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Intravoxel Incoherent Motion (IVIM) refers to translational movements which within a given voxel and during the measurement time present a distribution of speeds in orientation and/or amplitude. The IVIM concept has been used to estimate perfusion in tissues as blood flow in randomly oriented capillaries mimics a pseudo-diffusion process. IVIM-based perfusion MRI, which does not require contrast agents, has gained momentum recently, especially in the field oncology. In this introductory review the basic concepts, models, technical requirements and limitations inherent to IVIM-based perfusion MRI are outlined, as well as new, non-perfusion applications of IVIM MRI, such as virtual MR Elastography. •IVIM refers to translational movements which within a voxel present a distribution of speeds in orientation or amplitude.•The concept was introduced in 1986 with Diffusion MRI, as blood flow in capillaries (perfusion) mimics a diffusion process.•IVIM-based perfusion MRI, which does not require contrast agents, is gaining momentum, especially for oncologic applications.•IVIM does not only refer to blood microcirculation, as other sources of intravoxel incoherent motion are possible.

Transmembrane water exchange, including intra-to-extravascular and intra-to-extracellular ones, are potential biomarkers in the diagnosis and understanding of cancers, brain disorders, and other diseases. Filter-exchange imaging (FEXI), a special case of diffusion exchange spectroscopy (DEXSY) adapted for clinical applications, has the potential to reveal different physiological water exchange processes using the same MRI sequence. In this study, we aim to explore the feasibility of FEXI in measuring different water exchange processes by modulating the diffusion filter (bf) and detection blocks in FEXI. Two FEXI protocols were implemented on a 3T MRI clinical scanner and reveal distinct apparent exchange rate (AXR) contrast in brain tissues in seven healthy volunteers. AXR estimated from a FEXI protocol with bf ​= ​250 ​s/mm2, which is expected to filter out the vascular water specifically, are significantly larger than those of a FEXI protocol with bf ​= ​900 ​s/mm2. Besides, the filter efficiency of FEXI with bf ​= ​250 ​s/mm2 shows a strong correlation with vascular density, a metric estimated as the fraction of water exhibiting intravoxel incoherent motion (IVIM). AXR of FEXI with bf ​= ​250 ​s/mm2 agrees with the vascular water efflux rate constants reported by other independent measurements, although the physiological basis of the AXR of FEXI with bf ​= ​900 ​s/mm2 is not clear yet. Collectively, our current results demonstrate the feasibility of FEXI in measuring different water exchange processes in vivo, and that FEXI targeting the vascular water could help characterize the intra-to-extravascular water exchange process. [Display omitted]

Objective To evaluate histogram analysis of intravoxel incoherent motion (IVIM) for discriminating the Gleason grade of prostate cancer (PCa). Methods A total of 48 patients pathologically confirmed as having clinically significant PCa (size > 0.5 cm) underwent preoperative DW-MRI ( b of 0–900 s/mm 2 ). Data was post-processed by monoexponential and IVIM model for quantitation of apparent diffusion coefficients (ADCs), perfusion fraction f , diffusivity D and pseudo-diffusivity D *. Histogram analysis was performed by outlining entire-tumour regions of interest (ROIs) from histological–radiological correlation. The ability of imaging indices to differentiate low-grade (LG, Gleason score (GS) ≤6) from intermediate/high-grade (HG, GS > 6) PCa was analysed by ROC regression. Results Eleven patients had LG tumours (18 foci) and 37 patients had HG tumours (42 foci) on pathology examination. HG tumours had significantly lower ADCs and D in terms of mean, median, 10th and 75th percentiles, combined with higher histogram kurtosis and skewness for ADCs, D and f , than LG PCa ( p  < 0.05). Histogram D showed relatively higher correlations (ñ = 0.641–0.668 vs. ADCs: 0.544–0.574) with ordinal GS of PCa; and its mean, median and 10th percentile performed better than ADCs did in distinguishing LG from HG PCa. Conclusion It is feasible to stratify the pathological grade of PCa by IVIM with histogram metrics. D performed better in distinguishing LG from HG tumour than conventional ADCs. Key Points • GS had relatively higher correlation with tumour D than ADCs . • Difference of histogram D among two - grade tumours was statistically significant . • D yielded better individual features in demonstrating tumour grade than ADC . • D * and f failed to determine tumour grade of PCa .

