Screening for exclusion of high-risk bleeding features of esophageal varices in cirrhosis through CT and MRI.

BACKGROUND & AIM: Esophageal varices (EV) screening guidelines have evolved with improved risk stratification to avoid unnecessary esophagogastroduodenoscopy (EGD) in individuals with low bleeding risks. However, uncertainties persist in the recommendations for certain patient groups, particularly those with hepatocellular carcinoma (HCC) and/or receiving non-selective beta-blockers (NSBB) without prior endoscopy. This study assessed the efficacy of imaging in ruling out EVs and their high-risk features associated with bleeding in patients with cirrhosis and with HCC. We also evaluated the impact of NSBB on the detection of these characteristics. METHODS: A total of 119 patients undergoing EGD with CT and/or MRI within 90 days of the procedure were included. 87 patients had HCC. A new imaging grading system was developed utilizing the size of EVs and the extent of their protrusion into the esophagus lumen. The negative predictive value (NPV) of EVimaging(-) versus EVimaging (+) (grades 1-3) in ruling out the presence of EV and/or high-risk features by EGD was calculated. The predictive performance of imaging was determined by logistic regression. RESULTS: The NPV of imaging for detecting EV and high-risk features was 81 % and 92 %, respectively. Among HCC patients, the NPV for EV and high-risk features was 80 % and 64 %, respectively. Being on NSBB didn't statistically impact the imaging detection of EV. Imaging was a better predictor of high-risk EGD findings than Child-Turcotte-Pugh scores. CONCLUSIONS: Our results suggest that imaging can effectively rule out the presence of EV and high-risk features during EGD, even in patients with HCC and/or receiving NSBB.

Spectrum of Imaging Findings and Complications After Hepatic Transarterial Chemoembolization for Liver Tumors.

ABSTRACT: This study reviews the spectrum of imaging findings and complications after transarterial chemoembolization (TACE) for the treatment of primary liver tumors (hepatocellular carcinoma, cholangiocarcinoma) and liver metastases. The review encompasses a spectrum of imaging criteria for assessing treatment response, including the modified Response Evaluation Criteria in Solid Tumors guidelines, tumor enhancement, and apparent diffusion coefficient alterations.We discuss the expected posttreatment changes and imaging responses to TACE, describing favorable and poor responses. Moreover, we present cases that demonstrate potential complications post-TACE, including biloma formation, acute cholecystitis, abscesses, duodenal perforation, arterial injury, and nontarget embolization. Each complication is described in detail, considering its causes, risk factors, clinical presentation, and imaging characteristics.To illustrate these findings, a series of clinical cases is presented, featuring diverse imaging modalities including computed tomography, magnetic resonance imaging, and digital subtraction angiography.

Predicting survival of patients with advanced hepatocellular carcinoma receiving combination targeted immunotherapy: an evaluation of volumetric imaging parameters.

PURPOSE: To evaluate the potential of volumetric imaging in predicting survival of advanced hepatocellular carcinoma (HCC) patients receiving immunotherapy. METHODS: Retrospective analysis included 40 patients with advanced HCC who received targeted immunotherapy. Baseline and follow-up contrast-enhanced abdominal computed tomography (CT) scans were analyzed. The largest tumor was chosen as the index lesion. Viable tumor volume (qViable) and percentage tumor viability (%Viability) were calculated. Response Evaluation Criteria in Solid Tumors (RECIST) and Tumor volume change after treatment (qRECIST) were measured. Associations with overall survival (OS) were assessed. Cox regression analysis assessed the association between variables and overall survival (OS). A new prognostic stratification system was attempted to categorize patients based on significant predictors of OS. Patients with a baseline %viability > 69% and %viability reduction ≥ 8% were classified as better prognosis. Patients were stratified into better, intermediate and worse prognosis groups based on baseline %viability > 69% and ≥ 8% %viability reduction (better prognosis); baseline %viability ≤ 69% and < 8% %viability reduction (worse prognosis); remainder were intermediate prognosis. RESULTS: Patients with baseline %Viability > 69% and %Viability reduction ≥ 8% showed significantly higher OS. Multivariate analysis confirmed %Viability and %Viability reduction as significant predictors of OS. A prognostic stratification system using these parameters stratified patients into better, intermediate and worse prognosis groups, with the better prognosis showing highest OS. Most patients (97.5%) had stable disease by RECIST while the prognostic model re-classified 47.5% as better prognosis, 37.5% intermediate prognosis, and 15% worse prognosis. CONCLUSION: Volumetric parameters of %Viability and %Viability reduction predict OS in HCC patients undergoing immunotherapy.

