Comparison of biexponential and monoexponential model of diffusion weighted imaging in evaluation of renal lesions: preliminary experience. Invest Radiol. 2011;46:285-291. [PMID: 21102345 DOI: 10.1097/rli.0b013e3181ffc485]

Investigation of diffusion time dependence of apparent diffusion coefficient and intravoxel incoherent motion parameters in the human kidney

PURPOSE

To characterize the diffusion time (Δeff) dependence of apparent diffusion coefficient (ADC) and intravoxel incoherent motion-related parameters in the human kidney at 3 T.

METHODS

Sixteen healthy volunteers underwent an MRI examination at 3 T including diffusion-weighted imaging at different Δeff ranging from 24.1 to 104.1 ms. The extended mono-exponential ADC and intravoxel incoherent motion models were fitted to the data for each Δeff and the medullary and cortical ADC, (pseudo-)diffusion coefficients (D* and D) and flow-related signal fraction (f) were calculated.

RESULTS

When all the data were used for fitting, a significant trend toward higher ADC with increasing Δeff was observed between 24.1 and 104.1 ms (median and interquartile range: 2.38 [2.19, 2.47] to 2.84 [2.36, 2.90] × 10-3 mm2/s for cortex, and 2.28 [2.18, 2.37] to 2.82 [2.58, 3.11] × 10-3 mm2/s for medulla). In contrast, no significant differences in ADC were found when only the data acquired at b-values higher than 200 s/mm2 were used for fitting. When the intravoxel incoherent motion model was applied, cortical and medullary f increased significantly (cortex: 0.21 [0.15 0.27] to 0.37 [0.32, 0.49] × 10-3 mm2/s; medulla: 0.15 [0.13 0.29] to 0.41 [0.36 0.51] × 10-3 mm2/s). No significant changes in cortical and medullary D and D* were observed as diffusion time increased.

CONCLUSION

Renal perfusion and tubular flow substantially contribute to the observed increase in ADC over a wide range of Δeff between 24 and 104 ms.

Exploring the value of arterial spin labeling and six diffusion MRI models in differentiating solid benign and malignant renal tumors

OBJECTIVE

To explore the value of three-dimensional arterial spin labeling (ASL) and six diffusion magnetic resonance imaging (MRI) models in differentiating solid benign and malignant renal tumors.

METHODS

This retrospective study included 89 patients with renal tumors. All patients underwent ASL and ZOOMit diffusion-weighted imaging (DWI) examinations and were divided into three groups: clear cell renal cell carcinoma (ccRCC), non-ccRCC, and benign renal tumors (BRT). The mean and peak renal blood flow (RBFmean and RBFpeak) from ASL and fourteen diffusion parameters from mono-exponential DWI (Mono_DWI), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), fractional order calculus (FROC), and continuous-time random-walk (CTRW) model were analyzed. Binary logistic regression was used to determine the optimal parameter combinations. The diagnostic performance of various MRI-derived parameters and their combinations was compared.

RESULTS

Among the six diffusion models, the SEM model achieved the highest performance in differentiating ccRCC from non-ccRCC (area under the receiver operating characteristic curve [AUC] 0.880) and from BRT (AUC 0.891). IVIM model achieved the highest AUC (0.818) in differentiating non-ccRCC from BRT. Among all the MRI-derived parameters, RBFpeak combined with DKI_MK yielded the highest AUC (0.970) in differentiating ccRCC from non-ccRCC, and the combination of RBFpeak, SEM_DDC, and FROC_μ yielded the highest AUC (0.992) for differentiating ccRCC from BRT.

CONCLUSION

ASL and all diffusion models showed similar diagnostic performance in differentiating ccRCC from non-ccRCC or BRT, while the IVIM model performed better in distinguishing non-ccRCC from BRT. Combining ASL with diffusion models can provide additional value in predicting ccRCC.

RELEVANCE STATEMENT

Considering the increasing detection rate of incidental renal masses, accurate discrimination of benign and malignant renal tumors is crucial for decision-making. Combining ASL with diffusion MRI models offers a promising solution to this clinical issue.

KEY POINTS

All assessed models were effective for differentiating ccRCC from non-ccRCC or BRT. ASL and all diffusion models showed similar performance in differentiating ccRCC from non-ccRCC or BRT. Combining ASL with diffusion models significantly improved diagnostic efficacy in predicting ccRCC. IVIM model could better differentiate non-ccRCC from BRT.

Early and late assessment of renal allograft dysfunction using intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI): a prospective study

PURPOSE

To evaluate the ability of the Intravoxel Incoherent Motion (IVIM) and monoexponentially ADC in renal allograft function in the early and late phases of transplantation, and to predict their effectiveness in discrimination of the graft pathology.

METHODS

This is a prospective study included participants scanned with quantitative diffusion and perfusion sequences on a 3-T MR scanner (Philips, Ingenia); the ADC and IVIM parameters; were calculated. Correlations and regression analysis with the eGFR, transplantation periods, and pathology were assessed.

RESULTS

This study included 105 renal allograft recipients (85 males, and 20 females with mean age = 32.4 ± 11.9 years and age range = 22-61 years). There was a significant positive correlation between the whole parameters of the ADC and IVIM with eGFR however, the cortical parameters showed higher significant correlation coefficients (p < 0.001). Regression analysis revealed the most significant model can predict eGFR groups included cortical pseudo diffusion (D*) and cortical ADC (p < 0.001). In graft dysfunction eGFR was 61.5 ml/min and normal graft was 64 ml/min. This model demonstrates a high performance of an AUC 96% [0.93-0.97]. In the late transplantation, there is a higher correlation with D* compared to ADC, p-values = 0.001.

CONCLUSION

IVIM and ADC Values are significant biomarkers for renal allograft function assessment, cortical ADC, and D* had the highest performance even in situations with mild impairment that is not affect the eGFR yet as cases of proteinuria with normal eGFR. Furthermore, D* is superior to ADC in the late assessment of the renal transplant.

Probing Renal Microstructure and Function with Advanced Diffusion MRI: Concepts, Applications, Challenges, and Future Directions

Diffusion measurements in the kidney are affected not only by renal microstructure but also by physiological processes (i.e., glomerular filtration, water reabsorption, and urine formation). Because of the superposition of passive tissue diffusion, blood perfusion, and tubular pre-urine flow, the limitations of the monoexponential apparent diffusion coefficient (ADC) model in assessing pathophysiological changes in renal tissue are becoming apparent and motivate the development of more advanced diffusion-weighted imaging (DWI) variants. These approaches take advantage of the fact that the length scale probed in DWI measurements can be adjusted by experimental parameters, including diffusion-weighting, diffusion gradient directions and diffusion time. This forms the basis by which advanced DWI models can be used to capture not only passive diffusion effects, but also microcirculation, compartmentalization, tissue anisotropy. In this review, we provide a comprehensive overview of the recent advancements in the field of renal DWI. Following a short introduction on renal structure and physiology, we present the key methodological approaches for the acquisition and analysis of renal DWI data, including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), non-Gaussian diffusion, and hybrid IVIM-DTI. We then briefly summarize the applications of these methods in chronic kidney disease and renal allograft dysfunction. Finally, we discuss the challenges and potential avenues for further development of renal DWI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Multi-parametric MRI-based machine learning model for prediction of pathological grade of renal injury in a rat kidney cold ischemia-reperfusion injury model

BACKGROUND

Renal cold ischemia-reperfusion injury (CIRI), a pathological process during kidney transplantation, may result in delayed graft function and negatively impact graft survival and function. There is a lack of an accurate and non-invasive tool for evaluating the degree of CIRI. Multi-parametric MRI has been widely used to detect and evaluate kidney injury. The machine learning algorithms introduced the opportunity to combine biomarkers from different MRI metrics into a single classifier.

OBJECTIVE

To evaluate the performance of multi-parametric magnetic resonance imaging for grading renal injury in a rat model of renal cold ischemia-reperfusion injury using a machine learning approach.

METHODS

Eighty male SD rats were selected to establish a renal cold ischemia -reperfusion model, and all performed multiparametric MRI scans (DWI, IVIM, DKI, BOLD, T1mapping and ASL), followed by pathological analysis. A total of 25 parameters of renal cortex and medulla were analyzed as features. The pathology scores were divided into 3 groups using K-means clustering method. Lasso regression was applied for the initial selecting of features. The optimal features and the best techniques for pathological grading were obtained. Multiple classifiers were used to construct models to evaluate the predictive value for pathology grading.

RESULTS

All rats were categorized into mild, moderate, and severe injury group according the pathologic scores. The 8 features that correlated better with the pathologic classification were medullary and cortical Dp, cortical T2*, cortical Fp, medullary T2*, ∆T1, cortical RBF, medullary T1. The accuracy(0.83, 0.850, 0.81, respectively) and AUC (0.95, 0.93, 0.90, respectively) for pathologic classification of the logistic regression, SVM, and RF are significantly higher than other classifiers. For the logistic model and combining logistic, RF and SVM model of different techniques for pathology grading, the stable and perform are both well. Based on logistic regression, IVIM has the highest AUC (0.93) for pathological grading, followed by BOLD(0.90).

CONCLUSION

The multi-parametric MRI-based machine learning model could be valuable for noninvasive assessment of the degree of renal injury.

Comparison of conventional diffusion-weighted imaging and intravoxel incoherent motion in differentiating between chromophobe renal cell carcinoma and renal oncocytoma: a preliminary study

OBJECTIVE

Quantitative comparison of the diagnostic efficacy of conventional diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) in differentiating between chromophobe renal cell carcinoma (ChRCC) from renal oncocytoma (RO).

