Detection Of Liver Lesions Research Articles

Inflammatory Pseudotumor of the Liver, a Diagnostic Dilemma with Therapeutic Uncertainty in a Cohort of Bangladeshi Patients

Background: Inflammatory pseudotumor (IPT) is a benign lesion seldom encountered in clinical practice. It's mysterious in origin and remains ambiguous. Infection, stone, autoimmune disease, systemic inflammatory response, trauma, foreign body and neoplasm attributed to be the etiological factors. Advanced imaging modalities help in increased detection of focal liver lesion.

Liver Lesions and Acute Intracerebral Hemorrhage Detection Using Multimodal Fusion

Medical image fusion is designed to help physicians in their decisions by providing them with a preclinical image with enough information. Accurate assessment and effective treatment of the disease reduce the time it takes to relieve the symptoms of the disease. This article utilizes an effective data fusion approach to work on two different imaging modalities; computed tomography (CT) and magnetic resonance imaging (MRI). The data fusion approach is based on the combination of singular value decomposition (SVD) and the Fast Discrete Curvelet Transform (FDCT) techniques to reduce processing time during the fusion process. The SVD-FDCT data fusion approach is being tested with two multimodal medical image fusion applications. The first application concerns the detection of liver lesions and the second application concerns the early detection of acute intracerebral hemorrhage. Experimental tests demonstrate that not only the SVD-FDCT data fusion algorithm can treat the curved objects and edges effectively as the FDCT do. But also, the throughput of the fusion algorithm is comparable to related fusion algorithms such as principal component analysis (PCA), Transform and Discrete Wavelet Transform (DWT), dual-tree complex wavelet transform (DT-CWT), and Curvelet fusion algorithms.

Comparison and correlation of CT scan and MRI for focal liver lesion detection and characterization

Background: Liver diseases create diagnostic challenge for attending clinicians. Role of radiological imaging, particularly newer modalities like Ultrasound, Color Doppler, CT scan, MRI, DSA, are highly reliable. Early identification of liver lesions provides the opportunity for the success of therapeutic approach. Contrast enhanced CT scan and contrast enhanced MRI are most advanced and appropriate modalities to detect and characterize liver focal lesions. In present study we tried to compare and correlate findings of both modalities. Methodology: We evaluated 40 cases of liver pathologies which are suspected in sonography examination. All patients were undergone contrast enhanced CT scan as well as MRI evaluation. Various radiological findings are recorded in standard format. Result: In total 40 patients of focal liver pathology all age groups are included. Male: female ratio is 70:30.Patients are presented with various clinical symptoms like right hypochondriac pain, fever, lump, jaundice, weight loss etc. Benign lesions are found in 40% of cases and malignant lesions are found in 60 % of cases. Most common pathology is liver metastatic lesions which are picked up by MRI with 100% accuracy. CT is able to characterize only 10 out of 13 metastatic cases(77%). Few other cases of benign lesions like hemangioma, hamartoam ,adenoma and FNH are also remained indeterminate in CT scan which all are accurately diagnosed and characterized by MRI and confirmed in histopathology. A case of HCC, lymphoma and nodular dysplasia also remained indeterminate in CT scan and further diagnosed and characterized by MRI.

The effectiveness of transarterial chemoembolization in metastatic uveal melanoma of the liver

