Multi‐centre reproducibility of diffusion MRI parameters for clinical sequences in the brain

The purpose of this work was to assess the reproducibility of diffusion imaging, and in particular the apparent diffusion coefficient (ADC), intra‐voxel incoherent motion (IVIM) parameters and diffusion tensor imaging (DTI) parameters, across multiple centres using clinically available protocols with limited harmonization between sequences. An ice–water phantom and nine healthy volunteers were scanned across fives centres on eight scanners (four Siemens 1.5T, four Philips 3T). The mean ADC, IVIM parameters (diffusion coefficient D and perfusion fraction f) and DTI parameters (mean diffusivity MD and fractional anisotropy FA), were measured in grey matter, white matter and specific brain sub‐regions. A mixed effect model was used to measure the intra‐ and inter‐scanner coefficient of variation (CV) for each of the five parameters. ADC, D, MD and FA had a good intra‐ and inter‐scanner reproducibility in both grey and white matter, with a CV ranging between 1% and 7.4%; mean 2.6%. Other brain regions also showed high levels of reproducibility except for small structures such as the choroid plexus. The IVIM parameter f had a higher intra‐scanner CV of 8.4% and inter‐scanner CV of 24.8%. No major difference in the inter‐scanner CV for ADC, D, MD and FA was observed when analysing the 1.5T and 3T scanners separately. ADC, D, MD and FA all showed good intra‐scanner reproducibility, with the inter‐scanner reproducibility being comparable or faring slightly worse, suggesting that using data from multiple scanners does not have an adverse effect compared with using data from the same scanner. The IVIM parameter f had a poorer inter‐scanner CV when scanners of different field strengths were combined, and the parameter was also affected by the scan acquisition resolution. This study shows that the majority of diffusion MRI derived parameters are robust across 1.5T and 3T scanners and suitable for use in multi‐centre clinical studies and trials. © 2015 The Authors NMR in Biomedicine Published by John Wiley & Sons Ltd.     

Stroke assessment with intravoxel incoherent motion diffusion‐weighted MRI

Intravoxel incoherent motion (IVIM) diffusion‐weighted MRI can simultaneously measure diffusion and perfusion characteristics in a non‐invasive way. This study aimed to determine the potential utility of IVIM in characterizing brain diffusion and perfusion properties for clinical stroke. The multi‐b‐value diffusion‐weighted images of 101 patients diagnosed with acute/subacute ischemic stroke were retrospectively evaluated. The diffusion coefficient D, representing the water apparent diffusivity, was obtained by fitting the diffusion data with increasing high b‐values to a simple mono‐exponential model. The IVIM‐derived perfusion parameters, pseudodiffusion coefficient D*, vascular volume fraction f and blood flow‐related parameter fD*, were calculated with the bi‐exponential model. Additionally, the apparent diffusion coefficient (ADC) was fitted according to the mono‐exponential model using all b‐values. The diffusion parameters for the ischemic lesion and normal contralateral region were measured in each patient. Statistical analysis was performed using the paired Student t‐test and Pearson correlation test. Diffusion data in both the ischemic lesion and normal contralateral region followed the IVIM bi‐exponential behavior, and the IVIM model showed better goodness of fit than the mono‐exponential model with lower Akaike information criterion values. The paired Student t‐test revealed significant differences for all diffusion parameters (all P < 0.001) except D* (P = 0.218) between ischemic and normal areas. For all patients in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001) and f (r = 0.541, P < 0.001; r = 0.262, P = 0.008); significant correlation was also found between ADC and fD* in the ischemic region (r = 0.254, P = 0.010). For all pixels within the region of interest from a representative subject in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001), f (r = 0.823, P < 0.001; r = 0.652, P < 0.001) and fD* (r = 0.294, P < 0.001; r = 0.340, P < 0.001). These findings may have clinical implications for the use of IVIM imaging in the assessment and management of acute/subacute stroke patients. Copyright © 2016 John Wiley & Sons, Ltd.     

