Characterization of clear cell renal cell carcinoma with diffusion kurtosis imaging: correlation between diffusion kurtosis parameters and tumor cellularity

The aim of this study was to evaluate the role of diffusion kurtosis imaging (DKI) in the characterization of clear cell renal cell carcinoma (ccRCC) and to correlate DKI parameters with tumor cellularity. Fifty‐nine patients with pathologically diagnosed ccRCCs were evaluated by DKI on a 3‐T scanner. Regions of interest were drawn on the maps of the mean diffusion coefficient (MD) and mean diffusion kurtosis (MK). All ccRCCs were histologically graded according to the Fuhrman classification system. Tumor cellularity was measured by the nuclear‐to‐cytoplasm (N/C) ratio and the number of tumor cell nuclei (NTCN). ccRCCs were classified as grade 1 (n = 23), grade 2 (n = 24), grade 3 (n = 10) and grade 4 (n = 3). Both MD and MK could readily discriminate between normal renal parenchyma and ccRCCs (p < 0.001), and receiver operating characteristic (ROC) curve analysis showed that MK exhibited a better performance with an area under the ROC curve of 0.874 and sensitivity/specificity of 68.33%/100% (p < 0.001). Further, MD and MK were significantly different between grade 1 and grades 3 and 4 (p = 0.01, p < 0.001) and between grade 2 and grades 3 and 4 (p = 0.015, p < 0.005), respectively. However, no significant difference was found between grade 1 and grade 2 (p > 0.05) for both MD and MK. With regard to NTCN, no significant difference was found between any two grades (p > 0.05), and the N/C ratio changed significantly with grade (p < 0.01, between any two grades). Negative correlations were found between MK and MD (r = –0.56, p < 0.001), and between MD and N/C ratio (r = –0.36, p < 0.005), whereas MK and the N/C ratio were positively correlated (r = 0.45, p = 0.003). DKI could quantitatively characterize ccRCC with different grades by probing non‐Gaussian diffusion properties related to changes in the tumor microenvironment or tissue complexities in the tumor. Copyright © 2016 John Wiley & Sons, Ltd.     

Noise protection with N-acetyl-l-cysteine (NAC) using a variety of noise exposures,NAC doses,and routes of administration

Conclusion. These studies extend previous work on N-acetyl-l-cysteine (NAC) and noise, showing protection with NAC against a high-kurtosis noise, showing protection with NAC at low doses, as well as protection by oral gavage. The studies further reveal the potential for the use of NAC in a clinical population exposed to noise. Objective. To extend previous work on NAC protection from noise, the current study examined the effectiveness of NAC against a high-kurtosis noise that combined continuous and impact noise, tested the effectiveness of NAC at varying doses, and tested NAC when administered by gavage. Materials and methods. Chinchillas were tested for auditory brainstem responses (ABRs) at five frequencies before and at three time points after one of three noise exposures: high-kurtosis (2 h, 108 dB L_eq), impulse (75 pairs of 155 dB pSPL impulses), or continuous (4 kHz octave band, 105 dB SPL for 6 h). Animals were treated with NAC or saline vehicle before and after noise. Results. The NAC was protective against the high-kurtosis noise both at low doses and when given orally by gavage.     

Double‐pulsed diffusional kurtosis imaging

Diffusional kurtosis imaging (DKI) is extended to double‐pulsed‐field‐gradient (d‐PFG) diffusion MRI sequences. This gives a practical approach for acquiring and analyzing d‐PFG data. In particular, the leading d‐PFG effects, beyond what conventional single‐pulsed field gradient (s‐PFG) provides, are interpreted in terms of the kurtosis for a diffusion displacement probability density function (dPDF) in a six‐dimensional (6D) space. The 6D diffusional kurtosis encodes the unique information provided by d‐PFG sequences up to second order in the b‐value. This observation leads to a compact expression for the signal magnitude, and it suggests novel data acquisition and analysis methods. Double‐pulsed DKI (DP‐DKI) is demonstrated for in vivo mouse brain with d‐PFG data obtained at 7 T. Copyright © 2014 John Wiley & Sons, Ltd.     

Oscillating gradient diffusion kurtosis imaging of normal and injured mouse brains

Recent advances in diffusion MRI employ multiple diffusion encoding schemes with varying diffusion direction, weighting, and diffusion time to investigate specific microstructural properties in biological tissues. In this study, we examined time‐dependent diffusion kurtosis contrast in adult mouse brains and in neonatal mouse brains after hypoxic–ischemic (HI) injury. In vivo diffusion kurtosis maps were acquired with a short diffusion time using an oscillating gradient spin echo (OGSE) sequence at 100 Hz and with a relatively long diffusion time (20 ms) using a pulsed gradient spin echo (PGSE) sequence. In the adult mouse brain, we found that the cortex and hippocampus showed larger differences between OGSE kurtosis and PGSE kurtosis than major white matter tracts. In neonatal mouse brains with unilateral HI injury, the OGSE kurtosis map overall provided stronger edema contrast than the PGSE kurtosis map, and the differences between OGSE and PGSE kurtosis measurements in the edema region reflected heterogeneity of injury. This is the first in vivo study that has demonstrated multi‐direction OGSE kurtosis contrasts in the mouse brain. Comparing PGSE and OGSE kurtosis measures may provide additional information on microstructural changes after ischemic stroke.     

