Optimizing the image quality of peripancreatic blood vessels through the clinical application of single-energy spectral computed tomography (CT) imaging.

Background: With the increase of pancreatic tumor patients in recent years, there is an urgent need to find a way to treat pancreatic tumors. Surgery is one of the best methods for the treatment of pancreatic tumors, the success of which depends on the evaluation of peripancreatic vessels before surgery. Computed tomography (CT), as a non-invasive, fast, and economical auxiliary examination method, is undoubtedly one of the best means of clinical auxiliary examination. In this study, we investigated the impact of single-energy spectral CT imaging on the image quality of peripancreatic blood vessels and the clinical value of low-keV imaging in enhancing the image quality of peripancreatic arteriovenous vessels. Methods: We prospectively enrolled 103 patients who underwent abdominal vascular-enhanced CT examinations at the Affiliated Hospital of Hebei University between December 2022 and May 2023 and who were all scanned with the dual-energy feature on the United Imaging ATLAS scanner. The images were reconstructed at 70 keV, mixed energy, and optimized single energy in the post-processing station of United Imaging Healthcare Technology Co., Ltd. The CT value and contrast-to-noise ratio (CNR) of the superior mesenteric artery (SMA), gastroduodenal artery (GDA), inferior pancreaticoduodenal artery (IPDA), and superior mesenteric vein (SMV) were compared across energy levels, and then the image quality was subjectively evaluated. One-way analysis of variance and rank-sum tests were utilized for the statistical analysis. Results: The CT values of SMA, GDA, IPDA, and SMV in the optimal single energy group were 358.37±70.24, 323.36±88.23, 300.76±76.27, and 257.74±20.56 Hounsfield unit (HU), respectively, which were superior to those in the mixed energy (241.66±47.69, 235.17±53.71, 207.36±45.17, and 187.39±23.21 HU) and 70 keV groups (260.89±54.27, 252.41±58.87, 223.17±43.65, and 203.18±18.17 HU) (P<0.05). The diagnostic efficacy was greater in the optimal single energy group than in the other 2 groups (4.63±0.50, 3.91±0.57, and 4.23±0.83) (P<0.05). Conclusions: The optimal single energy for showing peripancreatic blood vessels is 62±7 keV when utilizing single-energy spectral CT imaging.

Comparison of Machine Learning Models Using Diffusion-Weighted Images for Pathological Grade of Intrahepatic Mass-Forming Cholangiocarcinoma.

Is the radiomic approach, utilizing diffusion-weighted imaging (DWI), capable of predicting the various pathological grades of intrahepatic mass-forming cholangiocarcinoma (IMCC)? Furthermore, which model demonstrates superior performance among the diverse algorithms currently available? The objective of our study is to develop DWI radiomic models based on different machine learning algorithms and identify the optimal prediction model. We undertook a retrospective analysis of the DWI data of 77 patients with IMCC confirmed by pathological testing. Fifty-seven patients initially included in the study were randomly assigned to either the training set or the validation set in a ratio of 7:3. We established four different classifier models, namely random forest (RF), support vector machines (SVM), logistic regression (LR), and gradient boosting decision tree (GBDT), by manually contouring the region of interest and extracting prominent radiomic features. An external validation of the model was performed with the DWI data of 20 patients with IMCC who were subsequently included in the study. The area under the receiver operating curve (AUC), accuracy (ACC), precision (PRE), sensitivity (REC), and F1 score were used to evaluate the diagnostic performance of the model. Following the process of feature selection, a total of nine features were retained, with skewness being the most crucial radiomic feature demonstrating the highest diagnostic performance, followed by Gray Level Co-occurrence Matrix lmc1 (glcm-lmc1) and kurtosis, whose diagnostic performances were slightly inferior to skewness. Skewness and kurtosis showed a negative correlation with the pathological grading of IMCC, while glcm-lmc1 exhibited a positive correlation with the IMCC pathological grade. Compared with the other three models, the SVM radiomic model had the best diagnostic performance with an AUC of 0.957, an accuracy of 88.2%, a sensitivity of 85.7%, a precision of 85.7%, and an F1 score of 85.7% in the training set, as well as an AUC of 0.829, an accuracy of 76.5%, a sensitivity of 71.4%, a precision of 71.4%, and an F1 score of 71.4% in the external validation set. The DWI-based radiomic model proved to be efficacious in predicting the pathological grade of IMCC. The model with the SVM classifier algorithm had the best prediction efficiency and robustness. Consequently, this SVM-based model can be further explored as an option for a non-invasive preoperative prediction method in clinical practice.

