Intravoxel incoherent motion imaging of tumor microenvironment in locally advanced breast cancer

Comparing primary tumors and metastatic nodes in head and neck cancer using intravoxel incoherent motion imaging: a preliminary experience

OBJECTIVE

This study aimed to use intravoxel incoherent motion (IVIM) imaging for investigating differences between primary head and neck tumors and nodal metastases and to evaluate IVIM efficacy in predicting outcome.

METHODS

Sixteen patients with head and neck cancer underwent IVIM diffusion-weighted imaging on a 1.5-T magnetic resonance imaging scanner. The significance of parametric difference between primary tumors and metastatic nodes were tested. Probabilities of progression-free survival and overall survival were estimated using the Kaplan-Meier method.

RESULTS

In comparison with metastatic nodes, the primary tumors had significantly higher vascular volume fraction (f) (P < 0.0009) and lower diffusion coefficient (D) (P < 0.0002). Patients with lower SD for D had prolonged progression-free survival and overall survival (P < 0.05).

CONCLUSIONS

Pretreatment IVIM measures were feasible in investigating the physiologic differences between the 2 tumor tissues. After appropriate validation, these findings might be useful in optimizing treatment planning and improving patient care.

Tumor perfusion-related parameter of diffusion-weighted magnetic resonance imaging: correlation with histological microvessel density

PURPOSE

We obtained intravoxel incoherent motion (IVIM) parameters through biexponential analysis on diffusion-weighted MR imaging (DWI) using multiple b values. Correlation was evaluated between these parameters and histological microvessel density (MVD) for the possibility of noninvasive evaluation of MVD with DWI.

METHODS

Twenty-five nude mice with the HT29 colorectal cancer cells implanted were analyzed after undergoing DWI with multiple b values (0, 50, 100, 300, 500, 700, and 1000 s/mm(2)). Tissue diffusivity (D(t)), pseudo-diffusion coefficient (D(p)), and perfusion fraction (f(p)) were calculated using a biexponential analysis, and these parameters were correlated with MVD. The MVD was determined with the CD31 stain. For statistical analysis, Spearman's rank correlation was applied.

RESULTS

The mean value and correlation coefficient with MVD for each IVIM parameter were as follows: D(t)  = 0.98 ± 0.06 × 10(-3) mm(2)/s with r = 0.139 (P = 0.508); D(p) = 23.70 ± 7.94 × 10(-3) mm(2)/s with r = 0.782 (P < 0.001); and f(p) = 15.58 ± 5.7% with r = 0.749 (P < 0.001). D(p) and f(p) showed significant correlation with MVD, but D(t) did not.

CONCLUSION

The IVIM parameters, D(p) and f(p), on DWI might be used in the noninvasive evaluation of MVD.

Diffusion-weighted intravoxel incoherent motion imaging of renal tumors with histopathologic correlation

PURPOSE

The aim of this study was to use intravoxel incoherent motion diffusion-weighted imaging to discriminate subtypes of renal neoplasms and to assess agreement between intravoxel incoherent motion (perfusion fraction, fp) and dynamic contrast-enhanced magnetic resonance imaging (MRI) metrics of tumor vascularity.

SUBJECTS AND METHODS

In this Health Insurance Portability and Accountability Act-compliant, institutional review board-approved prospective study, 26 patients were imaged at 1.5-T MRI using dynamic contrast-enhanced MRI with high temporal resolution and diffusion-weighted imaging using 8 b values (range, 0-800 s/mm). Perfusion fraction (fp), tissue diffusivity (Dt), and pseudodiffusivity (Dp) were calculated using biexponential fitting of the diffusion data. Apparent diffusion coefficient (ADC) was calculated with monoexponential fit using 3 b values of 0, 400, and 800 s/mm. Dynamic contrast-enhanced data were processed with a semiquantitative method to generate model-free parameter cumulative initial area under the curve of gadolinium concentration at 60 seconds (CIAUC60). Perfusion fraction, Dt, Dp, ADC, and CIAUC60 were compared between different subtypes of renal lesions. Perfusion fraction was correlated with CIAUC60.