Application of diffusional kurtosis imaging to detect occult brain damage in multiple sclerosis and neuromyelitis optica

Multiple sclerosis (MS) and neuromyelitis optica (NMO) are two common types of inflammatory demyelinating disease of the central nervous system. Early distinction of NMO from MS is crucial but quite challenging. In this study, 13 NMO spectrum disorder patients (Expanded Disability Status Scale (EDSS) of 3.0 ± 1.7, ranging from 2 to 6.5; disease duration of 5.3 ± 4.7 years), 17 relapsing–remitting MS patients (EDSS of 2.6 ± 1.4, ranging from 1 to 5.5; disease duration of 7.9 ± 7.8 years) and 18 healthy volunteers were recruited. Diffusional kurtosis imaging was employed to discriminate NMO and MS patients at the early or stable stage from each other, and from healthy volunteers. The presence of alterations in diffusion and diffusional kurtosis metrics in normal‐appearing white matter (NAWM) and diffusely increased mean diffusivity (MD) in the cortical normal‐appearing gray matter (NAGM) favors the diagnosis of MS rather than NMO. Meanwhile, normal diffusivities and kurtosis metrics in all NAWM as well as increases in MD in the frontal and temporal NAGM suggest NMO. Our results suggest that diffusion and diffusional kurtosis metrics may well aid in discriminating the two diseases.     

Diffusion MRI detects early brain microstructure abnormalities in 2‐month‐old 3×Tg‐AD mice

The 3×Tg‐AD mouse is one of the most studied animal models of Alzheimer's disease (AD), and develops both amyloid beta deposits and neurofibrillary tangles in a temporal and spatial pattern that is similar to human AD pathology. Additionally, abnormal myelination patterns with changes in oligodendrocyte and myelin marker expression are reported to be an early pathological feature in this model. Only few diffusion MRI (dMRI) studies have investigated white matter abnormalities in 3×Tg‐AD mice, with inconsistent results. Thus, the goal of this study was to investigate the sensitivity of dMRI to capture brain microstructural alterations in 2‐month‐old 3×Tg‐AD mice. In the fimbria, the fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), and radial kurtosis (K_┴) were found to be significantly lower in 3×Tg‐AD mice than in controls, while the mean diffusivity (MD) and radial diffusivity (D_┴) were found to be elevated. In the fornix, K_┴ was lower for 3×Tg‐AD mice; in the dorsal hippocampus MD and D_┴ were elevated, as were FA, MD, and D_┴ in the ventral hippocampus. These results indicate, for the first time, dMRI changes associated with myelin abnormalities in young 3×Tg‐AD mice, before they develop AD pathology. Morphological quantification of myelin basic protein immunoreactivity in the fimbria was significantly lower in the 3×Tg‐AD mice compared with the age‐matched controls. Our results demonstrate that dMRI is able to detect widespread, significant early brain morphological abnormalities in 2‐month‐old 3×Tg‐AD mice.     

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.     

扩散峰度成像对上皮性卵巢癌分型的鉴别诊断

目的 探讨扩散峰度成像（DKI）对Ⅰ型与Ⅱ型上皮性卵巢癌（EOC）的鉴别诊断价值。 方法 回顾性收集经手术病理证实的45例EOC病人的临床、病理及影像资料,平均年龄（50±13）岁。根据术后病理结果对EOC病人进行分组,分为Ⅰ型组（24例）和Ⅱ型组（21例）。所有病人均于术前行盆腔DKI检查,由2名放射科医师在DKI各参数伪彩图上分别测量平均扩散峰度（MK）、平行扩散峰度（Ka）、垂直扩散峰度（Kr）、平均扩散系数（MD）、平行扩散系数（Da）、垂直扩散系数（Dr）、各向异性分数（FA）、峰度各向异性分数（FAk）。采用Fisher确切概率检验、独立样本t检验或Mann-Whitney U检验比较2组间临床、病理及影像资料的差异,对差异有统计学意义的参数绘制受试者操作特征（ROC）曲线,分析其鉴别诊断效能。 结果 病理表现上,Ⅰ型中交界性肿瘤占比最高（50.0%）,Ⅱ型中浆液性癌占比最高（61.9%）;Ⅰ型中高分化癌占50%,Ⅱ型多表现为中低分化癌 （76.2%）,Ⅰ型EOC的分化程度高于Ⅱ型;Ⅰ型多数处于Ⅰ期（79.2%）,Ⅱ型多处于Ⅲ期(57.1%)（均P<0.05）。MRI影像上, Ⅰ型病灶多表现为囊性(41.7%)或囊实性（33.3%）,Ⅱ型多表现为实性（52.3%）;Ⅱ型（66.7%）腹水发生率高于Ⅰ型（29.2%）（均P<0.05）。Ⅰ型的MK、Ka和Kr值低于Ⅱ型,MD、Da和Dr值高于Ⅱ型（均P<0.05）。ROC曲线分析显示,MK阈值为0.504时,鉴别2组诊断的曲线下面积（AUC,0.817）最大,诊断敏感度（95.2%）、阴性预测值（92.9%）、准确度（78.9%）也最高,Da阈值为2.190时鉴别诊断的AUC（0.770）最小,而特异度（76.2%）、阳性预测值（75.9%）最高。 结论 DKI序列的定量参数MK、Ka、Kr、MD、Da及Dr均有助于鉴别Ⅰ型与Ⅱ型EOC,其中MK值鉴别诊断效能更大。