Intravoxel incoherent motion imaging kinetics during chemoradiotherapy for human papillomavirus‐associated squamous cell carcinoma of the oropharynx: preliminary results from a prospective pilot study

This study aims to identify the temporal kinetics of intravoxel incoherent motion (IVIM) MRI in patients with human papillomavirus‐associated (HPV+) oropharyngeal squamous cell carcinoma. Patients were enrolled under an Institutional Review Board (IRB)‐approved protocol as part of an ongoing prospective clinical trial. All patients underwent two MRI studies: a baseline scan before chemoradiotherapy and a mid‐treatment scan 3–4 weeks after treatment initiation. Parametric maps representing pure diffusion coefficient (D), pseudo‐diffusion coefficient (D*), perfusion fraction (f) and apparent diffusion coefficient (ADC) were generated. The Mann–Whitney U‐test was used to assess the temporal variation of IVIM metrics. Bayesian quadratic discriminant analysis (QDA) was used to evaluate the extent to which mid‐treatment changes in IVIM metrics could be combined to predict sites that would achieve complete response (CR) in multivariate analysis. Thirty‐one patients were included in the final analysis with 59 lesions. Pretreatment ADC and D values of the CR lesions (n = 19) were significantly lower than those of non‐CR lesions (n = 33). Mid‐treatment ADC, D and f values were significantly higher (p < 0.0001) than pretreatment values for all lesions. Each increase in normalized ΔADC of size 0.1 yielded a 1.45‐fold increase in the odds of CR (p < 0.0003), each increase in normalized ΔD of size 0.1 yielded a 1.53‐fold increase in the odds of CR (p < 0.0002), and each unit increase in Δf yielded a 2.29‐fold increase in the odds of CR (p < 0.02). Combined ΔD and ΔADC were integrated into a multivariate prediction model and attained an AUC of 0.87 (95% confidence interval: 0.79, 0.96), as well as a sensitivity of 0.63, specificity of 0.85 and accuracy of 0.78, under leave‐one‐out cross‐validation. In conclusion, IVIM is feasible and potentially useful in the prediction and assessment of the early response of HPV+ oropharyngeal squamous cell carcinoma to chemoradiotherapy. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Differentiating the histologic grades of gliomas preoperatively using amide proton transfer‐weighted (APTW) and intravoxel incoherent motion MRI

The purpose of this work was to investigate the diagnostic performance of amide proton transfer‐weighted (APTW) and intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in the preoperative grading of gliomas. Fifty‐one patients with suspected gliomas were recruited and underwent a preoperative MRI examination that included APTW and IVIM sequences. All cases were confirmed by postsurgical histopathology. APTW signal intensity, true diffusion coefficient (D), perfusion fraction (f) and pseudo‐diffusion coefficient (D*) were applied to assess the solid tumor component and contralateral normal‐appearing white matter. The relative APTW signal intensity (rAPTW) was also used. Independent‐sample and paired‐sample t‐tests were used to compare differences in MRI parameters between low‐grade glioma (LGG) and high‐grade glioma (HGG) groups. The diagnostic performance was assessed with the receiver operating characteristic curve. Twenty‐six patients were pathologically diagnosed with LGG and 25 were diagnosed with HGG. APTW, rAPTW and f values were significantly higher (all p < 0.001), whereas D values were significantly lower (p < 0.001) in the HGG group than in the LGG group. There was no significant difference between D* values for the two groups. rAPTW had an area under the curve (AUC) of 0.957, with a sensitivity of 100% and a specificity of 84.6%, followed by APTW, f, D and D*. The combined use of APTW and IVIM showed the best diagnostic performance, with an AUC of 0.986. In conclusion, APTW and IVIM, as two promising supplementary sequences for routine MRI, could be valuable in differentiating LGGs from HGGs.     

Triggered intravoxel incoherent motion MRI for the assessment of calf muscle perfusion during isometric intermittent exercise

The main aim of this paper was to propose triggered intravoxel incoherent motion (IVIM) imaging sequences for the evaluation of perfusion changes in calf muscles before, during and after isometric intermittent exercise. Twelve healthy volunteers were involved in the study. The subjects were asked to perform intermittent isometric plantar flexions inside the MRI bore. MRI of the calf muscles was performed on a 3.0 T scanner and diffusion‐weighted (DW) images were obtained using eight different b values (0 to 500 s/mm²). Acquisitions were performed at rest, during exercise and in the subsequent recovery phase. A motion‐triggered echo‐planar imaging DW sequence was implemented to avoid movement artifacts. Image quality was evaluated using the average edge strength (AES) as a quantitative metric to assess the motion artifact effect. IVIM parameters (diffusion D, perfusion fraction f and pseudo‐diffusion D*) were estimated using a segmented fitting approach and evaluated in gastrocnemius and soleus muscles. No differences were observed in quality of IVIM images between resting state and triggered exercise, whereas the non‐triggered images acquired during exercise had a significantly lower value of AES (reduction of more than 20%). The isometric intermittent plantar‐flexion exercise induced an increase of all IVIM parameters (D by 10%; f by 90%; D* by 124%; fD* by 260%), in agreement with the increased muscle perfusion occurring during exercise. Finally, IVIM parameters reverted to the resting values within 3 min during the recovery phase. In conclusion, the IVIM approach, if properly adapted using motion‐triggered sequences, seems to be a promising method to investigate muscle perfusion during isometric exercise.     

