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.

Diffuse infiltrative hepatocellular carcinoma: Multimodality imaging manifestations.

Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer, being the third most common cause of cancer-related death globally. HCC most frequently develops in the context of hepatic cirrhosis. HCC can manifest as various morphologic subtypes. Each pattern exhibits distinct behaviors in terms of imaging features, disease progression, response to therapy, and prognosis. While the nodular pattern is the most frequent subtype, infiltrative HCC is the least prevalent and makes up about 8%-20% of all HCC cases. Infiltrative HCC manifests as small tumor nodules that often spread across the entire liver or across a hepatic segment/lobe and is not identified as a focal tumor. On ultrasonography, infiltrative HCC presents as a markedly heterogeneous area with ill-defined echotexture, making it difficult to distinguish from background hepatic cirrhosis. On magnetic resonance imaging (MRI), infiltrating HCC typically manifests as a mild, poorly defined hepatic region with heterogeneous or homogenous aberrant signal intensity. Specifically, on T1-weighted MRI scans, infiltrating HCC frequently appears as largely hypointense and typically homogenous and mildly to moderately hyperintense on T2-weighted imaging. Infiltrative HCC frequently lacks a clearly defined boundary on cross-sectional imaging and can consequently fade into the background of the cirrhotic liver. As a result, infiltrating HCC is frequently not discovered until an advanced stage and has an associated poor prognosis. Thus, understanding imaging features associated with infiltrative HCC diagnosis is crucial for abdominal radiologists to ensure effective and timely care. We herein review imaging characteristics of infiltrative HCC.

Multimodality imaging of hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

Hepatocellular carcinoma and intrahepatic cholangiocarcinoma are the two most common primary malignant tumors of the liver. The similarities and variations in imaging characteristics that may aid in distinguishing between these two primary tumors will be discussed and outlined in this review. Knowledge of imaging techniques that are currently available would assist in the differentiation between these primary malignancies.

Vaccine-Derived Poliovirus Infection among Patients with Primary Immunodeficiency and Effect of Patient Screening on Disease Outcomes, Iran.

Patients with immunodeficiency-associated vaccine-derived poliovirus (iVDPV) are potential poliovirus reservoirs in the posteradication era that might reintroduce polioviruses into the community. We update the iVDPV registry in Iran by reporting 9 new patients. In addition to national acute flaccid paralysis surveillance, cases were identified by screening nonparalyzed primary immunodeficiency (PID) patients. Overall, 23 iVDPV patients have been identified since 1995. Seven patients (30%) never had paralysis. Poliovirus screening accelerated the iVDPV detection rate in Iran after 2014.The iVDPV infection rate among nonparalyzed patients with adaptive PID was 3.1% (7/224), several folds higher than previous estimates. Severe combined immunodeficiency patients had the highest risk for asymptomatic infection (28.6%) compared with other PIDs. iVDPV2 emergence has decreased after the switch from trivalent to bivalent oral poliovirus vaccine in 2016. However, emergence of iVDPV1 and iVDPV3 continued. Poliovirus screening in PID patients is an essential step in the endgame of polio eradication.

Candidiasis associated with very early onset inflammatory bowel disease: First IL10RB deficient case from the National Iranian Registry and review of the literature.

Defects in interleukin-10 (IL10) and interleukin-10 receptors (IL10R) are closely related to very early onset (infantile) inflammatory bowel disease (VEO-IBD). In the present study, we report a novel homozygous null mutation within interleukin-10 receptor B (IL10RB) gene in a child presenting with severe VEO-IBD. In accordance with previous reports, our patient manifested with chronic diarrhea, failure to thrive, intermittent fever and multiple anal ulcers associated with Candidiasis. Homozygous null mutation within IL10RB gene (c.92C > T, p.S31P) affecting the extracellular domain of protein was discovered in this patient. In conclusion, the diagnosis of IL-10R gene mutations should always be considered as a possible cause of refractory diarrhea and failure to thrive. Mutation analysis could help detect the genetic defects associated with these clinical manifestations and to determine the most appropriate treatment option for patients affected by this disease.

Clinical Manifestations, Immunological Characteristics and Genetic Analysis of Patients with Hyper-Immunoglobulin M Syndrome in Iran.

