Non-Gaussian analysis of diffusion weighted imaging in head and neck at 3T: a pilot study in patients with nasopharyngeal carcinoma

Optimal Experiment Design for Monoexponential Model Fitting: Application to Apparent Diffusion Coefficient Imaging

The monoexponential model is widely used in quantitative biomedical imaging. Notable applications include apparent diffusion coefficient (ADC) imaging and pharmacokinetics. The application of ADC imaging to the detection of malignant tissue has in turn prompted several studies concerning optimal experiment design for monoexponential model fitting. In this paper, we propose a new experiment design method that is based on minimizing the determinant of the covariance matrix of the estimated parameters (D-optimal design). In contrast to previous methods, D-optimal design is independent of the imaged quantities. Applying this method to ADC imaging, we demonstrate its steady performance for the whole range of input variables (imaged parameters, number of measurements, and range of b-values). Using Monte Carlo simulations we show that the D-optimal design outperforms existing experiment design methods in terms of accuracy and precision of the estimated parameters.

Evaluation of Head and Neck Tumors with Functional MR Imaging

Head and neck cancer is one of the most common cancers worldwide. MR imaging-based diffusion and perfusion techniques enable the noninvasive assessment of tumor biology and physiology, which supplement information obtained from standard structural scans. Diffusion and perfusion MR imaging techniques provide novel biomarkers that can aid monitoring in pretreatment, during treatment, and posttreatment stages to improve patient selection for therapeutic strategies; provide evidence for change of therapy regime; and evaluate treatment response. This review discusses pertinent aspects of the role of diffusion and perfusion MR imaging and computational analysis methods in studying head and neck cancer.

Functional magnetic resonance imaging techniques and their development for radiation therapy planning and monitoring in the head and neck cancers

Radiation therapy (RT), in particular intensity-modulated radiation therapy (IMRT), is becoming a more important nonsurgical treatment strategy in head and neck cancer (HNC). The further development of IMRT imposes more critical requirements on clinical imaging, and these requirements cannot be fully fulfilled by the existing radiotherapeutic imaging workhorse of X-ray based imaging methods. Magnetic resonance imaging (MRI) has increasingly gained more interests from radiation oncology community and holds great potential for RT applications, mainly due to its non-ionizing radiation nature and superior soft tissue image contrast. Beyond anatomical imaging, MRI provides a variety of functional imaging techniques to investigate the functionality and metabolism of living tissue. The major purpose of this paper is to give a concise and timely review of some advanced functional MRI techniques that may potentially benefit conformal, tailored and adaptive RT in the HNC. The basic principle of each functional MRI technique is briefly introduced and their use in RT of HNC is described. Limitation and future development of these functional MRI techniques for HNC radiotherapeutic applications are discussed. More rigorous studies are warranted to translate the hypotheses into credible evidences in order to establish the role of functional MRI in the clinical practice of head and neck radiation oncology.

Statistical assessment of bi-exponential diffusion weighted imaging signal characteristics induced by intravoxel incoherent motion in malignant breast tumors

BACKGROUND

The purpose of this study is to statistically assess whether bi-exponential intravoxel incoherent motion (IVIM) model better characterizes diffusion weighted imaging (DWI) signal of malignant breast tumor than mono-exponential Gaussian diffusion model.

METHODS

3 T DWI data of 29 malignant breast tumors were retrospectively included. Linear least-square mono-exponential fitting and segmented least-square bi-exponential fitting were used for apparent diffusion coefficient (ADC) and IVIM parameter quantification, respectively. F-test and Akaike Information Criterion (AIC) were used to statistically assess the preference of mono-exponential and bi-exponential model using region-of-interests (ROI)-averaged and voxel-wise analysis.

