Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging for predicting histological grade of hepatocellular carcinoma: Comparison with conventional diffusion-weighted imaging

Application of Intravoxel Incoherent Motion in Clinical Liver Imaging: A Literature Review

Intravoxel incoherent motion (IVIM) modeling is a widely used double-exponential model for describing diffusion-weighted imaging (DWI) signal, with a slow component related to pure molecular diffusion and a fast component associated with microcirculatory perfusion, which compensates for the limitations of traditional DWI. IVIM is a noninvasive technique for obtaining liver pathological information and characterizing liver lesions, and has potential applications in the initial diagnosis and treatment monitoring of liver diseases. Recent studies have demonstrated that IVIM-derived parameters are useful for evaluating liver lesions, including nonalcoholic fatty liver disease (NAFLD), liver fibrosis and liver tumors. However, the results are not stable. Therefore, it is necessary to summarize the current applications of IVIM in liver disease research, identify existing shortcomings, and point out the future development direction. In this review, we searched for studies related to hepatic IVIM-DWI applications over the past two decades in the PubMed database. We first introduce the fundamental principles and influential factors of IVIM, and then discuss its application in NAFLD, liver fibrosis, and focal hepatic lesions. It has been found that IVIM is still unstable in ensuring the robustness and reproducibility of measurements in the assessment of liver fibrosis grade and liver tumors differentiation, due to inconsistent and substantial overlap in the range of IVIM-derived parameters for different fibrotic stages. In the end, the future direction of IVIM-DWI in the assessment of liver diseases is discussed, emphasizing the need for further research on the stability of IVIM-derived parameters, particularly perfusion-related parameters, in order to promote the clinical practice of IVIM-DWI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

Advances in application of novel magnetic resonance imaging technologies in liver disease diagnosis

Liver disease is a major health concern globally, with high morbidity and mor-tality rates. Precise diagnosis and assessment are vital for guiding treatment approaches, predicting outcomes, and improving patient prognosis. Magnetic resonance imaging (MRI) is a non-invasive diagnostic technique that has been widely used for detecting liver disease. Recent advancements in MRI technology, such as diffusion weighted imaging, intravoxel incoherent motion, magnetic resonance elastography, chemical exchange saturation transfer, magnetic resonance spectroscopy, hyperpolarized MR, contrast-enhanced MRI, and ra-diomics, have significantly improved the accuracy and effectiveness of liver disease diagnosis. This review aims to discuss the progress in new MRI technologies for liver diagnosis. By summarizing current research findings, we aim to provide a comprehensive reference for researchers and clinicians to optimize the use of MRI in liver disease diagnosis and improve patient prognosis.

Multiparametric MR imaging with diffusion-weighted, intravoxel incoherent motion, diffusion tensor, and dynamic contrast-enhanced perfusion sequences to assess gallbladder wall thickening: a prospective study based on surgical histopathology

OBJECTIVE

To investigate the diagnostic performance of a multiparametric magnetic resonance imaging (MRI) protocol comprising quantitative MRI (diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), and dynamic contrast-enhanced (DCE) perfusion MRI) and conventional MRI in the characterization of gallbladder wall thickening (GWT).

METHODS

This prospective study comprised consecutive adults with GWT who underwent multiparametric MRI between July 2020 and April 2022. Two radiologists evaluated the MRI independently. The final diagnosis was based on surgical histopathology. The association of MRI parameters with malignant GWT was evaluated. The area under the curve (AUC) for the quantitative MRI parameters and diagnostic performance of conventional, and multiparametric MRI were compared. The interobserver agreement between two radiologists was calculated.

RESULTS

Thirty-five patients (mean age, 56 years, 23 females) with GWT (25 benign and ten malignant) were evaluated. The quantitative MRI parameters significantly associated with malignant GWT were apparent diffusion coefficient on DWI (p = 0.007) and mean diffusivity (MD) on DTI (p = 0.013), perfusion fraction (f) on IVIM (p = 0.033), time to peak enhancement (TTP, p = 0.008), and wash in rate (p = 0.049) on DCE-MRI. TTP had the highest AUC of 0.790, followed by MD (0.782) and f (0.742) (p = 0.213) for predicting malignant GWT. Multiparametric MRI had significantly higher sensitivity (90% vs. 80%, p = 0.045) than conventional MRI for diagnosing malignant GWT. The two radiologists' reading had substantial to near-perfect agreement (kappa = 0.639-1) and moderate to strong correlation (interclass correlation coefficient = 0.5-0.88).

CONCLUSION

Multiparametric protocol incorporating advanced sequences improved the diagnostic performance of MRI for differentiating benign and malignant GWT.

KEY POINTS

• Multiparametric MRI had 90% sensitivity and 88% specificity for diagnosing malignant GWT, compared to 80% sensitivity and 88% specificity for conventional CE-MRI. • Among the quantitative MRI parameters, TTP (perfusion-MRI) had the highest AUC of 0.790, followed by MD (0.782) and IVIM-f (0.742). • For most quantitative MRI parameters, there was moderate to strong agreement (ICC = 0.5-0.88).

Soft tissue sarcoma: intravoxel incoherent motion and diffusion kurtosis imaging parameters correlate with the histological grade and Ki-67 expression

BACKGROUND

Accurate prediction of the histological grade and Ki-67 expression of soft tissue sarcoma (STS) before surgery is essential for the subsequent diagnosis, treatment, and prognostic evaluation of patients.

PURPOSE

To evaluate intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in predicting the histological grade and Ki-67 expression of STS.

