Differentiation Of Focal Liver Lesions Research Articles

A systematic review and meta-analysis of spectral CT to differentiate focal liver lesions

To determine the feasibility of spectral computed tomography (CT) in the differentiation of focal liver lesions from hepatocellular carcinoma (HCC) using a network meta-analysis (NMA). The review was completed in accordance with PRISMA guidelines. Searches of three medical databases were performed. A total of nine articles were found for the qualitative synthesis. The meta-analysis was performed on five studies for the normalised iodine concentration (NIC; which is the iodine concentration in the lesion divided by the iodine concentration in the aorta) and the lesion-normal parenchyma iodine ratio (LNR; which is the iodine concentration in the lesion divided by the iodine concentration in the non-tumour hepatic parenchyma) on portal venous and arterial phase images due to sufficient data. Spectral CT can be used to differentiate HCC from hepatic haemangioma (HH), focal nodular hyperplasia (FNH), regenerative nodules, neuroendocrine tumours (NETs), abscesses, and angiomyolipoma (AML). Hepatic metastases versus abscess and FNH versus HH could also be differentiated. The NMA demonstrated that HCC, NETs, and regenerative nodules could be differentiated due to lower quantitative iodine values. FNH, AML, and HH all had higher values. Spectral CT shows promise in differentiating focal liver lesions. Studies with larger sample sizes are warranted. Future studies should be performed comparing benign lesions using quantitative markers.

Influence of age on gadoxetic acid disodium-induced transient respiratory motion artifacts in pediatric liver MRI.

Gd-EOB-DTPA-enhanced liver MRI is frequently compromised by transient severe motion artifacts (TSM) in the arterial phase, which limits image interpretation for the detection and differentiation of focal liver lesions and for the recognition of the arterial vasculature before and after liver transplantation. The purpose of this study was to investigate which patient factors affect TSM in children who undergo Gd-EOB-DTPA-enhanced liver MRI and whether younger children are affected as much as adolescents. One hundred and forty-eight patients (65 female, 83 male, 0.1-18.9 years old), who underwent 226 Gd-EOB-DTPA-enhanced MRIs were included retrospectively in this single-center study. The occurrence of TSM was assessed by three readers using a four-point Likert scale. The relation to age, gender, body mass index, indication for MRI, requirement for sedation, and MR repetition was investigated using uni- and multivariate logistic regression analysis. In Gd-EOB-DTPA-enhanced MRIs, TSM occurred in 24 examinations (10.6%). Patients with TSM were significantly older than patients without TSM (median 14.3 years; range 10.1-18.1 vs. 12.4 years; range 0.1-18.9, p<0.001). TSM never appeared under sedation. Thirty of 50 scans in patients younger than 10 years were without sedation. TSM were not observed in non-sedated patients younger than 10 years of age (p = 0.028). In a logistic regression analysis, age remained the only cofactor independently associated with the occurrence of TSM (hazard ratio 9.152, p = 0.049). TSM in Gd-EOB-DTPA-enhanced liver MRI do not appear in children under the age of 10 years.

Saliency-based 3D convolutional neural network for categorising common focal liver lesions on multisequence MRI

BackgroundThe imaging features of focal liver lesions (FLLs) are diverse and complex. Diagnosing FLLs with imaging alone remains challenging. We developed and validated an interpretable deep learning model for the classification of seven categories of FLLs on multisequence MRI and compared the differential diagnosis between the proposed model and radiologists.MethodsIn all, 557 lesions examined by multisequence MRI were utilised in this retrospective study and divided into training–validation (n = 444) and test (n = 113) datasets. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the performance of the model. The accuracy and confusion matrix of the model and individual radiologists were compared. Saliency maps were generated to highlight the activation region based on the model perspective.ResultsThe AUC of the two- and seven-way classifications of the model were 0.969 (95% CI 0.944–0.994) and from 0.919 (95% CI 0.857–0.980) to 0.999 (95% CI 0.996–1.000), respectively. The model accuracy (79.6%) of the seven-way classification was higher than that of the radiology residents (66.4%, p = 0.035) and general radiologists (73.5%, p = 0.346) but lower than that of the academic radiologists (85.4%, p = 0.291). Confusion matrices showed the sources of diagnostic errors for the model and individual radiologists for each disease. Saliency maps detected the activation regions associated with each predicted class.ConclusionThis interpretable deep learning model showed high diagnostic performance in the differentiation of FLLs on multisequence MRI. The analysis principle contributing to the predictions can be explained via saliency maps.

