Paracetamol-induced Liver Injury in An Experimental Rat Model: Noninvasive Assessment using DKI and the Effect of Gadoxetate on DKI Parameters.

PURPOSE: To explore the potential of diffusion kurtosis imaging (DKI) for assessing the degree of liver injury in a paracetamol-induced rat model and to simultaneously investigate the effect of intravenous gadoxetate on DKI parameters. METHODS: Paracetamol was used to induce hepatoxicity in 39 rats. The rats were pathologically classified into 3 groups: normal (n=11), mild necrosis (n=18), and moderate necrosis (n=10). DKI was performed before and, 15 min, 25 min, and 45 min after gadoxetate administration. Repeated-measures ANOVA with Tukey's multiple comparison test was used to investigate the effect of gadoxetate on mean diffusivity (MD) and mean diffusion kurtosis (MK) and to assess the differences in MD and MK among the three groups. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic accuracy of the MD values when discriminating between the necrotic groups. RESULTS: Gadoxetate had no significant effect on either the MD or the MK, and the effect size was small. The MD in the moderate necrosis group was significantly lower than that in the other two groups (F = 13.502, p < 0.001; η2 = 0.428 [95% CI: 0.082-0.637]), while the MK did not significantly differ among the three groups (F = 2.702, p = 0.081; η2 = 0.131 [95% CI: 0.001-0.4003]). The AUCs of MD for discriminating the moderate necrosis or normal group from the other groups were 0.921 (95% CI: 0.832-1.000) and 0.831 (95% CI: 0.701-0.961), respectively. CONCLUSION: It would be better to measure the MD and MK before gadoxetate injection. MD showed potential for assessing the degree of liver necrosis in a paracetamol-induced liver injury rat model.

Multiparametric magnetic resonance imaging-based assessment of the effect of adenomyosis on determining the depth of myometrial invasion in endometrial cancer.

Background: Accurate preoperative diagnosis of endometrial cancer (EC) with deep myometrial invasion (DMI) is critical to deciding whether to perform lymphadenectomy. However, the presence of adenomyosis makes distinguishing DMI from superficial myometrial invasion (SMI) on magnetic resonance imaging (MRI) challenging. We aimed to evaluate the accuracy of multiparametric MRI (mpMRI) in diagnosing DMI in EC coexisting with adenomyosis (EC-A) compared with EC without coexisting adenomyosis and to evaluate the effect of different adenomyosis subtypes on myometrial invasion (MI) depth in EC. Methods: Patients with histologically confirmed International Federation of Gynecology and Obstetrics (FIGO) stage I EC who underwent preoperative MRI were consecutively included in this 2-center retrospective study. Institution 1 was searched from January 2017 to November 2022 and institution 2 was searched from June 2017 to March 2021. Patients were divided into 2 groups: group A, patients with EC-A; group B, EC patients without coexisting adenomyosis, matched 1:2 according to age ±5 years and tumor grade. A senior radiologist assessed the MRI adenomyosis classification in group A. Then, 2 radiologists (R1/R2) independently interpreted T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), T1-weighted contrast-enhanced (T1CE), and a combination of all images (mpMRI) respectively, and then assessed MI depth. Accuracy, sensitivity, specificity, and the areas under the receiver operating curve (AUC) were calculated. The chi-square test was used to compare the accuracy of diagnosing DMI. Interobserver agreement was evaluated using the Kappa test. Results: A total of 70 cases in group A and 140 cases in group B were included. The accuracy, sensitivity, and specificity of consensus were 94.3% [95% confidence interval (CI): 88.9-99.7%] vs. 92.1% (95% CI: 87.7-96.6%), 60.0% (95% CI: 17-92.7%) vs. 86.7% (95% CI: 68.4-95.6%), and 96.9% (95% CI: 88.4-95.5%) vs. 93.6% (95% CI: 86.8-97.2%) (group A vs. group B, respectively). There was no significant difference in the diagnostic accuracy of DMI on each sequence between the groups (Reviewer 1/Reviewer 2): PT2WI=0.14/0.17, PDWI=0.50/0.33, PT1CE=0.90/0.18, PmpMRI=0.50/0.37. The AUC for T2WI, DWI, T1CE, and mpMRI (Reviewer 1/Reviewer 2), respectively, were 0.54 (95% CI: 0.42-0.66)/0.78 (95% CI: 0.67-0.87), 0.63 (95% CI: 0.50-0.74)/0.77 (95% CI: 0.65-0.86), 0.69 (95% CI: 0.57-0.80)/0.79 (95% CI: 0.68-0.88), and 0.91 (95% CI: 0.82-0.97)/0.89 (95% CI: 0.79-0.95) (group A) and 0.83 (95% CI: 0.76-0.89)/0.85 (95% CI: 0.78-0.90), 0.83 (95% CI: 0.76-0.89)/0.86 (95% CI: 0.79-0.91), 0.88 (95% CI: 0.82-0.93)/0.86 (95% CI: 0.80-0.92), and 0.91 (95% CI: 0.85-0.95)/0.87 (95% CI: 0.80-0.92) (group B). Interobserver agreement was highest with mpMRI [κ=0.387/0.695 (case/control)]. The consensus results of MRI categorization of adenomyosis revealed no significant difference in the accuracy of diagnosing DMI by adenomyosis subtype (Pspatial relationship>0.99, Paffected area=0.52, Paffected pattern=0.58, Paffected size>0.99). Conclusions: The presence of adenomyosis or adenomyosis subtype had no significant effect on the interpretation of the depth of MI. T1CE can increase the contrast between adenomyosis and cancer foci; therefore, the information provided by T1CE should be valued.

