Contrast-enhanced US for characterization of focal liver lesions: a comprehensive meta-analysis. Eur Radiol. 2018;28:2077-2088. [PMID: 29189932 DOI: 10.1007/s00330-017-5152-x]

PEGylated gas vesicles: a promising novel ultrasound contrast agent for diagnosis and guiding radiofrequency ablation of liver tumor

Ultrasound contrast agents (UCAs) play an important role in diagnosis and the imaging-guided treatment of liver tumor in clinical settings. However, most commercially available UCAs are micro-sized and fabricated through a chemical synthesis route. Here, we developed a new class of biosynthesized nanoscale contrast agent (PEG-GVs) and comprehensively compared its physicochemical characteristics and imaging performance with commercial Sonovue and Sonazoid. Our results revealed PEG-GVs may produce more stable and durable contrast signals, contributing to their penetration beyond blood vessels and long-time retention in liver. Interestingly, we found that PEG-GVs did not exhibit a continuously enhanced accumulation in the liver tumor due to the EPR effect, but displayed a rapid regression. The long-time retention of PEG-GVs in normal liver tissue and rapid regression from liver tumor lead to distinct display of liver tumor boundaries, enabling the early diagnosis of small liver metastases and presenting advantages in guiding radiofrequency ablation of liver tumor. Moreover, we have also verified that PEG-GVs exhibit excellent imaging performance and biosafety in macaques. Our study provides new insights into the roles of PEG-GVs in liver tumor diagnosis and ablation guidance.

Ultrasound innovations in abdominal radiology: evaluation of focal liver lesions

Focal liver lesions (FLLs) are common and are often first identified on abdominal ultrasound examinations. Although CT and MRI were historically required to noninvasively characterize many FLLs, introduction of microbubble contrast agents produced a groundbreaking change as contrast enhanced ultrasound (CEUS) showed vascularity to the capillary level for the first time. CEUS shows specific arterial phase enhancement patterns in benign lesions and accurately differentiates malignant lesions based on the timing and intensity of washout. Parametric time of arrival and microvascular imaging techniques can demonstrate vascularity in FLLs with significantly improved sensitivity compared with conventional Doppler techniques. Shear-wave elastography and quantitative ultrasound are generally used to evaluate diffuse liver disease but show promise in evaluation of FLLs.

Diagnostic value of contrast-enhanced ultrasound in ovarian cancer: a meta-analysis

BackgroundOvarian cancer has been reported to be the eighth most common cancer among women worldwide.PurposeTo assess the diagnostic efficacy of contrast-enhanced ultrasound (CEUS) in distinguishing between benign and malignant ovarian tumors.Material and MethodsA comprehensive search of scientific literature databases, including PubMed, Cochrane Library, Web of Science, Wanfang, and CNKI, was conducted from their inception to November 2019 to identify relevant studies on the use of CEUS in the differential diagnosis of benign and malignant ovarian tumors. Sensitivity (SEN), specificity (SPE), positive and negative likelihood ratios (LR+/LR-), diagnostic odds ratios (DORs), and their corresponding 95% confidence intervals (CIs) were retrieved and analyzed using Stata 15.0.ResultsAfter rigorous screening, a total of 15 high-quality clinical studies encompassing 934 patients with ovarian cancer, comprising 969 ovarian tumors (403 malignant tumors and 566 benign tumors), were included in the analysis. Data analysis revealed significant correlations between CEUS and various diagnostic indices for ovarian tumors: the combined SEN and SPE were 0.93 (95% CI = 0.88-0.96) and 0.93 (95% CI = 0.90-0.96), respectively, and the combined LR+ and LR- were 14.07 (95% CI = 9.46-20.92) and 0.08 (95% CI = 0.05-0.13), respectively, with a combined DOR of 185.15 (95% CI = 93.31-367.41). The area under the summary receiver operating characteristic curve (AUC) was 0.98 (95% CI = 0.96-0.99). No publication bias was detected in the meta-analysis (P = 0.62).ConclusionCEUS demonstrates significant value in the diagnosis and differential diagnosis of benign and malignant ovarian tumors.

Enhancing Liver Nodule Visibility and Diagnostic Classification Using Ultrasound Local Attenuation Coefficient Slope Imaging

OBJECTIVE

B-mode ultrasound (US) presents challenges in accurately detecting and distinguishing between benign and malignant liver nodules. This study utilized quantitative US local attenuation coefficient slope (LACS) imaging to address these limitations.

MATERIALS AND METHODS

This is a prospective, cross-sectional study in adult patients with definable solid liver nodules at US conducted from March 2021 to December 2023. The composite reference standard included histopathology when available or magnetic resonance imaging. LACS images were obtained using a phantom-free method. Nodule visibility was assessed by computing the contrast-to-noise ratio (CNR). Classification accuracy for differentiating benign and malignant lesions was assessed with the area under the receiver operating characteristic curve (AUC), along with sensitivity and specificity.

RESULTS

The study enrolled 97 patients (age: 62 y ± 13 [standard deviation]), with 57.0% malignant and 43.0% benign observations (size: 26.3 ± 18.9 mm). LACS images demonstrated higher CNR (12.3 dB) compared to B-mode (p < 0.0001). The AUC for differentiating nodules and liver parenchyma was 0.85 (95% confidence interval [CI]: 0.79-0.90), with higher values for malignant (0.93, CI: 0.88-0.97) than benign nodules (0.76, CI: 0.66-0.87). A LACS threshold of 0.94 dB/cm/MHz provided a sensitivity of 0.83 (CI: 0.74-0.89) and a specificity of 0.82 (CI: 0.73-0.88). LACS mean values were higher (p < 0.0001) in malignant (1.28 ± 0.27 dB/cm/MHz) than benign nodules (0.98 ± 0.19 dB/cm/MHz).

CONCLUSION

LACS imaging improves nodule visibility and provides better differentiation between benign and malignant liver nodules, showing promise as a diagnostic tool.

Ultrasound shear wave viscoelastography to characterize liver nodules

Purpose. To investigate the diagnostic performance of ultrasound (US)-based shear wave speed (SWS), shear wave attenuation (SWA), and combination of them as shear wave viscoelastography (SWVE) methods in patients undergoing US to characterize focal liver nodules.Materials and methods. In this prospective cross-sectional study, 70 patients with 72 nodules were enrolled. Investigational US and clinical magnetic resonance imaging (MRI) examinations were performed in all participants. The composite reference standard included MRI or histopathology to differentiate benign and malignant nodules. A linear discriminant analysis (LDA) was used to assess the combination of SWVE methods. Analyzes included Mann-WhitneyUtest, receiver operating characteristic analysis, and computation of sensitivity and specificity at the point that maximized the Youden index.Results. Mean SWS was significantly higher in malignant than benign nodules (2.49 ± 0.76 m s-1vs. 1.72 ± 0.70,p< 0.001), whereas SWA was lower (0.56 ± 0.30 vs. 1.10 ± 0.43 Np/m/Hz,p< 0.001). To differentiate between malignant and benign nodules, SWS with a threshold of 2.43 m s-1achieved a sensitivity of 0.54 (95% confidence interval (CI): 0.38-0.69) and a specificity of 0.88 (CI: 0.74-0.95). SWA with a threshold of 0.81 Np/m/Hz yielded a sensitivity of 0.81 (CI: 0.66-0.90) and a specificity of 0.74 (CI: 0.58-0.86). Combining these SWVE methods using a LDA resulted in a sensitivity of 0.81 (CI: 0.66-0.91) and a specificity of 0.86 (CI: 0.71-0.94).Conclusion. Malignant nodules had higher SWS and lower SWA than benign ones. The combination of SWS and SWA in a LDA classification algorithm increased the diagnostic performance.

Review of Clinical Applications of Sonazoid Ultrasound Contrast for Liver Evaluation

ABSTRACT

Sonazoid is a new ultrasound contrast agent with unique Kupffer phase imaging advantages and high mechanical index stability. This paper introduces the basic theories and advantages of Sonazoid ultrasound. Then, the application and latest advances of Sonazoid in the diagnosis and treatment of liver diseases are reviewed in detail. In addition, the advantages and disadvantages of Sonazoid ultrasound and its future directions are discussed. Sonazoid is expected to become an important tool for clinical ultrasound diagnosis and treatment.

