Applying arterial enhancement fraction (AEF) texture features to predict the tumor response in hepatocellular carcinoma (HCC) treated with Transarterial chemoembolization (TACE)

Background To evaluate the application of Arterial Enhancement Fraction (AEF) texture features in predicting the tumor response in Hepatocellular Carcinoma (HCC) treated with Transarterial Chemoembolization (TACE) by means of texture analysis. Methods HCC patients treated with TACE in Shengjing Hospital of China Medical University from June 2018 to December 2019 were retrospectively enrolled in this study. Pre-TACE Contrast Enhanced Computed Tomography (CECT) and imaging follow-up within 6 months were both acquired. The tumor responses were categorized according to the modified RECIST (mRECIST) criteria. Based on the CECT images, Region of Interest (ROI) of HCC lesion was drawn, the AEF calculation and texture analysis upon AEF values in the ROI were performed using CT-Kinetics (C.K., GE Healthcare, China). A total of 32 AEF texture features were extracted and compared between different tumor response groups. Multi-variate logistic regression was performed using certain AEF features to build the differential models to predict the tumor response. The Receiver Operator Characteristic (ROC) analysis was implemented to assess the discriminative performance of these models. Results Forty-five patients were finally enrolled in the study. Eight AEF texture features showed significant distinction between Improved and Un-improved patients (p < 0.05). In multi-variate logistic regression, 9 AEF texture features were applied into modeling to predict “Improved” outcome, and 4 AEF texture features were applied into modeling to predict “Un-worsened” outcome. The Area Under Curve (AUC), diagnostic accuracy, sensitivity, and specificity of the two models were 0.941, 0.911, 1.000, 0.826, and 0.824, 0.711, 0.581, 1.000, respectively. Conclusions Certain AEF heterogeneous features of HCC could possibly be utilized to predict the tumor response to TACE treatment.

Clinical and Pathological Attributes of Hepatocellular Carcinoma Showing Lack of Restricted Diffusion on Magnetic Resonance Imaging

Objective: To correlate non-restricted diffusion magnetic resonance imaging (MRI) patterns of hepatocellular carcinoma (HCC), with histopathology and clinical outcome.Material and Methods: We retrospectively evaluated pre-treatment MRIs showing non-restricted diffusion HCC lesions (≥1-centimeter), excluding lesions with poor quality/non-available diffusion weighted imaging (DWI). Three radiologists evaluated 37 lesions in 27 patients, for: T1-weighted (T1W)/T2-weighted (T2W) characteristics, arterial enhancement, washout on portal venous/delayed phase, capsular enhancement, intralesional fat component and presence of cirrhosis. Histopathological reports were categorized as: well/moderate/poorly differentiated. Kaplan-Meier survival analysis was calculated for clinical outcome.Results: From a total of 37 lesions, 24 lesions had available pathological grading, which revealed well and moderately differentiated equally (12 lesions each). None of the non-restricted diffusion HCCs were poorly differentiated. Thirty-five of the 37 lesions (94.6%) showed arterial enhancement with washout; 34 lesions (91.9%) were T2W hypo-/isointense, 33 esions (89.2%) were T1W iso-/hyperintense, 19 lesions (51.4%) showed capsular enhancement and 8 lesions (21.6%) had intralesional fat. These findings in the well and moderately differentiated groups were not significantly different (p-value 0.178-1.000). Overall mean-survival was 6.972 years (95% confidence interval (CI); 5.3-8.6). The 1-year, overall survival rate was 83.6% and for 3-years was 67.9%. Mean survival of well and moderately differentiated groups were 6.88 and 7.23 years (95% CI 5.7-8.0 and 4.4-10.1), respectively (p-value=0.319).Conclusion: DWI may help to predict histological grading of HCC and clinical outcome. We found that non-restricted diffusion HCCs were histologically well or moderately differentiated, with no significant difference of imaging findings and survival rates between the two groups. No poorly differentiated lesions were seen in our non-restricted HCC cohort.

