Comparing diagnostic accuracy of luminal water imaging with diffusion‐weighted and dynamic contrast‐enhanced MRI in prostate cancer: A quantitative MRI study

Luminal water imaging (LWI) is a new MRI T₂ mapping technique that has been developed with the aim of diagnosis of prostate carcinoma (PCa). This technique measures the fractional amount of luminal water in prostate tissue, and has shown promising preliminary results in detection of PCa. To include LWI in clinical settings, further investigation on the accuracy of this technique is required. In this study, we compare the diagnostic accuracy of LWI with those of diffusion‐weighted imaging (DWI) and dynamic contrast‐enhanced (DCE) MRI in detection and grading of PCa. Fifteen patients with biopsy‐proven PCa consented to participate in this ethics‐board‐approved prospective study. Patients were examined with LWI, DWI, and DCE sequences at 3 T prior to radical prostatectomy. Maps of MRI parameters were generated and registered to whole‐mount histology. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of individual and combined MR parameters. Correlation with Gleason score (GS) was evaluated using Spearman's rank correlation test. The results show that area under the ROC curve (AUC) obtained from LWI was equal to or higher than the AUC obtained from DWI, DCE, or their combination, in peripheral zone (0.98 versus 0.90, 0.89, and 0.91 respectively), transition zone (0.99 versus 0.98, n/a, and 0.98), and the entire prostate (0.85 versus 0.81, 0.75, and 0.84). The strongest correlation with GS was achieved from LWI (ρ = ?0.81 ± 0.09, P < 0.001). Results of this pilot study show that LWI performs equally well as, or better than, DWI and DCE in detection of PCa. LWI provides significantly higher correlation with GS than DWI and DCE. This technique can potentially be included in clinical MRI protocols to improve characterization of tumors. However, considering the small size of the patient population in this study, a further study with a larger cohort of patients and broader range of GS is required to confirm the findings and draw a firm conclusion on the applicability of LWI in clinical settings.     

Relationship between diffusion parameters derived from intravoxel incoherent motion MRI and perfusion measured by dynamic contrast‐enhanced MRI of soft tissue tumors

Our aim was to evaluate the link between diffusion parameters measured by intravoxel incoherent motion (IVIM) diffusion‐weighted imaging (DWI) and the perfusion metrics obtained with dynamic contrast‐enhanced (DCE) MRI in soft tissue tumors (STTs). Twenty‐eight patients affected by histopathologically confirmed STT were included in a prospective study. All patients underwent both DCE MRI and IVIM DWI. The perfusion fraction f, diffusion coefficient D and perfusion‐related diffusion coefficient D* were estimated using a bi‐exponential function to fit the DWI data. DCE MRI was acquired with a temporal resolution of 3–5 s. Maps of the initial area under the gadolinium concentration curve (IAUGC), time to peak (TTP) and maximum slope of increase (MSI) were derived using commercial software. The relationships between the DCE MRI and IVIM DWI measurements were assessed by Spearman's test. To exclude false positive results under multiple testing, the false discovery rate (FDR) procedure was applied. The Mann–Whitney test was used to evaluate the differences between all variables in patients with non‐myxoid and myxoid STT. No significant relationship was found between IVIM parameters and any DCE MRI parameters. Higher f and D*f values were found in non‐myxoid tumors compared with myxoid tumors (p = 0.004 and p = 0.003, respectively). MSI was significantly higher in non‐myxoid tumors than in myxoid tumors (p = 0.029). From the visual assessments of single clinical cases, both f and D*f maps were in satisfactory agreement with DCE maps in the extreme cases of an avascular mass and a highly vascularized mass, whereas, for tumors with slight vascularity or with a highly heterogeneous perfusion pattern, this association was not straightforward. Although IVIM DWI was demonstrated to be feasible in STT, our data did not support evident relationships between perfusion‐related IVIM parameters and perfusion measured by DCE MRI. Copyright © 2015 John Wiley & Sons, Ltd.     