Hepatic adenoma: evolution of a more individualized treatment approach.

BACKGROUND: Hepatic adenomas (HAs) are benign, solid liver lesions, which carry a risk of hemorrhage and malignant transformation. This review article highlights the advances in the diagnosis and management of HAs. METHODS: A comprehensive review was performed using MEDLINE/PubMed and Web of Science databases with a search period ending on September 30, 2023. Using PubMed, the terms "hepatocellular," "hepatic," and "adenoma" were searched. RESULTS: HA has been classified into at least 8 subtypes based on molecular pathology, each exhibiting unique histopathologic features, clinical considerations, and risk of malignant transformation. The most common subtype is inflammatory HA, followed by hepatocyte nuclear factor 1α-inactivated HA, ß-catenin exon 3-mutated HA (ßex3-HA), ß-catenin exon 7- or 8-mutated HA, sonic hedgehog HA, and unclassified HA. Magnetic resonance imaging is the best imaging method for diagnosis and can distinguish among HA subtypes based on fat and telangiectasia pathologic characteristics. The risk of malignant transformation varies among molecular subtypes, ranging from <1% to approximately 50%. Up to 42% of HAs present with spontaneous intratumoral hemorrhage and peritoneal hemorrhage. In general, only 15% to 20% of patients require surgery. HA larger than 5 cm are more likely to be complicated by bleeding and malignant transformation, regardless of subtype, and should generally be resected. In particular, ßex3-HA carries a high risk of malignant transformation and can be considered a true precancerous lesion. CONCLUSION: The management of HAs is based on a multidisciplinary approach. Clinical decision-making should integrate information on gender, tumor size, and HA subtyping. In the future, patients with HA will benefit from novel medical therapies tailored to the individual molecular subtypes.

Utilization of texture features of volumetric ADC maps in differentiating between serous cystadenoma and intraductal papillary neoplasms.

INTRODUCTION: The rising incidence of incidental detection of pancreatic cystic neoplasms has compelled radiologists to determine new diagnostic methods for the differentiation of various kinds of lesions. We aim to demonstrate the utility of texture features extracted from ADC maps in differentiating intraductal papillary mucinous neoplasms (IPMN) from serous cystadenomas (SCA). METHODS: This retrospective study was performed on 136 patients (IPMN = 87, SCA = 49) split into testing and training datasets. A total of 851 radiomics features were extracted from volumetric contours drawn by an expert radiologist on ADC maps of the lesions. LASSO regression analysis was used to determine the most predictive set of features and a radiomics score was developed based on their respective coefficients. A hyper-optimized support vector machine was then utilized to classify the lesions based on their radiomics score. RESULTS: A total of four Wavelet features (LHL/GLCM/LCM2, HLL/GLCM/LCM2, /LLL/First Order/90percent, /LLL/GLCM/MCC) were selected from all of the features to be included in our classifier. The classifier was optimized by altering hyperparameters and the trained model was applied to the validation dataset. The model achieved a sensitivity of 92.8, specificity of 90%, and an AUC of 0.97 in the training data set, and a sensitivity of 83.3%, specificity of 66.7%, and AUC of 0.90 in the testing dataset. CONCLUSION: A support vector machine model trained and validated on volumetric texture features extracted from ADC maps showed the possible beneficence of these features in differentiating IPMNs from SCAs. These results are in line with previous regarding the role of ADC maps in classifying cystic lesions and offers new evidence regarding the role of texture features in differentiation of potentially neoplastic and benign lesions.

Utilization of Radiomics Features Extracted From Preoperative Medical Images to Detect Metastatic Lymph Nodes in Cholangiocarcinoma and Gallbladder Cancer Patients: A Systemic Review and Meta-analysis.

