Genetic and phenotypic associations of frailty with cardiovascular indicators and behavioral characteristics.

INTRODUCTION: Frailty Index (FI) is a common measure of frailty, which has been advocated as a routine clinical test by many guidelines. The genetic and phenotypic relationships of FI with cardiovascular indicators (CIs) and behavioral characteristics (BCs) are unclear, which has hampered ability to monitor FI using easily collected data. OBJECTIVES: This study is designed to investigate the genetic and phenotypic associations of frailty with CIs and BCs, and further to construct a model to predict FI. METHOD: Genetic relationships of FI with 288 CIs and 90 BCs were assessed by the cross-trait LD score regression (LDSC) and Mendelian randomization (MR). The phenotypic data of these CIs and BCs were integrated with a machine-learning model to predict FI of individuals in UK-biobank. The relationships of the predicted FI with risks of type 2 diabetes (T2D) and neurodegenerative diseases were tested by the Kaplan-Meier estimator and Cox proportional hazards model. RESULTS: MR revealed putative causal effects of seven CIs and eight BCs on FI. These CIs and BCs were integrated to establish a model for predicting FI. The predicted FI is significantly correlated with the observed FI (Pearson correlation coefficient = 0.660, P-value = 4.96 × 10-62). The prediction model indicated "usual walking pace" contributes the most to prediction. Patients who were predicted with high FI are in significantly higher risk of T2D (HR = 2.635, P < 2 × 10-16) and neurodegenerative diseases (HR = 2.307, P = 1.62 × 10-3) than other patients. CONCLUSION: This study supports associations of FI with CIs and BCs from genetic and phenotypic perspectives. The model that is developed by integrating easily collected CIs and BCs data in predicting FI has the potential to monitor disease risk.

Treatment Response Assessment in Multiple Myeloma: Histogram Analysis of Total Tumor Apparent Diffusion Coefficient based on Whole-body Diffusion-weighted MR Imaging.

BACKGROUND: The International Myeloma Working Group (IMWG) consensus criteria for response assessment in multiple myeloma (MM) has methodological limitations. Whole-body diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) histogram analysis may be complementary to response assessment of MM. PURPOSE: To explore the role of histogram analysis of the ADC based on the total tumor volume (ttADC) in response assessment in patients with newly diagnosed MM (NDMM). STUDY TYPE: Retrospective. POPULATION: Thirty-six patients with NDMM. FIELD STRENGTH/SEQUENCE: 3.0T/single-shot DWI echo planar imaging (EPI) sequence with an integrated slice-by-slice shimming (iShim) technique. ASSESSMENT: Baseline (median: 1 day before treatment) and post-treatment (median: five cycles of therapy) whole-body DWI were analyzed. A region of interest (ROI) containing lesions on every section of baseline image was drawn to derive the per-patient total tumor data. Post-treatment image analysis was based on the same ROI as the corresponding baseline. Histogram metrics were extracted from both ROIs. Patients were categorized into the very good partial response or better (VGPR+) group and the less than VGPR group per the IMWG response criteria for response assessment. Progression-free survival (PFS) was also calculated. STATISTICAL TESTS: Mann-Whitney test and Fisher's exact or Chi-squared tests, Receiver operating characteristic (ROC) analysis and DeLong test, Kaplan-Meier analysis and Cox proportional hazards model. A two-tailed P-value <0.05 was considered statistically significant. RESULTS: Thirty patients were categorized into the VGPR+ group and six into the less than VGPR group. The ttADC histogram changes between post-treatment and baseline metrics (ΔttADC) revealed significant differences in all percentile values between the VGPR+ and less than VGPR groups. For distinguishing VGPR+, ΔttADC_5th percentile had the largest area under the curve (AUC) (0.950, 95% CI 0.821-0.995). Patients with lower ΔttADC_5th percentile values (cutoff point, 188.193) showed significantly longer PFS (HR = 34.911, 95% CI 6.392-190.677). DATA CONCLUSION: ttADC histogram may facilitate response assessment in patients with NDMM. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 4.