Utilization of Contrast-Enhanced Ultrasound in Diagnosis of Focal Liver Lesions

Background and aims: Focal liver lesions (FLL) are one of the most common indications for hepatology and hepatobiliary surgery consultation. In this retrospective study, we aim to assess if contrast-enhanced ultrasound (CEUS) can address diagnostic dilemmas in the evaluation of indeterminate liver lesions by identifying characteristics of indeterminate FLL on CEUS and correlating these with cross-sectional imaging and pathology findings. Methods: We retrospectively reviewed all patients who underwent CEUS evaluation for liver lesions over a 28-month period (Oct 2020 to Jan 2023) at the University of Kentucky. To assess the relationship between CEUS results and the corresponding CT, MRI, and/or pathologic findings, the McNemar-Bowker tests were performed. Results: Twenty-nine patients were included (after two exclusions from a total n of 31). Mean age was 54 years, 62% were female, and 48% had underlying cirrhosis. Of the 29 patients with initial cross-sectional imaging, the initial results showed malignancy or likely malignant lesion in 6 patients and benign or likely benign lesion in 6 patients. The remaining 17 patients had inconclusive/indeterminate results. CEUS clarified an "indeterminate" CT/MRI result 15 times out of 17 (88.2%), moving the diagnosis to "benign" 11 times while suggesting "malignant" only four times. When aggregating indeterminate cross-sectional results with either benign or malignant categories suggested by CEUS, CEUS never reversed a benign CT/MRI diagnosis but often reversed a malignant CT/MRI diagnosis. Conclusion: CEUS provided a definitive diagnosis of indeterminate liver lesions in approximately 90% of patients and avoided the need for biopsy in most patients. In cases where the liver lesions were biopsied, CEUS accurately distinguished malignant versus benign lesions as confirmed by biopsy findings. CEUS, therefore, has the potential to provide a precise diagnosis for the majority of indeterminate lesions.

A combined model based on radiomics features of Sonazoid contrast-enhanced ultrasound in the Kupffer phase for the diagnosis of well-differentiated hepatocellular carcinoma and atypical focal liver lesions: a prospective, multicenter study

OBJECTIVE

The objective of this study was to develop a combined model based on radiomics features of Sonazoid contrast-enhanced ultrasound (CEUS) during the Kupffer phase and to evaluate its value in differentiating well-differentiated hepatocellular carcinoma (w-HCC) from atypical benign focal liver lesions (FLLs).

METHODS

A total of 116 patients with preoperatively Sonazoid-CEUS confirmed w-HCC or benign FLL were selected from a prospective multiple study on the clinical application of Sonazoid in FLLs conducted from August 2020 to March 2021. According to the randomization principle, the patients were divided into a training cohort and a test cohort in a 7:3 ratio. Seventy-nine patients were used for establishing and training the radiomics model and combined model. In comparison, 37 patients were used for validating and comparing the performance of the models. The diagnostic efficacy of the models for w-HCC and atypical benign FLLs was evaluated using ROCs curves and decision curves. A combined model nomogram was created to assess its value in reducing unnecessary biopsies.

RESULTS

Among the patients, there were 55 cases of w-HCC and 61 cases of atypical benign FLLs, including 28 cases of early liver abscess, 16 cases of atypical hepatic hemangioma, 8 cases of hepatocellular dysplastic nodules (DN), and 9 cases of focal nodular hyperplasia (FNH). The radiomics model and combined model we established had AUCs of 0.905 and 0.951, respectively, in the training cohort, and the AUCs of the two models in the test cohort were 0.826 and 0.912, respectively. The combined model outperformed the radiomics feature model significantly. Decision curve analysis demonstrated that the combined model achieved a higher net benefit within a specific threshold probability range (0.25 to 1.00). A nomogram of the combined model was developed.

CONCLUSION

The combined model based on the radiomics features of Sonazoid-CEUS in the Kupffer phase showed satisfactory performance in diagnosing w-HCC and atypical benign FLLs. It can assist clinicians in timely detecting malignant FLLs and reducing unnecessary biopsies for benign diseases.

Ultrasomics differentiation of malignant and benign focal liver lesions based on contrast-enhanced ultrasound

OBJECTIVES

To establish a nomogram for differentiating malignant and benign focal liver lesions (FLLs) using ultrasomics features derived from contrast-enhanced ultrasound (CEUS).

METHODS

527 patients were retrospectively enrolled. On the training cohort, ultrasomics features were extracted from CEUS and b-mode ultrasound (BUS). Automatic feature selection and model development were performed using the Ultrasomics-Platform software, outputting the corresponding ultrasomics scores. A nomogram based on the ultrasomics scores from artery phase (AP), portal venous phase (PVP) and delayed phase (DP) of CEUS, and clinical factors were established. On the validation cohort, the diagnostic performance of the nomogram was assessed and compared with seniorexpert and resident radiologists.

RESULTS

In the training cohort, the AP, PVP and DP scores exhibited better differential performance than BUS score, with area under the curve (AUC) of 84.1-85.1% compared with the BUS (74.6%, P < 0.05). In the validation cohort, the AUC of combined nomogram and expert was significantly higher than that of the resident (91.4% vs. 89.5% vs. 79.3%, P < 0.05). The combined nomogram had a comparable sensitivity with the expert and resident (95.2% vs. 98.4% vs. 97.6%), while the expert had a higher specificity than the nomogram and the resident (80.6% vs. 72.2% vs. 61.1%, P = 0.205).

CONCLUSIONS

A CEUS ultrasomics based nomogram had an expert level performance in FLL characterization.

WFUMB Review Paper. Incidental Findings in Otherwise Healthy Subjects, How to Manage: Liver

An incidental focal liver lesion (IFLL) is defined as a hepatic lesion identified in a patient imaged for an unrelated reason. They are frequently encountered in daily practice, sometimes leading to unnecessary, invasive and potentially harmful follow-up investigations. The clinical presentation and the imaging aspects play an important role in deciding if, and what further evaluation, is needed. In low-risk patients (i.e., without a history of malignant or chronic liver disease or related symptoms), especially in those younger than 40 years old, more than 95% of IFLLs are likely benign. Shear Wave liver Elastography (SWE) of the surrounding liver parenchyma should be considered to exclude liver cirrhosis and for further risk stratification. If an IFLL in a low-risk patient has a typical appearance on B-mode ultrasound of a benign lesion (e.g., simple cyst, calcification, focal fatty change, typical hemangioma), no further imaging is needed. Contrast-Enhanced Ultrasound (CEUS) should be considered as the first-line contrast imaging modality to differentiate benign from malignant IFLLs, since it has a similar accuracy to contrast-enhanced (CE)-MRI. On CEUS, hypoenhancement of a lesion in the late vascular phase is characteristic for malignancy. CE-CT should be avoided for characterizing probable benign FLL and reserved for staging once a lesion is proven malignant. In high-risk patients (i.e., with chronic liver disease or an oncological history), each IFLL should initially be considered as potentially malignant, and every effort should be made to confirm or exclude malignancy. US-guided biopsy should be considered in those with unresectable malignant lesions, particularly if the diagnosis remains unclear, or when a specific tissue diagnosis is needed.

British Society of Gastroenterology guidelines for the management of hepatocellular carcinoma in adults

Deaths from the majority of cancers are falling globally, but the incidence and mortality from hepatocellular carcinoma (HCC) is increasing in the United Kingdom and in other Western countries. HCC is a highly fatal cancer, often diagnosed late, with an incidence to mortality ratio that approaches 1. Despite there being a number of treatment options, including those associated with good medium to long-term survival, 5-year survival from HCC in the UK remains below 20%. Sex, ethnicity and deprivation are important demographics for the incidence of, and/or survival from, HCC. These clinical practice guidelines will provide evidence-based advice for the assessment and management of patients with HCC. The clinical and scientific data underpinning the recommendations we make are summarised in detail. Much of the content will have broad relevance, but the treatment algorithms are based on therapies that are available in the UK and have regulatory approval for use in the National Health Service.

Value of Sonazoid-enhanced ultrasonography in characterizing indeterminate focal liver lesions on gadoxetic acid-enhanced liver MRI in patients without risk factors for hepatocellular carcinoma

PURPOSE

To evaluate the added value of contrast-enhanced ultrasonography (CEUS) using Sonazoid in characterizing focal liver lesions (FLLs) with indeterminate findings on gadoxetic acid-enhanced liver MRI in patients without risk factors for hepatocellular carcinoma (HCC).

METHODS

Patients who underwent CEUS using Sonazoid for characterizing indeterminate FLLs on gadoxetic acid-enhanced liver MRI were. The indeterminate FLLs were classified according to the degree of malignancy on a 5-point scale on MRI and combined MRI and CEUS. The final diagnosis was made either pathologically or based on more than one-year follow-up. The diagnostic performance was assessed using a receiver operating characteristic (ROC) curve analysis, and the net reclassification improvement (NRI) was calculated.

