Imaging features and management of focal liver lesions.

Notably, the number of incidentally detected focal liver lesions (FLLs) has increased dramatically in recent years due to the increased use of radiological imaging. The diagnosis of FLLs can be made through a well-documented medical history, physical examination, laboratory tests, and appropriate imaging methods. Although benign FLLs are more common than malignant ones in adults, even in patients with primary malignancy, accurate diagnosis of incidental FLLs is of utmost clinical significance. In clinical practice, FLLs are frequently evaluated non-invasively using ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI). Although US is a cost-effective and widely used imaging method, its diagnostic specificity and sensitivity for FLL characterization are limited. FLLs are primarily characterized by obtaining enhancement patterns through dynamic contrast-enhanced CT and MRI. MRI is a problem-solving method with high specificity and sensitivity, commonly used for the evaluation of FLLs that cannot be characterized by US or CT. Recent technical advancements in MRI, along with the use of hepatobiliary-specific MRI contrast agents, have significantly improved the success of FLL characterization and reduced unnecessary biopsies. The American College of Radiology (ACR) appropriateness criteria are evidence-based recommendations intended to assist clinicians in selecting the optimal imaging or treatment option for their patients. ACR Appropriateness Criteria Liver Lesion-Initial Characterization guideline provides recommendations for the imaging methods that should be used for the characterization of incidentally detected FLLs in various clinical scenarios. The American College of Gastroenterology (ACG) Clinical Guideline offers evidence-based recommendations for both the diagnosis and management of FLL. American Association for the Study of Liver Diseases (AASLD) Practice Guidance provides an approach to the diagnosis and management of patients with hepatocellular carcinoma. In this article, FLLs are reviewed with a comprehensive analysis of ACR Appropriateness Criteria, ACG Clinical Guideline, AASLD Practice Guidance, and current medical literature from peer-reviewed journals. The article includes a discussion of imaging methods used for the assessment of FLL, current recommended imaging techniques, innovations in liver imaging, contrast agents, imaging features of common nonmetastatic benign and malignant FLL, as well as current management recommendations.

Deep Learning-Based Approach for Identifying and Measuring Focal Liver Lesions on Contrast-Enhanced MRI.

BACKGROUND: The number of focal liver lesions (FLLs) detected by imaging has increased worldwide, highlighting the need to develop a robust, objective system for automatically detecting FLLs. PURPOSE: To assess the performance of the deep learning-based artificial intelligence (AI) software in identifying and measuring lesions on contrast-enhanced magnetic resonance imaging (MRI) images in patients with FLLs. STUDY TYPE: Retrospective. SUBJECTS: 395 patients with 1149 FLLs. FIELD STRENGTH/SEQUENCE: The 1.5 T and 3 T scanners, including T1-, T2-, diffusion-weighted imaging, in/out-phase imaging, and dynamic contrast-enhanced imaging. ASSESSMENT: The diagnostic performance of AI, radiologist, and their combination was compared. Using 20 mm as the cut-off value, the lesions were divided into two groups, and then divided into four subgroups: <10, 10-20, 20-40, and ≥40 mm, to evaluate the sensitivity of radiologists and AI in the detection of lesions of different sizes. We compared the pathologic sizes of 122 surgically resected lesions with measurements obtained using AI and those made by radiologists. STATISTICAL TESTS: McNemar test, Bland-Altman analyses, Friedman test, Pearson's chi-squared test, Fisher's exact test, Dice coefficient, and intraclass correlation coefficients. A P-value <0.05 was considered statistically significant. RESULTS: The average Dice coefficient of AI in segmentation of liver lesions was 0.62. The combination of AI and radiologist outperformed the radiologist alone, with a significantly higher detection rate (0.894 vs. 0.825) and sensitivity (0.883 vs. 0.806). The AI showed significantly sensitivity than radiologists in detecting all lesions <20 mm (0.848 vs. 0.788). Both AI and radiologists achieved excellent detection performance for lesions ≥20 mm (0.867 vs. 0.881, P = 0.671). A remarkable agreement existed in the average tumor sizes among the three measurements (P = 0.174). DATA CONCLUSION: AI software based on deep learning exhibited practical value in automatically identifying and measuring liver lesions. TECHNICAL EFFICACY: Stage 2.