Correlative assessment of tumor microcirculation using contrast‐enhanced perfusion MRI and intravoxel incoherent motion diffusion‐weighted MRI: is there a link between them?

The purpose of this study was to correlate intravoxel incoherent motion (IVIM) imaging with classical perfusion‐weighted MRI metrics in human gliomas. Parametric images for slow diffusion coefficient (D), fast diffusion coefficient (D*), and fractional perfusion‐related volume (f) in patients with high‐grade gliomas were generated. Maps of F_p (plasma flow), v_p (vascular plasma volume), PS (permeability surface–area product), v_e (extravascular, extracellular volume), E (extraction ratio), k_e (influx ratio into the interstitium), and t_c (vascular transit time) from dynamic contrast‐enhanced (DCE) and dynamic susceptibility contrast‐enhanced (DSC) MRI were also generated. A region‐of‐interest analysis on the contralateral healthy white matter and on the tumor areas was performed and the extracted parameter values were tested for any significant differences among tumor grades or any correlations. Only f could be significantly correlated to DSC‐derived v_p and t_c in healthy brain tissue. Concerning the tumor regions, F_p was significantly positively correlated with D* and inversely correlated with f in DSC measurements. The D*, f, and f × D* values in the WHO grade III gliomas were non‐significantly different from those in the grade IV gliomas. There was a trend to significant negative correlations between f and PS as well as between f × D* and k_e in DCE experiments. Presumably due to different theoretical background, tracer properties and modeling of the tumor vasculature in the IVIM theory, there is no clearly evident link between D*, f and DSC‐ and DCE‐derived metrics. Copyright © 2014 John Wiley & Sons, Ltd.     

Interstitial fluid pressure correlates with intravoxel incoherent motion imaging metrics in a mouse mammary carcinoma model

The effective delivery of a therapeutic drug to the core of a tumor is often impeded by physiological barriers, such as the interstitial fluid pressure (IFP). There are a number of therapies that can decrease IFP and induce tumor vascular normalization. However, a lack of a noninvasive means to measure IFP hinders the utilization of such a window of opportunity for the maximization of the treatment response. Thus, the purpose of this study was to investigate the feasibility of using intravoxel incoherent motion (IVIM) diffusion parameters as noninvasive imaging biomarkers for IFP. Mice bearing the 4T1 mammary carcinoma model were studied using diffusion‐weighted imaging (DWI), immediately followed by wick‐in‐needle IFP measurement. Voxelwise analysis was conducted with a conventional monoexponential diffusion model, as well as a biexponential model taking IVIM into account. There was no significant correlation of IFP with either the median apparent diffusion coefficient from the monoexponential model (r = 0.11, p = 0.78) or the median tissue diffusivity from the biexponential model (r = 0.30, p = 0.44). However, IFP was correlated with the median pseudo‐diffusivity (D_p) of apparent vascular voxels (r = 0.76, p = 0.02) and with the median product of the perfusion fraction and pseudo‐diffusivity (f_pD_p) of apparent vascular voxels (r = 0.77, p = 0.02). Although the effect of IVIM in tumors has been reported previously, to our knowledge, this study represents the first direct comparison of IVIM metrics with IFP, with the results supporting the feasibility of the use of IVIM DWI metrics as noninvasive biomarkers for tumor IFP. Copyright © 2011 John Wiley & Sons, Ltd.     