RESULTS

A total of 97 patients (mean age, 49 years ± 16, 41 men, 80 benign and 17 malignant lesions) were included. When CEUS was added to MRI, the area under the ROC curve increased, but the difference was not statistically significant (0.87 [95% confidence interval {CI}, 0.77-0.98] for MRI vs 0.93 [95% CI, 0.87-0.99] for CEUS added to MRI, P = 0.296). The overall NRI was 0.473 (95% CI, 0.100-0.845; P = 0.013): 33.8% (27/80) of benign lesions and 41.2% (7/17) of malignant lesions were appropriately reclassified, whereas 10.0% (8/80) of benign lesions and 17.6% (3/17) of malignant lesions were incorrectly reclassified.

CONCLUSIONS

Although performing CEUS with Sonazoid did not significantly improve the overall diagnostic performance in characterizing indeterminate FLLs on gadoxetic acid-enhanced liver MRI in patients without risk factors for HCC, it may increase radiologist's confidence in classifying FLLs.

Dynamic Contrast-Enhanced Ultrasound in the Prediction of Advanced Hepatocellular Carcinoma Response to Systemic and Locoregional Therapies

Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and the sixth most common malignant tumor in the world, with an incidence of 2-8% per year in patients with hepatic cirrhosis or chronic hepatitis. Despite surveillance schedules, it is sometimes diagnosed at an advanced stage, requiring complex therapeutic efforts with both locoregional and systemic treatments. Traditional radiological tools (computed tomography and magnetic resonance) are used for the post-treatment follow-up of HCC. The first follow-up imaging is performed at 4 weeks after resection or locoregional treatments, or after 3 months from the beginning of systemic therapies, and subsequently every 3 months for the first 2 years. For this reason, these radiological methods do not grant the possibility of an early distinction between good and poor therapeutic response. Contrast-enhanced ultrasound (CEUS) and dynamic contrast-enhanced ultrasound (DCE-US) have gained the interest of several researchers for their potential role in the early assessment of response to locoregional treatments (chemoembolization) or antiangiogenic therapies in patients with advanced HCC. In fact, DCE-US, through a quantitative analysis performed by specific software, allows the construction of time-intensity curves, providing an evaluation of the parameters related to neoplastic tissue perfusion and its potential changes following therapies. It has the invaluable advantage of being easily repeatable, minimally invasive, and able to grant important evaluations regarding patients' survival, essential for well-timed therapeutic changes in case of unsatisfying response, and eventual further treatment planning.

Ultrasound tissue scatterer distribution imaging: An adjunctive diagnostic tool for shear wave elastography in characterizing focal liver lesions

OBJECTIVES

Focal liver lesion (FLL) is a prevalent finding in cross-sectional imaging, and distinguishing between benign and malignant FLLs is crucial for liver health management. While shear wave elastography (SWE) serves as a conventional quantitative ultrasound tool for evaluating FLLs, ultrasound tissue scatterer distribution imaging (TSI) emerges as a novel technique, employing the Nakagami statistical distribution parameter to estimate backscattered statistics for tissue characterization. In this prospective study, we explored the potential of TSI in characterizing FLLs and evaluated its diagnostic efficacy with that of SWE.

METHODS

A total of 235 participants (265 FLLs; the study group) were enrolled to undergo abdominal examinations, which included data acquisition from B-mode, SWE, and raw radiofrequency data for TSI construction. The area under the receiver operating characteristic curve (AUROC) was used to evaluate performance. A dataset of 20 patients (20 FLLs; the validation group) was additionally acquired to further evaluate the efficacy of the TSI cutoff value in FLL characterization.

RESULTS

In the study group, our findings revealed that while SWE achieved a success rate of 49.43 % in FLL measurements, TSI boasted a success rate of 100 %. In cases where SWE was effectively implemented, the AUROCs for characterizing FLLs using SWE and TSI stood at 0.84 and 0.83, respectively. For instances where SWE imaging failed, TSI achieved an AUROC of 0.78. Considering all cases, TSI presented an overall AUROC of 0.81. There was no statistically significant difference in AUROC values between TSI and SWE (p > 0.05). In the validation group, using a TSI cutoff value of 0.67, the AUROC for characterizing FLLs was 0.80.

CONCLUSIONS

In conclusion, ultrasound TSI holds promise as a supplementary diagnostic tool to SWE for characterizing FLLs.

The Clinical Value of Multimodal Ultrasound for the Differential Diagnosis of Hepatocellular Carcinoma from Other Liver Tumors in Relation to Histopathology

Recent advances in the field of ultrasonography offer promising tools for the evaluation of liver tumors. We aim to assess the value of multimodal ultrasound in differentiating hepatocellular carcinomas (HCCs) from other liver lesions. We prospectively included 66 patients with 72 liver tumors. The histological analysis was the reference standard for the diagnosis of malignant liver lesions, and partially for benign tumors. All liver lesions were assessed by multiparametric ultrasound: standard ultrasound, contrast-enhanced ultrasound (CEUS), the point shear wave elastography (pSWE) using shear wave measurement (SWM) method and real-time tissue elastography (RTE). To diagnose HCCs, CEUS achieved a sensitivity, specificity, accuracy and positive predictive value (PPV) of 69.05%, 92.86%, 78.57% and 93.55%, respectively. The mean shear-wave velocity (Vs) value in HCCs was 1.59 ± 0.29 m/s, which was lower than non-HCC malignancies (p < 0.05). Using a cut-off value of 1.58 m/s, SWM achieved a sensitivity of 54.76%, and 82.35% specificity, for differentiating HCCs from other malignant lesions. The combination of SWM and CEUS showed higher sensitivity (79.55%) compared with each technique alone, while maintaining a high specificity (89.29%). In RTE, most HCCs (61.53%) had a mosaic pattern with dominant blue areas corresponding to type "c" elasticity. Elasticity type "c" was 70.59% predictive for HCCs. In conclusion, combining B-mode ultrasound, CEUS, pSWE and RTE can provide complementary diagnostic information and potentially decrease the requirements for other imaging modalities.

Sonazoid-enhanced ultrasonography for noninvasive imaging diagnosis of hepatocellular carcinoma: special emphasis on the 2022 KLCA-NCC guideline

Contrast-enhanced ultrasonography (CEUS) is a noninvasive imaging modality used to diagnose hepatocellular carcinoma (HCC) based on specific imaging features, without the need for pathologic confirmation. Two types of ultrasound contrast agents are commercially available: pure intravascular agents (such as SonoVue) and Kupffer agents (such as Sonazoid). Major guidelines recognize CEUS as a reliable imaging method for HCC diagnosis, although they differ depending on the contrast agents used. The Korean Liver Cancer Association-National Cancer Center guideline includes CEUS with either SonoVue or Sonazoid as a second-line diagnostic technique. However, Sonazoid-enhanced ultrasound is associated with several unresolved issues. This review provides a comparative overview of these contrast agents regarding pharmacokinetic features, examination protocols, diagnostic criteria for HCC, and potential applications in the HCC diagnostic algorithm.

Artificial intelligence for the classification of focal liver lesions in ultrasound - a systematic review

Focal liver lesions are detected in about 15% of abdominal ultrasound examinations. The diagnosis of frequent benign lesions can be determined reliably based on the characteristic B-mode appearance of cysts, hemangiomas, or typical focal fatty changes. In the case of focal liver lesions which remain unclear on B-mode ultrasound, contrast-enhanced ultrasound (CEUS) increases diagnostic accuracy for the distinction between benign and malignant liver lesions. Artificial intelligence describes applications that try to emulate human intelligence, at least in subfields such as the classification of images. Since ultrasound is considered to be a particularly examiner-dependent technique, the application of artificial intelligence could be an interesting approach for an objective and accurate diagnosis. In this systematic review we analyzed how artificial intelligence can be used to classify the benign or malignant nature and entity of focal liver lesions on the basis of B-mode or CEUS data. In a structured search on Scopus, Web of Science, PubMed, and IEEE, we found 52 studies that met the inclusion criteria. Studies showed good diagnostic performance for both the classification as benign or malignant and the differentiation of individual tumor entities. The results could be improved by inclusion of clinical parameters and were comparable to those of experienced investigators in terms of diagnostic accuracy. However, due to the limited spectrum of lesions included in the studies and a lack of independent validation cohorts, the transfer of the results into clinical practice is limited.