METHODS

A total of 48 patients with renal tumours who had undergone DWI and IVIM were divided into two groups-ChRCC (n = 28) and RO (n = 20) groups, and the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) and their diagnostic efficacy were compared between the two groups.

RESULTS

The D* values were higher in the ChRCCs group compared to the RO groups (0.019 ± 0.003 mm2/s vs 0.008 ± 0.002 mm2/s, P < .05). Moreover, the ADC, D and f values were higher in ROs compared to ChRCCs (0.61 ± 0.08 × 10-3 mm2/s vs 0.51 ± 0.06 × 10-3 mm2/s, 1.02 ± 0.15 × 10-3 mm2/s vs 0.86 ± 0.07 × 10-3 mm2/s, 0.41 ± 0.05 vs 0.28 ± 0.02, P < .05). The areas of the ADC, D, D* and f values under the ROC curves in differentiating ChRCCs from ROs were 0.713, 0.839, 0.856 and 0.906, respectively. The cut-off values of ADC, D, D* and f were 0.54, 0.91, 0.013 and 0.31, respectively. The AUC, sensitivity, specificity and accuracy of the f values were 0.906, 89.3%, 80.0% and 89.6%, respectively. For pairwise comparisons of ROC curves and diagnostic efficacy, IVIM parameters, that is, D, D* and f offered better diagnostic accuracy than ADC in differentiating ChRCCs from ROs (P = .013, .016, and .008) with f having the highest diagnostic accuracy.

CONCLUSION

IVIM parameters presented better performance than ADC in differentiating ChRCCs from ROs.

ADVANCES IN KNOWLEDGE

(1) D* values of ChRCCs were higher, while ADC, D and f values were lower than those of RO tumours. (2) f values had the highest diagnostic efficacy in differentiating ChRCC from RO. (3) IVIM parameters, that is, D, D* and f offered better diagnostic accuracy than ADC in differentiating ChRCC from RO (P=.013, .016, and .008).

Intravoxel incoherent motion diffusion-weighted imaging for evaluating the pancreatic perfusion in cirrhotic patients

PURPOSE

To assess the characteristics of pancreatic perfusion in normal pancreas versus cirrhotic patients using intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI).

METHODS

A total of 67 cirrhotic patients and 33 healthy subjects underwent IVIM on a 3.0 T MRI scanner. Diffusion coefficient (ADCslow), pseudo-diffusion coefficient (ADCfast), and perfusion fraction (f) were calculated based on the bi-exponential model. The pancreatic IVIM-derived parameters were then compared. In the cirrhotic group, the relationship was analyzed between IVIM-derived pancreatic parameters and different classes of hepatic function as determined by the Child-Pugh classification. Also, the pancreatic IVIM-derived parameters were compared among different classes of cirrhosis as determined by the Child-Pugh classification.

RESULTS

The f value of the pancreas in cirrhotic patients was significantly lower than that in normal subjects (p = 0.01). In the cirrhotic group, the f value of the pancreas decreased with the increase of the Child-Pugh classification (R = - 0.49, p = 0.00). The f value of the pancreas was significantly higher in Child-Pugh class A patients than in class B and C patients (p = 0.02, 0.00, respectively), whereas there was no significant difference between class B and C patients (p = 0.16).

CONCLUSION

The IVIM-derived perfusion-related parameter (f value) could be helpful for the evaluation of pancreatic perfusion in liver cirrhosis. Our data also suggest that the blood perfusion decrease in the pancreas is present in liver cirrhosis, and the pancreatic perfusion tends to decrease with the increasing severity of hepatic function.

TRIAL REGISTRATION

Trial registration number is 2021-ky-68 and date of registration for prospectively registered trials is February 23, 2022.

Role of intravoxel incoherent motion (IVIM) imaging in response assessment of hepatocellular carcinoma after transarterial chemoembolization (TACE) - A prospective study

INTRODUCTION

Response evaluation of hepatocellular carcinoma (HCC) currently is based on arterial phase enhancement which doesn't take into microstructural changes in the tumor after trans-arterial chemoembolization (TACE).

AIM

This prospective study was conducted to assess the feasibility and efficacy of intravascular incoherent motion imaging (IVIM) in response evaluation of HCC after TACE. 39 cirrhotic patients with 48 HCC underwent MR imaging 1 week within and 6weeks after TACE. IVIM parameters like Dslow (true diffusion), Dfast (pseudodiffusion), perfusion fraction and ADC were measured prior to and postTACE. The pre and post TACE values in LR-TR (LIRADS - treatment response) nonviable and viable lesions were compared using paired t-tests. ROC curve analysis was done to calculate sensitivity and specificity and propose cut-off values.

RESULT

Non-viable lesions showed a significant increase in Dslow (1.208 ± 0.581 vs 1.560 ± 0.494, P-value -.0207) and ADC (1.37 ± 0.53 vs 1.65 ± 0.4287, P value .016) after TACE. There was also significant decrease in Dfast (33.7 ± 10.4 vs 23.75 ± 12.13, P value .0005) and f (19.92 ± 10.54 vs 12.9 ± 10.41, P value .012) values after TACE in non-viable lesions compared to viable lesions. The change in true diffusion had the highest AUC (0.741) among IVIM parameters with greater than 0.075 increase between preTACE and postTACE values having a sensitivity and specificity of 81.8% and 60% respectively for complete response.

CONCLUSION

IVIM imaging is feasible to assess the response in HCC after TACE. True diffusion is more sensitive and specific than apparent diffusion in evaluating the response.

Application of DKI and IVIM imaging in evaluating histologic grades and clinical stages of clear cell renal cell carcinoma

Purpose

To evaluate the value of quantitative parameters derived from diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) in differentiating histologic grades and clinical stages of clear cell renal cell carcinoma (ccRCC).

Materials and methods

A total of 65 patients who were surgically and pathologically diagnosed as ccRCC were recruited in this study. In addition to routine renal magnetic resonance imaging examination, all patients underwent preoperative IVIM and DKI. The corresponding diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean diffusivity (MD), kurtosis anisotropy (KA), and mean kurtosis (MK) values were obtained. Independent-samples t-test or Mann-Whitney U test was used for comparing the differences in IVIM and DKI parameters among different histologic grades and clinical stages. The diagnostic efficacy of IVIM and DKI parameters was evaluated using the receiver operating characteristic (ROC) curve. Spearman's correlation analysis was used to separately analyze the correlation of each parameter with histologic grades and stages of ccRCC.

Results

The D and MD values were significantly higher in low-grade ccRCC than high-grade ccRCC (all p < 0.001) and in low-stage than high-stage ccRCC (all p < 0.05), and the f value of high-stage ccRCC was lower than that of low-stage ccRCC (p = 0.007). The KA and MK values were significantly higher in low-grade than high-grade ccRCC (p = 0.000 and 0.000, respectively) and in low-stage than high-stage ccRCC (p = 0.000 and 0.000, respectively). The area under the curve (AUC) values of D, D*, f, MD, KA, MK, DKI, and IVIM+DKI values were 0.825, 0.598, 0.626, 0.792, 0.750, 0.754, 0.803, and 0.857, respectively, in grading ccRCC and 0.837, 0.719, 0.710, 0.787, 0.796, 0.784, 0.864, 0.823, and 0.916, respectively, in staging ccRCC. The AUC of IVIM was 0.913 in staging ccRCC. The D, D*, and MD values were negatively correlated with the histologic grades and clinical stages (all p < 0.05), and the KA and MK values showed a positive correlation with histologic grades and clinical stages (all p < 0.05). The f value was also negatively correlated with the ccRCC clinical stage (p = 0.008).

Conclusion

Both the IVIM and DKI values can be used preoperatively to predict the degree of histologic grades and stages in ccRCC, and the D and MD values have better diagnostic performance in the grading and staging. Also, further slightly enhanced diagnostic efficacy was observed in the model with combined IVIM and DKI parameters.

Image downsampling expedited adaptive least-squares (IDEAL) fitting improves intravoxel incoherent motion (IVIM) analysis in the human kidney

PURPOSE

To improve the reliability of intravoxel incoherent motion (IVIM) model parameter estimation for the DWI in the kidney using a novel image downsampling expedited adaptive least-squares (IDEAL) approach.

METHODS

The robustness of IDEAL was investigated using simulated DW-MRI data corrupted with different levels of Rician noise. Subsequently, the performance of the proposed method was tested by fitting bi- and triexponential IVIM model to in vivo renal DWI data acquired on a clinical 3 Tesla MRI scanner and compared to conventional approaches (fixed D* and segmented fitting).

RESULTS

The numerical simulations demonstrated that the IDEAL algorithm provides robust estimates of the IVIM parameters in the presence of noise (SNR of 20) as indicated by relatively low absolute percentage bias (maximal sMdPB <20%) and normalized RMSE (maximal RMSE <28%). The analysis of the in vivo data showed that the IDEAL-based IVIM parameter maps were less noisy and more visually appealing than those obtained using the fixed D* and segmented methods. Further, coefficients of variation for nearly all IVIM parameters were significantly reduced in cortex and medulla for IDEAL-based biexponential (coefficients of variation: 4%-50%) and triexponential (coefficients of variation: 7.5%-75%) IVIM modelling compared to the segmented (coefficients of variation: 4%-120%) and fixed D* (coefficients of variation: 17%-174%) methods, reflecting greater accuracy of this method.

CONCLUSION

The proposed fitting algorithm yields more robust IVIM parameter estimates and is less susceptible to poor SNR than the conventional fitting approaches. Thus, the IDEAL approach has the potential to improve the reliability of renal DW-MRI analysis for clinical applications.

