Perfusion and diffusion in meningioma tumors: a preliminary multiparametric analysis with Dynamic Susceptibility Contrast and IntraVoxel Incoherent Motion MRI

Multiparametric MRI is a remarkable imaging method for the assessment of patho-physiological processes. In particular, brain tumor characterization has taken advantage of the development of advanced techniques such as Diffusion- (DWI) and Perfusion- (PWI) Weighted Imaging, but a thorough analysis of meningiomas is still lacking despite the variety of computational methods proposed.We compute perfusion and diffusion parametric maps relying on a well-defined methodological workflow, investigating possible correlations between pure and diffusion-based perfusion parameters in a cohort of 26 patients before proton therapy. A preliminary investigation of meningioma staging biomarkers based on IntraVoxel Incoherent Motion and Dynamic Susceptibility Contrast is also reported. We observed significant differences between the gross target volume and the normal appearing white matter for every investigated parameter, confirming the higher vascularization of the neoplastic tissue. DWI and PWI parameters appeared to be weakly correlated and we found that diffusion parameters – the perfusion fraction in particular – could be promising biomarkers for tumor staging.     

In vivo multiparametric magnetic resonance imaging study for differentiating the severity of hepatic warm ischemia-reperfusion injury in a rabbit model

ObjectivesTo assess the value of multiparametric magnetic resonance imaging including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI) and blood oxygen level dependent (BOLD) MRI in differentiating the severity of hepatic warm ischemia-reperfusion injury (WIRI) in a rabbit model.MethodsFifty rabbits were randomly divided into a sham-operation group and four test groups (n = 10 for each group) according to different hepatic warm ischemia times. IVIM, DTI and BOLD MRI were performed on a 3 T MR scanner with 11 b values (0 to 800 s/mm²), 2 b values (0 and 500 s/mm²) on 12 diffusion directions, multiple-echo gradient echo (GRE) sequences (TR/TE, 75/2.57–24.25 ms), respectively. IVIM, DTI and BOLD MRI parameters, hepatic biochemical and histopathological parameters were compared. Pearson and Spearman correlation methods were performed to assess the correlation between these MRI parameters and laboratory parameters. Furthermore, receiver operating characteristic (ROC) curves were compiled to determine diagnostic efficacies.ResultsTrue diffusion (Dslow), pseudodiffusion (Dfast), perfusion fraction (PF), mean diffusivity (MD) significantly decreased, while R2* significantly increased with prolonged warm ischemia times, and significant differences were found in all of biochemical and histopathological parameters (all P < 0.05). Dslow, PF, and R2* correlated significantly with all of biochemical and histopathological parameters (all |r| = 0.381–0.746, all P < 0.05). ROC analysis showed that the area under the ROC curve (AUC) of IVIM across hepatic WIRI groups was the largest among IVIM, DTI and BOLD.ConclusionsMultiparametric MRI may be helpful with characterization of early changes and determination of severity of hepatic WIRI in a rabbit model.     

Prediction of early response to concurrent chemoradiotherapy in cervical cancer: Value of multi-parameter MRI combined with clinical prognostic factors

PurposeThis study aimed to investigate the prediction of early response to concurrent chemoradiotherapy (CCRT) through a combination of pretreatment multi-parametric magnetic resonance imaging (MRI) with clinical prognostic factors (CPF) in cervical cancer patients.MethodsEighty-five patients with pathologically confirmed cervical cancer underwent conventional MRI, intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI), and dynamic contrast-enhanced MRI (DCE-MRI) before CCRT. The patients were divided into non- and residual tumor groups according to post-treatment MRI. Univariable and multivariable analyses were performed to pretreatment MRI parameters and CPF between the two groups, and optimal thresholds and predictive performance for post-treatment residual tumor occurrence were estimated by drawing the receiver operating characteristic (ROC) curve.ResultsThere were 52 patients in non- and 33 in residual group. The residual group showed a lower perfusion fraction (f) value and volume transfer constant (K^trans) value, a higher apparent diffusion coefficient (ADC) value, diffusion coefficient (D) value and volume fraction of extravascular extracellular space (V_e) value, and a higher stage than the non-residual tumor group (all P < .05). D, K^trans, V_e and stage were independent prognostic factors. The combination of D, K^trans and V_e improved the diagnostic performance compared with individual MRI parameters. A further combination of these three MRI parameters with stage exhibited the highest predictive performance.ConclusionsPretreatment D, K^trans, V_e and stage were independent prognostic factors for cervical cancer. The predictive capacity of multi-parametric MRI was superior to individual MRI parameters. The combination of multi-parametric MRI with CPF further improved the predictive performance.     