Incidental Findings in Pediatric Patients: How to Manage Liver Incidentaloma in Pediatric Patients

The World Federation for Ultrasound in Medicine and Biology (WFUMB) is addressing the issue of incidental findings (IFs) with a series of publications entitled "Incidental imaging findings-the role of ultrasound". IFs in the liver of newborns and children are rare and much less commonly encountered than in adults; as a result, they are relatively much more frequently malignant and life-threatening, even when they are of benign histology. Conventional B-mode ultrasound is the well-established first line imaging modality for the assessment of liver pathology in pediatric patients. US technological advances, resulting in image quality improvement, contrast-enhanced ultrasound (CEUS), liver elastography and quantification tools for steatosis have expanded the use of ultrasound technology in daily practice. The following overview is intended to illustrate incidentally detected liver pathology covering all pediatric ages. It aims to aid the examiner in establishing the final diagnosis. Management of incidentally detected focal liver lesions (FLL) needs to take into account the diagnostic accuracy of each imaging modality, the patient's safety issues (including ionizing radiation and nephrotoxic contrast agents), the delay in diagnosis, the psychological burden on the patient and the cost for the healthcare system. Moreover, this paper should help the pediatric clinician and ultrasound practitioner to decide which pathologies need no further investigation, which ones require interval imaging and which cases require further and immediate diagnostic procedures.

High frame-rate contrast enhanced ultrasound (HIFR-CEUS) in the characterization of small hepatic lesions in cirrhotic patients

BACKGROUND

To show the effectiveness of plane wave HighFrame-Rate CEUS (HiFR-CEUS) compared with "conventional" (plane wave) CEUS (C-CEUS) in the characterization of small (< 2 cm) focal liver lesions (FLLs) not easily detected by CT in cirrhotic patients. HiFR-CEUS exploit an ultra-wideband nonlinear process to combine fundamental, second and higher-order harmonic signals generated by ultrasound contrast agents to increase the frame rate. C-CEUS is limited by the transmission principle, and its frame-rate is around 10 FPS. With HiFR-CEUS (Shenzhen Mindray Bio-Medical Electronics Co., China), the frame-rate reached 60 FPS.

MATERIAL AND METHODS

Ultrasound detected small FLLs (< 2 cm) in 63 cirrhotic patients during follow-up (June 2019-February 2020); (7 nodules < 1 cm and were not evaluable by spiral CT). Final diagnosis was obtained with MRI (47) or fine needle aspiration (16 cases) C-CEUS was performed and HiFR-CEUS was repeated after 5 min; 0.8-1.2 ml of contrast media (SonoVue, Bracco, Italy) was used. 57 nodules were better evaluable with HiFR-CEUS; 6 nodules were equally evaluable by both techniques; final diagnosis was: 44 benign lesions (29 hemangiomas, 1 amartoma, 2 hepatic cysts; 2 focal nodular hyperplasias, 3 regenerative macronodules, 3 AV-shunts, 3 hepatic sparing areas and 1 focal steatosis) and 19 malignant one (17 HCCs, 1 cholangioca, 1 metastasis); statistical evaluation for better diagnosis with X2 test (SPSS vers. 26); we used LI-RADS classification for evaluating sensitivity, specificity PPV, NPV and diagnostic accuracy of C- and HFR-CEUS. Corrispective AU-ROC were calculated.

RESULTS

C-CEUS and HiFR-CEUS reached the same diagnosis in 29 nodules (13 nodules > 1 < 1.5 cm; 16 nodules > 1.5 < 2 cm); HiFR-CEUS reached a correct diagnosis in 32 nodules where C-CEUS was not diagnostic (6 nodules < 1 cm; 17 nodules > 1 < 1.5 cm; 9 nodules > 1.5 < 2 cm); C-CEUS was better in 2 nodules (1 < 1 cm and 1 > 1 < 1.5 cm). Some patient's (sex, BMI, age) and nodule's characteristics (liver segment, type of diagnosis, nodule's dimensions (p = 0.65)) were not correlated with better diagnosis (p ns); only better visualization (p 0.004) was correlated; C-CEUS obtained the following LI-RADS: type-1: 18 Nodules, type-2: 21; type-3: 7, type-4: 7; type-5: 8; type-M: 2; HiFR-CEUS: type-1: 38 Nodules, type-2: 2; type-3:4, type-4: 2; type-5: 15; type-M: 2; In comparison with final diagnosis: C-CEUS: TP: 17; TN: 39; FP: 5; FN:2; HIFR-CEUS: TP: 18; TN: 41; FP: 3; FN:1; C-CEUS: sens: 89.5%; Spec: 88.6%, PPV: 77.3%; NPV: 95.1%; Diagn Acc: 88.6% (AU-ROC: 0.994 ± SEAUC: 0.127; CI: 0.969-1.019); HiHFR CEUS: sens: 94.7%; Spec: 93.2%, PPV: 85.7%; NPV: 97.6%; Diagn Acc: 93.2% (AU-ROC: 0.9958 ± SEAUC: 0.106; CI: 0.975-1.017) FLL vascularization in the arterial phase was more visible with HiFR-CEUS than with C-CEUS, capturing the perfusion details in the arterial phase due to a better temporal resolution. With a better temporal resolution, the late phase could be evaluated longer with HiFR-CEUS (4 min C-CEUS vs. 5 min HiFR-CEUS).

CONCLUSION

Both C-CEUS and HIFR-CEUS are good non invasive imaging system for the characterization of small lesions detected during follow up of cirrhotic patients. HiFR-CEUS allowed better FLL characterization in cirrhotic patients with better temporal and spatial resolution capturing the perfusion details that cannot be easily observed with C-CEUS.

Small Study Effects in Diagnostic Imaging Accuracy: A Meta-Analysis

IMPORTANCE

Small study effects are the phenomena that studies with smaller sample sizes tend to report larger and more favorable effect estimates than studies with larger sample sizes.

OBJECTIVE

To evaluate the presence and extent of small study effects in diagnostic imaging accuracy meta-analyses.

DATA SOURCES

A search was conducted in the PubMed database for diagnostic imaging accuracy meta-analyses published between 2010 and 2019.

STUDY SELECTION

Meta-analyses with 10 or more studies of medical imaging diagnostic accuracy, assessing a single imaging modality, and providing 2 × 2 contingency data were included. Studies that did not assess diagnostic accuracy of medical imaging techniques, compared 2 or more imaging modalities or different methods of 1 imaging modality, were cost analyses, used predictive or prognostic tests, did not provide individual patient data, or were network meta-analyses were excluded.

DATA EXTRACTION AND SYNTHESIS

Data extraction was performed in accordance with the PRISMA guidelines.

MAIN OUTCOMES AND MEASURES

The diagnostic odds ratio (DOR) was calculated for each primary study using 2 × 2 contingency data. Regression analysis was used to examine the association between effect size estimate and precision across meta-analyses.

RESULTS

A total of 31 meta-analyses involving 668 primary studies and 80 206 patients were included. Fixed effects analysis produced a regression coefficient for the natural log of DOR against the SE of the natural log of DOR of 2.19 (95% CI, 1.49-2.90; P < .001), with computed tomography as the reference modality. Interaction test for modality and SE of the natural log of DOR did not depend on modality (Wald statistic P = .50). Taken together, this analysis found an inverse association between effect size estimate and precision that was independent of imaging modality. Of 26 meta-analyses that formally assessed for publication bias using funnel plots and statistical tests for funnel plot asymmetry, 21 found no evidence for such bias.

CONCLUSIONS AND RELEVANCE

This meta-analysis found evidence of widespread prevalence of small study effects in the diagnostic imaging accuracy literature. One likely contributor to the observed effects is publication bias, which can undermine the results of many meta-analyses. Conventional methods for detecting funnel plot asymmetry conducted by included studies appeared to underestimate the presence of small study effects. Further studies are required to elucidate the various factors that contribute to small study effects.

Interindividual Comparison of Frequency-Selective Nonlinear Blending to Conventional CT for Detection of Focal Liver Lesions Using MRI as the Reference Standard