Assessment of tumor necrotic fraction by dynamic contrast‐enhanced MRI: a preclinical study of human tumor xenografts with histopathologic correlation

Contrary to the common notion that tumor necrotic regions are non‐enhancing after contrast administration, recent evidence has shown that necrotic regions exhibit delayed and slow uptake of gadolinium tracer on dynamic contrast‐enhanced MRI (DCE MRI). The purpose of this study is to explore whether the mapping of tumor voxels with delayed and slow enhancement on DCE MRI can be used to derive estimates of tumor necrotic fraction. Patient‐derived tumor xenograft lines of seven human cancers were implanted in 26 mice which were subjected to DCE MRI performed using a spoiled gradient recalled sequence. Gadolinium tracer concentration was estimated using the variable flip angle technique. To identify tumor voxels exhibiting delayed and slow uptake of contrast medium, clustering analysis was performed using a k‐means clustering algorithm that classified tumor voxels according to their contrast enhancement patterns. Comparison of the percentage of tumor voxels exhibiting delayed and slow enhancement with the tumor necrotic fraction estimated on histology showed a strong correlation (r = 0.962, p < 0.001). The mapping of tumor regions with delayed and slow contrast uptake on DCE MRI correlated strongly with tumor necrotic fraction, and can potentially serve as a non‐invasive imaging surrogate for the in vivo assessment of necrotic fraction. Copyright © 2014 John Wiley & Sons, Ltd.     

Impact of contrast agent injection duration on dynamic contrast‐enhanced MRI quantification in prostate cancer

The volume transfer constant K^trans, which describes the leakage of contrast agent (CA) from vasculature into tissue, is the most commonly reported quantitative parameter for dynamic contrast‐enhanced (DCE‐) MRI. However, the variation in reported K^trans values between studies from different institutes is large. One of the primary sources of uncertainty is quantification of the arterial input function (AIF). The aim of this study is to determine the influence of the CA injection duration on the AIF and tracer kinetic analysis (TKA) parameters (i.e. K^trans, k_ep and v_e). Thirty‐one patients with prostate cancer received two DCE‐MRI examinations with an injection duration of 5 s in the first examination and a prolonged injection duration in the second examination, varying between 7.5 s and 30 s. The DCE examination was carried out on a 3.0 T MRI scanner using a transversal T₁‐weighted 3D spoiled gradient echo sequence (300 s duration, dynamic scan time of 2.5 s). Data of 29 of the 31 were further analysed. AIFs were determined from the phase signal in the left and right femoral arteries. K^trans, k_ep and v_e were estimated with the standard Tofts model for regions of healthy peripheral zone and tumour tissue. We observed a significantly smaller peak height and increased width in the AIF for injection durations of 15 s and longer. However, we did not find significant differences in K^trans, k_ep or v_e for the studied injection durations. The study demonstrates that the TKA parameters K^trans, k_ep and v_e, measured in the prostate, do not show a significant change as a function of injection duration.     

Towards higher sensitivity and stability of axon diameter estimation with diffusion‐weighted MRI

Diffusion‐weighted MRI is an important tool for in vivo and non‐invasive axon morphometry. The ActiveAx technique utilises an optimised acquisition protocol to infer orientationally invariant indices of axon diameter and density by fitting a model of white matter to the acquired data. In this study, we investigated the factors that influence the sensitivity to small‐diameter axons, namely the gradient strength of the acquisition protocol and the model fitting routine. Diffusion‐weighted ex. vivo images of the mouse brain were acquired using 16.4‐T MRI with high (G_max of 300 mT/m) and ultra‐high (G_max of 1350 mT/m) gradient strength acquisitions. The estimated axon diameter indices of the mid‐sagittal corpus callosum were validated using electron microscopy. In addition, a dictionary‐based fitting routine was employed and evaluated. Axon diameter indices were closer to electron microscopy measures when higher gradient strengths were employed. Despite the improvement, estimated axon diameter indices (a lower bound of ~ 1.8 μm) remained higher than the measurements obtained using electron microscopy (~1.2 μm). We further observed that limitations of pulsed gradient spin echo (PGSE) acquisition sequences and axonal dispersion could also influence the sensitivity with which axon diameter indices could be estimated. Our results highlight the influence of acquisition protocol, tissue model and model fitting, in addition to gradient strength, on advanced microstructural diffusion‐weighted imaging techniques. © 2016 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.     

Analysis of parametric histogram from dynamic contrast‐enhanced MRI: application in evaluating brain tumor response to radiotherapy

Dynamic contrast‐enhanced MRI (DCE MRI) has been used to study tumor response to treatment for many years. In this study, the modified full width at half‐maximum (mFWHM), calculated from the wash‐in slope histogram, is proposed as a parameter for the evaluation of changes in tumor heterogeneity which respond to radiotherapy. Twenty‐five patients with brain tumors were evaluated and divided into the nonresponder group (n = 11) and the responder group (n = 14) according to the Response Evaluation Criteria in Solid Tumors (RECIST). All selected tumors were evaluated by mFWHM ratios of post‐ to pre‐therapy (the ratio was defined as the therapeutic mFWHM ratio, TMR). The changes in kurtosis of the histograms and the averaged K^trans within a tumor were also calculated for comparison. The receiver operating characteristic analysis and Kaplan–Meier curves were used to examine the diagnosis ability. The TMR values were significantly higher in nonresponders than in responders (p < 0.001). When compared with the other two parameters, the proposed method also demonstrated better sensitivity and specificity. When adopting the TMR for the estimation of prognosis after therapy, there was a significant difference between the population survival curves. In conclusion, the derived mFWHM reflects tumor heterogeneity, and the ability to depict patient survival probability from TMR corresponds well with that from RECIST. The results reveal that, in brain tumors, progression may be exhibited not only by tumor size, but also by tumor heterogeneity. Copyright © 2012 John Wiley & Sons, Ltd.     

