Intravoxel incoherent motion diffusion-weighted MR imaging in assessing and characterizing solitary pulmonary lesions

Histogram analysis of continuous-time random walk and restrictive spectrum imaging for identifying hepatocellular carcinoma and intrahepatic cholangiocarcinoma

Background

To compare the ability and potential additional value of various diffusion models, including continuous-time random walk (CTRW), restrictive spectrum imaging (RSI), and diffusion-weighted imaging (DWI), as well as their associated histograms, in distinguishing the pathological subtypes of liver cancer.

Methods

40 patients with liver cancer were included in this study. Histogram metrics were derived from CTRW (D, α, β), RSI (f1, f2, f3), and DWI (ADC) parameters across the entire tumor volume. Statistical analyses included the Chi-square test, independent samples t-test, Mann-Whitney U test, ROC, logistic regression, and Spearman correlation.

Results

Patients with hepatocellular carcinoma exhibited higher values in f1 median, f1 20th, f1 40th, and f1 60th compared to patients with intrahepatic cholangiocarcinoma, whereas Dmean, Dmedian, D40th, D60th, and D80th percentiles were lower (P<0.05). Among the individual histogram parameters, f1 40th percentile demonstrated the highest accuracy (AUC = 0.717). Regarding the combined and single models, the total combined model exhibited the best diagnostic performance (AUC = 0.792). Although RSI showed higher diagnostic efficacy than CTRW (AUC = 0.731, 0.717), the combination of CTRW and RSI further improved diagnostic performance (AUC = 0.787), achieving superior sensitivity and specificity (sensitivity = 0.72, specificity = 0.80).

Conclusion

CTRW, RSI, and their corresponding histogram parameters demonstrated the ability to distinguish between pathological subtypes of liver cancer. Moreover, whole-lesion histogram parameters provided more comprehensive statistical insights compared to mean values alone.

Diagnostic performance of diffusion-weighted imaging versus 18F-FDG PET/CT in differentiating pulmonary lesions: an updated meta-analysis of comparative studies

OBJECTIVE

To compare the diagnostic accuracy of diffusion-weighted imaging (DWI) and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for differentiating pulmonary nodules and masses.

METHODS

We systematically searched six databases, including PubMed, EMBASE, the Cochrane Library, and three Chinese databases, to identify studies that used both DWI and PET/CT to differentiate pulmonary nodules. The diagnostic performance of DWI and PET/CT was compared and pooled sensitivity and specificity were calculated along with 95% confidence intervals (CIs). The Quality Assessment of Diagnostic Accuracy Studies 2 was used to assess the quality of the included studies, and STATA 16.0 software was utilized to perform statistical analysis.

RESULTS

Overall, 10 studies that enrolled a total of 871 patients with 948 pulmonary nodules were included in this meta-analysis. DWI had greater pooled sensitivity (0.85 [95% CI 0.77-0.90]) and specificity (0.91 [95% CI 0.82-0.96]) than PET/CT (sensitivity, 0.82 [95% CI 0.70-0.90]); specificity, (0.81, [95% CI 0.72-0.87]). The area under the curve of DWI and PET/CT were 0.94 (95% CI 0.91-0.96) and 0.87 (95% CI 0.84-0.90) (Z = 1.58, P > 0.05), respectively. The diagnostic odds ratio of DWI (54.46, [95% CI 17.98-164.99]) was superior to that of PET/CT (15.77, [95% CI 8.19-30.37]). The Deeks' funnel plot asymmetry test showed no publication bias. The Spearman correlation coefficient test revealed no significant threshold effect. Lesion diameter and reference standard could be potential causes for the heterogeneity of both DWI and PET/CT studies, and quantitative or semi-quantitative parameters used would be a potential source of bias for PET/CT studies.

CONCLUSION

As a radiation-free technique, DWI may have similar performance compare with PET/CT in differentiating malignant pulmonary nodules or masses from benign ones.

Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions

Background

Whole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions.

Purpose

To compare the diagnostic performance of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) in differentiating lung cancer from focal inflammatory lesions, based on whole-lesion volume histogram analysis.