OBJECTIVES: This study aimed to determine the methodological quality and evaluate the diagnostic performance of radiomics features in detecting lymph node metastasis on preoperative images in patients with cholangiocarcinoma and gallbladder cancer. METHODS: Publications between January 2005 and October 2022 were considered for inclusion. Databases such as Pubmed/Medline, Scopus, Embase, and Google Scholar were searched for relevant studies. The quality of the methodology of the manuscripts was determined using the Radiomics Quality Score and Quality Assessment of Diagnostic Accuracy Studies 2. Pooled results with corresponding 95% confidence intervals (CIs) were calculated using the DerSimonian-Liard method (random-effect model). Forest plots were used to visually represent the diagnostic profile of radiomics signature in each of the data sets pertaining to each study. Fagan plot was used to determine clinical applicability. RESULTS: Overall sensitivity was 0.748 (95% CI, 0.703-0.789). Overall specificity was 0.795 (95% CI, 0.742-0.839). The combined negative likelihood ratio was 0.299 (95% CI, 0.266-0.350), and the positive likelihood ratio was 3.545 (95% CI, 2.850-4.409). The combined odds ratio of the studies was 12.184 (95% CI, 8.477-17.514). The overall summary receiver operating characteristics area under the curve was 0.83 (95% CI, 0.80-0.86). Three studies applied nomograms to 8 data sets and achieved a higher pooled sensitivity and specificity (0.85 [0.80-0.89] and 0.85 [0.71-0.93], respectively). CONCLUSIONS: The pooled analysis showed that predictive models fed with radiomics features achieve good sensitivity and specificity in detecting lymph node metastasis in computed tomography and magnetic resonance imaging images. Supplementation of the models with biological correlates increased sensitivity and specificity in all data sets.

Outcome prediction for symptomatic patients with fibroids who underwent uterine artery embolization.

PURPOSE: To predict the clinical outcome of symptomatic patients with uterine leiomyomas who underwent uterine artery embolization (UAE), based on clinical and radiological features. METHODS: Patients with symptomatic uterine leiomyomas who underwent UAE from March 2010 to September 2019 were consecutively included in this retrospective study. Patients with persistent or recurrent symptoms and those who needed repeated UAE, myomectomy, or hysterectomy following the initial treatment were considered to have a poor outcome after UAE. The total and enhancing volume of the dominant leiomyoma in each location and uterine volume were obtained before and after UAE. Univariate and multivariate Cox proportional hazard analyses were used to evaluate the parameters that could predict poor outcome. RESULTS: A total of 116 patients (mean age, 45 ± 5 years) were included. Forty-six patients (46/116, 39.7%) showed poor outcome. Cox regression analysis showed higher hazard of poor outcome for younger patients vs. older patients (HR: 0.92, p-value: 0.01), patients with adenomyosis vs. patients without adenomyosis (HR: 2.47, p-value < 0.01), patients with adenomyosis thickness > 2.5 cm before UAE vs. patients without adenomyosis (HR: 4.2, p-value < 0.01) and for patients with intramural fibroid enhancement volume > 440 cm3 compared to patients with no intramural fibroids (p-value: 0.06). Multivariate Cox regression analysis including age, the thickness of adenomyosis, and intramural leiomyoma volume of enhancement before UAE was chosen as the best model to predict the outcome. CONCLUSIONS: Pretreatment clinical and MRI features could identify patients with a higher risk for poor outcome after UAE.

Differentiation between small hepatocellular carcinoma (<3 cm) and benign hepatocellular lesions in patients with Budd-Chiari syndrome: the role of multiparametric MR imaging.

Objective: To investigate the value of multiparametric MR imaging to differentiate between small hepatocellular carcinoma (s-HCC) versus benign liver lesions in patients with Budd-Chiari syndrome. Methods: 12 patients with benign hepatocellular lesions and 32 patients with small (<3 cm) HCCs were assessed. MRI images were reviewed by two radiologists blinded to the patient background information; lesion T1 and T2 signal intensities and ADC values were compared with the background liver. Enhancement of lesion relative to hepatic parenchyma [(T1Enh-T1liver)/T1liver] in the arterial, venous, and delayed phases was also compared between the two groups. A multivariable logistic model was developed using these categorical measures; the predictive value of the model was tested using the Area Under the Receiver operating characteristic (AU-ROC) curve for logistic models. P-values <0.05 were considered statistically significant. Results: There were consistent differences in T1lesion/T1liver, and T2lesion/T2liver, and ADClesion/ADCliver between benign hepatocellular lesions versus the sHCC group (p<0.001, p<0.001, p = 0.045, respectively). Lesion-to-background liver enhancement in the portal venous and delayed phases was different between the benign lesions versus sHCC (p=0.001). ROC analysis for the logistic model that included the T1 ratio, T2 ratio, and portal venous enhancement ratio demonstrated excellent discriminatory power with the area under the curve of 0.94. Conclusion: Multiparametric MR imaging is a useful method to help differentiate benign liver lesions from sHCC in patients with Budd-Chiari syndrome.

