Comparison of diffusion-weighted MRI and anti-Stokes Raman scattering (CARS) measurements of the inter-compartmental exchange-time of water in expression-controlled aquaporin-4 cells

From Brownian motion to virtual biopsy: a historical perspective from 40 years of diffusion MRI

Diffusion MRI was introduced in 1985, showing how the diffusive motion of molecules, especially water, could be spatially encoded with MRI to produce images revealing the underlying structure of biologic tissues at a microscopic scale. Diffusion is one of several Intravoxel Incoherent Motions (IVIM) accessible to MRI together with blood microcirculation. Diffusion imaging first revolutionized the management of acute cerebral ischemia by allowing diagnosis at an acute stage when therapies can still work, saving the outcomes of many patients. Since then, the field of diffusion imaging has expanded to the whole body, with broad applications in both clinical and research settings, providing insights into tissue integrity, structural and functional abnormalities from the hindered diffusive movement of water molecules in tissues. Diffusion imaging is particularly used to manage many neurologic disorders and in oncology for detecting and classifying cancer lesions, as well as monitoring treatment response at an early stage. The second major impact of diffusion imaging concerns the wiring of the brain (Diffusion Tensor Imaging, DTI), allowing to obtain from the anisotropic movement of water molecules in the brain white-matter images in 3 dimensions of the brain connections making up the Connectome. DTI has opened up new avenues of clinical diagnosis and research to investigate brain diseases, neurogenesis and aging, with a rapidly extending field of application in psychiatry, revealing how mental illnesses could be seen as Connectome spacetime disorders. Adding that water diffusion is closely associated to neuronal activity, as shown from diffusion fMRI, one may consider that diffusion MRI is ideally suited to investigate both brain structure and function. This article retraces the early days and milestones of diffusion MRI which spawned over 40 years, showing how diffusion MRI emerged and expanded in the research and clinical fields, up to become a pillar of modern clinical imaging.

Repeatability and reproducibility of apparent exchange rate measurements in yeast cell phantoms using filter-exchange imaging

OBJECTIVES

Development of a protocol for validation and quality assurance of filter-exchange imaging (FEXI) pulse sequences with well-defined and reproducible phantoms.

MATERIALS AND METHODS

A FEXI pulse sequence was implemented on a 7 T preclinical MRI scanner. Six experiments in three different test categories were established for sequence validation, demonstration of the reproducibility of phantoms and the measurement of induced changes in the apparent exchange rate (AXR). First, an ice-water phantom was used to investigate the consistency of apparent diffusion coefficient (ADC) measurements with different diffusion filters. Second, yeast cell phantoms were utilized to validate the determination of the AXR in terms of repeatability (same phantom and session), reproducibility (separate but comparable phantoms in different sessions) and directionality of diffusion encodings. Third, the yeast cell phantoms were, furthermore, used to assess potential AXR bias because of altered cell density and temperature. In addition, a treatment experiment with aquaporin inhibitors was performed to evaluate the influence of these compounds on the cell membrane permeability in yeast cells.

RESULTS

FEXI-based ADC measurements of an ice-water phantom were performed for three different filter strengths, showed good agreement with the literature value of 1.099 × 10-3 mm2/s and had a maximum coefficient of variation (CV) of 0.55% within the individual filter strengths. AXR estimation in a single yeast cell phantom and imaging session with five repetitions resulted in an overall mean value of (1.49 ± 0.05) s-1 and a CV of 3.4% between the chosen regions of interest. For three separately prepared phantoms, AXR measurements resulted in a mean value of (1.50 ± 0.04) s-1 and a CV of 2.7% across the three phantoms, demonstrating high reproducibility. Across three orthogonal diffusion directions, a mean value of (1.57 ± 0.03) s-1 with a CV of 1.9% was detected, consistent with isotropy of AXR in yeast cells. Temperature and AXR were linearly correlated (R2 = 0.99) and an activation energy EA of 37.7 kJ/mol was determined by Arrhenius plot. Furthermore, a negative correlation was found between cell density (as determined by the reference ADC/fe) and AXR (R2 = 0.95). The treatment experiment resulted in significantly decreased AXR values at different temperatures in the treated sample compared to the untreated control indicating an inhibiting effect.