Texture‐based and diffusion‐weighted discrimination of parotid gland lesions on MR images at 3.0 Tesla

The purpose of this study was to evaluate whether texture‐based analysis of standard MRI sequences and diffusion‐weighted imaging can help in the discrimination of parotid gland masses. The MR images of 38 patients with a biopsy‐ or surgery‐proven parotid gland mass were retrospectively analyzed. All patients were examined on the same 3.0 Tesla MR unit, with one standard protocol. The ADC (apparent diffusion coefficient) values of the tumors were measured with three regions of interest (ROIs) covering the entire tumor. Texture‐based analysis was performed with the texture analysis software MaZda (version 4.7), with ROI measurements covering the entire tumor in three slices. COC (co‐occurrence matrix), RUN (run‐length matrix), GRA (gradient), ARM (auto‐regressive model), and WAV (wavelet transform) features were calculated for all ROIs. Three subsets of 10 texture features each were used for a linear discriminant analysis (LDA) in combination with k nearest neighbor classification (k‐NN). Using histology as a standard of reference, benign tumors, including subtypes, and malignant tumors were compared with regard to ADC and texture‐based values, with a one‐way analysis of variance with post‐hoc t‐tests. Significant differences were found in the mean ADC values between Warthin tumors and pleomorphic adenomas, as well as between Warthin tumors and benign lesions. Contrast‐enhanced T1‐weighted images contained the most relevant textural information for the discrimination between benign and malignant parotid masses, and also for the discrimination between pleomorphic adenomas and Warthin tumors. STIR images contained the least relevant texture features, particularly for the discrimination between pleomorphic adenomas and Warthin tumors. Texture analysis proved to differentiate benign from malignant lesions, as well as pleomorphic adenomas from Warthin tumors, based on standard T_1w sequences (without and with contrast). Of all benign parotid masses, Warthin tumors had significantly lower ADC values than the other entities. Copyright © 2013 John Wiley & Sons, Ltd.     

Three‐dimensional dynamic contrast‐enhanced MRI for the accurate,extensive quantification of microvascular permeability in atherosclerotic plaques

Atherosclerotic plaques that cause stroke and myocardial infarction are characterized by increased microvascular permeability and inflammation. Dynamic contrast‐enhanced MRI (DCE‐MRI) has been proposed as a method to quantify vessel wall microvascular permeability in vivo. Until now, most DCE‐MRI studies of atherosclerosis have been limited to two‐dimensional (2D) multi‐slice imaging. Although providing the high spatial resolution required to image the arterial vessel wall, these approaches do not allow the quantification of plaque permeability with extensive anatomical coverage, an essential feature when imaging heterogeneous diseases, such as atherosclerosis. To our knowledge, we present the first systematic evaluation of three‐dimensional (3D), high‐resolution, DCE‐MRI for the extensive quantification of plaque permeability along an entire vascular bed, with validation in atherosclerotic rabbits. We compare two acquisitions: 3D turbo field echo (TFE) with motion‐sensitized‐driven equilibrium (MSDE) preparation and 3D turbo spin echo (TSE). We find 3D TFE DCE‐MRI to be superior to 3D TSE DCE‐MRI in terms of temporal stability metrics. Both sequences show good intra‐ and inter‐observer reliability, and significant correlation with ex vivo permeability measurements by Evans Blue near‐infrared fluorescence (NIRF). In addition, we explore the feasibility of using compressed sensing to accelerate 3D DCE‐MRI of atherosclerosis, to improve its temporal resolution and therefore the accuracy of permeability quantification. Using retrospective under‐sampling and reconstructions, we show that compressed sensing alone may allow the acceleration of 3D DCE‐MRI by up to four‐fold. We anticipate that the development of high‐spatial‐resolution 3D DCE‐MRI with prospective compressed sensing acceleration may allow for the more accurate and extensive quantification of atherosclerotic plaque permeability along an entire vascular bed. We foresee that this approach may allow for the comprehensive and accurate evaluation of plaque permeability in patients, and may be a useful tool to assess the therapeutic response to approved and novel drugs for cardiovascular disease. Copyright © 2015 John Wiley & Sons, Ltd.     