Objective To determine the measurement reproducibility of perfusion fraction f , pseudodiffusion coefficient D * and diffusion coefficient D in colorectal liver metastases and normal liver. Methods Fourteen patients with known colorectal liver metastases were examined twice using respiratory-triggered echo-planar DW-MRI with eight b values (0 to 900 s/mm 2 ) 1 h apart. Regions of interests were drawn around target metastasis and normal liver in each patient to derive ADC (all b values), ADC high ( b values ≥100 s/mm 2 ) and intravoxel incoherent motion (IVIM) parameters f , D * and D by least squares data fitting. Short-term measurement reproducibility of median ADC, ADC high , f , D * and D values were derived from Bland–Altman analysis. Results The measurement reproducibility for ADC, ADC high and D was worst in colorectal liver metastases (−21 % to +25 %) compared with liver parenchyma (−6 % to +8 %). Poor measurement reproducibility was observed for the perfusion-sensitive parameters of f (−75 % to +241 %) and D * (−89 % to +2,120 %) in metastases, and to a lesser extent the f (−24 % to +25 %) and D* (−31 % to +59 %) of liver. Conclusions Estimates of f and D * derived from the widely used least squares IVIM fitting showed poor measurement reproducibility. Efforts should be made to improve the measurement reproducibility of perfusion-sensitive IVIM parameters. Key Points • Quantitative diffusion-weighted MRI parameters are increasingly used for clinical management decisions. • However perfusion-sensitive intravoxel incoherent motion (IVIM) parameters showed poor measurement reproducibility. • Measurement reproducibility of IVIM parameters was worse in metastases than normal liver. • Efforts to improve measurement reproducibility of IVIM parameters should be explored.

Radiation necrosis is a serious potential adverse event of stereotactic radiosurgery that cannot be reliably differentiated from recurrent tumor using conventional imaging techniques. Intravoxel incoherent motion (IVIM) is a magnetic resonance imaging (MRI) based method that uses a diffusion-weighted sequence to estimate quantitative perfusion and diffusion parameters. This study evaluated the IVIM-derived apparent diffusion coefficient (ADC) and perfusion fraction (f), and compared the results to the gold standard histopathological-defined outcomes of radiation necrosis or recurrent tumor. Nine patients with ten lesions were included in this study; all lesions exhibited radiographic progression after stereotactic radiosurgery for brain metastases that subsequently underwent surgical resection due to uncertainty regarding the presence of radiation necrosis versus recurrent tumor. Pre-surgical IVIM was performed to obtain f and ADC values and the results were compared to histopathology. Five lesions exhibited pathological radiation necrosis and five had predominantly recurrent tumor. The IVIM perfusion fraction reliably differentiated tumor recurrence from radiation necrosis (f mean  = 10.1 ± 0.7 vs. 8.3 ± 1.2, p = 0.02; cutoff value of 9.0 yielding a sensitivity/specificity of 100%/80%) while the ADC did not distinguish between the two (ADC mean  = 1.1 ± 0.2 vs. 1.2 ± 0.4, p = 0.6). IVIM shows promise in differentiating recurrent tumor from radiation necrosis for brain metastases treated with radiosurgery, but needs to be validated in a larger cohort.

Objectives To assess the value of new magnetic resonance imaging (MRI) techniques in cervical cancer. Methods We searched PubMed and MEDLINE and reviewed articles published from 1990 to 2016 to identify studies that used MRI techniques, such as diffusion weighted imaging (DWI), intravoxel incoherent motion (IVIM) and dynamic contrast enhancement (DCE) MRI, to assess parametric invasion, to detect lymph node metastases, tumour subtype and grading, and to detect and predict tumour recurrence. Results Seventy-nine studies were included. The additional use of DWI improved the accuracy and sensitivity of the evaluation of parametrial extension. Most studies reported improved detection of nodal metastases. Functional MRI techniques have the potential to assess tumour subtypes and tumour grade differentiation, and they showed additional value in detecting and predicting treatment response. Limitations included a lack of technical standardisation, which limits reproducibility. Conclusions New advanced MRI techniques allow improved analysis of tumour biology and the tumour microenvironment. They can improve TNM staging and show promise for tumour classification and for assessing the risk of tumour recurrence. They may be helpful for developing optimised and personalised therapy for patients with cervical cancer. Teaching points • Conventional MRI plays a key role in the evaluation of cervical cancer. • DWI improves tumour delineation and detection of nodal metastases in cervical cancer. • Advanced MRI techniques show promise regarding histological grading and subtype differentiation. • Tumour ADC is a potential biomarker for response to treatment.

