Comparison of accuracy of intravoxel incoherent motion and apparent diffusion coefficient techniques for predicting malignancy of head and neck tumors using half-Fourier single-shot turbo spin-echo diffusion-weighted imaging

Purpose

To evaluate the use of the intravoxel incoherent motion (IVIM) technique in half-Fourier single-shot turbo spin-echo (HASTE) diffusion-weighted imaging (DWI), and to compare its accuracy to that of apparent diffusion coefficient (ADC) to predict malignancy in head and neck tumors.

Patients and methods

HASTE DW images of 33 patients with head and neck tumors (10 benign and 23 malignant) were evaluated. Using the IVIM technique, parameters (D, true diffusion coefficient; f, perfusion fraction; D*, pseudodiffusion coefficient) were calculated for each tumor. ADC values were measured over a range of b values from 0 to 1000 s/mm². IVIM parameters and ADC values in benign and malignant tumors were compared using Student's t test, receiver operating characteristics (ROC) analysis, and multivariate logistic regression modeling.

Results

Mean ADC and D values of malignant tumors were significantly lower than those of benign tumors (P < 0.05). Mean D* values of malignant tumors were significantly higher than those of benign tumors (P < 0.05). There was no significant difference in mean f values between malignant and benign tumors (P > 0.05). The technique of combining D and D* was the best for predicting malignancy; accuracy for this model was higher than that for ADC.

Conclusions

The IVIM technique may be applied in HASTE DWI as a diagnostic tool to predict malignancy in head and neck masses. The use of D and D* in combination increases the diagnostic accuracy in comparison with ADC.     

Intravoxel incoherent motion imaging of the kidney: alterations in diffusion and perfusion in patients with renal dysfunction

Purpose

To investigate the relationship between estimated glomerular filtration rate (eGFR) and parameters calculated using intravoxel incoherent motion (IVIM) imaging of the kidneys.

Materials and Methods

We studied 365 patients, divided into 4 groups based on eGFR levels (mL/min/1.73 m²): group 1, eGFR ≥ 80(n = 80); group 2, eGFR 60–80 (n = 156); group 3, eGFR 30–60 (n = 114); and group 4 ,eGFR < 30 (n = 15). IVIM imaging was used to acquire diffusion-weighted images at 12 b values. The diffusion coefficient of pure molecular diffusion (D), the diffusion coefficient of microcirculation or perfusion (D*), and perfusion fraction (f) were compared among the groups using group 1 as control.

Results

In the renal cortex, D* values were significantly lower in groups 2, 3, and 4 than in group 1. The D value of renal cortex was significantly low in only group 3. In the renal medulla, the D* and D values were significantly lower only in groups 2 and 3, respectively.

Conclusion

As renal dysfunction progresses, renal perfusion might be reduced earlier and affected more than molecular diffusion in the renal cortex. These changes are effectively detected by IVIM MR imaging.     

MRI quantification of diffusion and perfusion in bone marrow by intravoxel incoherent motion (IVIM) and non-negative least square (NNLS) analysis

Object

To assess the feasibility of measuring diffusion and perfusion fraction in vertebral bone marrow using the intravoxel incoherent motion (IVIM) approach and to compare two fitting methods, i.e., the non-negative least squares (NNLS) algorithm and the more commonly used Levenberg–Marquardt (LM) non-linear least squares algorithm, for the analysis of IVIM data.

Materials and Methods

MRI experiments were performed on fifteen healthy volunteers, with a diffusion-weighted echo-planar imaging (EPI) sequence at five different b-values (0, 50, 100, 200, 600 s/mm²), in combination with an STIR module to suppress the lipid signal. Diffusion signal decays in the first lumbar vertebra (L1) were fitted to a bi-exponential function using the LM algorithm and further analyzed with the NNLS algorithm to calculate the values of the apparent diffusion coefficient (ADC), pseudo-diffusion coefficient (D*) and perfusion fraction.

