhanced (DCE) MRI in soft tissue tumors (STTs). Twenty‐eight patients affected by histopathologically confirmed STT were included in a prospective study. All patients underwent both DCE MRI and IVIM DWI. The perfusion fraction f, diffusion coefficient D and perfusion‐related diffusion coefficient D* were estimated using a bi‐exponential function to fit the DWI data. DCE MRI was acquired with a temporal resolution of 3–5 s. Maps of the initial area under the gadolinium concentration curve (IAUGC), time to peak (TTP) and maximum slope of increase (MSI) were derived using commercial software. The relationships between the DCE MRI and IVIM DWI measurements were assessed by Spearman's test. To exclude false positive results under multiple testing, the false discovery rate (FDR) procedure was applied. The Mann–Whitney test was used to evaluate the differences between all variables in patients with non‐myxoid and myxoid STT. No significant relationship was found between IVIM parameters and any DCE MRI parameters. Higher f and D*f values were found in non‐myxoid tumors compared with myxoid tumors (p = 0.004 and p = 0.003, respectively). MSI was significantly higher in non‐myxoid tumors than in myxoid tumors (p = 0.029). From the visual assessments of single clinical cases, both f and D*f maps were in satisfactory agreement with DCE maps in the extreme cases of an avascular mass and a highly vascularized mass, whereas, for tumors with slight vascularity or with a highly heterogeneous perfusion pattern, this association was not straightforward. Although IVIM DWI was demonstrated to be feasible in STT, our data did not support evident relationships between perfusion‐related IVIM parameters and perfusion measured by DCE MRI. Copyright © 2015 John Wiley & Sons, Ltd.     

Intravoxel incoherent motion imaging kinetics during chemoradiotherapy for human papillomavirus‐associated squamous cell carcinoma of the oropharynx: preliminary results from a prospective pilot study

This study aims to identify the temporal kinetics of intravoxel incoherent motion (IVIM) MRI in patients with human papillomavirus‐associated (HPV+) oropharyngeal squamous cell carcinoma. Patients were enrolled under an Institutional Review Board (IRB)‐approved protocol as part of an ongoing prospective clinical trial. All patients underwent two MRI studies: a baseline scan before chemoradiotherapy and a mid‐treatment scan 3–4 weeks after treatment initiation. Parametric maps representing pure diffusion coefficient (D), pseudo‐diffusion coefficient (D*), perfusion fraction (f) and apparent diffusion coefficient (ADC) were generated. The Mann–Whitney U‐test was used to assess the temporal variation of IVIM metrics. Bayesian quadratic discriminant analysis (QDA) was used to evaluate the extent to which mid‐treatment changes in IVIM metrics could be combined to predict sites that would achieve complete response (CR) in multivariate analysis. Thirty‐one patients were included in the final analysis with 59 lesions. Pretreatment ADC and D values of the CR lesions (n = 19) were significantly lower than those of non‐CR lesions (n = 33). Mid‐treatment ADC, D and f values were significantly higher (p < 0.0001) than pretreatment values for all lesions. Each increase in normalized ΔADC of size 0.1 yielded a 1.45‐fold increase in the odds of CR (p < 0.0003), each increase in normalized ΔD of size 0.1 yielded a 1.53‐fold increase in the odds of CR (p < 0.0002), and each unit increase in Δf yielded a 2.29‐fold increase in the odds of CR (p < 0.02). Combined ΔD and ΔADC were integrated into a multivariate prediction model and attained an AUC of 0.87 (95% confidence interval: 0.79, 0.96), as well as a sensitivity of 0.63, specificity of 0.85 and accuracy of 0.78, under leave‐one‐out cross‐validation. In conclusion, IVIM is feasible and potentially useful in the prediction and assessment of the early response of HPV+ oropharyngeal squamous cell carcinoma to chemoradiotherapy. Copyright © 2015 John Wiley & Sons, Ltd.     