Assessment of vessel permeability by combining dynamic contrast‐enhanced and arterial spin labeling MRI

The forward volumetric transfer constant (K^trans), a physiological parameter extracted from dynamic contrast‐enhanced (DCE) MRI, is weighted by vessel permeability and tissue blood flow. The permeability × surface area product per unit mass of tissue (PS) in brain tumors was estimated in this study by combining the blood flow obtained through pseudo‐continuous arterial spin labeling (PCASL) and K^trans obtained through DCE MRI. An analytical analysis and a numerical simulation were conducted to understand how errors in the flow and K^trans estimates would propagate to the resulting PS. Fourteen pediatric patients with brain tumors were scanned on a clinical 3‐T MRI scanner. PCASL perfusion imaging was performed using a three‐dimensional (3D) fast‐spin‐echo readout module to determine blood flow. DCE imaging was performed using a 3D spoiled gradient‐echo sequence, and the K^trans map was obtained with the extended Tofts model. The numerical analysis demonstrated that the uncertainty of PS was predominantly dependent on that of K^trans and was relatively insensitive to the flow. The average PS values of the whole tumors ranged from 0.006 to 0.217 min^?1, with a mean of 0.050 min^?1 among the patients. The mean K^trans value was 18% lower than the PS value, with a maximum discrepancy of 25%. When the parametric maps were compared on a voxel‐by‐voxel basis, the discrepancies between PS and K^trans appeared to be heterogeneous within the tumors. The PS values could be more than two‐fold higher than the K^trans values for voxels with high K^trans levels. This study proposes a method that is easy to implement in clinical practice and has the potential to improve the quantification of the microvascular properties of brain tumors. Copyright © 2015 John Wiley & Sons, Ltd.     

Treatment response monitoring in patients with gastrointestinal stromal tumor using diffusion‐weighted imaging: preliminary results in comparison with positron emission tomography/computed tomography

We compared the parameters derived from diffusion‐weighted imaging (DWI) and positron emission tomography/computed tomography (PET/CT) for treatment response evaluation and response prediction in patients with gastrointestinal stromal tumor (GIST). Seven patients with histologically proven metastatic disease were enrolled. DWI and PET/CT data were collected from all patients at diagnosis and from six at follow‐up. All 37 lesions were identifiable in DWI with a sensitivity of 100%. To achieve higher accuracy, we used the apparent diffusion coefficient (ADC) of liver and background noise as thresholds for the measurement of the ADCs of lesions. Significant inverse correlations were found between ADC_{mean_thr} (ADC_mean with thresholds) and SUV_mean (mean standardized uptake value) (R² = 0.523, p < 0.001 at diagnosis, and R² = 0.916, p < 0.001 at follow‐up), between ADC_{mean_thr} and SUV_max (maximum SUV) (R² = 0.529, p < 0.001 at diagnosis, and R² = 0.761, p < 0.001 at follow‐up), between ΔADC_{mean_thr} (percentage change in ADC_{mean_thr}) and ΔSUV_mean (percentage change in SUV_mean) (R² = 0.384, p < 0.001), and between ΔADC_{mean_thr} and ΔSUV_max (percentage change in SUV_max) (R² = 0.500, p < 0.001). In lesion‐based analysis, pre‐treatment ADC_{mean_thr} outperformed SUV_mean and SUV_max in treatment response prediction, with an area under the receiver operating characteristic curve of 0.706. These results show that DWI can provide a quantitative assessment comparable with PET/CT in GIST lesion characterization, treatment response evaluation and response prediction. Copyright © 2012 John Wiley & Sons, Ltd.     

Optimization of saturation‐recovery dynamic contrast‐enhanced MRI acquisition protocol: monte carlo simulation approach demonstrated with gadolinium MR renography

