Strong noise attenuation method based on the multiuser kurtosis criterion

The strong noise produced by the leakage of electricity from marine seismic streamers is often received with seismic signals during marine seismic exploration. Traditional denoising methods show unsatisfactory effects when eliminating strong noise of this kind. Assuming that the strong noise signals have the same statistical properties, a blind source separation （BSS） algorithm is proposed in this paper that results in a new denoising algorithm based on the constrained multi-user kurtosis （MUK） optimization criterion. This method can separate strong noise that shares the same statistical properties as the seismic data records and then eliminate them. Theoretical and field data processing all show that the denoising algorithm, based on multi-user kurtosis optimization criterion, is valid for eliminating the strong noise which is produced by the leakage of electricity from the marine seismic streamer so as to preserve more effective signals and increase the signal-noise ratio. This method is feasible and widely applicable.

Nonparametric inferences for kurtosis and conditional kurtosis

Under the assumption of strictly stationary process, this paper proposes a nonparametric model to test the kurtosis and conditional kurtosis for risk time series. We apply this method to the daily returns of S＆P500 index and the Shanghai Composite Index, and simulate GARCH data for verifying the efficiency of the presented model. Our results indicate that the risk series distribution is heavily tailed, but the historical information can make its future distribution light-tailed. However the far future distribution＇s tails are little affected by the historical data.

Classification of Intervertebral Disc Degeneration in Low Back Pain Using Diffusional Kurtosis Imaging

Degenerative disc disease is the most common cause of low back pain. Intervertebral disc abnormalities are commonly evaluated by magnetic resonance imaging (MRI), and Pfirrmann’s system involves the use of T2-weighted images (T2WI) to classify disc degeneration. However, as this classification is based on visual evaluation, it is not possible to quantify degeneration using this method. The present study was performed to establish an MRI-based intervertebral disc classification system using diffusional kurtosis imaging (DKI), to quantify intervertebral disc water content according to the Pfirrmann classification. Sagittal mean diffusional kurtosis (MK) mapping was performed for the L3/4, L4/5, and L5/S1 intervertebral discs in 32 patients (15 female, 17 male;age range, 24 - 82 years;mean age, 57.7 years). The degree of disc degeneration was assessed in the midsagittal section on T2WI according to the Pfirrmann classification (grade I - V). The relationships between MK values, which are correlated with intervertebral disc composition changes, and grade of degeneration determined using the Pfirrmann classification were analyzed. The MK values tended to decrease with increasing grade of degeneration, and differed significantly between grades I and IV, but not between grade IV and V (P < 0.05, Mann-Whitney U test). DKI is an effective means of detecting the early stages of disc degeneration. Therefore, DKI may be a useful diagnostic tool for quantitative assessment of intervertebral disc degeneration.

Diffusion kurtosis imaging of microstructural changes in brain tissue affected by acute ischemic stroke in different locations

The location of an acute ischemic stroke is associated with its prognosis. The widely used Gaussian model-based parameter, apparent diffusion coefficient(ADC), cannot reveal microstructural changes in different locations or the degree of infarction. This prospective observational study was reviewed and approved by the Institutional Review Board of Xiamen Second Hospital, China(approval No. 2014002).Diffusion kurtosis imaging(DKI) was used to detect 199 lesions in 156 patients with acute ischemic stroke(61 males and 95 females), mean age 63.15 ± 12.34 years. A total of 199 lesions were located in the periventricular white matter(n = 52), corpus callosum(n = 14), cerebellum(n = 29), basal ganglia and thalamus(n = 21), brainstem(n = 21) and gray-white matter junctions(n = 62). Percentage changes of apparent diffusion coefficient(ΔADC) and DKI-derived indices(fractional anisotropy [ΔFA], mean diffusivity [ΔMD], axial diffusivity [ΔD_a], radial diffusivity ΔDr, mean kurtosis [ΔMK], axial kurtosis [ΔK_a], and radial kurtosis [ΔK_r]) of each lesion were computed relative to the normal contralateral region. The results showed that(1) there was no significant difference in ΔADC, ΔMD, ΔD_a or ΔD_r among almost all locations.(2) There was significant difference in ΔMK among almost all locations(except basal ganglia and thalamus vs. brain stem; basal ganglia and thalamus vs. gray-white matter junctions; and brainstem vs. gray-white matter junctions.(3) The degree of change in diffusional kurtosis in descending order was as follows: corpus callosum > periventricular white matter > brainstem > gray-white matter junctions > basal ganglia and thalamus > cerebellum. In conclusion, DKI could reveal the differences in microstructure changes among various locations affected by acute ischemic stroke, and performed better than diffusivity among all groups.