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T

Artificial neural networks (ANNs) were used for voxel‐wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was compared with conventional least‐squares regression (LSR) and state‐of‐the‐art multi‐step fitting (LSR‐MS) in Monte‐Carlo simulations and in vivo in terms of estimation accuracy and precision, number of outliers and sensitivity in the distinction between grey (GM) and white (WM) matter. Both the proposed ANN approach and LSR‐MS yielded visually increased parameter map quality. Estimations of all parameters (perfusion fraction f, diffusion coefficient D, pseudo‐diffusion coefficient D*, kurtosis K) were in good agreement with the literature using ANN, whereas LSR‐MS resulted in D* overestimation and LSR yielded increased values for f and D*, as well as decreased values for K. Using ANN, outliers were reduced for the parameters f (ANN, 1%; LSR‐MS, 19%; LSR, 8%), D* (ANN, 21%; LSR‐MS, 25%; LSR, 23%) and K (ANN, 0%; LSR‐MS, 0%; LSR, 15%). Moreover, ANN enabled significant distinction between GM and WM based on all parameters, whereas LSR facilitated this distinction only based on D and LSR‐MS on f, D and K. Overall, the proposed ANN approach was found to be superior to conventional LSR, posing a powerful alternative to the state‐of‐the‐art method LSR‐MS with several advantages in the estimation of IVIM–kurtosis parameters, which might facilitate increased applicability of enhanced diffusion models at clinical scan times.     

Correlation of Choline/Creatine and Apparent Diffusion Coefficient values with the prognostic parameters of Head and Neck Squamous Cell Carcinoma

The aim of this study was to measure choline/creatine (Ch/Cr) levels through ¹H‐MRS and apparent diffusion coefficient (ADC) values through diffusion‐weighted MRI, and to correlate these values with the prognostic parameters of head and neck squamous cell carcinoma (HNSCC). The institutional review board approved this study and informed written consent was obtained from all study participants. A prospective study of 43 patients (31 men and 12 women; mean age, 65 years) with HNSCC was conducted. Single‐voxel ¹H‐MRS was performed at the tumor or metastatic cervical lymph node with point‐resolved spectroscopy (PRESS) at TE = 135 ms. Diffusion‐weighted MR images with b values of 0, 500 and 1000 s/mm² and contrast MRI of the head and neck were performed. The Ch/Cr levels and ADC values of HNSCC were calculated. The gross tumor volume (GTV) was also calculated. The degree of tumor differentiation was determined through pathological examination. The HNSCC Ch/Cr level was negatively correlated with the ADC value (r = ?0.662, p = 0.001). There was a significant difference in the Ch/Cr and ADC values at different degrees of tumor differentiation (p = 0.003 and p = 0.001) and with different GTVs (p = 0.122 and p = 0.001). The following prognostic parameter categories were used: (i) poorly differentiated and undifferentiated versus well differentiated to moderately differentiated; and (ii) HNSCC with GTV < 30 cm³ versus GTV > 30 cm³. The cut‐off values for Cho/Cr and ADC for each category were 1.83, 0.95 and 1.94, 0.99, respectively, and the areas under the curve were 0.771, 0.967 and 0.726, 0.795, respectively, for each category. We conclude that the Ch/Cr levels determined using ¹H‐MRS and the ADC values are well correlated with several prognostic parameters of HNSCC. Copyright © 2016 John Wiley & Sons, Ltd.     

Reliable estimation of brain intravoxel incoherent motion parameters using denoised diffusion‐weighted MRI

In this study, we evaluate whether diffusion‐weighted magnetic resonance imaging (DW‐MRI) data after denoising can provide a reliable estimation of brain intravoxel incoherent motion (IVIM) perfusion parameters. Brain DW‐MRI was performed in five healthy volunteers on a 3 T clinical scanner with 12 different b‐values ranging from 0 to 1000 s/mm². DW‐MRI data denoised using the proposed method were fitted with a biexponential model to extract perfusion fraction (PF), diffusion coefficient (D) and pseudo‐diffusion coefficient (D*). To further evaluate the accuracy and precision of parameter estimation, IVIM parametric images obtained from one volunteer were used to resimulate the DW‐MRI data using the biexponential model with the same b‐values. Rician noise was added to generate DW‐MRI data with various signal‐to‐noise ratio (SNR) levels. The experimental results showed that the denoised DW‐MRI data yielded precise estimates for all IVIM parameters. We also found that IVIM parameters were significantly different between gray matter and white matter (P < 0.05), except for D* (P = 0.6). Our simulation results show that the proposed image denoising method displays good performance in estimating IVIM parameters (both bias and coefficient of variation were <12% for PF, D and D*) in the presence of different levels of simulated Rician noise (SNR_b=0 = 20‐40). Simulations and experiments show that brain DW‐MRI data after denoising can provide a reliable estimation of IVIM parameters.     