Results

The NNLS analysis revealed two diffusion components only in seven out of fifteen volunteers, with ADC = 0.60 ± 0.09 (10^− 3 mm²/s), D* = 28 ± 9 (10^− 3 mm²/s) and perfusion fraction = 14% ± 6%. The values obtained by the LM bi-exponential fit were: ADC = 0.45 ± 0.27 (10^− 3 mm²/s), D* = 63 ± 145 (10^− 3 mm²/s) and perfusion fraction = 27% ± 17%. Furthermore, the LM algorithm yielded values of perfusion fraction in cases where the decay was not bi-exponential, as assessed by NNLS analysis.

Conclusion

The IVIM approach allows for measuring diffusion and perfusion fraction in vertebral bone marrow; its reliability can be improved by using the NNLS, which identifies the diffusion decays that display a bi-exponential behavior.     

Diffusion-weighted magnetic resonance imaging of human skeletal muscles: gender-, age- and muscle-related differences in apparent diffusion coefficient

Purpose

To evaluate the apparent diffusion coefficient (ADC) of skeletal muscle based on signal intensity (SI) attenuation vs. increasing b values and to determine ADC differences in skeletal muscles between genders, age groups and muscles.

Materials and Methods

Diffusion-weighted images (b values in the range of 0–750 s/mm² at increments of 50 s/mm²) of the ankle dorsiflexors (116 subjects) and the erector spinae muscles (86 subjects) were acquired with a 1.5-T MR device. From the two different slopes obtained in SI vs. b-value logarithmic plots, ADC^b0–50 (b values=0 and 50 s/mm²) reflected diffusion and perfusion, while ADC^b50–750 (b values in the range of 50–750 s/mm² at increments of 50 s/mm²) approximated the true diffusion coefficient. Moreover, to evaluate whether this b-value combination is appropriate for assessing the flow component within muscles, diffusion-weighted images of the ankle dorsiflexors (10 subjects) were obtained before and during temporal arterial occlusion.

Results

ADC^b0–50 and ADC^b50–750 were found to be 2.64×10^–3 and 1.44×10^–3 mm²/s in the ankle dorsiflexors, and 3.02×10^–3 and 1.49×10^–3 mm²/s in the erector spinae muscles, respectively. ADC^b0–50 was significantly higher than ADC^b50–750 in each muscle (P<.01). The erector spinae muscles showed significantly higher ADC values than the ankle dorsiflexors (P<.01). However, for each muscle, there were few significant gender- and age-related ADC differences. Following temporal occlusion, ADC^b0–50 of the ankle dorsiflexors decreased significantly from 2.49 to 1.6×10^–3 mm²/s (P<.01); however, ADC^b50–750 showed no significant change.

Conclusion

Based on the SI attenuation pattern, muscle ADC could be divided into ADC that reflects both diffusion and perfusion, and ADC that approximates a true diffusion coefficient. There were significant differences in ADC of functionally distinct muscles. However, we barely found any gender- or age-related ADC differences for each muscle.     

Evaluation of noncirrhotic hepatic parenchyma with and without significant portal vein stenosis using diffusion-weighted echo-planar MR on the basis of multiple-perfusion-components theory

To determine whether diffusion-weighted echo-planar MR images are sensitive to liver perfusion difference.Noncirrhotic livers of 71 patients (43 males, 28 females; age range, 22-87 years; mean, 61 years) without (n=51) and with (n=20) significant (>70%) portal vein stenosis (accompanying proximal hepatic arterial stenosis and/or biliary tract obstruction in 10) by tumors were examined with diffusion-weighted echo-planar sequences (modified for b factors of 1, 28, 66, 288 and 600 s/mm²). On the basis of multiple-perfusion-components theory, i.e., assuming logarithm of signal intensity for liver perfusion is linearly attenuated versus logarithm of a smaller b factor, we defined the slope of the line as the perfusion-related D′ value. The D′ values of these livers were calculated from images with b factors of 1, 28, and 66 s/mm². The livers' apparent diffusion coefficient values for diffusion (ADC_d values) were calculated from images with b factors of 288 and 600 s/mm².The livers with significant portal vein stenosis had statistically lower mean D′ values than the livers without portal vein stenosis (P<.001 on the Mann-Whitney U test). However, there was no significant difference in ADC_d values between these liver types (P>.05).The D′ value calculated from diffusion-weighted echo-planar sequences with plural smaller b factors may be sensitive to liver perfusion difference.     