Methods

Fifty-nine patients with solitary pulmonary lesions underwent multiple b-values DWIs, which were then postprocessed using mono-exponential, bi-exponential and DKI models. Histogram parameters of the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), apparent diffusional kurtosis (K_app) and kurtosis-corrected diffusion coefficient (D_app) were calculated and compared between the lung cancer and inflammatory lesion groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance.

Results

The ADC^mean, ADC^median, D ^mean and D ^median values of lung cancer were significantly lower than those of inflammatory lesions, while the ADC^skewness, K_app ^mean, K_app ^median, K_app ^SD, K_app ^kurtosis and D_app ^skewness values of lung cancer were significantly higher than those of inflammatory lesions (all p < 0.05). ADC^skewness (p = 0.019) and D ^median (p = 0.031) were identified as independent predictors of lung cancer. D ^median showed the best performance for differentiating lung cancer from inflammatory lesions, with an area under the ROC curve of 0.777. Using a D ^median of 1.091 × 10^-3 mm²/s as the optimal cut-off value, the sensitivity, specificity, positive predictive value and negative predictive value were 69.23%, 85.00%, 90.00% and 58.62%, respectively.

Conclusions

Whole-lesion histogram analysis of DWI, IVIM and DKI parameters is a promising approach for differentiating lung cancer from inflammatory lesions, and D ^median shows the best performance in the differential diagnosis of solitary pulmonary lesions.

Differential value of diffusion kurtosis imaging and intravoxel incoherent motion in benign and malignant solitary pulmonary lesions

Objective

To investigate the diagnostic value of diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) whole-lesion histogram parameters in differentiating benign and malignant solitary pulmonary lesions (SPLs).

Materials and Methods

Patients with SPLs detected by chest CT examination and with further routine MRI, DKI and IVIM-DWI functional sequence scanning data were recruited. According to the pathological results, SPLs were divided into a benign group and a malignant group. Independent samples t tests (normal distribution) or Mann‒Whitney U tests (nonnormal distribution) were used to compare the differences in DKI (Dk, K), IVIM (D, D*, f) and ADC whole-lesion histogram parameters between the benign and malignant SPL groups. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficiency of the histogram parameters and determine the optimal threshold. The area under the curve (AUC) of each histogram parameter was compared by the DeLong method. Spearman rank correlation was used to analyze the correlation between histogram parameters and malignant SPLs.

Results

Most of the histogram parameters for diffusion-related values (Dk, D, ADC) of malignant SPLs were significantly lower than those of benign SPLs, while most of the histogram parameters for the K value of malignant SPLs were significantly higher than those of benign SPLs. DKI (Dk, K), IVIM (D) and ADC were effective in differentiating benign and malignant SPLs and combined with multiple parameters of the whole-lesion histogram for the D value, had the highest diagnostic efficiency, with an AUC of 0.967, a sensitivity of 90.00% and a specificity of 94.03%. Most of the histogram parameters for the Dk, D and ADC values were negatively correlated with malignant SPLs, while most of the histogram parameters for the K value were positively correlated with malignant SPLs.

Conclusions

DKI (Dk, K) and IVIM (D) whole-lesion histogram parameters can noninvasively distinguish benign and malignant SPLs, and the diagnostic performance is better than that of DWI. Moreover, they can provide additional information on SPL microstructure, which has important significance for guiding clinical individualized precision diagnosis and treatment and has potential clinical application value.

Value of IVIM in Differential Diagnoses between Benign and Malignant Solitary Lung Nodules and Masses: A Meta-analysis

Purpose

This study aims to evaluate the accuracy of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in distinguishing malignant and benign solitary pulmonary nodules and masses.

Methods

Studies investigating the diagnostic accuracy of IVIM-DWI in lung lesions published through December 2020 were searched. The standardized mean differences (SMDs) of the apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The sensitivity, specificity, area under the curve (AUC), publication bias, and heterogeneity were then summarized, and the source of heterogeneity and the reliability of combined results were explored by meta-regression and sensitivity analysis.

