In vivo assessment of optimal b-value range for perfusion-insensitive apparent diffusion coefficient imaging

Intravoxel Incoherent Motion Quantification Dependent on Measurement SNR and Tissue Perfusion: A Simulation Study

Background

The intravoxel incoherent motion (IVIM) model extracts both functional and structural information of a tissue using motion-sensitizing gradients.

Objective

The Objective of the present work is to investigate the impact of signal to noise ratio (SNR) and physiologic conditions on the validity of IVIM parameters.

Material and Methods

This study is a simulation study, modeling IVIM at a voxel, and also done 10,000 times for every single simulation. Complex noises with various standard deviations were added to signal in-silico to investigate SNR effects on output validity. Besides, some blood perfusion situations for different tissues were considered based on their physiological range to explore the impacts of blood fraction at each voxel on the validity of the IVIM outputs. Coefficient variation (CV) and bias of the estimations were computed to assess the validity of the IVIM parameters.

Results

This study has shown that the validity of IVIM output parameters highly depends on measurement SNR and physiologic characteristics of the studied organ.

Conclusion

IVIM imaging could be useful if imaging parameters are correctly selected for each specific organ, considering hardware limitations.

Self-supervised IVIM DWI parameter estimation with a physics based forward model

PURPOSE

To assess the robustness and repeatability of intravoxel incoherent motion model (IVIM) parameter estimation for the diffusion-weighted MRI in the abdominal organs under the constraints of noisy diffusion signal using a novel neural network method.

METHODS

Clinically acquired abdominal scans of Crohn's disease patients were retrospectively analyzed with regions segmented in the kidney cortex, spleen, liver, and bowel. A novel IVIM parameter fitting method based on the principle of a physics guided self-supervised convolutional neural network that does not require reference parameter estimates for training was compared to a conventional non-linear least squares (NNLS) algorithm, and a voxelwise trained artificial neural network (ANN).

RESULTS

Results showed substantial increase in parameter robustness to the noise corrupted signal. In an intra-session repeatability experiment, the proposed method showed reduced coefficient of variation (CoV) over multiple acquisitions in comparison to conventional NLLS method and comparable performance to ANN. The use of D and f estimates from the proposed method led to the smallest misclassification error in linear discriminant analysis for characterization between normal and abnormal Crohn's disease bowel tissue. The fitting of D∗ parameter remains to be challenging.

CONCLUSION

The proposed method yields robust estimates of D and f IVIM parameters under the constraints of noisy diffusion signal. This indicates a potential for the use of the proposed method in conjunction with accelerated DW-MRI acquisition strategies, which would typically result in lower signal to noise ratio.

Deep learning-based automatic delineation of anal cancer gross tumour volume: a multimodality comparison of CT, PET and MRI

BACKGROUND

Accurate target volume delineation is a prerequisite for high-precision radiotherapy. However, manual delineation is resource-demanding and prone to interobserver variation. An automatic delineation approach could potentially save time and increase delineation consistency. In this study, the applicability of deep learning for fully automatic delineation of the gross tumour volume (GTV) in patients with anal squamous cell carcinoma (ASCC) was evaluated for the first time. An extensive comparison of the effects single modality and multimodality combinations of computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) have on automatic delineation quality was conducted.

MATERIAL AND METHODS

18F-fluorodeoxyglucose PET/CT and contrast-enhanced CT (ceCT) images were collected for 86 patients with ASCC. A subset of 36 patients also underwent a study-specific 3T MRI examination including T2- and diffusion-weighted imaging. The resulting two datasets were analysed separately. A two-dimensional U-Net convolutional neural network (CNN) was trained to delineate the GTV in axial image slices based on single or multimodality image input. Manual GTV delineations constituted the ground truth for CNN model training and evaluation. Models were evaluated using the Dice similarity coefficient (Dice) and surface distance metrics computed from five-fold cross-validation.

RESULTS

CNN-generated automatic delineations demonstrated good agreement with the ground truth, resulting in mean Dice scores of 0.65-0.76 and 0.74-0.83 for the 86 and 36-patient datasets, respectively. For both datasets, the highest mean Dice scores were obtained using a multimodal combination of PET and ceCT (0.76-0.83). However, models based on single modality ceCT performed comparably well (0.74-0.81). T2W-only models performed acceptably but were somewhat inferior to the PET/ceCT and ceCT-based models.

CONCLUSION

CNNs provided high-quality automatic GTV delineations for both single and multimodality image input, indicating that deep learning may prove a versatile tool for target volume delineation in future patients with ASCC.

Task-driven assessment of experimental designs in diffusion MRI: A computational framework

This paper proposes a task-driven computational framework for assessing diffusion MRI experimental designs which, rather than relying on parameter-estimation metrics, directly measures quantitative task performance. Traditional computational experimental design (CED) methods may be ill-suited to experimental tasks, such as clinical classification, where outcome does not depend on parameter-estimation accuracy or precision alone. Current assessment metrics evaluate experiments' ability to faithfully recover microstructural parameters rather than their task performance. The method we propose addresses this shortcoming. For a given MRI experimental design (protocol, parameter-estimation method, model, etc.), experiments are simulated start-to-finish and task performance is computed from receiver operating characteristic (ROC) curves and associated summary metrics (e.g. area under the curve (AUC)). Two experiments were performed: first, a validation of the pipeline's task performance predictions against clinical results, comparing in-silico predictions to real-world ROC/AUC; and second, a demonstration of the pipeline's advantages over traditional CED approaches, using two simulated clinical classification tasks. Comparison with clinical datasets validates our method's predictions of (a) the qualitative form of ROC curves, (b) the relative task performance of different experimental designs, and (c) the absolute performance (AUC) of each experimental design. Furthermore, we show that our method outperforms traditional task-agnostic assessment methods, enabling improved, more useful experimental design. Our pipeline produces accurate, quantitative predictions of real-world task performance. Compared to current approaches, such task-driven assessment is more likely to identify experimental designs that perform well in practice. Our method is not limited to diffusion MRI; the pipeline generalises to any task-based quantitative MRI application, and provides the foundation for developing future task-driven end-to end CED frameworks.

ADC-Based Stratification of Molecular Glioma Subtypes Using High b-Value Diffusion-Weighted Imaging

PURPOSE

To investigate the diagnostic performance of in vivo ADC-based stratification of integrated molecular glioma grades.

MATERIALS AND METHODS

Ninety-seven patients with histopathologically confirmed glioma were evaluated retrospectively. All patients underwent pre-interventional MRI-examination including diffusion-weighted imaging (DWI) with implemented b-values of 500, 1000, 1500, 2000, and 2500 s/mm². Apparent Diffusion Coefficient (ADC), Mean Kurtosis (MK), and Mean Diffusivity (MD) maps were generated. The average values were compared among the molecular glioma subgroups of IDH-mutant and IDH-wildtype astrocytoma, and 1p/19q-codeleted oligodendroglioma. One-way ANOVA with post-hoc Games-Howell correction compared average ADC, MD, and MK values between molecular glioma groups. A Receiver Operating Characteristic (ROC) analysis determined the area under the curve (AUC).