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

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

Focal nodular hyperplasia of the liver: diffusion and perfusion MRI characteristics

Purpose

To present diffusion and perfusion magnetic resonance imaging (MRI) characteristics of focal nodular hyperplasia (FNH) of the liver.

Materials and Methods

Thirty-five patients with 52 FNHs (21 were pathologically-confirmed) underwent MRI at 1.5-T device. MR diffusion [diffusion-weighted imaging (DWI)] was performed using a free-breathing single-shot, spin-echo, echo-planar sequence with b gradient factor value of 500 s/mm². MR perfusion [perfusion-weighted imaging (PWI)] consisted of a 3D free-breathing LAVA sequence repeated up to 5 minutes after injection of 7 mL Gd-BOPTA (MultiHance, Bracco, Italy) and 20 mL saline flush at a flow rate of 4 mL/s. Apparent diffusion coefficient (ADC) and time-signal intensity curve (TSIC) were obtained for both normal liver and each FNH by two reviewers in conference; maximum enhancement (ME) percentage, time to peak enhancement (TTP), and maximal slope (MS) were also calculated.

Results

On DWI mean ADC value was 1.624×10^− 3 mm²/s for normal liver and 1.629×10^− 3 mm²/s for FNH. ADC value for each FNH and the normal liver was not statistically different (P= .936). On PWI, TSIC-Type 1 (quick and marked enhancement and quick decay followed by slowly decaying) was observed in all 52 FNHs, and TSIC-Type 2 (fast enhancement followed by slowly decaying plateau) in all normal livers. The mean ME, TTP and MS values were significantly different for FNH and normal liver (P= .005).

Conclusion

FNHs of the liver showed typical diffusion and perfusion MRI characteristics in all cases. On the ADC map, we could get similar value between the FNHs and the background parenchyma. On the perfusion imaging, FNHs showed a different pattern distinguished from the background liver.     

Intravoxel incoherent motion diffusion-weighted imaging in head and neck squamous cell carcinoma: Assessment of perfusion-related parameters compared to dynamic contrast-enhanced MRI

Purpose

To investigate the correlation between perfusion-related parameters obtained with intravoxel incoherent motion (IVIM) and classical perfusion parameters obtained with dynamic contrast-enhanced (DCE) magnetic resonance imaging in patients with head and neck squamous cell carcinoma (HNSCC), and to compare direct and asymptotic fitting, the pixel-by-pixel approach, and a region of interest (ROI)-based approach respectively for IVIM parameter calculation.

Materials and methods

Seventeen patients with HNSCC were included in this retrospective study. All magnetic resonance (MR) scanning was performed using a 3 T MR unit. Acquisition of IVIM was performed using single-shot spin-echo echo-planar imaging with three orthogonal gradients with 12 b-values (0, 10, 20, 30, 50, 80, 100, 200, 400, 800, 1000, and 2000). Perfusion-related parameters of perfusion fraction ‘f’ and the pseudo-diffusion coefficient ‘D*’ were calculated from IVIM data by using least square fitting with the two fitting methods of direct and asymptotic fitting, respectively. DCE perfusion was performed in a total of 64 dynamic phases with a 3.2-s phase interval. The two-compartment exchange model was used for the quantification of tumor blood volume (TBV) and tumor blood flow (TBF). Each tumor was delineated with a polygonal ROI for the calculation of f, f ? D* performed using both the pixel-by-pixel approach and the ROI-based approach. In the pixel-by-pixel approach, after fitting each pixel to obtain f, f ? D* maps, the mean value in the delineated ROI on these maps was calculated. In the ROI-based approach, the mean value of signal intensity was calculated within the ROI for each b-value in IVIM images, and then fitting was performed using these values. Correlations between f in a total of four combinations (direct or asymptotic fitting and pixel-by-pixel or ROI-based approach) and TBV were respectively analyzed using Pearson's correlation coefficients. Correlations between f ? D* and TBF were also similarly analyzed.