Corrigendum: DWI Combined With Hepatobiliary Phase Enhanced Imaging Can Better Differentiate Cholangiocarcinoma From Atypical Liver Abscesses.

[This corrects the article DOI: 10.3389/fonc.2022.723089.].

DWI Combined With Hepatobiliary-Phase Enhanced Imaging Can Better Differentiate Cholangiocarcinoma From Atypical Liver Abscesses.

Objective: To investigate the value of diffusion-weighted imaging (DWI) combined with the hepatobiliary phase (HBP) Gd-BOPTA enhancement in differentiating intrahepatic mass-forming cholangiocarcinoma (IMCC) from atypical liver abscess. Materials and Methods: A retrospective analysis was performed on 43 patients with IMCCs (IMCC group) and 25 patients with atypical liver abscesses (liver abscess group). The DWI signal, the absolute value of the contrast noise ratio (│CNR│) at the HBP, and visibility were analyzed. Results: A relatively high DWI signal and a relatively high peripheral signal were presented in 29 patients (67.5%) in the IMCC group, and a relatively high DWI signal was displayed in 15 patients (60.0%) in the atypical abscess group with a relatively high peripheral signal in only one (6.7%) patient and a relatively high central signal in 14 (93.3%, 14/15). A significant (P<0.001) difference existed in the pattern of signal between the two groups of patients. On T2WI, IMCC was mainly manifested by homogeneous signal (53.5%), whereas atypical liver abscesses were mainly manifested by heterogeneous signal and relatively high central signal (32%, and 64%), with a significant difference (P<0.001) in T2WI imaging presentation between the two groups. On the HBP imaging, there was a statistically significant difference in peripheral │CNR│ (P< 0.001) and visibility between two groups. The sensitivity of the HBP imaging was significantly (P=0.002) higher than that of DWI. The sensitivity and accuracy of DWI combined with enhanced HBP imaging were significantly (P=0.002 and P<0.001) higher than those of either HBP imaging or DWI alone. Conclusion: Intrahepatic mass-forming cholangiocarcinoma and atypical liver abscesses exhibit different imaging signals, and combination of DWI and hepatobiliary-phase enhanced imaging has higher sensitivity and accuracy than either technique in differentiating intrahepatic mass-forming cholangiocarcinoma from atypical liver abscesses.

Radiation Dose Reduction in Head and Neck Computed Tomography Angiography.

BACKGROUND AND AIM: The study aims to investigate the feasibility of further radiation dose reduction via the application of a high iodine delivery rate combined with automatic current modulation technology (high noise index) in head and neck computed tomography angiography. METHODS: Sixty-four patients who underwent routine head and neck computed tomographic angiography were randomly divided into two groups: a low-dose group of 32 cases and an ultra-low-dose group of 32 cases. The same image reconstruction technique was applied in both groups using the 50% adaptive statistical iterative reconstruction method. Quantitative and qualitative image quality assessment of the carotid artery, computed tomographic dose index volume, dose length product, and effective dose of the two groups were analyzed. RESULTS: The two groups were not significantly (P>0.05) different in age, gender, and body mass index. Significant (P<0.001) reduction of radiation dose was observed in all the parameters of computed tomographic dose index volume (18.12%), dose length product (19.91%), and effective dose (19.84%) in the ultra-low-dose group. Quantitative and qualitative image assessment produced similar results between the two groups, except for the higher mean vascular computed tomographic values found in the ultra-low dose group. CONCLUSION: Application of a higher iodine delivery rate combined with automatic current modulation technology (high noise index) in an existing low tube voltage protocol can further decrease the radiation dose and the total volume of contrast agent while maintaining similar image quality for patients undergoing computed tomography angiography of the head and neck, which can be recommended as the conventional scanning method.