Dynamic contrast‐enhanced (DCE) MRI is widely used for the measurement of tissue perfusion and to assess organ function. MR renography, which is acquired using a DCE sequence, can measure renal perfusion, filtration and concentrating ability. Optimization of the DCE acquisition protocol is important for the minimization of the error propagation from the acquired signals to the estimated parameters, thus improving the precision of the parameters. Critical to the optimization of contrast‐enhanced T₁‐weighted protocols is the balance of the T₁‐shortening effect across the range of gadolinium (Gd) contrast concentration in the tissue of interest. In this study, we demonstrate a Monte Carlo simulation approach for the optimization of DCE MRI, in which a saturation‐recovery T₁‐weighted gradient echo sequence is simulated and the impact of injected dose (D) and time delay (TD, for saturation recovery) is tested. The results show that high D and/or high TD cause saturation of the peak arterial signals and lead to an overestimation of renal plasma flow (RPF) and glomerular filtration rate (GFR). However, the use of low TD (e.g. 100 ms) and low D leads to similar errors in RPF and GFR, because of the Rician bias in the pre‐contrast arterial signals. Our patient study including 22 human subjects compared TD values of 100 and 300 ms after the injection of 4 mL of Gd contrast for MR renography. At TD = 100 ms, we computed an RPF value of 157.2 ± 51.7 mL/min and a GFR of 33.3 ± 11.6 mL/min. These results were all significantly higher than the parameter estimates at TD = 300 ms: RPF = 143.4 ± 48.8 mL/min (p = 0.0006) and GFR = 30.2 ± 11.5 mL/min (p = 0.0015). In conclusion, appropriate optimization of the DCE MRI protocol using simulation can effectively improve the precision and, potentially, the accuracy of the measured parameters. Copyright © 2016 John Wiley & Sons, Ltd.     

Comparison of different MRI sequences in lesion detection and early response evaluation of diffuse large B‐cell lymphoma – a whole‐body MRI and diffusion‐weighted imaging study

To compare different MRI sequences for the detection of lesions and the evaluation of response to chemotherapy in patients with diffuse large B‐cell lymphoma (DLBCL), 18 patients with histology‐confirmed DLBCL underwent 3‐T MRI scanning prior to and 1 week after chemotherapy. The MRI sequences included T₁‐weighted pre‐ and post‐contrast, T₂‐weighted with and without fat suppression, and a single‐shot echo‐planar diffusion‐weighted imaging (DWI) with two b values (0 and 800 s/mm²). Conventional MRI sequence comparisons were performed using the contrast ratio between tumor and normal vertebral body instead of signal intensity. The apparent diffusion coefficient (ADC) of the tumor was measured directly on the parametric ADC map. The tumor volume was used as a reference for the evaluation of chemotherapy response. The mean tumor volume was 374 mL at baseline, and decreased by 65% 1 week after chemotherapy (p < 0.01). The T₂‐weighted image with fat suppression showed a significantly higher contrast ratio compared with images from all other conventional MRI sequences, both before and after treatment (p < 0.01, respectively). The contrast ratio of the T₂‐weighted image with fat suppression decreased significantly (p < 0.01), and that of the T₁‐weighted pre‐contrast image increased significantly (p < 0.01), after treatment. However, there was no correlation between the change in contrast ratio and tumor volume. The mean ADC value was 0.68 × 10^–3 mm²/s at baseline; it increased by 89% after chemotherapy (p < 0.001), and the change in ADC value correlated with the change in tumor volume (r = 0.66, p < 0.01). The baseline ADC value also correlated inversely with the percentage change in ADC after treatment (r = ?0.62, p < 0.01). In conclusion, this study indicates that T₂‐weighted imaging with fat suppression is the best conventional sequence for the detection of lesions and evaluation of the efficacy of chemotherapy in DLBCL. DWI with ADC mapping is an imaging modality with both diagnostic and prognostic value that could complement conventional MRI. Copyright © 2013 John Wiley & Sons, Ltd.     

Interrelations of muscle functional MRI,diffusion‐weighted MRI and 31P‐MRS in exercised lower back muscles

Exercise‐induced changes of transverse proton relaxation time (T₂), tissue perfusion and metabolic turnover were investigated in the lower back muscles of volunteers by applying muscle functional MRI (mfMRI) and diffusion‐weighted imaging (DWI) before and after as well as dynamic ³¹P‐MRS during the exercise. Inner (M. multifidus, MF) and outer lower back muscles (M. erector spinae, ES) were examined in 14 healthy young men performing a sustained isometric trunk‐extension. Significant phosphocreatine (PCr) depletions ranging from 30% (ES) to 34% (MF) and Pi accumulations between 95% (left ES) and 120%–140% (MF muscles and right ES) were observed during the exercise, which were accompanied by significantly decreased pH values in all muscles (?pH ≈ –0.05). Baseline T₂ values were similar across all investigated muscles (approximately 27 ms at 3 T), but revealed right–left asymmetric increases (T₂,_inc) after the exercise (right ES/MF: T₂,_inc = 11.8/9.7%; left ES/MF: T₂,_inc = 4.6/8.9%). Analyzed muscles also showed load‐induced increases in molecular diffusion D (p = .007) and perfusion fraction f (p = .002). The latter parameter was significantly higher in the MF than in the ES muscles both at rest and post exercise. Changes in PCr (p = .03), diffusion (p < .01) and perfusion (p = .03) were strongly associated with T_2,inc, and linear mixed model analysis revealed that changes in PCr and perfusion both affect T_2,inc (p < .001). These findings support previous assumptions that T₂ changes are not only an intra‐cellular phenomenon resulting from metabolic stress but are also affected by increased perfusion in loaded muscles. Copyright © 2014 John Wiley & Sons, Ltd.     