Differentiating between Alzheimer’s disease, amnestic mild cognitive impairment, and normal aging via diffusion kurtosis imaging

Diffusion kurtosis imaging can be used to assess pathophysiological changes in tissue structure and to diagnose central nervous system diseases. However, its sensitivity in assessing hippocampal differences between patients with Alzheimer’s disease and those with amnestic mild cognitive impairment has not been characterized. Here, we examined 20 individuals with Alzheimer’s disease (11 men and 9 women, mean 73.2 ± 4.49 years), 20 with amnestic mild cognitive impairment (10 men and 10 women, mean 71.55 ± 4.77 years), and 20 normal controls (11 men and 9 women, mean 70.45 ± 5.04 years). We conducted diffusion kurtosis imaging, using a 3.0 T magnetic resonance scanner, to compare hippocampal differences among the three groups. The results demonstrated that the right hippocampal volume and bilateral mean kurtosis were remarkably smaller in individuals with Alzheimer’s disease compared with those with amnestic mild cognitive impairment and normal controls. Further, the mean kurtosis was lower in the amnestic mild cognitive impairment group compared with the normal control group. The mean diffusion in the left hippocampus was lower in the Alzheimer’s disease group than in the amnestic mild cognitive impairment and normal control groups, while the mean diffusion in the right hippocampus was lower in the Alzheimer’s disease group than in the normal control group. Fractional anisotropy was similar among the three groups. These results verify that bilateral mean kurtosis and mean diffusion are sensitive to the diagnosis of Alzheimer’s disease and amnestic mild cognitive impairment. This study was approved by the Ethics Review Board of Affiliated Sixth People’s Hospital of Shanghai Jiao Tong University, China on May 4, 2010 (approval No. 2010(C)-6).

Lattice structure adaptive IIR notch filter based on least square kurtosis

A new variable step-size algorithm for a second-order lattice form structure adaptive infinite impulse response （IIR） notch filter to detection and estimation frequency of sinusoids in Gaussian noises is proposed. Utilizing least square kurtosis of output signals as a cost function, the new gradient-based algorithm to update frequency of the adaptive IIR notch filter and the new variable step-size algorithm are given. The computer simulation results show that the proposed algorithm has better ability in suppressing colored Gaussian noises and better accuracy in estimating parameters at low SNR than previous algorithms.

Three-dimensional arterial spin labeling and diffusion kurtosis imaging in evaluating perfusion and infarct area size in acute cerebral ischemia

BACKGROUND Early thrombolytic therapy is crucial to treat acute cerebral infarction,especially since the onset of thrombolytic therapy takes 1-6 h.Therefore,early diagnosis and evaluation of cerebral infarction is important.AIM To investigate the diagnostic value of magnetic resonance multi-delay threedimensional arterial spin labeling(3DASL)and diffusion kurtosis imaging(DKI)in evaluating the perfusion and infarct area size in patients with acute cerebral ischemia.METHODS Eighty-four patients who experienced acute cerebral ischemia from March 2019 to February 2021 were included.All patients in the acute stage underwent magnetic resonance-based examination,and the data were processed by the system’s own software.The apparent diffusion coefficient(ADC),average diffusion coefficient(MD),axial diffusion(AD),radial diffusion(RD),average kurtosis(MK),radial kurtosis(fairly RK),axial kurtosis(AK),and perfusion parameters post-labeling delays(PLD)in the focal area and its corresponding area were compared.The correlation between the lesion area of cerebral infarction under MK and MD and T2-weighted imaging(T2WI)was analyzed.RESULTS The DKI parameters of focal and control areas in the study subjects were compared.The ADC,MD,AD,and RD values in the lesion area were significantly lower than those in the control area.The MK,RK,and AK values in the lesion area were significantly higher than those in the control area.The MK/MD value in the infarct lesions was used to determine the matching situation.MK/MD<5 mm was considered matching and MK/MD≥5 mm was considered mismatching.PLD1.5s and PLD2.5s perfusion parameters in the central,peripheral,and control areas of the infarct lesions in MK/MD-matched and-unmatched patients were not significantly different.PLD1.5s and PLD2.5s perfusion parameter values in the central area of the infarct lesions in MK/MD-matched and-unmatched patients were significantly lower than those in peripheral and control areas.The MK and MD maps showed a lesion area of 20.08±5.74 cm^(2) and 22.09±5.58 cm^(2),respectively.T2WI showed a lesion area of 19.76±5.02 cm^(2).There were no significant differences in the cerebral infarction lesion areas measured using the three methods.MK,MD,and T2WI showed a good correlation.CONCLUSION DKI parameters showed significant difference between the focal and control areas in patients with acute ischemic cerebral infarction.3DASL can effectively determine the changes in perfusion levels in the lesion area.There was a high correlation between the area of the infarct lesions diagnosed by DKI and T2WI.