Comparative study of conventional diffusion-weighted imaging and introvoxel incoherent motion in assessment of pathological grade of clear cell renal cell carcinoma

OBJECTIVE

To quantitatively compare the diagnostic values of conventional diffusion-weighted imaging (DWI) and introvoxel incoherent motion (IVIM) analysis of microstructural differences for clear cell renal cell carcinoma (ccRCC).

METHODS

Multiple b value DWIs and IVIMs were performed in patients with 146 ccRCCs, 42 with Grade Ⅰ, 46 with Grade Ⅱ, 28 with Grade Ⅲ and 30 with Grade Ⅳ. These tumours were divided into low (Ⅰ+Ⅱ, n = 88) and high grades (Ⅲ+Ⅳ, n = 58). The diagnostic efficacy of various diffusion parameters for predicting ccRCC grades was compared.

RESULTS

The mean signal-to-noise ratios (SNRs) of IVIM images at b = 0, 800 and 1500 s/mm2 were 31.9, 12.3 and 8.4, respectively. The apparent diffusion coefficient (ADC), D and D* values correlated negatively with ccRCC grading (r = -0.786,-0.913, -0879, p < 0.05). f values correlated positively with ccRCC grading (r = 0.811, p < 0.05). The ADC, D and D* values were higher for Grade Ⅱ ccRCC than that of Grade Ⅲ ccRCC (p < 005), however, f values were higher for Grade Ⅲ ccRCC than that of Grade Ⅱ ccRCC (p < 005). Receiver operating characteristic curve analyses showed that D values had the highest diagnostic efficacy in differentiating low/high and Ⅱ/Ⅲ ccRCC grading. The area under the curve, sensitivity, specificity and accuracy of the D values were 0.963, 0.960; 90.9%, 89.1%; 81.0%,78.6 and 89.0%, 87.8%, respectively. For pairwise comparisons of receiver operating characteristic curves and diagnostic efficacy, ADC was worse than IVIM (all p < 0.05).

CONCLUSION

IVIM parameters have better performance than ADC in differentiating ccRCC grading, given an adequate SNR of IVIM images.

ADVANCES IN KNOWLEDGE

1. D values had the highest diagnostic efficacy in differentiating low/high and Ⅱ/Ⅲ ccRCC grading. 2. IVIM parameters have better performance than ADC in differentiating ccRCC grading, given an adequate SNR of IVIM images. 3. The ADC, D and D* values correlated negatively with ccRCC grading, however, f values correlated positively with ccRCC grading.

A comparative study of four diffusion-weighted imaging models in the diagnosis of cervical cancer

BACKGROUND

Most commonly used diffusion-weighted imaging (DWI) models include intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and mono-exponential model (MEM). Previous studies of the four models were inconsistent on which model was more effective in distinguishing cervical cancer from normal cervical tissue.

PURPOSE

To assess the performance of four DWI models in characterizing cervical cancer and normal cervical tissue.

MATERIAL AND METHODS

Forty-seven women with suspected cervical carcinoma underwent DWI using eight b-values before treatment. Imaging parameters, calculated using IVIM, SEM, DKI, and MEM, were compared between cervical cancer and normal cervical tissue. The diagnostic performance of the models was evaluated using independent t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression analysis.

RESULTS

All parameters except pseudo-diffusion coefficient (D*) differed significantly between cervical cancer and normal cervical tissue (P < 0.001). Through logistic regression analysis, all combined models showed a significant improvement in area under the ROC curve (AUC) compared to individual DWI parameters. The model with combined IVIM parameters had a larger AUC value compared to those of other combined models (P < 0.05).

CONCLUSION

All four DWI models are useful for differentiating cervical cancer from normal cervical tissue and IVIM may be the optimal model.

Does diffusion-weighted magnetic resonance imaging help in the detection of renal parenchymal disease and staging/prognostication in chronic kidney disease?

Purpose

Diffusion-weighted imaging (DWI) in renal diseases is an upcoming modality, and its utility as an additional marker is yet to be proven. This study was intended to find the relationship between apparent diffusion coefficient (ADC) values with renal function tests and stages of chronic kidney disease (CKD) to assess renal dysfunction, and to label a cut-off for normal renal function and dysfunction.

Material and methods

A prospective diagnostic study was conducted on 120 patients: 60 with deranged renal function tests (RFT) and 60 with normal RFT. DWI using a 1.5-Tesla MRI (at b-values of 0 and 500 s/mm²) was done. A region of interest of size 1-2 cm² was placed on renal parenchyma in the region of medulla, one each, over the superior, mid, and lower regions of each kidney separately. ADC values were recorded for renal parenchyma and compared.

Results

In patients with renal dysfunction ADC values were significantly lower than in patients with normal function (1.75 ± 0.25 vs. 2.28 ± 0.21 of right kidney and 1.79 ± 0.17 vs. 2.29 ± 0.21 of left kidney [×10⁻³ mm²/s]; p = 0.001). ADC values of different stages of CKD showed a decreasing trend with increasing stage.

Conclusions

ADC values taken at all poles to get focal involvement of the kidney can be used to measure each kidney separately, and values can be individually correlated with the elevated renal parameters. The cut-off value of the mean ADC for individual kidneys was > 2.28 (×10⁻³ mm²/s) in normal renal function and < 2.00 (×10⁻³ mm²/s) in renal dysfunction.

Non-invasive investigation of early kidney damage in streptozotocin-induced diabetic rats by intravoxel incoherent motion diffusion-weighted (IVIM) MRI

Background

The current study investigated the performance of intravoxel incoherent motion diffusion (IVIM) technology in monitoring early renal injury in streptozotocin rats.

Methods

Forty-eight Sprague-Dawley (SD) rats were divided into a control group and a diabetic mellitus (DM) group. Six rats in each group were randomly selected for MR scans at four different time points (0, 4, 8, and 12 weeks). The IVIM-derived parameters (D, D*, f and ADC values) of the renal cortex (CO), outer and inner stripe of the outer medulla (OS, IS), and internal medulla (IM) were acquired. Changes in each IVIM-derived parameter over time were analyzed, and differences between the two groups at each point were assessed. The associations between the IVIM parameters and IV collagen expression, urine volume (UV), blood urea nitrogen (BUN), and serum creatinine (Scr) were investigated.

Results

The D and D* values of CO and the ADC values of CO, OS, IS and IM displayed significantly different trends between the two groups over time (P<0.05). In addition, significant correlations were discovered between the D* value of CO and UV and BUN (r=0.527, P=0.033; r=0.617, P=0.005), between the ADC value of IM and BUN (r=0.557, P=0.019) and between the f value of IM and BUN (r=0.527, P=0.033). No correlation was found between IVIM parameters and IV collagen expression and Scr.

Conclusions

IVIM is a potential sensitive and noninvasive technology for the simultaneous assessment of early renal cortical and medullary injuries induced by diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02530-8.

Effects of different breathing techniques on the IVIM-derived quantitative parameters of the normal pancreas

PURPOSE

To prospectively compare the differences in intravoxel incoherent motion (IVIM)-derived quantitative parameters in different anatomic locations of the normal pancreas with different breathing techniques in a healthy population.

METHOD

Twenty-six volunteers successfully underwent pancreas axial IVIM imaging with a 3.0-T MR system using 11 b-values (from 0 to 1000 sec/mm²) with three different breathing techniques: free breath (FB), liver dome scout (LDS), and phase scout (PS). The IVIM-derived quantitative parameters in three anatomic locations (head, body, and tail of the pancreas) were calculated. The intra-, inter-, and short-term consistency of IVIM-derived quantitative parameters were assessed by comparing 95% confidence interval (CI) of limits of agreement (LOA) of difference between measurements and clinical maximum allowed difference using the Bland-Altman method. The Kruskal-Wallis test was used to compare pancreatic IVIM-derived parameters.

RESULTS

In Bland-Altman graph, the maximum values of the 95% CIs of LOAs of D_slow, D_fast, and f were (0.123 ± 0.022) × 10^-3 mm²/sec, (22.093 ± 4.997) × 10^-3 mm²/sec, and (3.942 ± 0.621)%, and the consistency of D_slow and f was good and that of D_fast was poor overall. The D_slow, D_fast, and f values of normal pancreas were (1.056 ± 0.121) × 10^-3 mm²/sec, (55.755 ± 13.011) × 10^-3 mm²/sec, and (26.036 ± 2.361)%, respectively, and there aren't any breathing technique (P > 0.05) or location (P > 0.05) dependent differences.

CONCLUSIONS

Our study shows that IVIM-derived quantitative parameters of the pancreas may not be affected by breathing techniques and anatomic locations. The f and D_slow values have good repeated measurement consistency under different breathing techniques.

Target Heterogeneity in Oncology: The Best Predictor for Differential Response to Radioligand Therapy in Neuroendocrine Tumors and Prostate Cancer

Simple Summary

In the era of precision medicine, novel targets have emerged on the surface of cancer cells, which have been exploited for the purpose of radioligand therapy. However, there have been variations in the way these receptors are expressed, especially in prostate cancers and neuroendocrine tumors. This variable expression of receptors across the grades of cancers led to the concept of ‘target heterogeneity’, which has not just impacted therapeutic decisions but also their outcomes. Radiopharmaceuticals targeting receptors need to be used when there are specific indicators—either clinical, radiological, or at molecular level—warranting their use. In addition, response to these radioligands can be assessed using different techniques, whereby we can prognosticate further outcomes. We shall also discuss, in this review, the conventional as well as novel approaches of detecting heterogeneity in prostate cancers and neuroendocrine tumors.