Results

A total of 16 studies including 714 malignant and 355 benign lesions were included. Significantly lower ADC, D, and f values were found in malignant pulmonary lesions compared to those in benign lesions. The D value showed the best diagnostic performance (sensitivity = 0.90, specificity = 0.71, AUC = 0.91), followed by ADC (sensitivity = 0.84, specificity = 0.75, AUC = 0.88), f (sensitivity = 0.70, specificity = 0.62, AUC = 0.71), and D^* (sensitivity = 0.67, specificity = 0.61, AUC = 0.67). There was an inconspicuous publication bias in ADC, D, D* and f values, moderate heterogeneity in ADC, and high heterogeneity in D, D*, and f values. Subgroup analysis suggested that both ADC and D values had a significant higher sensitivity in “nodules or masses” than that in “nodules.”

Conclusions

The parameters derived from IVIM-DWI, especially the D value, could further improve the differential diagnosis between malignant and benign solitary pulmonary nodules and masses.

Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/#myprospero, identifier: CRD42021226664

Volumetric analysis of intravoxel incoherent motion diffusion-weighted imaging in preoperative assessment of non-small cell lung cancer

PURPOSE

To evaluate the potential of intravoxel incoherent motion (IVIM) and apparent diffusion coefficient (ADC) in the prediction of tumor grade, lymph node metastasis and pleural invasion of non-small cell lung cancer (NSCLC) before surgery.

MATERIALS AND METHODS

65 patients diagnosed with NSCLC by surgery were enrolled. IVIM-DWI (10 b-values, 0-1000 s/mm²) was performed before surgery. The mean and minimum ADC (ADC_mean, ADC_min) and IVIM parameters D, D* and f were independently measured and calculated by 2 radiologists by drawing regions of interest (ROIs) including the solid component of the whole tumor. Intraclass correlation coefficients (ICCs) were analysed. Spearman analysis was used to determine the correlation between IVIM parameters and tumor differentiation. Independent sample t-tests (normal distribution) or Mann-Whitney U tests (non-normal distribution) were used to compare the differences between the parameters in moderately-well and poorly differentiated groups, with and without lymph node metastasis and pleural invasion groups. Receiver operating characteristic (ROC) curves were generated.

RESULTS

The ADC_mean, ADC_min, D and f values were negatively correlated with the pathological grades of tumor (P < 0.05). The ADC_mean and D values of patients with poor differentiation and lymph node metastasis were significantly lower than that of patients with moderately-well differentiation and without lymph node metastasis (P < 0.001-0.012). The D value was significantly lower and f value was significantly higher among patients with pleural invasion than those without (P =   0.033 and < 0.001). ROC analysis showed that the area under the ROC curve (AUC) was larger for D in predicting the degree of differentiation (0.832) and lymph node metastasis (0.806), and higher for f in predicting pleural invasion (0.832).

CONCLUSIONS

IVIM is useful for predicting the tumor differentiation, lymph node metastasis and pleural invasion in NSCLC patients before surgery.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Predicting and Monitoring the Response of Anti-Angiogenic Treatment in the Orthotopic Nude Mouse Model of Lung Adenocarcinoma

BACKGROUND

The treatment efficacy of angiogenesis inhibitor could be underestimated at an early stage based on tumor volume changes. Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) can quantitatively assess tumors at the cellular level, but it is unclear whether it can provide useful information for assessing treatment response of anti-angiogenic treatment for lung adenocarcinoma.

PURPOSE

To determine the use of IVIM-DWI for non-invasive monitoring of the early response to anti-angiogenic treatment in the orthotopic transplantation of lung adenocarcinoma model.

STUDY TYPE

Prospective.

POPULATION

Thirty-seven nude mice were randomized into two groups: treatment group (received bevacizumab + cisplatin, N = 20) and control group (received saline, N = 17).

FIELD STRENGTH/SEQUENCE

Single-shot turbo spin-echo (TSE) IVIM-DWI, TSE T2-weighted imaging at 3.0 T.

ASSESSMENT

Tumor volume, IVIM parameters (apparent diffusion coefficient [ADC], diffusivity [D], perfusion fraction [f], and pseudo-diffusion coefficient [D*]) were measured before and 2 hours, 3, 7, 10 and 14 days after treatment. Regions of interest were manually drawn along the inner edge of the tumor by two radiologists with 5 and 10-year experience in magnetic resonance imaging. Pathological examinations (hematoxylin and eosin stain, cluster of differentiation 34) were performed.