RESULTS

For ROI-averaged analysis, 15 tumors were significantly better fitted by bi-exponential function and 14 tumors exhibited mono-exponential behavior. The calculated ADC, D (true diffusion coefficient) and f (pseudo-diffusion fraction) showed no significant differences between mono-exponential and bi-exponential preferable tumors. Voxel-wise analysis revealed that 27 tumors contained more voxels exhibiting mono-exponential DWI decay while only 2 tumors presented more bi-exponential decay voxels. ADC was consistently and significantly larger than D for both ROI-averaged and voxel-wise analysis.

CONCLUSIONS

Although the presence of IVIM effect in malignant breast tumors could be suggested, statistical assessment shows that bi-exponential fitting does not necessarily better represent the DWI signal decay in breast cancer under clinically typical acquisition protocol and signal-to-noise ratio (SNR). Our study indicates the importance to statistically examine the breast cancer DWI signal characteristics in practice.

Intravoxel Incoherent Motion Metrics as Potential Biomarkers for Survival in Glioblastoma

Objective

Intravoxel incoherent motion (IVIM) is an MRI technique with potential applications in measuring brain tumor perfusion, but its clinical impact remains to be determined. We assessed the usefulness of IVIM-metrics in predicting survival in newly diagnosed glioblastoma.

Methods

Fifteen patients with glioblastoma underwent MRI including spin-echo echo-planar DWI using 13 b-values ranging from 0 to 1000 s/mm². Parametric maps for diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were generated for contrast-enhancing regions (CER) and non-enhancing regions (NCER). Regions of interest were manually drawn in regions of maximum f and on the corresponding dynamic susceptibility contrast images. Prognostic factors were evaluated by Kaplan-Meier survival and Cox proportional hazards analyses.

Results

We found that f_CER and D*_CER correlated with rCBF_CER. The best cutoffs for 6-month survival were f_CER>9.86% and D*_CER>21.712 x10⁻³mm²/s (100% sensitivity, 71.4% specificity, 100% and 80% positive predictive values, and 80% and 100% negative predictive values; AUC:0.893 and 0.857, respectively). Treatment yielded the highest hazard ratio (5.484; 95% CI: 1.162–25.88; AUC: 0.723; P = 0.031); f_CER combined with treatment predicted survival with 100% accuracy.

Conclusions

The IVIM-metrics f_CER and D*_CER are promising biomarkers of 6-month survival in newly diagnosed glioblastoma.

Diffusion-Weighted Imaging of Nasopharyngeal Carcinoma: Can Pretreatment DWI Predict Local Failure Based on Long-Term Outcome?

BACKGROUND AND PURPOSE

Pretreatment prediction of patients with nasopharyngeal carcinoma who will fail conventional treatment would potentially allow these patients to undergo more intensive treatment or closer posttreatment monitoring. The aim of the study was to determine the ability of pretreatment DWI to predict local failure in patients with nasopharyngeal carcinoma based on long-term clinical outcome.

MATERIALS AND METHODS

One hundred fifty-eight patients with pretreatment DWI underwent analysis of the primary tumor to obtain the ADC mean, ADC skewness, ADC kurtosis, volume, and T-stage. Univariate and multivariate analyses using logistic regression were performed to compare the ADC parameters, volume, T-stage, and patient age in primary tumors with local failure and those with local control, by using a minimum of 5-year follow-up to confirm local control.

RESULTS

Local control was achieved in 131/158 (83%) patients (range, 60.3-117.7 months) and local failure occurred in 27/158 (17%) patients (range, 5.2-79.8 months). Compared with tumors with local control, those with local failure showed a significantly lower ADC skewness (ADC values with the greatest frequencies were shifted away from the lower ADC range) (P = .006) and lower ADC kurtosis (curve peak broader) (P = .024). The ADC skewness remained significant on multivariate analysis (P = .044). There was a trend toward higher tumor volumes in local failure, but the volume, together with T-stage and ADC mean, were not significantly different between the 2 groups.

CONCLUSIONS

Pretreatment DWI of primary tumors found that the skewness of the ADC distribution curve was a predictor of local failure in patients with nasopharyngeal carcinoma, based on long-term clinical outcome.