Results

In all combinations of f and TBV, f ? D* and TBF, there was a significant correlation. In the comparison of f and TBV, a moderate correlation was observed only between f obtained by direct fitting with the pixel-by-pixel approach, whereas a good correlation was observed in the comparisons using the other three combinations. In the comparison of f ? D* and TBF, a good correlation was observed only with f ? D* obtained by asymptotic fitting with the ROI-based approach. In contrast, moderate correlations were observed in the comparisons using the other three combinations.

Conclusion

IVIM was found to be feasible for the analysis of perfusion-related parameters in patients with HNSCC. Especially, the combination of asymptotic fitting with the ROI-based approach was better correlated with DCE perfusion.     

On the effects of a varied diffusion time in vivo: is the diffusion in white matter restricted?

The aim of this work was to study the diffusion-related signal attenuation curves (signal-vs.-b curves) measured perpendicular and parallel to the neuronal fibers of the corticospinal tract in vivo and to determine whether effects of restricted diffusion could be observed when varying the diffusion time (T_D). A biexponential model and a two-compartment model including exchange according to the Kärger formalism were employed to analyze the signal-vs.-b curves. To validate the two-compartment model, restricted diffusion with exchange was simulated for uniformly sized cylinders, using different diameters and exchange times. The model was shown to retrieve the simulated parameters well, also when the short gradient pulse approximation was not met. The in vivo measurements performed perpendicular to the tracts, using b values up to 28000 s/mm² and T_D values between 64 and 256 ms, did not show the effects of restricted diffusion as expected from previous ex vivo studies. The applied two-compartment model yielded an average axonal diameter of about 4 μm and an intracellular exchange time of about 300 ms, but did not fit statistically well to the data. In conclusion, this study indicates that if the diffusion is modeled as two compartments, of which one is restricted, exchange must be included in the model.     

Associations between IVIM histogram parameters and histopathology in rectal cancer

PurposeHistogram analysis can better reflect tumor heterogeneity than conventional imaging analysis. The present study analyzed possible correlations between histogram analysis parameters derived from Intravoxel-incoherent imaging (IVIM) and histopathological features in rectal cancer (RC).MethodsSeventeen patients with histopathologically proven rectal adenocarcinomas were retrospectively acquired. In all cases, pelvic MRI was performed. Diffusion weighted imaging was obtained using a multi-slice single-shot echo-planar imaging sequence with b values of 0, 50, 200, 500 and 1000 s/mm². Simplified IVIM analysis was performed using the IntelliSpace portal, version 10 and the following images were generated: f (perfusion fraction) map, D (true diffusion coefficient) map, and ADC map utilizing all b-values. Histogram based analysis of signal intensities was performed for every IVIM map using an in-house matlab tool. Histopathology was investigated using Ki 67 specimens with calculation of Ki 67-index and cellularity. CD31 stained specimens were used for calculation of microvessel density (MVD).ResultsThere were statistically significant correlations between Ki 67 index and mode derived from ADC as well as entropy from f, r=−0.50, p=.04 and r=−0.55, p=.02, respectively. MVD correlated well with parameters derived from f.ConclusionIVIM histogram analysis parameters can reflect histopathology in RC. ADC and D values are associated with proliferation potential. Perfusion fraction f is associated with MVD.     