Stroke assessment with intravoxel incoherent motion diffusion‐weighted MRI

Intravoxel incoherent motion (IVIM) diffusion‐weighted MRI can simultaneously measure diffusion and perfusion characteristics in a non‐invasive way. This study aimed to determine the potential utility of IVIM in characterizing brain diffusion and perfusion properties for clinical stroke. The multi‐b‐value diffusion‐weighted images of 101 patients diagnosed with acute/subacute ischemic stroke were retrospectively evaluated. The diffusion coefficient D, representing the water apparent diffusivity, was obtained by fitting the diffusion data with increasing high b‐values to a simple mono‐exponential model. The IVIM‐derived perfusion parameters, pseudodiffusion coefficient D*, vascular volume fraction f and blood flow‐related parameter fD*, were calculated with the bi‐exponential model. Additionally, the apparent diffusion coefficient (ADC) was fitted according to the mono‐exponential model using all b‐values. The diffusion parameters for the ischemic lesion and normal contralateral region were measured in each patient. Statistical analysis was performed using the paired Student t‐test and Pearson correlation test. Diffusion data in both the ischemic lesion and normal contralateral region followed the IVIM bi‐exponential behavior, and the IVIM model showed better goodness of fit than the mono‐exponential model with lower Akaike information criterion values. The paired Student t‐test revealed significant differences for all diffusion parameters (all P < 0.001) except D* (P = 0.218) between ischemic and normal areas. For all patients in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001) and f (r = 0.541, P < 0.001; r = 0.262, P = 0.008); significant correlation was also found between ADC and fD* in the ischemic region (r = 0.254, P = 0.010). For all pixels within the region of interest from a representative subject in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001), f (r = 0.823, P < 0.001; r = 0.652, P < 0.001) and fD* (r = 0.294, P < 0.001; r = 0.340, P < 0.001). These findings may have clinical implications for the use of IVIM imaging in the assessment and management of acute/subacute stroke patients. Copyright © 2016 John Wiley & Sons, Ltd.     

Assessment of diffusion parameters by intravoxel incoherent motion MRI in head and neck squamous cell carcinoma

The objectives of this study were to assess the diffusion parameters derived from intravoxel incoherent motion (IVIM) MRI in head and neck squamous cell carcinoma (HNSCC) and to investigate the agreement between different methods of tumor delineation and two numerical methods to extract the perfusion fraction f. Thirty‐seven untreated patients with histopathologically confirmed primary HNSCC were included retrospectively in the study. The entire volume of the primary tumor was outlined on diffusion‐weighted images using co‐registered morphological images as a guide to the tumor location. Apparent diffusion coefficient (ADC) and IVIM diffusion parameters were estimated considering the largest tumor section as well as the entire tumor volume. A bi‐exponential fit was implemented to extract f, D (pure diffusion coefficient) and D* (pseudo‐diffusion coefficient). A second simplified method, based on an asymptotic extrapolation, was used to determine f. The agreement between ADC and IVIM diffusion parameters derived from the delineation of single and multiple slices, and between the two f estimations, was assessed by Bland–Altman plots. The inter‐slice variability of ADC and IVIM diffusion parameters was evaluated. The Kruskal–Wallis test was used to investigate whether the tumor location had a statistically significant influence on the values of the parameters. Comparing the tumor delineation methods, a better accordance was found for ADC and D, with a mean percentage difference of less than 2%. Larger discrepancies were found for f and D*, with mean differences of 4.5% and 5.5%, respectively. When comparing the two f estimation methods, small mean differences were found (<3.5%), suggesting that the two methods may be considered as equivalent for the assessment of f in our patient population. The observed ADC and IVIM diffusion parameters were dependent on the anatomic site of the lesion, carcinoma of the nasopharynx showing more homogeneous and dissimilar estimations than other HNSCCs. Copyright © 2013 John Wiley & Sons, Ltd.     