BACKGROUND. Diagnosing liver lesions is challenging. CT is used for primary diagnosis, but its contrast resolution is limited. Investigating methods to improve detection of liver lesions is important. OBJECTIVE. The purpose of this study was to evaluate the effect of frequency-selective nonlinear blending on the detectability of liver lesions on CT. METHODS. A retrospective search yielded 109 patients with 356 malignant and benign liver lesions (191 principally diagnosed, 165 incidental findings) who underwent contrast-enhanced CT (CECT) in the portal venous phase and liver MRI between January 2012 and December 2017. Nonlinear blending was applied to CECT examinations, and three blinded readers independently rated the quality (5-point Likert scale) of randomly presented images. Focal lesions (n = 356) were evaluated for lesion identification and categorization to assess sensitivity. For 191 lesions (primary diagnosis), two readers evaluated CECT and nonlinear blending CT to compare lesion size and the accuracy of subjective measurements. A fourth reader performed ROI measurements for calculation of contrast-to-noise ratio (CNR), and a fifth reader reviewed MRI as the standard of reference. Statistics included interobserver agreement, quantitative comparisons of CNR, lesion size, and subjective image analyses of image quality and sensitivity for detecting liver lesions. RESULTS. Three readers rated the image quality of nonlinear blending CT (rating, 4; 10th-90th percentiles, 4-5) higher than that of CECT (rating, 2; 10th-90th percentiles, 1-3) (p < .001). CECT had good interreader agreement (interclass correlation coefficient [ICC], 0.81; 95% CI, 0.76-0.85), as did nonlinear blending CT (ICC, 0.75; 95% CI, 0.69-0.79). The median CNR of liver lesions increased with nonlinear blending (CECT, 4.18 [10th-90th percentiles, 1.67-9.06]; nonlinear blending CT, 12.49 [10th-90th percentiles, 6.18-23.39]; p < .001). Bland-Altman analysis of lesion size showed a reduction in underestimation from 2.5 (SD, 9.2) mm (95% CI, 1.2-3.9 mm) with CECT to 0.1 (SD, 3.9) mm (95% CI, -0.68 to 0.46 mm) for nonlinear blending CT (concordance correlation coefficient, 0.99). Sensitivity for detecting liver lesions increased to 86% for nonlinear blending CT. The sensitivity of CECT was 76%. CONCLUSION. Frequency-selective nonlinear blending in CECT increases image quality and CNR, increases the precision of size measurement, and increases sensitivity for detecting liver lesions. CLINICAL IMPACT. Use of nonlinear blending CT improves liver lesion detection and increases the accuracy of lesion size measurement, which is important when local ablation or liver transplant is being considered.

Deep learning radiomics for focal liver lesions diagnosis on long-range contrast-enhanced ultrasound and clinical factors

BACKGROUND

Routine clinical factors play an important role in the clinical diagnosis of focal liver lesions (FLLs); however, they are rarely used in computer-assisted diagnosis. Therefore, we developed a deep learning (DL) radiomics model, and investigated its effectiveness in diagnosing FLLs using long-range contrast-enhanced ultrasound (CEUS) cines and clinical factors.

METHODS

Herein, 303 patients with pathologically confirmed FLLs after surgery at three hospitals were retrospectively enrolled and divided into a training cohort (n=203), internal validation (IV) cohort (n=50) from one hospital with the ratio of 4:1, and external validation (EV) cohort (n=50) from the other two hospitals. Four DL radiomics models, namely Four Stream 3D convolutional neural network (FS3DU) (trained with CEUS cines only), FS3DU+A (trained with CEUS cines and alpha fetoprotein), FS3DU+H (trained with CEUS cines and hepatitis), and FS3DU+A+H (trained with CEUS cines, alpha fetoprotein, and hepatitis), were formed based on 3D convolutional neural networks (CNNs). They used approximately 20-s preoperative CEUS cines and/or clinical factors to extract spatiotemporal features for the classification of FLLs and the location of the region of interest. The area under curve of the receiver operating characteristic and diagnosis speed were calculated to evaluate the models in the IV and EV cohorts, and they were compared with those of two radiologists. Two-sided Delong tests were used to calculate the statistical differences between the models and radiologists.

RESULTS

FS3DU+A+H, which incorporated CEUS cines, hepatitis, and alpha fetoprotein, achieved the highest area under curve of 0.969 (95% CI: 0.901-1.000) and 0.957 (95% CI: 0.894-1.000) among radiologists and other models in IV and EV cohorts, respectively. A significant difference was observed when comparing FS3DU and radiologist 2 (all P<0.05). The diagnosis speed of all the models was the same (10.76 s per patient), and it was two times faster than those of the radiologists (radiologist 1: 23.74 and 27.75 s; radiologist 2: 25.95 and 29.50 s in IV and EV cohorts, respectively).

CONCLUSIONS

The proposed DL radiomics demonstrated excellent performance on the benign and malignant diagnosis of FLLs by combining CEUS cines and clinical factors. It could help the individualized characterization of FLLs, and enhance the accuracy of diagnosis in the future.

Interpretable Machine Learning for Characterization of Focal Liver Lesions by Contrast-Enhanced Ultrasound

This work proposes an interpretable radiomics approach to differentiate between malignant and benign focal liver lesions (FLLs) on contrast-enhanced ultrasound (CEUS). Although CEUS has shown promise for differential FLLs diagnosis, current clinical assessment is performed only by qualitative analysis of the contrast enhancement patterns. Quantitative analysis is often hampered by the unavoidable presence of motion artifacts and by the complex, spatiotemporal nature of liver contrast enhancement, consisting of multiple, overlapping vascular phases. To fully exploit the wealth of information in CEUS, while coping with these challenges, here we propose combining features extracted by the temporal and spatiotemporal analysis in the arterial phase enhancement with spatial features extracted by texture analysis at different time points. Using the extracted features as input, several machine learning classifiers are optimized to achieve semiautomatic FLLs characterization, for which there is no need for motion compensation and the only manual input required is the location of a suspicious lesion. Clinical validation on 87 FLLs from 72 patients at risk for hepatocellular carcinoma (HCC) showed promising performance, achieving a balanced accuracy of 0.84 in the distinction between benign and malignant lesions. Analysis of feature relevance demonstrates that a combination of spatiotemporal and texture features is needed to achieve the best performance. Interpretation of the most relevant features suggests that aspects related to microvascular perfusion and the microvascular architecture, together with the spatial enhancement characteristics at wash-in and peak enhancement, are important to aid the accurate characterization of FLLs.

High Frame Rate Contrast-enhanced Ultrasound Helps Differentiate Malignant and Benign Focal Liver Lesions

BACKGROUND AND AIMS

This study aimed to evaluate the diagnostic performance of high frame rate contrast-enhanced ultrasound (H-CEUS) of focal liver lesions (FLLs).

METHODS

From July 2017 to June 2019, conventional contrast-enhanced ultrasound (C-CEUS) and H-CEUS were performed in 78 patients with 78 nodules. The characteristics of C-CEUS and H-CEUS in malignant and benign groups and the differences between different lesion sizes (1-3 cm, 3-5 cm, or >5 cm) of C-CEUS and H-CEUS were examined. The diagnostic performance of C-CEUS and H-CEUS was analyzed. The chi-square test or Fisher's exact test was used to assess inter-group differences. The receiver operating characteristic curve was plotted to determine the diagnostic performance of C-CEUS and H-CEUS.

RESULTS

There were significant differences in the enhancement area, fill-in direction and vascular architecture between C-CEUS and H-CEUS for both benign and malignant lesions (all p=0.000-0.008), but there were no significant differences in washout results (p=0.566 and p=0.684, respectively). For lesions 1-3 cm in size, the enhancement area, fill-in direction, and vascular architecture on C-CEUS and H-CEUS were significantly different (all p=0.000), unlike for lesions 3-5 cm or >5 cm in size. For differentiation of malignant from benign FLLs in the 1-3 cm group, H-CEUS showed sensitivity, specificity, accuracy, and positive and negative predictive values of 92.86%, 95.0%, 96.3%, 90.48% and 93.75%, respectively, which were higher than those for C-CEUS (75.0%, 70.0%, 77.78%, 66.67% and 72.91%, respectively).

CONCLUSIONS

H-CEUS provided more vascular information which could help differentiate malignant from benign FLLs, especially for lesions 1-3 cm in size.

A Dual-modal Imaging Method Combining Ultrasound and Electromagnetism for Simultaneous Measurement of Tissue Elasticity and Electrical Conductivity

The mechanical and electrical properties of soft tissues are relative to soft tissues' pathological state. Modern medical imaging devices have shown a trend to multi-modal imaging, which will provide complementary functional information to improve the accuracy of disease diagnosis. However, no method or system can simultaneously measure the mechanical and electrical properties of the soft tissue. In this study, we proposed a novel dual-modal imaging method integrated by shear wave elasticity imaging (SWEI) and Magneto-acousto-electrical tomography (MAET) to measure soft tissue's elasticity and conductivity simultaneously. A dual-modal imaging system based on a linear array transducer is built, and the imaging performances of MAET and SWEI were respectively evaluated by phantoms experiment and \textit{in vitro} experiment. Conductivity phantom experiments show that the MAET in this dual-modal system can image conductivity gradient as low as 0.4 S/m. The phantom experiments show that the reconstructed 2-D elasticity maps of the phantoms with inclusions with a diameter larger than 5 mm are relatively accurate. \textit{In vitro} experiments show that the elasticity parameter can significantly distinguish the changes in tissue before and after heating. This study first proposes a method that can simultaneously obtain tissue elasticity and electrical conductivity to the best of our knowledge. Although this paper just carried out the proof of concept experiments of the new method, it demonstrates great potential for disease diagnosis in the future.