RESULTS

Two b-value-dependent ADC-based evaluations presented statistically significant differences between the three molecular glioma sub-groups (p < 0.001, respectively).

CONCLUSIONS

High-b-value ADC from preoperative DWI may be used to stratify integrated molecular glioma subgroups and save time compared to diffusion kurtosis imaging. Higher b-values of up to 2500 s/mm² may present an important step towards increasing diagnostic accuracy compared to standard DWI protocol.

Role of Diffusion-Weighted Magnetic Resonance Imaging in the Diagnosis and Grading of Hepatic Steatosis in Patients With Non-alcoholic Fatty Liver Disease: Comparison With Ultrasonography and Magnetic Resonance Spectroscopy

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is becoming the most common cause of cirrhosis. Although magnetic resonance spectroscopy (MRS) is considered the gold standard, it has a few limitations. The role of diffusion-weighted imaging (DWI), which is a simpler sequence, in the diagnosis and grading of fatty liver is not well studied. The aim of the study was to investigate the value of DWI in the diagnosis and grading of hepatic steatosis in patients with NAFLD.

MATERIALS AND METHODS

Fifty-one adults (mean age: 38 years; 28 men, 23 women) with NAFLD, diagnosed clinically and by ultrasonography (USG), were included in the study after obtaining informed consent and approval from the institute ethics committee. USG was performed for grading of hepatic steatosis in all patients, followed by magnetic resonance imaging with DWI and MRS, on a 1.5T scanner. The mean apparent diffusion coefficient (ADC) values and proton density fat fraction (PDFF) were calculated, and MRS was used as the gold standard. The mean ADC values were compared with the PDFF and USG grades.

RESULTS

There was a weak correlation between ADC values and PDFF (r = -0.36; P < 0.05). In addition, there was a weak correlation between the ADC values of the liver and USG grade (r = -0.34; P < 0.05). However, an overall increase in USG grades and PDFF was associated with decrease in the mean ADC value (P < 0.001).

CONCLUSION

DWI is not accurate in the diagnosis and grading of hepatic steatosis in patients with NAFLD. However, a significant increase in fat deposition in the liver lowers the ADC values.

B-Value Optimization in the Estimation of Intravoxel Incoherent Motion Parameters in Patients with Cervical Cancer

Objective

This study aimed to find the optimal number of b-values for intravoxel incoherent motion (IVIM) imaging analysis, using simulated and in vivo data from cervical cancer patients.

Materials and Methods

Simulated data were generated using literature pooled means, which served as reference values for simulations. In vivo data from 100 treatment-naïve cervical cancer patients with IVIM imaging (13 b-values, scan time, 436 seconds) were retrospectively reviewed. A stepwise b-value fitting algorithm calculated optimal thresholds. Feed forward selection determined the optimal subsampled b-value distribution for biexponential IVIM fitting, and simplified IVIM modeling using monoexponential fitting was attempted. IVIM parameters computed using all b-values served as reference values for in vivo data.

Results

In simulations, parameters were accurately estimated with six b-values, or three b-values for simplified IVIM, respectively. In vivo data showed that the optimal threshold was 40 s/mm² for patients with squamous cell carcinoma and a subsampled acquisition of six b-values (scan time, 198 seconds) estimated parameters were not significantly different from reference parameters (individual parameter error rates of less than 5%). In patients with adenocarcinoma, the optimal threshold was 100 s/mm², but an optimal subsample could not be identified. Irrespective of the histological subtype, only three b-values were needed for simplified IVIM, but these parameters did not retain their discriminative ability.

Conclusion

Subsampling of six b-values halved the IVIM scan time without significant losses in accuracy and discriminative ability. Simplified IVIM is possible with only three b-values, at the risk of losing diagnostic information.

Utility of diffusion weighted imaging with the quantitative apparent diffusion coefficient in diagnosing residual or recurrent hepatocellular carcinoma after transarterial chemoembolization: a meta-analysis

Background

Accurate and early diagnosis of residual tumors or intrahepatic recurrences after TACE is critically needed for determining the success of treatments and for guiding subsequent therapeutic planning. This meta-analysis was performed to assess the efficacy of diffusion weighted imaging (DWI) with the quantitative apparent diffusion coefficient (ADC) value in diagnosing residual or recurrent hepatocellular carcinoma after transarterial chemoembolization (TACE).

Materials and methods

A comprehensive literature search of PubMed, Embase, Web of Science, Scopus and the Cochrane Library database, from inception to July 2019, was conducted to select original studies on diagnosing residual or recurrent HCCs after TACE using DWI sequence with its ADC value. Two researchers independently chose study, extracted data, conducted meta-analysis, and evaluated methodological quality according to Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool.

Results

Twelve studies comprising 624 patients and 712 tumors were finally included. The pooled sensitivity, specificity and AUC value of DWI in diagnosing residual or recurrent HCCs after TACE were 85% (95%CI: 74–92%), 83% (95%CI: 75–88%) and 0.90 (95%CI: 0.87–0.92), respectively. Residual or recurrent HCCs have significantly lower ADC value than necrotic tumors (MD = -0.48, 95%CI: − 0.69~ − 0.27, P < 0.01).

Conclusion

This study demonstrated that DWI performed better in diagnosing residual or recurrent HCCs after TACE, and ADC value may serve as alternatives for further evaluation of residual or recurrent leisions in HCC patients after TACE.

Effect of intravoxel incoherent motion on diffusion parameters in normal brain

At very low diffusion weighting the diffusion MRI signal is affected by intravoxel incoherent motion (IVIM) caused by dephasing of magnetization due to incoherent blood flow in capillaries or other sources of microcirculation. While IVIM measurements at low diffusion weightings have been frequently used to investigate perfusion in the body as well as in malignant tissue, the effect and origin of IVIM in normal brain tissue is not completely established. We investigated the IVIM effect on the brain diffusion MRI signal in a cohort of 137 radiologically-normal patients (62 male; mean age = 50.2 ± 17.8, range = 18 to 94). We compared the diffusion tensor parameters estimated from a mono-exponential fit at b = 0 and 1000 s/mm² versus at b = 250 and 1000 s/mm². The asymptotic fitting method allowed for quantitative assessment of the IVIM signal fraction f* in specific brain tissue and regions. Our results show a mean (median) percent difference in the mean diffusivity of about 4.5 (4.9)% in white matter (WM), about 7.8 (8.7)% in cortical gray matter (GM), and 4.3 (4.2)% in thalamus. Corresponding perfusion fraction f* was estimated to be 0.033 (0.032) in WM, 0.066 (0.065) in cortical GM, and 0.033 (0.030) in the thalamus. The effect of f* with respect to age was found to be significant in cortical GM (Pearson correlation ρ ​= ​0.35, p ​= ​3*10^-5) and the thalamus (Pearson correlation ρ = 0.20, p = 0.022) with an average increase in f* of 5.17*10^-4/year and 3.61*10^-4/year, respectively. Significant correlations between f* and age were not observed for WM, and corollary analysis revealed no effect of gender on f*. Possible origins of the IVIM effect in normal brain tissue are discussed.