Should All Pancreatic Cystic Lesions with Worrisome or High-Risk Features Be Resected? A Clinical and Radiological Machine Learning Model May Help to Answer.

RATIONALE AND OBJECTIVES: According to current guidelines, pancreatic cystic lesions (PCLs) with worrisome or high-risk features may have overtreatment. The purpose of this study was to build a clinical and radiological based machine-learning (ML) model to identify malignant PCLs for surgery among preoperative PCLs with worrisome or high-risk features. MATERIALS AND METHODS: Clinical and radiological details of 317 pathologically confirmed PCLs with worrisome or high-risk features were retrospectively analyzed and applied to ML models including Support Vector Machine, Logistic Regression (LR), Decision Tree, Bernoulli NB, Gaussian NB, K Nearest Neighbors and Linear Discriminant Analysis. The diagnostic ability for malignancy of the optimal model with the highest diagnostic AUC in the cross-validation procedure was further evaluated in internal (n = 77) and external (n = 50) testing cohorts, and was compared to two published guidelines in internal mucinous cyst cohort. RESULTS: Ten clinical and radiological feature-based LR model was the optimal model with the highest AUC (0.951) in the cross-validation procedure. In the internal testing cohort, LR model reached an AUC, accuracy, sensitivity, and specificity of 0.927, 0.909, 0.914, and 0.905; in the external testing cohort, LR model reached 0.948, 0.900, 0.963, and 0.826. When compared to the European guidelines and the ACG guidelines, LR model demonstrated significantly better accuracy and specificity in identifying malignancy, while maintaining the same high sensitivity. CONCLUSION: Clinical- and radiological-based LR model can accurately identify malignant PCLs in patients with worrisome or high-risk features, possessing diagnostic performance better than the European guidelines as well as ACG guidelines.

Extracellular volume fraction of the pancreas predicts glucose intolerance in patients undergoing major pancreatic surgeries.

PURPOSE: Pancreatic T1 value and extracellular volume fraction (ECV) are potential imaging biomarkers for pancreatic exocrine and endocrine function. This study aims to evaluate the ability of native T1 value and ECV of the pancreas in predicting postoperative new-onset diabetes (NODM) and worsened glucose tolerance in patients undergoing major pancreatic surgeries. METHODS: This retrospective study involved 73 patients who underwent 3 T pancreatic MRI with pre- and postcontrast T1 mapping before major pancreatic surgeries. Patients were divided into non-diabetic, pre-diabetic and diabetic groups based on their glycated hemoglobin (HbA1c) value. Preoperative native T1 value and ECV of the pancreas were compared among the three groups. The correlation of pancreatic T1 value and ECV with HbA1c was assessed by linear regression analysis, and the ability of pancreatic T1 value and ECV for predicting postoperative NODM and worsened glucose tolerance was assessed using Cox Proportional hazards regression analysis. RESULTS: Native pancreatic T1 value and ECV were both significantly higher in diabetic patients compared to pre-diabetic/non-diabetic patients, and ECV was also significantly higher in pre-diabetic patients compared to non-diabetic patients (all p < 0.05). Both native pancreatic T1 value and ECV showed positive correlation with preoperative HbA1c value (r = 0.50 and 0.55, respectively, both p < 0.001). ECV > 30.7% was the only independent predictor for NODM (HR = 5.687, 95% CI: 1.557, 13.468, p = 0.012) and worsened glucose tolerance (HR = 6.783, 95% CI:, 1.753, 15.842, p = 0.010) after surgery. CONCLUSIONS: Pancreatic ECV predicts the risk of postoperative NODM and worsened glucose tolerance in patients undergoing major pancreatic surgeries.

[Effect of Deep Learning-based Contrast-enhanced CT Image Reconstruction on the Image Quality of the Biliary System].