RESULTS

We examined 14 clear cell, 4 papillary, 5 chromophobe, and 3 cystic renal cell carcinomas (RCCs). Although fp had higher accuracy (area under the curve, 0.74) for a diagnosis of clear cell RCC compared with Dt or ADC, the combination of fp and Dt had the highest accuracy (area under the curve, 0.78). The combination of fp and Dt diagnosed papillary RCC and cystic RCC with 100% accuracy, and clear cell RCC and chromophobe RCC, with 86.5% accuracy. There was significant strong correlation between fp and CIAUC60 (r = 0.82; P < 0.001).

CONCLUSION

Intravoxel incoherent motion parameters fp and Dt can discriminate renal tumor subtypes. Perfusion fraction demonstrates good correlation with CIAUC60 and can assess degree of tumor vascularity without the use of exogenous contrast agent.

Characterization and therapy monitoring of head and neck carcinomas using diffusion-imaging-based intravoxel incoherent motion parameters-preliminary results

INTRODUCTION

Using the intravoxel incoherent motion (IVIM) model, diffusion-related coefficient (D) and perfusion-related parameter (f) can be measured. Here, we used IVIM imaging to characterize squamous cell carcinomas of head and neck (HNSCC) and evaluated its application in follow-up after nonsurgical organ preserving therapy.

METHODS

Twenty-two patients with locally advanced HNSCC (clinical stage III to IVb) were examined before treatment using eight different b values (b = 0, 50, 100, 150, 200, 250, 700, 800 s/mm(2)). All patients were followed for at least 7.5 months after conclusion of therapy. In 16 of these patients, follow-up MRI was available. Using the IVIM approach, f and D were extracted using a bi-exponential fit. For comparison, ADC maps were calculated.

RESULTS

The initial values of f before therapy were located between 5.9 % and 12.9 % (mean: 9.4 ± 2.4 %) except for two outliers (f = 17.9 % and 18.2 %). These two patients exclusively displayed poor initial treatment response. Overall, high initial f (13.1 ± 4.1 % vs. 9.1 ± 2.4 %) and ADC (1.17 ± 0.08 × 10(-3) mm(2)/s vs. 0.98 ± 0.19 × 10(-3) mm(2)/s) were associated with poor short term outcome (n = 6) after 7.5 months follow-up. D values before treatment were 0.98 × 10(-3) ± 0.18 mm(2)/s and ADC values were 1.03 × 10(-3) ± 0.18 mm(2)/s. At follow-up, in all primary responders, D (69 ± 52 %), f (65 ± 46 %), and ADC (68 ± 49%) increased.

CONCLUSIONS

Our preliminary evaluation indicates that an initial high f may predict poor prognosis in HNSCC. In responders, a significant increase of all IVIM parameters after therapy was demonstrated.

Intravoxel incoherent motion MR imaging for prostate cancer: an evaluation of perfusion fraction and diffusion coefficient derived from different b-value combinations

There has been a resurgent interest in intravoxel incoherent motion (IVIM) MR imaging to obtain perfusion as well as diffusion information on lesions, in which the diffusion was modeled as Gaussian diffusion. However, it was observed that this diffusion deviated from expected monoexponential decay at high b-values and the reported perfusion in prostate is contrary to the findings in dynamic contrast-enhanced (DCE) MRI studies and angiogenesis. Thus, this work is to evaluate the effect of different b-values on IVIM perfusion fractions (f) and diffusion coefficients (D) for prostate cancer detection. The results show that both parameters depended heavily on the b-values, and those derived without the highest b-value correlated best with the results from DCE-MRI studies; specifically, f was significantly elevated (7.2% vs. 3.7%) in tumors when compared with normal tissues, in accordance with the volume transfer constant (K(trans); 0.39 vs. 0.18 min(-1)) and plasma fractional volume (v(p) ; 8.4% vs. 3.4%). In conclusion, it is critical to choose an appropriate range of b-values in studies or include the non-Gaussian diffusion contribution to obtain unbiased IVIM measurements. These measurements could eliminate the need for DCE-MRI, which is especially relevant in patients who cannot receive intravenous gadolinium-based contrast media.

Measurement reproducibility of perfusion fraction and pseudodiffusion coefficient derived by intravoxel incoherent motion diffusion-weighted MR imaging in normal liver and metastases

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.