PTEN Expression in Prostate Cancer: Relationship With Clinicopathologic Features and Multiparametric MRI Findings

OBJECTIVE. The objective of our study was to investigate whether phosphatase and tensin homolog (PTEN) expression is associated with clinicopathologic features and multiparametric MRI findings in prostate cancer. MATERIALS AND METHODS. Forty-three patients with prostate cancer who underwent radical prostatectomy were included. Index tumor was identified on pretreatment MRI and delineated in the area that correlated best with histopathology results. The apparent diffusion coefficient (ADC) from DWI and pharmacokinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) using the extended Tofts model (K^trans, k_ep, v_e, and v_p) within the tumor were estimated. The following clinicopathologic parameters were assessed: pretreatment serum levels of prostate-specific antigen, disseminated tumor cell status, age, Gleason score, tumor size, extraprostatic extension (EPE), tumor location, and lymph node metastases. Gene expression profiles were acquired in biopsies from the tumor using bead arrays, and validated using reverse transcription quantitative polymerase chain reaction (RT-qPCR) on a different part of the biopsy. RESULTS. Based on bead arrays (p = 0.006) and RT-qPCR (p = 0.03) data, a significantly lower ADC was found in tumors with low PTEN expression. Moreover, PTEN expression was negatively associated with lymph node metastases (bead arrays, p = 0.008; RT-qPCR, p < 0.001). A weak but significant association between PTEN expression, EPE (p = 0.048), and Gleason score (p = 0.028) was revealed on bead arrays. ADC was negatively correlated with Gleason score (p = 0.001) and tumor size (p = 0.023). No association among DCE parameters, PTEN expression, and clinicopathologic features was found. CONCLUSION. ADC derived from DWI may be useful in selecting patients with potentially aggressive tumor caused by PTEN deficiency.

MR Imaging of Pediatric Musculoskeletal Tumors:: Recent Advances and Clinical Applications

Pediatric musculoskeletal tumors comprise approximately 10% of childhood neoplasms, and MR imaging has been used as the imaging evaluation standard for these tumors. The role of MR imaging in these cases includes identification of tumor origin, tissue characterization, and definition of tumor extent and relationship to adjacent structures as well as therapeutic response in posttreatment surveillance. Technical advances have enabled quantitative evaluation of biochemical changes in tumors. This article reviews recent updates to MR imaging of pediatric musculoskeletal tumors, focusing on advanced MR imaging techniques and providing information on the relevant physics of these techniques, clinical applications, and pitfalls.

Developing quantitative MRI parameters to characterize host response and tissue ingrowth into collagen scaffolds

The in vivo evaluation of soft biomaterial implant remodeling routinely requires the surgical removal of the implant for subsequent histological assessment of tissue ingrowth and scaffold remodeling. This approach is very resource intensive, often destructive, and imposes practical limitations on how effectively these materials can be evaluated. MRI has the potential to non-invasively monitor the remodeling of implanted collagen scaffolds in real time. This study investigated the development of a model system to characterize the cellular infiltration, void area fraction, and angiogenesis in collagen scaffold implants using T₂ relaxation time and apparent diffusion coefficient (ADC) maps along with conventional histological techniques. Initial correlations found statistically significant relationships between the MRI and histological parameters for various regions of the implanted sponges: T₂ versus cell density (r ≈ -0.83); T₂ versus void area fraction (r ≈ +0.78); T₂ versus blood vessel density (r ≈ +0.95); ADC versus cell density (r ≈ -0.77); and ADC versus void area fraction (r ≈ +0.84). This suggests that MRI is sensitive to specific remodeling parameters and has the potential to serve as a non-invasive tool to monitor the remodeling of implanted collagen scaffolds, and to ultimately assess the ability of these scaffolds to regenerate the functional properties of damaged tissues such as tendons, ligaments, skin or skeletal muscle.

Modulating the water channel AQP4 alters miRNA expression, astrocyte connectivity and water diffusion in the rodent brain

Aquaporins (AQPs) facilitate water diffusion through the plasma membrane. Brain aquaporin-4 (AQP4) is present in astrocytes and has critical roles in normal and disease physiology. We previously showed that a 24.9% decrease in AQP4 expression after in vivo silencing resulted in a 45.8% decrease in tissue water mobility as interpreted from magnetic resonance imaging apparent diffusion coefficients (ADC). Similar to previous in vitro studies we show decreased expression of the gap junction protein connexin 43 (Cx43) in vivo after intracortical injection of siAQP4 in the rat. Moreover, siAQP4 induced a loss of dye-coupling between astrocytes in vitro, further demonstrating its effect on gap junctions. In contrast, silencing of Cx43 did not alter the level of AQP4 or water mobility (ADC) in the brain. We hypothesized that siAQP4 has off-target effects on Cx43 expression via modification of miRNA expression. The decreased expression of Cx43 in siAQP4-treated animals was associated with up-regulation of miR224, which is known to target AQP4 and Cx43 expression. This could be one potential molecular mechanism responsible for the effect of siAQP4 on Cx43 expression, and the resultant decrease in astrocyte connectivity and dramatic effects on ADC values and water mobility.

Diffusion-weighted imaging of hyperpolarized [13 C]urea in mouse liver

PURPOSE

To compare the apparent diffusion coefficient (ADC) of hyperpolarized (HP) [13 C,15 N]urea to the ADC of endogenous water in healthy and fibrotic mouse liver.

MATERIALS AND METHODS

ADC measurements for water and [13 C]urea were made in agarose phantoms at 14.1T. Next, the ADC of water and injected HP [13 C,15 N]urea were measured in eight CD1 mouse livers before and after induction of liver fibrosis using CCl4 . Liver fibrosis was quantified pathologically using the modified Brunt fibrosis score and compared to the measured ADC of water and urea.