Abstract

Tumor or target heterogeneity (TH) implies presence of variable cellular populations having different genomic characteristics within the same tumor, or in different tumor sites of the same patient. The challenge is to identify this heterogeneity, as it has emerged as the most common cause of ‘treatment resistance’, to current therapeutic agents. We have focused our discussion on ‘Prostate Cancer’ and ‘Neuroendocrine Tumors’, and looked at the established methods for demonstrating heterogeneity, each with its advantages and drawbacks. Also, the available theranostic radiotracers targeting PSMA and somatostatin receptors combined with targeted systemic agents, have been described. Lu-177 labeled PSMA and DOTATATE are the ‘standard of care’ radionuclide therapeutic tracers for management of progressive treatment-resistant prostate cancer and NET. These approved therapies have shown reasonable benefit in treatment outcome, with improvement in quality of life parameters. Various biomarkers and predictors of response to radionuclide therapies targeting TH which are currently available and those which can be explored have been elaborated in details. Imaging-based features using artificial intelligence (AI) need to be developed to further predict the presence of TH. Also, novel theranostic tools binding to newer targets on surface of cancer cell should be explored to overcome the treatment resistance to current treatment regimens.

Renal Diffusion-Weighted Imaging in Healthy Dogs: Reproducibility, Test-Retest Repeatability, and Selection of the Optimal b-value Combination

Diffusion-weighted imaging (DWI) magnetic resonance imaging can evaluate alterations in the microstructure of the kidney. The purpose of this study was to assess the apparent diffusion coefficient (ADC) and the intravoxel incoherent motion model (IVIM) parameters of a normal kidney in healthy dogs, to evaluate the effect of b-value combinations on the ADC value, and the reproducibility and test-retest repeatability in monoexponential and IVIM analysis. In this experimental study, the ADC, pure diffusion coefficient (D), pseudodiffusion coefficient (D^*), and perfusion fraction (f _p) were measured from both kidneys in nine healthy beagles using nine b-values (b = 0, 50, 70, 100, 150, 200, 500, 800, and 1,000 s/mm²) twice with a 1-week interval between measurements. Interobserver and intraobserver reproducibility, and test-retest repeatability of the measurements were calculated. ADC values were measured using 10 different b-value combinations consisting of three b-values each, and were compared to the ADC obtained from nine b-values. All the ADC, D, D^*, and f _p values measured from the renal cortex, medulla, and the entire kidney had excellent interobserver and intraobserver reproducibility, and test-retest repeatability. The ADC obtained from a b-value combination of 0, 100, and 800 s/mm² had the highest intraclass correlation coefficient with the ADC from nine b-values. The results of this study indicated that DWI MRI using multiple b-values is feasible for the measurement of ADC and IVIM parameters with high reproducibility and repeatability in the kidneys of healthy dogs. A combination of b = 0, 100, and 800 s/mm² can be used for ADC measurements when multiple b-values are not available in dogs.

A comparative study of methods for determining Intravoxel incoherent motion parameters in cervix cancer

Background

To compare different fitting methods for determining IVIM (Intravoxel Incoherent Motion) parameters and to determine whether the use of different IVIM fitting methods would affect differentiation of cervix cancer from normal cervix tissue.

Methods

Diffusion-weighted echo-planar imaging of 30 subjects was performed on a 3.0 T scanner with b-values of 0, 30, 100, 200, 400, 1000 s/mm². IVIM parameters were estimated using the segmented (two-step) fitting method and by simultaneous fitting of a bi-exponential function. Segmented fitting was performed using two different cut-off b-values (100 and 200 s/mm²) to study possible variations due to the choice of cut-off. Friedman’s test and Student’s t-test were respectively used to compare IVIM parameters derived from different methods, and between cancer and normal tissues.

Results

No significant difference was found between IVIM parameters derived from the segmented method with b-value cutoff of 200 s/mm² and the simultaneous fitting method (P>0.05). Tissue diffusivity (D) and perfusion fraction (f) were significantly lower in cervix cancer than normal tissue (P< 0.05).

Conclusions

IVIM parameters derived using fitting methods with small cutoff b-values could be different, however, the segmented method with b-value cutoff of 200 s/mm² are consistent with the simultaneous fitting method and both can be used to differentiate between cervix cancer and normal tissue.

The value of intravoxel incoherent motion and diffusion kurtosis imaging in the assessment of tumor regression grade and T stages after neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer

PURPOSE

To evaluate the role of IVIM and diffusion kurtosis imaging (DKI) in identifying pathologic complete response (pCR) and T stages after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC).

METHOD

Forty-two patients with biopsy-proven rectal adenocarcinoma, who underwent both pre-and post-CRT MRI with IVIM and DKI sequences on a 3 T scanner, were enrolled prospectively. According to the pathologic ypTNM stages and tumor regression grade (TRG), patients were grouped into pCR (TRG0) and non-pCR (TRG1-3) groups and low T stage (ypT0-2) and high T stage (ypT3-4) groups. IVIM parameters (the slow diffusion coefficient [D], fast diffusion coefficient [D*], perfusion fraction [f]), DKI parameters (mean diffusivity [MD] and mean kurtosis [MK]), and mono-exponential ADC were calculated and analyzed between groups.

RESULTS

The pCR group had significantly higher post-CRT ADC, D*, f, and MD values than non-pCR group, and higher percent changes in the ADC, f, and MD values (all P < 0.05). The post-CRT MD values yielded the highest AUC (0.788) with higher sensitivity than post-ADC values (82.9 % vs. 77.1 %, respectively). Post-CRT ADC and MD values and the percent changes in the ADC and MD values were also negatively correlated with TRG (all P < 0.05). Besides, negative correlations were found among the pre-CRT MD, post-CRT ADC, D, f, and MD values and the ypT stages (all P < 0.05).

CONCLUSIONS

Both IVIM and DKI parameters could provide more information when evaluating pCR and T stages after nCRT. In particular, the diagnostic performance of the MD values was more valuable than ADC values in being able to determine pCR.

Ki-67 labeling index and the grading of cerebral gliomas by using intravoxel incoherent motion diffusion-weighted imaging and three-dimensional arterial spin labeling magnetic resonance imaging

BACKGROUND

Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and three-dimensional arterial spin labeling (3D-ASL) have been applied to brain tumors; however, the relationship between their parameters and the Ki-67 labeling index (Ki-67 LI) for the grading of gliomas have yet to be investigated.

PURPOSE

The aim of this study is to compare multiple parameters obtained from IVIM-DWI and 3D-ASL with the Ki-67 LI when grading gliomas.

MATERIAL AND METHODS

Fifty-two patients with pathologically confirmed gliomas had undergone magnetic resonance imaging (MRI), including IVIM-DWI and 3D-ASL imaging. Mann-Whitney U tests were conducted and receiver operating characteristic (ROC) curves were generated to determine parameters for distinguishing high-grade gliomas (HGGs) from low-grade gliomas (LGGs). These parameters included the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo diffusivity (D*), perfusion fraction (f), cerebral blood flow (CBF), and their relative values (rADC, rD, rD*, rf, and rCBF). Spearman correlation analysis was used to assess the correlations of the parameters of MRI with the Ki-67 LI.

RESULTS

The rADC, rD, and rf were significantly lower in HGGs than in LGGs (P < 0.005 for all). The rD had a significantly greater area under the ROC curve than that of the other parameters in the differentiation of HGGs from LGGs (P < 0.05). Both the rD and rf were moderately negatively correlated with the Ki-67 LI.

CONCLUSION

Both the rD and rf can be used for the quantitative prediction of the Ki-67 LI. Among the extracted parameters, the rD had the significantly greatest diagnostic efficacy.

Application of monoexponential, biexponential, and stretched-exponential models of diffusion-weighted magnetic resonance imaging in the differential diagnosis of metastases and myeloma in the spine-Univariate and multivariate analysis of related parameters

OBJECTIVE

To explore the value of related parameters in monoexponential, biexponential, and stretched-exponential models of diffusion-weighted imaging (DWI) in differentiating metastases and myeloma in the spine.

METHODS

53 metastases and 16 myeloma patients underwent MRI with 10 b-values (0-1500 s/mm²). Parameters of apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), the distribution diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α) from DWI were calculated. The independent sample t test and the Mann-Whiney U test were used to compare the statistical difference of the parameter values between the two. Receiver operating characteristics (ROC) curve analysis was used to identify the diagnostic efficacy. Then substituted each parameter into the decision tree model and logistic regression model, identified meaningful parameters, and evaluated their joint diagnostic performance.

RESULTS

The ADC, D, and α values of metastases were higher than those of myeloma, whereas the D* value was lower than that of myeloma, and the difference was significant (p < 0.05); the area under the ROC curve for the above parameters was 0.661, 0.710, 0.781, and 0.743, respectively. There was no significant difference in the f and DDC values (p > 0.05). D and α were found to conform to the decision tree model, and the accuracy of model diagnosis was 84.1%. ADC and α were found to conform to the logistic regression model, and the accuracy was 87.0%.

CONCLUSION

The 3 models of DWI have certain values indifferentiating metastases and myeloma in spine, and the diagnostic performance of ADC, D, α and D*was better. Combining ADC with α may markedly aid in the differential diagnosis of the two.

ADVANCES IN KNOWLEDGE

Monoexponential, biexponential, and stretched-exponential models can offer additional information in the differential diagnosis of metastases and myeloma in the spine. Decision tree model and logistic regression model are effective methods to help further distinguish the two.

Diffusion processes modeling in magnetic resonance imaging

Background

The paper covers modern approaches to the evaluation of neoplastic processes with diffusion-weighted imaging (DWI) and proposes a physical model for monitoring the primary quantitative parameters of DWI and quality assurance. Models of hindered and restricted diffusion are studied.

