Liver Magnetic Resonance Imaging Research Articles

Pre-operative prediction of histopathological growth patterns of colorectal cancer liver metastasis using MRI-based radiomic models.

Histopathological growth patterns (HGPs) of colorectal liver metastases (CRLMs) have prognostic value. However, the differentiation of HGPs relies on postoperative pathology. This study aimed to develop a magnetic resonance imaging (MRI)-based radiomic model to predict HGP pre-operatively, following the latest guidelines. This retrospective study included 93 chemotherapy-naïve patients with CRLMs who underwent contrast-enhanced liver MRI and a partial hepatectomy between 2014 and 2022. Radiomic features were extracted from the tumor zone (RTumor), a 2-mm outer ring (RT+2), a 2-mm inner ring (RT-2), and a combined ring (R2+2) on late arterial phase MRI images. Analysis of variance method (ANOVA) and least absolute shrinkage and selection operator (LASSO) algorithms were used for feature selection. Logistic regression with five-fold cross-validation was used for model construction. Receiver operating characteristic curves, calibrated curves, and decision curve analyses were used to assess model performance. DeLong tests were used to compare different models. Twenty-nine desmoplastic and sixty-four non-desmoplastic CRLMs were included. The radiomic models achieved area under the curve (AUC) values of 0.736, 0.906, 0.804, and 0.794 for RTumor, RT-2, RT+2, and R2+2, respectively, in the training cohorts. The AUC values were 0.713, 0.876, 0.785, and 0.777 for RTumor, RT-2, RT+2, and R2+2, respectively, in the validation cohort. RT-2 exhibited the best performance. The MRI-based radiomic models could predict HGPs in CRLMs pre-operatively.

Effects of Semaglutide on Muscle Structure and Function in the SLIM LIVER Study.

Semaglutide, a GLP-1 receptor agonist, is highly effective for decreasing weight. Concomitant loss of muscle mass often accompanies weight loss and may have consequences on muscle function. This is a secondary analysis from the SLIM LIVER (ACTG A5371) study, a single-arm study of semaglutide in people with HIV (PWH) with metabolic dysfunction-associated steatotic liver disorder (MASLD). Participants received subcutaneous semaglutide for 24 weeks (titrated to 1 mg/week by week 4). Psoas volume and fat fraction were assessed from liver magnetic resonance imaging and physical function by 10-time chair rise test and 4m gait speed. Mean change from baseline to week 24 was estimated with linear regression modeling. 51 PWH enrolled; muscle measures were available from 46 participants. The mean age was 50 (standard deviation [SD] 11) years and BMI 35.5 (5.6) kg/m2, 43% were women, 33% Black, and 39% Hispanic/Latino. Psoas muscle volume decreased by 9.3% (95% confidence interval [CI]: -13.4, -5.2; p<0.001) over 24 weeks but psoas muscle fat did not significantly change (-0.42%, CI: -1.00, 0.17; p=0.16). Chair rise and gait speed had non-significant improvements of 1.27 seconds (CI: -2.7, 0.10) and 0.05 m/sec (CI: -0.01, 0.10), respectively (both p>0.07). The prevalence of slow gait speed (< 1 m/sec) decreased from 63% to 46% (p=0.029). In PWH receiving low-dose semaglutide for MASLD, despite decreased psoas muscle volume, there was no significant change in physical function. This suggests that function was maintained despite significant loss of muscle concomitant with weight loss.

Quantitative and qualitative evaluation of high-quality hepatobiliary phase imaging with shortened timing and utility in patients with compromised liver function.

