Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study.

OBJECTIVES: To investigate the effect of deep learning image reconstruction (DLIR) on the accuracy of iodine quantification and image quality of dual-energy CT (DECT) compared to that of other reconstruction algorithms in a phantom experiment and an abdominal clinical study. METHODS: An elliptical phantom with five different iodine concentrations (1-12 mgI/mL) was imaged five times with fast-kilovoltage-switching DECT for three target volume CT dose indexes. All images were reconstructed using filtered back-projection, iterative reconstruction (two levels), and DLIR algorithms. Measured and nominal iodine concentrations were compared among the algorithms. Contrast-enhanced CT of the abdomen with the same scanner was acquired in clinical patients. In arterial and portal venous phase images, iodine concentration, image noise, and coefficients of variation for four locations were retrospectively compared among the algorithms. One-way repeated-measures analyses of variance were used to evaluate differences in the iodine concentrations, standard deviations, coefficients of variation, and percentages of error among the algorithms. RESULTS: In the phantom study, the measured iodine concentrations were equivalent among the algorithms: within ± 8% of the nominal values, with root-mean-square deviations of 0.08-0.36 mgI/mL, regardless of radiation dose. In the clinical study (50 patients; 35 men; mean age, 68 ± 11 years), iodine concentrations were equivalent among the algorithms for each location (all p > .99). Image noise and coefficients of variation were lower with DLIR than with the other algorithms (all p < .01). CONCLUSIONS: The DLIR algorithm reduced image noise and variability of iodine concentration values compared with other reconstruction algorithms in the fast-kilovoltage-switching dual-energy CT. KEY POINTS: • In the phantom study, standard deviations and coefficients of variation in iodine quantification were lower on images with the deep learning image reconstruction algorithm than on those with other algorithms. • In the clinical study, iodine concentrations of measurement location in the upper abdomen were consistent across four reconstruction algorithms, while image noise and variability of iodine concentrations were lower on images with the deep learning image reconstruction algorithm.

Abbreviated Gadoxetic Acid-Enhanced MRI for the Detection of Liver Metastases in Patients With Potentially Resectable Pancreatic Ductal Adenocarcinoma.

BACKGROUND: Gadoxetic acid-enhanced magnetic resonance imaging (MRI) is useful in detecting liver metastases from pancreatic ductal adenocarcinoma (PDAC). However, the long examination time limits its utility in the initial workup of patients with PDAC. PURPOSE: To evaluate the incremental value of an abbreviated gadoxetic acid-enhanced MRI for the detection of liver metastases in patients with PDAC. STUDY TYPE: Retrospective. POPULATION: Patients (N = 130) with potentially resectable PDAC (women, 58 [44.6%]). FIELD STRENGTH/SEQUENCE: 1.5 T and 3 T; gradient dual-echo T1-weighted (in-phase and opposed-phase), fat-suppressed fast spin-echo T2-weighted, single-shot echo-planar diffusion-weighted, and three-dimensional fat-suppressed T1-weighted gradient-echo dynamic contrast-enhanced and hepatobiliary phase sequences, as well as contrast-enhanced computed tomography (CECT). ASSESSMENT: Three radiologists independently reviewed three different image sets to detect liver metastases: set 1, CECT alone; set 2, CECT and abbreviated MRI comprising fat-suppressed T2-weighted, diffusion-weighted, and hepatobiliary phase images; and set 3, CECT and standard gadoxetic acid-enhanced MRI. STATISTICAL TESTS: Figure of merit (FOM) was compared using the jackknife alternative free-response receiver operating characteristics, and other per-lesion and per-patient diagnostic parameters for each image set were compared using McNemar's and Fisher's test. P < 0.05 was considered statistically significant. RESULTS: A total of 43 liver metastases were identified in 13 patients. Reader-averaged FOM to detect liver metastases were significantly higher for sets 2 (0.884) and 3 (0.886) than for set 1 (0.609), while they were comparable between sets 2 and 3 (P = 0.96). The mean per-patient sensitivities, negative predictive values, and accuracies were significantly higher for sets 2 and 3 than for set 1, while those between sets 2 and 3 were not significantly different (not applicable, P > 0.99, and P > 0.99, respectively). DATA CONCLUSION: Gadoxetic acid-enhanced MRI combined with CECT had higher diagnostic performance than CECT alone for the detection of liver metastases in patients with PDAC. The incremental values were comparable for the abbreviated MRI and standard MRI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Estimation of pancreatic fibrosis and prediction of postoperative pancreatic fistula using extracellular volume fraction in multiphasic contrast-enhanced CT.