Material and method

To simulate hindered diffusion, we used aqueous solutions of polyvinylpyrrolidone with concentrations of 0 to 70%. We created siloxane-based water-in-oil emulsions that simulate restricted diffusion in the intracellular space. To obtain a high signal on DWI in the broadest range of b values, we used silicon oil with high T₂: cyclomethicone and caprylyl methicone. For quantitative assessment of our phantom, we performed DWI on 1.5T magnetic resonance scanner with various fat suppression techniques. We assessed water-in-oil emulsion as an extracorporeal source signal by simultaneously scanning a patient in whole-body DWI sequence.

Results

We developed phantom with control substances for apparent diffusion coefficient (ADC) measurements ranging from normal tissue to benign and malignant lesions: from 2.29 to 0.28 mm²/s. The ADC values of polymer solutions are well relevant to the mono-exponential equation with the mean relative difference of 0.91%.

Conclusion

The phantom can be used to assess the accuracy of the ADC measurements, as well as the effectiveness of fat suppression. The control substances (emulsions) can be used as a body marker for quality assurance in whole-body DWI with a wide range of b values.

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

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

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.

Comparison of Monoexponential, Biexponential, Stretched-Exponential, and Kurtosis Models of Diffusion-Weighted Imaging in Differentiation of Renal Solid Masses

Objective

To compare various models of diffusion-weighted imaging including monoexponential apparent diffusion coefficient (ADC), biexponential (fast diffusion coefficient [D_f], slow diffusion coefficient [D_s], and fraction of fast diffusion), stretched-exponential (distributed diffusion coefficient and anomalous exponent term [α]), and kurtosis (mean diffusivity and mean kurtosis [MK]) models in the differentiation of renal solid masses.

Materials and Methods

A total of 81 patients (56 men and 25 women; mean age, 57 years; age range, 30–69 years) with 18 benign and 63 malignant lesions were imaged using 3T diffusion-weighted MRI. Diffusion model selection was investigated in each lesion using the Akaike information criteria. Mann-Whitney U test and receiver operating characteristic (ROC) analysis were used for statistical evaluations.

Results

Goodness-of-fit analysis showed that the stretched-exponential model had the highest voxel percentages in benign and malignant lesions (90.7% and 51.4%, respectively). ADC, D_s, and MK showed significant differences between benign and malignant lesions (p < 0.05) and between low- and high-grade clear cell renal cell carcinoma (ccRCC) (p < 0.05). α was significantly lower in the benign group than in the malignant group (p < 0.05). All diffusion measures showed significant differences between ccRCC and non-ccRCC (p < 0.05) except D_f and α (p = 0.143 and 0.112, respectively). α showed the highest diagnostic accuracy in differentiating benign and malignant lesions with an area under the ROC curve of 0.923, but none of the parameters from these advanced models revealed significantly better performance over ADC in discriminating subtypes or grades of renal cell carcinoma (RCC) (p > 0.05).

Conclusion

Compared with conventional diffusion parameters, α may provide additional information for differentiating benign and malignant renal masses, while ADC remains the most valuable parameter for differentiation of RCC subtypes and for ccRCC grading.

Performing IVIM-DWI using the multifunctional nanosystem for the evaluation of the antitumor microcirculation changes

OBJECTIVES

There is a controversy about the D* and f values of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for mid- and long-term efficacy monitoring of tumor blood perfusion. To monitor the antitumor efficacy of the F/A-PLGA@DOX/SPIO nanosystem via IVIM-DWI and to explore the value of parameters pseudo-diffusion (D*) and fraction of pseudo-diffusion (f) for evaluating therapeutic effect in non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

Thirty-six A549 tumor-bearing mice were divided randomly into three groups (each n = 12). Group 1 (G1) was injected with saline (the control group). Group 2 (G2) and group 3(G3) were injected with DOX and F/A-PLGA@DOX/SPIO, respectively. Each group underwent IVIM-DWI scanning at baseline and 3, 14, 21, and 28 days after treatment. D* and f values were derived using GE AW 4.5 post-processing station. All mice were sacrificed for pathological examination.

RESULTS

The D* value of all three groups showed an upward trend, with the highest increase in G1 and the lowest in G3. Conversely, the f value of all groups trended to decrease within 7 days, of which G3 showed the most significant decline. Immunohistochemical staining revealed that vascular endothelial growth factor (VEGF)-positive staining rate and the microvessel density (MVD) of the tumors in G3 were significantly lower than those of the other groups (P < 0.05). The D* and f values were significantly and positively correlated to CD31 (r = 0.654, P < 0.001; r = 0.712, P < 0.001) and VEGF (r = 0.694, P < 0.001; r = 0.664, P < 0.001).

CONCLUSION

IVIM-DWI-derived parameters D* and f are valuable indicators for the evaluation of the antitumor microcirculation changes of multifunctional nanosystem.

Value of Intravoxel Incoherent Motion for Hepatocellular Carcinoma Grading

BACKGROUND

To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) parameters in estimation of hepatocellular carcinoma (HCC) grading.

MATERIALS AND METHODS

Twenty-nine patients with histopathologically diagnosed as 42 HCC at explant were included in this retrospective study. All patients were examined by 1.5T magnetic resonance imaging with the use of 4-channel phased array body coil. In addition to routine pre- and postcontrast sequences, IVIM (16 different b factors varying from 0 to 1300 s/mm²) and conventional diffusion-weighted imaging (3 different b factors of 50, 400, 800 s/mm²) were obtained with single-shot echo planar spin echo sequence. Apparent diffusion coefficient (ADC) and IVIM parameters including mean D (true diffusion coefficient), D* (pseudo-diffusion coefficient associated with blood flow), and f (perfusion fraction) values were calculated. Histopathologically, HCC was classified as low (grade 1, 2) and high (grade 3, 4) grade in accordance with the Edmondson-Steiner score. Quantitatively, ADC, D, D*, and f values were compared between the low- and high-grade groups by Student t test. The relationship between the parameters and histologic grade was analyzed using the Spearman's correlation test. To evaluate the diagnostic performance of the parameters, receiver operating characteristic analysis was performed.

RESULTS

High-grade HCCs had significantly lower ADC and D values than low grade groups (P = .005 and P = .026, retrospectively); ADC and D values were inversely correlated with tumor grade (r = -0.519, P = .011, r = -0.510, P = .026, respectively). High-grade HCCs had significantly higher f values when compared with the low-grade group (P = .005). The f values were positively correlated with tumor grade (r = 0.548, P = .007). The best discriminative parameter was f value. Cut-off value of 32% of f values showed sensitivity of 75.6% and a specificity of 73.5%.

CONCLUSION

ADC values and IVIM parameters such as f values appear to reflect the grade of HCCs.

Intravoxel incoherent motion diffusion-weighted imaging evaluated the response to concurrent chemoradiotherapy in patients with cervical cancer

To evaluate the application of multiple b values diffusion-weighted imaging based on biexponential signal decay model to predict the response to concurrent chemoradiotherapy in cervical cancer patients.This prospective study enrolled 28 patients (mean age: 50.89 ± 10.70 years) with cervical cancer confirmed by biopsy who received concurrent chemoradiotherapy. Pelvic magnetic resonance scans were performed 2 weeks before, 7 days and 21 days after the initiation of therapy, and 1 month after the end of the treatment. Diffusion-weighted imaging with b values of 0, 50, 450, and 850 s/mm were performed, and tumor volume, means of tumor apparent diffusion coefficient (ADC)min, ADCmean, ADCslow, ADCfast, and Ffast were measured.Pretreatment ADCmin and ADCslow of good outcome group were significantly higher than those of poor outcome group (P < .05). At the 7th day of the treatment, Ffast and its change rate of good outcome group were significantly higher than those of poor outcome group (P < .05). At the 7th day and 21st day of the treatment, Ffast showed a slowly increasing tendency with no significant difference compared with pretreatment value in poor outcome group (P < .05). One month post-treatment, only ADCslow change rate was significantly higher in good outcome group than that in poor outcome group.Intravoxel incoherent motion-related ADC values could be utilized to better predict the outcome of cervical cancer chemoradiotherapy.

The added value of intravoxel incoherent motion diffusion weighted imaging parameters in differentiating high-grade pancreatic neuroendocrine neoplasms from pancreatic ductal adenocarcinoma

The aim of the present study was to investigate the potential significance of intravoxel incoherent motion (IVIM)-diffusion weighted imaging (DWI) in differentiating high-grade pancreatic neuroendocrine neoplasms (pNENs) from pancreatic ductal adenocarcinoma (PDAC). A total of 50 patients, including 37 patients with PDAC and 13 patients with high-grade pNENs, underwent pancreatic multiple b-values DWI with 15 b-values including 0, 10, 20, 40, 60, 80, 100, 150, 200, 400, 800, 1,000, 1,200, 1,500 and 2,000 sec/mm². Standard apparent diffusion coefficient (ADC_standard) and IVIM parameter [slow apparent diffusion coefficient (D_slow), fast apparent diffusion coefficient (D_fast), fraction of fast apparent diffusion coefficient (ƒ)] values of PDAC and pNENs were compared. P<0.05 was considered to indicate a statistically significant difference. Receiver operating characteristics analysis was performed in order to evaluate the diagnostic potential of IVIM parameters for differentiating high-grade pNENs from PDAC. D_slow of pNENs was significantly lower compared with that of PDAC (0.460 vs. 0.579×10⁻³ mm²/sec; P=0.001). D_fast of pNENs was significantly higher compared with that of PDAC (13.361 vs. 4.985×10⁻³ mm²/sec; P<0.001). Area under the curve of D_slow, D_fast and combined D_slow and D_fast was 0.793, 0.863 and 0.885 respectively. The specificity and sensitivity of D_slow≤0.472×10⁻³ mm²/sec were 97.3 and 53.9%, respectively, for differentiating high-grade pNENs from PDAC. The specificity and sensitivity of D_fast >9.58×10⁻³ mm²/sec were 91.9 and 69.2%, respectively, for differentiating high-grade pNENs from PDAC. When D_slow and D_fast were combined, the specificity and sensitivity for differentiating high-grade pNENs from PDAC were 76.9 and 100%, respectively. Taken together, these results indicated that the diffusion-associated parameter D_slow and the perfusion-associated parameter D_fast of IVIM-DWI may differentiate high-grade pNENs from PDAC with high diagnostic accuracy, and that IVIM-DWI may be a valuable biomarker in differentiating pancreatic neoplasms.