STATISTICAL TESTS

Kolmogorov-Smirnov test, repeated-measure two-way analysis of variance test, Mann-Whitney U test, Pearson correlation analysis, receiver operating characteristic curve. P < 0.05 was considered statistically significant.

RESULTS

The tumor volume of the two groups was significantly different only on day 14 (control group vs. treatment group, 43.15 ± 18.28 mm3 vs. 28.41 ± 1.71 mm3 ). ADC2h , ADC10d , D2h , D7d , D10d , and D14d were significantly higher, while f10d and f14d were significantly lower in the treatment group compared to those of the control group. Both the △ADC2h (r = -0.631) and △D2h (r = -0.700) showed moderate correlations with the relative tumor volume on day 14.

DATA CONCLUSION

IVIM has the potential to predict and monitor the early response to anti-angiogenic treatment, earlier than size changes, for lung adenocarcinoma.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 4.

A Combination Analysis of IVIM-DWI Biomarkers and T2WI-Based Texture Features for Tumor Differentiation Grade of Cervical Squamous Cell Carcinoma

Purpose

To explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and texture analysis on T2-weighted imaging (T2WI) for evaluating pathological differentiation of cervical squamous cell carcinoma.

Method

This retrospective study included a total of 138 patients with pathologically confirmed poor/moderate/well-differentiated (71/49/18) who underwent conventional MRI and IVIM-DWI scans. The values of ADC, D, D ∗ , and f and 58 T2WI-based texture features (18 histogram features, 24 gray-level co-occurrence matrix features, and 16 gray-level run length matrix features) were obtained. Multiple comparison, correlation, and regression analyses were used.

Results

For IVIM-DWI, the ADC, D, D ∗ , and f were significantly different among the three groups (p < 0.05). ADC, D, and D ∗ were positively correlated with pathological differentiation (r = 0.262, 0.401, 0.401; p < 0.05), while the correlation was negative for f (r = -0.221; p < 0.05). The comparison of 52 parameters of texture analysis on T2WI reached statistically significant levels (p < 0.05). Multivariate logistic regression analysis incorporated significant IVIM-DWI, and texture features on T2WI showed good diagnostic performance both in the four differentiation groups (poorly vs. moderately, area under the curve(AUC) = 0.797; moderately vs. well, AUC = 0.954; poorly vs. moderately and well, AUC = 0.795; and well vs. moderately and poorly, AUC = 0.952). The AUCs of each parameters alone were smaller than that of each regression model (0.503∼0.684, 0.547∼0.805, 0.511∼0.712, and 0.636∼0.792, respectively; pairwise comparison of ROC curves between regression model and individual variables, p < 0.05).

Conclusions

IVIM-DWI biomarkers and T2WI-based texture features had potential to evaluate the pathological differentiation of cervical squamous cell carcinoma. The combination of IVIM-DWI with texture analysis improved the predictive performance.

Comparison of Conventional DWI, Intravoxel Incoherent Motion Imaging, and Diffusion Kurtosis Imaging in Differentiating Lung Lesions

Purpose

To compare conventional diffusion weighted imaging (DWI), intravoxel incoherent motion imaging (IVIM) and diffusion kurtosis imaging (DKI) in differentiating malignant and benign lung lesions.

Method

Fifty-five consecutive patients with lung lesions underwent multiple b-value DWI. The apparent diffusion coefficient (ADC), IVIM and DKI parameters were calculated using postprocessing software and compared between the malignant and benign groups. Receiver operating characteristic (ROC) analysis was performed for all parameters.

Results

ADC and D were lower in malignant lesions than in benign lesions, while Kapp was higher (P < 0.05). The differences in D*, f, and Dapp between the two groups were not significant (P > 0.05). The areas under the curves (AUCs) of ADC, D, and Kapp were 0.816, 0.864, and 0.822. The combination of all the significant parameters yielded an AUC of 0.880. There were no significant differences in diagnostic efficacy among ADC, D, Kapp and the predictor factor (PRE).

Conclusions

In this study, traditional DWI (ADC), IVIM (D), and DKI (Kapp) all had good diagnostic performance in differentiating malignant lung lesions from benign lesions, but the combination of ADC, D, and Kapp value had better diagnostic efficacy than these parameters alone.