Aim: to study the effectiveness of the use of transarterial chemoembolization (TACE) in the treatment of patients with metastatic uveal melanoma. Material and methods: in N.N. Blokhin National Medical Research Center of Oncology of the Ministry of Health of Russia in the period from 2000 to 2019 72 patients received treatment (TACE) for metastases of uveal melanoma in the liver. Of these: men – 22 (30,6%), women – 50 (69,4%). Average age 46,28±10,32 years, range 23–84 years. The time of detection of metastatic liver lesions after treatment of the primary tumor ranged from 2 to 252 months, the median was 24 months. The volume of liver damage was up to 25% in 19 patients, from 25% to 50% in 33 patients, from 50% to 75% in 20 patients. A total of 134 TACE interventions were performed. Depending on the volume of the lesion, the nature of the blood supply to the tumors and the response to treatment, patients underwent 1 to 5 sessions of TACE: in 27 patients one TACE, in 35 – two, in 5 – three, in 3 – four, and in 2 – five TACE. As an embolizing component, lipiodol 10 ml was used in 106 cases, microspheres in 16 cases (particle sizes varied from 100 to 500 μm), in 12 TACEs, combinations of the presented embolizing materials were used. Carboplatin, doxorubicin or gemcitabine were used as chemotherapy drugs. Results: 58 patients (80,6%) had a moderate postembolization syndrome, expressed by pain, febrile temperature, nausea, and vomiting. A local response (including complete response, partial response, or stabilization by mRECIST criteria) was observed in 53/72 (73,6%) patients with metastases of uveal melanoma. The duration of observation of patients after TACE was from 2 to 60 months. The median follow-up was 12,5 months. The group that responded to treatment, including stabilization, achieved a 1-year Kaplan-Meier overall survival rate of 72% and a 2-year rate of 45,6%. In patients with continued growth of lesions, the 1-year overall survival rate according to the Kaplan-Meier method was 42,6%, and the 2-year survival rate was not achieved. 48 patients were alive at the time of the study, 24 died from disease progression. Conclusions: the use of TACE in metastatic lesions of the liver by choroidal melanoma in combined treatment or in mono-regimen led to an objective response or stabilization of the process in 73,6% of patients. This method increases the overall survival of patients and is well tolerated.

Digital versus analog PET/CT in patients with known or suspected liver metastases.

To assess if digital PET/CT improves liver lesion detectability compared to analog PET/CT in patients with known or suspected liver metastases. We prospectively included 83 cancer patients, with one or more of these conditions: history of liver metastases, clinical risk of having liver metastases or presence of suspected liver metastases on the first of the two PET/CTs. All patients were consecutively scanned on each PET/CT on the same day after a single [18F]fluorodeoxyglucose dose injection. The order of acquisition was randomly assigned. Three nuclear medicine physicians assessed both PET/CTs by counting the foci of high uptake suspicious of liver metastases. Findings were correlated with appropriate reference standards; 19 patients were excluded from the analysis due to insufficient lesion nature confirmation. The final sample consisted of 64 patients (34 women, mean age 68 ± 12 years). As per-patient analysis, the mean number of liver lesions detected by the digital PET/CT (3.84 ± 4.25) was significantly higher than that detected by the analog PET/CT (2.91 ± 3.31); P < 0.001. Fifty-five patients had a positive PET/CT study for liver lesions. In 26/55 patients (47%), the digital PET/CT detected more lesions; 7/26 patients (27%) had detectable lesions only by the digital system and had <10 mm of diameter. Twenty-nine patients had the same number of liver lesions detected by both systems. In nine patients both PET/CT systems were negative for liver lesions. Digital PET/CT offers improved detectability of liver lesions over the analog PET/CT in patients with known or suspected liver metastases.

Abdominal ultrasonographic manifestations in pediatric patients with tuberous sclerosis complex.

BackgroundTuberous sclerosis complex (TSC) is a rare genetic disease which leads to formation of benign tumors in the brain and other organs of the body. Ultrasound (US) can detect the location, quantity, size and internal echo of TSC-associated renal diseases, liver angiomyolipoma (AML), and co-existing lesions, providing important diagnostic basis for clinical diagnosis. The aim of the present study was to investigate the abdominal ultrasonographic features of pediatric TSC and explore the advantages of abdominal ultrasonography in clinical practice.MethodsData of children with TSC, who presented to the Second Affiliated Hospital and Yuying Children’s Hospital, Wenzhou Medical University, between January 2016 and November 2018, were analyzed by a retrospective chart review. The cases were identified from electronic medical records (EMR) system and underwent ultrasonography, we yielded a total of 12 patients.ResultsThe 12 pediatric patients, including 5 boys and 7 girls, ranged in age from 9 months to 13 years old. And they all had a history of epilepsy. All the patients underwent brain magnetic resonance imaging (MRI) or computed tomography (CT) examination, which revealed a scattered distribution of multiple hyperintense nodules. Of the 12 patients, 10 had TSC-associated bilateral renal AMLs, 5 had hepatic AML, and 4 had renal cysts.ConclusionsUS is a useful and non-invasive tool for the detection of TSC-associated renal and liver lesions and for clinical follow-up among pediatric patients.