Clinical Intravoxel Incoherent Motion and Diffusion MR Imaging: Past, Present, and Future

The concept of diffusion magnetic resonance (MR) imaging emerged in the mid-1980s, together with the first images of water diffusion in the human brain, as a way to probe tissue structure at a microscopic scale, although the images were acquired at a millimetric scale. Since then, diffusion MR imaging has become a pillar of modern clinical imaging. Diffusion MR imaging has mainly been used to investigate neurologic disorders. A dramatic application of diffusion MR imaging has been acute brain ischemia, providing patients with the opportunity to receive suitable treatment at a stage when brain tissue might still be salvageable, thus avoiding terrible handicaps. On the other hand, it was found that water diffusion is anisotropic in white matter, because axon membranes limit molecular movement perpendicularly to the nerve fibers. This feature can be exploited to produce stunning maps of the orientation in space of the white matter tracts and brain connections in just a few minutes. Diffusion MR imaging is now also rapidly expanding in oncology, for the detection of malignant lesions and metastases, as well as monitoring. Water diffusion is usually largely decreased in malignant tissues, and body diffusion MR imaging, which does not require any tracer injection, is rapidly becoming a modality of choice to detect, characterize, or even stage malignant lesions, especially for breast or prostate cancer. After a brief summary of the key methodological concepts beyond diffusion MR imaging, this article will give a review of the clinical literature, mainly focusing on current outstanding issues, followed by some innovative proposals for future improvements.

Body Diffusion-weighted MR Imaging in Oncology: Imaging at 3 T

Advances in hardware and software enable high-quality body diffusion-weighted images to be acquired for oncologic assessment. 3.0 T affords improved signal/noise for higher spatial resolution and smaller field-of-view diffusion-weighted imaging (DWI). DWI at 3.0 T can be applied as at 1.5 T to improve tumor detection, disease characterization, and the assessment of treatment response. DWI at 3.0 T can be acquired on a hybrid PET-MR imaging system, to allow functional MR information to be combined with molecular imaging.

Parameter Estimation Error Dependency on the Acquisition Protocol in Diffusion Kurtosis Imaging

Mono-exponential kurtosis model is routinely fitted on diffusion weighted, magnetic resonance imaging data to describe non-Gaussian diffusion. Here, the purpose was to optimize acquisitions for this model to minimize the errors in estimating diffusion coefficient and kurtosis. Similar to a previous study, covariance matrix calculations were used, and coefficients of variation in estimating each parameter of this model were calculated. The acquisition parameter, b values, varied in discrete grids to find the optimum ones that minimize the coefficient of variation in estimating the two non-Gaussian parameters. Also, the effect of variation of the target values on the optimized values was investigated. Additionally, the results were benchmarked with Monte Carlo noise simulations. Simple correlations were found between the optimized b values and target values of diffusion and kurtosis. For small target values of the two parameters, there is higher chance of having significant errors; this is caused by maximum b value limits imposed by the scanner than the mathematical bounds. The results here, cover a wide range of parameters D and K so that they could be used in many directionally averaged diffusion weighted cases such as head and neck, prostate, etc.

Intravoxel Incoherent Motion Diffusion-weighted Magnetic Resonance Imaging for Monitoring the Early Response to ZD6474 from Nasopharyngeal Carcinoma in Nude Mouse

Early therapeutic effects of anti-angiogenic agent ZD6474 upon nasopharyngeal carcinoma (NPC) in nude mouse were monitored by using intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI). Mice bearing NPC underwent IVIM DWI at baseline and after 1, 3, and 7 days of treatment with ZD6474 or vehicle (n = 12 per group). Parameters of apparent diffusion coefficient (ADC), true diffusion coefficient (D), perfusion fraction (f), and blood pseudodiffusion coefficient (D*) at different time points were compared between the two groups or within the treated group. In the treated group, the perfusion-related parameters f and D* of the tumors decreased significantly on day 1 while the diffusion-related parameters ADC and D were significantly higher beginning on day 3 compared with the control group. The decreases in f on day 1 and D* on day 3 were moderately correlated with the smaller tumor size change on day 7. Moderate correlations were established between MVD and f and D* as well as between increased TUNEL or decreased Ki-67 index and ADC and D. This study supports that IVIM DWI is sensitive to detect the ZD6474-induced changes in NPC in nude mouse and the f parameter could predict early response to anti-angiogenic treatment.

Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practice

Technologic advances enable performance of diffusion-weighted imaging (DWI) at ultrahigh b-values, where standard monoexponential model analysis may not apply. Rather, non-Gaussian water diffusion properties emerge, which in cellular tissues are, in part, influenced by the intracellular environment that is not well evaluated by conventional DWI. The novel technique, diffusion kurtosis imaging (DKI), enables characterization of non-Gaussian water diffusion behavior. More advanced mathematical curve fitting of the signal intensity decay curve using the DKI model provides an additional parameter Kapp that presumably reflects heterogeneity and irregularity of cellular microstructure, as well as the amount of interfaces within cellular tissues. Although largely applied for neural applications over the past decade, a small number of studies have recently explored DKI outside the brain. The most investigated organ is the prostate, with preliminary studies suggesting improved tumor detection and grading using DKI. Although still largely in the research phase, DKI is being explored in wider clinical settings. When assessing extracranial applications of DKI, careful attention to details with which body radiologists may currently be unfamiliar is important to ensure reliable results. Accordingly, a robust understanding of DKI is necessary for radiologists to better understand the meaning of DKI-derived metrics in the context of different tumors and how these metrics vary between tumor types and in response to treatment. In this review, we outline DKI principles, propose biostructural basis for observations, provide a comparison with standard monoexponential fitting and the apparent diffusion coefficient, report on extracranial clinical investigations to date, and recommend technical considerations for implementation in body imaging.

Grading of Gliomas by Using Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MR Imaging and Diffusion Kurtosis MR Imaging

PURPOSE

To quantitatively compare the potential of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging models and diffusion kurtosis imaging in the grading of gliomas.

MATERIALS AND METHODS

This study was approved by the local ethics committee, and written informed consent was obtained from all subjects. Both diffusion-weighted imaging and diffusion kurtosis imaging were performed in 69 patients with pathologically proven gliomas by using a 3-T magnetic resonance (MR) imaging unit. An isotropic apparent diffusion coefficient (ADC), true ADC, pseudo-ADC, and perfusion fraction were calculated from diffusion-weighted images by using a biexponential model. A water molecular diffusion heterogeneity index and distributed diffusion coefficient were calculated from diffusion-weighted images by using a stretched exponential model. Mean diffusivity, fractional anisotropy, and mean kurtosis were calculated from diffusion kurtosis images. All values were compared between high-grade and low-grade gliomas by using a Mann-Whitney U test. Receiver operating characteristic and Spearman rank correlation analysis were used for statistical evaluations.

RESULTS

ADC, true ADC, perfusion fraction, water molecular diffusion heterogeneity index, distributed diffusion coefficient, and mean diffusivity values were significantly lower in high-grade gliomas than in low-grade gliomas (U = 109, 56, 129, 6, 206, and 229, respectively; P < .05). Pseudo-ADC and mean kurtosis values were significantly higher in high-grade gliomas than in low-grade gliomas (U = 98 and 8, respectively; P < .05). Both water molecular diffusion heterogeneity index (area under the receiver operating characteristic curve [AUC] = 0.993) and mean kurtosis (AUC = 0.991) had significantly greater AUC values than ADC (AUC = 0.866), mean diffusivity (AUC = 0.722), and fractional anisotropy (AUC = 0.500) in the differentiation of low-grade and high-grade gliomas (P < .05).