Repeatability of echo-planar-based diffusion measurements of the human prostate at 3 T

Echo-planar-based diffusion-weighted imaging (DWI) of the prostate is increasingly being suggested as a viable technique, complementing information derived from conventional magnetic resonance imaging methods for use in tissue discrimination. DWI has also been suggested as a potentially useful tool in the assessment of tumor response to treatment. In this study, the repeatability of apparent diffusion coefficient (ADC) values obtained from both DWI and diffusion tensor imaging (DTI) has been assessed as a precursor to determining the magnitude of treatment-induced changes required for reliable detection. The repeatability values of DWI and DTI were found to be similar, with ADC values repeatable to within 35% or less over a short time period of a few minutes and a longer time period of a month. Fractional anisotropy measurements were found to be less repeatable (between 26% and 71%), and any changes duly recorded in longitudinal studies must therefore be treated with a degree of caution.     

Role of diffusion tensor imaging metrics and in vivo proton magnetic resonance spectroscopy in the differential diagnosis of cystic intracranial mass lesions

The purpose of this study was to determine whether proton magnetic resonance spectroscopy (PMRS) and diffusion tensor imaging (DTI) indices, fractional anisotropy (FA) and mean diffusivity (MD) can be used to distinguish brain abscess from cystic brain tumors, which are difficult to distinguish by conventional magnetic resonance imaging (MRI). Fifty-three patients with intracranial cystic mass lesions and 10 normal controls were studied. Conventional MRI, PMRS and DTI of all the patients were performed on a 1.5-T GE scanner. Forty patients were with brain abscess and 13 with cystic tumors. Cytosolic amino acids (AAs) were present in 32 of 40 brain abscess patients. Out of 13 patients with cystic tumors, lactate and choline were seen in 3 and only lactate was present in 10 patients on PMRS. All 40 cases of abscess had high FA, while all 13 cases of tumor cysts had high MD values. We conclude that FA measurements are more sensitive in predicting the abscess, while PMRS and MD are more specific in differentiating abscess from cystic tumors. We suggest that PMRS should be combined with DTI rather than with diffusion-weighted imaging as FA can be used as an additional parameter for separation of abscess from other cystic intracranial mass lesions.     

低场MRI系统中线扫描扩散张量成像方法的研究

磁共振扩散张量成像(DTI)是在扩散加权成像(DWI)基础上发展起来的一种新型技术,可以无创伤显示脑白质纤维,诊断脑白质病变. 但是由于各种原因,DTI一般只在超导高场磁共振成像(MRI)仪器上进行,这就限制了这一重要诊断手段临床应用的广泛性. 本文在低场磁共振成像系统上应用线扫描实现了扩散张量成像,并测量了健康志愿者大脑内主要解剖结构的表观扩散系数(ADC)和各项异性分数(FA),得到的数据与高场仪器上的相关数据比较是吻合的. 因此临床上使用在低场强上得到的DTI图像评价脑白质是可行的,而且通常在临床上这也是足够的.     