Correlation study between intravoxel incoherent motion MRI and dynamic contrast-enhanced MRI in head and neck squamous cell carcinoma: Evaluation in primary tumors and metastatic nodes

ObjectiveTo correlate intravoxel incoherent motion (IVIM) imaging and dynamic contrast-enhanced (DCE) MRI in head and neck squamous cell carcinoma (HNSCC).MethodsForty untreated patients with HNSCC were included retrospectively in the study. Perfusion fraction f, diffusion coefficient D and perfusion-related diffusion coefficient D* were extracted by bi-exponential fitting of IVIM data. Semi-quantitative DCE-MRI parameters, including positive enhancement integral (PEI) and maximum slope of increase (MSI), were calculated. The relationships between all variables were assessed by Spearman's test for correlation.Results27 primary tumors (PTs) and 23 lymph nodes (LNs) were analyzed. The residual sum of squares (RSS), used to assess the fit quality, was significantly different between PTs and LNs, with the last showing lower values. In LNs, D* and the product D* × f were positively related to both nPEI and nMSI, while no significant correlation was found in PTs.ConclusionEvident relationships between D* and D* × f and DCE-MRI perfusion measurements were found in LNs, while no significant association emerged in PTs. This presumably is due to the poorer agreement between the experimental data and curve fitting for PTs, as compared to LNs. Additional work is warranted to improve the reliability of the IVIM parameter estimations in primary HNSCCs.     

Correlation between Hepatic Fat Content Using 3-Echo 3-D Dixon Method and Intravoxel Incoherent Motion (IVIM) Perfusion MR Imaging

Fat accumulates as droplets in the hepatocyte swelling, distortion of microcirculatory anatomy and compression of sinus. This study aims to investigate the correlation between the T2*-corrected fat fraction (FF) value acquired via gradient echo with a low flip angle and parenchymal pseudorandom blood perfusion (P _fraction), microcirculation (D _fast), and slow component of diffusion (D _slow), acquired via intravoxel incoherent motion (IVIM), and to investigate the blood microcirculation and diffusion components of liver parenchyma, according to fat deposition. A total of 126 patients underwent 3-T magnetic resonance imaging, including a 3-echo three-dimensional (3-D) gradient echo sequence with T2*-corrected Dixon reconstruction and IVIM sequence. Pearson’s correlation analysis was conducted to investigate the correlation of the FF obtained via the Dixon method with the apparent diffusion coefficient (ADC), D _slow, P _fraction, and D _fast obtained via IVIM. Correlation analysis was also conducted for the IVIM mapping images. A confidence level of p < 0.05 was set. A negative correlation was found between the T2*-corrected FF acquired using the 3-echo 3-D Dixon method and D _slow acquired via IVIM (r = ?0.181, p < 0.05). It was likely due to the increased extracellular collagen deposition and increased intracellular fat droplets during the progression of liver fibrosis.     

Diffusion tensor parameters and principal eigenvector coherence: Relation to b-value intervals and field strength

Diffusion-weighted MRI images acquired at b-value greater than 1000 s mm^− 2 measure the diffusion of a restricted pool of water molecules. High b-value images are accompanied by a reduction in signal-to-noise ratio (SNR) due to the application of large diffusion gradients. By fitting the diffusion tensor model to data acquired at incremental b-value intervals, we determined the effect of SNR on tensor parameters in normal human brains, in vivo. In addition, we also investigated the impact of field strength on the diffusion tensor model. Data were acquired at 1.5 and 3 T, at b-values 0, 1000, 2000 and 3000 s mm^− 2 in twenty diffusion-sensitised directions. Fractional anisotropy (FA), mean diffusivity (MD) and principal eigenvector coherence (κ) were calculated from diffusion tensors fitted between datasets with b-values 0–1000, 0–2000, 0–3000, 1000–2000 and 2000–3000 s mm^− 2. Field strength and b-value effects on diffusion parameters were analysed in white and grey matter regions of interest. Decreases in FA, κ and MD were found with increasing b-value in white matter. Univariate analysis showed a significant increase in FA with increasing field strength in highly organised white matter. These results suggest there are significant differences in diffusion parameters at 1.5 and 3 T and that the optimal results, in terms of the highest values of FA in white matter, are obtained at 3 T with a maximum b = 1000 s mm^− 2.     