BACKGROUND: Hyper-immunoglobulin M (HIGM) syndrome is a rare heterogeneous group of primary immunodeficiency disorders characterized by low or absent serum levels of IgG and IgA along with normal or elevated serum levels of IgM. METHODS: Clinical and immunological data were collected from the 75 patients' medical records diagnosed in Children's Medical Center affiliated to Tehran University Medical Sciences and other Universities of Medical Sciences in Iran. Among 75 selected patients, 48 patients (64%) were analyzed genetically using targeted and whole-exome sequencing. RESULTS: The ratio of male to female was 2.9:1. The median age at the onset of the disease, time of diagnosis, and diagnostic delay were 10.5, 50, and 24 months, respectively. Pneumonia and lower respiratory tract infections (61.3%) were the most common complications. Responsible genes were identified in 35 patients (72.9%) out 48 genetically analyzed patients. Cluster of differentiation 40 ligand gene was the most mutated gene observed in 24 patients (68.5%) followed by activation-induced cytidine deaminase gene in 7 patients, lipopolysaccharide-responsive and beige-like anchor (1 patient), nuclear factor-kappa-B essential modulator (1 patient), phosphoinositide-3-kinase regulatory subunit 1 (1 patient), and nuclear factor kappa B subunit 1 (1 patient) genes. Nineteen (25.3%) patients died during the study period, and pneumonia was the major cause of death occurred in 6 (31.6%) patients. CONCLUSION: Physicians in our country should carefully pay attention to respiratory tract infections and pneumonia, particularly in patients with a positive family history. Further investigations are required for detection of new genes and pathways resulting in HIGM phenotype.

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.

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.

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.

Magnetic Resonance Imaging-Based Assessment of Pancreatic Fat Strongly Correlates With Histology-Based Assessment of Pancreas Composition.

OBJECTIVE: The aim of the study is to assess the relationship between magnetic resonance imaging (MRI)-based estimation of pancreatic fat and histology-based measurement of pancreatic composition. MATERIALS AND METHODS: In this retrospective study, MRI was used to noninvasively estimate pancreatic fat content in preoperative images from high-risk individuals and disease controls having normal pancreata. A deep learning algorithm was used to label 11 tissue components at micron resolution in subsequent pancreatectomy histology. A linear model was used to determine correlation between histologic tissue composition and MRI fat estimation. RESULTS: Twenty-seven patients (mean age 64.0 ± 12.0 years [standard deviation], 15 women) were evaluated. The fat content measured by MRI ranged from 0% to 36.9%. Intrapancreatic histologic tissue fat content ranged from 0.8% to 38.3%. MRI pancreatic fat estimation positively correlated with microanatomical composition of fat (r = 0.90, 0.83 to 0.95], P < 0.001); as well as with pancreatic cancer precursor ( r = 0.65, P < 0.001); and collagen ( r = 0.46, P < 0.001) content, and negatively correlated with pancreatic acinar ( r = -0.85, P < 0.001) content. CONCLUSIONS: Pancreatic fat content, measurable by MRI, correlates to acinar content, stromal content (fibrosis), and presence of neoplastic precursors of cancer.

The Additive Value of Radiomics Features Extracted from Baseline MR Images to the Barcelona Clinic Liver Cancer (BCLC) Staging System in Predicting Transplant-Free Survival in Patients with Hepatocellular Carcinoma: A Single-Center Retrospective Analysis.

BACKGROUND: To study the additive value of radiomics features to the BCLC staging system in clustering HCC patients. METHODS: A total of 266 patients with HCC were included in this retrospective study. All patients had undergone baseline MR imaging, and 95 radiomics features were extracted from 3D segmentations representative of lesions on the venous phase and apparent diffusion coefficient maps. A random forest algorithm was utilized to extract the most relevant features to transplant-free survival. The selected features were used alongside BCLC staging to construct Kaplan-Meier curves. RESULTS: Out of 95 extracted features, the three most relevant features were incorporated into random forest classifiers. The Integrated Brier score of the prediction error curve was 0.135, 0.072, and 0.048 for the BCLC, radiomics, and combined models, respectively. The mean area under the receiver operating curve (ROC curve) over time for the three models was 81.1%, 77.3%, and 56.2% for the combined radiomics and BCLC models, respectively. CONCLUSIONS: Radiomics features outperformed the BCLC staging system in determining prognosis in HCC patients. The addition of a radiomics classifier increased the classification capability of the BCLC model. Texture analysis features could be considered as possible biomarkers in predicting transplant-free survival in HCC patients.

Response Assessment of Primary Liver Tumors to Novel Therapies: an Imaging Perspective.

The latest developments in cancer immunotherapy, namely the introduction of immune checkpoint inhibitors, have led to a fundamental change in advanced cancer treatments. Imaging is crucial to identify tumor response accurately and delineate prognosis in immunotherapy-treated patients. Simultaneously, advances in image acquisition techniques, notably functional and molecular imaging, have facilitated more accurate pretreatment evaluation, assessment of response to therapy, and monitoring for tumor recurrence. Traditional approaches to assessing tumor progression, such as RECIST, rely on changes in tumor size, while new strategies for evaluating tumor response to therapy, such as the mRECIST and the EASL, rely on tumor enhancement. Moreover, the assessment of tumor volume, enhancement, cellularity, and perfusion are some novel techniques that have been investigated. Validation of these novel approaches should rely on comparing their results with those of standard evaluation methods (EASL, mRECIST) while considering the ultimate outcome, which is patient survival. More recently, immunotherapy has been used in the management of primary liver tumors. However, little is known about its efficacy. This article reviews imaging modalities and techniques for assessing tumor response and survival in immunotherapy-treated patients with primary hepatic malignancies.

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.