Condition Evaluation in Steel Truss Bridge with Fused Hilbert Transform,Spectral Kurtosis,and Bandpass Filter

This study is concerned with the diagnosis of discrepancies in a steel truss bridge by identifying dynamic properties from the vibration response signals of the bridges.The vibration response signals collected at bridges under three different vehicular speeds of 10 km/hr,20 km/hr,and 30 km/hr are analyzed using statistical features such as kurtosis,magnitude of peak-to-peak,root mean square,crest factor as well as impulse factor in time domain,and Stockwell transform in the time-frequency domain.The considered statistical features except for kurtosis show uncertain behavior.The Stockwell transform showed low-resolution outcomes when the presence of noise in the recorded vibration responses.The elimination of noise and extraction of meaningful dynamic properties from the vibration responses is done by applying a new method which comes from the fusion of Hilbert transform with Spectral kurtosis and bandpass filtering.The outcomes obtained from Hilbert transform processed residual signals which are further filtered using bandpass filter show more robustness and accuracy in characterizing bridge modal frequencies from the noisy vibration responses.The proposed method produces a high-resolution frequency response which can unveil the joint discrepancy in the bridge structure.

Comparison of Kurtosis and Fourth Power Detectors with Applications to IR-UWB OOK Systems

On-off keying (OOK) is one of the modulation schemes for non-coherent impulse radio Ultra-wideband systems. In this paper, the utilization of the kurtosis detector (KD) and fourth power detector (FD) receivers for OOK signaling is introduced. We investigate the effect of integration interval and the optimum threshold on the performance of energy detector (ED), KD and FD receivers. The semi analytic expression of BER is obtained by using generalized extreme value distribution function for KD and FD receivers. From performance point of view, the simulation results show that FD receiver outperforms KD and ED receivers. In contrast, the sensitivity to the optimum threshold is greatly reduced in KD receiver compared to ED and FD receivers.

A Statistical Power Comparison of the Kolmogorov-Smirnov Two-Sample Test and the Wald Wolfowitz Test in Terms of Fixed Skewness and Fixed Kurtosis in Large Sample Sizes

In this study, the statistical powers of Kolmogorov-Smimov two-sample （KS-2） and Wald Wolfowitz （WW） tests, non-parametric tests used in testing data from two independent samples, have been compared in terms of fixed skewness and fixed kurtosis by means of Monte Carlo simulation. This comparison has been made when the ratio of variance is two as well as with equal and different sample sizes for large sample volumes. The sample used in the study is： （25, 25）, （25, 50）, （25, 75）, （25, 100）, （50, 25）, （50, 50）, （50, 75）, （50, 100）, （75, 25）, （75, 50）, （75, 75）, （75, 100）, （100, 25）, （100, 50）, （100, 75）, and （100, 100）. According to the results of the study, it has been observed that the statistical power of both tests decreases when the coefficient of kurtosis is held fixed and the coefficient of skewness is reduced while it increases when the coefficient of skewness is held fixed and the coefficient of kurtosis is reduced. When the ratio of skewness is reduced in the case of fixed kurtosis, the WW test is stronger in sample volumes （25, 25）, （25, 50）, （25, 75）, （25, 100）, （50, 75）, and （50, 100） while KS-2 test is stronger in other sample volumes. When the ratio of kurtosis is reduced in the case of fixed skewness, the statistical power of WW test is stronger in volume samples （25, 25）, （25, 75）, （25, 100）, and （75, 25） while KS-2 test is stronger in other sample volumes.