Dynamic contrast‐enhanced MRI model selection for predicting tumor aggressiveness in papillary thyroid cancers

The purpose of this study was to identify the optimal tracer kinetic model from T₁‐weighted dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) data and evaluate whether parameters estimated from the optimal model predict tumor aggressiveness determined from histopathology in patients with papillary thyroid carcinoma (PTC) prior to surgery. In this prospective study, 18 PTC patients underwent pretreatment DCE‐MRI on a 3 T MR scanner prior to thyroidectomy. This study was approved by the institutional review board and informed consent was obtained from all patients. The two‐compartment exchange model, compartmental tissue uptake model, extended Tofts model (ETM) and standard Tofts model were compared on a voxel‐wise basis to determine the optimal model using the corrected Akaike information criterion (AICc) for PTC. The optimal model is the one with the lowest AICc. Statistical analysis included paired and unpaired t‐tests and a one‐way analysis of variance. Bonferroni correction was applied for multiple comparisons. Receiver operating characteristic (ROC) curves were generated from the optimal model parameters to differentiate PTC with and without aggressive features, and AUCs were compared. ETM performed best with the lowest AICc and the highest Akaike weight (0.44) among the four models. ETM was preferred in 44% of all 3419 voxels. The ETM estimates of K^trans in PTCs with the aggressive feature extrathyroidal extension (ETE) were significantly higher than those without ETE (0.78 ± 0.29 vs. 0.34 ± 0.18 min^?1, P = 0.005). From ROC analysis, cut‐off values of K^trans, v_e and v_p, which discriminated between PTCs with and without ETE, were determined at 0.45 min^?1, 0.28 and 0.014 respectively. The sensitivities and specificities were 86 and 82% (K^trans), 71 and 82% (v_e), and 86 and 55% (v_p), respectively. Their respective AUCs were 0.90, 0.71 and 0.71. We conclude that ETM K^trans has shown potential to classify tumors with and without aggressive ETE in patients with PTC.     

Blood–spinal cord barrier permeability in experimental spinal cord injury: dynamic contrast‐enhanced MRI

After a primary traumatic injury, spinal cord tissue undergoes a series of pathobiological changes, including compromised blood–spinal cord barrier (BSCB) integrity. These vascular changes occur over both time and space. In an experimental model of spinal cord injury (SCI), longitudinal dynamic contrast‐enhanced MRI (DCE‐MRI) studies were performed up to 56 days after SCI to quantify spatial and temporal changes in the BSCB permeability in tissue that did not show any visible enhancement on the post‐contrast MRI (non‐enhancing tissue). DCE‐MRI data were analyzed using a two‐compartment pharmacokinetic model. These studies demonstrate gradual restoration of BSCB with post‐SCI time. However, on the basis of DCE‐MRI, and confirmed by immunohistochemistry, the BSCB remained compromised even at 56 days after SCI. In addition, open‐field locomotion was evaluated using the 21‐point Basso–Beattie–Bresnahan scale. A significant correlation between decreased BSCB permeability and improved locomotor recovery was observed. Copyright © 2008 John Wiley & Sons, Ltd.     

DCE‐MRI prediction of survival time for patients with glioblastoma multiforme: using an adaptive neuro‐fuzzy‐based model and nested model selection technique

This pilot study investigates the construction of an Adaptive Neuro‐Fuzzy Inference System (ANFIS) for the prediction of the survival time of patients with glioblastoma multiforme (GBM). ANFIS is trained by the pharmacokinetic (PK) parameters estimated by the model selection (MS) technique in dynamic contrast enhanced‐magnetic resonance imaging (DCE‐MRI) data analysis, and patient age. DCE‐MRI investigations of 33 treatment‐naïve patients with GBM were studied. Using the modified Tofts model and MS technique, the following physiologically nested models were constructed: Model 1, no vascular leakage (normal tissue); Model 2, leakage without efflux; Model 3, leakage with bidirectional exchange (influx and efflux). For each patient, the PK parameters of the three models were estimated as follows: blood plasma volume (v_p) for Model 1; v_p and volume transfer constant (K^trans) for Model 2; v_p, K^trans and rate constant (k_ep) for Model 3. Using Cox regression analysis, the best combination of the estimated PK parameters, together with patient age, was identified for the design and training of ANFIS. A K‐fold cross‐validation (K = 33) technique was employed for training, testing and optimization of ANFIS. Given the survival time distribution, three classes of survival were determined and a confusion matrix for the correct classification fraction (CCF) of the trained ANFIS was estimated as an accuracy index of ANFIS's performance. Patient age, k_ep and v_e (K^trans/k_ep) of Model 3, and K^trans of Model 2, were found to be the most effective parameters for training ANFIS. The CCF of the trained ANFIS was 84.8%. High diagonal elements of the confusion matrix (81.8%, 90.1% and 81.8% for Class 1, Class 2 and Class 3, respectively), with low off‐diagonal elements, strongly confirmed the robustness and high performance of the trained ANFIS for predicting the three survival classes. This study confirms that DCE‐MRI PK analysis, combined with the MS technique and ANFIS, allows the construction of a DCE‐MRI‐based fuzzy integrated predictor for the prediction of the survival of patients with GBM.     