Relationships between spinal cord blood flow measured with flow-sensitive alternating inversion recovery (FAIR) and neurobehavioral outcomes in rat spinal cord injury

In the traumatically injured spinal cord, decreased perfusion is believed to contribute to secondary tissue damage beyond the primary mechanical impact, and restoration of perfusion is believed to be a promising therapeutic target. However, methods to monitor spinal cord perfusion non-invasively are limited. Perfusion magnetic resonance imaging (MRI) techniques established for the brain have not been routinely adopted to the spinal cord. The purpose of this study was to examine the relationship between spinal cord blood flow (SCBF) and injury severity in a rat thoracic spinal cord contusion injury (SCI) model using flow-sensitive alternating inversion recovery (FAIR) with two variants of the label position. SCBF as a marker of severity was compared to T₁ mapping and to spinal cord-optimized diffusion weighted imaging (DWI) with filtered parallel apparent diffusion coefficient. Thirty-eight rats underwent a T10 contusion injury with varying severities (8 sham; 10 mild; 10 moderate; 10 severe) with MRI performed at 1 day post injury at the lesion site and follow-up neurological assessments using the Basso, Beattie, Bresnahan (BBB) locomotor scoring up to 28 days post injury. Using whole-cord regions of interest at the lesion epicenter, SCBF was decreased with injury severity and had a significant correlation with BBB scores at 28 days post injury. Importantly, estimates of arterial transit times (ATT) in the injured spinal cord were not altered after injury, which suggests that FAIR protocols optimized to measure SCBF provide more value in the context of acute traumatic injury to the cord. T₁-relaxation time constants were strongly related to injury severity and had a larger extent of changes than either SCBF or DWI measures. These findings suggest that perfusion decreases in the spinal cord can be monitored non-invasively after injury, and multi-parametric MRI assessments of perfusion, diffusion, and relaxation capture unique features of the pathophysiology of preclinical injury.     

Gadoxetic acid-enhanced MRI compared with CT during angiography in the diagnosis of hepatocellular carcinoma

Purpose

To assess the value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) for the pre-therapeutic detection of hepatocellular carcinoma (HCC) using receiver operating characteristic (ROC) analysis with the combination of computed tomography (CT) arterial portography and CT hepatic arteriography (CTAP/CTHA).

Materials and Methods

A total of 54 consecutive patients with 87 nodular HCCs were retrospectively analyzed. All HCC nodules were confirmed pathologically. Three blinded readers independently reviewed 432 hepatic segments, including 78 segments with 87 HCCs. Each reader read two sets of images: Set 1, CTAP/CTHA; Set 2, gadoxetic acid-enhanced MRI including a gradient dual-echo sequence and diffusion-weighted imaging (DWI). The ROC method was used to analyze the results. The sensitivity, specificity, positive predictive value, negative predictive value and sensitivity according to tumor size were evaluated.

Results

For each reader, the area under the curve was significantly higher for Set 2 than for Set 1. The mean area under the curve was also significantly greater for Set 2 than for Set 1 (area under the curve, 0.98 vs. 0.93; P = .0009). The sensitivity was significantly higher for Set 2 than for Set 1 for all three readers (P = .012, .013 and .039, respectively). The difference in the specificity, positive predictive values and negative predictive values of the two modalities for each reader was not significant (P > .05).

Conclusion

Gadoxetic acid-enhanced MRI including a gradient dual-echo sequence and DWI is recommended for the pre-therapeutic evaluation of patients with HCC.     

Towards safe operation of an active retinal prosthesis during functional MRI and diffusion tensor imaging

ObjectiveTo determine if the Argus II retinal prosthesis can operate during functional MRI (fMRI) and diffusion tensor imaging (DTI) acquisitions and if currents induced in the prosthesis by imaging are at safe levels.Materials and methodsOne Argus II retinal prosthesis was modified to enable current measurements during imaging. Active electronics were modified to enable operation during scans. Induced current was measured during diagnostic scans, which were previously shown to be safe for implanted patients, and during fMRI and DTI scans. All measurements were performed using an ASTM phantom to ensure reproducible placement.ResultsThe prosthesis was able to maintain communication with the external RF coil during the fMRI and DTI scans except briefly during pre-scans. Current levels induced during fMRI and DTI scans were consistently below those measured during diagnostic scans.ConclusionsfMRI and DTI may be safely performed while the Argus II retinal prosthesis is operating.     