RESULTS

In cell-free phantoms with 12.5% agarose, water ADC was nearly twice the ADC of urea (1.93 × 10-3 mm2 /s vs. 1.00 × 10-3 mm2 /s). The mean ADC values of water and [13 C,15 N]urea in healthy mouse liver (±SD) were nearly identical [(0.75 ± 0.11) × 10-3 mm2 /s and (0.75 ± 0.22) × 10-3 mm2 /s, respectively]. Mean water and [13 C,15 N]urea ADC values in fibrotic liver (±SD) were (0.84 ± 0.22) × 10-3 mm2 /s and (0.75 ± 0.15) × 10-3 mm2 /s, respectively. Neither water nor urea ADCs were statistically different in the fibrotic livers compared to baseline (P = 0.14 and P = 0.99, respectively). Water and urea ADCs were positively correlated at baseline (R2  = 0.52 and P = 0.045) but not in fibrotic livers (R2  = 0.23 and P = 0.23).

CONCLUSION

ADC of injected hyperpolarized urea in healthy liver reflects a smaller change as compared to free solution than ADC of water. This may reflect differences in cellular compartmentalization of the two compounds. No significant change in ADC of either water or urea were observed in relatively mild stages of liver fibrosis.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:141-151.

Effect of Perfusion on Diffusion Kurtosis Imaging Estimates for In Vivo Assessment of Integrated 2016 WHO Glioma Grades : A Cross-Sectional Observational Study

PURPOSE

To assess the role of perfusion-related signal decay on diffusion kurtosis imaging (DKI) estimates for in vivo stratification of glioma according to the integrated approach of the 2016 World Health Organization classification of tumors of the central nervous system (2016 CNS WHO).

METHODS

In this study 77 patients with histopathologically confirmed glioma were retrospectively assessed between January 2013 and February 2017 in a prospective trial. Mean kurtosis (MK) and mean diffusivity (MD) metrics from DKI were assessed by two physicians blinded to the study from a volume of interest around the entire solid tumor. Wilcoxon's signed-rank test compared perfusion-biased and perfusion-corrected MK (MK_pb and MK_pc) and MD (MD_pb, MD_pc) values. One-way ANOVA was used to compare MK_pb&pc and MD_pb&pc values between 2016 WHO glioma grades. Spearman's correlation coefficient was used to correlate them with 2016 WHO glioma grades. Receiver operating characteristic (ROC) analysis was performed on MK_pb&pc and MD_pb&pc for the significant results.

RESULTS

The MK_pc values were significantly higher than MK_pb values (p < 0.001), whereas MD_pc values were significantly lower than MD_pb values (p < 0.001). For stratifying gliomas, MK_pb values (ROC AUC range, 0.818-0.979) showed a higher diagnostic performance than MK_pc values (ROC AUC range, 0.773-0.975), whereas MD_pb values (ROC AUC range, 0.744-0.928) showed less diagnostic performance than MD_pc values (ROC AUC range, 0.753-0.934). The diagnostic accuracy of MK_pb was 80.0%.

CONCLUSION

The MK and MD estimates of DKI are influenced by microcapillary blood perfusion; however, taking the effect of perfusion on DKI metrics into account does not substantially impact their overall diagnostic performance in classifying glioma according to the 2016 CNS WHO.

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.

Diagnostic value of combined diffusion-weighted imaging with dynamic contrast enhancement MRI in differentiating malignant from benign bone lesions

AIM

To determine the diagnostic value of combined diffusion-weighted imaging (DWI) with dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) in differentiating malignant from benign bone lesions.

MATERIALS AND METHODS

DWI and DCE-MRI were performed in 36 patients (14 were benign and 22 were malignant). The mean apparent diffusion coefficient (ADC) values and signal enhanced extent (SEE), slope value, and time-signal intensity curve (TIC) type were recorded by two observers. Between-group comparison was made using the independent sample t-test and receiver-operating characteristic (ROC) analysis.

RESULTS

There was a significant difference between the mean ADC value of the benign ([1.75±0.50]×10^-3 mm²/s) and malignant ([1.11±0.47]×10^-3 mm²/s) groups (p=0.001). The threshold ADC value of ≤1.10×10^-3 mm²/s resulted in a sensitivity of 77.3%, a specificity of 92.9%, and an accuracy of 85.1%. A type III curve was found in 23 cases (21 malignant and two benign), a type II curve was seen in six cases (one malignant and five benign), and a type I curve in seven cases (all were benign). The SEE and slope values in the benign and malignant groups were 227.96±172.08, 325.60±125.86 (p=0.058); 0.97±0.67%/s, 3.19±3.20%/s (p=0.016), respectively. ROC analysis showed a sensitivity of 95.5%, a specificity of 85.7%, and an accuracy of 90.6% for malignancy, based on a slope cut-off value of >1.46%/s. Combining ADC and slope values resulted in a sensitivity of 100%, a specificity of 85.7%, and an accuracy of 92.9%.

CONCLUSIONS

Both DWI and DCE-MRI showed promising results for differentiating malignant from benign bone lesions. A combination of DWI and DCE-MRI was the most valuable of the three.

Rectal cancer: Short-term reproducibility of intravoxel incoherent motion parameters in 3.0T magnetic resonance imaging

The aim of this study was to evaluate the short-term test-retest reproducibility of diffusion-weighted magnetic resonance imaging (DW-MRI) parameters of rectal cancer with 3.0T MRI.Twenty-six patients with rectal cancer underwent MRI, including diffusion-weighted imaging with 8 b values. Apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) parameters (D, pure diffusion; f, perfusion fraction; D*, pseudodiffusion coefficient) were, respectively, calculated. The short-term test-retest reproducibility, the intra and interobserver variation of the IVIM parameters were assessed based on the repeatability coefficient and Bland-Altman limits of agreement.There was no significant intra or interobserver difference observed in the parameters on the same DW-MRI scan. The corresponding repeatability coefficient of intra- and interobserver analysis for ADC, D, f, and D* was 5.4%, 11.1%, 55.4%, and 40.3%; 10.9%, 41.6%, 134.0%, and 177.6%, respectively. The test-retest repeatability coefficient for ADC, D, f, and D* was 19.1%, 24.5%, 126.3%, and 197.4%, respectively, greater than the intraobserver values.ADC and D have better short-term test-retest reproducibility than f and D*. Considering the poor test-retest reproducibility for f and D,* variance in these 2 parameters should be interpreted with caution in longitudinal studies on rectal cancer in which treatment response and recurrence are monitored.