MATERIAL AND METHODS

A total of 40 patients underwent 3-T MRI, including conventional sequences; IVIM and DKI parameters were obtained. All patients were divided into a low-grade (grade 1 and grade 2) group and a high-grade (grade 3) group through pathological analysis. Ki-67 expression of each lesion was calculated. Chi-square test, independent sample t-test, Mann-Whitney U test, Pearson, Spearman, and receiver operating characteristic curve analysis were performed.

RESULTS

There were 17 patients in the low-grade group and 23 in the high-grade group. Ki-67 expression was in the range of 10%-80%. D value was inversely correlated with Ki-67 expression. MK value showed a moderate positive correlation with Ki-67 expression. Regarding histological grading, only the peritumoral enhancement was statistically different between low- and high-grade STS on conventional MRI (P=0.024). The high-grade group had significantly higher MK value and lower D and MD value than the low-grade group. MK value showed the best diagnostic performance. The combination of MK and MD yielded the highest specificity (88.24%), and the combination of D, MK, and MD yielded the best area under the curve value (0.841) and sensitivity (95.65%).

CONCLUSION

IVIM and DKI parameters were correlated with Ki-67 expression and could help differentiate between low- and high-grade STS.

Application of intravoxel incoherent motion diffusion-weighted imaging in hepatocellular carcinoma

The morbidity and mortality of hepatocellular carcinoma (HCC) rank 6^th and 4^th, respectively, among malignant tumors worldwide. Traditional diffusion-weighted imaging (DWI) uses the apparent diffusion coefficient (ADC) obtained by applying the monoexponential model to reflect water molecule diffusion in active tissue; however, the value of ADC is affected by microcirculation perfusion. Using a biexponential model, intravoxel incoherent motion (IVIM)-DWI quantitatively measures information related to pure water molecule diffusion and microcirculation perfusion, thus compensating for the shortcomings of DWI. The number of studies examining the application of IVIM-DWI in patients with HCC has gradually increased over the last few years, and many results show that IVIM-DWI has vital value for HCC differentiation, pathological grading, and predicting and evaluating the treatment response. The present study principally reviews the principle of IVIM-DWI and its research progress in HCC differentiation, pathological grading, predicting and evaluating the treatment response, predicting postoperative recurrence and predicting gene expression prediction.

The Roles of Diffusion Kurtosis Imaging and Intravoxel Incoherent Motion Diffusion-Weighted Imaging Parameters in Preoperative Evaluation of Pathological Grades and Microvascular Invasion in Hepatocellular Carcinoma

Background

Currently, there are disputes about the parameters of diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), and diffusion-weighted imaging (DWI) in predicting pathological grades and microvascular invasion (MVI) in hepatocellular carcinoma (HCC). The aim of our study was to investigate and compare the predictive power of DKI and IVIM-DWI parameters for preoperative evaluation of pathological grades and MVI in HCC.

Methods

PubMed, Web of Science, and Embase databases were searched for relevant studies published from inception to October 2021. Review Manager 5.3 was used to summarize standardized mean differences (SMDs) of mean kurtosis (MK), mean diffusivity (MD), tissue diffusivity (D), pseudo diffusivity (D*), perfusion fraction (f), mean apparent diffusion coefficient (ADCmean), and minimum apparent diffusion coefficient (ADCmin). Stata12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC). Overall, 42 up-to-standard studies with 3,807 cases of HCC were included in the meta-analysis.

Results

The SMDs of ADCmean, ADCmin, and D values, but not those of D* and f values, significantly differed between well, moderately, and poorly differentiated HCC (P < 0.01). The sensitivity, specificity, and AUC of the MK, D, ADCmean, and ADCmin for preoperative prediction of poorly differentiated HCC were 69%/94%/0.89, 87%/80%/0.89, 82%/75%/0.86, and 83%/64%/0.81, respectively. In addition, the sensitivity, specificity, and AUC of the D and ADCmean for preoperative prediction of well-differentiated HCC were 87%/83%/0.92 and 82%/88%/0.90, respectively. The SMDs of ADCmean, ADCmin, D, MD, and MK values, but not f values, showed significant differences (P < 0.01) between MVI-positive (MVI+) and MVI-negative (MVI-) HCC. The sensitivity and specificity of D and ADCmean for preoperative prediction of MVI+ were 80%/80% and 74%/71%, respectively; the AUC of the D (0.87) was significantly higher than that of ADCmean (0.78) (Z = −2.208, P = 0.027). Sensitivity analysis showed that the results of the above parameters were stable and reliable, and subgroup analysis confirmed a good prediction effect.

Conclusion

DKI parameters (MD and MK) and IVIM-DWI parameters (D value, ADCmean, and ADCmin) can be used as a noninvasive and simple preoperative examination method to predict the grade and MVI in HCC. Compared with ADCmean and ADCmin, MD and D values have higher diagnostic efficacy in predicting the grades of HCC, and D value has superior diagnostic efficacy to ADCmean in predicting MVI+ in HCC. However, f value cannot predict the grade or MVI in HCC.

An attention-based deep learning model for predicting microvascular invasion of hepatocellular carcinoma using an intra-voxel incoherent motion model of diffusion-weighted magnetic resonance imaging

The intra-voxel incoherent motion model of diffusion-weighted magnetic resonance imaging (IVIM-DWI) with a series of images with differentb-values has great potential as a tool for detecting, diagnosing, staging, and monitoring disease progression or the response to treatment. The current clinical tumour characterisation using IVIM-DWI is based on the parameter values derived from the IVIM model. On the one hand, the calculation accuracy of such parameter values is susceptible to deviations due to noise and motion; on the other hand, the performance of the parameter values is rather limited with respect to tumour characterisation. In this article, we propose a deep learning approach to directly extract spatiotemporal features from a series ofb-value images of IVIM-DWI using a deep learning network for lesion characterisation. Specifically, we introduce an attention mechanism to select dominant features from specificb-values, channels, and spatial areas of the multipleb-value images for better lesion characterisation. The experimental results for clinical hepatocellular carcinoma (HCC) when using IVIM-DWI demonstrate the superiority of the proposed deep learning model for predicting the microvascular invasion (MVI) of HCC. In addition, the ablation study reflects the effectiveness of the attention mechanism for improving MVI prediction. We believe that the proposed model may be a useful tool for the lesion characterisation of IVIM-DWI in clinical practice.