Diffusion‐weighted MRI with intravoxel incoherent motion modeling for assessment of muscle perfusion in the thigh during post‐exercise hyperemia in younger and older adults

Aging is associated with impaired endothelium‐dependent vasodilation that leads to muscle perfusion impairment and contributes to organ dysfunction. Impaired muscle perfusion may result in inadequate delivery of oxygen and nutrients during and after muscle contraction, leading to muscle damage. The ability to study the relationship between perfusion and muscle damage has been limited using traditional muscle perfusion measures, which are invasive and risky. To overcome this limitation, we optimized a diffusion‐weighted MRI sequence and validated an intravoxel incoherent motion (IVIM) analysis based on Monte Carlo simulation to study muscle perfusion impairment with aging during post‐exercise hyperemia. Simulation results demonstrated that the bias of IVIM‐derived perfusion fraction (f_p ) and diffusion of water molecules in extra‐vascular tissue (D ) ranged from ?3.3% to 14% and from ?16.5% to 0.002%, respectively, in the optimized experimental condition. The dispersion in f_p and D ranged from 3.2% to 9.5% and from 0.9% to 1.1%, respectively. The mid‐thigh of the left leg of four younger (21–30 year old) and four older (60–90 year old) healthy females was studied using the optimized protocol at baseline and at seven time increments occurring every 3.25 min following in‐magnet dynamic knee extension exercise performed using a MR‐compatible ergometer with a workload of 0.4 bar for 2.5 min. After exercise, both f_p and D significantly increased in the rectus femoris (active muscle during exercise) but not in adductor magnus (inactive muscle), reflecting the fact that the local increase in perfusion with both groups showed a maximum value in the second post‐exercise time‐point. A significantly greater increase in perfusion from the baseline (p < 0.05) was observed in the younger group (37 ± 12.05%) compared with the older group (17.57 ± 15.92%) at the first post‐exercise measurement. This work establishes a reliable non‐invasive method that can be used to study the effects of aging on dynamic changes in muscle perfusion as they relate to important measures of physical function.     

APT、ASL及DCE-MRI在胶质瘤分级诊断中的应用

目的:探讨酰胺质子转移成像（APT）、动脉自旋标记技术（ASL）、动态对比增强磁共振成像（DCE-MRI）等多模态MRI技术对胶质瘤术前分级诊断的价值。方法:前瞻性收集41例经病理证实的胶质瘤患者,其中低级别胶质瘤（LGG）18例、高级别胶质瘤（HGG）23例。由2名医生独立测量获取肿瘤实质区的平均APT（mAPT）、平均脑血流量（mCBF）、平均容积转运常数（mKtrans）,并计算测量者之间的一致性系数（ICC）。采用受试者工作特征曲线比较各参数区分LGG和HGG的诊断效能,并对不同成像技术的AUC进行比较,最后采用二元逻辑回归的方法进行多模态联合评估。结果:测量者之间一致性良好。HGG肿瘤实质区的mAPT、mCBF、mKtrans均大于LGG,差异均具有统计学意义（P<0.05）。当独立应用于分级诊断时,mAPT、mCBF、mKtrans的 AUC分别为0.96、0.91、0.93;mAPT、mCBF、mKtrans敏感性分别为0.91、0.91、0.83;mKtrans、mAPT、mCBF特异性分别为1.00、0.94、0.83。当联合应用于分级诊断时,3种成像技术联合显示出最佳诊断效能。三者联合的AUC可达1.00,mAPT联合mCBF、mCBF联合mKtrans、mAPT联合mKtrans的AUC分别为0.99、0.99、 0.97;三者联合的敏感性可达1.00,mAPT联合mCBF、mCBF联合mKtrans 、mAPT联合mKtrans的敏感性分别为0.96、0.96、0.91;三者联合的特异性为0.94,其中任意两者联合的特异性均可达1.00。结论:APT、ASL、DCE-MRI这3种技术对胶质瘤术前分级均显示出良好的诊断价值,其中APT诊断效能最好,ASL最差,3种技术的AUC无统计学差异。当联合应用于分级诊断时,可提高鉴别诊断的能力,其中3种技术的联合是强大的胶质瘤分级技术。     

Hierarchical non‐negative matrix factorization to characterize brain tumor heterogeneity using multi‐parametric MRI