Objective To evaluate the effect of a deep learning reconstruction (DLR) method on the visibility of contrast-enhanced CT images of the biliary system by comparing it with different iterative reconstruction algorithms including the adaptive iterative dose reduction 3D (AIDR 3D) algorithm,forward projected model based iterative reconstruction solution (FIRST),and filtered back projection (FBP) algorithm. Methods A total of 30 patients subjected to abdominal contrast-enhanced CT and diagnosed with dilatation of common bile duct or extrahepatic bile duct were retrospectively included in this study.The images of the portal phase were reconstructed via four different algorithms (FBP,AIDR 3D,FIRST,and DLR).Signal to noise ratio (SNR) and contrast to noise ratio (CNR) of the dilated bile duct,liver parenchyma,measurable bile duct lesions,and image noise were compared between the four datasets.In subjective analyses,two radiologists independently scored the image quality (best:4 points,second:3 points;third:2 points;fourth:1 point) of the four datasets based on the noise and image visual quality of the biliary system.The Friedman and the Bonferroni-Dunn post-hoc tests were performed for comparison. Results The DLR images (bile duct:4.42±0.87;liver parenchyma:3.78±1.47) yielded higher CNR than the FBP (bile duct:2.21±1.02,P<0.001;liver parenchyma:1.43±1.29,P<0.001),AIDR 3D (bile duct:2.81±0.91,P=0.024;liver parenchyma:2.39±1.94,P=0.278),and FIRST (bile duct:2.51±1.24,P<0.001;liver parenchyma:2.45±1.81,P=0.003) images.Furthermore,the DLR images had higher SNR (bile duct:1.39±0.85,liver parenchyma:9.75±1.90) than the FBP (bile duct:0.86±0.63,P<0.001;liver parenchyma:3.31±1.12,P<0.001) and FIRST (bile duct:1.01±0.61,P=0.013;liver parenchyma:5.73±1.37,P<0.001) images,and showed lower noise (10.51±3.53) than the FBP(4.10±3.92,P<0.001),AIDR 3D (15.72±2.41,P=0.032),and FIRST (17.20±3.82,P<0.001) images.SNR and CNR showed no significant differences between FIRST and AIDR 3D images (all P>0.05).DLR images [4(4,4)] obtained higher score than FPB [1(1,1),P<0.001],AIDR3D[3 (2,3),P=0.029],and FIRST[2 (2,3),P<0.001] images. Conclusion DLR algorithm improved the subjective and objective quality of the contrast-enhanced CT image of the biliary system.

A systematic review of prognosis predictive role of radiomics in pancreatic cancer: heterogeneity markers or statistical tricks?

OBJECTIVES: We aimed to systematically evaluate the prognostic prediction accuracy of radiomics features extracted from pre-treatment imaging in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: Radiomics literature on overall survival (OS) prediction of PDAC were all included in this systematic review. A further meta-analysis was performed on the effect size of first-order entropy. Methodological quality and risk of bias of the included studies were assessed by the radiomics quality score (RQS) and prediction model risk of bias assessment tool (PROBAST). RESULTS: Twenty-three studies were finally identified in this review. Two (8.7%) studies compared prognosis prediction ability between radiomics model and TNM staging model by C-index, and both showed a better performance of the radiomics. Twenty-one (91.3%) studies reported significant predictive values of radiomics features. Nine (39.1%) studies were included in the meta-analysis, and it showed a significant correlation between first-order entropy and OS (HR 1.66, 95%CI 1.18-2.34). RQS assessment revealed validation was only performed in 5 (21.7%) studies on internal datasets and 2 (8.7%) studies on external datasets. PROBAST showed that 22 (95.7%) studies have a high risk of bias in participants because of the retrospective study design. CONCLUSION: First-order entropy was significantly associated with OS and might improve the accuracy of PDAC prognosis prediction. Existing studies were poorly validated, and it should be noted in future studies. Modification of PROBAST for radiomics studies is necessary since the strict requirements of prospective study design may not be applicable to the demand for a large sample size in the model construction stage. KEY POINTS: • Radiomics based on the primary lesion holds great potential for prognosis prediction. First-order entropy was significantly associated with the overall survival of PDAC and might improve the accuracy of current PDAC prognosis prediction. • We strongly recommend that at least an internal validation should be conducted in any radiomics study. Attention should be paid to the complex relationships between radiomics features. • Due to the close relationship between radiomics and big data, the strict requirement of prospective study design in PROABST may not be appropriate for radiomics studies. A balance between study types and sample sizes for radiomics studies needs to be found in the model construction stage.