Dynamic Contrast-Enhanced and Intravoxel Incoherent Motion MRI Biomarkers Are Correlated to Survival Outcome in Advanced Hepatocellular Carcinoma

Objective: This study assessed dynamic contrast-enhanced (DCE)-MRI and intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) parameters to prospectively predict survival outcomes in participants with advanced hepatocellular carcinoma (HCC) who received lenalidomide, a dual antiangiogenic and immunomodulatory agent, as second-line therapy in a Phase II clinical trial. Materials and methods: Forty-four participants with advanced HCC who had progression after sorafenib as first-line treatment were prospectively enrolled. Pretreatment MRI parameters—obtained from DCE-MRI (peak, slope, AUC, K^trans, K_ep, and V_e), apparent diffusion coefficient (ADC), and IVIM DWI (pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f))—were derived from the largest hepatic tumor. The Cox model was used to investigate the associations of the parameters with progression-free survival (PFS) and overall survival (OS). Results: Median PFS and OS were 2.3 and 8.0 months, respectively. Univariate analysis showed that participants with a high slope (p = 0.024), K_ep (p < 0.001), and ADC (p = 0.018) values had longer PFS than those with low values; participants with a small tumor size (p = 0.006), high slope (p = 0.01), ADC (p = 0.015), and f (p = 0.012) values had longer OS than those with low values did. Cox multivariable analysis revealed that K_ep (p < 0.001) and ADC (p = 0.009) remained independent predictors of PFS; slope (p = 0.003) and ADC (p = 0.009) remained independent predictors of OS. Moreover, K_ep and slope were still significant after Bonferroni correction was performed (p < 0.005). Conclusion: Both pretreatment DCE-MRI and IVIM DWI parameters, especially slope and ADC, may predict PFS and OS in participants with HCC receiving lenalidomide as second-line therapy.

The Role of Non-Gaussian Models of Diffusion Weighted MRI in Hepatocellular Carcinoma: A Systematic Review

The importance of Diffusion Weighted Imaging (DWI) in hepatocellular carcinoma (HCC) has been widely handled in the literature. Due to the mono-exponential model limitations, several studies recently investigated the role of non-Gaussian DWI models in HCC. However, their results are variable and inconsistent. Therefore, the aim of this systematic review is to summarize current knowledge on non-Gaussian DWI techniques in HCC. A systematic search of the literature, including PubMed, Google Scholar, MEDLINE, and ScienceDirect databases, was performed to identify original articles since 2010 that evaluated the role of non-Gaussian DWI models for HCC diagnosis, grading, response to treatment, and prognosis. Studies were grouped and summarized according to the non-Gaussian DWI models investigated. We focused on the most used non-Gaussian DWI models (Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Stretched Exponential—SE). The quality of included studies was evaluated by using QUADAS-2 and QUIPS tools. Forty-three articles were included, with IVIM and DKI being the most investigated models. Although the role of non-Gaussian DWI models in clinical settings has not fully been established, our findings showed that their parameters may potentially play a role in HCC. Further studies are required to identify a standardized DWI acquisition protocol for HCC diagnosis, grading, response to treatment, and prognosis.

Comparative study of evaluating the microcirculatory function status of primary small HCC between the CE (DCE-MRI) and Non-CE (IVIM-DWI) MR Perfusion Imaging

PURPOSE

To compare the difference of evaluating the microcirculatory function status of primary small HCC between DCE-MRI with two-compartmental pharmacokinetic model and IVIM-DWI.

METHODS

27 patients (22 men, 5 women; mean age, 49 years; range 36-65 years) with primary single sHCC who underwent IVIM-DWI and DCE-MRI before the operation were included in this retrospective study. The MR perfusion parameters are Ktrans, Ve, Kep, D, D* and f. Pathological results include pathological grade (low grade ≤ II, high grade > II) and MVD. The perfusion parameters and pathological results of sHCC were analyzed and compared in their relevance, sensitivity and specificity. Statistical methods included Spearman and ROC curve analysis.

RESULTS

The perfusion parameters (Ktrans, Kep, D*, f) were significantly positive correlated (r = 0.892, 0.808, 0.589 and 0.543, P = 0.000, 0.000, 0.001 and 0.003 with MVD of sHCC. The parameter Ve and D values were negatively correlated (r = - 0.454 and - 0.399, P = 0.017 and 0.039, respectively) with the pathological grade. Regarding the evaluation MVD of sHCC, the evaluation of the sensitivity and specificity performance was present in descending order: Ktrans > Kep > PF > D*. In the evaluation pathological grade of sHCC, the sensitivity and specificity were better by parameters D than Ve.

CONCLUSION

DCE-MRI is better than IVIM-DWI for evaluation microcirculation functional status of sHCC. But for evaluating the pathological grade, IVIM-DWI is better than DCE-MRI. Combination of the two imaging techniques may provide more comprehensive evaluation in microcirculation functional status of the sHCC.