To assess the utility of IVIM parameters in evaluating uterine fibroid blood flow compared to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) derived blood flow. Sixteen premenopausal women with uterine fibroids were enrolled in this prospective study. Pelvic MRI scans were obtained for each subject, both with and without continuous intravenous infusion of oxytocin, known to decrease significantly uterine fibroid blood flow, to assess the changes in blood flow of uterine fibroids. IVIM and DCE analyses were conducted using separate dedicated software. The bi-exponential IVIM model was used to estimate perfusion fraction (f), pseudo-diffusion coefficient (D*), and diffusion coefficient (D). DCE blood flow values were derived via T1 perfusion deconvolution arithmetic, utilizing a first pass of an AIF curve. The correlation between the parameters were analyzed by Spearman’s rank correlation analysis due to small sample size. Means of the parameters were compared with a nonparametric Wilcoxon sign rank method for each pair. Statistically significant positive correlations were found between perfusion fraction values and DCE blood flow values with oxytocin (Spearson’s ρ = 0.78, p  = 0.0004), and between fD* values and DCE blood flow values with oxytocin (Spearson’s ρ = 0.64, p  = 0.0071). Significant differences in blood flow were detected across most IVIM parameters: f, D*, and fD* ( p  < 0.001, p  = 0.0027, and p  = 0.0002, respectively) when comparing the values without oxytocin and with oxytocin. IVIM imaging shows promise for assessing blood flow in uterine fibroids.

Ki-67 is a nuclear antigen widely used in routine pathologic analyses as a tumor cell proliferation marker for lung cancer. However, Ki-67 expression analyses using immunohistochemistry (IHC) are invasive and frequently influenced by tissue sampling quality. In this study, we assessed the feasibility of noninvasive magnetic resonance imaging (MRI) in predicting the Ki-67 labeling indices (LIs). A total of 51 lung cancer patients, including 42 non-small cell lung cancer (NSCLC) cases and nine small cell lung cancer (SCLC) cases, were enrolled in this study. Quantitative MRI parameters from conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) were obtained, and their correlations with tumor tissue Ki-67 expression were analyzed. We found that the true diffusion coefficient (D value) from IVIM was negatively correlated with Ki-67 expression (Spearman r = -0.76, < 0.001). The D values in the high Ki-67 group were significantly lower than those in the low Ki-67 group (0.90 ± 0.21 × 10 mm /s vs. 1.22 ± 0.30 × 10 mm /s). Among three MRI techniques used, D values from IVIM showed the best performance for distinguishing the high Ki-67 group from low Ki-67 group in receiver operating characteristic (ROC) analysis with an area under the ROC curve (AUROC) of 0.85 (95% CI: 0.73-0.97, < 0.05). Moreover, D values performed well for differentiating SCLC from NSCLC with an AUROC of 0.82 (95% CI: 0.68-0.90), Youden index of 0.72, and F1 score of 0.81. In conclusion, D values were negatively correlated with Ki-67 expression in lung cancer tissues and can be used to distinguish high from low proliferation statuses, as well as SCLC from NSCLC.