Effects of contrast enhancement boost postprocessing technique in combination with different reconstruction algorithms on the image quality of abdominal CT angiography.

OBJECTIVES: To investigate whether contrast-enhancement-boost (CE-boost) in combination with hybrid iterative reconstruction (Hybrid IR, also named HIR [AIDR 3D, adaptive iterative dose reduction three dimensional]) and model-based iterative reconstruction (MBIR [FIRST, forward projected model-based IR solution]) algorithms can improve the image quality of abdominal CT angiography (CTA). METHODS: This retrospective study included 50 patients who underwent abdominal CTA. Both arterial and portal phases were reconstructed using three different algorithms [filtered-back projection (FBP), AIDR 3D, and FIRST] separately. CE-boost was performed additionally to generate AIDR 3D-boost and FIRST-boost images. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the arteries and portal system were compared among the five datasets (FBP, AIDR 3D, FIRST, AIDR 3D-boost, FIRST-boost). In subjective analyses, two radiologists independently ordered images (5, best; 1, worst) based on the visual image quality of distal arterial or portal venous branches. The Friedman and the Dunn-Bonferroni post-hoc tests were used for statistical analysis. RESULTS: FIRST-boost arterial and portal images had the lowest noise compared with FBP, AIDR 3D, FIRST, and AIDR 3D-boost images (all P < 0.05), and significantly higher SNR and CNR than FBP, AIDR 3D, and FIRST images (all P < 0.05). AIDR 3D-boost images showed lower noise, and higher SNR and CNR than FBP and AIDR 3D images (all P < 0.05). FIRST-boost images had higher subjective grading scores than FBP, AIDR 3D, and AIDR 3D-boost images (all P < 0.05). CONCLUSION: The postprocessing technique CE-boost can improve the image quality of abdominal CTA images. MBIR in combination with CE-boost (FIRST-boost) images had the best image quality compared with the other four image datasets.

Relationship Between Non-Alcoholic Fatty Liver Disease and Abdominal and Pericardial Adipose Tissue in Middle-Aged and Elderly Subjects.

OBJECTIVE: The present study aimed to explore the relationship between non-alcoholic fatty liver disease (NAFLD) and abdominal and pericardial adipose tissue in middle-aged and elderly subjects. METHODS: Between July 2019 and July 2020, 471 subjects attending the Health Care Medical Department of Peking Union Medical College Hospital for a medical examination were enrolled in the study. The volume and distribution of abdominal adipose tissue together with the volume of pericardial adipose tissue were calculated according to the results of the abdominal computed tomography. The differences between subjects with NAFLD and the normal population were analyzed. RESULTS: The volume of pericardial adipose tissue, abdominal visceral and subcutaneous adipose tissue, the total volume of abdominal adipose tissue, and volume of pelvic visceral adipose tissue were all significantly increased in subjects with NAFLD. For every 100 cm3 increase in the volume of abdominal visceral adipose tissue, the incidence of developing NAFLD increased by 9.4%. According to the results of the receiver operating curve, the cut-off point of abdominal visceral adipose tissue for the diagnosis of NAFLD was 2691.1 cm3. CONCLUSION: Overall, the risk of NAFLD increases significantly with the increase in the volume of adipose tissue.

Correlation Between the Distribution of Abdominal, Pericardial and Subcutaneous Fat and Muscle and Age and Gender in a Middle-Aged and Elderly Population.