Biexponential analysis of intravoxel incoherent motion in calf muscle before and after exercise: Comparisons with arterial spin labeling perfusion and T2

PurposeThis study aimed to clarify exercise-induced changes in intravoxel incoherent motion (IVIM) parameters obtained from diffusion-weighted imaging (DWI) of the calf muscle, as well as the relationships between IVIM parameters, perfusion, and water content in muscle tissue.Materials and methodsThirteen healthy volunteers underwent IVIM-DWI, arterial spin labeling (ASL), and multi-echo spin-echo T₂ mapping of the right calf on a 3.0-T magnetic resonance imaging scanner before and after performing dorsiflexion exercise. From the data, we derived the perfusion-related diffusion coefficient (D^⁎), perfusion component fraction (F), blood flow parameter (FD^⁎), and restricted diffusion coefficient (D) in the tibialis anterior muscle. The muscle blood flow (MBF) and transverse relaxation time (T₂) were also calculated from the ASL and multi-echo spin-echo data, respectively. We compared the parameters measured before and after exercise and assessed the relationship of each IVIM-derived perfusion parameter (D^⁎, F, and FD^⁎) with MBF and each diffusion parameter (D and ADC) or F with T₂.ResultsNotably, all these parameters were significantly increased after exercise. Before exercise, the FD^⁎ exhibited a significant positive correlation with the MBF, whereas no significant correlation was observed between D^⁎ or F and MBF. After exercise, both D^⁎ and FD^⁎ exhibited significant positive correlations with MBF, whereas F was not significantly correlated with MBF. Additionally, D was significantly correlated with T₂ after exercise, but not before exercise. No significant correlations were found between ADC and T₂ either before or after exercise.ConclusionsThe IVIM analyses before and after exercise enable the simultaneous evaluation of exercise-induced changes in perfusion and water diffusion in the muscle and increases the body of information on muscle physiology.     

DTI at 7 and 3 T: systematic comparison of SNR and its influence on quantitative metrics

Diffusion tensor imaging (DTI) and advanced related methods such as diffusion spectrum and kurtosis imaging are limited by low signal-to-noise ratio (SNR) at conventional field strengths. DTI at 7 T can provide increased SNR; however, B0 and B1 inhomogeneity and shorter T2? still pose formidable challenges. The purpose of this study was to quantify and compare SNR at 7 and 3 T for different parallel imaging reduction factors, R, and TE, and to evaluate SNRs influences on fractional anisotropy (FA) and apparent diffusion coefficient (ADC). We found that R>4 at 7 T and R≥2 at 3 T were needed to reduce geometric distortions due to B0 inhomogeneity. For these R at 7 T, SNR was 70-90 for b=0 s/mm² and 22-28 for b=1000s/mm² in central brain regions. SNR was lower at 3 T (40 for b=0 s/mm² and 15 for b=1000 s/mm²) and in lateral brain regions at 7 T due to B1 inhomogeneity. FA and ADC did not change with MRI field strength, SENSE factor or TE in the tested range. However, the coefficient of variation for FA increased for SNR <15 and for SNR <10 in ADC, consistent with published theoretical studies. Our study demonstrates that 7 T is advantageous for DTI and lays the groundwork for further development. Foremost, future work should further address challenges with B0 and B1 inhomogeneity to take full advantage for the increased SNR at 7 T.     

Intravoxel incoherent motion magnetic resonance imaging for breast cancer: A comparison with molecular subtypes and histological grades