Analysis of Imaging Modalities for Detecting Liver Lesions: (Review Artical)

Analysis of Imaging Modalities for Detecting Liver Lesions: (Review Artical)

Focal lesions of the liver: imaging appearances and management.

With the increasing use of cross-sectional imaging, the detection of incidental liver lesions has become more common. Accurate and reliable characterisation of these is vital for optimal patient care. Owing to the great improvements in medical imaging technology in recent years, particularly magnetic resonance imaging, it is now possible to characterise a significant proportion of these non-invasively. This is of paramount importance in improving patient safety and reducing costs by avoiding unnecessary biopsies. This article gives a synopsis of the different imaging modalities for liver. It depicts the salient imaging features of the common benign and malignant focal liver lesions on different imaging modalities, with emphasis on magnetic resonance imaging. It demonstrates the pseudolesions, variants, mimics and pitfalls that occur in liver imaging. The tailored magnetic resonance imaging protocols including abbreviated ones, the contrast agents and the pathway for managing incidental liver lesions in the author's institution are covered.

P.438 The capacity of schizophrenia and bipolar disorder individuals for autonomous treatment decision making

To compare the diagnostic efficacy of Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) vs. multidetector computed tomography (MDCT) for the detection and classification of focal liver lesions, differentiated also for lesion entity and size; a separate analysis of pre- and postcontrast images as well as T2-weighted MRI sequences of focal and exclusively solid lesions was integrated.Twenty-nine patients with 130 focal liver lesions underwent MDCT (64-detector-row; contrast medium iopromide; native, arterial, portalvenous, venous phase) and MRI (1.5-T; dynamic and tissue-specific phase 20 min after application of Gd-EOB-DTPA). Hepatic lesions were verified against a standard of reference (SOR). CT and MR images were independently analysed by four blinded radiologists on an ordinal 6-point-scale, determining lesion classification and diagnostic confidence.Among 130 lesions, 68 were classified as malignant and 62 as benign by SOR. The detection of malignant and benign lesions differed significantly between combined and postcontrast MRI vs. MDCT; overall detection rate was 91.5% for combined MRI and 80.4% for combined MDCT (p < 0.05). Considering all four readers together, combined MDCT achieved sensitivity of 66.2%, specificity of 79.0%, and diagnostic accuracy of 72.3%; combined MRI reached superior diagnostic efficacy: sensitivity 86.8%, specificity 94.4%, accuracy 90.4% (p < 0.05). Differentiated for lesion size, in particular lesions <20 mm revealed diagnostic benefit by MRI. Postcontrast MRI also achieved higher overall sensitivity, specificity, and accuracy compared to postcontrast MDCT for focal and exclusively solid liver lesions (p < 0.05).Combined and postcontrast Gd-EOB-DTPA-enhanced MRI provided significantly higher overall detection rate and diagnostic accuracy, including low inter-observer variability, compared to MDCT in a single centre study.

Irregular Respiratory Motion Compensation for Liver Contrast-Enhanced Ultrasound via Transport-Based Motion Estimation.

Contrast-enhanced ultrasound (CEUS) imaging has been widely applied for the detection and characterization of focal liver lesions (FLLs), for its ability to visualize the blood flow in real time. However, cyclic liver motion poses a great challenge to the recovery of perfusion curves as well as quantitative kinetic parameters estimation. Recently, a few gating methods have been proposed to eliminate unexpected intensity fluctuations by the breathing phase estimation, with the assumption that each breathing phase corresponds to a specific lesion position strictly. While practical liver motion tends to be irregular due to changes in the patient's underlying physiologic status, that is, the same phase might not correspond to the same position. To tackle the challenge of motion irregularity, we present a novel motion estimation-based respiratory compensation method, named RCME, which first estimates salient motion information through the framework of optimal transport (OT) by jointly modeling pixel intensity as well as their locations and then employs sparse subspace clustering (SSC) to identify the subset of frames acquired at the same position. Our proposed method is evaluated on 15 clinical CEUS sequences in both qualitative and quantitative manners. Experimental results demonstrate good performance on irregular liver motion compensation.