A closed form of a kurtosis parameter of a hypergeometric-Gaussian type-Ⅱ beam

Based on the irradiance moment definition and the analytical expression of waveform propagation for hypergeometric- Gaussian type-II beams passing through an ABCD system, the kurtosis parameter is derived analytically and illustrated numerically. The kurtosis parameters of the Gaussian beam, modified Bessel modulated Gaussian beam with quadrature radial and elegant Laguerre-Gaussian beams are obtained by treating them as special cases of the present treatment. The obtained results show that the kurtosis parameter depends on the change of the beam order m and the hollowness parameter p, such as its decrease with increasing m and increase with increasing p.

Kurtosis parameters of super Lorentz-Gauss beams through a paraxial and real ABCD optical system

Based on the propagation equation of higher-order intensity moments, analytical propagation expressions for the kurtosis parameters of a super Lorentz-Gauss （SLG） SLG01 beam through a paraxial and real ABCD optical system are derived. By replacing the parameters in the expressions of the kurtosis parameters of the SLC01 beam, the kurtosis parameters of the SLG10 and SLGll beams through a paraxial and real ABCD optical system can be easily obtained. The kurtosis parameters of an SLG01 beam through a paraxial and real ABCD optical system depend on two ratios. One is the ratio of the transfer matrix element B to the product of the transfer matrix element A and the diffraction-free range of the super-Lorentzian part. The other is the ratio of the width parameter of the super-Lorentzian part to the waist of the Gaussian part. As a numerical example, the properties of the kurtosis parameters of an SLG01 beam propagating in free space are illustrated. The influences of different parameters on the kurtosis parameters of an SLG01 beam are analysed in detail.

Study of fluctuations in the Martian magnetosheath using a kurtosis technique:Mars Express observations

Planetary magnetosheaths are characterized by high plasma wave and turbulence activity.The Martian magnetosheath is no exception;both upstream and locally generated plasma waves have been observed in the region between its bow shock and magnetic boundary layer,its induced magnetosphere.This statistical study of wave activity in the Martian magnetosheath is based on 12 years(2005-2016)of observations made during Mars Express(MEX)crossings of the planet’s magnetosheath-in particular,data on electron density and temperature data collected by the electron spectrometer(ELS)of the plasma analyzer(ASPERA-3)experiment on board the MEX spacecraft.A kurtosis parameter has been calculated for these plasma parameters.This value indicates intermittent behavior in the data when it is higher than 3(the value for a normal or Gaussian distribution).The variation of wave activity occurrence has been analyzed in relation to solar cycle,Martian orbit,and distance to the bow shock.Non-Gaussian properties are observed in the magnetosheath of Mars on all analyzed scales,especially in those near the proton gyrofrequency in the upstream region of the Martian magnetosphere.We also report that non-Gaussian behavior is most prominent at the smaller scales(higher frequencies).A significant influence of the solar cycle was also observed;the kurtosis parameter is higher during declining and solar maximum phases,when the presence of disturbed solar wind conditions,caused by large scale solar wind structures,increases.The kurtosis decreases with increasing distance from the bow shock,which indicates that the intermittence level is higher near the bow shock.In the electron temperature data the kurtosis is higher near the perihelion due to the higher incidence of EUV when the planet is closer to the Sun,which causes a more extended exosphere,and consequently increases the wave activity in the magnetosheath and its upstream region.The extended exosphere seems to play a lower effect in the electron density data.

A SIGNAL-ADAPTIVE ALGORITHM FOR BLIND SEPARATION OF SOURCES WITH MIXED KURTOSIS SIGNS

This paper addresses the problem of Blind Source Separation (BSS) and presents a new BSS algorithm with a Signal-Adaptive Activation (SAA) function (SAA-BSS). By taking the sum of absolute values of the normalized kurtoses as a contrast function, the obtained signal-adaptive activation function automatically satisfies the local stability and robustness conditions. The SAA-BSS exploits the natural gradient learning on the Stiefel manifold, and it is an equivariant algorithm with a moderate computational load. Computer simulations show that the SAA-BSS can perform blind separation of mixed sub-Gaussian and super-Gaussian signals and it works more efficiently than the existing algorithms in convergence speed and robustness against outliers.