New frontiers in liver ultrasound: From mono to multi parametricity

Modern liver ultrasonography (US) has become a "one-stop shop" able to provide not only anatomic and morphologic but also functional information about vascularity, stiffness and other various liver tissue properties. Modern US techniques allow a quantitative assessment of various liver diseases. US scanning is no more limited to the visualized plane, but three-dimensional, volumetric acquisition and consequent post-processing are also possible. Further, US scan can be consistently merged and visualized in real time with Computed Tomography and Magnetic Resonance Imaging examinations. Effective and safe microbubble-based contrast agents allow a real time, dynamic study of contrast kinetic for the detection and characterization of focal liver lesions. Ultrasound can be used to guide loco-regional treatment of liver malignancies and to assess tumoral response either to interventional procedures or medical therapies. Microbubbles may also carry and deliver drugs under ultrasound exposure. US plays a crucial role in diagnosing, treating and monitoring focal and diffuse liver disease. On the basis of personal experience and literature data, this paper is aimed to review the main topics involving recent advances in the field of liver ultrasound.

Comparison Between SonoVue and Sonazoid Contrast-Enhanced Ultrasound in Characterization of Focal Nodular Hyperplasia Smaller Than 3 cm

OBJECTIVES

This study aimed to compare the diagnostic efficacy of contrast-enhanced ultrasound (CEUS), including SonoVue (SV; sulfur hexafluoride; Bracco SpA, Milan, Italy) and Sonazoid (SZ; perflubutane; GE Healthcare, Oslo, Norway), and explore the differences between them in the characterization of CEUS features in focal nodular hyperplasia (FNH) smaller than 3 cm.

METHODS

This retrospective study included 31 lesions smaller than 3 cm diagnosed as FNH by CEUS between April 2019 and November 2019. Nine patients underwent SZ CEUS examinations, and 22 patients underwent SV CEUS examinations; all of them were confirmed by pathologic examinations or 2 other kinds of CEUS methods. We compared the CEUS features between SZ and SV in different phases, including arterial, portal venous, delayed, and Kupffer (SZ) phases.

RESULTS

Twenty-eight lesions were eventually diagnosed as FNH; 3 were misdiagnosed as FNH by SV CEUS. The overall diagnostic accuracy of CEUS including SZ and SV was 90.3% (28 of 31). No significant difference was found (P > .05) for the positive predictive value. Likewise, no significant difference in depicting centrifugal filling (9 of 9 versus 19 of 19), spoke wheel artery (6 of 9 versus 8 of 19), or feeding artery (2 of 9 versus 10 of 19) features was found between the contrast agents; However, SZ was significantly better at depicting the presence of a central scar than SV (5 of 9 versus 3 of 19; P = .030). Misdiagnosed cases are discussed in detail.

CONCLUSIONS

Contrast-enhanced ultrasound enables an accurate diagnosis in FNH smaller than 3 cm. Sonazoid CEUS and SV CEUS were comparable in diagnosing small FNH, and both agents were highly capable of depicting the centrifugal filling dynamic process of FNH smaller than 3 cm. Sonazoid CEUS might be better than SV CEUS at depicting a central scar.

Perfluorobutane contrast-enhanced ultrasonography for the diagnosis of HCC: a systematic review and meta-analysis

OBJECTIVES

Perfluorobutane ultrasound contrast agent as a new type of contrast agent has a good performance in the diagnosis of hepatocellular carcinoma (HCC). This study aim to evaluate the accuracy and reliability of Perfluorobutane contrast-enhanced ultrasonography (P-CEUS) in the diagnosis of HCC with a systematic review and meta-analysis.

METHODS

Web of Science, EMBASE, Cochrane, Clinical Key, Wan Fang, CBM and CNKI databases were systematically searched and checked for studies using P-CEUS in HCC, from 2007 to 2020. 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

Nine studies were included in this meta-analysis and the overall diagnostic accuracy in characterization of HCC was as follows: pooled sensitivity, 0.90 (95% confidence interval: 0.82-0.95); pooled specificity, 0.97 (0.93-0.98); pooled positive likelihood ratio, 27.2 (14.1 to - 52.3); and pooled negative likelihood ratio, 0.10 (0.06-0.18). The area under the comprehensive receiving operation characteristic curve was 0.98 (0.97-0.99).

CONCLUSION

The sensitivity and specificity of P-CEUS are more valuable than other imaging techniques (such as computer tomography or magnetic resonance imaging). However, due to the large differences in the data samples collected in this study, statistical heterogeneity results. P-CEUS can significantly improve the diagnostic efficiency of previous contrast-enhanced ultrasound for HCC. PROSPERO registration number: PROSPERO (CRD42020200040).

Contrast-enhanced ultrasound for screening hepatocellular carcinoma: an implemented program at a semi-rural academic center

Purpose

To describe our early experience using a contrast-enhanced ultrasound (CEUS) protocol for surveillance of hepatocellular carcinoma (HCC) at a semi-rural academic medical center.

Methods

Retrospective, longitudinal study of the first 100 patients who underwent CEUS liver screening imaging over 2 years. Each patient underwent a standard of care abdominal ultrasound, which was checked with the radiologist, who searched for a focal lesion on the cine clips to target specifically with contrast. If none was present, the HCC contrast-enhanced screening protocol consisting of individual sweeps of the right and left lobes was performed from 0 to 60 s and 3–4 min post contrast—Lumason was utilized. Images, report details, and patient demographics were analyzed.

Results

66 men and 34 women (average age, 59 ± 13 years) were included. On average, the distance from patient’s home to our institution was 39 miles (range 2–179 miles). The majority of our patients were covered under Private insurance (46%) with 43% covered by Medicare. CEUS exams on average took 35 min to complete. Lumason was administered in split doses for an average total of 5 mL per exam. Of the 10 lesions identified, there were five LI-RADS 3, two LI-RADS 4, one LI-RADS 5, two LI-RADS M, and one bland portal vein thrombus. There were no complications reported.

Conclusion

This semi-rural single-center study demonstrates the feasibility of starting a HCC CEUS screening program. CEUS can be performed in conjunction with routine ultrasound imaging with added benefit of identifying and characterizing lesions in one setting.

Complementary imaging of ultrasound and PET/CT: A new opportunity?

AIM

To evaluate the effectiveness of complementary imaging of high-resolution ultrasound including CEUS with PET/CT for tissue characterization and tumor detection.

MATERIAL AND METHODS

100 patients were examined with PET/CT and US/CEUS between January 2018 until February 2020. All patients underwent PET/CT followed by selective US/CEUS within 4 weeks. Comparison regarding concordant or diverging findings in PET/CT and US. Analysis of the differences concerning the lesions number of found by PET/CT and US/CEUS or the possibility of a secured diagnosis following ultrasound causing therapeutic changes.

RESULTS

Diverging findings regarding the number of liver lesions in PET/CT and CEUS were found in 35 out of 64 patients (54%). Regarding renal lesions, a more definite diagnosis following ultrasound, causing a change of therapeutic approach, was achieved in 89%. Concordant results in PET/CT and US were found in 83% of patients with splenic and nodal findings. In 78% of patients with increased musculoskeletal or soft tissue tracer uptake, US was able to make a secured diagnosis with therapeutic changes.

CONCLUSION

The present results indicate a strong benefit of complementary imaging of PET/CT and selective, high-resolution ultrasound especially in patients with liver, renal and musculoskeletal or soft tissue findings.

Preoperative classification of primary and metastatic liver cancer via machine learning-based ultrasound radiomics

OBJECTIVE

To investigate the application of machine learning-based ultrasound radiomics in preoperative classification of primary and metastatic liver cancer.

METHODS

Data of 114 consecutive histopathologically confirmed patients with liver cancer from January 2018 to November 2019 were retrospectively analyzed. All patients underwent liver ultrasonography within 1 week before hepatectomy or fine-needle biopsy. The liver lesions were manually segmented by two experts using ITK-SNAP software. Seven categories of radiomics features, including first-order, two-dimensional shape, gray-level co-occurrence matrices, gray-level run-length matrix, gray-level size-zone matrix, neighboring gray tone difference matrix, and gray-level dependence matrix, were extracted on the Pyradiomics platform. Fourteen filters were applied to the original images, and derived images were obtained. Then, the dimensions of radiomics features were reduced by least absolute shrinkage and selection operator (Lasso) method. Finally, k-nearest neighbor (KNN), logistic regression (LR), multilayer perceptron (MLP), random forest (RF), and support vector machine (SVM) were employed to distinguish primary liver cancer from metastatic liver cancer by a fivefold cross-validation strategy. The performance of the established model was mainly evaluated by the area under the receiver operating characteristic (ROC) curve (AUC) and accuracy.

RESULTS

One thousand four hundred nine radiomics features were extracted from the original images and/or derived images for each patient. The mentioned five machine learning classifiers were able to differentiate primary liver cancer from metastatic liver cancer. LR outperformed other classifiers, with the accuracy of 0.843 ± 0.078 (AUC, 0.816 ± 0.088; sensitivity, 0.768 ± 0.232; specificity, 0.880 ± 0.117).