White matter changes in multiple sclerosis: correlation of q-space diffusion MRI and 1H MRS

OBJECTIVE: To explore the diagnostic usefulness of high b-value diffusion magnetic resonance brain imaging ("q-space" imaging) in multiple sclerosis (MS). More specifically, we aimed at evaluating the ability of this methodology to identify tissue damage in the so-called normal-appearing white matter (NAWM). DESIGN: In this study we examined the correlation between q-space diffusion imaging and magnetic resonance spectroscopy (MRS)-based two-dimensional 1H chemical shift imaging. Eight MS patients with different degree of disease severity and seven healthy subjects were scanned in a 1.5-T magnetic resonance imaging (MRI) scanner. The MRI protocol included diffusion tensor imaging (DTI) (with bmax of 1000 s/mm2), high b-value diffusion-weighted imaging (with bmax of 14,000 s/mm2) and 2D chemical shift imaging. The high b-value data set was analyzed using the q-space methodology to produce apparent displacement and probability maps. RESULTS: We found that the q-space diffusion displacement and probability image intensities correlated well with N-acetylaspartate levels (r=.61 and .54, respectively). Furthermore, NAWM that was abnormal on MRS was also found to be abnormal using q-space diffusion imaging. In these areas, the q-space displacement values increased from 3.8+/-0.2 to 4.6+/-0.6 microm (P<.02), the q-space probability values decreased from 7.4+/-0.3 to 6.8+/-0.3 (P<.002), while DTI revealed only a small, but still significant, reduction in fractional anisotropy values from 0.40+/-0.02 to 0.37+/-0.02 (P<.05). CONCLUSION: High b-value diffusion imaging can detect tissue damage in the NAWM of MS patients. Despite the theoretical limitation of this method, in practice it provides additional information which is clinically relevant for detection of tissue damage not seen in conventional imaging techniques.     

Individual identification using multi-metric of DTI in Alzheimer's disease and mild cognitive impairment

Accurate identification of Alzheimer's disease(AD) and mild cognitive impairment(MCI) is crucial so as to improve diagnosis techniques and to better understand the neurodegenerative process. In this work, we aim to apply the machine learning method to individual identification and identify the discriminate features associated with AD and MCI. Diffusion tensor imaging scans of 48 patients with AD, 39 patients with late MCI, 75 patients with early MCI, and 51 age-matched healthy controls(HCs) are acquired from the Alzheimer's Disease Neuroimaging Initiative database. In addition to the common fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity metrics, there are two novel metrics,named local diffusion homogeneity that used Spearman's rank correlation coefficient and Kendall's coefficient concordance,which are taken as classification metrics. The recursive feature elimination method for support vector machine(SVM)and logistic regression(LR) combined with leave-one-out cross validation are applied to determine the optimal feature dimensions. Then the SVM and LR methods perform the classification process and compare the classification performance.The results show that not only can the multi-type combined metrics obtain higher accuracy than the single metric, but also the SVM classifier with multi-type combined metrics has better classification performance than the LR classifier.Statistically, the average accuracy of the combined metric is more than 92% for all between-group comparisons of SVM classifier. In addition to the high recognition rate, significant differences are found in the statistical analysis of cognitive scores between groups. We further execute the permutation test, receiver operating characteristic curves, and area under the curve to validate the robustness of the classifiers, and indicate that the SVM classifier is more stable and efficient than the LR classifier. Finally, the uncinated fasciculus, cingulum, corpus callosum, corona radiate, external capsule, and internal capsule have been regarded as the most important white matter tracts to identify AD, MCI, and HC. Our findings reveal a guidance role for machine-learning based image analysis on clinical diagnosis.     