Endoscopic Ultrasound-Guided Tissue Sampling for the Cytohistological Diagnosis of Focal Liver Lesions.

BACKGROUND: Focal liver lesions (FLL) often require cytohistological evaluation. Endoscopic Ultrasound (EUS)-guided tissue acquisition (EUS-TA) is highly accurate in diagnosing pancreatic and gastrointestinal malignancies. The aim of our study was to evaluate the role of EUS-TA in the characterization of FLL. METHODS: A retrospective analysis of a prospective database of patients who underwent EUS-TA for the evaluation of FLL. Diagnostic yield, adverse events and factors associated with diagnostic yield were evaluated as endpoints. The effect of variables such as needle size, lesion size, rapid on-site evaluation (ROSE) and the use of cytological or histological needles were analyzed. RESULTS: A total of 114 cases were included (mean age 68.05 ± 11.35 years, 64 male). A correct diagnosis was made using EUS-TA in 100 of the 114 cases (diagnostic yield of 88%). The EUS-TA of additional extrahepatic lesions during the same EUS procedure increased the diagnostic yield to 94%. No adverse events were reported. Multivariate analysis did not identify any factor influencing the diagnostic yield. CONCLUSIONS: EUS-TA is a highly accurate and safe technique for the differential diagnosis of FLL and could be considered as the primary approach in this setting.

Carcinoembryonic antigen in the diagnosis, treatment, and follow-up of focal liver lesions.

In this editorial review, we comment on the article published in the recent issue of the World Journal of Gastrointestinal Surgery. Carcinoembryonic antigen (CEA) is a fetal glycoprotein and can be secreted in very small amounts from healthy adults after birth. CEA is widely used not only for diagnostic tumor markers but also importantly for the management of some gastrointestinal tumors. The most common clinical use is surveillance for the monitoring of colorectal carcinoma. However, CEA can become elevated in several malign or benign characterized pathologies. Serum CEA level may vary depending on the location of the lesion, whether it metastasizes or not, and its histopathological characteristics. It has been determined that cases with high preoperative CEA have a more aggressive course and the risk of metastasis to the lymph tissue and liver increases. In this editorial review, we focused on evaluating the role of CEA in clinical practice with a holistic approach, including the diagnostic and prognostic significance of CEA in patients with focal liver lesions, the role of CEA in follow-up after definitive surgery, and also hepatic resection for metastasis, and the management of all patients with raised CEA.

Endoscopic ultrasound-guided tissue acquisition for the diagnosis of focal liver lesion.

In patients with liver tumors, the histopathology examination can assist in diagnosis, staging, prognosis, and therapeutic management strategy. Endoscopic ultrasound (EUS)-guided tissue acquisition using fine needle aspiration (FNA) or more newly fine needle biopsy (FNB) is a well-developed technique in order to evaluate and differentiate the liver masses. The goal of the EUS-FNA or EUS-FNB is to provide an accurate sample for a histopathology examination. Therefore, malignant tumors such as hepatocarcinoma, cholangiocarcinoma and liver metastasis or benign tumors such as liver adenoma, focal hyperplastic nodular tumors and cystic lesions can be accurately diagnosed using EUS-guided tissue acquisition. EUS-FNB using 19 or 22 Ga needle provide longer samples and a higher diagnostic accuracy in patients with liver masses when compared with EUS-FNA. Few data are available on the diagnostic accuracy of EUS-FNB when compared with percutaneously, ultrasound, computer tomography or transjugulary-guided liver biopsies. This review will discuss the EUS-guided tissue acquisition options in patients with liver tumors and its efficacy and safety in providing accurate samples. The results of the last studies comparing EUS-guided liver biopsy with other conventional techniques are presented. The EUS-guided tissue acquisition using FNB can be a suitable technique in suspected liver lesions in order to provide an accurate histopathology diagnosis, especially for those who require endoscopy.

