Pancreatic Cancer Surveillance and Survival of High-Risk Individuals.

Importance: Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease with increasing incidence. The majority of PDACs are incurable at presentation, but population-based screening is not recommended. Surveillance of high-risk individuals for PDAC may lead to early detection, but the survival benefit is unproven. Objective: To compare the survival of patients with surveillance-detected PDAC with US national data. Design, Setting, and Participants: This comparative cohort study was conducted in multiple US academic medical centers participating in the Cancer of the Pancreas Screening program, which screens high-risk individuals with a familial or genetic predisposition for PDAC. The comparison cohort comprised patients with PDAC matched for age, sex, and year of diagnosis from the Surveillance, Epidemiology, and End Results (SEER) program. The Cancer of the Pancreas Screening program originated in 1998, and data collection was done through 2021. The data analysis was performed from April 29, 2022, through April 10, 2023. Exposures: Endoscopic ultrasonography or magnetic resonance imaging performed annually and standard-of-care surgical and/or oncologic treatment. Main Outcomes and Measures: Stage of PDAC at diagnosis, overall survival (OS), and PDAC mortality were compared using descriptive statistics and conditional logistic regression, Cox proportional hazards regression, and competing risk regression models. Sensitivity analyses and adjustment for lead-time bias were also conducted. Results: A total of 26 high-risk individuals (mean [SD] age at diagnosis, 65.8 [9.5] years; 15 female [57.7%]) with PDAC were compared with 1504 SEER control patients with PDAC (mean [SD] age at diagnosis, 66.8 [7.9] years; 771 female [51.3%]). The median primary tumor diameter of the 26 high-risk individuals was smaller than in the control patients (2.5 [range, 0.6-5.0] vs 3.6 [range, 0.2-8.0] cm, respectively; P < .001). The high-risk individuals were more likely to be diagnosed with a lower stage (stage I, 10 [38.5%]; stage II, 8 [30.8%]) than matched control patients (stage I, 155 [10.3%]; stage II, 377 [25.1%]; P < .001). The PDAC mortality rate at 5 years was lower for high-risk individuals than control patients (43% vs 86%; hazard ratio, 3.58; 95% CI, 2.01-6.39; P < .001), and high-risk individuals lived longer than matched control patients (median OS, 61.7 [range, 1.9-147.3] vs 8.0 [range, 1.0-131.0] months; 5-year OS rate, 50% [95% CI, 32%-80%] vs 9% [95% CI, 7%-11%]). Conclusions and Relevance: These findings suggest that surveillance of high-risk individuals may lead to detection of smaller, lower-stage PDACs and improved survival.

Multiple diffusion models for predicting pathologic response of esophageal squamous cell carcinoma to neoadjuvant chemotherapy.

BACKGROUND: To assess the feasibility and diagnostic performance of the fractional order calculus (FROC), continuous-time random-walk (CTRW), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), mono-exponential (MEM) and stretched exponential models (SEM) for predicting response to neoadjuvant chemotherapy (NACT) in patients with esophageal squamous cell carcinoma (ESCC). MATERIALS AND METHODS: This study prospectively included consecutive ESCC patients with baseline and follow up MR imaging and pathologically confirmed cT1-4aN + M0 or T3-4aN0M0 and underwent radical resection after neoadjuvant chemotherapy (NACT) between July 2019 and January 2023. Patients were divided into pCR (TRG 0) and non-pCR (TRG1 + 2 + 3) groups according to tumor regression grading (TRG). The Pre-, Post- and Delta-treatment models were built. 18 predictive models were generated according to different feature categories, based on six models by five-fold cross-validation. Areas under the curve (AUCs) of the models were compared by using DeLong method. RESULTS: Overall, 90 patients (71 men, 19 women; mean age, 64 years ± 6 [SD]) received NACT and underwent baseline and Post-NACT esophageal MRI, with 29 patients in the pCR group and 61 patients in the non-pCR group. Among 18 predictive models, The Pre-, Post-, and Delta-CTRW model showed good predictive efficacy (AUC = 0.722, 0.833 and 0.790). Additionally, the Post-FROC model (AUC = 0.907) also exhibited good diagnostic performance. CONCLUSIONS: Our study indicates that the CTRW model, along with the Post-FROC model, holds significant promise for the future of NACT efficacy prediction in ESCC patients.