To compare high flip angle (FA) hepatobiliary-phase (hHBP) imaging with variable time intervals to conventional HBP (cHBP) to assess the impact of increased FA on image quality in shortened HBP imaging. Data from 218 patients, divided into normal liver group (n = 184) and decompensated liver group (n = 34), who underwent liver magnetic resonance imaging (MRI) including 10-min, 15-min, 20-min hHBP, and cHBP were analyzed. Signal-to-noise ratio (SNR), contrast-ratio (CR), contrast-to-noise ratio (CNR), signal intensity ratios (SIRs), and relative enhancement (RE) of the liver were calculated for quantitative analysis. Sharpness, noise, and artifacts of the image, contrast media visibility, overall image quality, and lesion conspicuity were evaluated by two abdominal radiologists. Quantitative analysis showed that SNR, RE, SIR for liver/muscle, liver/spleen, and CR of all hHBP images demonstrated a significantly higher value compared to cHBP images in the normal liver group (p < 0.001). These values were also superior in the normal liver group compared to the decompensated liver group (p < 0.01). In qualitative analysis, both normal and decompensated liver groups exhibited significantly superior image sharpness in all hHBP images compared to cHBP images and the overall image quality of the 15-min and 20-min hHBP did not show significant difference compared to cHBP. All values tended to be better in the normal liver group than the decompensated liver group with statistical significance except for lesion conspicuity (p < 0.01). High-FA HBP has proven to be a valuable image acquisition method, potentially shortening liver MR imaging time while maintaining acceptable image quality.

Risk of type 2 diabetes, MASLD and cardiovascular disease in people living with polycystic ovary syndrome.

Abstract Background Polycystic ovary syndrome (PCOS) is associated with adverse clinical outcomes that may differ according to PCOS phenotype. Methods Using UK Biobank data, we compared the incidence of type 2 diabetes (T2D), metabolic dysfunction associated steatotic liver disease, cardiovascular disease (CVD), hormone-dependent cancers, and dementia between PCOS participants and age- and body mass index-matched controls. We also compared multiorgan (liver, cardiac, and brain) magnetic resonance imaging (MRI) data and examined the impact of PCOS phenotype (hyperandrogenic and normoandrogenic) on these outcomes. Results We included 1008 women with PCOS (defined by diagnostic codes, self-reported diagnoses, or clinical/biochemical features of hyperandrogenism and a/oligoCmenorrhoea) and 5017 matched controls (5:1 ratio); median age, 61 years, body mass index, 28.4 kg/m². Adjusted Cox proportional hazard modeling demonstrated PCOS participants had greater incident T2D [hazard ratio (HR) 1.47; 95% confidence interval (CI), 1.11-1.95] and all-cause CVD (1.76; 1.35-2.30). No between-group differences existed for cancers or dementia. Liver MRI confirmed more PCOS participants had hepatic steatosis (proton density fat fraction &amp;gt;5.5%: 35.9 vs 23.9%; P = .02) and higher fibroinflammation (corrected T1 721.4 vs 701.5 ms; P = &amp;lt;.01) vs controls. No between-group difference existed for cardiac (biventricular/atrial structure and function) or brain (grey and white matter volumes) imaging. Normoandrogenic (but not hyperandrogenic) PCOS participants had greater incident all-cause CVD (1.82; 1.29-2.56) while hyperandrogenic (but not normoandrogenic) PCOS participants were more likely to have hepatic steatosis (8.96 vs 6.04 vs 5.23%; P = .03) with greater fibroinflammation (776.3 vs 707.7 vs 701.9 ms; P=&amp;lt;.01). Conclusion Cardiometabolic disease may be increased in PCOS patients with a disease phenotype-specific pattern.