CONCLUSIONS

Using ice-water and yeast cell-based phantoms, a protocol for the validation of FEXI pulse sequences was established for the assessment of stability, repeatability, reproducibility and directionality. In addition, a strong dependence of AXR on cell density and temperature was shown. As AXR is an emerging novel imaging biomarker, the suggested protocol will be useful for quality assurance of AXR measurements within a study and potentially across multiple sites.

Diagnostic value of multiple b-value diffusion-weighted imaging in discriminating the malignant from benign breast lesions

OBJECTIVE

The conventional breast Diffusion-weighted imaging (DWI) was subtly influenced by microcirculation owing to the insufficient selection of the b values. However, the multiparameter derived from multiple b-value exhibits more reliable image quality and maximize the diagnostic accuracy. We aim to evaluate the diagnostic performance of stand-alone parameter or in combination with multiparameter derived from multiple b-value DWI in differentiating malignant from benign breast lesions.

METHODS

A total of forty-one patients diagnosed with benign breast tumor and thirty-eight patients with malignant breast tumor underwent DWI using thirteen b values and other MRI functional sequence at 3.0 T magnetic resonance. Data were accepted mono-exponential, bi-exponential, stretched-exponential, aquaporins (AQP) model analysis. A receiver operating characteristic curve (ROC) was used to evaluate the diagnostic performance of quantitative parameter or multiparametric combination. The Youden index, sensitivity and specificity were used to assess the optimal diagnostic model. T-test, logistic regression analysis, and Z-test were used. P value < 0.05 was considered statistically significant.

RESULT

The ADC_avg, ADC_max, f, and α value of the malignant group were lower than the benign group, while the ADC_fast value was higher instead. The ADC_min, ADC_slow, DDC and ADC_AQP showed no statistical significance. The combination (ADC_avg-ADC_fast) yielded the largest area under curve (AUC = 0.807) with sensitivity (68.42%), specificity (87.8%) and highest Youden index, indicating that multiparametric combination (ADC_avg-ADC_fast) was validated to be a useful model in differentiating the benign from breast malignant lesion.

CONCLUSION

The current study based on the multiple b-value diffusion model demonstrated quantitatively multiparametric combination (ADC_avg-ADC_fast) exhibited the optimal diagnostic efficacy to differentiate malignant from benign breast lesions, suggesting that multiparameter would be a promising non-invasiveness to diagnose breast lesions.

Distribution of intraperitoneally administered deuterium-labeled water in aquaporin-4-knockout mouse brain after middle cerebral artery occlusion

Introduction

As the movement of water in the brain is known to be involved in neural activity and various brain pathologies, the ability to assess water dynamics in the brain will be important for the understanding of brain function and the diagnosis and treatment of brain diseases. Aquaporin-4 (AQP4) is a membrane channel protein that is highly expressed in brain astrocytes and is important for the movement of water molecules in the brain.

Methods

In this study, we investigated the contribution of AQP4 to brain water dynamics by administering deuterium-labeled water (D₂O) intraperitoneally to wild-type and AQP4 knockout (AQP4-ko) mice that had undergone surgical occlusion of the middle cerebral artery (MCA). Water dynamics in the infarct region and on either side of the anterior cerebral artery (ACA) was monitored with proton-density-weighted imaging (PDWI) performed on a 7T animal MRI.

Results

D₂O caused a negative signal change quickly after administration. The AQP4-ko mice showed a delay of the time-to-minimum in both the contralateral and ipsilateral ACA regions compared to wild-type mice. Also, only the AQP4- ko mice showed a delay of the time-to-minimum in the ipsilateral ACA region compared to the contralateral side. In only the wild-type mice, the signal minimum in the ipsilateral ACA region was higher than that in the contralateral ACA region. In the infarct region, the signal attenuation was slower for the AQP4-ko mice in comparison to the wild-type mice.

Discussion

These results suggest that AQP4 loss affects water dynamics in the ACA region not only in the infarct region. Dynamic PDWI after D₂O administration may be a useful tool for showing the effects of AQP4 in vivo.

Heterogeneity evaluation of multi-high b-value apparent diffusion coefficient on cerebral ischemia in MCAO rat

Purpose

To assess brain damage in a rat model of cerebral ischemia based on apparent diffusion coefficient (ADC) data obtained from multi-high b-values and evaluate the relationship between Aquaporin 4 (AQP4) expression and ADC.