The assessment of the free water fraction in the brain provides important information about extracellular processes such as atrophy and neuroinflammation in various clinical conditions as well as in normal development and aging. Free water estimates from diffusion MRI are assumed to account for freely diffusing water molecules in the extracellular space, but may be biased by other pools of molecules in rapid random motion, such as the intravoxel incoherent motion (IVIM) of blood, where water molecules perfuse in the randomly oriented capillary network. The goal of this work was to separate the signal contribution of the perfusing blood from that of free-water and of other brain diffusivities. The influence of the vascular compartment on the estimation of the free water fraction and other diffusivities was investigated by simulating perfusion in diffusion MRI data. The perfusion effect in the simulations was significant, especially for the estimation of the free water fraction, and was maintained as long as low b-value data were included in the analysis. Two approaches to reduce the perfusion effect were explored in this study: (i) increasing the minimal b-value used in the fitting, and (ii) using a three-compartment model that explicitly accounts for water molecules in the capillary blood. Estimation of the model parameters while excluding low b-values reduced the perfusion effect but was highly sensitive to noise. The three-compartment model fit was more stable and additionally, provided an estimation of the volume fraction of the capillary blood compartment. The three-compartment model thus disentangles the effects of free water diffusion and perfusion, which is of major clinical importance since changes in these components in the brain may indicate different pathologies, i.e., those originating from the extracellular space, such as neuroinflammation and atrophy, and those related to the vascular space, such as vasodilation, vasoconstriction and capillary density. Diffusion MRI data acquired from a healthy volunteer, using multiple b-shells, demonstrated an expected non-zero contribution from the blood fraction, and indicated that not accounting for the perfusion effect may explain the overestimation of the free water fraction evinced in previous studies. Finally, the applicability of the method was demonstrated with a dataset acquired using a clinically feasible protocol with shorter acquisition time and fewer b-shells. •Perfusing capillary blood affects the estimation of diffusivities.•Other fast diffusing components such as the free water fraction are overestimated.•A three-compartment model including tissue, free water and blood is proposed.•Separating perfusing blood signal from water diffusion improves freewater estimation.•Clinical feasibility is demonstrated with simulations and real data.

Spherical deconvolution is a widely used approach to quantify the fiber orientation distribution (FOD) from diffusion MRI data of the brain. The damped Richardson-Lucy (dRL) is an algorithm developed to perform robust spherical deconvolution on single-shell diffusion MRI data while suppressing spurious FOD peaks due to noise or partial volume effects. Due to recent progress in acquisition hardware and scanning protocols, it is becoming increasingly common to acquire multi-shell diffusion MRI data, which allows for the modelling of multiple tissue types beyond white matter. While the dRL algorithm could, in theory, be directly applied to multi-shell data, it is not optimised to exploit its information content to model the signal from multiple tissue types. In this work, we introduce a new framework based on dRL – dubbed generalized Richardson-Lucy (GRL) – that uses multi-shell data in combination with user-chosen tissue models to disentangle partial volume effects and increase the accuracy in FOD estimation. Further, GRL estimates signal fraction maps associated to each user-selected model, which can be used during fiber tractography to dissect and terminate the tracking without need for additional structural data. The optimal weighting of multi-shell data in the fit and the robustness to noise and to partial volume effects of GRL was studied with synthetic data. Subsequently, we investigated the performance of GRL in comparison to dRL and to multi-shell constrained spherical deconvolution (MSCSD) on a high-resolution diffusion MRI dataset from the Human Connectome Project and on an MRI dataset acquired at 3T on a clinical scanner. In line with previous studies, we described the signal of the cerebrospinal-fluid and of the grey matter with isotropic diffusion models, whereas four diffusion models were considered to describe the white matter. With a third dataset including small diffusion weightings, we studied the feasibility of including intra-voxel incoherent motion effects due to blood pseudo-diffusion in the modelling. Further, the reliability of GRL was demonstrated with a test-retest scan of a subject acquired at 3T. Results of simulations show that GRL can robustly disentangle different tissue types at SNR above 20 with respect to the non-weighted image, and that it improves the angular accuracy of the FOD estimation as compared to dRL. On real data, GRL provides signal fraction maps that are physiologically plausible and consistent with those obtained with MSCSD, with correlation coefficients between the two methods up to 0.96. When considering IVIM effects, a high blood pseudo-diffusion fraction is observed in the medial temporal lobe and in the sagittal sinus. In comparison to dRL and MSCSD, GRL provided sharper FODs and less spurious peaks in presence of partial volume effects, but the FOD reconstructions are also highly dependent on the chosen modelling of white matter. When performing fiber tractography, GRL allows to terminate fiber tractography using the signal fraction maps, which results in a better tract termination at the grey-white matter interface or at the outer cortical surface. In terms of inter-scan reliability, GRL performed similarly to or better than compared methods. In conclusion, GRL offers a new modular and flexible framework to perform spherical deconvolution of multi-shell data. •A generalized Richardson-Lucy (GRL) method to leverage multi-shell diffusion MRI data.•GRL improves the quality of the WM FOD estimation.•GRL can fit diffusion signals with models of choice – including DTI, DKI and NODDI.•GRL disentangle partial volume effects of WM with GM, CSF and others like IVIM.•GRL uses the signal fraction estimates to terminate the fiber tractography.