Evaluation of the ability of insulin resistance and lipid-related indices to predict the presence of NAFLD in obese adolescents

BackgroundNonalcoholic fatty liver disease (NAFLD) has become an important health issue in adolescents. Although several parameters and indices have been investigated for the evaluation of NAFLD in adults, these indices are limited in adolescents. In this study, body mass index, waist circumference, triponderal mass index, HbA1c, homeostatic model assessment insulin resistance (HOMA-IR), triglyceride/high-density lipoprotein (Tg/HDL), the lipid accumulation product (LAP) index, the triglyceride-glucose (TyG) index and the aminotransferase (AT) index were examined together, and their diagnostic values in the clinical treatment of NAFLD were compared.Materials and methodsSeventynine adolescents (10–19 years old) with obesity who were admitted to a pediatric clinic between January and August 2022 and who were diagnosed with exogenous obesity without any comorbidities were included in the study. The presence of NAFLD was evaluated by liver magnetic resonance imaging. The laboratory findings were obtained retrospectively from system records. Parameters were compared between the NAFLD (+) and NAFLD (-) groups. Logistic regression analysis was used to determine the most effective factors for NAFLD treatment. Receiver operating characteristic (ROC) analysis was performed with significant indices. Sex, HOMA-IR, TyG and AT indices were evaluated together with multivariate analysis to design a diagnostic scale.ResultsHbA1c, HOMA-IR, AT indices and TyG indices were greater in the NAFLD (+) group (P = 0.012; P = 0.001; P = 0.012; P = 0.002, respectively). There was a positive correlation between liver fat percentage and HOMA-IR, the TyG index, the AT index, and Tg/HDL. According to the regression analysis, male sex and elevated HOMA-IR were determined to be significant risk factors for the presence of NAFLD. A probability scale with 4 parameters [sex, HOMA-IR, the TyG index, and alanine aminotransferase (ALT)] was designed with 82.5% specificity and 80% sensitivity.ConclusionEvaluation of the HOMA-IR and TyG indices, especially in high-risk patients, will support the diagnosis of NAFLD via ultrasonography. A probability scale with ALT, HOMA-IR, TyG, and sex data with a diagnostic accuracy of 80% may aid in the diagnosis of NAFLD in adolescents with obesity.

Diagnostic performance of CT/MRI LI-RADS v2018 in non-cirrhotic steatotic liver disease.

To assess the performance of computed tomography (CT)/magnetic resonance imaging (MRI) Liver Imaging Reporting and Data System (LI-RADS) among patients with non-cirrhotic steatotic liver disease (SLD). This IRB-approved, retrospective study included 119 observations from 77 adult patients (36 women, 41 men; median 64 years) who underwent liver CT or MRI from 2010 to 2023. All patients had histopathologic evidence of SLD without cirrhosis. Three board-certified abdominal radiologists blinded to tissue diagnosis and imaging follow-up assessed observations with LI-RADS. The positive predictive value (PPV), sensitivity, specificity, accuracy, and inter-reader agreement were calculated. Seventy-five observations (63%) were benign and 44 (37%) were malignant. PPV for hepatocellular carcinoma (HCC) was 0-0% for LR-1, 0-0% for LR-2, 0-7% for LR-3, 11-20% for LR-4, 75-88% for LR-5, 0-8% for LR-M, and 50-75% for LR-TIV. For LR-5 in identifying HCC, sensitivity was 79-83%, specificity was 91-97%, and accuracy was 89-92%. For composite categories of LR-5, LR-M, or LR-TIV in identifying malignancy, sensitivity was 86-89%, specificity was 85-96%, and accuracy was 86-93%. The most common false positives for LR-5 were hepatocellular adenomas. Only 59-65% of HCCs showed non-peripheral washout at CT versus 67-83% at MRI, though nearly all had an enhancing capsule. PPV and accuracy of LR-5 for HCC did not differ by modality. Inter-reader agreement for major features ranged from 0.667 to 0.830 and was 0.766 for the final category. Despite challenges such as the lower prevalence of non-peripheral washout at CT and overlapping imaging features between HCC and hepatocellular adenomas, LI-RADS may serve as an effective tool in assessing focal liver lesions in SLD. LI-RADS in non-cirrhotic steatotic liver disease can effectively diagnose hepatocellular carcinoma and malignancy at computed tomography and magnetic resonance imaging, thereby guiding clinical management decisions and expediting patient care pathways. Performance of LI-RADS is unknown in non-cirrhotic patients with steatotic liver disease. LI-RADS 5 category showed a high pooled specificity of 91-97% for hepatocellular carcinoma. LI-RADS can non-invasively risk stratify focal liver observations in non-cirrhotic patients with steatotic liver disease.