Preliminary study of 3 T-MRI native T1-mapping radiomics in differential diagnosis of non-calcified solid pulmonary nodules/masses

BACKGROUND

Cumulative CT radiation damage was positively correlated with increased tumor risks. Although it has recently been known that non-radiation MRI is alternative for pulmonary imaging. There is little known about the value of MRI T1-mapping in the diagnosis of pulmonary nodules. This article aimed to investigate the value of native T1-mapping-based radiomics features in differential diagnosis of pulmonary lesions.

METHODS

73 patients underwent 3 T-MRI examination in this prospective study. The 99 pulmonary lesions on native T1-mapping images were segmented twice by one radiologist at indicated time points utilizing the in-house semi-automated software, followed by extraction of radiomics features. The inter-class correlation coefficient (ICC) was used for analyzing intra-observer's agreement. Dimensionality reduction and feature selection were performed via univariate analysis, and least absolute shrinkage and selection operator (LASSO) analysis. Then, the binary logical regression (LR), support vector machine (SVM) and decision tree classifiers with the input of optimal features were selected for differentiating malignant from benign lesions. The receiver operative characteristics (ROC) curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated. Z-test was used to compare differences among AUCs.

RESULTS

107 features were obtained, of them, 19.5% (n = 21) had relatively good reliability (ICC ≥ 0.6). The remained 5 features (3 GLCM, 1 GLSZM and 1 shape features) by dimensionality reduction were useful. The AUC of LR was 0.82(95%CI: 0.67-0.98), with sensitivity, specificity and accuracy of 70%, 85% and 80%. The AUC of SVM was 0.82(95%CI: 0.67-0.98), with sensitivity, specificity and accuracy of 70, 85 and 80%. The AUC of decision tree was 0.69(95%CI: 0.49-0.87), with sensitivity, specificity and accuracy of 50, 85 and 73.3%.

CONCLUSIONS

The LR and SVM models using native T1-mapping-based radiomics features can differentiate pulmonary malignant from benign lesions, especially for uncertain nodules requiring long-term follow-ups.

Whole-lesion histogram analysis of mono-exponential and bi-exponential diffusion-weighted imaging in differentiating lung cancer from benign pulmonary lesions using 3 T MRI

AIM

To investigate whether whole-lesion histogram analysis of apparent diffusion coefficient (ADC) values derived from mono-exponential and bi-exponential diffusion-weighted imaging (DWI) can differentiate lung cancer from benign pulmonary lesions.

MATERIALS AND METHODS

Thirty-two patients with lung cancer and 17 patients with benign pulmonary lesions were included retrospectively. All patients underwent DWI before surgery or biopsy. ADC histogram parameters, including mean, percentile values (10^th and 90^th), kurtosis, and skewness, were calculated independently by two radiologists. The histogram parameters were compared between patients with lung cancer and benign lesions. Receiver operating characteristic curves were constructed to evaluate the diagnostic performance.

RESULTS

The ADC_Mean, ADC_10th, D_Mean, D_10th were significantly lower in lung cancer (1.187 ± 0.144 × 10^-3; 0.440 ± 0.062 × 10^-3; 1.068 ± 0.108 × 10^-3; and 0.422 ± 0.049 × 10^-3 mm/s) compared to benign lesions (1.418 ± 0.274 × 10^-3; 0.555 ± 0.113 × 10^-3; 1.216 ± 0.149 × 10^-3; and 0.490 ± 0.044 × 10^-3 mm/s; p<0.05). The ADC_Skewness and D_Skewness were significantly different between lung cancer (2.35 ± 0.72; 2.58 ± 1.14) and benign lesions (1.85 ± 0.54; 1.59 ± 1.47; p<0.05). D_10th was robust in differentiating lung cancer from benign lesions. Using 0.453 × 10^-3 mm/s as the optimal threshold, the sensitivity, specificity, and accuracy of D_10th were 78.12%, 82.35%, and 79.6%, respectively.

CONCLUSION

Whole-lesion histogram analysis of ADC values derived by mono-exponential and bi-exponential DWI using 3 T magnetic resonance imaging helps distinguish lung cancer from benign pulmonary lesions.