Tissue characterization in brain tumors and, in particular, in high‐grade gliomas is challenging as a result of the co‐existence of several intra‐tumoral tissue types within the same region and the high spatial heterogeneity. This study presents a method for the detection of the relevant tumor substructures (i.e. viable tumor, necrosis and edema), which could be of added value for the diagnosis, treatment planning and follow‐up of individual patients. Twenty‐four patients with glioma [10 low‐grade gliomas (LGGs), 14 high‐grade gliomas (HGGs)] underwent a multi‐parametric MRI (MP‐MRI) scheme, including conventional MRI (cMRI), perfusion‐weighted imaging (PWI), diffusion kurtosis imaging (DKI) and short‐TE ¹H MRSI. MP‐MRI parameters were derived: T₂, T₁ + contrast, fluid‐attenuated inversion recovery (FLAIR), relative cerebral blood volume (rCBV), mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK) and the principal metabolites lipids (Lip), lactate (Lac), N‐acetyl‐aspartate (NAA), total choline (Cho), etc. Hierarchical non‐negative matrix factorization (hNMF) was applied to the MP‐MRI parameters, providing tissue characterization on a patient‐by‐patient and voxel‐by‐voxel basis. Tissue‐specific patterns were obtained and the spatial distribution of each tissue type was visualized by means of abundance maps. Dice scores were calculated by comparing tissue segmentation derived from hNMF with the manual segmentation by a radiologist. Correlation coefficients were calculated between each pathologic tissue source and the average feature vector within the corresponding tissue region. For the patients with HGG, mean Dice scores of 78%, 85% and 83% were obtained for viable tumor, the tumor core and the complete tumor region. The mean correlation coefficients were 0.91 for tumor, 0.97 for necrosis and 0.96 for edema. For the patients with LGG, a mean Dice score of 85% and mean correlation coefficient of 0.95 were found for the tumor region. hNMF was also applied to reduced MRI datasets, showing the added value of individual MRI modalities. Copyright © 2015 John Wiley & Sons, Ltd.     

Multi‐centre reproducibility of diffusion MRI parameters for clinical sequences in the brain

The purpose of this work was to assess the reproducibility of diffusion imaging, and in particular the apparent diffusion coefficient (ADC), intra‐voxel incoherent motion (IVIM) parameters and diffusion tensor imaging (DTI) parameters, across multiple centres using clinically available protocols with limited harmonization between sequences. An ice–water phantom and nine healthy volunteers were scanned across fives centres on eight scanners (four Siemens 1.5T, four Philips 3T). The mean ADC, IVIM parameters (diffusion coefficient D and perfusion fraction f) and DTI parameters (mean diffusivity MD and fractional anisotropy FA), were measured in grey matter, white matter and specific brain sub‐regions. A mixed effect model was used to measure the intra‐ and inter‐scanner coefficient of variation (CV) for each of the five parameters. ADC, D, MD and FA had a good intra‐ and inter‐scanner reproducibility in both grey and white matter, with a CV ranging between 1% and 7.4%; mean 2.6%. Other brain regions also showed high levels of reproducibility except for small structures such as the choroid plexus. The IVIM parameter f had a higher intra‐scanner CV of 8.4% and inter‐scanner CV of 24.8%. No major difference in the inter‐scanner CV for ADC, D, MD and FA was observed when analysing the 1.5T and 3T scanners separately. ADC, D, MD and FA all showed good intra‐scanner reproducibility, with the inter‐scanner reproducibility being comparable or faring slightly worse, suggesting that using data from multiple scanners does not have an adverse effect compared with using data from the same scanner. The IVIM parameter f had a poorer inter‐scanner CV when scanners of different field strengths were combined, and the parameter was also affected by the scan acquisition resolution. This study shows that the majority of diffusion MRI derived parameters are robust across 1.5T and 3T scanners and suitable for use in multi‐centre clinical studies and trials. © 2015 The Authors NMR in Biomedicine Published by John Wiley & Sons Ltd.     

