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.

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.

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.

Evaluating protein cross-linking as a therapeutic strategy to stabilize SOD1 variants in a mouse model of familial ALS.

Mutations in the gene encoding Cu-Zn superoxide dismutase 1 (SOD1) cause a subset of familial amyotrophic lateral sclerosis (fALS) cases. A shared effect of these mutations is that SOD1, which is normally a stable dimer, dissociates into toxic monomers that seed toxic aggregates. Considerable research effort has been devoted to developing compounds that stabilize the dimer of fALS SOD1 variants, but unfortunately, this has not yet resulted in a treatment. We hypothesized that cyclic thiosulfinate cross-linkers, which selectively target a rare, 2 cysteine-containing motif, can stabilize fALS-causing SOD1 variants in vivo. We created a library of chemically diverse cyclic thiosulfinates and determined structure-cross-linking-activity relationships. A pre-lead compound, "S-XL6," was selected based upon its cross-linking rate and drug-like properties. Co-crystallographic structure clearly establishes the binding of S-XL6 at Cys 111 bridging the monomers and stabilizing the SOD1 dimer. Biophysical studies reveal that the degree of stabilization afforded by S-XL6 (up to 24°C) is unprecedented for fALS, and to our knowledge, for any protein target of any kinetic stabilizer. Gene silencing and protein degrading therapeutic approaches require careful dose titration to balance the benefit of diminished fALS SOD1 expression with the toxic loss-of-enzymatic function. We show that S-XL6 does not share this liability because it rescues the activity of fALS SOD1 variants. No pharmacological agent has been proven to bind to SOD1 in vivo. Here, using a fALS mouse model, we demonstrate oral bioavailability; rapid engagement of SOD1G93A by S-XL6 that increases SOD1G93A's in vivo half-life; and that S-XL6 crosses the blood-brain barrier. S-XL6 demonstrated a degree of selectivity by avoiding off-target binding to plasma proteins. Taken together, our results indicate that cyclic thiosulfinate-mediated SOD1 stabilization should receive further attention as a potential therapeutic approach for fALS.

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.

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.

Prevalence of different LI-RADS v2018 categories in high-risk patients undergoing CT- or MRI-based screening for hepatocellular carcinoma.

PURPOSE: To estimate the prevalence of Liver Imaging Reporting and Data System (LI-RADS, LR) v2018 categories reported on CT or MRI performed for hepatocellular carcinoma (HCC) screening. MATERIALS AND METHODS: This retrospective study included all reports for CT and MRI exams performed for HCC screening patients between 8/2018 and 4/2020. Patients with ultrasound, CT, or MRI of the abdomen within two years of the index exam were excluded. From each radiology report, we extracted number of reported liver observations, and LI-RADS v2018 category for each observation. RESULTS: There were 329 patients (170 [52%] male, mean age 59 years [SD 12]), of whom 177 (54%) had MRI with gadoxetate, 72 (22%) had MRI with extracellular contrast, 7 (2%) had MRI with unspecified contrast, and 73 (22%) had CT. Of 329 patients, 199 (60%) had no reported observations; 130 patients had 166 reported observations: 114 (68.7%) LR-1, 8 (4.8%) LR-2, 21 (12.6%) LR-3, 6 (3.6%) LR-4, 13 (7.8%) LR-5, 3 (1.8%) LR-M, and 1 (0.6%) LR-TIV. Of 114 LR-1 observations, 78 (68%) were cysts, 17 (15%) were hemangiomas, 12 (11%) were vascular shunts, 3 (3%) were focal nodular hyperplasia, 2 (2%) were siderotic nodules, 1 (1%) was a lipoma, and 1 (1%) was biliary hamartoma. There were 23 observations with probably or definitely malignant categories (LR-4, LR-5, LR-M or LR- TIV), reported in 20/329 (6%) of patients. CONCLUSION: In a cohort of at-risk patients undergoing contrast-enhanced CT/MRI for HCC screening, 60% of had no liver observations, and 6 % had probably or definitely malignant observations. IMPLICATIONS FOR PATIENT CARE: The prevalence of LI-RADS v2018 categories on CT or MR exams used for HCC screening can help develop screening criteria and assess cost-effectiveness of surveillance strategies with CT and MRI.