Evaluating the Histopathology of Pancreatic Ductal Adenocarcinoma by Intravoxel Incoherent Motion-Diffusion Weighted Imaging Comparing With Diffusion-Weighted Imaging

Objectives

To explore the differences between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion-weighted imaging (DWI) in evaluating the histopathological characters of pancreatic ductal adenocarcinoma (PDAC).

Methods

This retrospective study enrolled 50 patients with PDAC confirmed by pathology from December 2018 to May 2020. All patients underwent DWI and IVIM-DWI before surgeries. Patients were classified into low- and high-fibrosis groups. Apparent diffusion coefficient (ADC), diffusion coefficient (D), false diffusion coefficient (D*), and perfusion fraction (f) were measured by two radiologists, respectively in GE AW 4.7 post-processing station, wherein ADC values were derived by mono-exponential fits and f, D, D* values were derived by biexponential fits. The tumor tissue was stained with Sirius red, CD34, and CK19 to evaluate fibrosis, microvascular density (MVD), and tumor cell density. Furthermore, the correlation between ADC, D, D*, and f values and histopathological results was analyzed.

Results

The D values were lower in the high-fibrosis group than in the low-fibrosis group, while the f values were opposite. Further, no statistically significant differences were detected in ADC and D* values between the high- and low-fibrosis groups. The AUC of D and f values had higher evaluation efficacy in the high- and low-fibrosis groups than ADC values. A significant negative correlation was established between D values, and fibrosis and a significant positive correlation were observed between f values and fibrosis. No statistical difference was detected between DWI/IVIM parameters values and MVD or tumor cell density except for the positive correlation between D* values and tumor cell density.

Conclusions

D and f values derived from the IVIM model had higher sensitivity and diagnostic performance for grading fibrosis in PDAC compared to the conventional DWI model. IVIM-DWI may have the potential as an imaging biomarker for predicting the fibrosis grade of PDAC.

The value of diffusion-weighted imaging based on monoexponential and biexponential models for the diagnosis of benign and malignant lung nodules and masses

OBJECTIVES

The objective is to compare the efficacy of diffusion-weighted imaging (DWI) parameters of mean and minimum apparent diffusion coefficient (ADCmean and ADCmin) and intravoxel incoherent motion (IVIM) in the differentiation of benign and malignant lung nodules and masses.

METHODS

Lung lesions measured larger than 1.5 cm on CT were included between August 2015 and September 2018. DWI (10 b-values, 0-1000 s/mm2) scans were performed, and the data were post-processed to derive the ADCmean, ADCmin and IVIM parameters of true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f). An independent sample t-test or Mann-Whitney U test was used to compare benign and malignant parameters. Receiver operating characteristic curves were generated and a Z test was used.

RESULTS

121 patients were finally enrolled, each with one lesion. Examined 121 lesions were malignant in 88 (72.7%) and benign in 33 (27.3%). The ADCmean of malignant pulmonary nodules was significantly lower than that of benign pulmonary nodules (t = 3.156, p = 0.006), whereas the other parameters revealed no significant differences (p = 0.162-0.690). Receiver operating characteristic curve analysis revealed that an ADCmean threshold value of 1.43 × 10-3 mm2/s yielded 88.57% sensitivity and 64.29% specificity. While for lung masses, the ADCmean, ADCmin, D and D* values in malignant pulmonary masses were significantly lower (P﹤0.001-0.011). Among them, the D value exhibited the best diagnostic performance when the threshold of D was 1.23 × 10-3mm2/s, which yielded a sensitivity of 90.57% and a specificity of 89.47% (Z = 2.230, 3.958, 2.877 and p = 0.026, ﹤0.001 and 0.004, respectively).

CONCLUSION

ADC is the most robust parameter to differentiate benign and malignant lung nodules, whereas D is the most robust parameter to differentiate benign and malignant lung masses.

ADVANCES IN KNOWLEDGE

This is the first study to compare all the quantitative parameters of DWI and IVIM mentioned in the literatures for assessing lung lesions; Second, we divided the lesions into lung nodules and lung masses with the size of 3 cm as the boundary.