A study of the correlations between IVIM-DWI parameters and the histologic differentiation of hepatocellular carcinoma

The present study aimed to investigate the value of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) in the preoperative prediction of the histologic differentiation of hepatocellular carcinoma (HCC). Seventy HCC patients were scanned with a 3.0 T magnetic resonance scanner. The values of apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D*), and the fraction of the fast apparent diffusion coefficient (f) were measured. Analysis of variance was used to compare the differences in parameters between groups with different degrees of histologic differentiation. p < 0.05 was considered statistically significant. Receiver operating characteristic (ROC) curves were used to analyse the efficacy of IVIM-DWI parameters for predicting the histologic differentiation of HCC. The ADC and D values for well, moderately and poorly differentiated HCC were 1.35 ± 0.17 × 10^-3 mm²/s, 1.16 ± 0.17 × 10^-3 mm²/s, 0.98 ± 0.21 × 10^-3 mm²/s, and 1.06 ± 0.15 × 10^-3 mm²/s, 0.88 ± 0.16 × 10^-3 mm²/s, 0.76 ± 0.18 × 10^-3 mm²/s, respectively, and all differences were significant. The D* and f values of the three groups were 32.87 ± 14.70 × 10^-3 mm²/s, 41.68 ± 17.90 × 10^-3 mm²/s, 34.54 ± 18.60 × 10^-3 mm²/s and 0.22 ± 0.07, 0.23 ± 0.08, 0.18 ± 0.07, respectively, with no significant difference. When the cut-off values of ADC and D were 1.25 × 10^-3 mm²/s and 0.97 × 10^-3 mm²/s, respectively, their diagnostic sensitivities and specificities for distinguishing well differentiated HCC from moderately differentiated and poorly differentiated HCC were 73.3%, 85.5%, 86.7%, and 78.2%, and their areas under the ROC curve were 0.821 and 0.841, respectively. ADC and D values can be used preoperatively to predict the degree of histologic differentiation in HCC, and the D value has better diagnostic value.

A study of the correlations between IVIM-DWI parameters and the histologic differentiation of hepatocellular carcinoma

The present study aimed to investigate the value of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) in the preoperative prediction of the histologic differentiation of hepatocellular carcinoma (HCC). Seventy HCC patients were scanned with a 3.0 T magnetic resonance scanner. The values of apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D*), and the fraction of the fast apparent diffusion coefficient (f) were measured. Analysis of variance was used to compare the differences in parameters between groups with different degrees of histologic differentiation. p < 0.05 was considered statistically significant. Receiver operating characteristic (ROC) curves were used to analyse the efficacy of IVIM-DWI parameters for predicting the histologic differentiation of HCC. The ADC and D values for well, moderately and poorly differentiated HCC were 1.35 ± 0.17 × 10⁻³ mm²/s, 1.16 ± 0.17 × 10⁻³ mm²/s, 0.98 ± 0.21 × 10⁻³ mm²/s, and 1.06 ± 0.15 × 10⁻³ mm²/s, 0.88 ± 0.16 × 10⁻³ mm²/s, 0.76 ± 0.18 × 10⁻³ mm²/s, respectively, and all differences were significant. The D* and f values of the three groups were 32.87 ± 14.70 × 10⁻³ mm²/s, 41.68 ± 17.90 × 10⁻³ mm²/s, 34.54 ± 18.60 × 10⁻³ mm²/s and 0.22 ± 0.07, 0.23 ± 0.08, 0.18 ± 0.07, respectively, with no significant difference. When the cut-off values of ADC and D were 1.25 × 10⁻³ mm²/s and 0.97 × 10⁻³ mm²/s, respectively, their diagnostic sensitivities and specificities for distinguishing well differentiated HCC from moderately differentiated and poorly differentiated HCC were 73.3%, 85.5%, 86.7%, and 78.2%, and their areas under the ROC curve were 0.821 and 0.841, respectively. ADC and D values can be used preoperatively to predict the degree of histologic differentiation in HCC, and the D value has better diagnostic value.

Diffusion-Weighted Imaging Reflects Tumor Grading and Microvascular Invasion in Hepatocellular Carcinoma

BACKGROUND

To date, there are inconsistent data about relationships between diffusion-weighted imaging (DWI) and tumor grading/microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Our purpose was to systematize the reported results regarding the role of DWI in prediction of tumor grading/MVI in HCC.

METHOD

MEDLINE library, Scopus, and Embase data bases were screened up to December 2019. Overall, 29 studies with 2,715 tumors were included into the analysis. There were 20 studies regarding DWI and tumor grading, 8 studies about DWI and MVI, and 1 study investigated DWI, tumor grading, and MVI in HCC.

RESULTS

In 21 studies (1,799 tumors), mean apparent diffusion coefficient (ADC) values (ADC_mean) were used for distinguishing HCCs. ADC_mean of G1-3 lesions overlapped significantly. In 4 studies (461 lesions), minimum ADC (ADC_min) was used. ADC_min values in G1/2 lesions were over 0.80 × 10^-3 mm²/s and in G3 tumors below 0.80 × 10^-3 mm²/s. In 4 studies (241 tumors), true diffusion (D) was reported. A significant overlapping of D values between G1, G2, and G3 groups was found. ADC_mean and MVI were analyzed in 9 studies (1,059 HCCs). ADC_mean values of MIV+/MVI- lesions overlapped significantly. ADC_min was used in 4 studies (672 lesions). ADC_min values of MVI+ tumors were in the area under 1.00 × 10^-3 mm²/s. In 3 studies (227 tumors), D was used. Also, D values of MVI+ lesions were predominantly in the area under 1.00 × 10^-3 mm²/s.