Intravoxel incoherent motion assessment of liver fibrosis staging in MASLD.

PURPOSE: Partial correlation analysis was performed to account for the interference of steatosis changes and inflammatory factors, to determine the true correlation between fibrosis and IVIM parameters (Dfast, Dslow, and F), and to evaluate the diagnostic efficacy of IVIM for liver fibrosis. METHODS: A total of 106 patients with metabolic dysfunction-associated steatotic liver disease (MASLD) examined by IVIM from November 2016 to November 2023 at our hospital were retrospectively included. Preliminary analysis of each IVIM parameter and correlations with pathological findings were performed using Spearman correlation analysis, and partial correlation analysis was used to exclude the interference of other pathological factors, thus yielding the true correlations between IVIM parameters (Dfast, Dslow, and F) and pathology. The diagnostic efficacy of IVIM parameters for diagnosing MASLD was assessed via receiver operating characteristic (ROC) curve analysis. RESULTS: Spearman correlation analysis of all the IVIM parameters revealed correlations with steatosis, lobular inflammation, and ballooning. Partial correlation analysis indicated that Dfast was correlated with the pathological fibrosis stage (r = - 0.593, P < 0.001), Dslow was correlated with the pathological steatosis score (r = - 0.313, P < 0.05), and F was correlated with the pathological fibrosis stage and steatosis score (r = - 0.456 and 0.255, P < 0.001 and P < 0.05). In the diagnosis of hepatic fibrosis, significant hepatic fibrosis, advanced liver fibrosis and cirrhosis, Dfast achieved areas under the ROC curve of 0.763, 0.801, 0.853, and 0.897, respectively. The threshold values for diagnosing different fibrosis stages using Dfast (10-3 mm2/s) were 57.613, 54.587, 52.714, and 51.978, respectively. CONCLUSION: According to our partial correlation analysis, there was a moderate correlation between Dfast and F according to fibrosis stage, and Dfast was not influenced by inflammation or steatosis when diagnosing fibrosis in MASLD patients. A relatively close Dfast threshold is insufficient for accurately and noninvasively assessing various stages of MASLD fibrosis. In clinical practice, this approach can be considered an alternative method for the preliminary assessment of fibrosis in MASLD patients.

Assessment of cumulative cancer risk attributable to diagnostic X-ray radiation: a large cohort study.