Evaluation of efficacy of transcatheter arterial chemoembolization for hepatocellular carcinoma using magnetic resonance diffusion-weighted imaging

Although the efficacy of transcatheter arterial chemoembolization (TACE) has been recommended as first-line therapy for nonsurgical patients with hepatocellular carcinoma (HCC), it is difficult to accurately predict the efficacy of TACE. Therefore, this study evaluated the efficacy of TACE for HCC using magnetic resonance (MR) diffusion-weighted imaging (DWI). A total of 84 HCC patients who received initial TACE were selected and assigned to the stable group (n=39) and the progressive group (n=45). Before TACE treatment, a contrast-enhanced MR scan and DWI (b=300, 600, and 800 s/mm²) were performed on all patients. The modified response evaluation criteria in solid tumors were used for evaluation of tumor response. Receiver operating characteristic curve was employed to predict the value of apparent diffusion coefficient (ADC) for TACE efficacy. The ADC values of HCC patients in the progressive group were higher than those in the stable group at different b-values (b=300, 600, and 800 s/mm²) before TACE treatment. The area under the curve of ADC values with b-values of 300, 600, and 800 s/mm² were 0.693, 0.724, and 0.746; the threshold values were 1.94×10^-3 mm²/s, 1.28×10^-3 mm²/s, and 1.20×10^-3 mm²/s; the sensitivity values were 55.6%, 77.8%, and 73.3%; and the specificity values were 82.1%, 61.5%, and 71.8%, respectively. Our findings indicate that the ADC values of MR-DWI may accurately predict the efficacy of TACE in the treatment of HCC patients.

Standard-b-Value Versus Low-b-Value Diffusion-Weighted Imaging in Hepatic Lesion Discrimination: A Meta-analysis

OBJECTIVE

We sought to determine the comparative diagnostic performance of standard-b-value (500-1000s/mm) versus low-b-value (≤500 s/mm) diffusion-weighted imaging (DWI) in the discrimination of hepatic lesions.

METHODS

A total of 1775 hepatic malignant lesions and 1120 benign hepatic lesions from 21 studies were included.

RESULTS

(1) The global sensitivity was 0.86 (95% confidence interval [CI], 0.847-0.879), the specificity was 0.82 (95% CI, 0.797-0.842), the positive likelihood ratio (PLR) was 6.234 (95% CI, 4.260-9.123), the negative likelihood ratio (NLR) was 0.175 (95% CI, 0.135-0.227), and diagnostic odds ratio (DOR) was 42.836 (95% CI, 24.134-76.031). The area under the curve (AUC) and Q* index were 0.93 and 0.87. Publication bias was not present (P > 0.05). (2)The sensitivity of a subgroup meta-analysis of standard-b-value DWI was 0.858 (95% CI, 0.835-0.880), the specificity was 0.836 (95% CI, 0.807-0.863), the PLR was 6.527 (95% CI, 3.857-11.046), the NLR was 0.168 (95% CI, 0.123-0.239), and the DOR was 49.716 (95% CI, 22.897-107.98). The AUC and Q* index were 0.941 and 0.88. (3)The sensitivity of a subgroup meta-analysis of low-b-value DWI was 0.87 (95% CI, 0.84-0.89), the specificity was 0.80 (95% CI, 0.76-0.83), the PLR was 6.22 (95% CI, 3.29-11.76), the NLR was 0.19 (95% CI, 0.12-0.29), and the DOR was 37.14 (95% CI, 14.80-93.18). The AUC and Q* index were 0.922 and 0.86.

CONCLUSIONS

Hepatic DWI is useful in differentiating between malignant and benign hepatic lesions. Standard-b-value DWI displayed an overall superior diagnostic accuracy over low-b-value DWI. Further trials needed to determine whether increasing b values beyond 1000 s/mm affects the diagnostic accuracy of hepatic lesion discrimination.

Repeatability of derived parameters from histograms following non-Gaussian diffusion modelling of diffusion-weighted imaging in a paediatric oncological cohort

OBJECTIVES

To examine repeatability of parameters derived from non-Gaussian diffusion models in data acquired in children with solid tumours.

METHODS

Paediatric patients (<16 years, n = 17) were scanned twice, 24 h apart, using DWI (6 b-values, 0-1000 mm-2 s) at 1.5 T in a prospective study. Tumour ROIs were drawn (3 slices) and all data fitted using IVIM, stretched exponential, and kurtosis models; percentage coefficients of variation (CV) calculated for each parameter at all ROI histogram centiles, including the medians.

RESULTS

The values for ADC, D, DDCα, α, and DDCK gave CV < 10 % down to the 5th centile, with sharp CV increases below 5th and above 95th centile. K, f, and D* showed increased CV (>30 %) over the histogram. ADC, D, DDCα, and DDCK were strongly correlated (ρ > 0.9), DDCα and α were not correlated (ρ = 0.083).

CONCLUSION

Perfusion- and kurtosis-related parameters displayed larger, more variable CV across the histogram, indicating observed clinical changes outside of D/DDC in these models should be interpreted with caution. Centiles below 5th for all parameters show high CV and are unreliable as diffusion metrics. The stretched exponential model behaved well for both DDCα and α, making it a strong candidate for modelling multiple-b-value diffusion imaging data.

KEY POINTS

• ADC has good repeatability as low 5th centile of the histogram distribution. • High CV was observed for all parameters at extremes of histogram. • Parameters from the stretched exponential model showed low coefficients of variation. • The median ADC, D, DDC α , and DDC K are highly correlated and repeatable. • Perfusion/kurtosis parameters showed high CV variations across their histogram distributions.

Evaluating Instantaneous Perfusion Responses of Parotid Glands to Gustatory Stimulation Using High-Temporal-Resolution Echo-Planar Diffusion-Weighted Imaging

BACKGROUND AND PURPOSE

Parotid glands secrete and empty saliva into the oral cavity rapidly after gustatory stimulation. However, the role of the temporal resolution of DWI in investigating parotid gland function remains uncertain. Our aim was to design a high-temporal-resolution echo-planar DWI pulse sequence and to evaluate the instantaneous MR perfusion responses of the parotid glands to gustatory stimulation.

MATERIALS AND METHODS

This prospective study enrolled 21 healthy volunteers (M/F = 2:1; mean age, 45.2 ± 12.9 years). All participants underwent echo-planar DWI (total scan time, 304 seconds; temporal resolution, 4 s/scan) on a 1.5T MR imaging scanner. T2WI (b = 0 s/mm²) and DWI (b = 200 s/mm²) were qualitatively assessed. Signal intensity of the parotid glands on T2WI, DWI, and ADC was quantitatively analyzed. One-way ANOVA with post hoc group comparisons with Bonferroni correction was used for statistical analysis. P < .05 was statistically significant.

RESULTS

Almost perfect interobserver agreement was achieved (κ ≥ 0.656). The parotid glands had magnetic susceptibility artifacts in 14.3% (3 of 21) of volunteers during swallowing on DWI but were free from perceptible artifacts at the baseline and at the end of scans on all images. Increased ADC and reduced signal intensity of the parotid glands on T2WI and DWI occurred immediately after oral administration of lemon juice. Maximal signal change of ADC (24.8% ± 10.8%) was significantly higher than that of T2WI (-10.1% ± 5.2%, P < .001). The recovery ratio of ADC (100.71% ± 42.34%) was also significantly higher than that of T2WI (22.36% ± 15.54%, P < .001).