Liver imaging and pregnancy: what to expect when your patient is expecting.

Liver diseases in pregnancy can be specific to gestation or only coincidental. In the latter case, the diagnosis can be difficult. Rapid diagnosis of maternal-fetal emergencies and situations requiring specialized interventions are crucial to preserve the maternal liver and guarantee materno-fetal survival. While detailed questioning of the patient and a clinical examination are highly important, imaging is often essential to reach a diagnosis of these liver diseases and lesions. Three groups of liver diseases may be observed during pregnancy: (1) diseases related to pregnancy: intrahepatic cholestasis of pregnancy, pre-eclampsia, eclampsia, hemolysis, elevated liver enzymes and low platelets (HELLP) syndrome, and acute fatty liver of pregnancy; (2) liver diseases that are more frequent during or exacerbated by pregnancy: acute herpes simplex hepatitis, Budd-Chiari syndrome, hemorrhagic hereditary telangiectasia, hepatocellular adenoma, portal vein thrombosis, and cholelithiasis; (3) coincidental conditions, including acute hepatitis, incidental focal liver lesions, metabolic dysfunction-associated steatotic liver disease, cirrhosis, hepatocellular carcinoma, liver abscesses and parasitosis, and liver transplantation. Specific knowledge of the main imaging findings is required to reach an early diagnosis, for adequate follow-up, and to avoid adverse consequences in both the mother and the fetus.Critical relevance statement Pregnancy-related liver diseases are the most important cause of liver dysfunction in pregnant patients and, in pregnancy, even common liver conditions can have an unexpected turn. Fear of radiations should never delay necessary imaging studies in pregnancy.Key points• Pregnancy-related liver diseases are the most frequent cause of liver dysfunction during gestation.• Fear of radiation should never delay necessary imaging studies.• Liver imaging is important to assess liver emergencies and for the diagnosis and follow-up of any other liver diseases.• Common liver conditions and lesions may take an unexpected turn during pregnancy.• Pregnancy-specific diseases such as pre-eclampsia and HELLP syndrome must be rapidly identified. However, imaging should never delay delivery when it is considered to be urgent for maternal-fetal survival.

To assess the quantitative features of focal liver lesions in gadoxetic acid enhanced MRI and to determine whether these features can accurately differentiate benign form malignant lesions.

PURPOSE: The study aims at assessing the quantitative features which distinguish focal liver lesions (FLLs) in gadoxetic acid (GA) enhanced liver MRI and at determining whether these features can accurately differentiate benign from malignant lesions. MATERIAL AND METHODS: 107 patients with 180 unequivocal FLLs in previous examinations were included in a single-center retrospective study. All patients underwent a MRI test of the liver with GA. 99 benign and 74 malignant lesions were included. The group of benign lesions consisted of 60 focal nodular hyperplasias (FNH), 22 hemangiomas (HMG), 6 hepatic adenomas (HA), and 11 other benign lesions (1 angiomyolipioma, 6 lesions histopathology diagnoses as benign without further specification, or ones lacking features of malignancy, and 4 lesions radiologically diagnosed as benign which remained stable in the follow-up studies). The group of malignant lesions consisted of primary 51 hepatocellular carcinomas, 12 metastases, and 11 metastases from melanoma malignum (MM meta). 7 FLLs were excluded (4 cases of uncertain histopathological diagnosis, 2 cholangiocarcinomas, and 1 regenerative nodule). For the included lesions ROI (region of interest) measurements were taken by two observers in the T2-w, ADC (apparent diffusion coefficient) and in the T1-w sequence in the hepatobiliary phase (HBP). The interobserver agreement was evaluated with the Wilcoxon test. The Kruskal - Wallis, Mann - Whitney U and post hoc Dunn's tests were applied to assess if there were any significant differences in the ROI values between individual lesions. The variables with the p values of < 0.05 were considered statistically significant. RESULTS: We found significant differences in the ROI values between lesions with p < 0.0001. Strikingly high ROI values in the T2-w sequence were found for HMG. The lowest ADC values were encountered for metastases and MM metastases. The highest ROI values in the HBP were found for FNH, and the lowest for metastases. We also found statistically significant differences in the ROI values between benign and malignant lesions with benign lesions presenting statistically higher ROI values compared to malignant lesions. CONCLUSIONS: There were significant differences in the ROI values among different types of FLLs. The predominant quantitative feature in the T2-w sequence was a strikingly high ROI value for HMG. Benign lesions presented statistically higher ROI values in the T2-w, ADC, and HBP sequences compared to malignant lesions. This was true for all lesions except for HA.