Diffusion-weighted imaging of the brain at 7 T with echo-planar and turbo spin echo sequences: preliminary results

Ultra-high-field clinical MRI scanners (e.g., 7 T and above) are becoming increasingly prevalent and can potentially enhance diagnostic ability through higher contrast, resolution and/or sensitivity. Diffusion-weighted MRI is a highly valued component in today's radiological exam and may benefit from the enhanced signal-to-noise ratio provided by high field with the appropriate imaging strategy. The most common diffusion pulse sequence readout (echo-planar imaging (EPI)) has been widely employed for in vivo human 7 T diffusion tensor imaging (DTI). In this article, we present results of brain DTI at 7 T with two diffusion-weighted imaging pulse sequence readouts: echo-planar imaging (EPI-DTI) and turbo spin echo (TSE-DTI). Results indicate that analogous coverage, quality and resolution typical of lower field (2 mm) can be obtained by properly processed EPI-DTI at 7 T, and, with some reduction in efficiency and sharpness, TSE-DTI at 7 T. Furthermore, 7 T TSE-DTI shows promise in obtaining higher-resolution results in targeted acquisitions of specific brain areas.     

Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI

Diffusion tensor mapping with MRI can noninvasively track neural connectivity and has great potential for neural scientific research and clinical applications. For each diffusion tensor imaging (DTI) data acquisition scheme, the diffusion tensor is related to the measured apparent diffusion coefficients (ADC) by a transformation matrix. With theoretical analysis we demonstrate that the noise performance of a DTI scheme is dependent on the condition number of the transformation matrix. To test the theoretical framework, we compared the noise performances of different DTI schemes using Monte-Carlo computer simulations and experimental DTI measurements. Both the simulation and the experimental results confirmed that the noise performances of different DTI schemes are significantly correlated with the condition number of the associated transformation matrices. We therefore applied numerical algorithms to optimize a DTI scheme by minimizing the condition number, hence improving the robustness to experimental noise. In the determination of anisotropic diffusion tensors with different orientations, MRI data acquisitions using a single optimum b value based on the mean diffusivity can produce ADC maps with regional differences in noise level. This will give rise to rotational variances of eigenvalues and anisotropy when diffusion tensor mapping is performed using a DTI scheme with a limited number of diffusion-weighting gradient directions. To reduce this type of artifact, a DTI scheme with not only a small condition number but also a large number of evenly distributed diffusion-weighting gradients in 3D is preferable.     

EADC Values in Diagnosis of Renal Lesions by 3.0 T Diffusion-Weighted Magnetic Resonance Imaging: Compared with the ADC Values

Exponential apparent diffusion coefficient (EADC) is an indicator of diffusion-weighted imaging (DWI) and reflects the pathological changes of tissues quantitatively. However, no study has been investigated in the space-occupying kidney disease using EADC values. This study aims to evaluate the diagnostic role of EADC values at a high magnetic field strength (3.0 T) in kidney neoplastic lesions, compared with that of the ADC values. Ninety patients with suspected renal tumors (including 101 suspected renal lesions) and 20 healthy volunteers were performed MRI scanning. Diffusion-weighted imaging was performed with a single-shot spin-echo echo-planar imaging (SE-EPI) sequence at a diffusion gradient of b = 500 s/mm². We found renal cell carcinoma (RCC) can be distinguished from angiomyolipoma, and clear cell carcinoma can be distinguished from non-clear cell carcinoma by EADC value. There was significant difference in overall EADC values between renal cell carcinoma (0.150 ± 0.059) and angiomyolipoma (0.270 ± 0.108) when b value was 500 s/mm². When receiver operating characteristic (ROC) was higher than 0.192, the sensitivity and specificity of EADC value of renal cell carcinoma were 84.6 and 81.1 %, respectively. In conclusion, EADC map shows the internal structure of the kidney tumor more intuitively than the ADC map dose, and is also in line with the observation habits of the clinicians. EADC can be used as an effective imaging method for tumor diagnosis.     