Methods

Thirty eight male Sprague-Dawley rats were randomized into two groups: (1) sham controls (n = 6) and (2) cerebral ischemia (successful model, n = 19). All rats underwent diffusion-weighted imaging (DWI) with both standard b-values and multi-high b-values (2,500-4,500 s/mm²) using a 3.0-T device. Standard ADC (ADC_st) maps and multi-high b-value ADCs (ADC_mh) were calculated, respectively. Aquaporin 4 expression was quantified using Western blot. Relative values of ADC_st and ADC_mh, AQP4 expression were compared between the sham group and the ischemia group. Correlations between ADC values and AQP4 expression were evaluated.

Results

At 0.5 h after suture insertion, the value of ADC_mh on the lesion was obviously decreased, and there was no difference in lesion volume when compared with ADC_st. After reperfusion, besides similar regions where ADC_st values decreased, we also found additional large values on ADC_mh within the cortex of the ipsilateral side or surrounding the lesion. The lesion evolution of the large value on ADC_mh was quite different from other indicators. But the total ADC_mh values were still significantly associated with ADC_st. The AQP4 protein expression level was appreciably increased after middle cerebral artery occlusion (MCAO), but there was no correlation between AQP4 expression either with ADC_mh or ADC_st.

Conclusion

We found the large values on ADC_mh during the progression of cerebral infarction is varied, but there was no correlation between ADC_mh values and AQP4 expression. ADC_mh may indicate the heterogeneity of ischemia lesions, but the underlying pathological basis should be further explored.

Quantitative measurement of diffusion-weighted imaging signal using expression-controlled aquaporin-4 cells: Comparative study of 2-compartment and diffusion kurtosis imaging models

The purpose of this study was to compare parameter estimates for the 2-compartment and diffusion kurtosis imaging models obtained from diffusion-weighted imaging (DWI) of aquaporin-4 (AQP4) expression-controlled cells, and to look for biomarkers that indicate differences in the cell membrane water permeability. DWI was performed on AQP4-expressing and non-expressing cells and the signal was analyzed with the 2-compartment and diffusion kurtosis imaging models. For the 2-compartment model, the diffusion coefficients (Df, Ds) and volume fractions (Ff, Fs, Ff = 1-Fs) of the fast and slow compartments were estimated. For the diffusion kurtosis imaging model, estimates of the diffusion kurtosis (K) and corrected diffusion coefficient (D) were obtained. For the 2-compartment model, Ds and Fs showed clear differences between AQP4-expressing and non-expressing cells. Fs was also sensitive to cell density. There was no clear relationship with the cell type for the diffusion kurtosis imaging model parameters. Changes to cell membrane water permeability due to AQP4 expression affected DWI of cell suspensions. For the 2-compartment and diffusion kurtosis imaging models, Ds was the parameter most sensitive to differences in AQP4 expression.

Multi-parameter diffusion and perfusion magnetic resonance imaging and radiomics nomogram for preoperative evaluation of aquaporin-1 expression in rectal cancer

PURPOSE

The overexpression of aquaporin-1 (AQP1) is associated with poor prognosis in rectal cancer. This study aimed to explore the value of multi-parameter diffusion and perfusion MRI and radiomics models in predicting AQP1 high expression.

METHODS

This prospective study was performed from July 2019 to February 2021, which included rectal cancer participants after preoperative rectal MRI, with diffusion-weighted imaging, intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and dynamic contrast-enhanced (DCE) sequences. Radiomic features were extracted from MR images, and immunohistochemical tests assessed AQP1 expression. Selected quantitative MRI and radiomic features were analyzed. Receiver operating characteristic (ROC) curves evaluated the predictive performance. The nomogram performance was evaluated by its calibration, discrimen, and clinical utility. The intraclass correlation coefficient evaluated the interobserver agreement for the MRI features.

RESULTS

110 participants with the age of 60.7 ± 12.5 years been enrolled in this study. The apparent diffusion coefficient (ADC), IVIM_D, DKI_diffusivity, and DCE_Ktrans were significantly higher in participants with high AQP1 expression than in those with low expression (P < 0.05). ADC (b = 1000, 2000, and 3000 s/mm²), IVIM_D, DKI_diffusivity, and DCE_Ktrans were positively correlated (r = 0.205, 0.275, 0.37, 0.235, 0.229, and 0.227, respectively; P < 0.05), whereas DKI_Kurtosis was negatively correlated (r = - 0.22, P = 0.021) with AQP1 expression. ADC (b = 3000 s/mm²), IVIM_D, DKI_ diffusivity, DKI_Kurtosis, and DCE_Ktrans had moderate diagnostic efficiencies for high AQP1 expression (AUC = 0.715, 0.636, 0.627, 0.633, and 0.632, respectively; P < 0.05). The radiomic features had excellent predictive efficiency for high AQP1 expression (AUC = 0.967 and 0.917 for training and validation). The model-based nomogram had C-indexes of 0.932 and 0.851 for the training and validation cohorts, which indicated good fitting to the calibration curves (p > 0.05).