OBJECTIVE: To investigate the diagnostic performance of the extracellular volume (ECV) fraction in multiphasic contrast-enhanced computed tomography (CE-CT) for estimating histologic pancreatic fibrosis and predicting postoperative pancreatic fistula (POPF). METHODS: Eighty-five patients (49 men; mean age, 69 years) who underwent multiphasic CE-CT followed by pancreaticoduodenectomy with pancreaticojejunal anastomosis between January 2012 and December 2018 were retrospectively included. The ECV fraction was calculated from absolute enhancements of the pancreas and aorta between the precontrast and equilibrium-phase images, followed by comparisons among histologic pancreatic fibrosis grades (F0‒F3). The diagnostic performance of the ECV fraction in advanced fibrosis (F2‒F3) was evaluated using receiver operating characteristic curve analysis. Multivariate logistic regression analysis was used to evaluate the associations of the risk of POPF development with patient characteristics, histologic findings, and CT imaging parameters. RESULTS: The mean ECV fraction of the pancreas was 34.4% ± 9.5, with an excellent intrareader agreement of 0.811 and a moderate positive correlation with pancreatic fibrosis (r = 0.476; p < 0.001). The mean ECV fraction in advanced fibrosis was significantly higher than that in no/mild fibrosis (44.4% ± 10.8 vs. 31.7% ± 6.7; p < 0.001), and the area under the receiver operating characteristic curve for the diagnosis of advanced fibrosis was 0.837. Twenty-two patients (25.9%) developed clinically relevant POPF. Multivariate logistic regression analysis demonstrated that the ECV fraction was a significant predictor of POPF. CONCLUSIONS: The ECV fraction can offer quantitative information for assessing pancreatic fibrosis and POPF after pancreaticojejunal anastomosis. KEY POINTS: • There was a moderate positive correlation of the extracellular volume (ECV) fraction of the pancreas in contrast-enhanced CT with the histologic grade of pancreatic fibrosis (r = 0.476; p < 0.001). • The ECV fraction was higher in advanced fibrosis (F2‒F3) than in no/mild fibrosis (F0‒F1) (p < 0.001), with an AUC of 0.837 for detecting advanced fibrosis. • The ECV fraction was an independent risk factor for predicting subclinical (odds ratio, 0.81) and clinical (odds ratio, 0.80) postoperative pancreatic fistula.

Clinical Application of Quantitative MR Imaging in Nonalcoholic Fatty Liver Disease.

Viral hepatitis was previously the most common cause of chronic liver disease. However, in recent years, nonalcoholic fatty liver disease (NAFLD) cases have been increasing, especially in developed countries. NAFLD is histologically characterized by fat, fibrosis, and inflammation in the liver, eventually leading to cirrhosis and hepatocellular carcinoma. Although biopsy is the gold standard for the assessment of the liver parenchyma, quantitative evaluation methods, such as ultrasound, CT, and MRI, have been reported to have good diagnostic performances. The quantification of liver fat, fibrosis, and inflammation is expected to be clinically useful in terms of the prognosis, early intervention, and treatment response for the management of NAFLD. The aim of this review was to discuss the basics and prospects of MRI-based tissue quantifications of the liver, mainly focusing on proton density fat fraction for the quantification of fat deposition, MR elastography for the quantification of fibrosis, and multifrequency MR elastography for the evaluation of inflammation.

Evaluation and Prediction of Treatment Response for Hepatocellular Carcinoma.

The incidence of hepatocellular carcinoma (HCC) is still on the rise in North America and Europe and is the second leading cause of cancer-related mortality. The treatment of HCC varies, with surgery and locoregional therapy (LRT) such as radiofrequency ablation and transcatheter arterial chemoembolization, and radiation therapy being the primary treatment. Currently, systemic therapy with molecular-targeted agents and immune checkpoint inhibitors (ICIs) is becoming a major treatment option for the unresectable HCC. As the HCC after LRT or systemic therapy often remains unchanged in size and shows loss of contrast effect in contrast-enhanced CT or MRI, the response evaluation criteria in solid tumors (RECIST) and World Health Organization criteria, which are usually used to evaluate the treatment response of solid tumors, are not appropriate for HCC. The modified RECIST (mRECIST) and the European Association for the Study of the Liver (EASL) criteria were developed for HCC, with a focus on viable lesions. The latest 2018 edition of the Liver Imaging Reporting and Data System (LI-RADS) also includes a section on the evaluation of treatment response. The cancer microenvironment influences the therapeutic efficacy of ICIs. Several studies have examined the utility of gadoxetic acid-enhanced MRI for predicting the pathological and molecular genetic patterns of HCC. In the future, it may be possible to stratify prognosis and predict treatment response prior to systemic therapy by using pre-treatment imaging findings.