CONCLUSION

ADC_min reflects tumor grading, and ADC_min and D predict MVI in HCC. Therefore, these DWI parameters should be estimated for every HCC lesion for pretreatment tumor stratification. ADC_mean cannot predict tumor grading/MVI in HCC.

A Correlative Study Between IVIM-DWI Parameters and the Expression Levels of Ang-2 and TKT in Hepatocellular Carcinoma

Background

Noninvasive evaluation of the expression of angiopoietin-2 (Ang-2) and transketolase (TKT) in hepatocellular carcinoma (HCC) is of great significance for the clinical development of individualized treatment plans. However, the correlation between intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) and the expression of Ang-2 and TKT has not been reported. We sought to investigate the correlations between IVIM-DWI parameters and Ang-2 and TKT expression levels in HCCs.

Methods

Conventional non-enhanced magnetic resonance imaging (MRI) and IVIM-DWI and dynamic contrast MRI were performed for 61 patients with HCC before surgical treatment. Various IVIM-DWI parameters, such as apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D^*) and fraction of fast apparent diffusion coefficient (f), were calculated using Function-MADC software. Expression levels of Ang-2 and TKT in HCC were detected via immunohistochemical staining and classified into two grades. Independent sample t tests were used to compare differences in parameters between the two groups. The Spearman rank correlation test was used to analyze the correlations between IVIM-DWI parameters and Ang-2 and TKT expression levels in HCCs.

Results

The D^* and f values were significantly higher in the high Ang-2 group than in the low Ang-2 group; there were no obvious between-group differences in ADC and D. Ang-2 expression was positively correlated with D* and f but not with ADC and D. The ADC and D values were significantly lower in the high TKT group than in the low TKT group, whereas the between-group differences for D* and f were not significant. TKT expression was negatively correlated with ADC and D but not with D* and f.

Conclusions

IVIM-DWI can be used to evaluate Ang-2 and TKT expression in HCC.

Pre-radiofrequency ablation MRI imaging features predict the local tumor progression in hepatocellular carcinoma

To investigate whether MRI features could preoperatively predict local tumor progression (LTP) in patients with hepatocellular carcinoma (HCC) treated with radiofrequency ablation (RFA) as the first-line treatment and improve a novel predictive model through developing a nomogram including various conventional MRI parameters. 105 patients with HCCs who had received RFA were enrolled. All patients had undergone conventional MRI before RFA. Uni- and multivariable analyses for LTP were assessing using a Cox proportional hazards model. The developed MRI-based nomogram was further designed based on multivariable logistic analysis in our study and the usefulness of the developed model was validated according to calibration curves and the C-index. Rim enhancement (hazard ratio: 2.689, P = .044) and the apparent diffusion coefficient (ADC) values (hazard ratio: 0.055, P = .038) were statistically significant independent predictors of LTP after RFA at multivariable analysis. The performance of the nomogram incorporating two MRI parameters (with a C-index of 0.782) was improved compared with that based on rim enhancement and ADC alone (with C-index values of 0.630 and 0.728, respectively). The calibration curve of the MRI-based nomogram showed good conformance between evaluation and observation at 0.5, 1, and 1.5 years after RFA. The preliminary predictive model based on MRI findings including rim enhancement and ADC value could be used preoperatively to estimate the risk of LTP of HCC after RFA as the first-line treatment.

Comparative Study of Amide Proton Transfer Imaging and Intravoxel Incoherent Motion Imaging for Predicting Histologic Grade of Hepatocellular Carcinoma

Background: Preoperative grading of hepatocellular carcinoma (HCC) is an important factor associated with prognosis after liver resection. The promising prediction of the differentiation of HCC remains a challenge. The purpose of our study was to investigate the value of amide proton transfer (APT) imaging in predicting the histological grade of HCC, compared with the intravoxel incoherent motion (IVIM) imaging.

Methods: From September 2018 to February 2020, 88 patients with HCC were enrolled and divided into four groups (G1, G2, G3, and G4) based on the histologic grades. Preoperative APT signal intensity (SI), apparent diffusion coefficient (ADC), true molecular diffusion coefficient (D), pseudo-diffusion coefficient (D^*), and perfusion fraction (f ) of HCC were independently measured by two radiologists. The averaged values of those parameters were compared using an analysis of variance. The Spearman rank analysis was used to compare the correlation between those imaging parameters and the histological grades. Receiver operating characteristic (ROC) curve analysis was used to explore the predictive performance.

Results: There were significant differences in APT SI, ADC, D, and f among the four grades of HCC (all P < 0.001). A moderate to good relationship was found between APT SI and the histologic grade of HCC (r = 0.679, P < 0.001). APT SI had an area under the ROC curve (AUC) of 0.890 (95% CI: 0.805–0.947) for differentiating low- from high-grade HCC, and the corresponding sensitivity and specificity were 85.71% and 82.05%, respectively. Comparison of ROC curves demonstrated that the AUC of APT SI was significantly higher than those of IVIM-derived parameter (Z = 2.603, P = 0.0092; Z = 2.099, P = 0.0358; Z = 4.023, P = 0.0001; Z = 2.435, P = 0.0149, compared with ADC, D, D^*, and f , respectively). Moreover, the combination of both techniques further improved the diagnostic performance, with an AUC of 0.929 (95% CI: 0.854–0.973).

Conclusion: APT imaging may be a potential noninvasive biomarker for the prediction of histologic grading of HCC and complements IVIM imaging for the more accurate and comprehensive characterization of HCC.