CONCLUSION

Diffusion and perfusion MRI can indicate the aquaporin-1 expression in rectal cancer, and radiomic features can enhance the predictive efficiency for high AQP1 expression. A nomogram for high aquaporin-1 expression will improve clinical decision-making.

Exploring cell membrane water exchange in aquaporin-4-deficient ischemic mouse brain using diffusion-weighted MRI

BACKGROUND

Aquaporin-4 is a membrane channel protein that is highly expressed in brain astrocytes and facilitates the transport of water molecules. It has been suggested that suppression of aquaporin-4 function may be an effective treatment for reducing cellular edema after cerebral infarction. It is therefore important to develop clinically applicable measurement systems to evaluate and better understand the effects of aquaporin-4 suppression on the living body.

METHODS

Animal models of focal cerebral ischemia were created by surgically occluding the middle cerebral artery of wild-type and aquaporin-4 knockout mice, after which multi-b-value multi-diffusion-time diffusion-weighted imaging measurements were performed. Data were analyzed with both the apparent diffusion coefficient (ADC) model and a compartmental water-exchange model.

RESULTS

ADCs were estimated for five different b value ranges. The ADC of aquaporin-4 knockout mice in the contralateral region was significantly higher than that of wild-type mice for each range. In contrast, aquaporin-4 knockout mice had significantly lower ADC than wild-type mice in ischemic tissue for each b-value range. Genotype-dependent differences in the ADC were particularly significant for the lowest ranges in normal tissue and for the highest ranges in ischemic tissue. The ADCs measured at different diffusion times were significantly different for both genotypes. Fitting of the water-exchange model to the ischemic region data found that the water-exchange time in aquaporin-4 knockout mice was approximately 2.5 times longer than that in wild-type mice.

CONCLUSIONS

Multi-b-value multi-diffusion-time diffusion-weighted imaging may be useful for in vivo research and clinical diagnosis of aquaporin-4-related diseases.

Glaucoma detection in Latino population through OCT's RNFL thickness map using transfer learning

PURPOSE

Glaucoma is the leading cause of irreversible blindness worldwide. It is estimated that over 60 million people around the world have this disease, with only part of them knowing they have it. Timely and early diagnosis is vital to delay/prevent patient blindness. Deep learning (DL) could be a tool for ophthalmologists to give a more informed and objective diagnosis. However, there is a lack of studies that apply DL for glaucoma detection to Latino population. Our contribution is to use transfer learning to retrain MobileNet and Inception V3 models with images of the retinal nerve fiber layer thickness map of Mexican patients, obtained with optical coherence tomography (OCT) from the Instituto de la Visión, a clinic in the northern part of Mexico.

METHODS

The IBM Foundational Methodology for Data Science was used in this study. The MobileNet and Inception V3 topologies were chosen as the analytical approaches to classify OCT images in two classes, namely glaucomatous and non-glaucomatous. The OCT files were collected from a Zeiss OCT machine at the Instituto de la Visión, and classified by an expert into the two classes under study. These images conform a dataset of 333 files in total. Since this research work is focused on RNFL thickness map images, the OCT files were cropped to obtain only the RNFL thickness map images of the corresponding eye. This action was carried out for images in both classes, glaucomatous and non-glaucomatous. Since some images were damaged (with black spots in which data was missing), these images were cut-out and cut-off. After the preparation process, 50 images per class were used for training. Fifteen images per class, different than the ones used in the training stage, were used for running predictions. In total, 260 images were used in the experiments, 130 per eye. Four models were generated, two trained with MobileNet, one for the left eye and one for the right eye, and another two trained with Inception V3. TensorFlow was used for running transfer learning.