Immune tumoral microenvironment in gliomas: focus on CD3+ T cells,Vδ1+ T cells,and microglia/macrophages

Gliomas are histologically defined as low-grade gliomas (LGG) and high-grade gliomas (HGG). The most common type of HGG is the glioblastoma (GBM). We aimed to determine the immunological characteristics of CD3 T-cells, Vδ1 T-cells, and microglia/macrophages infiltrating brain gliomas. We collected 24 formalin-fixed paraffin-embedded samples issued from 19 cases of GBM and 5 cases of LGG. An immunohistochemical analysis was performed using anti-CD3, anti-Vδ1, and anti-iba-1 antibodies. Labelling indexes (LI) of CD3 and Vδ1 were evaluated quantitatively, and other CD3, Vδ1, and iba-1 staining characteristics were evaluated qualitatively. The median age of patients was 49 years in GBM and 52 years in LGG. The sex ratio was 1.4 and GBM predominated in males (p?=?0.05). In GBM, the medians of CD3-LI and Vδ1-LI were 30 and 3.5 respectively. CD3-LI inversely correlated with survival in GBM cases (r?=????0.543; p?=?0.016). CD3 staining intensity correlated with CD3-LI (p?<?0.0001) and with the survival in GBM cases (p?=?0.003). Compared to LGG, the CD3-LI, the intensity of intra-tumoral Vδ1 staining, and the amount of iba-1 were higher in GBM (p?=?0.042; p?=?0.014; and p?=?0.001 respectively). The iba-1 organization was more amoeboid in older patients and more branched in younger patients (p?=?0.028) and tended to be more amoeboid in cases with high iba-1 amount (p?=?0.09). Our results suggest that a high level of CD3-LI and a strong intra-tumoral infiltration of Vδ1 T-cells as well as a high involvement of TAM can be considered potential markers of poor prognosis of GBM. However, this requires further studies on more balanced GBM-LGG sample, including an expanded panel of biomarkers.

     

An intravoxel oriented flow model for diffusion‐weighted imaging of the kidney

By combining intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI) we introduce a new diffusion model called intravoxel oriented flow (IVOF) that accounts for anisotropy of diffusion and the flow‐related signal. An IVOF model using a simplified apparent flow fraction tensor (IVOF_f) is applied to diffusion‐weighted imaging of human kidneys. The kidneys of 13 healthy volunteers were examined on a 3 T scanner. Diffusion‐weighted images were acquired with six b values between 0 and 800 s/mm² and 30 diffusion directions. Diffusivity and flow fraction were calculated for different diffusion models. The Akaike information criterion was used to compare the model fit of the proposed IVOF_f model to IVIM and DTI. In the majority of voxels the proposed IVOF_f model with a simplified apparent flow fraction tensor performs better than IVIM and DTI. Mean diffusivity is significantly higher in DTI compared with models that account for the flow‐related signal. The fractional anisotropy of diffusion is significantly reduced when flow fraction is considered to be anisotropic. Anisotropy of the apparent flow fraction tensor is significantly higher in the renal medulla than in the cortex region. The IVOF_f model describes diffusion‐weighted data in the human kidney more accurately than IVIM or DTI. The apparent flow fraction in the kidney proved to be anisotropic.     

Reliable estimation of brain intravoxel incoherent motion parameters using denoised diffusion‐weighted MRI

In this study, we evaluate whether diffusion‐weighted magnetic resonance imaging (DW‐MRI) data after denoising can provide a reliable estimation of brain intravoxel incoherent motion (IVIM) perfusion parameters. Brain DW‐MRI was performed in five healthy volunteers on a 3 T clinical scanner with 12 different b‐values ranging from 0 to 1000 s/mm². DW‐MRI data denoised using the proposed method were fitted with a biexponential model to extract perfusion fraction (PF), diffusion coefficient (D) and pseudo‐diffusion coefficient (D*). To further evaluate the accuracy and precision of parameter estimation, IVIM parametric images obtained from one volunteer were used to resimulate the DW‐MRI data using the biexponential model with the same b‐values. Rician noise was added to generate DW‐MRI data with various signal‐to‐noise ratio (SNR) levels. The experimental results showed that the denoised DW‐MRI data yielded precise estimates for all IVIM parameters. We also found that IVIM parameters were significantly different between gray matter and white matter (P < 0.05), except for D* (P = 0.6). Our simulation results show that the proposed image denoising method displays good performance in estimating IVIM parameters (both bias and coefficient of variation were <12% for PF, D and D*) in the presence of different levels of simulated Rician noise (SNR_b=0 = 20‐40). Simulations and experiments show that brain DW‐MRI data after denoising can provide a reliable estimation of IVIM parameters.     