Sodium and proton diffusion MRI as biomarkers for early therapeutic response in subcutaneous tumors

The ability to quantitate early effects of tumor therapeutic response using noninvasive imaging would have a major impact in clinical oncology. One area of active research interest is the ability to use MR techniques to detect subtle changes in tumor cellular density. In this study, sodium and proton diffusion MRI were compared for their ability to detect early cellular changes in tumors treated with a cytotoxic chemotherapy. Subcutaneous 9L gliosarcomas were treated with a single dose of 1,3-bis(2-chloroethyl)-1-nitrosourea. Both sodium and diffusion imaging modalities were able to detect changes in tumor cellularity as early as 2 days after treatment, which continued to evolve as increased signal intensities reached a maximum approximately 8 days posttreatment. Early changes in tumor sodium and apparent diffusion coefficient values were predictive of subsequent tumor shrinkage, which occurred approximately 10 days later. Overall, therapeutical induced changes in sodium and diffusion values were found to have similar dynamic and spatial changes. These findings suggest that these imaging modalities detected similar early cellular changes after treatment. The results of this study support the continued clinical testing of diffusion MRI for evaluation of early tumor treatment response and demonstrate the complementary insights of sodium MRI for oncology applications.     

Non-gaussian models of 3-Tesla diffusion-weighted MRI for the differentiation of pancreatic ductal adenocarcinomas from neuroendocrine tumors and solid pseudopapillary neoplasms

PurposeTo assess the MRI performance in differentiating pancreatic ductal adenocarcinomas (PDACs), from solid pseudopapillary neoplasms (SPNs) and pancreatic neuroendocrine tumors (PNETs) using non-gaussian diffusion-weighted imaging models.MethodsThis was a retrospective study of patients diagnosed with PDACs (01/2015–06/2019) or with PNETs or SPNs diagnosed (01/2011–12/2019) at our hospital. The lesions were randomized 1:1 to the primary and validation cohorts. The regions of interest (ROIs) were manually drawn on each slice at DWI (b = 1500 s/mm²) from 3 T MRI. D (diffusion coefficient), D* (pseudodiffusion coefficient), f (perfusion fraction), distributed diffusion coefficient (DDC), α (diffusion heterogeneity index), mean diffusivity (MD) and mean kurtosis (MK) were obtained. The parameters with largest performance for differentiation were used to establish a diagnostic model.ResultsThere were 148, 56, and 60 patients with PDAC, PNET, and SPN, respectively. For differentiating PDACs from SPNs, f and MK values were used to establish a diagnostic model with areas under the receiver operating characteristic curves (AUCs) of 0.92 and 0.89 in the primary and validation groups, respectively. For distinguishing PDACs from PNETs, α and MK values were used to establish a diagnostic model with AUCs of 0.87 and 0.86 in the primary and validation groups, respectively. The accuracy rate of the subjective evaluation with the assistance of non-gaussian DWI models for differentiating PDAC from SPNs and PNETs were higher than that of subjective diagnosis alone (P < 0.05).ConclusionsThe non-gaussian DWI models could assist radiologists in accurately differentiating PDACs from PNETs and SPNs.     

Intermolecular double quantum coherences (iDQc) and diffusion-weighted imaging (DWI) imaging of the human brain at 1.5 T

To study the sensitivity of intermolecular double quantum coherences (iDQc) imaging contrast to brain microstructure and brain anisotropy, we investigated the iDQC contrast between differently structured areas of the brain according to the strength and the direction of the applied correlation gradient. Thus diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) maps have been obtained. This procedure, which consists of analyzing both iDQc and DWI images at different gradient strength and gradient direction, could be a promising tool for clinical brain investigations performed with higher than 1.5 T magnetic fields.     

Quantitative assessment of intracranial tumor response to dexamethasone using diffusion, perfusion and permeability magnetic resonance imaging