CONCLUSIONS

Instantaneous parotid perfusion responses to gustatory stimulation can be quantified by ADC by using high-temporal-resolution echo-planar DWI.

Non-parametric intravoxel incoherent motion analysis in patients with intracranial lesions: Test-retest reliability and correlation with arterial spin labeling

Intravoxel incoherent motion (IVIM) analysis of diffusion imaging data provides biomarkers of true passive water diffusion and perfusion properties. A new IVIM algorithm with variable adjustment of the b-value threshold separating diffusion and perfusion effects was applied for cerebral tissue characterization in healthy volunteers, computation of test-retest reliability, correlation with arterial spin labeling, and assessment of applicability in a small cohort of patients with malignant intracranial masses. The main results of this study are threefold: (i) accounting for regional differences in the separation of the perfusion and the diffusion components improves the reliability of the model parameters; (ii) if differences in the b-value threshold are not accounted for, a significant tissue-dependent systematic bias of the IVIM parameters occurs; (iii) accounting for voxel-wise differences in the b-value threshold improves the correlation with CBF measurements in healthy volunteers and patients. The proposed algorithm provides a robust characterization of regional micro-vascularization and cellularity without a priori assumptions on tissue diffusion properties. The glioblastoma multiforme with its inherently high variability of tumor vascularization and tumor cell density may benefit from a non-invasive clinical characterization of diffusion and perfusion properties.

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The novel IVIM algorithm accounts for regional differences in the separation of the perfusion and the diffusion components.

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The algorithm improves the reliability of IVIM parameters.

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The algorithm improves the correlation with CBF in healthy volunteers and patients.

Comparison of diffusion-weighted imaging and T2-weighted single shot fast spin-echo: Implications for LI-RADS characterization of hepatocellular carcinoma

PURPOSE

To evaluate the performance of diffusion-weighted imaging (DWI) and T2-weighted single shot fast spin-echo (SSFSE) imaging of the liver in the detection of hepatocellular carcinoma (HCC) in reference to the LI-RADS classification system.

METHODS

MR images of 40 patients with 68 LI-RADS grade 3-5 lesions were analyzed. Two readers independently reviewed sequences and characterized lesion signal intensity, followed by consensus evaluation. CE-MRI served as reference standard. Sensitivities were compared across sequences. Lesion-to-liver contrast-to-noise ratios (CNRs) and apparent diffusion coefficients (ADCs) were measured and compared using the Wilcoxon signed-rank test across sequences and the Mann-Whitney U or Kruskal-Wallis test between LI-RADS categories. Inter-reader variability was assessed using Cohen's kappa statistic.

RESULTS

Consensus sensitivities of LI-RADS 3-5 lesions using SSFSE images versus DWI were similar (0.53-0.63, p=0.089), however, the sensitivity with DWI b=700 was higher (0.63) than DWI b=0 (0.53, p=0.039). Lesion-to-liver CNRs were larger for all DWI sequences compared to SSFSE images (p<0.001 for all). ADCs of large (>2cm) LIRADS 3-5 lesions were lower than those of small lesions (1.09±0.33 vs. 1.31±0.26, p=0.02), however lesion ADCs were not different from those of adjacent hepatic parenchyma for any LI-RADS lesion.

CONCLUSIONS

DWI has a similar sensitivity compared to SSFSE, but intensity on DWI likely represents intrinsic T2 signal hyper-intensity rather than restricted diffusion as the ADC values were not lower than adjacent parenchyma. Therefore it may not be appropriate to consider hyper-intensity on high b-value as a separate ancillary criteria to T2 hyper-intensity in LI-RADS.

Spatially-constrained probability distribution model of incoherent motion (SPIM) for abdominal diffusion-weighted MRI

Quantitative diffusion-weighted MR imaging (DW-MRI) of the body enables characterization of the tissue microenvironment by measuring variations in the mobility of water molecules. The diffusion signal decay model parameters are increasingly used to evaluate various diseases of abdominal organs such as the liver and spleen. However, previous signal decay models (i.e., mono-exponential, bi-exponential intra-voxel incoherent motion (IVIM) and stretched exponential models) only provide insight into the average of the distribution of the signal decay rather than explicitly describe the entire range of diffusion scales. In this work, we propose a probability distribution model of incoherent motion that uses a mixture of Gamma distributions to fully characterize the multi-scale nature of diffusion within a voxel. Further, we improve the robustness of the distribution parameter estimates by integrating spatial homogeneity prior into the probability distribution model of incoherent motion (SPIM) and by using the fusion bootstrap solver (FBM) to estimate the model parameters. We evaluated the improvement in quantitative DW-MRI analysis achieved with the SPIM model in terms of accuracy, precision and reproducibility of parameter estimation in both simulated data and in 68 abdominal in-vivo DW-MRIs. Our results show that the SPIM model not only substantially reduced parameter estimation errors by up to 26%; it also significantly improved the robustness of the parameter estimates (paired Student's t-test, p < 0.0001) by reducing the coefficient of variation (CV) of estimated parameters compared to those produced by previous models. In addition, the SPIM model improves the parameter estimates reproducibility for both intra- (up to 47%) and inter-session (up to 30%) estimates compared to those generated by previous models. Thus, the SPIM model has the potential to improve accuracy, precision and robustness of quantitative abdominal DW-MRI analysis for clinical applications.

Quantitative apparent diffusion coefficient (ADC) values as an imaging biomarker for fibrosis in pediatric Crohn's disease: preliminary experience

PURPOSE

To compare histopathology with ADC values in strictured bowel segments in pediatric patients with known Crohn's disease and surgical bowel resection.

METHODS

Magnetic resonance enterography (MRE) images of 14 subjects with Crohn's disease who had surgical bowel resection for strictures were retrospectively reviewed. Five of 14 subjects had DWI (b=0, 500, 1000) sequences included in the MRE study. ADC measurements were made by placing ROI's in the strictured bowel wall and compared to full-thickness histologic analysis of resected specimens. ADC values were also compared to control ADC measurements (in normal and inflamed-nonstenotic bowel segments) as well as the mean ADC values of Crohn's patients published in the literature.

RESULTS

All five subjects had transmural fibrosis. The mean ADC value with b = 500 was 0.92 ± 0.10 × 10(-3) mm(2)/s and with b = 1000 was 0.8 ± 0.05 × 10(-3) mm(2)/s. There was a significant difference in ADC values between strictures and inflamed-nonstenotic segments (p=0.0143) and between normal and diseased bowel segments (p=0.009-0.0143).