18F-FET and 18F-choline PET-CT in patients with MRI-suspected low-grade gliomas: a pilot study

AimTo investigate the diagnostic accuracy of O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine (¹⁸F-FET) and fluoromethyl-(¹⁸F)-dimethyl-2-hydroxyethyl-ammonium chloride (¹⁸F-FCH) computed tomography (CT) in patients with primary low-grade gliomas (LGG).MethodsThe study enrolled patients with magnetic resonance imaging (MRI)-suspected LGG. Patients underwent both ¹⁸F-FET and ¹⁸F-FCH positron emission tomography (PET)-CT. Brain PET-CT was performed according to standard protocol – 20 minutes after intravenous injection of 185 MBq of ¹⁸F-FET and 185 MBq of ¹⁸F-FCH PET. Surgery and pathohistological diagnosis were performed in the next two weeks.ResultsWe observed significantly better concordance between tumor histology and ¹⁸F-FET PET (weighted Kappa 0.74) compared with both ¹⁸F-FCH (weighted Kappa 0.15) and MRI (weighted Kappa 0.00). Tumor histology was significantly associated with ¹⁸F-FET (odds ratio 12.87; 95% confidence interval [CI], 0.49-333.70; P = 0.013, logistic regression analysis). Receiver operating characteristic curve analysis comparing ¹⁸F-FCH (area under the curve [AUC] 0.625, 95% CI 0.298-0.884) and ¹⁸F-FET (AUC 0.833, 95% CI 0.499-0.982) showed better diagnostic properties of ¹⁸F-FET (AUC difference 0.208, 95% CI -0.145 to 0.562, P = 0.248).ConclusionPerforming PET-CT in patients with newly diagnosed LGG should be preceded by a selection of an appropriate radiopharmaceutical. ¹⁸F-FET seems to be more accurate than ¹⁸F-FCH in the LGG diagnosis.