How to update esophageal masses imaging using literature review (MRI and CT features).

MRI offers new opportunities for detailed visualization of the different layers of the esophageal wall, as well as early detection and accurate characterization of esophageal lesions. Staging of esophageal tumors including extramural extent of disease, and status of the adjacent organ can also be performed by MRI with higher accuracy compared to other imaging modalities including CT and esophageal endoscopy. Although MDCT appears to be the primary imaging modality that is indicated for preoperative staging of esophageal cancer to assess tumor resectability, MDCT is considered less accurate in T staging. This review aims to update radiologists about emerging imaging techniques and the imaging features of various esophageal masses, emphasizing the imaging features that differentiate between esophageal masses, demonstrating the critical role of MRI in esophageal masses. CRITICAL RELEVANCE STATEMENT: MRI features may help differentiate mucosal high-grade neoplasia from early invasive squamous cell cancer of the esophagus, also esophageal GISTs from leiomyomas, and esophageal malignant melanoma has typical MR features. KEY POINTS: MRI can accurately visualize different layers of the esophagus potentially has a role in T staging. MR may accurately delineate esophageal fistulae, especially small mediastinal fistulae. MRI features of various esophageal masses are helpful in the differentiation.

Utility of pelvic CT in patients undergoing surveillance for hepatocellular carcinoma: A retrospective multi-institutional study.

OBJECTIVE: To determine the frequency, characteristics and clinical significance of incidental pelvic findings reported on abdominopelvic CT performed for hepatocellular carcinoma (HCC) surveillance in at-risk patients. MATERIAL AND METHODS: This two-center retrospective study received institutional review board approval with a waiver of informed consent. The radiologic reports of the CT exams performed 1/1/2010-2/28/2023 for HCC surveillance were reviewed. Exams were obtained with intravenous contrast material and included hepatic arterial and portal venous phases of the abdomen; images of the pelvis were acquired during the portal venous phase. Reported imaging findings and imaging-related recommendations either by the radiologists or the corresponding caregiver, if present, were retrospectively tabulated. The patient's medical records were reviewed to determine if there were any recommendations that were considered clinically important and culminated in any further interventions or treatments. RESULTS: 259 adults (1st center: mean age, 60 ± 11 years, 49% male and 2nd center: 56.26 ± 6.2 years, 48% male) at risk for HCC underwent 327 abdominopelvic CT exams for HCC surveillance at two centers. A total of 622 pelvic findings (mean, 2.2/ exam) were reported, including 131 bladder, 120 alimentary tract, 133 vascular, 51 gynecologic, 37 prostate, 33 lymph node, 27 inguinal, 44 peritoneal, and 46 skeletal. 52 of 622 reported findings (8.3%) were associated with actionable recommendations. 24 of the 52 actionable recommendations/clinical suggestions were implemented as follows: five complimentary imaging, ten additional laboratory tests, and nine non-imaging recommendations. Of note, only eight applied recommendations culminated in a clinical outcome, which included four urinary tract infection treatments. CONCLUSION: Pelvic CT findings were associated with a clinical benefit to the patient in 1.3% of exams. These results suggest that pelvic imaging should be omitted from CT-based HCC surveillance. CLINICAL RELEVANCE: Without compromising valuable information, patients undergoing HCC surveillance-CT may not require additional pelvic coverage.

ACR Appropriateness Criteria® Sepsis.

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. A search for the underlying cause of infection typically includes radiological imaging as part of this investigation. This document focuses on thoracic and abdominopelvic causes of sepsis. In 2017, the global incidence of sepsis was estimated to be 48.9 million cases, with 11 million sepsis-related deaths (accounting for nearly 20% of all global deaths); therefore, understanding which imaging modalities and types of studies are acceptable or not acceptable is imperative. The 5 variants provided include the most commonly encountered scenarios in the setting of sepsis along with recommendations and data for each imaging study. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

R2* mapping and reduced field-of-view diffusion-weighted imaging for preoperative assessment of nonenlarged lymph node metastasis in rectal cancer.