Reliable estimation of incoherent motion parametric maps from diffusion-weighted MRI using fusion bootstrap moves

Diffusion-weighted MRI has the potential to provide important new insights into physiological and microstructural properties of the body. The Intra-Voxel Incoherent Motion (IVIM) model relates the observed DW-MRI signal decay to parameters that reflect blood flow in the capillaries (D*), capillaries volume fraction (f), and diffusivity (D). However, the commonly used, independent voxel-wise fitting of the IVIM model leads to imprecise parameter estimates, which has hampered their practical usage. In this work, we improve the precision of estimates by introducing a spatially-constrained Incoherent Motion (IM) model of DW-MRI signal decay. We also introduce an efficient iterative "fusion bootstrap moves" (FBM) solver that enables precise parameter estimates with this new IM model. This solver updates parameter estimates by applying a binary graph-cut solver to fuse the current estimate of parameter values with a new proposal of the parameter values into a new estimate of parameter values that better fits the observed DW-MRI data. The proposals of parameter values are sampled from the independent voxel-wise distributions of the parameter values with a model-based bootstrap resampling of the residuals. We assessed both the improvement in the precision of the incoherent motion parameter estimates and the characterization of heterogeneous tumor environments by analyzing simulated and in vivo abdominal DW-MRI data of 30 patients, and in vivo DW-MRI data of three patients with musculoskeletal lesions. We found our IM-FBM reduces the relative root mean square error of the D* parameter estimates by 80%, and of the f and D parameter estimates by 50% compared to the IVIM model with the simulated data. Similarly, we observed that our IM-FBM method significantly reduces the coefficient of variation of parameter estimates of the D* parameter by 43%, the f parameter by 37%, and the D parameter by 17% compared to the IVIM model (paired Student's t-test, p<0.0001). In addition, we found our IM-FBM method improved the characterization of heterogeneous musculoskeletal lesions by means of increased contrast-to-noise ratio of 19.3%. The IM model and FBM solver combined, provide more precise estimate of the physiological model parameter values that describing the DW-MRI signal decay and a better mechanism for characterizing heterogeneous lesions than does the independent voxel-wise IVIM model.

Motion correction of multi-b-value diffusion-weighted imaging in the liver

RATIONALE AND OBJECTIVES

Motion artifacts are a significant source of error in the acquisition and quantification of parameters from multi-b-value diffusion-weighted imaging (DWI). The objective of this article is to present a reliable method to reduce motion-related artifacts during free-breathing at higher b-values when signal levels are low.

MATERIALS AND METHODS

Twelve patients referred for magnetic resonance imaging of the liver underwent a clinical magnetic resonance imaging examination of the abdominal region that included DWI. Conventional single-shot spin-echo echo planar imaging acquisitions of the liver during free breathing were repeated in a "time-resolved" manner during a single acquisition to obtain data for multi-b-value analysis, alternating between low and high b-values. Image registration using a normalized mutual information similarity measure was used to correct for spatial misalignment of diffusion-weighted volumes caused by motion. Registration error was estimated indirectly by comparing the normalized root-mean-square error (NRMSE) values of data fitted to the biexponential intra-voxel incoherent motion model before and after motion correction. Regions of interest (ROIs) were selected in the liver close to the surface of the liver and close to internal structures such as large bile ducts and blood vessels.

RESULTS

For the 12 patient datasets, the mean NRMSE value for the motion-corrected ROIs (0.38 ± 0.16) was significantly lower than the mean NRMSE values for the non-motion-corrected ROIs (0.41 ± 0.13) (P < .05). In cases where there was substantial respiratory motion during the acquisition, visual inspection verified that the algorithm markedly improved alignment of the liver contours between frames.

CONCLUSIONS

The proposed method addresses motion-related artifacts to increase robustness in multi-b-value acquisitions.

Quantitative analysis of diffusion-weighted magnetic resonance imaging in malignant breast lesions using different b value combinations

Objectives

To explore how apparent diffusion coefficients (ADCs) in malignant breast lesions are affected by selection of b values in the monoexponential model and to compare ADCs with diffusion coefficients (Ds) obtained from the biexponential model.

Methods

Twenty-four women (mean age 51.3 years) with locally advanced breast cancer were included in this study. Pre-treatment diffusion-weighted magnetic resonance imaging was performed using a 1.5-T system with b values of 0, 50, 100, 250 and 800 s/mm². Thirteen different b value combinations were used to derive individual monoexponential ADC maps. All b values were used in the biexponential model.