CONCLUSIONS

Machine learning-based ultrasound radiomics features are able to non-invasively distinguish primary liver tumors from metastatic liver tumors.

KEY POINTS

• Ultrasound-based radiomics was initially used for preoperative classification of primary versus metastatic liver cancer. • Multiple machine learning-based algorithms with cross-validation strategy were applied to extract machine learning-based ultrasound radiomics features. • Distinction between primary and metastatic tumors was obtained with a sensitivity of 0.768 and a specificity of 0.880.

Contrast-enhanced ultrasound in the diagnosis of infiltrative hepatocellular carcinoma: A report of three cases

Infiltrative hepatocellular carcinoma (HCC) is a challenging imaging diagnosis due to its ill-defined appearance and variable enhancement, which may be difficult to distinguish from background changes from cirrhosis. The literature on the role of contrast-enhanced ultrasound (CEUS) in the diagnosis of infiltrative HCC is currently limited. CEUS has greater sensitivity for contrast enhancement due to its temporal resolution, and can be used when there is contraindication to CT or MRI contrast. We present 3 cases where CEUS aided in the diagnosis of infiltrative HCC in patients with equivocal CT and MRI findings and/or renal failure, with significant implications for management. As current guidelines focus on the role of CEUS in characterizing defined focal liver lesions or discrete observations on precontrast US, further studies are warranted to validate the utility of CEUS in the noninvasive diagnosis of infiltrative HCC and delineate its role in algorithms for imaging workup.

Performance of Ultrasound Techniques and the Potential of Artificial Intelligence in the Evaluation of Hepatocellular Carcinoma and Non-Alcoholic Fatty Liver Disease

Global statistics show an increasing percentage of patients that develop non-alcoholic fatty liver disease (NAFLD) and NAFLD-related hepatocellular carcinoma (HCC), even in the absence of cirrhosis. In the present review, we analyzed the diagnostic performance of ultrasonography (US) in the non-invasive evaluation of NAFLD and NAFLD-related HCC, as well as possibilities of optimizing US diagnosis with the help of artificial intelligence (AI) assistance. To date, US is the first-line examination recommended in the screening of patients with clinical suspicion of NAFLD, as it is readily available and leads to a better disease-specific surveillance. However, the conventional US presents limitations that significantly hamper its applicability in quantifying NAFLD and accurately characterizing a given focal liver lesion (FLL). Ultrasound contrast agents (UCAs) are an essential add-on to the conventional B-mode US and to the Doppler US that further empower this method, allowing the evaluation of the enhancement properties and the vascular architecture of FLLs, in comparison to the background parenchyma. The current paper also explores the new universe of AI and the various implications of deep learning algorithms in the evaluation of NAFLD and NAFLD-related HCC through US methods, concluding that it could potentially be a game changer for patient care.

Contrast-enhanced ultrasound of benign and malignant liver lesions in children

Contrast-enhanced ultrasound (CEUS) is increasingly being used in children. One of the most common referrals for CEUS performance is characterization of indeterminate focal liver lesions and follow-up of known liver lesions. In this setting, CEUS is performed with intravenous administration of ultrasound contrast agents (UCAs). When injected into a vein, UCA microbubbles remain confined within the vascular network until they dissipate. Therefore, visualization of UCA within the tissues and lesions corresponds to true blood flow. CEUS enables continuous, real-time observation of the enhancement pattern of a focal liver lesion, allowing in most cases for a definite diagnosis and obviating the need for further cross-sectional imaging or other interventional procedures. The recent approval of Lumason (Bracco Diagnostics, Monroe Township, NJ) for pediatric liver CEUS applications has spurred the widespread use of CEUS. In this review article we describe the role of CEUS in pediatric liver applications, focusing on the examination technique and interpretation of main imaging findings of the most commonly encountered benign and malignant focal liver lesions. We also compare the diagnostic performance of CEUS with other imaging modalities for accurate characterization of focal liver lesions.

Interobserver agreement for contrast-enhanced ultrasound of liver imaging reporting and data system: A systematic review and meta-analysis

BACKGROUND

Hepatocellular carcinoma is the most common primary liver malignancy. From the results of previous studies, Liver Imaging Reporting and Data System (LI-RADS) on contrast-enhanced ultrasound (CEUS) has shown satisfactory diagnostic value. However, a unified conclusion on the interobserver stability of this innovative ultrasound imaging has not been determined. The present meta-analysis examined the interobserver agreement of CEUS LI-RADS to provide some reference for subsequent related research.

AIM

To evaluate the interobserver agreement of LI-RADS on CEUS and analyze the sources of heterogeneity between studies.

METHODS

Relevant papers on the subject of interobserver agreement on CEUS LI-RADS published before March 1, 2020 in China and other countries were analyzed. The studies were filtered, and the diagnostic criteria were evaluated. The selected references were analyzed using the "meta" and "metafor" packages of R software version 3.6.2.

RESULTS

Eight studies were ultimately included in the present analysis. Meta-analysis results revealed that the summary Kappa value of included studies was 0.76 [95% confidence interval, 0.67-0.83], which shows substantial agreement. Higgins I 2 statistics also confirmed the substantial heterogeneity (I 2 = 91.30%, 95% confidence interval, 85.3%-94.9%, P < 0.01). Meta-regression identified the variables, including the method of patient enrollment, method of consistency testing, and patient race, which explained the substantial study heterogeneity.

CONCLUSION

CEUS LI-RADS demonstrated overall substantial interobserver agreement, but heterogeneous results between studies were also obvious. Further clinical investigations should consider a modified recommendation about the experimental design.

Contrast-Enhanced Ultrasound for Focal Hepatic Lesions: When to Use and How to Differentiate Lesions?

Contrast-enhanced ultrasound can be used effectively to evaluate focal hepatic lesions and offers unique advantages over computed tomography and magnetic resonance imaging. Serial vascular filling patterns of focal hepatic lesions during arterial, portal, and late phases can provide unique information on lesion characterization and differentiation. Sensitive depiction of arterial hypervascularity and analysis of washout pattern are clues for differentiation of several indeterminate hepatic nodules on conventional ultrasound and computed tomography/magnetic resonance. In this report, we present cases demonstrating clinical applications of contrast-enhanced ultrasound in the diagnosis and management of focal hepatic lesions.

Diagnostic Value of High Frame Rate Contrast-enhanced Ultrasonography and Post-processing Contrast Vector Imaging for Evaluation of Focal Liver Lesions: A Feasibility Study

This study evaluated the feasibility of contrast vector imaging (CVI) to characterize focal liver lesions. From July to October 2019, we prospectively enrolled 30 patients with focal liver lesions (hepatocellular carcinoma [HCC] [n = 19], metastasis [n = 8], combined HCC-cholangiocarcinoma [CC] [n = 1], intra-hepatic CC [n = 1] and sclerosed hemangioma [n = 1]). Contrast-enhanced ultrasound (CEUS) was performed with high frame rate contrast harmonic imaging technique by one radiologist, and post-processing CVI was obtained and analyzed by two radiologists. On combined CVI with CEUS, the staining pattern was significantly predominant in HCCs (9/11, 81.8%), while peripheral rim was frequent in non-HCCs (5/8, 62.5%) (p = 0.020). HCCs exhibited feeding arteries (8/11, 45.5%) and high velocity variance (10/11, 90.9 %), whereas non-HCCs showed detour pattern (4/8, 50.0%) with either a high or low velocity variance (4/8, 50.0%, both), with no significant inter-group differences (p = 0.052 and 0.080, respectively). In conclusion, CVI was feasible and provided quantitative and multi-parametric information of different types of hepatic tumors.

A Pilot Study on Efficacy of Lipid Bubbles for Theranostics in Dogs with Tumors

The combined administration of microbubbles and ultrasound (US) is a promising strategy for theranostics, i.e., a combination of therapeutics and diagnostics. Lipid bubbles (LBs), which are experimental theranostic microbubbles, have demonstrated efficacy in vitro and in vivo for both contrast imaging and drug delivery in combination with US irradiation. To evaluate the clinical efficacy of LBs in combination with US in large animals, we performed a series of experiments, including clinical studies in dogs. First, contrast-enhanced ultrasonography using LBs (LB-CEUS) was performed on the livers of six healthy Beagles. The hepatic portal vein and liver tissue were enhanced; no adverse reactions were observed. Second, LB-CEUS was applied clinically to 21 dogs with focal liver lesions. The sensitivity and specificity were 100.0% and 83.3%, respectively. These results suggested that LB-CEUS could be used safely for diagnosis, with high accuracy. Finally, LBs were administered in combination with therapeutic US to three dogs with an anatomically unresectable solid tumor in the perianal and cervical region to determine the enhancement of the chemotherapeutic effect of liposomal doxorubicin; a notable reduction in tumor volume was observed. These findings indicate that LBs have potential for both therapeutic and diagnostic applications in dogs in combination with US irradiation.