ADAPTIVE KURTOSIS OPTIMIZATION AUTOFOCUS ALGORITHM

This paper proposes an autofocus algorithm used for Synthetic Aperture Radar (SAR) images, called Adaptive Kurtosis Optimization Autofocus Algorithm (AKOAA). The AKOAA can reduce the differ-ence between initial value and real value in focusing by adaptively adjusting the initial value, therefore effec-tively improve the local extremum problem in the Contrast Optimization Autofocus Algorithm (COAA) and speed up the convergence velocity. The principle and realization method of AKOAA are thoroughly investi-gated, and experimental results using real L-band SAR data show that the focus speed of AKOAA is nearly doubled compared with that of the COAA, and the image contrast of AKOAA is improved as well.

Estimation of Population Variance Using the Coefficient of Kurtosis and Median of an Auxiliary Variable under Simple Random Sampling

In this study we have proposed a modified ratio type estimator for population variance of the study variable y under simple random sampling without replacement making use of coefficient of kurtosis and median of an auxiliary variable x. The estimator’s properties have been derived up to first order of Taylor’s series expansion. The efficiency conditions derived theoretically under which the proposed estimator performs better than existing estimators. Empirical studies have been done using real populations to demonstrate the performance of the developed estimator in comparison with the existing estimators. The proposed estimator as illustrated by the empirical studies performs better than the existing estimators under some specified conditions i.e. it has the smallest Mean Squared Error and the highest Percentage Relative Efficiency. The developed estimator therefore is suitable to be applied to situations in which the variable of interest has a positive correlation with the auxiliary variable.

Diffusional kurtosis imaging: a promising technique for detecting microstructural changes in neural development and regeneration

Brain development is one of the most fascinating subjects in the field of biological sciences. Nonetheless, our scientific commu- nity still faces challenges in trying to understand the concepts that define the underlying mechanisms of neural tissue devel- opment. After all, it is a very complex subject to grasp and many of the processes that take place during central nervous system maturation are yet to be ascertained. Despite this challenge, we have come to recognize that understanding the natural course of normal brain tissue development on both microscopic and macroscopic scales is the key to deciphering the mechanisms through which these neural networks also heal and regenerate. Realizing this concept, my good friend and colleague, Dr. Sar- ah Milla, and I decided to take on a human study to investigate brain maturation using non-invasive imaging techniques in the pediatric population at New York University （NYU） School of Medicine （Paydar et al., 2013）. Our research subjects included 59 normal infants with an age spectrum ranging from birth to approximately 5 years of age, when the brain is in its most active stage of development. We implemented a Magnetic Resonance Imaging （MRI） diffusion technique called Diffusional Kurtosis Imaging （DKI） to investigate the microstructural changes that occur in both the white matter （WM） and gray matter （GM） in the developing brain.

Application of diffusion kurtosis imaging technology in evaluating early mild traumatic brain injury

Objective To explore the value of magnetic resonance diffusion kurtosis imaging in diagnosing early tiny changes of brain tissue after mild traumatic brain injury.Methods A total of 22 patients with mild traumatic brain injury(study group)and 20 healthy subjects(control group)were enrolled in this study,and diffusion kurtosis imaging magnetic resonance scanning was employed in all subjects.fractional anisotropy,fractional anisotropy of kurtosis,mean kurtosis,axial kurtosis and radial kurtosis of diffusion kurtosis imaging parameters in the genu of corpus callosum,splenium corporis callosi,internal capsule,thalamus,putamen,cortex of frontal lobe,temporal lobe and parietal lobe at control group,the injured side and the mirror regions were measured,and the results were compared between the two groups.The receiver operating characteristic curve was used to evaluate the ability of different parameters in diagnosing mild traumatic brain injury.Results Compared with the control group,in the study group fractional anisotropy values of bilateral genu of corpus callosum,splenium corporis callosi,internal capsule and thalamus were significantly reduced,and fractional anisotropy of kurtosis values of bilateral thalamus and putamen were significantly reduced,and the differences were statistically significant(P<0.05).Compared with the control group,in the study group mean kurtosis and axial kurtosis values of bilateral genu of corpus callosum,posterior limb of Internal capsule,thalamus,putamen and cortex of temporal lobe were significantly reduced,while radial kurtosis values in the genu of corpus callosum,thalamus,cortex of frontal lobe,temporal lobe at the injured side were increased,and the differences were statistically significant(P<0.05).Conclusion DKI techniques can sensitively detect the early tiny pathologic changes of cerebral tissue in mild traumatic brain injury patients,which provide more imaging evidence for the clinical early diagnosis treatment and prognosis.