On the sensitivity of the diffusion MRI signal to brain activity in response to a motor cortex paradigm

Diffusion functional magnetic resonance imaging (dfMRI) is a promising technique to map functional activations by acquiring diffusion‐weighed spin‐echo images. In previous studies, dfMRI showed higher spatial accuracy at activation mapping compared to classic functional MRI approaches. However, it remains unclear whether dfMRI measures result from changes in the intracellular/extracellular environment, perfusion, and/or T₂ values. We designed an acquisition/quantification scheme to disentangle such effects in the motor cortex during a finger‐tapping paradigm. dfMRI was acquired at specific diffusion weightings to selectively suppress perfusion and free‐water diffusion, then time series of the apparent diffusion coefficient (ADC‐fMRI) and of intravoxel incoherent motion (IVIM) effects were derived. ADC‐fMRI provided ADC estimates sensitive to changes in perfusion and free‐water volume, but not to T₂/T₂* values. With IVIM modeling, we isolated the perfusion contribution to ADC, while suppressing T₂ effects. Compared to conventional gradient‐echo blood oxygenation level‐dependent fMRI, activation maps obtained with dfMRI and ADC‐fMRI had smaller clusters, and the spatial overlap between the three techniques was below 50%. Increases of perfusion fractions were observed during task in both dfMRI and ADC‐fMRI activations. Perfusion effects were more prominent with ADC‐fMRI than with dfMRI but were significant in less than 25% of activation regions. IVIM modeling suggests that the sensitivity to task of dfMRI derives from a decrease of intracellular/extracellular diffusion and an increase of the pseudo‐diffusion signal fraction, leading to different, more confined spatial activation patterns compared to classic functional MRI.

An alternative approach to contrast-enhanced imaging: diffusion-weighted imaging and T1-weighted imaging identifies and quantifies necrosis in Wilms tumour

OBJECTIVES

Volume of necrosis in Wilms tumour is informative of chemotherapy response. Contrast-enhanced T1-weighted MRI (T1w) provides a measure of necrosis using gadolinium. This study aimed to develop a non-invasive method of identifying non-enhancing (necrotic) tissue in Wilms tumour.

METHODS

In this single centre, retrospective study, post-chemotherapy MRI data from 34 Wilms tumour patients were reviewed (March 2012-March 2017). Cases with multiple b value diffusion-weighted imaging (DWI) and T1w imaging pre- and post-gadolinium were included. Fractional T1 enhancement maps were generated from the gadolinium T1w data. Multiple linear regression determined whether fitted parameters from a mono-exponential model (ADC) and bi-exponential model (IVIM - intravoxel incoherent motion) (D, D*, f) could predict fractional T1 enhancement in Wilms tumours, using normalised pre-gadolinium T1w (T1wnorm) signal as an additional predictor. Measured and predicted fractional enhancement values were compared using the Bland-Altman plot. An optimum threshold for separating necrotic and viable tissue using fractional T1 enhancement was established using ROC.

RESULTS

ADC and D (diffusion coefficient) provided the strongest predictors of fractional T1 enhancement in tumour tissue (p < 0.001). Using the ADC-T1wnorm model (adjusted R2 = 0.4), little bias (mean difference = - 0.093, 95% confidence interval = [- 0.52, 0.34]) was shown between predicted and measured values of fractional enhancement and analysed via the Bland-Altman plot. The optimal threshold for differentiating viable and necrotic tissue was 33% fractional T1 enhancement (based on measured values, AUC = 0.93; sensitivity = 85%; specificity = 90%).

CONCLUSIONS

Combining ADC and T1w imaging predicts enhancement in Wilms tumours and reliably identifies and measures necrotic tissue without gadolinium.

KEY POINTS

• Alternative method to identify necrotic tissue in Wilms tumour without using contrast agents but rather using diffusion and T 1 weighted MRI. • A method is presented to visualise and quantify necrotic tissue in Wilms tumour without contrast. • The proposed method has the potential to reduce costs and burden to Wilms tumour patients who undergo longitudinal follow-up imaging as contrast agents are not used.

Detecting impaired function of renal allografts at the early stage after transplantation using intravoxel incoherent motion imaging

Background

Detecting renal allografts with impaired function early after renal transplantation and timely intervention are important to ensure a successful outcome.

Purpose

To detect impaired function of renal allografts at the early stage after renal transplantation using intravoxel incoherent motion imaging (IVIM).

Material and Methods

Forty-six recipients with good allograft function and 32 recipients with impaired function were included in this study. All participants were scanned with IVIM using 11 b-values on a 3-T magnetic resonance (MR) scanner; the apparent diffusion coefficient (ADC), ADC of slow diffusion (ADCslow), pseudo-diffusion (ADCfast), and perfusion fraction (f) values were calculated using a full bi-exponential model. Correlations between estimated glomerular filtration rate (eGFR) and the IVIM parameters were assessed by using Spearman correlation analysis. Receiver operating characteristics were used to assess the diagnostic utilities for detecting allografts with impaired function.

Results

The ADC, ADCslow, ADCfast, and f values of the renal cortex and the ADC and ADCslow values of the renal medulla were significantly higher in allografts with good function compared to those with impaired function (all P < 0.05). There was a significant corticomedullary difference in ADCslow, ADC, and f in all allografts. ADCfast values were higher in the cortex than in the medulla for allografts with good function but no differences were seen in allografts with impaired function ( P > 0.05). Combined use of all cortical IVIM parameters has higher efficacy in detecting renal allograft dysfunction than any single parameter (sensitivity = 90.62%; specificity = 78.26%).

Conclusion

IVIM technique may be useful for detecting renal allograft dysfunction, especially combined use of cortical parameters.

Role of Intravoxel Incoherent Motion in Discriminating Hepatitis B Virus-Related Intrahepatic Mass-Forming Cholangiocarcinoma from Hepatocellular Carcinoma Based on Liver Imaging Reporting and Data System v2018

Backgroud: Intravoxel incoherent motion (IVIM) could be used to characterize benign and malignant hepatic lesions and predict the histological grade of hepatocellular carcinoma (HCC). To evaluate IVIM-derived parameters for differentiating between hepatitis B virus (HBV)-related intrahepatic mass-forming cholangiocarcinoma (IMCC) and HCC based on the Liver Imaging Reporting and Data System (LI-RADS) v2018. Materials and Methods: 20 IMCC patients and one-to-one matched control HCC patients were retrospectively assessed. IVIM scanning with 11 b-values (from 0 to 1500 s/mm²) was obtained using a 3.0-T magnetic resonance scanner. Apparent diffusion coefficient (ADC) and IVIM parameters, including diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f), were compared between IMCC and HCC. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performances of ADC, D, f, and D*. The LI-RADS features and a final category were also compared using LI-RADS v2018. Results: ADC and D were significantly higher in IMCC than in HCC (p = 0.012 and p = 0.007, respectively); f was significantly higher in HCC than in IMCC (p = 0.004). The area under the ROC curve values for ADC, D, and f for differentiating HBV-related IMCC from HCC were 0.724, 0.753, and 0.741, respectively. Conclusion: The majority of HBV-related IMCCs can be categorized as LR-M by using LI-RADS. However, atypical IMCCs may be classified as non-LR-M. ADC, D, and f values may be helpful in differentiating HBV-related IMCC from HCC, and similar diagnostic performances were obtained for these values.

Noninvasive assessment of renal fibrosis by magnetic resonance imaging and ultrasound techniques

Renal fibrosis is a useful biomarker for diagnosis and guidance of therapeutic interventions of chronic kidney disease (CKD), a worldwide disease that affects more than 10% of the population and is one of the major causes of death. Currently, tissue biopsy is the gold standard for assessment of renal fibrosis. However, it is invasive, and prone to sampling error and observer variability, and may also result in complications. Recent advances in diagnostic imaging techniques, including magnetic resonance imaging (MRI) and ultrasonography, have shown promise for noninvasive assessment of renal fibrosis. These imaging techniques measure renal fibrosis by evaluating its impacts on the functional, mechanical, and molecular properties of the kidney, such as water mobility by diffusion MRI, tissue hypoxia by blood oxygenation level dependent MRI, renal stiffness by MR and ultrasound elastography, and macromolecule content by magnetization transfer imaging. Other MR techniques, such as T1/T2 mapping and susceptibility-weighted imaging have also been explored for measuring renal fibrosis. Promising findings have been reported in both preclinical and clinical studies using these techniques. Nevertheless, limited specificity, sensitivity, and practicality in these techniques may hinder their immediate application in clinical routine. In this review, we will introduce methodologies of these techniques, outline their applications in fibrosis imaging, and discuss their limitations and pitfalls.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Evaluation of the Cell Density and Angiogenesis of Cirrhosis-Related Nodules in an Experimental Rat Model: Comparison and Correlation With Dynamic Contrast-Enhanced MRI

Background

Intravoxel incoherent motion diffusion‐weighted imaging (IVIM‐DWI) and dynamic contrast‐enhanced MRI (DCE‐MRI) are sensitive imaging modalities for detecting liver lesions, but their value in evaluating cirrhosis‐related nodules remains unclear.