OBJECTIVE: The present study aimed to explore the relationships between the distribution of abdominal fat and muscle and age and gender in a middle-aged and elderly population. METHODS: The levels of abdominal (visceral and subcutaneous) fat, pericardial fat, and psoas major muscle were measured in subjects who had physical examinations at the Health and Medical Department of Peking Union Medical College Hospital from July 2019 to June 2020. The relationship between fat in different areas (ie, different types of fat) and the relationship between different types of fat and the psoas major muscle were investigated in the context of different genders and ages. RESULTS: The distribution of fat and muscle differed between males and females of the middle-aged and elderly study sample. Volumes of pericardial fat, total abdominal fat, and visceral fat were significantly lower in females than in males, and the area of the psoas major muscle was also significantly lower in females than in males. Levels of subcutaneous fat and total abdominal fat showed no significant correlation with age. The level of muscle showed a significant negative correlation with age. CONCLUSION: 1) Within the middle-aged and elderly sample, male subjects had higher levels than females of all types of fat except for abdominal subcutaneous fat, and had higher levels of psoas muscle than females. 2) Pericardial fat increased with age, whereas levels of abdominal fat did not change significantly with age. 3) The area of psoas major muscle appears to be positively correlated with volumes of all types of fat: subjects with more fat tended to have higher levels of psoas major muscle.

[Correlation of Intravoxel Incoherent Motion-derived Parameters with Computer Tomography Perfusion Parameters in Insulinoma].

Objective To prospectively evaluate the correlation between intravoxel incoherent motion (IVIM)-derived parameters and CT perfusion parameters as well as the pathological grade in insulinoma. Methods A total of 55 patients with suspected insulinoma undergoing IVIM and CT perfusion scans were prospectively enrolled. The images were post-processed to obtain IVIM parameters including apparent diffusion coefficient (ADC),diffusion (D),perfusion correlated diffusion (D*),and f,and CT perfusion parameters including blood flow (BF),blood volume (BV),and permeability (PM). The pathological specimens were stained to obtain pathological parameters including the grading,ki-67 index,and the mitotic count. The IVIM derived parameters of normal pancreas including head,body,and tail as well as that of the pancreatic insulinoma were compared. The correlation between IVIM parameters and CT perfusion parameters as well as the pathological parameters was analyzed. Results ADC and D values of pancreatic tail were significantly lower than those of the pancreatic head and neck (all P<0.001). There were significant differences in all IVIM parameters between insulinoma and normal pancreas (all P<0.001). The ADC and f value of the normal pancreas was positively correlated with BF (r=0.437,P=0.003;r=0.357,P=0.010). There is no correlation between the remaining IVIM parameters and the CT perfusion parameters as well as between IVIM parameters and pathological parameters (all P>0.05). Conclusions IVIM parameters differ at different anatomical parts of normal pancreas. IVIM parameters can distinguish normal pancreatic parenchyma from insulinoma. The ADC value is weakly correlated with BF.

Comparison and evaluation of the efficacy of compressed SENSE (CS) and gradient- and spin-echo (GRASE) in breath-hold (BH) magnetic resonance cholangiopancreatography (MRCP).