CONCLUSIONS

Quantitative ADC measures of transmural fibrosis are lower compared to the reported values of inflammation in Crohn's disease. To our knowledge, this is the first pediatric pilot study to investigate the correlation of quantitative DWI with histology of surgical specimens in pediatric patients with Crohn's disease. Our results are comparable to a recently published study in adult Crohn's patients showing a significant correlation between a decrease in ADC values and fibrosis.

Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors

PURPOSE

To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis.

MATERIALS AND METHODS

This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44 ± 11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (Dt), perfusion fraction (fp), and pseudo-diffusivity (Dp) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann-Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman's rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression.

RESULTS

The average values of the ADC and IVIM biomarkers, Dt and fp, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly fp and Dp, showed significant correlation with hormonal factor expression.

CONCLUSION

Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients.

KEY POINTS

• Novel IVIM biomarkers characterize heterogeneous breast cancer. • Histogram analysis enables quantification of tumour heterogeneity. • IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.

Estimation of optimal b-value sets for obtaining apparent diffusion coefficient free from perfusion in non-small cell lung cancer

The purpose of this study was to determine optimal sets of b-values in diffusion-weighted MRI (DW-MRI) for obtaining monoexponential apparent diffusion coefficient (ADC) close to perfusion-insensitive intravoxel incoherent motion (IVIM) model ADC (ADCIVIM) in non-small cell lung cancer. Ten subjects had 40 DW-MRI scans before and during radiotherapy in a 1.5 T MRI scanner. Respiratory triggering was applied to the echo-planar DW-MRI with TR ≈ 4500 ms, TE  =  74 ms, eight b-values of 0-1000 μs μm(-2), pixel size  =  1.98 × 1.98 mm(2), slice thickness  =  6 mm, interslice gap  =  1.2 mm, 7 axial slices and total acquisition time ≈6 min. One or more DW-MRI scans together covered the whole tumour volume. Monoexponential model ADC values using various b-value sets were compared to reference-standard ADCIVIM values using all eight b-values. Intra-scan coefficient of variation (CV) of active tumour volumes was computed to compare the relative noise in ADC maps. ADC values for one pre-treatment DW-MRI scan of each of the 10 subjects were computed using b-value pairs from DW-MRI images synthesized for b-values of 0-2000 μs μm(-2) from the estimated IVIM parametric maps and corrupted by various Rician noise levels. The square root of mean of squared error percentage (RMSE) of the ADC value relative to the corresponding ADCIVIM for the tumour volume of the scan was computed. Monoexponential ADC values for the b-value sets of 250 and 1000; 250, 500 and 1000; 250, 650 and 1000; 250, 800 and 1000; and 250-1000 μs μm(-2) were not significantly different from ADCIVIM values (p > 0.05, paired t-test). Mean error in ADC values for these sets relative to ADCIVIM were within 3.5%. Intra-scan CVs for these sets were comparable to that for ADCIVIM. The monoexponential ADC values for other sets-0-1000; 50-1000; 100-1000; 500-1000; and 250 and 800 μs μm(-2) were significantly different from the ADCIVIM values. From Rician noise simulation using b-value pairs, there was a wide range of acceptable b-value pairs giving small RMSE of ADC values relative to ADCIVIM. The pairs for small RMSE had lower b-values as the noise level increased. ADC values of a two b-value set-250 and 1000 μs μm(-2), and all three b-value sets with 250, 1000 μs μm(-2) and an intermediate value approached ADCIVIM, with relative noise comparable to that of ADCIVIM. These sets may be used in lung tumours using comparatively short scan and post-processing times. Rician noise simulation suggested that the b-values in the vicinity of these experimental best b-values can be used with error within an acceptable limit. It also suggested that the optimal sets will have lower b-values as the noise level becomes higher.

Impact of the calculation algorithm on biexponential fitting of diffusion-weighted MRI in upper abdominal organs

PURPOSE

To compare the variability, precision, and accuracy of six different algorithms (Levenberg-Marquardt, Trust-Region, Fixed-Dp , Segmented-Unconstrained, Segmented-Constrained, and Bayesian-Probability) for computing intravoxel-incoherent-motion-related parameters in upper abdominal organs.

METHODS

Following the acquisition of abdominal diffusion-weighted magnetic resonance images of 10 healthy men, six distinct algorithms were employed to compute intravoxel-incoherent-motion-related parameters in the left and right liver lobe, pancreas, spleen, renal cortex, and renal medulla. Algorithms were evaluated regarding inter-reader and intersubject variability. Comparability of results was assessed by analyses of variance. The algorithms' precision and accuracy were investigated on simulated data.

RESULTS

A Bayesian-Probability based approach was associated with very low inter-reader variability (average Intraclass Correlation Coefficients: 96.5-99.6%), the lowest inter-subject variability (Coefficients of Variation [CV] for the pure diffusion coefficient Dt : 3.8% in the renal medulla, 6.6% in the renal cortex, 10.4-12.1% in the left and right liver lobe, 15.3% in the spleen, 15.8% in the pancreas; for the perfusion fraction Fp : 15.5% on average; for the pseudodiffusion coefficient Dp : 25.8% on average), and the highest precision and accuracy. Results differed significantly (P < 0.05) across algorithms in all anatomical regions.

CONCLUSION

The Bayesian-Probability algorithm should be preferred when computing intravoxel-incoherent-motion-related parameters in upper abdominal organs.

Apparent diffusion coefficient measurement by diffusion weighted magnetic resonance imaging is a useful tool in differentiating renal tumors

BACKGROUND

To determine the clinical value of apparent diffusion coefficient (ADC) measurement by diffusion weighted magnetic resonance imaging (DW-MRI) in differentiating renal tumors.

METHODS

Electronic databases were searched using combinations of keywords and free words relating to renal tumor, ADC and DW-MRI. Based on carefully selected inclusion and exclusion criteria, relevant case-control studies were identified and the related clinical data was acquired. Statistical analyses were performed using STATA 12.0 (Stata Corporation, College station, TX).

RESULTS

Sixteen case-control studies were ultimately included in the present meta-analysis. These 16 high quality studies contained a combined total of 438 normal renal tissues and 832 renal tumor lesions (597 malignant and 235 benign). The results revealed that ADC values of malignant renal tumor tissues were markedly lower than normal renal tissues and benign renal tumor tissues. ADC values of benign renal tumor tissues were also significantly lower than normal renal tissue.

CONCLUSIONS

ADC measurement by DW-MRI provided clinically useful information on the internal structure of renal tumors and could be an important radiographic index for differentiation of malignant renal tumors from benign renal tumors.

Insights into quantitative diffusion-weighted MRI for musculoskeletal tumor imaging

OBJECTIVE

The purposes of this article are to discuss the technical considerations for performing quantitative diffusion-weighted MRI (DWI) with apparent diffusion coefficient (ADC) mapping, examine the role of DWI in whole-body MRI, and review how DWI with ADC mapping can serve as an adjunct to information gleaned from conventional MRI in the radiologic evaluation of musculoskeletal lesions.