The role of MDCT and MRI in the diagnosis of focal liver diseases

Despite the great technical achievements in the field of tomographic examinations (CT, MRI), the problem of differentiation of focal liver lesions cannot always be solved only in a non-invasive way. At the same time, MRI with a hepatospecific agent, gadoxetic acid, can solve many problems, primarily related to the diagnosis of liver metastases and monitoring of nodules in cirrhotic liver. The aim. To show the advantages of MRI with hepatobiliary MRI contrast agents as the final phase of non-invasive diagnosis of focal liver lesions. Material and methods . Abstracts of 183 scientific articles (2010–2019) were selected in the PubMed information and analytical system for the keywords “focal liver lesion” and “gadoxetic acid”. Articles about special aspects of MRI examination or general information were excluded. 29 full-text articles were selected for analysis. Results . The analysis data are grouped in three categories as “diagnosis of liver metastases”, “diagnosis of HCC against the background of normal hepatic parenchyma”, “MRI diagnosis of HCC against the background of cirrhosis”. Conclusion. The main achievement of MRI diagnostics with gadoxetic acid is the differentiation of small focal liver lesions, including metastases, regenerative nodes, dysplastic nodes, and highly differentiated HCC. This allows you to increasingly avoid invasive methods in the diagnosis of focal liver lesions. Integrated MRI technologies (MRI-DVI and MRI with gadoxetic acid) are currently the most informative, safe and in demand. In MRI with hepatobiliary contrast agents, the intensity of the HCC signal in the hepatospecific phase is considered as an imaging tumor biomarker. Border small liver nodules are usually not hypervascular, they are hypointensive in the hepatospecific phase.

Intraoperative Shear Wave Elastography vs. Contrast-Enhanced Ultrasound for the Characterization and Differentiation of Focal LiverLesions to Optimize Liver Tumor Surgery.

Assessment of intraoperative quantitative shear wave elastography (SWE) and contrast-enhanced ultrasound (CEUS) for the characterization of focal liver lesions (FLLs) during liver surgery using postoperative histopathological results as the gold standard. US data of 79 consecutive patients with 98 FLLs who underwent liver surgery between 08/2015 - 06/2017 were prospectively acquired and retrospectively analyzed. Multifrequency linear/T-shaped probes (6 - 9 MHz) were used to store cine loops of at least 5 s and images of B-mode, SWE and CEUS. The first CEUS loop was continuously documented over 1 min. in each case. Quantitative SWE analysis of FLLs was performed by placing 5 regions of interest to measure shear wave speed (m/s) and stiffness (kPa). CEUS was evaluated during the arterial, portal venous and late phase after i. v. bolus injections of 2.4 - 10 ml sulfur hexafluoride microbubbles. Postoperative histopathology after tumor resection or intraoperative biopsy was obtained to confirm findings of SWE and CEUS. Of 98 FLLs in 79 patients (mean age: 58 years sd ± 12y) 88 were malignant and 10 were benign ranging from 0.69 to 15.2 cm in size (mean: 2.8 cm, sd ± 2.25 cm). SWE characterized 73/88 FLLs correctly as malignant and 7/10 as benign using a cut-off value of 2.5 m/s/21.3 kPa (p < 0.0005). The sensitivity was 83 %, specificity 70 %, accuracy 82 %. CEUS could correctly identify 86/88 malignant and 8/10 benign FLLs. The sensitivity was 98 %, specificity 80 %, accuracy 96 %. SWE could correctly identify 2 malignant FLLs which CEUS falsely characterized as benign. Intraoperative CEUS and SWE are excellent tools for the highly accurate visualization, characterization and malignancy assessment of hepatic tumors during liver surgery.

