Preoperative assessment of microvascular invasion of hepatocellular carcinoma using non-Gaussian diffusion-weighted imaging with a fractional order calculus model: A pilot study.

PURPOSE: To assess the clinical potential of a set of new diffusion parameters (D, ß, and µ) derived from fractional order calculus (FROC) diffusion model in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: Between January 2019 to November 2020, a total of 63 patients with HCC were enrolled in this study. Diffusion-weighted images were acquired by using ten b-values (0-2000 s/mm2). The FROC model parameters including diffusion coefficient (D), fractional order parameter (ß), a microstructural quantity (µ) together with a conventional apparent diffusion coefficient (ADC) were calculated. Intraclass coefficients were calculated for assessing the agreement of parameters quantified by two radiologists. The differences of these values between the MVI-positive and MVI-negative HCC groups were compared by using independent sample t-test or the Mann-Whitney U test. Then the parameters showing significant differences between subgroups, including the ß and D, were integrated to develop a comprehensive predictive model via binary logistic regression. The diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis. RESULTS: Among all the studied diffusion parameters, significant differences were found in D, ß, and ADC between the MVI-positive and MVI-negative groups. MVI-positive HCCs showed significantly higher ß values (0.65 ± 0.17 vs. 0.51 ± 0.13, P = 0.001), along with lower D values (0.84 ± 0.11 µm2/ms vs. 1.03 ± 0.13 µm2/ms, P < 0.001) and lower ADC values (1.38 ± 0.46 µm2/ms vs. 2.09 ± 0.70 µm2/ms, P < 0.001) than those of MVI-negative HCCs. According to the ROC analysis, the combination of D and ß demonstrated the largest area under the ROC curve (0.920) compared with individual parameters (D: 0.912; ß: 0.733; and ADC: 0.831) for differentiating MVI-positive from MVI-negative HCCs. CONCLUSIONS: The FROC parameters can be used as noninvasive quantitative imaging markers for preoperatively predicting the MVI status of HCCs.

Quantitative Assessment of Restriction Spectrum MR Imaging for the Diagnosis of Breast Cancer and Association With Prognostic Factors.

BACKGROUND: Restriction spectrum imaging (RSI) is an advanced quantitative diffusion-weighted magnetic resonance imaging (DWI) technique to assess breast cancer. PURPOSE: To investigate the ability of RSI to differentiate the benign and malignant breast lesions and the association with prognostic factors of breast cancer. STUDY TYPE: Retrospective. POPULATION: Seventy women (mean age, 49.6 ± 12.3 years) with 56 malignant and 19 benign breast lesions. FIELD STRENGTH/SEQUENCE: 3-T; RSI-based DWI sequence with echo-planar imaging technique. ASSESSMENT: The apparent diffusion coefficient (ADC) and RSI parameters (restricted diffusion f1 , hindered diffusion f2 , free diffusion f3 , and signal fractions f1 f2 ) were calculated by two readers for the whole lesion volume and compared between the benign and malignant groups and the subgroups with different statuses of prognostic factors in breast cancer. STATISTICAL TESTS: Mann-Whitney U test or Student's t-test was applied to compare the quantitative parameters between the different groups. Intraclass correlation coefficient (ICC) was used to assess readers' reproducibility. Binary logistic regression was used to combine parameters. Area under the curve (AUC) of receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of parameters to distinguish benign from malignant breast lesions. A P-value <0.05 was considered statistically significant. RESULTS: Malignant breast lesions showed significantly lower ADC and f3 values, and significantly higher f1 and f1 f2 values than the benign lesions, with AUC of 0.951, 0.877, 0.868, and 0.860, respectively. When RSI-derived parameters and ADC were combined, the diagnostic performance was superior to either single parameter (AUC = 0.973). The f3 value was significantly differed between estrogen receptor (ER)-positive and ER-negative tumors. The ADC, f1 , f3 , and f1 f2 values were significantly different progesterone receptor (PR)-positive and PR-negative status. DATA CONCLUSION: The RSI-derived parameters (f1 , f3 , and f1 f2 ) may facilitate the differential diagnosis between benign and malignant breast lesions. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Assessment of an MR Elastography-Based Nomogram as a Potential Imaging Biomarker for Predicting Microvascular Invasion of Hepatocellular Carcinoma.