CONCLUSION

Water molecular diffusion heterogeneity index and mean kurtosis values may provide additional information and improve the grading of gliomas compared with conventional diffusion parameters.

Diffusion Magnetic Resonance Imaging: What Water Tells Us about Biological Tissues

Since its introduction in the mid-1980s, diffusion magnetic resonance imaging (MRI), which measures the random motion of water molecules in tissues, revealing their microarchitecture, has become a pillar of modern neuroimaging. Its main clinical domain has been the diagnosis of acute brain stroke and neurogical disorders, but it is also used in the body for the detection and management of cancer lesions. It can also produce stunning maps of white matter tracks in the brain, with the potential to aid in the understanding of some psychiatric disorders. However, in order to exploit fully the potential of this method, a deeper understanding of the mechanisms that govern the diffusion of water in tissues is needed.

Whole-body diffusion kurtosis imaging: initial experience on non-Gaussian diffusion in various organs

INTRODUCTION

Diffusion kurtosis imaging (DKI) is based on a non-Gaussian diffusion model that should inherently better account for restricted water diffusion within the complex microstructure of most tissues than the conventional diffusion-weighted imaging (DWI), which presumes Gaussian distributed water molecule displacement probability. The aim of this investigation was to test the technical feasibility of in vivo whole-body DKI, probe for organ-specific differences, and compare whole-body DKI and DWI results.

MATERIALS AND METHODS

Eight healthy subjects underwent whole-body DWI on a clinical 3.0 T magnetic resonance imaging system. Echo-planar images in the axial orientation were acquired at b-values of 0, 150, 300, 500, and 800 mm²/s. Parametrical whole-body maps of the diffusion coefficient (D), the kurtosis (K), and the traditional apparent diffusion coefficient (ADC) were generated. Goodness of fit was compared between DKI and DWI fits using the sums of squared residuals. Data groups were tested for significant differences of the mean by paired Student t tests.

RESULTS

Good-quality parametrical whole-body maps of D, K, and ADC could be computed. Compared with ADC values, D values were significantly higher in the cerebral gray matter (by 30%) and white matter (27%), renal cortex (23%) and medulla (21%), spleen (101%), as well as erector spinae muscle (34%) (each P value <0.001). No significant differences between D and ADC were found in the cerebrospinal fluid (P = 0.08) and in the liver (P = 0.13). Curves of DKI fitted the measurement points significantly better than DWI curves did in most organs.

CONCLUSIONS

Whole-body DKI is technically feasible and may reflect tissue microstructure more meaningfully than whole-body DWI.

Histogram analysis of diffusion kurtosis magnetic resonance imaging in differentiation of pathologic Gleason grade of prostate cancer

OBJECTIVE

To investigate diagnostic performance of diffusion kurtosis imaging with histogram analysis for stratifying pathologic Gleason grade of prostate cancer (PCa).

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board, and written informed consent was waived. A total of 110 patients pathologically confirmed as having PCa (diameter>0.5 cm) underwent preoperative diffusion-weighted magnetic resonance imaging (b value of 0-2,100 s/mm(2)) at 3T. Data were postprocessed by monoexponential and diffusion kurtosis models for quantitation of apparent diffusion coefficients (ADCs), apparent diffusion for Gaussian distribution (D(app)), and apparent kurtosis coefficient (K(app)). The measurement was based on an entire-tumor histogram analysis approach. The ability of imaging indices for differentiating low-grade (LG) PCa (Gleason score [GS]≤6) from intermediate-/high-grade (HG: GS>6) PCa was analyzed by receiver operating characteristic regression.