Added value of contrast enhancement boost images in routine multiphasic contrast-enhanced CT for the diagnosis of small (<20 mm) hypervascular hepatocellular carcinoma.

PURPOSE: To investigate the added value of contrast enhancement boost (CE-boost) images in multiphasic contrast-enhanced CT (CE-CT) for diagnosing small (<20 mm) hypervascular hepatocellular carcinoma (HCC). MATERIALS AND METHODS: This retrospective study included 69 patients (age, 74 ± 8 years; 52 men) with 70 hypervascular HCCs (<20 mm) who underwent multiphasic CE-CT (pre-contrast, late arterial phase [LAP], portal venous phase [PVP], and equilibrium phase). Two types of CE-boost images were generated by subtracting PVP from LAP (LA-PV) images and LAP from PVP (PV-LA) images to enhance the contrast effect of hepatic arterial and portal venous perfusion more selectively. Tumor-to-liver contrast-to-noise ratios (CNRs) in CE-boost images were compared with those in CE-CT images using the Wilcoxon signed-rank test. Two independent readers reviewed the imaging datasets: CE-CT alone and CE-CT with CE-boost images. The diagnostic performance of each dataset was compared using jackknife alternative free-response receiver operating characteristics (JAFROC-1). RESULTS: The tumor-to-liver CNRs in the LA-PV (6.4 ± 3.0) and PV-LA (-3.3 ± 2.1) images were greater than those in the LAP (3.2 ± 1.7) and PVP images (-1.1 ± 1.4) (p <.001 for both). The reader-averaged figures of merit were 0.751 for CE-CT alone and 0.807 for CE-CT with CE-boost images (p <.001). Sensitivities increased by adding CE-boost images for both readers (p <.001 and = 0.03), while positive predictive values were equivalent (p >.99). CONCLUSION: Adding CE-boost images to multiphasic CE-CT can improve the diagnostic accuracy and sensitivity for small hypervascular HCC by increasing the tumor-to-liver CNR.

Prediction of post-hepatectomy liver failure using gadoxetic acid-enhanced magnetic resonance imaging for hepatocellular carcinoma with portal vein invasion.

PURPOSE: Accurate prediction of post-hepatectomy liver failure (PHLF) is important in advanced hepatocellular carcinoma (HCC). We aimed to retrospectively evaluate the utility of gadoxetic acid-enhanced MRI for predicting PHLF in patients who underwent anatomic hepatectomy for HCC with portal vein invasion. METHODS: Forty-one patients (32 men, 9 women) were included. Hepatobiliary-phase MR images were acquired 20 min after injection of gadoxetic acid using a 3D fat-suppressed T1-weighted spoiled gradient-echo sequence. Liver-spleen ratio (LSR), remnant hepatocellular uptake index (rHUI), and HUI were calculated. The severity of PHLF was defined according to the International Study Group of Liver Surgery. Differences in LSR between the resected liver and the remnant liver, and HUI and rHUI/HUI between no/mild and severe PHLF were compared using the Wilcoxon signed-rank test and Wilcoxon rank-sum test, respectively. Univariate and multivariate logistic regression analyses were performed to identify predictors of severe PHLF. Areas under the receiver operating characteristic curves (AUCs) of rHUI and rHUI/HUI were calculated for predicting severe PHLF. RESULTS: Nine patients developed severe PHLF. LSR of the remnant liver was significantly higher than that of the resected liver (P < 0.001). Severe PHLF demonstrated significantly lower rHUI (P < 0.001) and rHUI/HUI (P < 0.001) compared with no/mild PHLF. Multivariate logistic regression analysis showed that decreased rHUI (P = 0.012, AUC=0.885) and rHUI/HUI (P = 0.002, AUC=0.852) were independent predictors of severe PHLF. CONCLUSION: Gadoxetic acid-enhanced MRI can be a promising noninvasive examination for assessing global and regional liver function, allowing estimation of the functional liver remnant and accurate prediction of severe PHLF before hepatic resection.