There is increasing interest in obtaining quantitative imaging parameters to aid in the assessment of tumor responses to treatment. In this study, the feasibility of performing integrated diffusion, perfusion and permeability magnetic resonance imaging (MRI) for characterizing responses to dexamethasone in intracranial tumors was assessed. Eight patients with glioblastoma, five with meningioma and three with metastatic carcinoma underwent MRI prior to and 48-72 h following dexamethasone administration. The MRI protocol enabled quantification of the volume transfer constant (K(trans)), extracellular space volume fraction (nu(e)), plasma volume fraction (nu(p)), regional cerebral blood flow (rCBF), regional cerebral blood volume (rCBV), longitudinal relaxation time (T(1)) and mean diffusivity (D(av)). All subjects successfully completed the imaging protocol for the presteroid and poststeroid scans. Significant reductions were observed after the treatment for K(trans), nu(e) and nu(p) in enhancing tumor as well as for T(1) and D(av) in the edematous brain in glioblastoma; on the other hand, for meningioma, significant differences were seen only in edematous brain T(1) and D(av). No significant difference was observed for any parameter in metastatic carcinoma, most likely due to the small sample size. In addition, no significant difference was observed for enhancing tumor rCBF and rCBV in any of the tumor types, although the general trend was for rCBV to be reduced and for rCBF to be more variable. The yielded parameters provide a wealth of physiologic information and contribute to the understanding of dexamethasone actions on different types of intracranial tumors.     

Advanced diffusion models in head and neck squamous cell carcinoma patients: Goodness of fit,relationships among diffusion parameters and comparison with dynamic contrast-enhanced perfusion

PurposeWe assessed advanced fitting models of diffusion weighted imaging (DWI) in head/neck squamous cell carcinoma (HNSCC) patients to determine the best goodness of fit and correlations among diffusion parameters. We compared these results with those of dynamic contrast-enhanced (DCE) perfusion parameters.Materials and methodsWe retrospectively evaluated 32 HNSCC patients (12 sinonasal, 20 pharynx/oral cavity). The DWI acquisition used single-shot spin-echo echo-planar imaging (EPI) with 12 b-values (0 − 2000). We calculated 14 DWI parameters using mono-exponential, bi-exponential, and tri-exponential models, stretched exponential model (SEM) and diffusion kurtosis imaging (DKI) models. We compared each model's goodness of fit using the residual sum of squares (RSS), Akaike Information Criterion (AIC) and Bayesian information criterion (BIC) value. We determined the correlation between each pair of DWI parameters and between each DWI parameter and DCE perfusion parameter.ResultsThe tri-exponential fit's RSS, AIC and BIC values were significantly smaller than those for bi-exponential fit. The RSS, AIC and BIC values of the SEM fit and DKI fit were significantly smaller than mono-exponential model. Significant correlations were observed in 30 pairs (sinonasal cavity) and 31 (sinonasal cavity group) among 91 DWI parameter combinations. Significant correlations were also observed in nine pairs (both sinonasal cavity and pharynx/oral cavity group) among 64 DWI/DCE perfusion parameter pairs, in particular, high positive correlations between the tri-exponential model's intermediate diffusion fraction (f₂) and the volume of the extracellular extravascular space per unit volume of tissue (v_e) were observed in both patient groups.ConclusionWe identified several correlations between DWI parameters by advanced fitting models and correlations between DWI and DCE parameters. These will help determine HNSCC patients' detailed tissue structures.     

Volumetric q-space imaging by 3D diffusion-weighted MRI

High b-value diffusion magnetic resonance imaging (MRI) enables us to detect far smaller architectures, by using q-space analysis, than the resolution in conventional MRI. Average displacement, one of the q-space parameters, quantitatively reflects architecture size and is very useful in observing small changes in microstructures in vivo (e.g., neurodegeneration, tumor heterogeneity, and others). Diffusion-weighted imaging (DWI) is performed by a two-dimensional (2D) multislice method; however, due to finite slice thickness and slice gap, there is a partial-volume effect that makes it difficult to detect the net q-space signal. On the other hand, three-dimensional (3D) MRI, having the advantages of very thin slice thickness and no slice gap (contiguous slices), allows volumetric evaluation acquired in a small isotropic voxel, as compared to 2D multislice imaging. Little is known about the isotropic high-resolution 3D DWI application to q-space analysis. In this study, we have developed and implemented a high b-value 3D DWI sequence, applied q-space analysis to study the reliability of high b-value 3D DWI and obtained a microscopic analytical map with isotropic high resolution and less contamination.