Focal Lesions in Fatty Liver: If Quantitative Analysis Facilitates the Differentiation of Atypical Benign from Malignant Lesions

Washout on Contrast-Enhanced Ultrasound of Benign Focal Liver Lesions-A Review on Its Frequency and Possible Causes

In all imaging methods, including contrast-enhanced ultrasound (CEUS), enhancement in the late phase (LP) is an important criterion for differentiating between benign and malignant focal liver lesions (FLLs). In general, malignant liver lesions are characterized by hypoenhancement and washout in the LP. A lesion with LP hyperenhancement or isoenhancement in the non-cirrhotic liver is usually benign. However, LP hypoenhancement in benign lesions is not so rare, and is even normal and the standard for some lesions, and there are exceptions for each tumor entity that can represent a diagnostic challenge. Knowing these contrast patterns and exceptions is key for correct diagnosis and patient management. The following narrative review describes the contrast behaviors and the frequency of washout and LP hypoenhancement for common as well as rare benign liver lesions and analyzes its causes.

Rare and lacking typical clinical symptoms of liver tumors: Four case reports

BACKGROUND

Rare liver tumors (RLTs) have an extremely low likelihood of forming, and some have been recorded only in isolated cases. The lack of normal clinical symptoms in RLTs makes preoperative diagnosis extremely challenging, which results in frequent misinterpretation. The present case report helps enhance our ability to recognize and treat uncommon liver tumor disorders.

CASE SUMMARY

We describe four distinct examples of rare liver tumor diseases. These cases were all true cases with no conventional clinical signs or imaging findings. In all patients, hepatic occupancy was discovered on physical examination, which raised the preoperative suspicion of hepatic cancer. All tumors were surgically removed, and postoperative histology and immunohistochemistry were performed to confirm the diagnosis. The first patient had primary hepatic fibrosarcoma. The second case involved a primary hepatic neuroendocrine tumors. These two patients had malignant liver tumors, and both had extremely satisfactory surgical outcomes. The third case involved focal hepatic steatosis, and the fourth case involved a single necrotic nodule in the liver. These two patients had benign liver tumors, but they had already undergone surgery and did not require any postoperative care.

CONCLUSION

The number of patients with RLTs is small, and the clinical and imaging results are vague. Preoperative diagnosis is challenging, and patients are sometimes mistakenly diagnosed with liver cancer, which leads to unnecessary surgical therapy in certain individuals.

Wavelet radiomics features from multiphase CT images for screening hepatocellular carcinoma: analysis and comparison

Early detection of liver malignancy based on medical image analysis plays a crucial role in patient prognosis and personalized treatment. This task, however, is challenging due to several factors, including medical data scarcity and limited training samples. This paper presents a study of three important aspects of radiomics feature from multiphase computed tomography (CT) for classifying hepatocellular carcinoma (HCC) and other focal liver lesions: wavelet-transformed feature extraction, relevant feature selection, and radiomics features-based classification under the inadequate training samples. Our analysis shows that combining radiomics features extracted from the wavelet and original CT domains enhance the classification performance significantly, compared with using those extracted from the wavelet or original domain only. To facilitate the multi-domain and multiphase radiomics feature combination, we introduce a logistic sparsity-based model for feature selection with Bayesian optimization and find that the proposed model yields more discriminative and relevant features than several existing methods, including filter-based, wrapper-based, or other model-based techniques. In addition, we present analysis and performance comparison with several recent deep convolutional neural network (CNN)-based feature models proposed for hepatic lesion diagnosis. The results show that under the inadequate data scenario, the proposed wavelet radiomics feature model produces comparable, if not higher, performance metrics than the CNN-based feature models in terms of area under the curve.

Diagnosis of liver tumors by multimodal ultrasound imaging

To investigate the diagnostic value of multimodal ultrasound imaging composed of conventional ultrasonography (US), contrast-enhanced ultrasonography (CEUS), and shear wave elastography (SWE) for liver tumors.Between October 2017 and October 2019, US, CEUS, and SWE examinations of a total of 158 liver tumors in 136 patients at The First Affiliated Hospital of Nanchang University were performed. The histopathological or imaging diagnostic results were used as controls to evaluate the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of US, CEUS, SWE, and multimodal ultrasound imaging, which combines these 3 modes, in the differential diagnosis of benign and malignant liver tumors.Among the 158 tumors, there were 64 benign tumors, including 55 cases of hepatic hemangioma, 3 cases of focal nodular hyperplasia of the liver, 4 cases of hepatic cyst, and 2 cases of focal nonuniform distribution of fat in the liver. There were 94 malignant tumors, including 32 cases of hepatocellular carcinoma, 22 cases of intrahepatic cholangiocellular carcinoma, 29 cases of metastatic liver cancer, and 11 cases of dysplastic nodules in cirrhotic liver. In the diagnosis of benign and malignant liver tumors, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 82.56%, 68.06%, 75.96%, 75.53%, and 76.56% for US; 92.39%, 86.36%, 89.87%, 90.43%, and 89.06% for CEUS; 87.14%, 76.81%, 82.91%, 82.98%, and 82.81% for SWE; and 97.85%, 95.38%, 96.83%, 96.81%, and 96.88% for multimodal ultrasound imaging, respectively. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were all significantly higher for multimodal ultrasound imaging than those values for US, CEUS, and SWE (all P < .05). The areas under the receiver operating characteristic curve for US, CEUS, SWE, and multimodal ultrasound imaging in the diagnosis of benign and malignant liver tumors were 0.760, 0.897, 0.829, and 0.968, respectively.US, CEUS, and SWE all have diagnostic value in the diagnosis of benign and malignant liver tumors. Multimodal ultrasound imaging could significantly increase the accuracy of the diagnosis of benign and malignant liver tumors and has higher value for clinical application.