Characterization and stratification of prostate lesions based on comprehensive multiparametric MRI using detailed whole‐mount histopathology as a reference standard

The purpose of this study was to characterize prostate cancer (PCa) based on multiparametric MR (mpMR) measures derived from MRI, diffusion, spectroscopy, and dynamic contrast‐enhanced (DCE) MRI, and to validate mpMRI in detecting PCa and predicting PCa aggressiveness by correlating mpMRI findings with whole‐mount histopathology. Seventy‐eight men with untreated PCa received 3 T mpMR scans prior to radical prostatectomy. Cancerous regions were outlined, graded, and cancer amount estimated on whole‐mount histology. Regions of interest were manually drawn on T₂‐weighted images based on histopathology. Logistic regression was used to identify optimal combinations of parameters for the peripheral zone and transition zone to separate: (i) benign from malignant tissues; (ii) Gleason score (GS) ≤3 + 3 disease from ≥GS3 + 4; and (iii) ≤ GS3 + 4 from ≥GS4 + 3 cancers. The performance of the models was assessed using repeated fourfold cross‐validation. Additionally, the performance of the logistic regression models created under the assumption that one or more modality has not been acquired was evaluated. Logistic regression models yielded areas under the curve (AUCs) of 1.0 and 0.99 when separating benign from malignant tissues in the peripheral zone and the transition zone, respectively. Within the peripheral zone, combining choline, maximal enhancement slope, apparent diffusion coefficient (ADC), and citrate measures for separating ≤GS3 + 3 from ≥GS3 + 4 PCa yielded AUC = 0.84. Combining creatine, choline, and washout slope yielded AUC = 0.81 for discriminating ≤GS3 + 4 from ≥GS4 + 3 disease. Within the transition zone, combining washout slope, ADC, and creatine yielded AUC = 0.93 for discriminating ≤GS3 + 3 and ≥GS3 + 4 cancers. When separating ≤GS3 + 4 from ≥GS4 + 3 PCa, combining choline and washout slope yielded AUC = 0.92. MpMRI provides excellent separation between benign tissues and PCa, and across PCa tissues of different aggressiveness. The final models prominently feature spectroscopy and DCE‐derived metrics, underlining their value within a comprehensive mpMRI examination.     

Cluster analysis of DCE‐MRI data identifies regional tracer‐kinetic changes after tumor treatment with high intensity focused ultrasound

Evaluation of high intensity focused ultrasound (HIFU) treatment with MRI is generally based on assessment of the non‐perfused volume from contrast‐enhanced T₁‐weighted images. However, the vascular status of tissue surrounding the non‐perfused volume has not been extensively investigated with MRI. In this study, cluster analysis of the transfer constant K^trans and extravascular extracellular volume fraction v_e, derived from dynamic contrast‐enhanced MRI (DCE‐MRI) data, was performed in tumor tissue surrounding the non‐perfused volume to identify tumor subregions with distinct contrast agent uptake kinetics. DCE‐MRI was performed in CT26.WT colon carcinoma‐bearing BALB/c mice before (n = 12), directly after (n = 12) and 3 days after (n = 6) partial tumor treatment with HIFU. In addition, a non‐treated control group (n = 6) was included. The non‐perfused volume was identified based on the level of contrast enhancement. Quantitative comparison between non‐perfused tumor fractions and non‐viable tumor fractions derived from NADH‐diaphorase histology showed a stronger agreement between these fractions 3 days after treatment (R² to line of identity = 0.91) compared with directly after treatment (R² = 0.74). Next, k‐means clustering with four clusters was applied to K^trans and v_e parameter values of all significantly enhanced pixels. The fraction of pixels within two clusters, characterized by a low K^trans and either a low or high v_e, significantly increased after HIFU. Changes in composition of these clusters were considered to be HIFU induced. Qualitative H&E histology showed that HIFU‐induced alterations in these clusters may be associated with hemorrhage and structural tissue disruption. Combined microvasculature and hypoxia staining suggested that these tissue changes may affect blood vessel functionality and thereby tumor oxygenation. In conclusion, it was demonstrated that, in addition to assessment of the non‐perfused tumor volume, the presented methodology gives further insight into HIFU‐induced effects on tumor vascular status. This method may aid in assessment of the consequences of vascular alterations for the fate of the tissue. Copyright © 2015 John Wiley & Sons, Ltd.     