Diagnosis of focal liver lesions from ultrasound images using a pretrained residual neural network.

OBJECTIVE: This study aims to develop a ResNet50-based deep learning model for focal liver lesion (FLL) classification in ultrasound images, comparing its performance with other models and prior research. METHODOLOGY: We retrospectively collected 581 ultrasound images from the Chulabhorn Hospital's HCC surveillance and screening project (2010-2018). The dataset comprised five classes: non-FLL, hepatic cyst (Cyst), hemangioma (HMG), focal fatty sparing (FFS), and hepatocellular carcinoma (HCC). We conducted 5-fold cross-validation after random dataset partitioning, enhancing training data with data augmentation. Our models used modified pre-trained ResNet50, GGN, ResNet18, and VGG16 architectures. Model performance, assessed via confusion matrices for sensitivity, specificity, and accuracy, was compared across models and with prior studies. RESULTS: ResNet50 outperformed other models, achieving a 5-fold cross-validation accuracy of 87 ± 2.2%. While VGG16 showed similar performance, it exhibited higher uncertainty. In the testing phase, the pretrained ResNet50 excelled in classifying non-FLL, cysts, and FFS. To compare with other research, ResNet50 surpassed the prior methods like two-layered feed-forward neural networks (FFNN) and CNN+ReLU in FLL diagnosis. CONCLUSION: ResNet50 exhibited good performance in FLL diagnosis, especially for HCC classification, suggesting its potential for developing computer-aided FLL diagnosis. However, further refinement is required for HCC and HMG classification in future studies.

Review on Pediatric Malignant Focal Liver Lesions with Imaging Evaluation: Part I.

Malignant focal liver lesions (FLLs) are commonly reported in adults but rarely seen in the pediatric population. Due to the rarity, the understanding of these diseases is still very limited. In children, most malignant FLLs are congenital. It is very important to choose appropriate imaging examination concerning various factors. This paper will outline common pediatric malignant FLLs, including hepatoblastoma, hepatocellular carcinoma, and cholangiocarcinoma and discuss them against the background of the latest knowledge on comparable/similar tumors in adults. Medical imaging features are of vital importance for the non-invasive diagnosis and follow-up of treatment of FLLs in pediatric patients. The use of CEUS in pediatric patients for characterizing those FLLs that remain indeterminate on conventional B mode ultrasounds may be an effective option in the future and has great potential to be integrated into imaging algorithms without the risk of exposure to ionizing radiation.

Review on Pediatric Malignant Focal Liver Lesions with Imaging Evaluation: Part II.

Malignant focal liver lesions (FLLs) represent various kinds of epithelial and mesenchymal tumors. In pediatric patients, the understanding of pediatric liver diseases and associated imaging manifestations is essential for making accurate diagnosis and differential diagnosis. This paper will discuss the latest knowledge of the common pediatric malignant FLLs, including undifferentiated embryonal sarcoma, rhabdomyosarcoma, epithelioid hemangioendothelioma, angiosarcoma, and malignant rhabdoid tumor. Medical imaging features are not only helpful for clinical diagnosis, but can also be useful in the evaluation and follow-up of pre- and post-treatment. The future perspectives of contrast-enhanced ultrasound (CEUS) enhancement patterns of FLLs in pediatric patients are also mentioned.

Assessing the impact and resource implications of contrast-enhanced ultrasound on workflow of patients with incidental focal liver lesions on the UK national health service.