DIAGNOSTIC ACCURACY OF CONTRAST ENHANCED ULTRASONOGRAPHY IN FOCAL LIVER LESIONS DETECTED BY CONTRAST ENHANCED COMPUTED TOMOGRAPHY

Context: Contrast enhanced Ultrasonography(CEUS) has improved the detection and characterization of focal liver lesions, offering comparable results to those with contrast CT when ultra-sound exploration is technically satisfactory.The vascular property of the lesion in arterial, portal and delayed phases by enhancement and washout is used in this technique. Aim: The aim of the study is to interpret the use of contrast-enhanced ultra-sound (CEUS) in characterising the focal liver lesions and compare the diagnostic accuracy of the contrast-enhanced ultra-sound with contrast enhanced CT Materials and Methods: This is a cross sectional analytical study in patients with focal liver lesions detected by USG/CECT coming to Department of Radio diagnosis in Government Stanley Hospital.The duration of the study is two and a half years from January 2017 to July 2019.Sample Size was total of 51 patients detected by CECT /USG as focal liver lesions registered in Govt. Stanley Medical College Hospital between January 2017 to July 2019. Results: Diagnostic accuracy for CEUS is 76.46 % and CECT is 83.9%. Sensitivity, specificity , PPV ,NPV and Diagnostic accuracy of the CEUS is almost near equal or comparable with that of CECT. Conclusion: CEUS has ability to detect and characterise of focal liver lesions with no risk of radiation exposure and aids in real time imaging assessment.The study parameters like sensitivity, specificity and diagnostic accuracy of the CEUS are comparable with that of CECT.CEUS can be used to characterise the focal liver lesions in patients where CECT is contraindicated.

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses

Detection and characterization of focal liver lesions (FLLs) is key for optimizing treatment for patients who may have a primary hepatic cancer or metastatic disease to the liver. This is the first study to develop an EUS-based convolutional neural network (CNN) model for the purpose of identifying and classifying FLLs. A prospective EUS database comprising cases of FLLs visualized and sampled via EUS was reviewed. Relevant still images and videos of liver parenchyma and FLLs were extracted. Patient data were then randomly distributed for the purpose of CNN model training and testing. Once a final model was created, occlusion heatmap analysis was performed to assess the ability of the EUS-CNN model to autonomously identify FLLs. The performance of the EUS-CNN for differentiating benign and malignant FLLs was also analyzed. A total of 210,685 unique EUS images from 256 patients were used to train, validate, and test the CNN model. Occlusion heatmap analyses demonstrated that the EUS-CNN model was successful in autonomously locating FLLs in 92.0% of EUS video assets. When evaluating any random still image extracted from videos or physician-captured images, the CNN model was 90% sensitive and 71% specific (area under the receiver operating characteristic [AUROC], 0.861) for classifying malignant FLLs. When evaluating full-length video assets, the EUS-CNN model was 100% sensitive and 80% specific (AUROC, 0.904) for classifying malignant FLLs. This study demonstrated the capability of an EUS-CNN model to autonomously identify FLLs and to accurately classify them as either malignant or benign lesions.