Triphasic Computed Tomography Hounsfield and Pattern in Differentiation of Focal Liver Lesions

Triphasic Computed Tomography Hounsfield and Pattern in Differentiation of Focal Liver Lesions

Diffusion Weighted Magnetic Resonance Imaging for the Classification of Focal Liver Lesions as Benign or Malignant.

To assess the role of diffusion weighted imaging sequence (DWI), routinely used in hepatic magnetic resonance imaging (MRI) for the differentiation of focal liver lesions (FLLs) as benign or malignant. 99 FLLs assessed by liver MRI in 80 patients were included in the present study. All lesions were retrospectively analyzed by two experienced radiologists, independent from each other, who were not aware of the previous results obtained by using different imaging techniques. All included FLLs had a final histological diagnosis or a final diagnosis based on consensus reading by two experienced radiologists and follow-up at 6 months. The FLLs signal was qualitatively appreciated on the b-800 sequences and on the apparent diffusion coefficient (ADC) map. The ADC value of each FLL was measured and the ADC ratio between the ADC value of the assessed FLL and that of the surrounding liver parenchyma were calculated. The mean ADC value for benign FLLs as assessed by the two independent readers was 1.78 x 10¯³ and 1.72 x 10¯³, respectively. The mean ADC value for malignant FLLs was 0.92 x 10¯³ for the first reader and 0.95 x 10¯³ for the second reader. The mean ADC ratio for benign FLLs was 1.91 and 1.85 for the two readers and for malignant FLLs was 0.91 and 0.94, respectively. Using an ADC value lower than 1.024 x 10¯³ offers a specificity of 100% and a sensitivity of 62.5% for the diagnosis of malignant FLLs. The ADC value is an indicator which is less prone to interobserver variability (correlation of 0.919→1). The ADC ratio has, as the analysis of the ROC curve shows, the best predictive value for differentiation between benign and malignant FLLs. Analysis of the signal intensity on the DWI b-800 image alone is of no significance in differentiating benign from malignant FLLs (p>0.05). The ADC value and the ADC ratio assessed on liver DWI are useful diagnostic tools in the differential diagnosis of benign vs. malignant FLLs. Quantitative methods such as calculating the ADC value or ADC ratio have better diagnostic value than the qualitative techniques.

Magnetic resonance imaging of the chest in the evaluation of cancer patients: state of the art.

Recent studies have demonstrated that the use of paramagnetic hepatobiliary contrast agents in the acquisition of magnetic resonance images remarkably improves the detection and differentiation of focal liver lesions, as compared with extracellular contrast agents. Paramagnetic hepatobiliary contrast agents initially show the perfusion of the lesions, as do extracellular agents, but delayed contrast-enhanced images can demonstrate contrast uptake by functional hepatocytes, providing further information for a better characterization of the lesions. Additionally, this intrinsic characteristic increases the accuracy in the detection of hepatocellular carcinomas and metastases, particularly the small-sized ones. Recently, a hepatobiliary contrast agent called gadolinium ethoxybenzyl dimeglumine, that is simply known as gadoxetic acid, was approved by the National Health Surveillance Agency for use in humans. The authors present a literature review and a practical approach of magnetic resonance imaging utilizing gadoxetic acid as contrast agent, based on patients' images acquired during their initial experiment.

Diffusion weighted imaging of liver lesions suspect for metastases: Apparent diffusion coefficient (ADC) values and lesion contrast are independent from Gd-EOB-DTPA administration

PurposeGadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced liver MRI is widely used for detection and differentiation of focal liver lesions. Diffusion weighted imaging (DWI) including apparent diffusion coefficient (ADC) measurements is increasingly utilised as a fast and, with limitations, quantitative method for liver lesion detection and characterisation. Herein we investigate whether the administration of Gd-EOB-DTPA affects DWI. Materials and methods31 consecutive patients referred to standardised liver MRI (1.5T, Gd-EOB-DTPA, 0.025mmol/kg) were retrospectively reviewed. All underwent a breathhold DWI sequence before and after contrast agent administration (EPI-DWI, TR/TE (effective): 2100/62ms, b-values: 0 and 800s/mm2). Patients with previously treated liver lesions were excluded. Signal intensity of lesion, parenchyma and noise on DWI images as well as the ADC value were measured after identification by two observers in consensus using manually placed regions of interest. The reference standard was imaging follow-up determined separately by two radiologists. Data analysis included signal-to-noise (SNR) ratio and contrast-to-noise ratio (CNR) calculations, comparisons were drawn by employing multiple Bonferroni corrected Wilcoxon signed-rank tests. Results50 malignant and 39 benign lesions were identified. Neither SNR, CNR nor ADC values showed significant differences between pre- and postcontrast DWI. Both pre- and postcontrast ADC values differed significantly between benign and malignant lesions (P<0.001). ConclusionWe did not identify a significant influence of Gd-EOB-DTPA on DWI of liver lesions. This allows for individual tailoring of imaging protocols according to clinical needs.

Differentiation of Focal Liver Lesions: Usefulness of Parametric Imaging with Contrast-enhanced US

To evaluate whether parametric imaging with contrast material-enhanced ultrasonography (US) is superior to visual assessment for the differential diagnosis of focal liver lesions (FLLs). This study had institutional review board approval, and verbal patient informed consent was obtained. Between August 2005 and October 2008, 146 FLLs in 145 patients (63 women, 82 men; mean age, 62.5 years; age range, 22-89 years) were imaged with real-time low-mechanical-index contrast-enhanced US after a bolus injection of 2.4 mL of a second-generation contrast agent. Clips showing contrast agent uptake kinetics (including arterial, portal, and late phases) were recorded and subsequently analyzed off-line with dedicated image processing software. Analysis of the dynamic vascular patterns (DVPs) of lesions with respect to adjacent parenchyma allowed mapping DVP signatures on a single parametric image. Cine loops of contrast-enhanced US and results from parametric imaging of DVP were assessed separately by three independent off-site readers who classified each lesion as benign, malignant, or indeterminate. Sensitivity, specificity, accuracy, and positive and negative predictive values were calculated for both techniques. Interobserver agreement (κ statistics) was determined. Sensitivities for visual interpretation of cine loops for the three readers were 85.0%, 77.9%, and 87.6%, which improved significantly to 96.5%, 97.3%, and 96.5% for parametric imaging, respectively (P < .05, McNemar test), while retaining high specificity (90.9% for all three readers). Accuracy scores of parametric imaging were higher than those of conventional contrast-enhanced US for all three readers (P < .001, McNemar test). Interobserver agreement increased with DVP parametric imaging compared with conventional contrast-enhanced US (change of κ from 0.54 to 0.99). Parametric imaging of DVP improves diagnostic performance of contrast-enhanced US in the differentiation between malignant and benign FLLs; it also provides excellent interobserver agreement.

Effect of a Comprehensive Image Processing on Radiologists’ Performance in Differential Diagnosis of Liver Lesions Using CT and MRI