Background: Focal liver lesions (FLL) are abnormal growths that require timely identification. Contrast-enhanced ultrasound (CEUS) is a cost-effective imaging modality for characterising FLL with similar sensitivity to computed tomography (CT) and magnetic resonance imaging (MRI). Despite being recommended by NICE, its adoption within the national health service (NHS) is limited due to low clinical demand, limited referral, and lack of knowledge. Purpose: To evaluate the impact of CEUS on patients with incidental FLL and assess the resource implications of introducing CEUS as a diagnostic service within the NHS. Material and methods: A patient flow review and cost-minimisation analysis were conducted. This involved a targeted literature review, NHS Trust stakeholder consultations, and development of a Microsoft Excel cost-minimisation model to explore potential value of CEUS use versus CT and MRI by episode. A scenario analysis of the base-case explored increasing CEUS use to 50% and 90%. A sensitivity analysis was performed to assess how changes in assumptions impacted the model and the resulting cost estimates. Results: The model, comparing a world with and without CEUS, showed that current use (base-case: 5%) resulted in cost savings of £224,790/year. The sensitivity analysis indicated that regardless of changes to the assumptions, CEUS still resulted in cost savings to the NHS. By increasing CEUS use to 50% and 90%, cost savings of up to £2,247,894/year and £4,046,208/year could be achieved, respectively. Conclusion: By standardising CEUS use for characterising FLL, substantial cost savings could be realised, whilst reducing wait times and expanding diagnostic capacity, thus preserving limited CT and MRI capacity for high-priority cases.

Machine learning for malignant versus benign focal liver lesions on US and CEUS: a meta-analysis.

OBJECTIVES: To perform a meta-analysis of the diagnostic performance of learning (ML) algorithms (conventional and deep learning algorithms) for the classification of malignant versus benign focal liver lesions (FLLs) on US and CEUS. METHODS: Available databases were searched for relevant published studies through September 2022. Studies met eligibility criteria if they evaluate the diagnostic performance of ML for the classification of malignant and benign focal liver lesions on US and CEUS. The pooled per-lesion sensitivities and specificities for each modality with 95% confidence intervals were calculated. RESULTS: A total of 8 studies on US, 11 on CEUS, and 1 study evaluating both methods met the inclusion criteria with a total of 34,245 FLLs evaluated. The pooled sensitivity and specificity of ML for the malignancy classification of FLLs were 81.7% (95% CI, 77.2-85.4%) and 84.8% (95% CI, 76.0-90.8%) for US, compared to 87.1% (95% CI, 81.8-91.0%) and 87.0% (95% CI, 83.1-90.1%) for CEUS. In the subgroup analysis of studies that evaluated deep learning algorithms, the sensitivity and specificity of CEUS (n = 4) increased to 92.4% (95% CI, 88.5-95.0%) and 88.2% (95% CI, 81.1-92.9%). CONCLUSIONS: The diagnostic performance of ML algorithms for the malignant classification of FLLs was high for both US and CEUS with overall similar sensitivity and specificity. The similar performance of US may be related to the higher prevalence of DL models in that group.

[Ultrasound diagnostics of the liver : Principles and important pathologies]. / Ultraschalldiagnostik der Leber : Grundlagen und wichtige Pathologien.

Diffuse changes in the liver parenchyma, focal lesions and blood flow in hepatic vessels can be assessed using ultrasound. Screening by ultrasound can be used to detect hepatocellular carcinomas as possible malignant sequelae of liver cirrhosis. As metastases are far more frequent than primary malignant liver tumors, secondary malignant neoplasms should be taken into consideration as a differential diagnosis in the presence of focal liver lesions. This particularly concerns patients with a known metastatic disease. Benign focal liver lesions are often incidentally discovered in women of childbearing age. Cysts, hemangiomas and focal nodular hyperplasia mostly show typical morphological features in ultrasound and do not require further follow-up; however, with hepatic adenomas, regular follow-up is recommended due to the risk of bleeding and/or malignant transformation.

Non-invasive evaluation of vascular architecture of focal liver lesions by micro vascular imaging.