RESULTS

The evaluation results of the MobileNet model for the left eye are, accuracy: 86%, precision: 87%, recall: 87%, and F1 score: 87%. The evaluation results of the MobileNet model for the right eye are, accuracy: 90%, precision: 90%, recall: 90%, and F1 score: 90%. The evaluation results of the Inception V3 model for the left eye are, accuracy: 90%, precision: 90%, recall: 90%, and F1 score: 90%. The evaluation results of the Inception V3 model for the right eye are, accuracy: 90%, precision: 90%, recall: 90%, and F1 score: 90%.

CONCLUSION

In average, the evaluation results for right eye images were the same for both models. The Inception V3 model showed slight better average results than the MobileNet model in the case of classifying left eye images.

Monte Carlo Simulator for Diffusion-weighted Imaging Sequences

We developed a Monte Carlo simulator for diffusion-weighted imaging sequences which displays the motion of water molecules and computes the dynamic phase dispersion due to the applied motion probing gradients. This simulator can be used to validate the analytical equations of diffusion models and understand their limitations due to their approximations. Here, we introduce the software and some specific use cases. The software can be downloaded from the following website: https://www.nirs.qst.go.jp/amr_diag.

Attempts at the Characterization of In-Cell Biophysical Processes Non-Invasively-Quantitative NMR Diffusometry of a Model Cellular System

In the literature, diffusion studies of cell systems are usually limited to two water pools that are associated with the extracellular space and the entire interior of the cell. Therefore, the time-dependent diffusion coefficient contains information about the geometry of these two water regions and the water exchange through their boundary. This approach is due to the fact that most of these studies use pulse techniques and relatively low gradients, which prevents the achievement of high b-values. As a consequence, it is not possible to register the signal coming from proton populations with a very low bulk or apparent self-diffusion coefficient, such as cell organelles. The purpose of this work was to obtain information on the geometry and dynamics of water at a level lower than the cell size, i.e., in cellular structures, using the time-dependent diffusion coefficient method. The model of the cell system was made of baker’s yeast (Saccharomyces cerevisiae) since that is commonly available and well-characterized. We measured characteristic fresh yeast properties with the application of a compact Nuclear Magnetic Resonance (NMR)-Magritek Mobile Universal Surface Explorer (MoUSE) device with a very high, constant gradient (~24 T/m), which enabled us to obtain a sufficient stimulated echo attenuation even for very short diffusion times (0.2–40 ms) and to apply very short diffusion encoding times. In this work, due to a very large diffusion weighting (b-values), splitting the signal into three components was possible, among which one was associated only with cellular structures. Time-dependent diffusion coefficient analysis allowed us to determine the self-diffusion coefficients of extracellular fluid, cytoplasm and cellular organelles, as well as compartment sizes. Cellular organelles contributing to each compartment were identified based on the random walk simulations and approximate volumes of water pools calculated using theoretical sizes or molar fractions. Information about different cell structures is contained in different compartments depending on the diffusion regime, which is inherent in studies applying extremely high gradients.

Mapping white matter damage distribution in neuromyelitis optica spectrum disorders with a multimodal MRI approach

BACKGROUND

The pathogenetic mechanisms sustaining neuroinflammatory disorders may originate from the cerebrospinal fluid.

OBJECTIVE

To evaluate white matter damage with diffusion tensor imaging and T1/T2-weighted ratio at progressive distances from the ventricular system in neuromyelitis optica spectrum disorders and multiple sclerosis.

METHODS

Fractional anisotropy, mean, axial, and radial diffusivity and T1/T2-weighted ratio maps were obtained from patients with seropositive neuromyelitis optica spectrum disorders, multiple sclerosis, and healthy controls (n = 20 each group). White matter damage was assessed as function of ventricular distance within progressive concentric bands.

RESULTS

Compared to healthy controls, neuromyelitis optica spectrum disorders patients had similar fractional anisotropy, radial and axial diffusivity, increased mean diffusivity (p = 0.009-0.013) and reduced T1/T2-weighted ratio (p = 0.024-0.037) in all bands. In multiple sclerosis, gradient of percentage lesion volume and intra-lesional mean and axial diffusivity were higher in periventricular bands. Compared to healthy controls, multiple sclerosis patients had reduced fractional anisotropy (p = 0.001-0.043) in periventricular bands, increased mean (p < 0.001), radial (p < 0.001-0.004), and axial diffusivity (p = 0.002-0.008) and preserved T1/T2-weighted ratio in all bands.