High‐temporospatial‐resolution dynamic contrast‐enhanced (DCE) wrist MRI with variable‐density pseudo‐random circular Cartesian undersampling (CIRCUS) acquisition: evaluation of perfusion in rheumatoid arthritis patients

This study is to evaluate highly accelerated three‐dimensional (3D) dynamic contrast‐enhanced (DCE) wrist MRI for assessment of perfusion in rheumatoid arthritis (RA) patients. A pseudo‐random variable‐density undersampling strategy, circular Cartesian undersampling (CIRCUS), was combined with k–t SPARSE‐SENSE reconstruction to achieve a highly accelerated 3D DCE wrist MRI. Two healthy volunteers and 10 RA patients were studied. Two patients were on methotrexate (MTX) only (Group I) and the other eight were treated with a combination therapy of MTX and anti‐tumor necrosis factor (TNF) therapy (Group II). Patients were scanned at baseline and 3 month follow‐up. DCE MR images were used to evaluate perfusion in synovitis and bone marrow edema pattern in the RA wrist joints. A series of perfusion parameters was derived and compared with clinical disease activity scores of 28 joints (DAS28). 3D DCE wrist MR images were obtained with a spatial resolution of 0.3 × 0.3 × 1.5 mm³ and temporal resolution of 5 s (with an acceleration factor of 20). The derived perfusion parameters, most notably transition time (dT) of synovitis, showed significant negative correlations with DAS28‐ESR (r = ?0.80, p < 0.05) and DAS28‐CRP (r = ?0.87, p < 0.05) at baseline and also correlated significantly with treatment responses evaluated by clinical score changes between baseline and 3 month follow‐up (with DAS28‐ESR r = ?0.79, p < 0.05, and DAS28‐CRP r = ?0.82, p < 0.05). Highly accelerated 3D DCE wrist MRI with improved temporospatial resolution has been achieved in RA patients and provides accurate assessment of neovascularization and perfusion in RA joints, showing promise as a potential tool for evaluating treatment responses. Copyright © 2015 John Wiley & Sons, Ltd.     

Assessment of early docetaxel response in an experimental model of human breast cancer using DCE‐MRI,ex vivo HR MAS,and in vivo 1H MRS

The purpose of this study was to evaluate the use of dynamic contrast‐enhanced (DCE) MRI, in vivo ¹H MRS and ex vivo high resolution magic angle spinning (HR MAS) MRS of tissue samples as methods to detect early treatment effects of docetaxel in a breast cancer xenograft model (MCF‐7) in mice. MCF‐7 cells were implanted subcutaneously in athymic mice and treated with docetaxel (20, 30, and 40 mg/kg) or saline six weeks later. DCE‐MRI and in vivo ¹H MRS were performed on a 7 T MR system three days after treatment. The dynamic images were used as input for a two‐compartment model, yielding the vascular parameters K^trans and v_e. HR MAS MRS, histology, and immunohistochemical staining for proliferation (Ki‐67), apoptosis (M30 cytodeath), and vascular/endothelial cells (CD31) were performed on excised tumor tissue. Both in vivo spectra and HR MAS spectra were used as input for multivariate analysis (principal component analysis (PCA) and partial least squares regression analysis (PLS)) to compare controls to treated tumors. Tumor growth was suppressed in docetaxel‐treated mice compared to the controls. The anti‐tumor effect led to an increase in K^trans and v_e values in all the treated groups. Furthermore, in vivo MRS and HR MAS MRS revealed a significant decrease in choline metabolite levels for the treated groups, in accordance with reduced proliferative index as seen on Ki‐67 stained sections. In this study DCE‐MRI, in vivo MRS and ex vivo HR MAS MRS have been used to demonstrate that docetaxel treatment of a human breast cancer xenograft model results in changes in the vascular dynamics and metabolic profile of the tumors. This indicates that these MR methods could be used to monitor intra‐tumoral treatment effects. Copyright © 2009 John Wiley & Sons, Ltd.