R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma

Background:Due to development of magnetic resonance-based functional imaging, it is easier to detect micro-structural alterations of tumor tissues. The aim of this study was to conduct a preliminary evaluation of the correlation of non-Gaussian diffusion kurtosis imaging (DKI) parameters with expression of molecular markers (epidermal growth factor receptor [ EGFR];anaplastic lymphoma kinase [ ALK];Ki-67 protein) in patients with advanced lung adenocarcinoma, using routine diffusion-weighted imaging as the reference standard. Methods::Data from patients with primary lung adenocarcinoma diagnosed at Cancer Hospital, Chinese Academy of Medical Sciences (CHCAMS) from 2016 to 2019 were collected for retrospective analysis. The pathologic and magnetic resonance imaging data of 96 patients who met the inclusion criteria were included in this study. Specifically, the Kapp and Dapp parameters measured from the DKI model;apparent diffusion coefficient (ADC) value from the diffusion-weighted imaging model;and the EGFR, ALK, and Ki-67 biomarkers detected by immunohistochemistry and/or molecular biology techniques after biopsy or surgery were evaluated. The relations between quantitative parameters (ADC, Kapp, Dapp) and pathologic outcomes ( EGFR, ALK, and Ki-67 expression) were analyzed by Spearman correlation test. Results:Of the 96 lung adenocarcinoma lesions (from 96 patients), the number of EGFR- and ALK-positive and high Ki-67 expressing lesions were 53, 12, and 83, respectively. The Kapp values were significantly higher among patients with EGFR-positive mutations (0.81 ± 0.12 vs. 0.66 ± 0.10, t = 6.41, P < 0.001), ALK rearrangement-negative (0.76 ± 0.12 vs. 0.60 ± 0.15, t = 4.09, P < 0.001), and high Ki-67 proliferative index (PI) (0.76 ± 0.12 vs. 0.58 ± 0.13, t = 4.88, P < 0.001). The Dapp values were significantly lower among patients with high Ki-67 PI (3.19 ± 0.69 μm 2/ms vs. 4.20 ± 0.83 μm 2/ms, t = 4.80, P < 0.001) and EGFR-positive mutations (3.11 ± 0.73 μm 2/ms vs. 3.59 ± 0.77 μm ^2/ms, t = 3.12, P = 0.002). The differences in mean Dapp (3.73 ± 1.26 μm^ 2/ms vs. 3.26 ± 0.68 μm 2/ms, t = 1.96, P = 0.053) or ADC values ([1.34 ± 0.81] × 10^ -3 mm ^2/s vs. [1.33 ± 0.41] × 10 ^-3 mm ^2/s, t = 0.07, P = 0.941) between the groups with or without ALK rearrangements were not statistically significant. The ADC values were significantly lower among patients with EGFR-positive mutation ([1.19 ± 0.37] × 10 ^-3 mm^ 2/s vs. [1.50 ± 0.53] × 10 ^-3 mm ^2/s, t = 3.38, P = 0.001) and high Ki-67 PI ([1.28 ± 0.39] × 10 -3 mm 2/s vs. [1.67 ± 0.77] × 10^ -3 mm^ 2/s, t = 2.88, P = 0.005). Kapp was strongly positively correlated with EGFR mutations ( r = 0.844, P = 0.008), strongly positively correlated with Ki-67 PI ( r = 0.882, P = 0.001), and strongly negatively correlated with ALK rearrangements ( r = -0.772, P = 0.001). Dapp was moderately correlated with EGFR mutations ( r = -0.650, P = 0.024) or Ki-67 PI ( r = -0.734, P = 0.012). ADC was moderately correlated with Ki-67 PI ( r = -0.679, P = 0.033). Conclusions:The Kapp value of DKI parameters was strongly correlated with different expression of EGFR, ALK, and Ki-67 in advanced lung adenocarcinoma. The results potentially indicate a surrogate measure of the status of different molecular markers assessed by non-invasive imaging tools.