Invasive ductal carcinoma: correlation of apparent diffusion coefficient value with pathological prognostic factors

The aim of this study was to correlate the apparent diffusion coefficient (ADC) value of invasive ductal carcinoma with pathological prognostic factors. A prospective study was conducted on 59 untreated female patients (mean age 46 years) with invasive ductal carcinoma. All patients were examined at 1.5 Tesla using dedicated bilateral breast coil. They underwent diffusion weighted MR imaging of the breast using a single shot echo planar imaging with a b‐factor of 200 and 400 sec/mm2. Apparent diffusion coefficient (ADC) maps were reconstructed. The ADC value of the breast cancer was calculated and correlated with the pathologic prognostic factors (tumor size, grade and lymph nodes). The mean ADC values of invasive ductal carcinoma were significantly lower in patients with high grade, large breast cancer as well as those with axillary lymph nodes metastasis in a statistically significant way (p = 0.001 for the three factors). The mean ADC value of invasive ductal carcinoma was correlated with histologic grade (r = ?0.675, p = 0.001), tumor size (r = 0.504, p = 0.001) and showed lower ADC values with positive lymph node metastasis. Apparent diffusion coefficient value is correlated with pathological parameters of invasive ductal carcinoma. The lower ADC values are associated with higher histological grade, larger tumor size and presence of axillary lymph nodes. So, the ADC value can be considered as a promising prognostic parameter that may identify highly aggressive breast cancer. Copyright © 2010 John Wiley & Sons, Ltd.     

An intravoxel oriented flow model for diffusion‐weighted imaging of the kidney

By combining intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI) we introduce a new diffusion model called intravoxel oriented flow (IVOF) that accounts for anisotropy of diffusion and the flow‐related signal. An IVOF model using a simplified apparent flow fraction tensor (IVOF_f) is applied to diffusion‐weighted imaging of human kidneys. The kidneys of 13 healthy volunteers were examined on a 3 T scanner. Diffusion‐weighted images were acquired with six b values between 0 and 800 s/mm² and 30 diffusion directions. Diffusivity and flow fraction were calculated for different diffusion models. The Akaike information criterion was used to compare the model fit of the proposed IVOF_f model to IVIM and DTI. In the majority of voxels the proposed IVOF_f model with a simplified apparent flow fraction tensor performs better than IVIM and DTI. Mean diffusivity is significantly higher in DTI compared with models that account for the flow‐related signal. The fractional anisotropy of diffusion is significantly reduced when flow fraction is considered to be anisotropic. Anisotropy of the apparent flow fraction tensor is significantly higher in the renal medulla than in the cortex region. The IVOF_f model describes diffusion‐weighted data in the human kidney more accurately than IVIM or DTI. The apparent flow fraction in the kidney proved to be anisotropic.     

A novel bayesian approach with conditional autoregressive specification for intravoxel incoherent motion diffusion‐weighted MRI

The Intra‐Voxel Incoherent Motion (IVIM) model is largely adopted to estimate slow and fast diffusion coefficients of water molecules in biological tissues, which are used in cancer applications. The most reported fitting approach is a voxel‐wise segmented non‐linear least square, whereas Bayesian approaches with a direct fit, also considering spatial regularization, were proposed too. In this work a novel segmented Bayesian method was proposed, also in combination with a spatial regularization through a Conditional Autoregressive (CAR) prior specification. The two segmented Bayesian approaches, with and without CAR specification, were compared with two standard least‐square and a direct Bayesian fitting methods. All approaches were tested on simulated images and real data of patients with head‐and‐neck and rectal cancer. Estimation accuracy and maps noisiness were quantified on simulated images, whereas the coefficient of variation and the goodness of fit were evaluated for real data. Both versions of the segmented Bayesian approach outperformed the standard methods on simulated images for pseudo‐diffusion (D^?) and perfusion fraction (f), whilst the segmented least‐square fitting remained the less biased for the diffusion coefficient (D). On real data, Bayesian approaches provided the less noisy maps, and the two Bayesian methods without CAR generally estimated lower values for f and D^? coefficients with respect to the other approaches. The proposed segmented Bayesian approaches were superior, in terms of estimation accuracy and maps quality, to the direct Bayesian model and the least‐square fittings. The CAR method improved the estimation accuracy, especially for D^?.     