Impact of iterative reconstructions on image quality and detectability of focal liver lesions in low-energy monochromatic images

To assess the impact of iterative reconstructions on image quality and detectability of focal liver lesions in low-energy monochromatic images from a Fast kV-Switching Dual Energy CT (KVSCT) platform. Acquisitions on an image-quality phantom were performed using a KVSCT for three dose levels (CTDIvol:12.72/10.76/8.79mGy). Raw data were reconstructed for five energy levels (40/50/60/70/80keV) using Filtered Back Projection (FBP) and four levels of ASIR (ASIR30/ASIR50/ASIR70/ASIR100). Noise power spectrum (NPS) and task-based transfer function (TTF) were measured before computing a Detectability index (d') to model the detection task of liver metastasis (LM) and hepatocellular carcinoma (HCC) as function of keV. From 40 to 70keV, noise-magnitude was reduced on average by -68%±1% with FBP; -61%±3% with ASIR50 and -52%±6% with ASIR100. The mean spatial frequency of the NPS decreased when the energy level decreased and the iterative level increased. TTF values at 50% decreased as the energy level increased and as the percentage of ASIR increased. The detectability of both lesions increased with increasing dose level and percentage of ASIR. For the LM, d' peaked at 70keV for all reconstruction types, except for ASIR70 at 12.72mGy and ASIR100, where d' peaked at 50keV. For HCC, d' peaked at 60keV for FBP and ASIR30 but peaked at 50keV for ASIR50, ASIR70 and ASIR100. Using percentage of ASIR above 50% at low-energy monochromatic images could limit the increase of noise-magnitude, benefit from spatial resolution improvement and hence enhance detectability of subtle low contrast focal liver lesions such as HCC.

Survey on Recent Works in Computed Tomography based Computer ‑ Aided Diagnosis of Liver using Deep Learning Techniques

Computed tomography (CT) scanning is a non-invasive diagnostic imaging technique that provides more detailed information about the liver than standard X-rays. Unlike ultrasound (US) examination, the quality of the CT image is not highly operator dependent. Plenty of works has been done using computer-aided diagnosis (CAD) for liver using conventional machine learning algorithms with better results. Recent advances especially in deep learning technology, can detect, classify, segment patterns in medical images where the advancements in deep learning has been shifted to medical domain also. One of the core abilities of deep learning is that they could learn feature representations automatically from data instead of feeding hand crafted features based on application. In this review, the basics of deep learning is introduced and their success in liver segmentation and lesion detection, classification using CT imaging modality is reviewed and their different network architectures is also discussed. Transfer learning is an interesting approach in deep learning which is also discussed. So, deep learning and CAD system has made a huge impact and has produced enhanced performance in healthcare industry.

Focal Liver Lesion Detection in Ultrasound Image Using Deep Feature Fusions and Super Resolution

This research presents a machine vision approach to detect lesions in liver ultrasound as well as resolving some issues in ultrasound such as artifacts, speckle noise, and blurring effect. The anisotropic diffusion is modified using the edge preservation conditions which found better than traditional ones in quantitative evolution. To dig for more potential information, a learnable super-resolution (SR) is embedded into the deep CNN. The feature is fused using Gabor Wavelet Transform (GWT) and Local Binary Pattern (LBP) with a pre-trained deep CNN model. Moreover, we propose a Bayes rule-based informative patch selection approach to reduce the processing time with the selective image patches and design an algorithm to mark the lesion region from identified ultrasound image patches. To train this model, standard data ensures promising resolution. The testing phase considers generalized data with a varying resolution and test the performance of the model. Exploring cross-validation, it finds that a 5-fold strategy can successfully eradicate the overfitting problem. Experiment data are collected using 298 consecutive ultrasounds comprising 15,296 image patches. This proposed feature fusion technique confirms satisfactory performance compared to the current relevant works with an accuracy of 98.40%.

Evaluation of the Reproducibility of Bolus Transit Quantification With Contrast-Enhanced Ultrasound Across Multiple Scanners and Analysis Software Packages-A Quantitative Imaging Biomarker Alliance Study.