BACKGROUND: Microvascular invasion (MVI) is a well-established poor prognostic factor for hepatocellular carcinoma (HCC). Preoperative prediction of MVI is important for both therapeutic and prognostic purposes, but noninvasive methods are lacking. PURPOSE: To develop an MR elastography (MRE)-based nomogram for the preoperative prediction of MVI in HCC. STUDY TYPE: Prospective. SUBJECTS: A total of 111 patients with surgically resected single HCC (52 MVI-positive and 59 MVI-negative), randomly allocated to training and validation cohorts (7:3 ratio). FIELD STRENGTH/SEQUENCE: 2D-MRE and conventional sequences (T1-weighted in-phase and opposed phase gradient echo, T2-weighted fast spin echo, diffusion-weighted single-shot spin echo echo-planar, and dynamic contrast-enhanced T1-weighted gradient echo) at 3.0 T. ASSESSMENT: MRE-stiffness and conventional qualitative and quantitative MRI features were evaluated and compared between MVI-positive and MVI-negative HCCs. STATISTICAL TESTS: Univariable and multivariable logistic regression analyses were applied to identify potential predictors for MVI, and a nomogram was constructed according to the predictive model. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance. Harrell's C-index evaluated the discrimination performance of the nomogram, calibration curves analyzed its diagnostic performance and decision curve analysis determined its clinical usefulness. A P value <0.05 was considered statistically significant. RESULTS: Tumor stiffness >6.284 kPa (odds ratio [OR] = 24.38) and the presence of arterial peritumoral enhancement (OR = 6.36) were independent variables associated with MVI. The areas under the ROC curves for tumor stiffness were 0.81 (95% confidence interval [CI]: 0.70, 0.89) and 0.77 (95% CI: 0.60, 0.90) in the training and validation cohorts, respectively. When both predictive variables were integrated, the best nomogram performance was achieved with C-indices of 0.88 (95% CI: 0.78, 0.94) and 0.87 (95% CI: 0.71, 0.96) in the two cohorts, fitting well in calibration curves. The decision curve exhibited optimal net benefit with a wide range of threshold probabilities for the nomogram. DATA CONCLUSION: An MRE-based nomogram may be a potential noninvasive imaging biomarker for predicting MVI of HCC preoperatively. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.

Pulmonary Functional Imaging for Lung Adenocarcinoma: Combined MRI Assessment Based on IVIM-DWI and OE-UTE-MRI.

PURPOSE: The goal of current study was to introduce noninvasive and reproducible MRI methods for in vivo functional assessment of lung adenocarcinoma (LUAD). METHODS: Forty-four patients with pathologically confirmed LUAD were included in this study. All the lesions were classified as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IA). The IA lesions were further divided into five subtype patterns, including acinar, lepidic, papillary, micropapillary and solid. Tumors were grouped depending on predominant subtype: low grade (AIS, MIA or lepidic predominant), intermediate grade (papillary or acinar predominant) and high grade (micropapillary, or solid predominant). Spirometry was performed according to American Thoracic Society guidelines. For each patient, Intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) analysis and oxygen-enhanced MRI (OE-MRI) analysis were performed. Spearman's test was used to assess the relationship between a) whole lung mean percent signal enhancement (PSE) and pulmonary function tests (PFTs) parameters; b) IVIM-derived parameters and PFTs parameters; c) tumor mean PSE and IVIM-derived parameters. Kruskal -Wallis tests were applied to test the difference of tumor mean PSE and IVIM-derived parameters between different histological tumor grades. Receiver operating characteristics (ROC) analysis was used to evaluate the diagnostic performance. RESULTS: Whole lung mean PSE was significantly positively correlated with PFTs parameters (r = 0.40 ~ 0.44, P < 0.05). f value derived from IVIM-DWI was significantly negatively correlated with PFTs parameters (r = -0.38 ~ -0.47, P < 0.05). Both tumor mean PSE (P = 0.030 < 0.05) and f (P = 0.022 < 0.05) could differentiate different histological grades. f was negatively correlated with tumor mean PSE (r = -0.61, P < 0.001). For the diagnostic performance, the combination of tumor mean PSE and f outperformed than using tumor mean PSE or f alone in both sensitivity and area under the ROC curve. CONCLUSIONS: The combined measurement of OE-MRI and IVIM-DWI may serve as a promising method for the noninvasive and non-radiation evaluation of pulmonary function. Quantitative analyses achieved by OE-MRI and IVIM-DWI offer an approach of the classification of LUAD subtypes.

Texture analysis based on ADC maps and T2-FLAIR images for the assessment of the severity and prognosis of ischaemic stroke.