OBJECTIVE: To explore the value of vascular architecture detected by micro vascular imaging (MVI) in preoperative diagnosis of focal liver lesions (FLLs). METHODS: In this retrospective study, patients with surgery and histopathologically proved or radiologically confirmed FLLs were included. Vascular architecture of FLLs were acquired by color Doppler flow imaging (CDFI) and MVI on LOGIQ™ E20 ultrasound machine (C1-6 convex array probes). Alder semiquantitative analysis (grade 0-3) and morphologic features of blood vessels (pattern a-f) were used to assess the blood flow within the FLLs. Interobserver agreement for evaluating blood flow of FLLs was analyzed. Using Adler's grading or morphologic patterns as diagnostic criteria for malignant FLLs, the diagnostic efficiency was analyzed and compared. RESULTS: From October 2021 and February 2022, 50 patients diagnosed with 40 malignant FLLs and 10 benign FLLs were finally included. The Kappa value within two observers for evaluating the blood flow of FLLs was 0.78 for MVI and 0.55 for CDFI. According to Alder semiquantitative analysis, more high-level blood flow signals (grade 2-3) were detected by MVI than CDFI (P < 0.05). Based on high-level blood flow signals (grade 2-3) and hypervascular supply patterns (pattern e and f), the diagnostic accuracy for malignant FLLs were 76% and 68% for MVI, 56% and 38% for CDFI, respectively. CONCLUSION: MVI is superior to CDFI in evaluating vascular architecture of FLLs. The high-level flow signals and hypervascular pattern detected by MVI have a useful and complementary value in preoperative non-invasive identification of malignant FLLs.

Applicability of multidimensional convolutional neural networks on automated detection of diverse focal liver lesions in multiphase CT images.

PURPOSE: To investigate the applicability of multidimensional convolutional neural networks (CNNs) together with multiphase contrast-enhanced CT images on automated detection of diverse focal liver lesions (FLLs). METHODS: We trained detection models based on 2.5D and 3D CNN frameworks using 567 patients with 3892 FLLs and validated on a relatively large independent cohort of 1436 patients with 4723 lesions. The detection performance across different phases (arterial, portal venous [PV], and combined phases) was assessed for the 2.5D model. The lesions were divided into two groups with a cutoff size of 20 mm, and further subdivided into four subgroups of <10, 10-20, 20-50, and ≥50 mm, to verify the detection rates for lesions of different sizes for the 2.5D and 3D models. McNemar's test was used to compare the detection sensitivities among different methods. In addition, sensitivity with 95% confidence intervals and free-response receiver operating characteristics (FROC) curves were plotted for visualization of the detectability. RESULTS: In the 2.5D model, the detection rate of PV phase outperformed arterial phase, and a combination of the two phases further improved the performance over a single phase. The detection sensitivities in the arterial, PV, and combined phases were 0.737 versus 0.802 versus 0.832 for all lesions. The 3D model was superior to the 2.5D model for detecting benign lesions (0.896 vs. 0.807, p < 0.001), malignant lesions (0.940 vs. 0.918, p = 0.013), and all lesions (0.902 vs. 0.832, p < 0.001) regardless of size division. Particularly, the 3D model showed higher sensitivity than the 2.5D model in detecting lesions smaller than 20 mm (0.868 vs. 0.759, p < 0.001). For lesions larger than 20 mm, both the 3D and the 2.5D models achieved excellent detection performance. CONCLUSIONS: The proposed CNN detection model was demonstrated to adaptively learn the feature representations of diverse FLLs and generalize well to a large-scale validation dataset. The use of multiphase significantly improved the detectability of FLLs compared to single phase. 3D CNN framework showed an enhanced capability over the 2.5D in the detection of FLLs, particularly small lesions. The promising performance shows that the proposed CNN detection system could be a powerful clinical tool for the early detection of hepatic tumors.

[18F]FAPI PET/CT in the evaluation of focal liver lesions with [18F]FDG non-avidity.