Low-grade gliomas (LGG) have been receiving increasing attention due to a better understanding of their natural history and clinical diversity, improvements in pathological classification, development of diagnostic and treatment modalities, and new clinical trials. All of this has changed the management paradigm. LGG are a group of relatively uncommon, diffusely infiltrative malignancies (ie, astrocytomas, oligodendrogliomas) classified as grade II according to the World Health Organization (WHO) 2016 grading system. These gliomas account for approximately 15% of all gliomas, with the incidence rate of 1/100 000 persons per year (1). They arise mostly in the younger and middle-age group, with an average age at diagnosis of 35 years. Although traditionally considered benign, LGG gradually evolve into high-grade tumors. This happens in approximately half of the patients within five years (2). Since LGG are potentially curable tumors, patients need to be correctly diagnosed and treated according to the guidelines. The main treatment modalities are surgery, radiation therapy, and chemotherapy. Patients with low-risk tumors and an indolent disease course, in whom long survival is expected, require active surveillance.The diagnosis of gliomas is based on clinical symptoms, clinical history, brain imaging, and histological and molecular data. Combining different radiological and nuclear medicine techniques allows the visualization of different morphological and functional changes.Preoperative imaging of brain lesions patients with gliomas enables the assessment of size, location, relationship to the functional centers and white matter tracts, as well as of tumor grade. In this setting, multiparametric magnetic resonance imaging (MRI), including both conventional and functional sequences, such as diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), and MR spectroscopy (MRS) serves as a gold standard. LGG usually present as hypointensities on T1-weighted imaging (T1W) and hyperintensities on T2-weighted imaging (T2W) and fluid attenuated inversion recovery (FLAIR) imaging. The lesions can present with intratumoral calcifications or cysts and minimal perilesional edema. Contrast enhancement, if present, is minimal. Nevertheless, although contrast enhancement has been associated with a higher degree of malignancy, some degree of contrast enhancement may be seen in up to 60% of LGG (3). In particular, LGG are characterized by less restricted diffusion on diffusion-weighted sequences, and perfusion parameters similar or lower than that of normal white matter. MRS can help to clarify the diagnosis but does not make it definitive. MRS findings are non-specific, indicative of the neoplastic nature, but not of the degree. A more accurate diagnosis of patients with LGG could be provided by an integration of morphological and functional imaging modalities.Diagnostic possibilities and therapeutic strategies in patients with brain tumors are enhanced by the development of hybrid technology as well as the availability of specific radiopharmaceuticals. Positron emission tomography-computed tomography (PET-CT) scanning is one of the most promising modalities in this setting.O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine (¹⁸F-FET) has been approved as a PET radiopharmaceutical for the characterization of brain lesions suggestive of gliomas. ¹⁸F-FET accumulates in glioma cells due to an increased expression of L-amino acid transporters LAT 1, LAT 2, and LAT 3. ¹⁸F-FET has the advantage of displaying a high tumor-to-background ratio and of not accumulating in inflammatory lesions. Several studies have indicated that ¹⁸F-FET PET in combination with MRI can improve the diagnostic and therapeutic assessment of patients with gliomas for neurosurgery (4-6).Radioactive choline is a tracer of choice in PET imaging of patients with prostate cancer. The use of choline in PET imaging is based on increased phosphorylcholine levels and an elevated phosphatidylcholine turnover in malignant cells. The use of radioactive choline in brain tumors was first described in 1997 (7,8). Because of low uptake in normal brain parenchyma, fluoromethyl-(¹⁸F)-dimethyl-2-hydroxyethyl-ammonium chloride (¹⁸F-FCH) is still a good alternative in diagnostic centers where ¹⁸F-FET is not available.A rat model comparing ¹⁸F-FET and ¹⁸F-choline showed a better performance of ¹⁸F-FET in gliomas (9). No study so far has compared ¹⁸F-FCH and ¹⁸F-FET in patients with LGG. The aim of this pilot study was to determine the diagnostic accuracy of ¹⁸F-FET and ¹⁸F-FCH in patients with LGG.     

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T

Artificial neural networks (ANNs) were used for voxel‐wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was compared with conventional least‐squares regression (LSR) and state‐of‐the‐art multi‐step fitting (LSR‐MS) in Monte‐Carlo simulations and in vivo in terms of estimation accuracy and precision, number of outliers and sensitivity in the distinction between grey (GM) and white (WM) matter. Both the proposed ANN approach and LSR‐MS yielded visually increased parameter map quality. Estimations of all parameters (perfusion fraction f, diffusion coefficient D, pseudo‐diffusion coefficient D*, kurtosis K) were in good agreement with the literature using ANN, whereas LSR‐MS resulted in D* overestimation and LSR yielded increased values for f and D*, as well as decreased values for K. Using ANN, outliers were reduced for the parameters f (ANN, 1%; LSR‐MS, 19%; LSR, 8%), D* (ANN, 21%; LSR‐MS, 25%; LSR, 23%) and K (ANN, 0%; LSR‐MS, 0%; LSR, 15%). Moreover, ANN enabled significant distinction between GM and WM based on all parameters, whereas LSR facilitated this distinction only based on D and LSR‐MS on f, D and K. Overall, the proposed ANN approach was found to be superior to conventional LSR, posing a powerful alternative to the state‐of‐the‐art method LSR‐MS with several advantages in the estimation of IVIM–kurtosis parameters, which might facilitate increased applicability of enhanced diffusion models at clinical scan times.     