Management of Mucinous Cystic Neoplasms of the Liver.

BACKGROUND: Mucinous cystic neoplasms of the liver (MCN-L) including biliary cystadenomas (BCA) and biliary cystadenocarcinomas (BCAC) are rare cystic lesions that comprise less than 5% of all liver cysts and affect only a small subset of individuals. We herein review the current evidence regarding the clinical presentation, imaging characteristics, tumor markers, pathological findings, clinical management, and prognosis of MCN-L. METHODS: A comprehensive review of the literature was performed using MEDLINE/Pubmed and Web of Science databases. In PubMed, the terms "biliary cystadenoma," "biliary cystadenocarcinoma," and "non parasitic hepatic cysts" were queried to identify the most recent data on MCN-L. RESULTS: US imaging, CT, and MRI, as well as consideration of clinicopathological features, are required to appropriately characterize and diagnose hepatic cystic tumors. BCA are premalignant lesions and cannot be reliably differentiated from BCAC based on imaging alone. As such, both types of lesions should be treated with margin-negative surgical resection. Following surgical resection, recurrence is fairly low among patients with BCA and BCAC. Despite having worse long-term outcomes than BCA, the prognosis following surgical resection of BCAC still remains more favorable than other primary malignant liver tumors. CONCLUSION: MCN-L are rare cystic liver tumors that include BCA and BCAC, which can be difficult to differentiate based on imaging alone. Surgical resection remains the mainstay of management for MCN-L with recurrence being generally uncommon. Future multi-institutional studies are still required to better understand the biology behind BCA and BCAC to improve the care of patients with MCN-L.

Predictive role of radiomics features extracted from preoperative cross-sectional imaging of pancreatic ductal adenocarcinoma in detecting lymph node metastasis: a systemic review and meta-analysis.

Lymph node metastases are associated with poor clinical outcomes in pancreatic ductal adenocarcinoma (PDAC). In preoperative imaging, conventional diagnostic modalities do not provide the desired accuracy in diagnosing lymph node metastasis. The current review aims to determine the pooled diagnostic profile of studies examining the role of radiomics features in detecting lymph node metastasis in PDAC. PubMed, Google Scholar, and Embase databases were searched for relevant articles. The quality of the studies was examined using the Radiomics Quality Score and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tools. Pooled results for sensitivity, specificity, likelihood, and odds ratios with the corresponding 95% confidence intervals (CIs) were calculated using a random-effect model (DerSimonian-Liard method). No significant publication bias was detected among the studies included in this meta-analysis. The pooled sensitivity of the validation datasets included in the study was 77.4% (72.7%, 81.5%) and pooled specificity was 72.4% (63.8, 79.6%). The diagnostic odds ratio of the validation datasets was 9.6 (6.0, 15.2). No statistically significant heterogeneity was detected for sensitivity and odds ratio (P values of 0.3 and 0.08, respectively). However, there was significant heterogeneity concerning specificity (P = 0.003). The pretest probability of having lymph node metastasis in the pooled databases was 52% and a positive post-test probability was 76% after the radiomics features were used, showing a net benefit of 24%. Classifiers trained on radiomics features extracted from preoperative images can improve the sensitivity and specificity of conventional cross-sectional imaging in detecting lymph node metastasis in PDAC.

PET/MR enterography in inflammatory bowel disease: A review of applications and technical considerations.

Positron emission tomography (PET) magnetic resonance (MR) enterography is a novel hybrid imaging technique that is gaining popularity in the study of complex inflammatory disorders of the gastrointestinal system, such as inflammatory bowel disease (IBD). This imaging technique combines the metabolic information of PET imaging with the spatial resolution and soft tissue contrast of MR imaging. Several studies have suggested potential roles for PET/MR imaging in determining the activity status of IBD, evaluating treatment response, stratifying risk, and predicting long-term clinical outcomes. However, there are challenges in generalizing findings due to limited studies, technical aspects of hybrid MR/PET imaging, and clinical indications of this imaging modality. This review aims to further elucidate the possible role of PET/MR in IBD, highlight important technical aspects of imaging, and address potential pitfalls and prospects of this modality in IBDs.