OBJECTIVE: To assess the risk of cancer induced by diagnostic X-ray exposure in multiple radiological examinations and to explore the relevant influences to provide a reference for rational usage of X-ray examinations. METHODS: Data for all adult patients who underwent X-ray examinations from August 2004 to April 2020 in a general hospital was collected, including sex, age, primary diagnosis, and X-ray examination. Based on the Biological Effects of Ionizing Radiations report, age and sex and effective dose for a single X-ray examination were used to calculate the lifetime attributable risk (LAR). Patients whose cancer LAR values were in the top 5% were considered to have a high cancer risk; the factors influencing this status were explored by using multivariate logistic regression analyses. RESULTS: In total, 1,143,413 patients with 3,301,286 X-ray examinations were included. LARs of cancer incidence and death were < 0.2% and < 0.13% among 95% of patients and they were > 1% among 0.21% and 0.07% of patients. High risks of incidence and death were significantly associated with corrected exposure frequency (odds ratio [OR], 1.080 and 1.080), sex (OR, male vs. female, 0.421 and 0.372), and year of birth (OR, 1.088 and 1.054), with all p values < 0.001. Among 20 disease categories, congenital disease (OR, 3.792 and 4.024), genitourinary disease (OR, 3.608 and 3.202), digestive disease (OR, 3.247 and 3.272), and tumor disease (OR, 2.706 and 2.767) had the strongest associations with high risks of incidence and death (all p values < 0.001). CONCLUSIONS: Cancer risk induced by diagnostic X-ray examinations can be considered acceptable clinically. Patients having certain diseases are potentially at a relative higher risk due to recurrent examinations. KEY POINTS: • It was the first large-scale investigation of cumulative X-ray exposure in China, involving more than 3.3 million X-ray scans of all types of diagnostic X-ray examinations for about 1.1 million patients during the past 16 years. • The study revealed that the incidence risk of cancer induced by X-ray-related examinations was 0.01% on average, which was substantially lower than that of cancer induced by non-X-ray radiation. The risk could be considered acceptable clinically. • Patients having certain diseases were potentially at a relatively higher cancer risk due to recurrent X-ray examinations. The cumulative effect of X-ray exposure could not be ignored and was worthy of attention.

Noninvasive Assessment of APAP (N-acetyl-p-aminophenol)-Induced Hepatotoxicity Using Multiple MRI Parameters in an Experimental Rat Model.

BACKGROUND: Early detection and accurate assessment of N-acetyl-p-aminophenol (APAP)-induced hepatotoxicity can prevent further aggravation of liver injury and reduce the incidence of liver failure. PURPOSE: To evaluate the potential of multiple MRI parameters for assessing APAP-induced hepatotoxicity in an experimental rat model. STUDY TYPE: Prospective. ANIMAL MODEL: Twenty-one APAP-treated rats and 12 control rats. FIELD STRENGTH/SEQUENCE: A 3 T, T1 mapping, Gd-EOB-DTPA-enhanced MRI, and intravoxel incoherent motion (IVIM). ASSESSMENT: The severity of histological changes was assessed by a liver pathologist. Rat livers were pathologically classified into three groups: normal (n = 12), mild necrosis (n = 13), and moderate necrosis (n = 8). T1 relaxation time (T1) and diffusion parameters were measured. The reduction rate of T1 (ΔT1%) at different time points, the maximum value of ΔT1%, time period to the maximum value of ΔT1%, and time period from ΔT1max (%) to 2/3 value of ΔT1max (%) (ΔT1-T2/3) were calculated. Transporters activities like organic anion-transporting polypeptide 1 (oatp1) and multidrug resistance-associated protein 2 (mrp2) were compared among different necrotic groups. STATISTICAL TESTS: ANOVA/Kruskal-Wallis. Pearson/Spearman correlation. P < 0.05 was considered statistical significance. RESULTS: T1 Precontrast and ΔT1-T2/3 were strongly correlated with the severity of necrosis (r = 0.9094; r = 0.7978, respectively) and showed significant differences between the two groups. The apparent diffusion coefficient (ADC) and tissue diffusivity (D) values were significantly lower in the moderate necrosis group than in the normal and mild necrosis groups. The oatp1 activity of the necrosis groups was significantly reduced compared to that of the normal group, but the differences between normal and mild (P = 0.21), normal and moderate group (P = 0.56) were not significant. Meanwhile, enlargement of bile canaliculi and sparse microvilli was observed in the necrotic groups. CONCLUSION: MRI parameters such as precontrast T1 and ΔT1-T2/3 had promising potential in assessing the severity of early-stage hepatotoxicity in an APAP overdose rat model. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Deep learning analysis in coronary computed tomographic angiography imaging for the assessment of patients with coronary artery stenosis.