The ability and utility of diffusion-weighted magnetic resonance imaging with different 'b' values in the differentiation of benign from malignant lung lesions

Purpose

To evaluate the ability and the utility of diffusion-weighted magnetic resonance imaging (MRI) with different ‘b’ values to visualise benign and malignant lung lesions, and to determine which ‘b’ value (b = 300, 500, or 1000 s/mm²) was most useful in differentiating benign from malignant lung lesions.

Material and methods

A total of 100 patients (28 women, 72 men; mean age = 57.19 ± 13.44 years; age range = 20-83 years). Diffusion-weighted imaging (DWI) was obtained with ‘b’ values of 300, 500, and 1000 s/mm². The signal intensity of lesions on DWI images was analysed, and the apparent diffusion coefficient (ADC) values of the lesions were calculated. MRI was performed in all patients after having presented at our department for thoracic computed tomography for various reasons.

Results

A statistically significant difference in DWI signal scores was detected between benign and malignant lesions for all ‘b’ factors (p < 0.0001 for each). The sensitivity and specificity were 95% and 64%, respectively, when a score of 3 for β = 300 s/mm²; 90% and 69%, respectively, when a score of 3 for β = 500 s/mm²; and 84% and 74%, respectively, when a score of 3 for β = 1000 s/mm². ADC values showed significant differences between benign and malignant lesions for all ‘b’ factors (p < 0.0001 for each).

Conclusions

Using ‘b’ values of 300, 500, and 1000 s/mm², DWI signal intensity scores and ADC values are effective methods for the differential diagnosis of malignant and benign pulmonary lesions.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging of Lung Cancer: Comparison Between Turbo Spin-Echo and Echo-Planar Imaging

OBJECTIVE

The aim of the study was to compare intravoxel incoherent motion diffusion-weighted imaging (DWI) for evaluating lung cancer using single-shot turbo spin-echo (TSE) and single-shot echo-planar imaging (EPI) in a 3T MR system.

METHODS

Both single-shot TSE-DWI and single-shot EPI-DWI were scanned twice respectively for 15 patients with lung cancer. Distortion ratio, signal-to-noise ratio, and contrast-to-noise ratio were compared between the 2 techniques. The Bland-Altman analysis was performed to analyze reproducibility between the parameters of TSE-DWI and EPI-DWI. Short-term test-retest repeatability, as well as interobserver agreement, was evaluated using the coefficient of variation (CV) and the intraclass correlation coefficient (ICC).

RESULT

Turbo spin-echo DWI has lower signal-to-noise ratio and similar contrast-to-noise ratio compared with EPI-DWI. Distortion ratio of TSE-DWI was significantly smaller than that of EPI-DWI. The apparent diffusion coefficient (ADC) and true diffusivity (D) of TSE-DWI showed higher values than those of EPI-DWI. The Bland-Altman analysis showed unacceptable limits of agreement between these 2 sequences. Test-retest repeatability was good for ADC and D of EPI-DWI (CV, 14.11%-16.60% and 17.08%-19.53%) and excellent for ADC and D of TSE-DWI (CV, 4.8%-6.19% and 6.05%-8.71%), but relatively poor for perfusion fraction (f) and pseudo-diffusion coefficient (D*) (CV, 25.95%-27.70% and 56.92%-71.84% for EPI, 23.67%-28.67% and 60.85%-70.17% for TSE). For interobserver agreement, both techniques were good to excellent in ADC and D (The lower limit of 95% confidence interval for ICC was almost all greater than 0.75), whereas D* and f had higher interobserver variabilities with D* of TSE-DWI showing poorest reproducibility (ICC, -0.27 to 0.12).

CONCLUSIONS

Lung DWI or IVIM using TSE could provide distortion-free images and improve the test-retest robustness of ADC and D as compared with EPI-DWI; however, it might exert a negative effect on perfusion parameter D*.

Differentiating between malignant and benign solid solitary pulmonary lesions: are intravoxel incoherent motion and diffusion kurtosis imaging superior to conventional diffusion-weighted imaging?

OBJECTIVE

To quantitatively compare the diagnostic values of various diffusion parameters obtained from mono- and biexponential diffusion-weighted imaging (DWI) models and diffusion kurtosis imaging (DKI) in differentiating between benign and malignant solitary pulmonary lesions (SPLs).