CONTRACT GRANT SPONSOR: Chinese Academy of Medical Sciences (CAMS) Initiative for Innovative Medicine; Contract grant number: 2017-I2M-1-001; Contract grant sponsor: Outstanding Youth Fund of Peking Union Medical College Hospital; Contract grant number: JQ201704; Contract grant sponsor: National Natural Science Foundation of China; Contract grant number: 81871512; Contract grant sponsor: National Public Welfare Basic Scientific Research Program of Chinese Academy of Medical Sciences; Contract grant numbers: 2018PT32003 and 2017PT32004. BACKGROUND: Both compressed-sensing (CS) and gradient- and spin-echo (GRASE) sequences can achieve 3D magnetic resonance cholangiopancreatography (MRCP) with a single breath-hold (BH). This work hypothesized that compared with conventional navigator-triggered (NT)-MRCP, the two BH-MRCP protocols, GRASE and CS, may provide better imaging quality, especially for patients with irregular breathing. PURPOSE: To evaluate and compare the image quality and diagnostic performance of three MRCP protocols. STUDY TYPE: Prospective. SUBJECTS: Seventy-four patients suspected to have duct-related pathologies were enrolled. FIELD STRENGTH: 3.0T. SEQUENCES: NT-MRCP, BH-CS-MRCP, and BH-GRASE-MRCP. ASSESSMENT: Breath regularity was evaluated subjectively according to the respiratory waves. The acquisition time was compared. The pancreaticobiliary system was divided into 12 segments and evaluated on a 5-point scale. The diagnostic performance of the three MRCPs was evaluated and compared. STATISTICAL TESTS: The Friedman test with a post-hoc test, receiver operating characteristic (ROC) curve analysis, McNemar test, and Kendall's W test were used. RESULTS: The BH-MRCP decreased the scan time significantly (P < 0.05). The overall imaging scores of GRASE-MRCP and CS-MRCP were significantly higher than that of NT-MRCP for patients with irregular breathing (4.283 and 4.283 vs. 3.000, both P < 0.05). Compared with NT-MRCP, the diagnostic performance of BH-CS and BH-GRASE MRCP was significantly improved for patients with irregular breathing (AUC = 0.860 and 0.863 vs. 0.572, both P < 0.001). DATA CONCLUSION: Compared with conventional NT-MRCP, the overall imaging quality and diagnostic performance of BH-CS and BH-GRASE MRCP were not significantly different for patients with regular breathing and significantly superior for patients with irregular breathing. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:824-832.

Value of Texture Analysis on Gadoxetic Acid-enhanced MR for Detecting Liver Fibrosis in a Rat Model.

Objective To explore the ability of texture analysis of gadoxetic acid-enhanced magnetic resonance imaging (MRI) T1 mapping images, as well as T1-weighted (T1W), T2-weighted (T2W) and apparent diffusion coefficient (ADC) maps for distinguishing between varying degrees of hepatic fibrosis in an experimental rat model.Methods Liver fibrosis in rats was induced by carbon tetrachloride intraperitoneal injection for 4-12 weeks (n=30). In the control group (n=10) normal saline was applied. The MRI protocol contained T2W, diffusion weighted imaging, pre-and post-contrast image series of T1W and T1 mapping images. METAVIR score was used to grade liver fibrosis as normal (F0), mild fibrosis (F1-2), and advanced fibrosis (F3-4). Texture parameters including mean gray-level intensity (Mean), standard deviation (SD), Entropy, mean of positive pixels (MPP), Skewness, and Kurtosis were obtained. Nonparametric Mann-Whitney U test was used to compare the average value of each texture parameter in each sequence for assessing the difference between F0 and F≥1 as well as F0-2 and F3-4. Receiver operating characteristic (ROC) curves were obtained to assess the diagnosing accuracy of the parameters for differentiating no liver fibrosis from liver fibrosis and rats with liver fibrosis grading F0-2 from those with grading F3-4. The area under ROC curve (AUC) was calculated to evaluate the diagnostic efficiency of texture parameters.Results Finally, 20 rats completed MR T1 mapping image scan. The pathologic staging of these 20 rats was no fibrosis (F0, n=6), mild fibrosis (F1-2, n=5) and advanced fibrosis (F3-4, n=9). On pre-contrast T1 mapping image, Entropy was seen to be statistically significant higher in the F≥1 group than that in the F0 group at each spatial scaling factor (SSF) setting (P=0.015, 0.015, 0.015, 0.013, 0.015 and 0.018 respectively to SSF=0, 2, 3, 4, 5, 6), and Mean of the F≥1 rats was statistically significant higher than that of the F0 rats at SSF 4, 5, 6 (P=0.004, 0.006, and 0.013, respectively). Entropy and Mean showed a moderate diagnostic performance in most SSF settings of T1 mapping pre-contrast images for differentiation of normal liver from liver fibrosis.Conclusions Certain texture features of gadoxetic acid-enhanced MR images, especially the Entropy of non-contrast T1 mapping image, was found to be a useful biomarker for the diagnosis of liver fibrosis.