Contrast enhanced ultrasound (CEUS) is now broadly used clinically for liver lesion detection and characterization. Obstacles to the efforts to quantify perfusion with CEUS have been the lack of a standardized approach and undocumented reproducibility. The use of multiple scanners and different analysis software packages compounds the degree of variability. Our objectives were to standardize a CEUS-based approach for quantification of perfusion-related parameters of liver lesions and to evaluate the variability of bolus transit parameters (rise time [RT], mean transit time [MTT], peak intensity, and area under the curve) obtained from various clinical ultrasound scanners and analysis software. Bolus transit as a way of evaluating perfusion has been investigated both in vivo and in vitro in the past but without establishing its reproducibility. We developed a tissue flow phantom that produces time-intensity curves very similar to those extracted from clinical cine loops of liver lesions. We evaluated the variability of the bolus transit parameters with 4 commercial scanners (Philips iU22, Philips EPIQ, GE LOGIQ E9, and Siemens Acuson Sequoia) and 3 different analysis software packages in multiple trials (15 per scanner). The variability (coefficient of variation) from repeated trials and while using a single scanner and software was less than 8% for RT, less than 12% for MTT, less than 49% for peak intensity, and less than 50% for area under the curve. Currently, it is not possible to directly compare amplitude values from different scanners and analysis software packages owing to the arbitrary linearization algorithm used among manufacturers; however, it is possible for time parameters (RT and MTT). The variability when using a different scanner with the same analysis software package was less than 9% for RT and less than 21% for MTT. The variability when using a different analysis software with the same scanner was less than 9% for RT and less than 15% for MTT. In all the evaluations we have performed, RT is the least variable parameter, while MTT is only slightly more variable. The present study will lay the groundwork for multicenter patient evaluations with CEUS quantification of perfusion-related parameters with the bolus transit technique. When using the protocol and method developed here, it is possible to perform perfusion quantification on different scanners and analysis software and be able to compare the results. The current work is the first study that presents a comparison of bolus transit parameters derived from multiple systems and software packages.

Beyond the vascular profile: conventional DWI, IVIM and kurtosis in the assessment of hepatocellular carcinoma.

To describe the role of the Diffusion Weighted Imaging (DWI) in the assessment of hepatocellular carcinoma (HCC). Several electronic databases were evaluated in the present review. The search included articles published from January 2010 to May 2019. The references of all articles were also evaluated. All titles and abstracts were assessed, and only the studies of DWI in patients with HCC were retained. HCC is the most common primitive hepatic cancer. The non-invasive radiological criteria for HCC diagnosis are based on the presence of the specific vascular profile characterized by contrast uptake during arterial phase, defined as arterial hyperenhancement, followed by washout in the venous/portal phase. However, arterial hyperenhancement and wash out appearance have a sensitivity rate of 50-60% in lesion smaller than 2 cm. Therefore, other functional parameters have been introduced in the detection and characterization of HCC nodules. DWI has been applied to liver imaging as an excellent tool for detection and characterization of focal liver lesions, increasing clinical confidence and decreasing false positives. The assessment of DW images can be done qualitatively and quantitatively, through the apparent diffusion coefficient (ADC) map. Intravoxel incoherent motion (IVIM) is a more sophisticated analysis, a biexponential model, to better defining the relationship between signal attenuation and increasing b value that separately reproduces tissue diffusivity and tissue perfusion. Traditionally DWI approach to analyze data is founded on the hypothesis that water molecules diffuse within a voxel following a single direction with a Gaussian behavior without any restriction. However, according to the presence of microstructures, water molecules within biologic tissues exhibits a non-Gaussian phenomena proposed by Jensen in 2005 called Diffusion Kurtosis Imaging (DKI). This approach assesses the kurtosis coefficient (K) that shows the deviance of diffusion from a Gaussian approach, and the diffusion coefficient (D) with the correction of non-Gaussian bias. DKI is an advanced DWI model that quantifies non-Gaussian behavior of diffusion and provides both a corrected ADC, as well as the excess kurtosis of tissue, a measure of the extent to which tissue diffusion deviates from a Gaussian pattern. It is believed that the DKI model is more sensitive to tissue microstructural complexity than standard DW. DWI should be an integral part of study protocol for HCC patients, considering the great advantages due to DWI and DWI-based approaches in detection and characterization of HCC.

Pyogenic Liver Abscesses Caused by Acute Appendicitis: Frequency and Diagnostic and Therapeutic Recommendations.