PURPOSE: This prospective study was aimed to investigate the potential utility of [18F]fibroblast activation protein inhibitor (FAPI) PET/CT for evaluating focal liver lesions (FLLs) with [18F]FDG non-avidity. METHODS: From January 2021 to March 2022, this prospective study included 80 FLLs that were not avid on [18F]FDG PET/CT from 37 patients, then underwent [18F]FAPI PET/CT. All patients with FLL(s) with biopsy-proof or follow-up confirmation were categorized into four subgroups (20 hepatocellular carcinomas [HCCs]/5 non-HCC malignancies/4 inflammatory FLLs/8 benign noninflammatory FLLs). The diagnostic value of [18F]FAPI for detecting liver malignancy was determined by visual evaluation. Differences in the maximum standardized uptake value (SUVmax) and lesion-to-background ratio (LBR) obtained from [18F]FAPI PET/CT among the four subgroups were analyzed by semiquantitative analysis. RESULTS: Among the thirty-seven enrolled participants (34 males; median age 57 years, range 48-67 years), on visual evaluation, the sensitivity, specificity, and accuracy of [18F]FAPI PET for detecting liver malignancy in the patient-based analysis were 96.0% (24/25), 58.3% (7/12), and 83.8% (31/37), respectively. On semiquantitative analysis, the SUVmax and LBR of [18F]FAPI PET in liver malignancy (33 HCC lesions; 19 non-HCC malignant lesions) were significantly higher than those in 11 benign noninflammatory FLLs [HCC: SUVmax: 6.4 vs. 4.5, P = 0.017; LBR: 5.1 vs. 1.5, P = 0.003; non-HCC: SUVmax: 5.5 vs. 4.5, P = 0.008; LBR: 4.4 vs. 1.5, P = 0.042]. Notably, there was no significant difference in the SUVmax of [18F]FAPI PET between 33 HCC lesions and 17 inflammatory FLLs (6.4 vs. 8.2, P = 0.37), but the LBR of [18F]FAPI PET in HCC were significantly lower than that in inflammatory FLLs (5.1 vs. 9.1, P = 0.003). CONCLUSIONS: [18F]FAPI PET/CT shows high sensitivity in detecting HCC and non-HCC malignancy with [18F]FDG non-avidity. [18F]FAPI might be a promising radiopharmaceutical for the differential diagnosis of benign noninflammatory FLLs and liver malignancy with [18F]FDG non-avidity.

Contrast-Enhanced Intraoperative Ultrasound of the Liver.

Contrast-enhanced intraoperative ultrasound (CE-IOUS) is a relatively new but valuable tool that is increasingly used as an adjunct to computed tomography, MRI, and IOUS for patients undergoing liver surgery. CE-IOUS has an important role in 2 main settings: the discrimination of indeterminate lesions detected in cirrhotic livers by conventional IOUS and in the detection of colorectal liver metastasis that may be overlooked by other imaging modalities. The intraoperative nature of the imaging and interpretation allows for CE-IOUS to directly affect surgical decision-making that may importantly affect patient outcomes.

Differential diagnosis of different types of solid focal liver lesions using two-dimensional shear wave elastography.

BACKGROUND: The clinical management and prognosis differ between benign and malignant solid focal liver lesions (FLLs), as well as among different pathological types of malignant FLLs. Accurate diagnosis of the possible types of solid FLLs is important. Our previous study confirmed the value of shear wave elastography (SWE) using maximal elasticity (Emax) as the parameter in the differential diagnosis between benign and malignant FLLs. However, the value of SWE in the differential diagnosis among different pathological types of malignant FLLs has not been proved. AIM: To explore the value of two-dimensional SWE (2D-SWE) using Emax in the differential diagnosis of FLLs, especially among different pathological types of malignant FLLs. METHODS: All the patients enrolled in this study were diagnosed as benign, malignant or undetermined FLLs by conventional ultrasound. Emax of FLLs and the periphery of FLLs was measured using 2D-SWE and compared between benign and malignant FLLs or among different pathological types of malignant FLLs. RESULTS: The study included 32 benign FLLs in 31 patients and 100 malignant FLLs in 96 patients, including 16 cholangiocellular carcinomas (CCCs), 72 hepatocellular carcinomas (HCCs) and 12 liver metastases. Thirty-five FLLs were diagnosed as undetermined by conventional ultrasound. There were significant differences between Emax of malignant (2.21 ± 0.57 m/s) and benign (1.59 ± 0.37 m/s) FLLs (P = 0.000), and between Emax of the periphery of malignant (1.52 ± 0.39 m/s) and benign (1.36 ± 0.44 m/s) FLLs (P = 0.040). Emax of liver metastases (2.73 ± 0.99 m/s) was significantly higher than that of CCCs (2.14 ± 0.34 m/s) and HCCs (2.14 ± 0.46 m/s) (P = 0.002). The sensitivity, specificity and accuracy were 71.00%, 84.38% and 74.24% respectively, using Emax > 1.905 m/s (AUC 0.843) to diagnose as malignant and 23 of 35 (65.74%) FLLs with undetermined diagnosis by conventional ultrasound were diagnosed correctly. CONCLUSION: Malignant FLLs were stiffer than benign ones and liver metastases were stiffer than primary liver carcinomas. 2D-SWE with Emax was a useful complement to conventional ultrasound for the differential diagnosis of FLLs.