Purpose

To investigate whether IVIM‐DWI and DCE‐MRI can differentiate different types of cirrhosis‐related nodules, and whether these modalities can monitor changes in cell density and angiogenesis during the malignant transformation of cirrhosis‐related nodules in a rat model

Study Type

Prospective.

Animal Model

Thirty‐five male Sprague–Dawley rats with 106 cirrhosis‐related nodules (19 regenerative nodules [RNs], 47 dysplastic nodules [DNs], and 40 hepatocellular carcinomas [HCCs]).

Field Strength/Sequence

IVIM‐DWI and DCE sequence at 3.0T MRI.

Assessment

IVIM‐DWI parameters (D, D*, f, and apparent diffusion coefficient [ADC]) and DCE‐MRI parameters (K^trans, K_ep, and V_e) were calculated by two radiologists using postprocessing software. The “cell density” and “unpaired arterial ratio” were analyzed with a microscope by two pathologists.

Statistical Tests

MRI parameters were compared among the different types of nodules by one‐way analysis of variance or the Kruskal–Wallis test. The Pearson correlation test was used to analyze the correlation of MRI parameters with the pathological types of nodules, cell density, and unpaired arterial ratio.

Results

The K^trans, K_ep, and V_e values of HCCs were significantly higher than those of DNs and RNs. D and ADC values were significantly lower in HCCs than in DNs and RNs. There were moderate positive correlations of K^trans with the pathological types of nodules and the unpaired arterial ratio. Moderate negative correlations were observed among D, ADC, and the pathological types of nodules, between D and cell density, and between ADC and cell density.

Data Conclusion

IVIM‐DWI and DCE‐MRI are valuable in differentiating different types of cirrhotic‐related nodules. D and ADC are correlated with changes in cell density during the malignant transformation of cirrhosis‐related nodules, while K^trans is correlated with increased angiogenesis.

Level of Evidence: 1

Technical Efficacy: Stage 1

J. Magn. Reson. Imaging 2020;51:812–823.

Intravoxel incoherent motion diffusion MR and diffusion kurtosis imaging for discriminating atypical bone metastasis from benign bone lesion

Objectives:

To investigate the feasibility of intravoxel incoherent motion (IVIM) diffusion MR and diffusion kurtosis imaging (DKI) in discriminating atypical bone metastasis from benign bone lesion in patients with tumors.

Methods:

Patients with bone lesions in lower extremity suspected of metastases were enrolled in this prospective study. IVIM diffusion MR and DKI were performed before biopsy. Apparent diffusion coefficient (ADC), true diffusion (D), perfusion fraction (f) and perfusion-related pseudodiffusion (D*) were generated with IVIM, while mean kurtosis (MK) and mean diffusion (MD) generated with DKI. Two radiologists blinded to pathology results separately measured these parameters for each lesion through drawing region of interest. Intraclass correlation coefficient was used to determine the inter-reader viability in measurement. The patients with pathology-confirmed metastasis or benign lesion were analyzed. The Mann–Whitney test was used to compare IVIM and DKI parameters between metastasis group and benign lesion group. Receiver operating characteristic curves were constructed to evaluate the ability of discrimination.

Results:

Bone lesions from 28 patients (metastasis, n = 15; benign lesion, n = 13; mean age = 55 years; age range, 34~77) were analyzed with IVIM and DKI. Intraclass correlation coefficient was greater than 0.8 for all parameters. ADC, D and MD were significantly lower in metastases versus benign lesions (p<0.05). MK and f value were significantly higher in metastases versus benign lesions (p<0.05). D* was not significantly different between the two groups (p>0.05). Areas under curve for ADC, D, f, MK and MD were 0.935, 0.939, 0.891, 0.840 and 0.844 respectively.

Conclusions:

IVIM and DKI derived parameters distinguish between atypical bone metastasis and benign bone lesion in selected patients with tumors.

Advances in knowledge:

Bone metastasis and benign bone lesion differ in water molecular diffusion.

Intravoxel incoherent motion derived true diffusion distinguishes between atypical bone metastasis and benign lesion.

Differentiating between malignant and benign renal tumors: do IVIM and diffusion kurtosis imaging perform better than DWI?

OBJECTIVE

To quantitatively compare the diagnostic values of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) in differentiating between malignant and benign renal tumors.

METHODS

Multiple b value DWIs and DKIs were performed in 180 patients with renal tumors, which were divided into clear cell renal cell carcinoma (ccRCC), non-ccRCC, and benign renal tumor group. The apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean kurtosis (MK), and mean diffusivity (MD) maps were calculated. The diagnostic efficacy of various diffusion parameters for predicting malignant renal tumors was compared.

RESULTS

The ADC, D, and MD values of ccRCCs were higher, while D*, f, and MK values were lower than those of benign renal tumors (all p < 0.025). The D* and f values of non-ccRCCs were lower than those of benign renal tumors (p = 0.002 and p < 0.001, respectively). The difference of ADC, D, MD, and MK values between non-ccRCCs and benign renal tumors was not statistically significant (p > 0.05). The ADC, D, MD, and f values of ccRCCs were higher, while MK values were lower than those of non-ccRCCs (all p < 0.001). The AUC values of ADC, D, D*, f, MK, and MD were 0.849, 0.891, 0.708, 0.656, 0.862, and 0.838 for differentiating ccRCCs from benign renal tumors, respectively. The AUC values of D* and f were 0.772 and 0.866 for discrimination between non-ccRCCs and benign renal tumors, respectively.

CONCLUSION

IVIM parameters are the best, while DWI and DKI parameters have similar performance in differentiating malignant and benign renal tumors.

KEY POINTS

• The D value is the best parameter for differentiating ccRCC from benign renal tumors. • The f value is the best parameter for differentiating non-ccRCC from benign renal tumors. • Conventional DWI and DKI have similar performance in differentiating malignant and benign renal tumors.

Value of intravoxel incoherent motion for differential diagnosis of renal tumors

BACKGROUND

Few studies have reported on the use of intravoxel incoherent motion (IVIM) for renal tumors.

PURPOSE

To investigate the value of IVIM for distinguishing renal tumors.

MATERIAL AND METHODS

Thirty-one patients with clear cell renal cell carcinomas (CCRCCs), 13 patients with renal angiomyolipomas with minimal fat (RAMFs), eight patients with chromophobe renal cell carcinomas (ChRCCs), and ten patients with papillary renal cell carcinomas (PRCCs) were examined. The tissue diffusivity (D), pseudodiffusivity (D*), and perfusion fraction (f) were calculated.

RESULTS

The D and f values were highest for CCRCCs, lowest for PRCCs, and intermediate for ChRCCs and RAMFs ( P < 0.05). The D values of CCRCCs differed significantly from those of ChRCCs and PRCCs ( P < 0.05). The D* values were highest for RAMFs, lowest for ChRCCs, and intermediate for CCRCCs and PRCCs ( P < 0.05). Statistically significant differences were observed between the D* values of CCRCCs and RAMFs ( P < 0.05). The D* values of the CCRCCs differed significantly from the D* values of the ChRCCs ( P < 0.05). Using the D and f values of 1.10 and 0.41, respectively, as the threshold values for differentiating CCRCCs from RAMFs, ChRCCs, and PRCCs, the best results had sensitivities of 81.0% and 66.8% and specificities of 85.7% and 81.0%, respectively. Using the D* value of 0.038 as the threshold value for differentiating RAMFs from CCRCCs, ChRCCs, and PRCCs, the best result obtained had a sensitivity of 90.5% and specificity of 76.2%.

CONCLUSION

IVIM may provide information for differentiating renal tumor types.

Characterization of focal liver lesions using the stretched exponential model: comparison with monoexponential and biexponential diffusion-weighted magnetic resonance imaging

OBJECTIVE

To compare the stretched exponential model of diffusion-weighted imaging (DWI) with monoexponential and biexponential models in terms of the ability to characterize focal liver lesions (FLLs).

METHODS

This retrospective study included 180 patients with FLLs who underwent magnetic resonance imaging including DWI with nine b values at 3.0 T. The distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index (α) from a stretched exponential model; true diffusion coefficient (D_t), pseudo-diffusion coefficient (D_p), and perfusion fraction (f) from a biexponential model; and apparent diffusion coefficient (ADC) were calculated for each lesion. Diagnostic performances of the parameters were assessed through receiver operating characteristic (ROC) analysis. For 20 patients with treated hepatic metastases, the correlation between the DWI parameters and the percentage of tumor necrosis on pathology was evaluated using the Spearman correlation coefficient.

RESULTS

DDC had the highest area under the ROC curve (AUC, 0.905) for differentiating malignant from benign lesions, followed by D_t (0.903) and ADC (0.866), without significant differences among them (DDC vs. D_t, p = 0.946; DDC vs. ADC, p = 0.157). For distinguishing hypovascular from hypervascular lesions, and hepatocellular carcinoma from metastasis, f  had a significantly higher AUC than the other DWI parameters (p < 0.05). The α had the strongest correlation with the degree of tumor necrosis (ρ = 0.655, p = 0.002).

CONCLUSION

The DDC from stretched exponential model of DWI demonstrated excellent diagnostic performance for differentiating malignant from benign FLLs. The α is promising for evaluating the degree of necrosis in treated metastases.

KEY POINTS

• The stretched exponential DWI model is valuable for characterizing focal liver lesions. • The DDC from stretched exponential model shows excellent performance for differentiating malignant from benign focal liver lesions. • The α from stretched exponential model is promising for evaluating the degree of necrosis in hepatic metastases after chemotherapy.