The aim of the current study is to investigate the diagnostic value of R2* mapping versus reduced field-of-view diffusion-weighted imaging (rDWI) of the primary lesion of rectal cancer for preoperative prediction of nonenlarged lymph node metastasis (NLNM). Eighty-one patients with pathologically confirmed rectal cancer underwent preoperative R2* mapping and rDWI sequences before total mesorectal excisions and accompanying regional lymph node dissections. Two radiologists independently performed whole-tumor measurements of R2* and apparent diffusion coefficient (ADC) parameters on primary lesions of rectal cancer. Patients were divided into positive (NLNM+) and negative (NLNM-) groups based on their pathological analysis. The tumor location, maximum diameter of the tumor, and maximum short diameter of the lymph node were assessed. R2* and ADC, pT stage, tumor grade, status of mesorectal fascia, and extramural vascular invasion were also studied for their potential relationships with NLNM using multivariate logistic regression analysis. The NLNM+ group had significantly higher R2* (43.56 ± 8.43 vs. 33.87 ± 9.57, p < 0.001) and lower ADC (1.00 ± 0.13 vs. 1.06 ± 0.22, p = 0.036) than the NLNM- group. R2* and ADC were correlated to lymph node metastasis (r = 0.510, p < 0.001 for R2*; r = -0.235, p = 0.035 for ADC). R2* and ADC showed good and moderate diagnostic abilities in the assessment of NLNM status with corresponding area-under-the-curve values of 0.795 and 0.636. R2* provided a significantly better diagnostic performance compared with ADC for the prediction of NLNM status (z = 1.962, p = 0.0498). The multivariate logistic regression analysis demonstrated that R2* was a compelling factor of lymph node metastasis (odds ratio = 56.485, 95% confidence interval: 5.759-554.013; p = 0.001). R2* mapping had significantly higher diagnostic performance than rDWI from the primary tumor of rectal cancer in the prediction of NLNM status.

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.

Practical Application of Multivendor MRI-Based R2* Mapping for Liver Iron Quantification at 1.5 T and 3.0 T.

BACKGROUND: Recent multicenter, multivendor MRI-based R2* vs. liver iron concentration (LIC) calibrations (i.e., MCMV calibrations) may facilitate broad clinical dissemination of R2*-based LIC quantification. However, these calibrations are based on a centralized offline R2* reconstruction, and their applicability with vendor-provided R2* maps is unclear. PURPOSE: To determine R2* ranges of agreement between the centralized and three MRI vendors' R2* reconstructions. STUDY TYPE: Prospective. SUBJECTS: Two hundred and seven subjects (mean age 37.6 ± 19.6 years; 117 male) with known or suspected iron overload from four academic medical centers. FIELD STRENGTH/SEQUENCE: Standardized multiecho spoiled gradient echo sequence at 1.5 T and 3.0 T for R2* mapping and a multiple spin-echo sequence at 1.5 T for LIC quantification. MRI vendors: GE Healthcare, Philips Healthcare, and Siemens Healthineers. ASSESSMENT: R2* maps were generated using both the centralized and vendor reconstructions, and ranges of agreement were determined. R2*-LIC linear calibrations were determined for each site, field strength, and reconstruction and compared with the MCMV calibrations. STATISTICAL TESTS: Bland-Altman analysis to determine ranges of agreement. Linear regression, analysis of covariance F tests, and Tukey's multiple comparison testing to assess reproducibility of calibrations across sites and vendors. A P value <0.05 was considered significant. RESULTS: The upper limits of R2* ranges of agreement were approximately 500, 375, and 330 s-1 for GE, Philips, and Siemens reconstructions, respectively, at 1.5 T and approximately 700 and 800 s-1 for GE and Philips, respectively, at 3.0 T. Within the R2* ranges of agreement, vendor R2*-LIC calibrations demonstrated high reproducibility (no significant differences between slopes or intercepts; P ≥ 0.06) and agreed with the MCMV calibrations (overlapping 95% confidence intervals). DATA CONCLUSION: Based on the determined upper limits, R2* measurements obtained from vendor-provided R2* maps may be reliably and practically used to quantify LIC less than approximately 8-13 mg/g using the MCMV calibrations and similar acquisition parameters as this study. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 3.