Hepatic tumors: pitfall in diagnostic imaging

On computed tomography (CT) and magnetic resonance imaging (MRI), hepatocellular tumors are characterized based on typical imaging findings. However, hepatocellular adenoma, focal nodular hyperplasia, and hepatocellular carcinoma can show uncommon appearances at CT and MRI, which may lead to diagnostic challenges. When assessing focal hepatic lesions, radiologists need to be aware of these atypical imaging findings to avoid misdiagnoses that can alter the management plan. The purpose of this review is to illustrate a variety of pitfalls and atypical features of hepatocellular tumors that can lead to misinterpretations providing specific clues to the correct diagnoses.

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non-invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/CT), advanced MRI, optical or ultrasound imaging.This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and, then point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now.Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by advances in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as "data", and - through the wider adoption of advanced analysis, including machine learning approaches and a "big data" concept - move to the next stage of non-invasive tumour phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi-dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging.

Non-invasive diagnosis of liver fibrosis: A review of current imaging modalities

Hundreds of millions of patients are suffering from cirrhosis and other chronic liver diseases worldwide, and this public health problem continues to grow. It has been proven that liver fibrosis is reversible after the elimination of the etiology, especially in the early stage. Thus, early diagnosis of liver fibrosis is of vital importance for clinical treatment. Liver biopsy remains the gold standard for both diagnosis and staging of fibrosis, but is suboptimal, due in large parts to its invasive nature and sundry associated complications. To overcome this, a number of non-invasive diagnosis based on serum biomarkers or imaging modalities have been developed. While diagnosis based on serum biomarkers is cheaper and more acceptable to patients, almost none developed to date are liver-specific, and may engender a false positive error. The imaging modalities have evolved rapidly and are taking on more and more important roles in the diagnosis of liver fibrosis.

CEUS LI-RADS: a pictorial review

Contrast-enhanced ultrasound (CEUS) greatly improved the diagnostic accuracy of US in the detection and characterization of focal liver lesions (FLLs), and it is suggested and often included in many international guidelines as an important diagnostic tool in the imaging work-up of cirrhotic patients at risk for developing hepatocellular carcinoma (HCC). In particular, CEUS Liver Imaging Reporting and Data System (LI-RADS) provides standardized terminology, interpretation, and reporting for the diagnosis of HCC. The aim of this pictorial essay is to illustrate CEUS features of nodules discovered at US in cirrhotic liver according to LI-RADS categorization.

Application of new ultrasound techniques for focal liver lesions

Ultrasonography (US) has the overwhelming advantages of not entailing radiation exposure and being a noninvasive, real-time, convenient, easy-to-perform, and relatively inexpensive imaging modality. It is used as the first-line imaging modality for screening, detection, and diagnosis of focal liver lesions (FLLs) [small hepatocellular carcinomas (HCCs), in particular]. However, with the increasing demand for accurate and early diagnosis of small HCCs, newer radiologic methods need to be explored to overcome certain limitations of US. For example, the imaging is easily negatively affected by the presence of gas, rib cage, and subcutaneous fat, and is insensitive for capturing the subtle but vital information on the blood flow. It was in response to this need that new promising technologies such as contrast-enhanced ultrasound and fusion imaging were introduced for the detection of liver lesions. This paper presents an overview of the epidemiology and mechanisms of the development of HCCs, with an emphasis on the application of US in the diagnosis and treatment of FLLs. The aim of this article is to provide the state-of-the-art developments in the imaging diagnosis of FLLs and evaluation of ablation treatment of early HCCs. By keeping abreast of these recent advances, we hope that doctors and researchers working in the field of diagnosis/treatment of liver diseases will be able to discriminate benign FLLs such as regenerative nodules and focal nodular hyperplasia from HCCs, so as to avoid unnecessary repeated tumor biopsies and overtreatment. In particular, we expect that small HCCs or precancerous nodules (such as dysplastic nodules) can be accurately diagnosed and appropriately treated even at an early stage.

[Sonographic diagnostics of liver tumors]

Liver tumors are often incidentally found during ultrasound examinations. The decision on further diagnostic imaging depends on the clinical context and the appearance in B mode ultrasound. This review highlights the role of grey scale and contrast-enhanced ultrasound (CEUS) and summarizes the ultrasonographic key features of the most common benign and malignant liver tumors. Conventional grey scale ultrasound is recommended in several guidelines for screening and follow-up of liver tumors in certain risk populations but its ability to characterize liver tumors is limited in most cases. The CEUS has an excellent tolerability and enables liver tumor characterization with a high sensitivity and specificity. The diagnostic value of CEUS is comparable to magnetic resonance imaging. In the case of unclear lesions, inconclusive findings by different imaging methods or if molecular targeted treatment is pursued, ultrasound-guided biopsy is often mandatory. Ultrasound is a rapidly and ubiquitously available method for the detection of liver tumors and CEUS is the only imaging method that enables real-time examination of all contrast phases in the liver. It should therefore be used as the first line imaging method for liver tumor characterization.

Tumor-specific design of PEGylated gadolinium-based nanoscale particles: Facile synthesis, characterization, and improved magnetic resonance imaging of metastasis lung cancer

Herein we report the synthesis and characterization of the antifouling Gadolinium oxide (Gd₂O₃) nanoparticles (NPs) modified with PEG with improved biocompatibility for MR imaging purposes. In this report, using the solvothermal decomposition of Gadolinium (III) in the presence of Na₃cit, monitored by surface modification with PEG and L-Cys. The synthesized nanoparticles were confirmed by the TEM, DLS and UV-Visible spectroscopy. The morphological results show normal distance across of the flawless Gd₂O₃-PEG-Cys-NPs show 7.9 ± 0.4 nm, discretely, with a thin size exchange. This infers the surface adjustment does not obviously alteration the center size of the Gd₂O₃-NPs when contrasted with the perfect sodium citrate-balanced out Gd₂O₃-NPs. The Gd₂O₃-PEG-L-Cys-NPs are highly stable at room temperature, water dispersible and importantly less cytotoxic at high concentration of the NPs. The T₁-weighted MR phantasm readings evidentially displayed that the formed PEG coated Gd₂O₃-PEG and Gd₂O₃-PEG-Cys-NPs with and without Cys may be performed as the promising T₁-weighted MR imaging. The NPs displays no signs of toxicity against the human blood, which represents the biocompatibility for the human medicine applications. The Gd₂O₃-PEG-Cys-NPs shows relatively, high r₁ acceptable cytocompatibility, target specific cancer cells and activate the dual mode MR imaging of lung metastasis cancer model in vitro. The development of versatile zwitterion functionalized Gd₂O₃ may be promising as an active nanoparticle probe for improved multi-model of MR imaging agents for various cancer diseases.

Diagnostic performance of contrast-enhanced ultrasound and magnetic resonance imaging for detecting colorectal liver metastases: A systematic review and meta-analysis

OBJECTIVES

To determine the diagnostic performance of contrast-enhanced ultrasound, diffusion-weighted magnetic resonance imaging and contrast-enhanced magnetic resonance imaging for detecting colorectal liver metastases.

METHODS

We performed comprehensive searches of the MEDLINE, EMBASE, and Cochrane Library databases to identify studies reporting the per-lesion diagnostic accuracy of contrast-enhanced ultrasound, diffusion-weighted magnetic resonance imaging, and contrast-enhanced magnetic resonance imaging for detecting colorectal liver metastases. Studies published between January 2003 and December 2018 with reference standards, including histopathology and intraoperative observation, and/or follow-up, were included. Sources of bias were assessed using the QUADAS-2 tool. A linear mixed-effects regression model was used to determine sensitivity estimates.

RESULTS

Overall, 47 articles were included. The sensitivity estimates for contrast-enhanced ultrasound, diffusion-weighted magnetic resonance imaging, and contrast-enhanced magnetic resonance imaging for detecting colorectal liver metastases were 85.3%, 83.0%, and 90.1%, respectively. For lesions ≥10 mm in diameter, the sensitivities were 93.1%, 92.9%, and 94.5%, respectively. In 21 articles using histopathology as the only reference standard, the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio for contrast-enhanced ultrasound/contrast-enhanced magnetic resonance imaging were 86%/91%, 91%/95%, 9.2/16.6, 0.15/0.10, and 61/170, respectively.

CONCLUSIONS

CEUS showed a diagnostic ability comparable to that of DWI and CEMRI, particularly for lesions ≥10 mm in diameter.