An investigation of the efficacy of shear wave elastography in the characterization of benign and malignant liver lesions.

Purpose: To investigate whether shear wave elastography (SWE) examination, which has recently been proposed as an accessory radiological examination technique, is effective in characterizing focal liver lesions (FLLs). Material and methods: A total of 105 patients, comprising 48 males and 57 females, underwent SWE examination. The mean age of the patients was 53.31 ± 1.59 (age range 5-87) years. The SWE measurements were obtained from FLLs that were approximately 2 to 8 cm in depth in a box that was approximately 0.5 × 1 cm wide on an ultrasonography (USG) screen from approximately 2 different locations. Receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic SWE values in the differentiation of benign and malignant lesions. Sensitivity, specificity, and positive predictive and negative predictive values were calculated in the presence of significant limit values. Results: The SWE values, in kPa and m/s, in the malignant lesions were significantly higher than those in the benign lesions (p = 0.006, p = 0.011). In the ROC curve analysis, the cut-off value was calculated as 9.005 kPa in the differentiation of malignant lesions from benign lesions. The area under the ROC curve was calculated as 0.656 in the range of 0.551-0.761 with 95% reliability. Sensitivity was calculated as 64.2%, specificity as 61.5%, positive predictive value as 63%, and negative predictive value as 62.7%. Conclusions: In addition to providing little contribution to the differentiation of benign and malignant lesions, the SWE technique is thought to contribute to a certain extent, especially in suspected cases, during the diagnosis with cross-sectional methods.

Endoscopic Ultrasound-Guided Fine-Needle Biopsy versus Fine-Needle Aspiration in the Diagnosis of Focal Liver Lesions: Prospective Head-to-Head Comparison.

Endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) or fine-needle aspiration (EUS-FNA) from focal liver lesions are indicated in selected cases, but there has been no previous comparison of needle types of the same size. The aim of our study was to compare the histologic diagnostic accuracy and adequacy of cores obtained with EUS-FNB needles in contrast to those obtained with FNA needles in focal liver lesions. This prospective one-center study included patients with left lobe hepatic focal lesions with contraindications for percutaneous liver biopsy or need for EUS for concomitant lesions. Each patient had one pass of 22G EUS-FNB (Franseen) needle and one pass of 22G EUS-FNA in a crossover manner, without macroscopic on-site evaluation. Each sample was analyzed separately for histologic adequacy and diagnosis. The final diagnosis was based on histology results or on imaging follow-up in the case of negative biopsies. The EUS-FNB samples (n = 30) were found to be more adequate for histologic analysis, with more cellularity and longer tissue aggregates than the EUS-FNA samples (n = 30). The accuracy of EUS-FNB was 100%, whereas that of EUS-FNA was 86.7% (p = 0.039). No post-procedure complications were noted. The 22G EUS-FNB needle proved superior to 22G EUS-FNA in terms of tissue acquisition diagnostic accuracy and histologic adequacy in focal liver lesions.