Dynamic intravoxel incoherent motion imaging of skeletal muscle at rest and after exercise

The purpose of this work was to demonstrate the feasibility of intravoxel incoherent motion imaging (IVIM) for non‐invasive quantification of perfusion and diffusion effects in skeletal muscle at rest and following exercise. After IRB approval, eight healthy volunteers underwent diffusion‐weighted MRI of the forearm at 3 T and eight different b values between 0 and 500 s/mm² with a temporal resolution of 57 s per dataset. Dynamic images were acquired before and after a standardized handgrip exercise. Diffusion (D) and pseudodiffusion (D*) coefficients as well as the perfusion fraction (F_P) were measured in regions of interest in the flexor digitorum superficialis and profundus (FDS/FDP), brachioradialis, and extensor carpi radialis longus and brevis muscles by using a multi‐step bi‐exponential analysis in MATLAB. Parametrical maps were calculated voxel‐wise. Differences in D, D*, and F_P between muscle groups and between time points were calculated using a repeated measures analysis of variance with post hoc Bonferroni tests. Mean values and standard deviations at rest were the following: D*, 28.5 ± 11.4 × 10^?3 mm²/s; F_P, 0.03 ± 0.01; D, 1.45 ± 0.09 × 10^?3 mm²/s. Changes of IVIM parameters were clearly visible on the parametrical maps. In the FDS/FDP, D* increased by 289 ± 236% (p < 0.029), F_P by 138 ± 58% (p < 0.01), and D by 17 ± 9% (p < 0.01). A significant increase of IVIM parameters could also be detected in the brachioradialis muscle, which however was significantly lower than in the FDS/FDP. After 20 min, all parameters were still significantly elevated in the FDS/FDP but not in the brachioradialis muscle compared with the resting state. The IVIM approach allows simultaneous quantification of muscle perfusion and diffusion effects at rest and following exercise. It may thus provide a useful alternative to other non‐invasive methods such as arterial spin labeling. Possible fields of interest for this technique include perfusion‐related muscle diseases, such as peripheral arterial occlusive disease. Copyright © 2014 John Wiley & Sons, Ltd.     

VERDICT MRI for radiation treatment response assessment in neuroendocrine tumors

Noninvasive methods to study changes in tumor microstructure enable early assessment of treatment response and thus facilitate personalized treatment. The aim of this study was to evaluate the diffusion MRI model, Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT), for early response assessment to external radiation treatment and to compare the results with those of more studied sets of parameters derived from diffusion-weighted MRI data. Mice xenografted with human small intestine tumors were treated with external radiation treatment, and diffusion MRI experiments were performed on the day before and up to 2 weeks after treatment. The diffusion models VERDICT, ADC, IVIM, and DKI were fitted to MRI data, and the treatment response of each tumor was calculated based on pretreatment tumor growth and post-treatment tumor volume regression. Linear regression and correlation analysis were used to evaluate each model and their respective parameters for explaining the treatment response. VERDICT analysis showed significant changes from day −1 to day 3 for the intracellular and extracellular volume fraction, as well as the cell radius index (p < 0.05; Wilcoxon signed-rank test). The strongest correlation between the diffusion model parameters and the tumor treatment response was seen for the ADC, kurtosis-corrected diffusion coefficient, and intracellular volume fraction on day 3 (τ = 0.47, 0.52, and −0.49, respectively, p < 0.05; Kendall rank correlation coefficient). Of all the tested models, VERDICT held the strongest explanatory value for the tumor treatment response on day 3 (R² = 0.75, p < 0.01; linear regression). In conclusion, VERDICT has potential for early assessment of external radiation treatment and may provide further insights into the underlying biological effects of radiation on tumor tissue. In addition, the results suggest that the time window for assessment of treatment response using dMRI may be narrow.     

Tumor apparent diffusion coefficient as an imaging biomarker to predict tumor aggressiveness in patients with estrogen‐receptor‐positive breast cancer