To evaluate whether a comprehensive image processing method as CAD using CT and MRI can improve the radiologists' diagnosis performance in the differentiation of focal liver lesions. A clinical image database used in this study consists of 14 cases of each lesion including hepatic cysts, hepatocellular carcinoma (HCC), metastatic liver cancer, and hemangioma. This technique by using MR images obtained with various imaging sequences and a series of dynamic MR and dynamic CT images is designed for the enhancement of liver lesions pixel by pixel. In this method, we make the pixel sizes of MR images the same size of CT image by using tri-linear interpolation technique. Then the 3D image registration technique based on mutual information is applied for the matching of images. The image intensity pattern with and without contrast enhancement is determined as the template for the differential detection of each lesion. Pixel-by-pixel cross-correlation coefficient is calculated for the enhancement of each lesion. The radiologists' performance in distinguishing between the liver lesion was evaluated by receiver operating characteristic analysis (ROC) with a continuous rating scale. In free-response ROC analysis, true positive fractions were 75%, 87%, 85%, and 86% for hepatic cysts, HCC, metastatic liver cancer and hemangioma, respectively. Furthermore, average number of false positive and false negatives per image was 3.4 and 0.3, respectively. When radiologists made differential diagnosis of the liver lesions with the images of this technique, diagnostic accuracy was statistically significantly improved compared to the diagnostic accuracy without the images of this technique. The average area under the ROC curve (Az value) improved from 0.881 to 0.964 (p=0.069) for the differential diagnosis of hepatic cysts. Furthermore, the Az value of HCC, metastatic liver cancer, and hemangioma improved from 0.951 to 0.979 (p=0.040), from 0.946 to 0.976 (p=0.226), and from 0.966 to 0.987(p=0.045), respectively. A comprehensive image processing method as CAD using CT and MRI can improve the radiologists' diagnostic performance in the differentiation of focal liver lesions. CLINICAL RELEVANCE/APPLICATION: This method improved the performance of differential detection of liver lesions from a large number of images and it would save radiologists' reading time, and thus could assist their diagnosis.

Differentiation of focal liver lesions using three-dimensional ultrasonography: Retrospective and prospective studies

To differentiate focal liver lesions based on enhancement patterns using three-dimensional ultrasonography (3D US) with perflubutane-based contrast agent. Two hundred and eighty two patients with focal liver lesions, including 168 hepatocellular carcinomas (HCCs), 63 metastases, 40 hemangiomas and 11 focal nodular hyperplasias (FNHs), were examined by 3D US with perflubutane-based contrast agent. Tomographic ultrasound images and sonographic angiograms were reconstructed. Among 282 lesions, enhancement patterns of 163 lesions between January 2007 and October 2007 were analyzed retrospectively. Then from November 2007 to May 2008, compared with contrast-enhanced (CE) 2D US, CE 3D US was performed on 119 lesions for prospective differential diagnosis. Sensitivity, specificity, area under receiver operating characteristic curve (A(z)) and inter-reader agreement were assessed. With the tridimensional view, dominant enhancement patterns were revealed as diffuse enhancement or peripheral ring-like enhancement, followed with washout change for HCCs or metastases, respectively, and peripheral nodular enhancement or diffuse enhancement with spoke-wheel arteries, followed by persistent enhancement for hemangiomas or FNHs, respectively. At CE 3D US, the prospective differentiation of lesions showed sensitivity 92% (mean for two readers), specificity 91% and A(z) value 0.95 for HCCs, 84%, 97%, and 0.95 for metastases, 91%, 98%, and 0.98 for hemangiomas and 80%, 99%, and 0.99 for FNHs, respectively, while good to excellent inter-reader agreement was achieved. No significant difference exists between prospective diagnosis accuracy at CE 3D US and that at CE 2D US. CE 3D US provides a spatial perspective for liver tumor enhancement, and could help in differentiating focal liver lesions.

Application of an artificial neural network to the computer-aided differentiation of focal liver disease in MR imaging

The differentiation of focal liver lesions in magnetic resonance (MR) imaging is primarily based on the intensity and homogeneity of lesions with different imaging sequences. However, these imaging findings are falsely interpreted in some patients because of the complexities involved. Our aim is to establish a computer-aided diagnosis system named LiverANN for classifying the pathologies of focal liver lesions into five categories using the artificial neural network (ANN) technique. On each MR image, a region of interest (ROI) in the focal liver lesion was delineated by a radiologist. The intensity and homogeneity within the ROI were calculated automatically, producing numerical data that were analyzed by feeding them into the LiverANN as inputs. Outputs were the following five pathologic categories of hepatic disease: hepatic cyst, hepatocellular carcinoma, dysplasia in cirrhosis, cavernous hemangioma, and metastasis. Of the 320 MR images obtained from 80 patients (four images per patient) with liver lesions, our LiverANN classified 50 cases of a training set into five types of liver lesions with a training accuracy of 100% and 30 test cases with a testing accuracy of 93%. The experiment demonstrated that our LiverANN, which functions as a computer-aided differentiation tool, can provide radiologists with a second opinion during the radiologic diagnostic procedure.