Results

Median ADC (including all b values) and D were 1.04 × 10^-3 mm²/s (range 0.82–1.61 × 10^-3 mm²/s) and 0.84 × 10^-3 mm²/s (range 0.17–1.56 × 10^-3 mm²/s), respectively. There was a strong positive correlation between ADCs and Ds. For clinically relevant b value combinations, maximum deviation between ADCs including and excluding low b values (<100 s/mm²) was 11.8 %.

Conclusion

Selection of b values strongly affects ADCs of malignant breast lesions. However, by excluding low b values, ADCs approach biexponential Ds, demonstrating that microperfusion influences the diffusion signal. Thus, care should be taken when ADC calculation includes low b values.

Key Points

• Diffusion-weighted sequences are increasingly used in breast magnetic resonance imaging

• Diffusion-weighting (b) values strongly influence apparent diffusion coefficients of malignant lesions

• Exclusion of low b values reduces the apparent diffusion coefficient

• Flow-insensitive monoexponential apparent diffusion coefficients approach biexponential diffusion coefficients

Extension of the intravoxel incoherent motion model to non-gaussian diffusion in head and neck cancer

PURPOSE

To extend the intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) model to restricted diffusion and to simultaneously quantify the perfusion and restricted diffusion parameters in neck nodal metastases.

MATERIALS AND METHODS

The non-gaussian (NG)-IVIM model was developed and tested on diffusion-weighted MRI data collected on a 1.5-Tesla MRI scanner from eight patients with head and neck cancer. Voxel-wise parameter quantification was performed by using a noise-rectified least-square fitting method. The NG-IVIM, IVIM, Kurtosis, and ADC (apparent diffusion coefficient) models were used for comparison. For each voxel, within the metastatic node, the optimal model was determined using the Bayesian Information Criterion. The voxel percentage preferred by each model was calculated and the optimal model map was generated. Monte Carlo simulations were performed to evaluate the accuracy and precision dependency of the new model.

RESULTS

For the eight neck nodes, the range of voxel percentage preferred by the NG-IVIM model was 2.3-79.3%. The optimal modal maps showed heterogeneities within the tumors. The Monte Carlo simulations demonstrated that the accuracy and precision of the NG-IVIM model improved by increasing signal-to-noise ratio and b value.

CONCLUSION

The NG-IVIM model characterizes perfusion and restricted diffusion simultaneously in neck nodal metastases.

Assessment of hepatocellular carcinoma using apparent diffusion coefficient and diffusion kurtosis indices: preliminary experience in fresh liver explants

OBJECTIVES

The objective was to perform ex vivo evaluation of non-Gaussian diffusion kurtosis imaging (DKI) for assessment of hepatocellular carcinoma (HCC), including presence of treatment-related necrosis, using fresh liver explants.

METHODS

Twelve liver explants underwent 1.5-T magnetic resonance imaging using a DKI sequence with maximal b-value of 2000 s/mm(2). A standard monoexponential fit was used to calculate apparent diffusion coefficient (ADC), and a non-Gaussian kurtosis fit was used to calculate K, a measure of excess kurtosis of diffusion, and D, a corrected diffusion coefficient accounting for this non-Gaussian behavior. The mean value of these parameters was measured for 16 HCCs based upon histologic findings. For each metric, HCC-to-liver contrast was calculated, and coefficient of variation (CV) was computed for voxels within the lesion as an indicator of heterogeneity. A single hepatopathologist determined HCC necrosis and cellularity.

RESULTS

The 16 HCCs demonstrated intermediate-to-substantial excess diffusional kurtosis, and mean corrected diffusion coefficient D was 23% greater than mean ADC (P=.002). HCC-to-liver contrast and CV of HCC were greater for K than ADC or D, although these differences were significant only for CV of HCCs (P≤.046). ADC, D and K all showed significant differences between non-, partially and completely necrotic HCCs (P≤.004). Among seven nonnecrotic HCCs, cellularity showed a strong inverse correlation with ADC (r=-0.80), a weaker inverse correlation with D (-0.24) and a direct correlation with K (r=0.48).

CONCLUSIONS

We observed non-Gaussian diffusion behavior for HCCs ex vivo; this DKI model may have added value in HCC characterization in comparison with a standard monoexponential model of diffusion-weighted imaging.

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(p)D(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.

Prostate cancer: feasibility and preliminary experience of a diffusional kurtosis model for detection and assessment of aggressiveness of peripheral zone cancer

PURPOSE

To assess the feasibility of diffusional kurtosis (DK) imaging for distinguishing benign from malignant regions, as well as low- from high-grade malignant regions, within the peripheral zone (PZ) of the prostate in comparison with standard diffusion-weighted (DW) imaging.