Comparison of hepatic epithelioid angiomyolipoma and non-hepatitis B, non-hepatitis C hepatocellular carcinoma on contrast-enhanced ultrasound

PURPOSE

The purpose of this study was to retrospectively compare the imaging features of hepatic epithelioid angiomyolipoma (HEAML) to those of hepatocellular carcinoma negative for hepatitis B surface antigen and hepatitis C antibody (NBNC-HCC) on contrast-enhanced ultrasound (CEUS) with sulphur hexafluoride microbubbles.

MATERIAL AND METHODS

Twenty-two patients (4 men, 18 women) with a mean age of 42.6±10.2 (SD) years (range: 22-63 years) with histopathologically confirmed HEMAL were included in the study. Forty-four patients (30 men, 14 women) with a mean age of 57.3±15.9 years (range: 19-85 years) with histopathologically confirmed NBNC-HCC were randomly selected from our institution's database as a control group. The CEUS characteristics of the two groups were compared.

RESULTS

On conventional ultrasound, significant differences in tumor diameter were found between HEAML (4.0±2.0 [SD] cm; range: 1.3-8.9cm) and NBNC-HCC (8.4±4.4 [SD] cm; range: 1.6-18cm) (P<0.001) as well as in degrees of enhancement during the portal (P=0.001) and late phases (P=0.003), contrast distribution (P<0.001) and absence of pseudocaspule (P<0.001). On CEUS, hyperenhancement during the arterial phase was observed in 21/22 (95.5%) HEAMLs and in 43/44 (97.7%) NBNC-HCCs (P>0.999). Homogeneous enhancement was more frequent in HEAMLs (20/22; 90.9%) than in NBNC-HCCs (13/44; 29.6%) (P<0.001). Pseudocapsule was observed in 0/22 HEAMLs (0.0%) and in 36/44 NBNC-HCCs (81.8%) (P=0.017). A prolonged enhancement was observed in 5/22 HEAMLs (22.7%) and in 0/44 NBNC-HCCs (0.0%) (P<0.001) during the late phase.

CONCLUSION

CEUS with sulphur hexafluoride microbubbles is helpful in discriminating between HEAML and NBNC-HCC. Homogeneous enhancement and lack of pseudocapsule are suggestive features for the diagnosis of HEAML.

3D image guidance assisted identification of colorectal cancer liver metastases not seen on intraoperative ultrasound: results from a prospective trial

BACKGROUND

Neoadjuvant treatment of colorectal liver metastases has become increasingly common, and while effective, often renders small metastases difficult to visualize on intraoperative US. The objective of this study was to determine the utility of a 3D image-guidance system in patients with intraoperative sonographically-occult CRLM.

METHODS

50 patients with at least one CRLM ≤ 1.5 cm were enrolled in this prospective trial of an FDA-approved Explorer image-guidance system. If the tumor(s) seen on preoperative imaging were not identified with intraoperative US, Explorer was used to target the US examination to the involved area for a more focused assessment. The primary endpoint was the proportion of cases with sonographically-occult metastases identified using Explorer.

RESULTS

Forty-eight patients with preoperative scans within eight weeks of surgery were included for analysis. Forty-six patients were treated with preoperative chemotherapy (median 4 months, range 2-24 months). Overall, 22 sonographically-occult tumors in 14 patients were interrogated by Explorer, of which 15 tumors in 10 patients were located with image-guidance assistance. The only difference between patients with tumors not identified on US and those who did was the number of tumors (median 3 vs. 2, p = 0.018).

CONCLUSION

3D image-guidance can assist in identifying small CRLM, particularly after treatment with chemotherapy.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02806037, https://clinicaltrials.gov/ct2/show/NCT02806037.

Contrast-enhanced US for characterization of focal liver lesions: a comprehensive meta-analysis

OBJECTIVES

This meta-analysis was performed to evaluate the accuracy of contrast-enhanced ultrasound (CEUS) in differentiating malignant from benign focal liver lesions (FLLs).

METHODS

Cochrane Library, PubMed and Web of Science databases were systematically searched and checked for studies using CEUS in characterization of FLLs. Data necessary to construct 2×2 contingency tables were extracted from included studies. The QUADAS tool was utilized to assess the methodologic quality of the studies. Meta-analysis included data pooling, subgroup analyses, meta-regression and investigation of publication bias was comprehensively performed.

RESULTS

Fifty-seven studies were included in this meta-analysis and the overall diagnostic accuracy in characterization of FLLs was as follows: pooled sensitivity, 0.92 (95%CI: 0.91-0.93); pooled specificity, 0.87 (95%CI: 0.86-0.88); diagnostic odds ratio, 104.20 (95%CI: 70.42-154.16). Subgroup analysis indicated higher diagnostic accuracy of the second-generation contrast agents (CAs) than the first-generation CA (Levovist; DOR: 118.27 vs. 62.78). Furthermore, Sonazoid demonstrated the highest diagnostic accuracy among three major CAs (SonoVue, Levovist and Sonazoid; DOR: 118.82 vs. 62.78 vs. 227.39). No potential publication bias was observed of the included studies.

CONCLUSION

CEUS is an accurate tool to stratify the risk of malignancy in FLLs. The second-generation CAs, especially Sonazoid may greatly improve diagnostic performance.

KEY POINTS

• CEUS shows excellent diagnostic accuracy in differentiating malignant from benign FLLs. • The second-generation CAs have higher diagnostic accuracy than first-generation CAs. • Sonazoid demonstrates the highest diagnostic accuracy among three major CAs.