Clinical value of MRI liver-specific contrast agents: a tailored examination for a confident non-invasive diagnosis of focal liver lesions

Screening of the liver for hepatic lesion detection and characterization is usually performed with either ultrasound or CT. However, both techniques are suboptimal for liver lesion characterization and magnetic resonance (MR) imaging has emerged as the preferred radiological investigation. In addition to unenhanced MR imaging techniques, contrast-enhanced MR imaging can demonstrate tissue-specific physiological information, thereby facilitating liver lesion characterization. Currently, the classes of contrast agents available for MR imaging of the liver include non-tissue-specific extracellular gadolinium chelates and tissue-specific hepatobiliary or reticuloendothelial agents. In this review, we describe the MR features of the more common focal hepatic lesions, as well as appropriate imaging protocols. A special emphasis is placed on the clinical use of non-specific and liver-specific contrast agents for differentiation of focal liver lesions. This may aid in the accurate diagnostic workup of patients in order to avoid invasive procedures, such as biopsy, for lesion characterization. A diagnostic strategy that considers the clinical situation is also presented.

Focal liver lesions: Role of contrast-enhanced ultrasound

The introduction of microbubble contrast agents and the development of contrast-specific techniques have opened new possibilities in liver imaging. Initially, only intermittent imaging with Doppler detection was available. Second-generation contrast agents and low mechanical index real-time scanning techniques are decisive advances that enable convenient liver examinations with high sensitivity and specificity. Hepatic lesions usually show typical perfusion and enhancement patterns through the various contrast phases, which help their characterization. Several published studies and the daily clinical routine show that, as opposed to conventional ultrasound (US), contrast-enhanced US can substantially improve detection and differentiation of focal liver lesions. Today, contrast-enhanced US is the dynamic imaging modality of choice for differentiation of focal liver lesions. Contrast uptake patterns of the most relevant liver lesions, as well as important clinical indications are presented and discussed.

Characterization of focal liver lesions with superparamagnetic iron oxide-enhanced MR imaging: value of distributional phase T1-weighted imaging.

ObjectiveTo determine the potential value of distributional-phase T1-weighted ferumoxides-enhanced magnetic resonance (MR) imaging for tissue characterization of focal liver lesions.Materials and MethodsFerumoxides-enhanced MR imaging was performed using a 1.5-T system in 46 patients referred for evaluation of known or suspected hepatic malignancies. Seventy-three focal liver lesions (30 hepatocellular carcinomas [HCC], 12 metastases, 15 cysts, 13 hemangiomas, and three cholangiocarcinomas) were evaluated. MR imaging included T1-weighted double-echo gradient-echo (TR/TE: 150/4.2 and 2.1 msec), T2*-weighted gradient-echo (TR/TE: 180/12 msec), and T2-weighted turbo spin-echo MR imaging at 1.5 T before and after intravenous administration of ferumoxides (15 mmol/kg body weight). Postcontrast T1-weighted imaging was performed within eight minutes of infusion of the contrast medium (distributional phase). Both qualitative and quantitative analysis was performed.ResultsDuring the distributional phase after infusion of ferumoxides, unique enhancement patterns of focal liver lesions were observed for hemangiomas, metastases, and hepatocellular carcinomas. On T1-weighted GRE images obtained during the distributional phase, hemangiomas showed a typical positive enhancement pattern of increased signal; metastases showed ring enhancement; and hepatocellar carcinomas showed slight enhancement. Quantitatively, the signal-to-noise ratio of hemangiomas was much higher than that of other tumors (p < .05) and was similar to that of intrahepatic vessels. This finding permitted more effective differentiation between hemangiomas and other malignant tumors.ConclusionT1-weighted double-echo FLASH images obtained soon after the infusion of ferumoxides, show characteristic enhancement patterns and improved the differentiation of focal liver lesions.