Comparison of the Diagnostic Value of Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MRI in Differentiating Tumor Stage and Histological Grade of Bladder Cancer

RATIONALE AND OBJECTIVES

We aimed to determine the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging (DWI) models in differentiating tumor stage and grade of bladder cancer.

MATERIALS AND METHODS

Forty-five patients with pathologically confirmed bladder cancer underwent multi-b-value DWI. An apparent diffusion coefficient (ADC) was calculated from DWI by using a monoexponential model. A true diffusion coefficient (D), perfusion-related pseudo-diffusion coefficient (D*), and perfusion fraction (f) were calculated from DWI by using a biexponential model. A water molecular diffusion heterogeneity index (α) and distributed diffusion coefficient (DDC) were calculated from DWI by using a stretched exponential model. All parameters were compared between different stages and grades by using the Mann-Whitney U test. Receiver operating characteristic and intrareader correlation coefficient analysis were used for statistical evaluations.

RESULTS

ADC, D, f, and DDC values were significantly higher in the non-muscle-invasive vs muscle-invasive bladder cancers (P = .000, .000, .002, and .000, respectively) and in low-grade vs high-grade ones (P = .000, .000, .018, and .000, respectively). D* value was significantly lower in the low-grade bladder cancers compared to high-grade ones (P = .012). The areas under the receiver operating characteristic curve of ADC, D, and DDC values were 0.945, 0.912, and 0.946 in staging bladder cancers; 0.866, 0.862, and 0.856 in grading bladder cancers, respectively.

CONCLUSION

Biexponential and stretched exponential DWI models may provide more parameters in staging and grading bladder cancers and show a slight difference between DDC and ADC values in staging bladder cancers. These two DWI models, as well as the monoexponential models, were very helpful in staging and grading bladder cancers.

Meta-analysis of diffusion-weighted imaging in the differential diagnosis of renal lesions

PURPOSE

To assess the diagnostic value of diffusion-weighted imaging (DWI) in distinguishing between renal malignant and benign lesions.

MATERIALS AND METHODS

Electronic databases were systematically searched to identify original studies evaluating DWI findings on renal lesions from January 2000 through January 2018. Pooled weighted estimates of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were calculated. A summary receiver operator characteristic (sROC) curve was constructed to calculate the area under the sROC curve (AUC). Publication bias was assessed by using Deeks' asymmetry test.

RESULTS

A total of 15 studies including 1386 renal lesions were eligible in the meta-analysis. The pooled sensitivity and specificity with a corresponding 95% confidence interval (CI) were 0.83 (95% CI: 0.80-0.86) and 0.74 (95% CI: 0.71-0.78), respectively. The PLR, NLR, and DOR were 3.21 (95% CI: 2.39-4.32), 0.24 (95% CI: 0.18-0.30), and 15.95 (95% CI: 11.19-22.71), respectively. The AUC was 0.87 (95% CI: 0.84-0.90). Significant heterogeneity was observed between the included studies. Reference standard, country, and gradient factor were identified as the most important variable sources. No evidence of notable publication bias was reported.

CONCLUSIONS

DWI is an informative MRI modality in discriminating benign and malignant lesions and exhibits moderately high diagnostic accuracy. However, it remains inconclusive and limited in the absence of an optimal b value and ADC cutoff value. High-quality prospective studies regarding DWI have yet to be conducted to explore optimal imaging parameters and diagnostic thresholds.

Measurement and scan reproducibility of parameters of intravoxel incoherent motion in renal tumor and normal renal parenchyma: a preliminary research at 3.0 T MR

PURPOSE

To prospectively estimate measurement and scan reproducibility of parameters of intravoxel incoherent motion (IVIM) in renal tumors, normal renal cortex, and medulla.

METHODS

Twenty-four consecutive patients (twelve males and twelve females; median age 56.7 years, range 32-71 years) with 25 renal tumors (20 renal cell carcinomas, one urothelium carcinoma, three angiomyolipomas, and one oncocytoma) were examined twice using IVIM₁ and IVIM₂ with 9 and 16 b values, respectively, at 3.0 T. All the patients were re-scanned in 24-48 h. Regions of interest (ROIs) were placed in solid part of tumor, normal cortex, and medulla to derive IVIM parameters D (true diffusion coefficient), D* (pseudodiffusion coefficient), and f (perfusion fraction of pseudodiffusion). Differences in parameters between two IVIM sets and intra-observer, inter-observer, and scan-rescan differences were assessed using paired t tests. Intra-observer, inter-observer, and scan-rescan reproducibility were assessed by measuring coefficient of variation and Bland-Altman limits of agreements.

RESULTS

Intra-observer reproducibility of renal tumors, normal renal cortex, and medulla was excellent for apparent diffusion coefficient (ADC; CV: 3.45%-5.34%, BA-LA: -14% to 18%) and D (CV: 3.65% to 6.04%, BA-LA: -18% to 19%), good for f (CV: 11.96%-16.08%, BA-LA: -76.4% to 92.1% except f of medulla with CV of 32.59% and BA-LA of -76.4% to 92.1% in IVIM₁), and poor for D* (CV: 25.0% to 75.4%, BA-LA: -111% to 150%). The same order was in inter-observer reproducibility analysis. Scan-rescan reproducibility was the worst of the three parameters. Renal medulla showed worse reproducibility than renal tumors and the normal cortex. The metrics of IVIM₂ had better reproducibility than IVIM₁.

CONCLUSION

Excellent reproducibility evaluation for ADC and D, good for f, and poor for D* derived from IVIM was performed in renal tumors, normal renal cortex, and medulla. D* has limited reliability and scan-rescan reproducibility should be improved.

Pre-TACE kurtosis of ADCtotal derived from histogram analysis for diffusion-weighted imaging is the best independent predictor of prognosis in hepatocellular carcinoma

PURPOSE

To determine the feasibility of pre-TACE IVIM imaging based on histogram analysis for predicting prognosis in the treatment of unresectable hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

Fifty-five patients prospectively underwent 1.5T MRI 1 week before TACE. Histogram metrics for IVIM parameters and ADCs maps between responders and non-responders with mRECIST assessment were compared. Kaplan-Meier, log-rank tests and Cox proportional hazard regression model were used to correlate variables with time to progression (TTP).

RESULTS

Mean (p = 0.022), median (p = 0.043), and 25^th percentile (p < 0.001) of perfusion fraction (PF), mean (p < 0.001), median (p < 0.001), 25^th percentile (p < 0.001) and 75^th percentile (p = 0.001) of ADC_(0,500), mean (p = 0.005), median (p = 0.008) and 25^th percentile (p = 0.039) of ADC_total were higher, while skewness and kurtosis of PF (p = 0.001, p = 0.005, respectively), kurtosis of ADC_(0,500) and ADC_total (p = 0.005, p = 0.001, respectively) were lower in responders compared to non-responders. Multivariable analysis demonstrated that mRECIST was associated with TTP independently, and kurtosis of ADC_total had the best predictive performance for disease progression.

CONCLUSION

Pre-TACE kurtosis of ADC_total is the best independent predictor for TTP.

KEY POINTS

• mRECIST was associated with TTP independently. • Lower kurtosis and higher mean for ADCs tend to have good response. • Pre-TACE kurtosis of ADC _total is the best independent predictor for TTP.

Renal Adiposity Confounds Quantitative Assessment of Markers of Renal Diffusion With MRI: A Proposed Correction Method

OBJECTIVES

Recent studies have indicated that excessive fat may confound assessment of diffusion in organs with high fat content, such as the liver and breast. However, the extent of this effect in the kidney, which is not considered a major fat deposition site, remains unclear. This study tested the hypothesis that renal fat may impact diffusion-weighted imaging (DWI) parameters, and proposes a 3-compartment model (TCM) to circumvent this effect.

METHODS

Using computer simulations, we investigated the effect of fat on assessment of apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM), and TCM-derived pure-diffusivity. We also investigated the influence of magnetic resonance repetition (TR) and echo time (TE) on DWI parameters as a result of variation in the relative contribution of the fat signal. Apparent diffusion coefficient, IVIM and TCM DWI parameters were calculated in domestic pigs fed a high-cholesterol (obese group) or normal diet (lean group), and correlated to renal histology. Intravoxel incoherent motion-derived pure-diffusivity was also compared among 15 essential hypertension patients classified by body mass index (BMI) (high vs normal). Finally, pure-diffusivity was calculated and compared in 8 patients with atherosclerotic renal artery stenosis (ARAS) and 5 healthy subjects using IVIM and TCM.

RESULTS

Simulations showed that unaccounted fat results in the underestimation of IVIM-derived pure diffusivity. The underestimation increases as the fat fraction increases, with higher pace at lower fat contents. The underestimation was larger for shorter TR and longer TE values due to the enhancement of the relative contribution of the fat signal. Moreover, TCM, which incorporates highly diffusion-weighted images (b > 2500 s/mm), could correct for fat-dependent underestimation. Animal studies in the lean and obese groups confirmed lower ADC and IVIM pure-diffusivity in obese versus lean pigs with otherwise healthy kidneys, whereas pure-diffusivity calculated using TCM were not different between the 2 groups. Similarly, essential hypertension patients with high BMI had lower ADC (1.9 vs 2.1 × 10 mm/s) and pure-diffusivity (1.7 vs 1.9 × 10 mm/s) than those with normal BMI. Pure-diffusivity calculated using IVIM was not different between the ARAS and healthy subjects, but TCM revealed significantly lower diffusivity in ARAS.

CONCLUSIONS

Excessive renal fat may cause underestimation of renal ADC and IVIM-derived pure-diffusivity, which may hinder detection of renal pathology. Models accounting for fat contribution may help reduce the variability of diffusivity calculated using DWI.