The purpose of this retrospective study was to evaluate whether tumor apparent diffusion coefficient (ADC) was correlated with pathologic biomarkers such as tumor cellularity, Ki67, tumor‐infiltrating lymphocytes (TILs), and peritumoral lymphocytic infiltrate (PLI) in patients with estrogen receptor (ER)‐positive breast cancer. The study was approved by the institutional review board and informed consent was waived. From July 2014 to December 2014, we reviewed 140 ER‐positive tumors in 138 consecutive patients (range, 28–77 years; mean, 52 years) who underwent preoperative breast MRI and definitive surgery. All patients underwent diffusion‐weighted imaging with a 3T scanner. Two radiologists drew the region of interest of the entire tumor and obtained the mean and pixel‐based histogram of ADC. On pathology, two pathologists reviewed tumor cellularity, Ki67, TILs, and PLI. Multiple linear regression analysis was used to determine pathologic variables independently associated with ADC. Tumors with high tumor cellularity and high Ki67 had significantly lower ADCs than those with low tumor cellularity and low Ki67 (P < 0.05 for all). Tumors without PLI had significantly higher standard deviation than those with PLI (0.23 ± 0.08 versus 0.18 ± 0.05; P < 0.001). Median ADC was negatively correlated with tumor cellularity (r = ?0.441), and Ki67 (r = ?0.382). The standard deviation of ADC was also negatively correlated with the degree of PLI (r = ?0.319). On multivariate linear regression analysis, tumor cellularity and Ki67 were independently associated with tumor ADC. Tumor ADC would be an MRI biomarker for the prediction of tumor aggressiveness indicators such as Ki67, tumor cellularity, and PLI in ER‐positive breast cancer. Copyright © 2016 John Wiley & Sons, Ltd.     

The effect of noise and lipid signals on determination of Gaussian and non‐Gaussian diffusion parameters in skeletal muscle

This work characterizes the effect of lipid and noise signals on muscle diffusion parameter estimation in several conventional and non‐Gaussian models, the ultimate objectives being to characterize popular fat suppression approaches for human muscle diffusion studies, to provide simulations to inform experimental work and to report normative non‐Gaussian parameter values. The models investigated in this work were the Gaussian monoexponential and intravoxel incoherent motion (IVIM) models, and the non‐Gaussian kurtosis and stretched exponential models. These were evaluated via simulations, and in vitro and in vivo experiments. Simulations were performed using literature input values, modeling fat contamination as an additive baseline to data, whereas phantom studies used a phantom containing aliphatic and olefinic fats and muscle‐like gel. Human imaging was performed in the hamstring muscles of 10 volunteers. Diffusion‐weighted imaging was applied with spectral attenuated inversion recovery (SPAIR), slice‐select gradient reversal and water‐specific excitation fat suppression, alone and in combination. Measurement bias (accuracy) and dispersion (precision) were evaluated, together with intra‐ and inter‐scan repeatability. Simulations indicated that noise in magnitude images resulted in <6% bias in diffusion coefficients and non‐Gaussian parameters (α, K), whereas baseline fitting minimized fat bias for all models, except IVIM. In vivo, popular SPAIR fat suppression proved inadequate for accurate parameter estimation, producing non‐physiological parameter estimates without baseline fitting and large biases when it was used. Combining all three fat suppression techniques and fitting data with a baseline offset gave the best results of all the methods studied for both Gaussian diffusion and, overall, for non‐Gaussian diffusion. It produced consistent parameter estimates for all models, except IVIM, and highlighted non‐Gaussian behavior perpendicular to muscle fibers (α ~ 0.95, K ~ 3.1). These results show that effective fat suppression is crucial for accurate measurement of non‐Gaussian diffusion parameters, and will be an essential component of quantitative studies of human muscle quality.     

Characterization of a rat orthotopic pancreatic head tumor model using three‐dimensional and quantitative multi‐parametric MRI

The purpose of this study was to investigate the reliability of 3D isotropic MRI and quantitative multi‐parametric MRI characterization on an orthotopic pancreatic head tumor model in rats. 3D isotropic T₂‐weighted MRI was performed as a routine for tumor longitudinal follow‐up and volume estimation. Common bile duct diameter was measured from 3D multiplanar reconstruction. Quantitative multi‐parametric measurements including pixel‐wise T₂, T₁ relaxivity, apparent diffusion coefficient (ADC) and apparent diffusion kurtosis mapping were performed twice throughout tumor growth. Semi‐quantitative and quantitative analyses based on an extended Tofts model were applied to region‐of‐interest‐based dynamic contrast‐enhanced imaging, followed by contrast ratio measurement on standard contrast‐enhanced imaging. Moreover, low‐level texture‐based analysis was inspected for T₂, T₁, ADC and contrast ratio measurements. Results indicated that multi‐parametric MRI showed good reproducibility for tumor characterization; the measurements were not affected by tumor growth. Tumor growth was further confirmed with histology examinations. To conclude, state‐of‐the‐art clinical MRI techniques were translated to this preclinical tumor model with high reliability, and have paved the way for translational oncology studies on this tumor model.