PurposeThe purpose of this paper is to investigate whether the IVIM parameters (D, D *, f) helps to determine the molecular subtypes and histological grades of breast cancer.MethodsFifty-one patients with breast cancer were included in the study. All subjects were examined by 3 T Magnetic Resonance Imaging (MRI). Diffusion-weighted imaging (DWI) was undertaken with 16 b-values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histopathological reports were reviewed to histological grade, histological type, and immunohistochemistry. IVIM parameters of tumors with different histological grades and molecular subtypes were compared.ResultsD* and f were significantly different between molecular subtypes (p = 0.019, p = 0.03 respectively). D* and f were higher in the HER-2 group and lower in Triple negative (−) group (D*:36.8 × 10⁻³ ± 5.3 × 10⁻³ mm²/s, f:29.5%, D*:29.8 × 10⁻³ ± 5.6 × 10⁻³ mm²/s, f:21.5% respectively). There was a significant difference in D* and f between HER-2 and Triple (−) subgroups (p = 0,028, p = 0.024, respectively). D* was also significantly different between the HER-2 group and the Luminal group (p = 0,041). While histological grades increase, D and f values tend to decrease, and D* tends to increase. While the Ki-67 index increases, D* and f values tend to increase, and D tend to decrease.ConclusionD* and f values measured with IVIM imaging were useful for assessing breast cancer molecular subtyping. IVIM imaging may be an alternative to breast biopsy for sub-typing of breast cancer with further research.     

Usefulness of diffusion derived vessel density computed from a simplified IVIM imaging protocol: An experimental study with rat biliary duct blockage induced liver fibrosis

ObjectivesLiver vessel density can be evaluated by DDVD (diffusion derived vessel density): DDVD_(b0b1) = Sb0/ROIarea0 – Sb1/ROIarea1, where Sb0 and Sb1 refer to the liver signal when b is 0 or 1 s/mm². Sb1 and ROIarea1 may be replaced by other b-values. With a rat biliary duct ligation (BDL) model, this study assesses the usefulness of liver DDVD computed from a simplified IVIM imaging protocol using b = 25 and b = 50 to replace b = 1 s/mm², alone and in combination with other IVIM parameters.MethodsMale Sprague-Dawley rats were used. The rat number was 5, 5, 5, and 3 respectively, for the timepoints of 7, 14, 21, 28 days post-BDL surgery. 12 rats had partial biliary duct recanalization performed after the rats had BDL for 7 days and then again followed-up for a mean of 14 days. Liver diffusion MRIs were acquired at 3.0 T with a b-value distribution of 0, 25, 50, 75, 100, 150, 300, 700, 1000 s/mm². DDVD_mean (control rats n = 6) was the mean of DDVD_(b0b25) and DDVD_(b0b50). IVIM fitting started from b = 0 s/mm² with segmented fitting and a threshold b of 50 s/mm² (n = 5 for control rats). Three 3-D spaces were constructed using a combination of the four diffusion parameters.ResultsThe control rats and BDL rats (n = 18) had a liver DDVD_mean of 84.0 ± 26.2 and 44.7 ± 14.4 au/pixel (p < 0.001). All 3-D spaces totally separated healthy livers and all fibrotic livers (n = 30, BDL rats and recanalization rats). The mean relative distance between healthy liver cluster and fibrotic liver cluster was 0.331 for PF, D_slow, and D_fast; 0.381 for PF, D_fast, and DDVD_mean; and 0.384 for PF, D_slow, and DDVD_mean.ConclusionA combination of PF, D_slow, and D_fast allows total separation of healthy livers and fibrotic livers and the integration of DDVD improved the separation.     

Perfusion parameters derived from MRI for preoperative prediction of IDH mutation and MGMT promoter methylation status in glioblastomas