Radiomics and machine learning analysis of liver magnetic resonance imaging for prediction and early detection of tumor response in colorectal liver metastases.

The aim of this study was to demonstrate the effectiveness of a machine learning-based radiomics model for distinguishing tumor response and overall survival in patients with unresectable colorectal liver metastases (CRLM) treated with targeted biological therapy. We prospectively recruited 17 patients with unresectable liver metastases of colorectal cancer, who had been given targeted biological therapy as the first line of treatment. All patients underwent liver magnetic resonance imaging (MRI) three times up until 8 weeks after chemotherapy. We evaluated the diagnostic performance of machine learning-based radiomics model in tumor response of liver MRI compared with the guidelines for the Response Evaluation Criteria in Solid Tumors. Overall survival was evaluated using the Kaplan-Meier analysis and compared to the Cox proportional hazard ratios following univariate and multivariate analyses. Performance measurement of the trained model through metrics showed the accuracy of the machine learning model to be 76.5%, and the area under the receiver operating characteristic curve was 0.857 (95% confidence interval [CI], 0.605-0.976; P < 0.001). For the patients classified as non-progressing or progressing by the radiomics model, the median overall survival was 17.5 months (95% CI, 12.8-22.2), and 14.8 months (95% CI, 14.2-15.4), respectively (P = 0.431, log-rank test). Machine learning-based radiomics models could have the potential to predict tumor response in patients with unresectable CRLM treated with biologic therapy.

Machine learning reveals the contribution of lipoproteins to liver triglyceride content and inflammation.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the most common chronic liver disease worldwide and is strongly associated with metabolic comorbidities, including dyslipidemia. Herein, we aim to estimate the prevalence of MASLD and metabolic dysfunction-associated steatohepatitis (MASH) in Europeans with isolated hypercholesterolemia and isolated hypertriglyceridemia in the UK Biobank and to estimate the independent contribution of lipoproteins to liver triglyceride content. We selected 218,732 Europeans from the UK Biobank without chronic viral hepatitis and other causes of liver disease, of whom 14,937 with liver magnetic resonance imaging (MRI) data available. Next, to examine the relationships between traits in predicting liver triglyceride content, we compared the predictive performance of several machine learning methods and selected the best performing algorithms based on the minimum cross-validated mean squared error (MSE). There was an approximately 3-fold and 4-fold enrichment of MASLD and MASH in individuals with isolated hypertriglyceridemia (p=1.23E-41 and p=1.29E-10, respectively), whereas individuals with isolated hypercholesterolemia had a marginal higher rate of MASLD and no difference in MASH rate compared to control group (p=0.019 and p=0.97, respectively). Among machine learning methods, feed-forward neural network had the best cross-validation MSE on the validation set. Circulating triglycerides, after body mass index (BMI), were the second strongest independent predictor of liver proton density fat fraction (PDFF) with the largest absolute mean Shapley additive explanation (SHAP) value. Isolated hypertriglyceridemia is the second strongest, after obesity, independent predictor of MASLD/MASH. Individuals with hypertriglyceridemia, but not with hypercholesterolemia, should be screened for liver disease.

Inhibition of hepatocellular carcinoma cells through ferroptosis therapy using Fe3O4/Ag nanocomposites

In the current study, Fe3O4/Ag nanohybrids demonstrating high efficiency in liver cancer ferroptosis therapy and MR imaging were synthesized using a facile one-pot approach. Subsequently, their morphology, chemical composition, structure, Fenton reaction activity, and magnetic resonance (MR) contrast effect were systemically assessed. Importantly, the in vitro studies demonstrated that the Fe3O4/Ag nanohybrids had a high therapeutic efficiency in treating liver cancer cells and performed exceptionally well during T2-weight MR imaging. Correspondingly, these Fe3O4/Ag nanohybrids demonstrate significant potential for use in the field of biomedicine.