Incremental value of automatically segmented perirenal adipose tissue for pathological grading of clear cell renal cell carcinoma: a multicenter cohort study.

OBJECTIVES: Accurate preoperative prediction of the pathological grade of clear cell renal cell carcinoma (ccRCC) is crucial for optimal treatment planning and patient outcomes. This study aims to develop and validate a deep-learning (DL) algorithm to automatically segment renal tumours, kidneys, and perirenal adipose tissue (PRAT) from computed tomography (CT) images and extract radiomics features to predict the pathological grade of ccRCC. METHODS: In this cross-ethnic retrospective study, a total of 614 patients were divided into a training set (383 patients from the local hospital), an internal validation set (88 patients from the local hospital), and an external validation set (143 patients from the public dataset). A two-dimensional TransUNet-based DL model combined with the train-while-annotation method was trained for automatic volumetric segmentation of renal tumours, kidneys, and visceral adipose tissue (VAT) on images from two groups of datasets. PRAT was extracted using a dilation algorithm by calculating voxels of VAT surrounding the kidneys. Radiomics features were subsequently extracted from three regions of interest of CT images, adopting multiple filtering strategies. The least absolute shrinkage and selection operator (LASSO) regression was used for feature selection, and the support vector machine (SVM) for developing the pathological grading model. Ensemble learning was used for imbalanced data classification. Performance evaluation included the Dice coefficient for segmentation and metrics such as accuracy and area under curve (AUC) for classification. The WHO/International Society of Urological Pathology (ISUP) grading models were finally interpreted and visualized using the SHapley Additive exPlanations (SHAP) method. RESULTS: For automatic segmentation, the mean Dice coefficient achieved 0.836 for renal tumours and 0.967 for VAT on the internal validation dataset. For WHO/ISUP grading, a model built with features of PRAT achieved a moderate AUC of 0.711 (95% CI, 0.604-0.802) in the internal validation set, coupled with a sensitivity of 0.400 and a specificity of 0.781. While model built with combination features of the renal tumour, kidney, and PRAT showed an AUC of 0.814 (95% CI, 0.717-0.889) in the internal validation set, with a sensitivity of 0.800 and a specificity of 0.753, significantly higher than the model built with features solely from tumour lesion (0.760; 95% CI, 0.657-0.845), with a sensitivity of 0.533 and a specificity of 0.767. CONCLUSION: Automated segmentation of kidneys and visceral adipose tissue (VAT) through TransUNet combined with a conventional image morphology processing algorithm offers a standardized approach to extract PRAT with high reproducibility. The radiomics features of PRAT and tumour lesions, along with machine learning, accurately predict the pathological grade of ccRCC and reveal the incremental significance of PRAT in this prediction.

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.

Radiological biomarkers reflecting visceral fat distribution help distinguish inflammatory bowel disease subtypes: a multicenter cross-sectional study.

OBJECTIVES: To achieve automated quantification of visceral adipose tissue (VAT) distribution in CT images and screen out parameters with discriminative value for inflammatory bowel disease (IBD) subtypes. METHODS: This retrospective multicenter study included Crohn's disease (CD) and ulcerative colitis (UC) patients from three institutions between 2012 and 2021, with patients with acute appendicitis as controls. An automatic VAT segmentation algorithm was developed using abdominal CT scans. The VAT volume, as well as the coefficient of variation (CV) of areas within the lumbar region, was calculated. Binary logistic regression and receiver operating characteristic analysis was performed to evaluate the potential of indicators to distinguish between IBD subtypes. RESULTS: The study included 772 patients (365 CDs, median age [inter-quartile range] = 31.0. (25.0, 42.0) years, 255 males; 241 UCs, 46.0 (34.0, 55.5) years, 138 males; 166 controls, 40.0 (29.0, 53.0) years, 80 males). CD patients had lower VAT volume (CD = 1584.95 ± 1128.31 cm3, UC = 1855.30 ± 1326.12 cm3, controls = 2470.91 ± 1646.42 cm3) but a higher CV (CD = 29.42 ± 15.54 %, p = 0.006 and p ˂ 0.001) compared to UC and controls (25.69 ± 12.61 % vs. 23.42 ± 15.62 %, p = 0.11). Multivariate analysis showed CV was a significant predictor for CD (odds ratio = 6.05 (1.17, 31.12), p = 0.03). The inclusion of CV improved diagnostic efficiency (AUC = 0.811 (0.774, 0.844) vs. 0.803 (0.766, 0.836), p = 0.08). CONCLUSION: CT-based VAT distribution can serve as a potential biomarker for distinguishing IBD subtypes. CRITICAL RELEVANCE STATEMENT: Visceral fat distribution features extracted from CT images using an automated segmentation algorithm (1.14 min) show differences between Crohn's disease and ulcerative colitis and are promising for practical radiological screening. KEY POINTS: • Radiological parameters reflecting visceral fat distribution were extracted for the discrimination of Crohn's disease (CD) and ulcerative colitis (UC). • In CD, visceral fat was concentrated in the lower lumbar vertebrae, and the coefficient of variation was a significant predictor (OR = 6.05 (1.17, 31.12), p = 0.03). • The differences between CD, UC, and controls are promising for practical radiological screening.