Pattern recognition analysis of directional intravoxel incoherent motion MRI in ischemic rodent brains

This study aimed to demonstrate a reliable automatic segmentation method for independently separating reduced diffusion and decreased perfusion areas in ischemic stroke brains using constrained nonnegative matrix factorization (cNMF) pattern recognition in directional intravoxel incoherent motion MRI (IVIM‐MRI). First, the feasibility of cNMF‐based segmentation of IVIM signals was investigated in both simulations and in vivo experiments. The cNMF analysis was independently performed for S₀‐normalized and scaled (by the difference between the maximum and minimum) IVIM signals, respectively. Segmentations of reduced diffusion (from S₀‐normalized IVIM signals) and decreased perfusion (from scaled IVIM signals) areas were performed using the corresponding cNMF pattern weight maps. Second, Monte Carlo simulations were performed for directional IVIM signals to investigate the relationship between the degree of vessel alignment and the direction of the diffusion gradient. Third, directional IVIM‐MRI experiments (x, y and z diffusion‐gradient directions, 20 b values at 7 T) were performed for normal (n = 4), sacrificed (n = 1, no flow) and ischemic stroke models (n = 4, locally reduced flow). The results showed that automatic segmentation of the hypoperfused lesion using cNMF analysis was more accurate than segmentation using the conventional double‐exponential fitting. Consistent with the simulation, the double‐exponential pattern of the IVIM signals was particularly strong in white matter and ventricle regions when the directional flows were aligned with the applied diffusion‐gradient directions. cNMF analysis of directional IVIM signals allowed robust automated segmentation of white matter, ventricle, vascular and hypoperfused regions in the ischemic brain. In conclusion, directional IVIM signals were simultaneously sensitive to diffusion and aligned flow and were particularly useful for automatically segmenting ischemic lesions via cNMF‐based pattern recognition.     

Increased brain perfusion contrast with T2‐prepared intravoxel incoherent motion (T2prep IVIM) MRI

The feasibility to measure brain perfusion using intravoxel incoherent motion (IVIM) MRI has been reported recently with currently clinically available technology. The method is intrinsically local and quantitative, but is contaminated by partial volume effects with cerebrospinal fluid (CSF). Signal from CSF can be suppressed by a 180° inversion recovery (180°‐IR) magnetization preparation, but this also leads to strong suppression of blood and brain tissue signal. Here, we take advantage of the different T₂ relaxations of blood and brain relative to CSF, and implement a T₂‐prepared IVIM (T2prep IVIM) inversion recovery acquisition, which permits a recovery of between 43% and 57% of arterial and venous blood magnetization at excitation time compared with the theoretical recovery of between 27% and 30% with a standard 180°‐IR. We acquired standard IVIM (IVIM), T2prep IVIM and dynamic susceptibility contrast (DSC) images at 3 T using a 32‐multichannel receiver head coil in eight patients with known large high‐grade brain tumors. We compared the contrast and contrast‐to‐noise ratio obtained in the corresponding cerebral blood volume images quantitatively, as well as subjectively by two neuroradiologists. Our findings suggest that quantitative cerebral blood volume contrast and contrast‐to‐noise ratio, as well as subjective lesion detection, contrast quality and diagnostic confidence, are increased with T2prep IVIM relative to IVIM and DSC. Copyright © 2014 John Wiley & Sons, Ltd.     

A metabolomic data fusion approach to support gliomas grading

Magnetic resonance imaging (MRI) is the current gold standard for the diagnosis of brain tumors. However, despite the development of MRI techniques, the differential diagnosis of central nervous system (CNS) primary pathologies, such as lymphoma and glioblastoma or tumor‐like brain lesions and glioma, is often challenging. MRI can be supported by in vivo magnetic resonance spectroscopy (MRS) to enhance its diagnostic power and multiproject‐multicenter evaluations of classification of brain tumors have shown that an accuracy around 90% can be achieved for most of the pairwise discrimination problems. However, the survival rate for patients affected by gliomas is still low. The High‐Resolution Magic‐Angle‐Spinning Nuclear Magnetic Resonance (HR‐MAS NMR) metabolomics studies may be helpful for the discrimination of gliomas grades and the development of new strategies for clinical intervention. Here, we propose to use T₂‐filtered, diffusion‐filtered and conventional water‐presaturated spectra to try to extract as much information as possible, fusing the data gathered by these different NMR experiments and applying a chemometric approach based on Multivariate Curve Resolution (MCR). Biomarkers important for glioma's discrimination were found. In particular, we focused our attention on cystathionine (Cyst) that shows promise as a biomarker for the better prognosis of glioma tumors.