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.

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.

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.

Factors associated with the healing time of pemphigus vulgaris oral lesions: A prospective study.

OBJECTIVES: This study determines the healing time of lesions on different locations and the contributing factors to the healing time in patients with pemphigus. METHODS: In this prospective study, newly diagnosed patients with mucosal lesions were included. A dermatologist evaluated the lesions, disease status, side effects and assigned the PDAI. Follow-up visits were conducted monthly until the patient reached complete remission and every three months thereafter. A Tzanck smear was performed on lesions clinically suspected to be herpetic in origin. RESULTS: Sixty patients enrolled in the study with a mean age of 45.9 ± 11.7 years. The buccal lesions took the longest to resolve (73[33.5-105.5] days). However, the posterior pharynx lesions showed the shortest healing time (20[13.0-25.5] days). The likelihood of improvement in buccal and soft palate lesions decreased by 5% and 3% with each additional year of age, respectively. Also, the resolution duration of soft palate lesions was significantly shorter in female patients than males (median of 24.0 days vs. 38.5 days). In contrast, lower gingival lesions resolve significantly faster in male patients by a median of 9 days. Herpes simplex virus infection increases the healing time of lesions by 26 days (median of 55 days vs. 29 days, hazard ratio 2.62, 95% CI: 1.04-5.92). CONCLUSIONS: Buccal and lower gingival lesions are more recalcitrant to treatment, while posterior pharynx lesions heal most rapidly. Furthermore, older age was also associated with a lower rate of lesion improvement.

Risk Factors of COVID-19 Associated Mucormycosis (CAM) in Iranian Patients: A Single-Center Retrospective Study.

BACKGROUND: COVID-19 associated mucormycosis (CAM) has been known as one of the most severe post-COVID morbidities. OBJECTIVES: To describe CAM cases, identify possible risk factors, and report outcomes of patients. METHODS: This retrospective study was performed in Amir-Alam Hospital, Tehran, Iran between February 2020 and September 2021. Patients with mucormycosis who had an active or previous diagnosis of COVID-19 have been included. RESULTS: Of 94 patients with mucormycosis, 52 (33 men and 19 women; mean age: 57.0 ± 11.82 years) were identified with an active or history of COVID-19. Rhino-orbital, rhino maxillary, rhino-orbito cerebral subtypes of mucormycosis were detected in 6 (11.5%), 18(34.6%), and 28(53.8%) patients. As a control group, 130 (69 men and 61 women; mean age: 53.10 ± 14.49 years) random RT-PCR-confirmed COVID-19 patients without mucormycosis have been included. The mean interval between COVID-19 diagnosis and initial mucormycosis symptoms was 16.63 ± 8.4 days (range 0-51). Those in the CAM group had a significantly more severe course of COVID-19 (OR = 3.60, P-value < 0.01). Known history of previous diabetes mellitus (OR = 7.37, P-value < 0.01), smoking (OR = 4.55, P-value < 0.01), and history of receiving high-dose corticosteroid pulse therapy because of more severe COVID-19 (P-value = 0.022) were found as risk factors. New-onset post-COVID hyperglycemia was lower in the CAM group (46.2% vs. 63.8%; OR = 0.485, P-value = 0.028). After treatment of the CAM group, 41(78.8%) of patients recovered from mucormycosis. The mean ages of the expired patients in the CAM group were significantly higher than those who recovered from mucormycosis (66.18 ± 9.56 vs. 54.56 ± 11.22 years; P < 0.01); and COVID-19 disease was more severe (P = 0.046). CONCLUSION: Either active or history of COVID-19 can cause an increase in the risk of mucormycosis development. Some of the most important risk factors are the medical history of diabetes mellitus, smoking, and high-dose corticosteroid therapy. CAM is important possible comorbidity related to COVID-19, which could make the post-COVID conditions more complicated. More research and studies with greater sample sizes among different ethnicities are needed to explore the association between COVID-19 and mucormycosis.