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.

COVID vaccine-induced lupus nephritis: Case report and review of the literature.

Vaccines offer an effective strategy to prevent infectious diseases with minimal adverse effects. On rare occasions, vaccination can disrupt the immune response leading to induction of autoimmune diseases. We describe a case of new-onset lupus nephritis following COVID-19 vaccination with the first dose of the Pfizer vaccine. Her symptoms and lab values improved with steroids, hydroxychloroquine, and mycophenolate mofetil.

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.

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.

Incremental value of volumetric multiparametric MRI over Fudan score for prognosis of unresectable intrahepatic cholangiocarcinoma treated with systemic chemotherapy.

BACKGROUND: Individualized patient care requires prognostic models customized to a tumor and an individual's disease profile for reliable survival prediction. MRI has prognostic value for intrahepatic cholangiocarcinoma (ICCA). Existing prognostic models for ICCA exclude imaging-based information about an individual's tumor that may reflect important aspects of tumor's biology. Fudan score, a prognostic model applicable to unresectable ICCA, is limited by subjective morphologic imaging parameters. OBJECTIVES: To assess the prognostic value of baseline volumetric multiparametric MRI in unresectable intrahepatic cholangiocarcinoma (ICCA) treated with systemic chemotherapy and the incremental value of MRI over the Fudan score. METHODS: This retrospective study included 114 ICCA patients treated with systemic chemotherapy between 2007 and 2021 after a baseline MRI. The single largest tumor was volumetrically assessed for anatomic (total tumor volume and diameter) and functional parameters (viable tumor volume, percentage-viable tumor volume, viable tumor burden, and ADC). A derivation cohort of 30 patients was utilized to identify MRI parameters associated with overall survival (OS) using Cox regression analysis. The incremental value of MRI over Fudan score was assessed on an independent sub-cohort of 84 patients using Kaplan-Meier analysis and C-index. RESULTS: 114 patients (64 years +/- 11; 61 women) were evaluated. Pre-treatment high (>1350x10-6 mm2/sec) ADC was the only independent predictor of OS (HR, 8.07; P < 0.001). Replacing subjective tumor boundary with objective ADC value, and using modified biochemical thresholds increased the prognostic stratification for the risk groups in the modified ADC-Fudan model compared to the original Fudan model (median survival 12 and 4.5 months; P = 0.055; vs. 11 and 3 months; P < 0.001). The modified ADC-Fudan model demonstrated an 11 % improvement over the original Fudan model (c-index: 0.80 vs. 0.69; P = 0.044) for survival prediction. CONCLUSIONS: High pre-treatment volumetric ADC was associated with unfavorable prognosis in patients with unresectable intrahepatic cholangiocarcinoma treated with systemic chemotherapy. Supplementing the original Fudan model with ADC and modified serum marker thresholds improved the survival prediction performance by 11% in the resulting modified ADC-Fudan model. CLINICAL IMPACT: Volumetric MRI could improve the survival prediction among ICCA patients prior to receiving potentially toxic and expensive palliative chemotherapies. This could potentially guide individualized therapy for this patient cohort.

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.