CONCLUSION

The primary role of whole-body DWI is in tumor detection; localized DWI is helpful in differentiating malignant bone and soft-tissue lesions. After treatment, an increase in tumor ADC values correlates with response to cytotoxic therapy. The use of DWI in the evaluation of musculoskeletal lesions requires knowledge of potential diagnostic pitfalls that stem from technical challenges and confounding biochemical factors that influence ADC maps but are unrelated to lesion cellularity.

Comparison of fitting methods and b-value sampling strategies for intravoxel incoherent motion in breast cancer

PURPOSE

To compare fitting methods and sampling strategies, including the implementation of an optimized b-value selection for improved estimation of intravoxel incoherent motion (IVIM) parameters in breast cancer.

METHODS

Fourteen patients (age, 48.4 ± 14.27 years) with cancerous lesions underwent 3 Tesla breast MRI examination for a HIPAA-compliant, institutional review board approved diffusion MR study. IVIM biomarkers were calculated using "free" versus "segmented" fitting for conventional or optimized (repetitions of key b-values) b-value selection. Monte Carlo simulations were performed over a range of IVIM parameters to evaluate methods of analysis. Relative bias values, relative error, and coefficients of variation (CV) were obtained for assessment of methods. Statistical paired t-tests were used for comparison of experimental mean values and errors from each fitting and sampling method.

RESULTS

Comparison of the different analysis/sampling methods in simulations and experiments showed that the "segmented" analysis and the optimized method have higher precision and accuracy, in general, compared with "free" fitting of conventional sampling when considering all parameters. Regarding relative bias, IVIM parameters fp and Dt differed significantly between "segmented" and "free" fitting methods.

CONCLUSION

IVIM analysis may improve using optimized selection and "segmented" analysis, potentially enabling better differentiation of breast cancer subtypes and monitoring of treatment.

Dynamic perfusion and diffusion MRI of cortical spreading depolarization in photothrombotic ischemia

Cortical spreading depolarization (CSD) is known to exacerbate ischemic damage, as the number of CSDs correlates with the final infarct volumes and suppressing CSDs improves functional outcomes. To investigate the role of CSD in ischemic damage, we developed a novel rat model of photothrombotic ischemia using a miniature implantable optic fiber that allows lesion induction inside the magnetic resonance imaging (MRI) scanner. We were able to precisely control the location and the size of the ischemic lesion, and continuously monitor dynamic perfusion and diffusion MRI signal changes at high temporal resolution before, during and after the onset of focal ischemia. Our model showed that apparent diffusion coefficient (ADC) and cerebral blood flow (CBF) in the ischemic core dropped immediately after lesion onset by 20±6 and 41±23%, respectively, and continually declined over the next 5h. Meanwhile, CSDs were observed in all animals (n=36) and displayed either a transient decrease of ADC by 17±3% or an increase of CBF by 104±15%. All CSDs were initiated from the rim of the ischemic core, propagated outward, and confined to the ipsilesional cortex. Additionally, we demonstrated that by controlling the size of perfusion-diffusion mismatch (which approximates the penumbra) in our model, the number of CSDs correlated with the mismatch area rather than the final infarct volume. This study introduces a novel platform to study CSDs in real-time with high reproducibility using MRI.

Effect of intravenous gadolinium-DTPA on diffusion-weighted imaging of brain tumors: a short temporal interval assessment

PURPOSE

To determine the effect of intravenous administration of gadolinium (Gd) contrast medium (Gd-DTPA) on diffusion-weighted imaging (DWI) for the evaluation of normal brain parenchyma vs. brain tumor following a short temporal interval.

MATERIALS AND METHODS

Forty-four DWI studies using b values of 0 and 1000 s/mm(2) were performed before, immediately after, 1 min after, 3 min after, and 5 min after the administration of Gd-DTPA on 62 separate lesions including 15 meningioma, 17 glioma and 30 metastatic lesions. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and apparent diffusion coefficient (ADC) values of the brain tumor lesions and normal brain tissues were measured on pre- and postcontrast images. Statistical analysis using paired t-test between precontrast and postcontrast data were obtained on three brain tumors and normal brain tissue.

RESULTS

The SNR and CNR of brain tumors and the SNR of normal brain tissue showed no statistical differences between pre- and postcontrast (P > 0.05). The ADC values on the three cases of brain tumors demonstrated significant initial increase on the immediate time point (P < 0.01) and decrease on following the 1 min time point (P < 0.01) after contrast. Significant decrease of ADC value was still found at 3min and 5min time point in the meningioma group (P < 0.01) with gradual normalization over time. The ADC values of normal brain tissues demonstrated significant initial elevation on the immediately postcontrast DWI sequence (P < 0.01).

CONCLUSION

Contrast medium can cause a slight but statistically significant change on the ADC value within a short temporal interval after the contrast administration. The effect is both time and lesion-type dependent.

Diffusion-weighted MRI and optimal b-value for characterization of liver lesions

BACKGROUND

Diffusion-weighted imaging (DWI) is commonly used to distinguish between benign and malignant liver lesions. However, different b-values are recommended.

PURPOSE

To determine the most suitable b-value in DWI for differentiation of benign and malignant liver lesions.

MATERIAL AND METHODS

A total of 124 lesions in 89 consecutive patients (43 men, 46 women; age, mean ± standard deviation, 58 ± 14 years) with a pathological or radiological diagnosis of malignant or benign focal liver lesions after magnetic resonance imaging (MRI) were included in this study. Routine abdominal MRI and DWI were performed using seven b-values (0, 50, 200, 400, 600, 800, 1000 s/mm(2)). Lesions were analyzed for benignity/malignity using apparent diffusion coefficient (ADC) values with 10 b-value combinations and by measuring the lesion/normal parenchyma ADC ratio.

RESULTS

Mean ADC values were significantly different between malignant and benign lesions for all b-value combinations (P=0.000). The best b-value combination was 0 and 800 (Az=0.935). Using lower b-values such as 0 and 50 together with higher b-values ≥ 600 s/mm(2) was beneficial (Az=0.928 and 0.927). Mean ADC values were approximately 13% (1-15%) higher in total when b=0 and b=50 s/mm(2) were included in multiple b-value combinations.

CONCLUSION

In DWI, we recommend the use of b-values of 0 and 800 s/mm(2) as two b-values, or b=0, 50, 600, 800, and 1000 s/mm(2) as multiple b-values for distinguishing between benign and malignant liver lesions. Mean ADC value is 13% higher in total by additional use of b=0 and b=50 s/mm(2) in multiple b-value combinations.