CONCLUSION

White matter damage is higher at periventricular level in multiple sclerosis and diffuse in neuromyelitis optica spectrum disorders. Fractional anisotropy preservation, associated with increased mean diffusivity and reduced T1/T2-weighted ratio may reflect astrocyte damage.

Based on Histogram Analysis: ADCaqp Derived from Ultra-high b-Value DWI could be a Non-invasive Specific Biomarker for Rectal Cancer Prognosis

Aquaporins (AQP) are not only water channel protein, but also potential prognostic indicator and therapeutic target for rectal cancer. Some previous studies have demonstrated the AQP expression could be estimated by ADC_aqp value derived from ultra-high b-value diffusion-weighted imaging (DWI). We aim to determine whether ADC_aqp could be a new and specific biomarker for indicating the AQP expression and prognostic factors of rectal cancer. 76 untreated patients with rectal cancer confirmed by colonoscopy biopsy were enrolled. ADC_aqp value was generated from ultra-high b-value DWI with five b-values (1700–3500 s/mm²). AQP (AQP1, 3 and 5)staining intensity was estimated by both of software (QuPath) and manual manner. The relationships between histogram features of ADC_aqp and AQP staining intensity were analyzed. The correlations between histogram features of ADC_aqp and differentiation degrees (good, moderate, poor), T stage (T1–2 vs T3–4), and lymph node status (N+ vs N−) were also evaluated respectively. The mean, 75^th percentile and 97.5^th percentile of ADC_aqp were correlated with AQP1 staining intensity (r = 0.237, 0.323 and 0.362, respectively, all P < 0.05) . No correlation was found between the histogram features of ADC_aqp and AQP3 or AQP5 staining intensity. The mean, 50^th percentile, 75^th percentile and 97.5^th percentile of ADC_aqp value exhibited significant differences between differentiation status (all P < 0.05). Histogram features of ADC_aqp value showed no significant differences in two subgroups of T stage and lymph node status (all P > 0.05). Histogram analysis showed that the ADC_aqp value derived from ultra-high b-value DWI of rectal cancer could reflect AQP1’s expression and rectal cancer’s malignancy degree. ADC_aqp might be a new imaging biomarker for evaluating rectal cancer.

The Glymphatic System: A Review of the Challenges in Visualizing its Structure and Function with MR Imaging

The central nervous system (CNS) was previously thought to be the only organ system lacking lymphatic vessels to remove waste products from the interstitial space. Recently, based on the results from animal experiments, the glymphatic system was hypothesized. In this hypothesis, cerebrospinal fluid (CSF) enters the periarterial spaces, enters the interstitial space of the brain parenchyma via aquaporin-4 (AQP4) channels in the astrocyte end feet, and then exits through the perivenous space, thereby clearing waste products. From the perivenous space, the interstitial fluid drains into the subarachnoid space and meningeal lymphatics of the parasagittal dura. It has been reported that the glymphatic system is particularly active during sleep. Impairment of glymphatic system function might be a cause of various neurodegenerative diseases such as Alzheimer’s disease, normal pressure hydrocephalus, glaucoma, and others. Meningeal lymphatics regulate immunity in the CNS. Many researchers have attempted to visualize the function and structure of the glymphatic system and meningeal lymphatics in vivo using MR imaging. In this review, we aim to summarize these in vivo MR imaging studies and discuss the significance, current limitations, and future directions. We also discuss the significance of the perivenous cyst formation along the superior sagittal sinus, which is recently discovered in the downstream of the glymphatic system.

Imaging of Hypoxic Tumor: Correlation between Diffusion-weighted MR Imaging and 18F-fluoroazomycin Arabinoside Positron Emission Tomography in Head and Neck Carcinoma

We investigated the usefulness of diffusion-weighted imaging (DWI) for detecting changes in the structure of hypoxic cells by evaluating the correlation between ¹⁸F-fluoroazomycin arabinoside (FAZA) positron emission tomography activity and DWI parameters in head and neck carcinoma. The diffusion coefficient corresponding to the slow compartment of a two-compartment model had a significant positive correlation with FAZA activity (ρ = 0.58, P = 0.016), whereas the diffusional kurtosis from diffusion kurtosis imaging had a significant negative correlation (ρ = -0.62, P = 0.008), which suggests that those DWI parameters might be useful as indicators for changes in cell structure.