MATERIALS AND METHODS

The institutional review board approved this retrospective HIPAA-compliant study and waived informed consent. Forty-seven patients with prostate cancer underwent 3-T magnetic resonance imaging by using a pelvic phased-array coil and DW imaging (maximum b value, 2000 sec/mm2). Parametric maps were obtained for apparent diffusion coefficient (ADC); the metric DK (K), which represents non-Gaussian diffusion behavior; and corrected diffusion (D) that accounts for this non-Gaussianity. Two radiologists reviewed these maps and measured ADC, D, and K in sextants positive for cancer at biopsy. Data were analyzed by using mixed-model analysis of variance and receiver operating characteristic curves.

RESULTS

Seventy sextants exhibited a Gleason score of 6; 51 exhibited a Gleason score of 7 or 8. K was significantly greater in cancerous sextants than in benign PZ (0.96±0.24 vs 0.57±0.07, P<.001), as well as in cancerous sextants with higher rather than lower Gleason score (1.05±0.26 vs 0.89±0.20, P<.001). K showed significantly greater sensitivity for differentiating cancerous sextants from benign PZ than ADC or D (93.3% vs 78.5% and 83.5%, respectively; P<.001), with equal specificity (95.7%, P>.99). K exhibited significantly greater sensitivity for differentiating sextants with low- and high-grade cancer than ADC or D (68.6% vs 51.0% and 49.0%, respectively; P≤.004) but with decreased specificity (70.0% vs 81.4% and 82.9%, respectively; P≤.023). K had significantly greater area under the curve for differentiating sextants with low- and high-grade cancer than ADC (0.70 vs 0.62, P=.010). Relative contrast between cancerous sextants and benign PZ was significantly greater for D or K than ADC (0.25±0.14 and 0.24±0.13, respectively, vs 0.18±0.10; P<.001).

CONCLUSION

Preliminary findings suggest increased value for DK imaging compared with standard DW imaging in prostate cancer assessment.

Diffusion weighted imaging of the normal breast: reproducibility of apparent diffusion coefficient measurements and variation with menstrual cycle and menopausal status

OBJECTIVES

To establish the reproducibility of apparent diffusion coefficient (ADC) measurements in normal fibroglandular breast tissue and to assess variation in ADC values with phase of the menstrual cycle and menopausal status.

METHODS

Thirty-one volunteers (13 premenopausal, 18 postmenopausal) underwent magnetic resonance twice (interval 11-22 days) using diffusion-weighted MRI. ADC(total) and a perfusion-insensitive ADC(high) (omitting b = 0) were calculated. Reproducibility and inter-observer variability of mean ADC values were assessed. The difference in mean ADC values between the two phases of the menstrual cycle and the postmenopausal breast were evaluated.

RESULTS

ADC(total) and ADC(high) showed good reproducibility (r% = 17.6, 22.4). ADC(high) showed very good inter-observer agreement (kappa = 0.83). The intraclass correlation coefficients (ICC) were 0.93 and 0.91. Mean ADC values were significantly lower in the postmenopausal breast (ADC(total) 1.46 ± 0.3 × 10(-3) mm(2)/s, ADC(high) 1.33 ± 0.3 × 10(-3) mm(2)/s) compared with the premenopausal breast (ADC(total) 1.84 ± 0.26 × 10(-3) mm(2)/s, ADC(high) 1.77 ± 0.26 × 10(-3) mm(2)/s; both P < 0.001). No significant difference was seen in ADC values in relation to menstrual cycle (ADC(total) P = 0.2, ADC(high) P = 0.24) or between postmenopausal women taking or not taking oestrogen supplements (ADC(total) P = 0.6, ADC(high) P = 0.46).

CONCLUSIONS

ADC values in fibroglandular breast tissue are reproducible. Lower ADC values within the postmenopausal breast may reduce diffusion-weighted contrast and have implications for accurately detecting tumours.

KEY POINTS

• ADC values from fibroglandular breast tissue are measured reproducibly by multiple observers. • Mean ADC values were significantly lower in postmenopausal than premenopausal breast tissue. • Mean ADC values did not vary significantly with menstrual cycle. • Low postmenopausal ADC values may hinder tumour detection on DW-MRI.