MRI Features for Predicting Microvascular Invasion of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

<b><i>Purpose:</i></b> Microvascular invasion (MVI) is an important prognostic factor in patients with hepatocellular carcinoma (HCC). However, the reported results of magnetic resonance imaging (MRI) features for predicting MVI of HCC are variable and conflicting. Therefore, this meta-analysis aimed to identify the significant MRI features for MVI of HCC and to determine their diagnostic value. <b><i>Methods:</i></b> Original studies reporting the diagnostic performance of MRI for predicting MVI of HCC were identified in MEDLINE and EMBASE up until January 15, 2020. Study quality was assessed using QUADAS-2. A bivariate random-effects model was used to calculate the meta-analytic pooled diagnostic odds ratio (DOR) and 95% confidence interval (CI) for each MRI feature for diagnosing MVI in HCC. The meta-analytic pooled sensitivity and specificity were calculated for the significant MRI features. <b><i>Results:</i></b> Among 235 screened articles, we found 36 studies including 4,274 HCCs. Of the 15 available MRI features, 7 were significantly associated with MVI: larger tumor size (&#x3e;5 cm) (DOR = 5.2, 95% CI [3.0–9.0]), rim arterial enhancement (4.2, 95% CI [1.7–10.6]), arterial peritumoral enhancement (4.4, 95% CI [2.8–6.9]), peritumoral hypointensity on hepatobiliary phase imaging (HBP) (8.2, 95% CI [4.4–15.2]), nonsmooth tumor margin (3.2, 95% CI [2.2–4.4]), multifocality (7.1, 95% CI [2.6–19.5]), and hypointensity on T1-weighted imaging (T1WI) (4.9, 95% CI [2.5–9.6]). Both peritumoral hypointensity on HBP and multifocality showed very high meta-analytic pooled specificities for diagnosing MVI (91.1% [85.4–94.8%] and 93.3% [74.5–98.5%], respectively). <b><i>Conclusions:</i></b> Seven MRI features including larger tumor size, rim arterial enhancement, arterial peritumoral enhancement, peritumoral hypointensity on HBP, nonsmooth margin, multifocality, and hypointensity on T1WI were significant predictors for MVI of HCC. These MRI features predictive of MVI can be useful in the management of HCC.

Contrast enhanced ultrasound (CEUS) with parametric imaging and time intensity curve analysis (TIC) for evaluation of the success of prostate arterial embolization (PAE) in cases of prostate hyperplasia

AIM: To evaluate the use of dynamic contrast enhanced ultrasound (CEUS) with parametric color-coded imaging and time intensity curve analysis (TIC) for planning and follow-up after prostate arterial embolization (PAE). MATERIAL/METHOD: Before and after selective iliacal embolization by PAE with a follow up of 6 months 18 male patients (43–78 years, mean 63±3.5 years) with histopathological proven benign prostate hyperplasia were examined by one experienced examiner. A multifrequency high resolution probe (1–6 MHz) was used for transabdominal ultrasound and CEUS with bolus injections of 2.4 ml sulphur-hexafluoride microbubbles. Independent evaluation of color-coded parametric imaging before and after PAE by in PACS stored DICOM loops from arterial phase (10–15 s) up to 1min were performed. Criteria for successful treatment were reduction of early arterial enhancement by changes of time to peak (TTP) and area under the curve (AUC) by measurements in 8 regions of interest (ROI) of 5 mm in diameter at the margin and in the center and changes from hyperenhancement in parametric imaging (perfusion evaluation of arterial enhancement over 15 s) from red and yellow to blue and green by partial infarctions. Reference imaging method was the contrast high resolution 3 tesla magnetic resonance tomography (MRI) using 3D vibe sequences before and after PAE and for the follow up after 3 and 6 months. RESULTS: PAE was technically and clinically successful in all 18 patients with less clinical symptoms and reduction of the gland volume. In all cases color-coded CEUS parametric imaging was able to evaluate partial infarction after embolization with changes from red and yellow to green and blue colors in the embolization areas. Relevant changes could be evaluated for TIC-analysis of CEUS with reduced arterial enhancement in the arterial phase and prolonged enhancement of up to 1 min with significant changes (p = 0.0024). The area under the curve (AUC) decreased from 676±255.04 rU (160 rU–1049 rU) before PAE to 370.43±255.19 rU (45 rU–858 rU) after PAE. Time to peak (TTP) did not change significantly (p = 0.6877); TTP before PAE was 25.82±9.04 s (12.3 s–42.5 s) and after PAE 24.43±9.10 s (12–39 s). Prostate volume decreased significantly (p = 0.0045) from 86.93±34.98 ml (30–139 ml) before PAE to 50.57±26.26 ml (19–117 ml) after PAE. There were no major complications and, in most cases (14/18) a volume reduction of the benign prostate hyperplasia occurred. CONCLUSION: Performed by an experienced examiner CEUS with parametric imaging and TIC-analysis is highly useful to further establish prostatic artery embolization (PAE) as a successful minimal invasive treatment of benign prostatic hyperplasia.