PurposeTo investigate the feasibility for preoperative prediction of IDH mutation and MGMT promoter methylation status in glioblastomas(GBMs) by intravoxel incoherent motion(IVIM) and dynamic susceptibility contrast(DSC).MethodsPreoperative IVIM and DSC images of 71 patients(IDH mutation:45, IDH wildtype: 26; MGMT methylation: 31, MGMT unmethylation:40) with glioblastomas were analyzed retrospectively. Perfusion parameters including microcirculation perfusion coefficient(D*), perfusion fraction(f), cerebral blood volume(CBV) and cerebral blood flow(CBF) were measured. Corrected perfusion parameters containing corrected perfusion coefficient(ADC_perf) and simplified perfusion fraction(SPF) were from the simplified IVIM with 3 b values. Correlations among parameters were analyzed by Spearman correlation. All parameters were compared with Mann-Whitney U test. Univariate and multivariate logistic regression models were constructed. The receiver operating characteristic(ROC) curve was analyzed.ResultsThe IVIM parameters showed merely moderate correlations with CBV and showed no correlation with CBF. IDH mutation GBMs showed lower D*, ADC_perf, SPF, CBV and higher f than IDH wildtype GBMs(all p < 0.05). D* was the independent predictor for IDH mutation with the highest AUC of 0.912(95%CI: 0.821–0.966). The D*, ADC_perf, SPF and CBV of MGMT promoter methylation GBMs were lower than unmethylation GBMs while f was higher(all p < 0.05). Multivariate model showed the highest prediction efficacy for MGMT promoter methylation with an AUC of 0.915(95%CI: 0.824–0.968). The CBF was not useful in distinguishing IDH mutation and MGMT promoter methylation status(p = 0.055, 0.215).ConclusionIDH mutation and MGMT promoter methylation status in GBMs can be assessed effectively by IVIM and DSC. Besides, D* was the independent predictor of IDH mutation status.     

Geometric analysis of the b-dependent effects of Rician signal noise on diffusion tensor imaging estimates and determining an optimal b value

The optimal diffusion weighting (DW) factor, b, for use in diffusion tensor imaging (DTI) studies remains uncertain. In this study, the geometric relations of DW quantities are examined, in particular, the effects of Rician noise in the measured magnetic resonance signal. This geometric analysis is used to make theoretical predictions for selecting a b value to reduce the influence of noise. It is shown that the optimal b value for DTI studies in healthy human parenchyma is approximately b=1200 s mm⁻², with a simple relation given as well for a given expected apparent diffusion coefficient. Monte-Carlo simulations on sets of realistic DTI measures are then performed, verifying the optimal DW for minimizing estimate errors. The effects of noise on various DTI parameters such as anisotropy indices (fractional anisotropy and scaled relative anisotropy), mean diffusivity, radial diffusivity, eigenvalues and the direction of the first eigenvector are investigated as well.     

Apparent diffusion coefficient of line scan diffusion image in normal prostate and prostate cancer—comparison with single-shot echo planner image

Purpose

This retrospective study was designed to evaluate the apparent diffusion coefficient (ADC) of line scan diffusion images (LSDI) in normal prostate and prostate cancer. Single-shot echo planner images (SS-EPI) were used for comparison.

Materials and Methods

Twenty prostate tumors were examined by conventional MRI in 14 patients prior to radical prostatectomy. All patients were examined with a 1.5-T MR imager (Signa CV/i ver. 9.1 GE Medical System Milwaukee, WI, USA). Diffusion-weighted MR imaging (DWI) using LSDI was performed with a pelvic phased-array coil, with b values of 5 and 800 s/mm². DWI using SS-EPI was performed with a body coil, with b values of 0 and 800 s/mm². The ADCs of each sequence for 14 normal prostate and 20 prostate cancers were histopathologically assessed. Signal-to-noise ratio (SNR) on DWI was estimated and compared for each sequence.

Results

The mean ADCs (±S.D.) of normal peripheral zones (PZ), transition zones (TZ) and cancer (in 10⁻³ mm²/s) that used LSDI were 1.42±0.12, 1.23±0.10 and 0.79±0.19, respectively. Those that used SS-EPI were 1.76±0.26, 1.38±0.20 and 1.05±0.27, respectively. Using unpaired t test (P<.05), we found a significant difference in each sequence between normal tissue (both PZ and TZ) and the cancer. Paired t test (P<.05) also registered a significant difference between LSDI and SS-EPI. Mean SNR for DWI using LSDI was 16.49±5.03, while the DWI using SS-EPI was 18.85±9.26. The difference between the SNR of each sequence was not statistically significant by paired t test.

Conclusion

We found that ADCs using LSDI and SS-EPI showed similar tendencies in the same patients. However, in all regions, LSDI ADCs had smaller standard deviations than SS-EPI ADCs.