Progress of intravoxel incoherent motion diffusion-weighted imaging in liver diseases

Traditional magnetic resonance (MR) diffusion-weighted imaging (DWI) uses a single exponential model to obtain the apparent diffusion coefficient to quantitatively reflect the diffusion motion of water molecules in living tissues, but it is affected by blood perfusion. Intravoxel incoherent motion (IVIM)-DWI utilizes a double-exponential model to obtain information on pure water molecule diffusion and microcirculatory perfusion-related diffusion, which compensates for the insufficiency of traditional DWI. In recent years, research on the application of IVIM-DWI in the diagnosis and treatment of hepatic diseases has gradually increased and has achieved considerable progress. This study mainly reviews the basic principles of IVIM-DWI and related research progress in the diagnosis and treatment of hepatic diseases.

Quantitative Evaluation of Intravoxel Incoherent Motion and Diffusion Kurtosis Imaging in Assessment of Pathological Grade of Clear Cell Renal Cell Carcinoma

RATIONALE AND OBJECTIVES

To evaluate the diagnostic value of intravoxel incoherent motion and diffusion kurtosis imaging parameters for clear cell renal cell carcinoma (ccRCC) grading.

MATERIALS AND METHODS

A total of 60 patients with pathologically proven ccRCC who underwent intravoxel incoherent motion and diffusion kurtosis imaging were retrospectively evaluated. The standard apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean kurtosis (MK), and mean diffusivity (MD) maps were calculated and compared between high-grade and low-grade ccRCC using Mann-Whitney U test. Receiver-operating characteristic analysis was performed for all parameters.

RESULTS

ADC, D and MD values were significantly lower for high-grade ccRCC compared to low-grade ccRCC (p < 0.05). MK values were significantly higher in high-grade ccRCC compared to low-grade ccRCC (p < 0.05). However, D* and f were not significantly difference between the two groups (p > 0.05). MD had the largest area under the curve (AUC = 0.888), followed by ADC (AUC = 0.796), D (AUC = 0.780), MK (AUC = 0.736), f (AUC = 0.582), and D*(AUC = 0.533).

CONCLUSION

Diffusion-related parameters (D, ADC, MD, and MK) were able to significantly distinguish between low- and high-grade ccRCC. However, perfusion-related parameters (D* and f) were unable to separate high- and low-grade ccRCC. MD may be the most promising parameter for grading ccRCC in the clinic.

Intravoxel incoherent motion diffusion-weighted imaging to differentiate hepatocellular carcinoma from intrahepatic cholangiocarcinoma

The present study aimed to explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). This study included 65 patients with malignant hepatic nodules (55 with HCC, 10 with ICC), and 17 control patients with normal livers. All patients underwent IVIM-DWI scans on a 3.0 T magnetic resonance imaging (MRI) scanner. The standard apparent diffusion coefficient (ADC), pure diffusion coefficient (Dslow), pseudo-diffusion coefficient (Dfast), and perfusion fraction (f) were obtained. Differences in the parameters among the groups were analysed using one-way ANOVA, with p < 0.05 indicating statistical significance. Receiver operating characteristic (ROC) curve analysis was used to compare the efficacy of each parameter in differentiating HCC from ICC. ADC, Dslow, Dfast, f significantly differed among the three groups. ADC and Dslow were significantly lower in the HCC group than in the ICC group, while Dfast was significantly higher in the HCC group than in the ICC group; f did not significantly differ between the HCC and ICC groups. When the cut-off values of ADC, Dslow, and Dfast were 1.27 × 10−3 mm2/s, 0.81 × 10−3 mm2/s, and 26.04 × 10−3 mm2/s, respectively, their diagnostic sensitivities for differentiating HCC from ICC were 98.18%, 58.18%, and 94.55%, their diagnostic specificities were 50.00%, 80.00%, and 80.00%, and their areas under the ROC curve (AUCs) were 0.687, 0.721, and 0.896, respectively. Dfast displayed the largest AUC value. IVIM-DWI can be used to differentiate HCC from ICC.

Intravoxel incoherent motion diffusion-weighted imaging to differentiate hepatocellular carcinoma from intrahepatic cholangiocarcinoma

The present study aimed to explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). This study included 65 patients with malignant hepatic nodules (55 with HCC, 10 with ICC), and 17 control patients with normal livers. All patients underwent IVIM-DWI scans on a 3.0 T magnetic resonance imaging (MRI) scanner. The standard apparent diffusion coefficient (ADC), pure diffusion coefficient (D_slow), pseudo-diffusion coefficient (D_fast), and perfusion fraction (f) were obtained. Differences in the parameters among the groups were analysed using one-way ANOVA, with p < 0.05 indicating statistical significance. Receiver operating characteristic (ROC) curve analysis was used to compare the efficacy of each parameter in differentiating HCC from ICC. ADC, D_slow, D_fast, f significantly differed among the three groups. ADC and D_slow were significantly lower in the HCC group than in the ICC group, while D_fast was significantly higher in the HCC group than in the ICC group; f did not significantly differ between the HCC and ICC groups. When the cut-off values of ADC, D_slow, and D_fast were 1.27 × 10⁻³ mm²/s, 0.81 × 10⁻³ mm²/s, and 26.04 × 10⁻³ mm²/s, respectively, their diagnostic sensitivities for differentiating HCC from ICC were 98.18%, 58.18%, and 94.55%, their diagnostic specificities were 50.00%, 80.00%, and 80.00%, and their areas under the ROC curve (AUCs) were 0.687, 0.721, and 0.896, respectively. D_fast displayed the largest AUC value. IVIM-DWI can be used to differentiate HCC from ICC.

Diagnostic accuracy of quantitative diffusion parameters in the pathological grading of hepatocellular carcinoma: A meta-analysis

BACKGROUND

Accurate preoperative assessment of the pathological grade of hepatocellular carcinoma (HCC) could greatly benefit prognostic predictions.