BACKGROUND AND OBJECTIVE: Recently, deep convolutional neural network has significantly improved image classification and image segmentation. If coronary artery disease (CAD) can be diagnosed through machine learning and deep learning, it will significantly reduce the burdens of the doctors and accelerate the critical patient diagnoses. The purpose of the study is to assess the practicability of utilizing deep learning approaches to process coronary computed tomographic angiography (CCTA) imaging (termed CCTA-artificial intelligence, CCTA-AI) in coronary artery stenosis. MATERIALS AND METHODS: A CCTA reconstruction pipeline was built by utilizing deep learning and transfer learning approaches to generate auto-reconstructed CCTA images based on a series of two-dimensional (2D) CT images. 150 patients who underwent successively CCTA and digital subtraction angiography (DSA) from June 2017 to December 2017 were retrospectively analyzed. The dataset was divided into two parts comprising training dataset and testing dataset. The training dataset included the CCTA images of 100 patients which are trained using convolutional neural networks (CNN) in order to further identify various plaque classifications and coronary stenosis. The other 50 CAD patients acted as testing dataset that is evaluated by comparing the auto-reconstructed CCTA images with traditional CCTA images on the condition that DSA images are regarded as the reference method. Receiver operating characteristic (ROC) analysis was used for statistical analysis to compare CCTA-AI with DSA and traditional CCTA in the aspect of detecting coronary stenosis and plaque features. RESULTS: AI significantly reduces time for post-processing and diagnosis comparing to the traditional methods. In identifying various degrees of coronary stenosis, the diagnostic accuracy of CCTA-AI is better than traditional CCTA (AUCAI = 0.870, AUCCCTA = 0.781, P < 0.001). In identifying ≥ 50% stenotic vessels, the accuracy, sensitivity, specificity, positive predictive value and negative predictive value of CCTA-AI and traditional method are 86% and 83%, 88% and 59%, 85% and 94%, 73% and 84%, 94% and 83%, respectively. In the aspect of identifying plaque classification, accuracy of CCTA-AI is moderate compared to traditional CCTA (AUC = 0.750, P < 0.001). CONCLUSION: The proposed CCTA-AI allows the generation of auto-reconstructed CCTA images from a series of 2D CT images. This approach is relatively accurate for detecting ≥50% stenosis and analyzing plaque features compared to traditional CCTA.

Assessment of liver fibrosis with liver and spleen magnetic resonance elastography, serum markers in chronic liver disease.

BACKGROUND: The accurate assessment of liver fibrosis is essential for patients with chronic liver disease. A liver biopsy is an invasive procedure that has many potential defects and complications. Therefore, noninvasive assessment techniques are of considerable value for clinical diagnosis. Liver and spleen magnetic resonance elastography (MRE) and serum markers have been proposed for quantitative and noninvasive assessment of liver fibrosis. This study aims to compare the diagnostic performance of liver and spleen stiffness measured by MRE, fibrosis index based on the 4 factors (FIB-4), aspartate aminotransferase-to-platelet ratio index (APRI), and their combined models for staging hepatic fibrosis. METHODS: One hundred and twenty patients with chronic liver disease underwent MRE scans. Liver and spleen stiffness were measured by the MRE stiffness maps. Serum markers were collected to calculate FIB-4 and APRI. Liver biopsies were used to identify pathologic grading. Spearman's rank correlation analysis evaluated the correlation between the parameters and fibrosis stages. Receiver operating characteristic (ROC) analysis evaluated the performance of the four individual parameters, a liver and spleen stiffness combined model, and an all-parameters combined model in assessing liver fibrosis. RESULTS: Liver stiffness, spleen stiffness, FIB-4, and APRI were all correlated with fibrosis stage (r=0.87, 0.64, 0.65, and 0.51, respectively, all P<0.001). Among the 4 individual diagnostic markers, liver stiffness showed the highest values in staging F1-4, F2-4, F3-4 and F4 (AUC =0.89, 0. 97, 0.95, and 0.95, all P<0.001). The AUCs of the liver and spleen stiffness combined model in the F1-4, F2-4, F3-4, and F4 staging groups were 0.89, 0.97, 0.95, and 0.96, respectively (all P<0.001). The corresponding AUCs of the all-parameters combined model were 0.90, 0.97, 0.95, and 0.96 (all P<0.001). The AUCs of the liver and spleen stiffness combined model were significantly higher than those of APRI, FIB-4 in the F2-4, F3-4, and F4 staging groups (all P<0.05). Both combined models were not significantly different from liver stiffness in staging liver fibrosis (all P>0.05). CONCLUSIONS: Liver stiffness measured with MRE had better diagnostic performance than spleen stiffness, APRI, and FIB-4 for fibrosis staging. The combined models did not significantly improve the diagnostic value compared with liver stiffness in staging fibrosis.