Utility of abbreviated MRI in the post-treatment evaluation of rectal cancer.

Post-treatment evaluation of patients with rectal cancer (RC) using magnetic resonance imaging (MRI) burdens medical resources, necessitating an exploration of abbreviated protocols. To evaluate the diagnostic performance of abbreviated MRI (A-MRI) for the post-treatment evaluation of RC patients. This retrospective study included RC patients who underwent non-contrast rectal MRI and standard liver MRI, as well as abdominal contrast-enhanced computed tomography (CECT) for post-treatment evaluation. A-MRI comprised diffusion-weighted imaging (DWI) and T2-weighted imaging of the upper abdomen and the pelvic cavity. Three radiologists independently reviewed A-MRI, CECT, and standard liver MRI in the detection of viable disease. The diagnostic performances were compared using a reference standard considering all available information, including pathology, FDG-PET, endoscopic results, and clinical follow-up. We included 78 patients (50 men, 28 women; mean age=60.9 ± 10.2 years) and observed viable disease in 34 (43.6%). On a per-patient-basis analysis, A-MRI showed significantly higher sensitivity (95% vs. 81%, P = 0.04) and higher accuracy (93% vs. 82%, P < 0.01), compared to those of CECT, while A-MRI showed comparable sensitivity (91% vs. 91%, P = 0.42) and accuracy (97% vs. 98%, P = 0.06) to that of standard liver MRI. On a per-lesion-based analysis, A-MRI exhibited significantly superior lesion detectability than that of CECT (figure of merit 0.91 vs. 0.77, P < 0.01) and comparable to that of standard liver MRI (figure of merit 0.91 vs. 0.92, P = 0.75). A-MRI exhibited higher sensitivity and diagnostic accuracy than those of CECT in the post-treatment evaluation of RC, while it showed comparable performances with standard liver MRI. A-MRI provides diagnostic added value in the follow-up of RC patients.

Accelerated Diffusion-Weighted Magnetic Resonance Imaging of the Liver at 1.5 T With Deep Learning-Based Image Reconstruction: Impact on Image Quality and Lesion Detection.

To perform image quality comparison between deep learning-based multiband diffusion-weighted sequence (DL-mb-DWI), accelerated multiband diffusion-weighted sequence (accelerated mb-DWI), and conventional multiband diffusion-weighted sequence (conventional mb-DWI) in patients undergoing clinical liver magnetic resonance imaging (MRI). Fifty consecutive patients who underwent clinical MRI of the liver at a 1.5-T scanner, between September 1, 2021, and January 31, 2022, were included in this study. Three radiologists independently reviewed images using a 5-point Likert scale for artifacts and image quality factors, in addition to assessing the presence of liver lesions and lesion conspicuity. DL-mb-DWI acquisition time was 65.0 ± 2.4 seconds, significantly (P < 0.001) shorter than conventional mb-DWI (147.5 ± 19.2 seconds) and accelerated mb-DWI (94.3 ± 1.8 seconds). DL-mb-DWI received significantly higher scores than conventional mb-DWI for conspicuity of the left lobe (P < 0.001), sharpness of intrahepatic vessel margin (P < 0.001), sharpness of the pancreatic contour (P < 0.001), in-plane motion artifact (P = 0.002), and overall image quality (P = 0.005) by reader 2. DL-mb-DWI received significantly higher scores for conspicuity of the left lobe (P = 0.006), sharpness of the pancreatic contour (P = 0.020), and in-plane motion artifact (P = 0.042) by reader 3. DL-mb-DWI received significantly higher scores for strength of fat suppression (P = 0.004) and sharpness of the pancreatic contour (P = 0.038) by reader 1. The remaining quality parameters did not reach statistical significance for reader 1. Novel diffusion-weighted MRI sequence with deep learning-based image reconstruction demonstrated significantly decreased acquisition times compared with conventional and accelerated mb-DWI sequences, while maintaining or improving image quality for routine abdominal MRI. DL-mb-DWI offers a potential alternative to conventional mb-DWI in routine clinical liver MRI.