PURPOSE

To assess and compare the diagnostic accuracy of the apparent diffusion coefficient (ADC) and tissue diffusivity (D) for the noninvasive pathological grading of HCC.

STUDY TYPE

Meta-analysis.

DATA SOURCES

PubMed/Medline, EMBASE, the Web of Science, and the Cochrane Library were searched to find related original articles published up to May 30, 2019.

FIELD STRENGTH/SEQUENCE

Diffusion-weighted imaging (DWI) and/or intravoxel incoherent motion (IVIM) were performed with a 1.5T or 3.0T scanner.

ASSESSMENT

The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess the methodologic quality.

STATISTICAL TESTS

The bivariate random-effects model was used to obtain the pooled sensitivity and specificity, and the area under summary receiver operating characteristic curve (AUROC) was obtained. Subgroup analyses were performed.

RESULTS

A total of 16 original articles (1428 HCCs) were included. Most studies had a low to unclear risk of bias and minimal concerns regarding applicability. For the discrimination of well-differentiated HCCs, the pooled sensitivity and specificity of the ADC value were 85% and 92%, respectively. For the discrimination of poorly differentiated HCCs, the pooled sensitivity and specificity of the ADC value and D were 84% and 80%, and 92% and 77%, respectively. The summary AUROC of D (0.94) was significantly higher than that of ADC (0.89) (z = -2.718, P = 0.007). The subgroup analyses identified three covariates including size, number of included lesions in the studies, and blindness to the reference standard as possible sources of heterogeneity.

DATA CONCLUSION

This meta-analysis showed that the ADC and D values had a high to excellent accuracy for the noninvasive pathological grading of HCCs and that the D value was superior to the ADC value for discriminating poorly differentiated HCCs.

LEVEL OF EVIDENCE

3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1581-1593.

Identification of a 3-mRNA signature as a novel potential prognostic biomarker in patients with ovarian serous cystadenocarcinoma in G2 and G3

The use of mRNAs as biomarkers serves to diagnose, treat, as well as aid the prognosis of cancer. The present study involved an analysis of mRNAs in the cell cycle at the G2 and G3 tumor grades for the prognosis of ovarian serous cystadenocarcinoma (OSC) using 364 clinical samples (G2:G3=42:322). Statistics aided the identification of NPFFR2, XPNPEP2 and CELA3B; the 3-mRNA model that allows for classification of patients into high- and low-risk groups using a median value of 0.9580745. The rates of survival varied (P=0.00149) and the independent detection of stratification of the risk of this disease was validated with success using the 3-mRNA signature, which was demonstrated to be more successful than the weight model. This approach was revealed to provide the prognosis of grade G2 and G3 in patients with OSC compared with factors used traditionally. Compared with traditional factors, this 3-mRNA model was demonstrated to be the only and independent prognostic factor for patients with G2 and G3 stage OSC. A literature survey was also performed in the present study in order to assess the role of the 3 genes and indirectly prove their effectiveness. The establishment of this new genetic model will enhance prospective prognosis and treatment for patients with OSC.

The Application of Intravoxel Incoherent Motion Diffusion-Weighted Imaging in the Diagnosis of Hilar Obstructive Jaundice

OBJECTIVE

The aim of this study was to investigate the potential of intravoxel incoherent motion diffusion-weighted imaging in diagnosing hilar obstructive jaundice.

METHODS

Fifty-nine patients diagnosed with hilar obstructive jaundice were enrolled in our hospital form January 2017 to January 2018. All the patients received scanning by a 3.0-T nuclear magnetic resonance scanner. The values of apparent diffusion coefficient (ADC)slow, ADCfast, and f were obtained and analyzed by 2 experienced radiologists. The differences between patients with hilar biliary obstruction and healthy volunteers in ADCslow, ADCfast, and f values were analyzed. Moreover, the differences between benign and malignant obstructive jaundice in ADCslow, ADCfast, and f values were analyzed. According to the serum levels of total bilirubin, patients were divided into 3 groups: mild, moderate, and severe obstructive jaundice. The differences between the 3 groups in ADCslow, ADCfast, and f values were also analyzed.

RESULTS

The ADCfast values were obviously lower in patients with hilar obstructive jaundice than in healthy controls, whereas no significant difference in the values of ADCslow and f was found between both groups. The optimal cutoff value for ADCfast was 0.0341. The ADCfast values were significantly different between patients with benign and malignant hilar obstructive jaundice. The ADCfast values were negatively associated with the severity of hilar obstructive jaundice.

CONCLUSIONS

Intravoxel incoherent motion diffusion-weighted imaging was a promising method for diagnosing hilar biliary obstruction jaundice.

Hepatocellular carcinoma: Can LI-RADS v2017 with gadoxetic-acid enhancement magnetic resonance and diffusion-weighted imaging improve diagnostic accuracy?

BACKGROUND

The Liver Imaging Reporting and Data System (LI-RADS), supported by the American College of Radiology (ACR), has been developed for standardizing the acquisition, interpretation, reporting, and data collection of liver imaging examinations in patients at risk for hepatocellular carcinoma (HCC). Diffusion-weighted imaging (DWI), which is described as an ancillary imaging feature of LI-RADS, can improve the diagnostic efficiency of LI-RADS v2017 with gadoxetic acid-enhanced magnetic resonance imaging (MRI) for HCC.

AIM

To determine whether the use of DWI can improve the diagnostic efficiency of LI-RADS v2017 with gadoxetic acid-enhanced magnetic resonance MRI for HCC.