Background: Pyogenic liver abscesses (PLA) are caused by biliary diseases or hematogenous spreading of mostly intra-abdominal infections. Liver abscesses resulted in hematogenous spreading of infections via the portal vein, such as abscesses caused by acute appendicitis. Pyogenic liver abscesses associated with appendicitis have rarely been described in the literature, especially in adults. The standard therapeutic procedures for liver abscesses are broad-spectrum antibiotic therapy and percutaneous drainage. Surgery for liver abscesses is required in cases of unsuccessful processes. Patients and Methods: A retrospective analysis of patients with liver abscesses between January 2005 and June 2013 was performed. Parameters investigated included demographics, etiologies of abscesses, treatment modalities, and germ spectrum including antibiotic profile. Five cases of PLA caused by appendicitis were reviewed in detail. Results: During the study period, 49 patients with PLA and 1,986 patients with acute appendicitis were treated in our hospital. Twenty-one patients with PLA were treated with antibiotic agents and computed tomography (CT)-guided drainage. Liver resections were necessary in 29 of the patients with PLA. In five patients with PLA, abscesses were caused by an acute appendicitis (9.4% of all PLA, 0.25% of all appendicitis operations). Diagnosis of appendicitis as cause of PLA was made during surgery for liver resections in three patients. Previous imaging was not clear in all cases of PLA caused by appendicitis. The most common pre-operative symptoms in patients with PLA caused by appendicitis were fever and right upper quadrant tenderness. Discussion: Pyogenic liver abscesses caused by acute appendicitis are rare. In the study period of eight and one-half years nearly 2,000 cases of acute appendicitis were treated and five of these patients developed liver abscesses (0.25%). Pyogenic liver abscesses should be considered in patients with unusual high infectious parameters, septic symptoms, and detection of unknown liver lesions.

Liver findings in patients with Carney complex, germline PRKAR1A pathogenic variants, and link to cardiac myxomas.

This study aimed to evaluate liver involvement in patients with Carney complex (CNC) based on a large cohort and to analyze any germline PRKAR1A genotype-phenotype association of liver disease. The study included 83 patients with CNC, followed between 1995 and 2018 at a tertiary research center. We reviewed liver images, recorded types and number of lesions and analyzed per genotype: all patients were sequenced for the PRKAR1A gene. A total of 29/83 patients (24.0%) had liver radiological findings. Patients with liver lesion had a significantly higher rate of pathogenic variants detected in the PRKAR1A gene (72.4 vs 38.9%, P = 0.005, respectively). Patients with a pathogenic variant detected on germline PRKAR1A analysis had a higher risk for having a liver lesion compared with patients with wild-type (WT) PRKAR1A alleles (21/42 (50.0%) vs 8/41 (19.5%), respectively, P = 0.004). Among patients with liver lesions, those with a nonsense PRKAR1A pathogenic-variant had more liver lesions (7/7) than among those with other pathogenic-variant types (8/22, P = 0.001). In multivariable analysis, detection of liver lesion(s) was associated with an odds ratio of 5.2 for cardiac myxomas (95% CI 1.55-17.49, P = 0.008). In conclusion, patients with CNC, particularly with a PRKAR1A pathogenic variant, have a higher rate of liver lesions. Additionally, liver lesions are associated with a high risk for cardiac myxomas in this population.

Contrast-enhanced ultrasound imaging of the liver: a review of the clinical evidence for SonoVue and Sonazoid.

Contrast-enhanced ultrasound (CEUS) has become an established modality in various clinical indications for liver diseases. SonoVue®, a pure blood pure agent, and Sonazoid®, which exhibits an additional Kupffer phase, are contrast agents approved for liver imaging. This review discusses and compares the current clinical evidence for these two ultrasound contrast agents in the characterization and detection of focal liver lesions in the non-cirrhotic and cirrhotic liver, as well as for the use in interventional procedures such as liver biopsy guidance, and local ablation treatment monitoring. Reference is made to clinical studies which evaluated the accuracy of CEUS using a standard of reference, its safety, or to comparative studies of these two agents.