OBJECTIVES: To explore the feasibility of texture analysis based on T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) images and apparent diffusion coefficient (ADC) maps in the assessment of the severity and prognosis of ischaemic stroke using the National Institutes of Health Stroke Scale (NIHSS) and modified Rankin scale (mRS) scores, respectively. METHODS: Overall, 116 patients diagnosed with subacute ischaemic stroke were included in this retrospective study. Based on T2-FLAIR images and ADC maps, 15 texture features were extracted from the ROIs of each patient using grey-level co-occurrence matrix (GLCM) and local binary pattern histogram Fourier (LBP-HF) methods. The correlations of NIHSS score on admission (NIHSSbaseline), NIHSS score 24 h after stroke onset (NIHSS24h) and mRS score with the texture features were evaluated using Spearman's partial correlations. The receiver operating characteristic (ROC) curve was used to compare the performance of the selected texture features in the evaluation of stroke severity and prognosis. RESULTS: Texture features derived from the T2-FLAIR images and ADC maps were correlated with NIHSS score and mRS score. EntropyADC and 0.75QuantileT2-FLAIR showed the best diagnostic performance for assessing stroke severity. The combination of EntropyADC and 0.75QuantileT2-FLAIR achieved a better performance in the evaluation of stroke severity (AUC = 0.7, p = 0.01) than either feature alone. Only 0.05QuantileT2-FLAIR was found to be correlated with mRS score, and none of the texture features were predictive of mRS score. CONCLUSION: Texture features derived from T2-FLAIR images and ADC maps might serve as biomarkers to evaluate stroke severity, but were insufficient to predict stroke prognosis.

Assessment of iron deposition and white matter maturation in infant brains by using enhanced T2 star weighted angiography (ESWAN): R2* versus phase values.

BACKGROUND AND PURPOSE: Iron deposition and white matter (WM) maturation are very important for brain development in infants. It has been reported that the R2* and phase values originating from the gradient-echo sequence could both reflect the iron and myelination. The aim of this study was to investigate age-related changes of R2* and phase value, and compare their performances for monitoring iron deposition and WM maturation in infant brains. METHODS: 56 infants were examined by enhanced T2 star weighted angiography (ESWAN) and diffusion tensor imaging in the 1.5T MRI system. The R2* and phase values were measured from the deep gray nuclei and WM. Fractional anisotropy (FA) values were measured only in the WM regions. Correlation analyses were performed to explore the relation among the two parameters (R2* and phase values) and postmenstrual age (PMA), previously published iron concentrations as well as FA values. RESULTS: We found significantly positive correlations between the R2* values and PMA in both of the gray nuclei and WM. Moreover, R2* values had a positive correlation with the iron reference concentrations in the deep gray nuclei and the FA in the WM. However, phase values only had the positive correlation with PMA and FA in the internal capsule, and no significant correlation with PMA and iron content in the deep gray nuclei. CONCLUSIONS: Compared with the phase values, R2* may be a preferable method to estimate the iron deposition and WM maturation in infant brains.

Assessment of intratumoral micromorphology for patients with clear cell renal cell carcinoma using susceptibility-weighted imaging.

BACKGROUND: Multiple treatment options exist for the management of renal cell carcinomas. Preoperative evaluation of clear cell renal cell carcinoma (CRCC) grades is important for deciding upon the appropriate method of therapy. We hypothesize that susceptibility weighted imaging (SWI) is sensitive enough to detect intratumoral microvessles and microbleeding in renal cell carcinoma, which can be used to grade CRCC. MATERIAL AND METHODS: Retrospective reviews of 37 patients with pathologically proven CRCCs were evaluated. All patients underwent SWI examinations. The characteristics of intratumoral susceptibility signal intensity (ITSS) includes the likelihood of the presence of ITSS, morphology of ITSS, dominant structure of ITSS and ratio of ITSS area to tumor area, which were all assessed on SWI. The results were compared using the nonparametric Mann-Whitney test. RESULTS: ITSS was seen in all patients except 4 patients with low-grade CRCCs. There was no significant difference between low and high-grade CRCCs when looking at the likelihood of the presence of ITSS. There was a significant difference in the mean score of dominant structures between low and high-grade CRCCs. Specifically, more dominant vascular structures and less hemorrhage were seen in low-grade tumors (2.15±1.05) compared to high-grade tumors (1.27±0.47) (P<0.005). The ratio of ITSS area to tumor area was also significantly higher for the high-grade group (1.55±0.52) than that for the low-grade group (0.88±0.43) on SWI (P<0.005). CONCLUSION: SWI is useful for grading CRCCs.