METHODS

In this institutional review board-approved study, 245 observations of high risk of HCC were retrospectively acquired from 203 patients who underwent gadoxetic acid-enhanced MRI from October 2013 to April 2018. Two readers independently measured the maximum diameter and recorded the presence of each lesion and assigned scores according to LI-RADS v2017. The test was used to determine the agreement between the two readers with or without DWI. In addition, the sensitivity (SE), specificity (SP), accuracy (AC), positive predictive value (PPV), and negative predictive value (NPV) of LI-RADS were calculated. Youden index values were used to compare the diagnostic performance of LI-RADS with or without DWI.

RESULTS

Almost perfect interobserver agreement was obtained for the categorization of observations with LI-RADS (kappa value: 0.813 without DWI and 0.882 with DWI). For LR-5, the diagnostic SE, SP, and AC values were 61.2%, 92.5%, and 71.4%, respectively, with or without DWI; for LR-4/5, they were 73.9%, 80%, and 75.9% without DWI and 87.9%, 80%, and 85.3% with DWI; for LR-4/5/M, they were 75.8%, 58.8%, and 70.2% without DWI and 87.9%, 58.8%, and 78.4% with DWI; for LR- 4/5/TIV, they were 75.8%, 75%, and 75.5% without DWI and 89.7%, 75%, and 84.9% with DWI. The Youden index values of the LI-RADS classification without or with DWI were as follows: LR-4/5: 0.539 vs 0.679; LR-4/5/M: 0.346 vs 0.467; and LR-4/5/TIV: 0.508 vs 0.647.

CONCLUSION

LI-RADS v2017 has been successfully applied with gadoxetate-enhanced MRI for patients at high risk for HCC. The addition of DWI significantly increases the diagnostic efficiency for HCC.

Joint Consensus Statement of the Indian National Association for Study of the Liver and Indian Radiological and Imaging Association for the Diagnosis and Imaging of Hepatocellular Carcinoma Incorporating Liver Imaging Reporting and Data System

Hepatocellular carcinoma (HCC) is the 6th most common cancer and the second most common cause of cancer-related mortality worldwide. There are currently no universally accepted practice guidelines for the diagnosis of HCC on imaging owing to the regional differences in epidemiology, target population, diagnostic imaging modalities, and staging and transplant eligibility. Currently available regional and national guidelines include those from the American Association for the Study of Liver Disease (AASLD), the European Association for the Study of the Liver (EASL), the Asian Pacific Association for the Study of the Liver, the Japan Society of Hepatology, the Korean Liver Cancer Study Group, Hong Kong, and the National Comprehensive Cancer Network in the United States. India with its large population and a diverse health infrastructure faces challenges unique to its population in diagnosing HCC. Recently, American Association have introduced a Liver Imaging Reporting and Data System (LIRADS, version 2017, 2018) as an attempt to standardize the acquisition, interpretation, and reporting of liver lesions on imaging and hence improve the coherence between radiologists and clinicians and provide guidance for the management of HCC. The aim of the present consensus was to find a common ground in reporting and interpreting liver lesions pertaining to HCC on imaging keeping LIRADSv2018 in mind.

Could intravoxel incoherent motion diffusion-weighted magnetic resonance imaging be feasible and beneficial to the evaluation of gastrointestinal tumors histopathology and the therapeutic response?

Gastrointestinal tumors (GTs) are among the most common tumors of the digestive system and are among the leading causes of cancer death worldwide. Functional magnetic resonance imaging (MRI) is crucial for assessment of histopathological changes and therapeutic responses of GTs before and after chemotherapy and radiotherapy. A new functional MRI technique, intravoxel incoherent motion (IVIM), could reveal more detailed useful information regarding many diseases. Currently, IVIM is widely used for various tumors because the derived parameters (diffusion coefficient, D; pseudo-perfusion diffusion coefficient, D*; and perfusion fraction, f) are thought to be important surrogate imaging biomarkers for gaining insights into tissue physiology. They can simultaneously reflect the microenvironment, microcirculation in the capillary network (perfusion) and diffusion in tumor tissues without contrast agent intravenous administration. The sensitivity and specificity of these parameters used in the evaluation of GTs vary, the results of IVIM in GTs are discrepant and the variability of IVIM measurements in response to chemotherapy and/or radiotherapy in these studies remains a source of controversy. Therefore, there are questions as to whether IVIM diffusion-weighted MRI is feasible and helpful in the evaluation of GTs, and whether it is worthy of expanded use.

Diagnostic value of imaging examinations in patients with primary hepatocellular carcinoma

Primary hepatocellular carcinoma (PHC) includes hepatocellular carcinoma, intrahepatic cholangiocarcinoma and other pathological types and is characterized by rapid progression. Most of the clinical diagnoses are made at late stage or when distant metastasis occurs, increasing the difficulty of treatment and resulting in a poor prognosis. Therefore, the early diagnosis of PHC plays an important role in timely treatment and the improvement of prognosis. The gold standard for the diagnosis of primary liver cancer is liver biopsy, but it has limitations as an invasive examination. Presently, imaging has become the first choice for the diagnosis of liver cancer. We here summarize the new methods and techniques of imaging in diagnosis and evaluation of primary liver cancer in recent years, including ultrasonography, computed tomography perfusion imaging, diffusion-weighted imaging technology-voxel incoherent motion, diffusion tensor imaging, iterative decomposition of water and fat with echo asymmetry and least squares estimation-iron quantification, dynamic enhanced magnetic resonance imaging and hepatocyte-specific contrast medium imaging. Imaging diagnosis can not only evaluate the degree of differentiation, blood supply and perfusion, and invasiveness of the lesion, but also predict the prognosis, evaluate liver function, and provide references for clinical diagnosis and treatment.