METHODS

Multiple b-value DWIs and DKIs were performed in 89 patients with SPL by using a 3-T magnetic resonance (MR) imaging unit. The apparent diffusion coefficient (ADC) of various b-value sets, true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), apparent diffusional kurtosis (Kapp), and kurtosis-corrected diffusion coefficient (Dapp) were calculated and compared between the malignant and benign groups using a Mann-Whitney U test. Receiver-operating characteristic analysis was performed for all parameters.

RESULT

The ADC(0, 150) values of malignant tumors were lower than those of the benign group (p = 0.01). The ADC(0, 300), ADC(0, 500), ADC(0, 600), ADC(0, 800), ADC(0, 1000), ADCtotal, D, and Dapp of malignant tumors were significantly lower than those of benign lesions (all p < 0.001). D*, f, and Kapp showed no statistically significant differences between the two groups. ADCtotal showed the highest area under the curve (AUC = 0.862), followed by ADC(0, 800)(AUC = 0.844), ADC(0, 600)(AUC = 0.843), D(AUC = 0.834), ADC(0, 1000)(AUC = 0.834) and ADC(0, 500)(AUC = 0.824), Dapp(AUC = 0.796), and ADC(0, 300) (AUC = 0.773). However, the difference in diagnostic efficacy among these parameters was not statistically significant (p > 0.05).

CONCLUSION

Intravoxel incoherent motion (IVIM) and DKI-derived parameters have similar performance compared with conventional ADC in differentiating SPLs.

KEY POINTS

• Mono- and biexponential DWI and DKI are feasible for differentiating SPLs. • ADC (0, ≥500) has better performance than ADC (0, <500) in assessing SPLs. • IVIM and DKI have similar performance compared with conventional DWI in differentiating SPLs.

Diffusion-weighted MRI in solitary pulmonary lesions: associations between apparent diffusion coefficient and multiple histopathological parameters

Apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) has gained wide attention as potential tool for differentiating between malignant and benign solitary pulmonary lesions (SPLs). The overall effects of multiple histopathological parameters on ADC have not been elucidated, which may help to explain the overlapping of ADC between malignant and benign SPLs. The study sought to explore associations between ADC and histopathological parameters in SPLs, and to compare diagnostic capability of ADC among different types of SPLs. Multiple histopathological parameters (cell density, nuclear-to-cytoplasm ratio, necrotic fraction, presence of mucus and grade of differentiation) were quantified in 52 malignant and 13 benign SPLs with surgical pathology available. Cell density (β = −0.40) and presence of mucus (β = 0.77) were independently correlated with ADC in malignant SPLs. The accurate diagnosis rate of squamous carcinomas, adenocarcinomas without mucus and malignant tumors with mucus was 100%, 82% and 0%, respectively. Our study suggested that cell density and presence of mucus are independently correlated with ADC in malignant SPLs. Squamous carcinoma maybe more accurately diagnosed as malignancy by ADC value. Malignant SPLs with mucus and adenocarcinomas with low cell density should be kept in mind in differentiating SPLs using ADC because of insufficient diagnostic capability.

Intrahepatic cholangiocarcinoma in the setting of HBV-related cirrhosis: Differentiation with hepatocellular carcinoma by using Intravoxel incoherent motion diffusion-weighted MR imaging

Accurate preoperative differentiation of intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) in the setting of cirrhotic liver is of great clinical significance because the treatment and prognosis of these entities differ markedly. Through a retrospectively research, we sought to determine the diagnostic performances of intravoxel incoherent motion (IVIM) and diffusion weighted imaging (DWI) parameters in the differentiating of ICC and HCC. According to the results, we found that apparent diffusion coefficient (ADC) derived from mono-exponential model and true ADC (ADC^slow) derived from bi-exponential model can be used to distinguish the ICC and HCC, and ADC^slowentailed the higher diagnostic performance than ADC. However, pseudo-ADC (ADC^fast) and perfusion fraction (f) can not be used to differentiate ICC and HCC. These results suggested that IVIM and DWI parameters can be useful in differentiating ICC and HCC and might be helpful in selecting the treatment plan and predicting prognosis.