Multiple solid pancreatic lesions: Prevalence and features of non-malignancies on dynamic enhanced CT.

OBJECTIVE: To determine the prevalence of multiple solid pancreatic lesions on dynamic enhanced CT performed for suspected pancreatic diseases, and to identify CT features of non-malignancies. METHODS: We investigated 8096 consecutive patients who underwent dynamic enhanced CT pancreas protocol at a tertiary center over 40 months. The final clinical /pathological diagnosis served as reference standard. The diagnostic accuracy of dynamic enhanced CT for non-malignancies was calculated. A univariate and multivariate analysis was conducted to identify features that predict non-malignancies. RESULTS: Multiple solid pancreatic lesions were identified in 121 patients. The prevalence of non-malignancies was 19.8% (24/121). The most common non-malignancy was autoimmune pancreatitis (n = 21; 17.4%). Common lesions with malignant potential included neuroendocrine neoplasia (n = 62; 51.2%), ductal adenocarcinoma (n = 15; 12.4%), metastasis (n = 9; 7.4%), and lymphoma (n = 7; 5.8%). Dynamic enhanced CT had a sensitivity of 79.2% and a specificity of 92.8% for diagnosing non-malignancies. Elevated serum IgG4 level (p < 0.001), hypo-enhancement in arterial phase (p = 0.001), hyper-enhancement in equilibrium phase (p = 0.009) and location in both proximal and distal pancreas (p = 0.036) were predictors of non-malignancies, whereas pancreatic duct morphology and vascular invasion status were not. CONCLUSION: Multiple solid pancreatic lesions were rare, with a wide spectrum. Dynamic enhanced CT provides clues for identifying non-malignancies.

Correlation Between Dual-energy and Perfusion CT in Patients with Focal Liver Lesions Using Third-generation Dual-source CT Scanner.

Objective To compare measurements of dual-energy CT iodine map parameters and liver perfusion CT parameters in patients with focal liver lesions using a third-generation dual-source CT scanner. Methods Between November 2015 and August 2016,33 patients with non-cystic focal lesions of liver were enrolled in this study. CT examinations were performed with a third-generation dual-source CT. The study CT protocol included a perfusion CT and dual-energy arterial and portal venous scans,with a time interval of 15 minutes. Iodine attenuation was measured at five region of interests including areas of high,medium,and low density within the lesion,as well as right and left liver parenchyma from the iodine map,while arterial liver perfusion (ALP),portal venous liver perfusion (PVP),and hepatic perfusion index (HPI) at the same location were measured from perfusion CT. The Pearson product-moment correlation coefficient was used to evaluate the relationship between iodine attenuation and perfusion parameters. Results The iodine attenuation at arterial phase showed significant intra-individual correlation with ALP (r=0.812,95% CI=0.728-0.885,P<0.001)and PVP (r=-0.209,95% CI=-0.323--0.073,P=0.007),but not significantly correlated with HPI (r=0.058,95% CI=0.046-0.498,P=0.461). The iodine attenuation at portal venous phase showed significant correlation with PVP (r=0.214,95% CI=0.072-0.361,P=0.005) but not with HPI(r=0.036,95% CI=-0.002-0.242,P=0.649). The mean effective dose of arterial phase and portal venous phase of dual-energy CT together [(3.53±1.17)mSv] was significantly lower than that of the perfusion CT [(14.53±0.45)mSv](t=25.212,P<0.001). Conclusion Iodine attenuation from arterial phase of dual energy CT demonstrates significant correlation with ALP and PVP,and iodine attenuation from portal venous phase demonstrates significant correlation with PVP.