RESULTS

There were 49 LG tumors and 77 HG tumors at pathologic findings. HG-PCa had significantly lower ADCs, lower diffusion kurtosis diffusivity (D(app)), and higher kurtosis coefficient (K(app)) in mean, median, 10th, and 90th percentile, with higher D(app) in skewness and kurtosis than LG-PCa (P< 0.05). The 10th ADCs, the 10th D(app), and the 90th K(app) showed relatively higher area under receiver operating characteristic curve (Az), Youden index, and positive likelihood ratio in stratifying aggressiveness of PCa against other indices. The 90th K(app) showed relatively higher correlation (ρ>0.6) with ordinal GS of PCa; significantly higher Az, sensitivity, and specificity (0.889, 74.1%, and 93.9%, respectively) than the 10th D(app) did (0.765, 61.0%, and 79.6%, respectively; P<0.05); and higher Az and specificity than the 10th ADCs did (0.738 and 71.4%, respectively; P<0.05) in differentiating LG-PCa from HG-PCa.

CONCLUSIONS

It demonstrated a good reliability of histogram diffusion kurtosis imaging for stratifying pathologic GS of PCa. The 90th K(app) had better diagnostic performance in differentiating LG-PCa from HG-PCa.

Diffusion kurtosis imaging predicts neoadjuvant chemotherapy responses within 4 days in advanced nasopharyngeal carcinoma patients

PURPOSE

To explore the clinical value of diffusion kurtosis imaging (DKI) and monoexponential diffusion-weighted imaging (DWI) for predicting early response to neoadjuvant chemotherapy (NAC) in patients with nasopharyngeal carcinoma (NPC).

MATERIALS AND METHODS

Fifty-nine patients with stage III-IVb NPC underwent four 3.0T MR scans: prior to, and on the 4th, 21st, 42nd days after NAC initiation. The parameters of DKI (corrected diffusion coefficient, D; excess diffusion kurtosis coefficient, K) and monoexponential DWI (apparent diffusion coefficient, ADC) were obtained at the first three scans. Statistical methods included Student's t-test or Mann-Whitney U-test, receiver operating characteristic (ROC) curve analyses and paired X(2) test.

RESULTS

D(pre) in responders group (RG) was significantly lower than nonresponders group (NRG) (1.029 ± 0.033 vs. 1.184 ± 0.055, ×10(-3) mm(2) /s, P = 0.020). ADC(day4) and ΔD(day4) were the most useful parameters of the two diffusional models to distinguish RG from NRG, respectively (area under the curve, 0.761 vs. 0.895). ΔD(day4) was more sensitive than ADC(day4) to predict treatment response to NAC (P = 0.006).

CONCLUSION

Both DKI and monoexponential DWI showed potential to predict treatment response to NAC prior to morphological change. DKI may be superior to monoexponential DWI for predicting early response to NAC in patients with locally advanced NPC.

Amide proton transfer-weighted imaging of the head and neck at 3 T: a feasibility study on healthy human subjects and patients with head and neck cancer

The aim of this study was to explore the feasibility and repeatability of amide proton transfer-weighted (APTw) MRI for the head and neck on clinical MRI scanners. Six healthy volunteers and four patients with head and neck tumors underwent APTw MRI scanning at 3 T. The APTw signal was quantified by the asymmetric magnetization transfer ratio (MTRasym) at 3.5 ppm. Z spectra of normal tissues in the head and neck (masseter muscle, parotid glands, submandibular glands and thyroid glands) were analyzed in healthy volunteers. Inter-scan repeatability of APTw MRI was evaluated in six healthy volunteers. Z spectra of patients with head and neck tumors were produced and APTw signals in these tumors were analyzed. APTw MRI scanning was successful for all 10 subjects. The parotid glands showed the highest APTw signal (~7.6% average), whereas the APTw signals in other tissues were relatively moderate. The repeatability of APTw signals from the masseter muscle, parotid gland, submandibular gland and thyroid gland of healthy volunteers was established. Four head and neck tumors showed positive mean APTw ranging from 1.2% to 3.2%, distinguishable from surrounding normal tissues. APTw MRI was feasible for use in the head and neck regions at 3 T. The preliminary results on patients with head and neck tumors indicated the potential of APTw MRI for clinical applications.