Using GPT-4 for LI-RADS feature extraction and categorization with multilingual free-text reports.

The Liver Imaging Reporting and Data System (LI-RADS) offers a standardized approach for imaging hepatocellular carcinoma. However, the diverse styles and structures of radiology reports complicate automatic data extraction. Large language models hold the potential for structured data extraction from free-text reports. Our objective was to evaluate the performance of Generative Pre-trained Transformer (GPT)-4 in extracting LI-RADS features and categories from free-text liver magnetic resonance imaging (MRI) reports. Three radiologists generated 160 fictitious free-text liver MRI reports written in Korean and English, simulating real-world practice. Of these, 20 were used for prompt engineering, and 140 formed the internal test cohort. Seventy-two genuine reports, authored by 17 radiologists were collected and de-identified for the external test cohort. LI-RADS features were extracted using GPT-4, with a Python script calculating categories. Accuracies in each test cohort were compared. On the external test, the accuracy for the extraction of major LI-RADS features, which encompass size, nonrim arterial phase hyperenhancement, nonperipheral 'washout', enhancing 'capsule' and threshold growth, ranged from .92 to .99. For the rest of the LI-RADS features, the accuracy ranged from .86 to .97. For the LI-RADS category, the model showed an accuracy of .85 (95% CI: .76, .93). GPT-4 shows promise in extracting LI-RADS features, yet further refinement of its prompting strategy and advancements in its neural network architecture are crucial for reliable use in processing complex real-world MRI reports.

Added Value of Liver MRI in Patients Eligible for Surgical Resection or Ablation of Colorectal Liver Metastases Based on CT: A Systematic Review and Meta-Analysis.

Abdominal computed tomography (CT) is the standard imaging modality for detection and staging in patients with colorectal liver metastases (CRLM). Although liver magnetic resonance imaging (MRI) is superior to CT in detecting small lesions, guidelines are ambiguous regarding the added value of an additional liver MRI in the surgical workup of patients with CRLM. Therefore, this systematic review and meta-analysis aimed to evaluate the clinical added value of liver MRI in patients eligible for resection or ablation of CRLM based on CT. A systematic search was performed in the PubMed, Embase, and Cochrane Library databases through June 23, 2023. Studies investigating the impact of additional MRI on local treatment plan following CT in patients with CRLM were included. Risk of bias was assessed using the QUADAS-2 tool. The pooled weighted proportions for the primary outcome were calculated using random effect meta-analysis. Overall, 11 studies with 1440 patients were included, of whom 468 patients (32.5%) were assessed for change in local treatment plan. Contrast-enhanced liver MRI was used in 10 studies, including gadoxetic acid in 9 studies. Liver MRI with diffusion-weighted imaging was used in 8 studies. Pooling of data found a 24.12% (95% confidence interval, 15.58%-32.65%) change in the local treatment plan based on the added findings of liver MRI following CT. Sensitivity analysis including 5 studies (268 patients) focusing on monophasic portal venous CT followed by gadoxetic acid-enhanced liver MRI with diffusion-weighted imaging showed a change of local treatment plan of 17.88% (95% confidence interval, 5.14%-30.62%). This systematic review and meta-analysis found that liver MRI changed the preinterventional local treatment plan in approximately one-fifth of patients eligible for surgical resection or ablation of CRLM based on CT. These findings suggest a clinically relevant added value of routine liver MRI in the preinterventional workup of CRLM, which should be confirmed by large prospective studies.

Focal fatty sparing areas of the pediatric steatotic liver: pseudolesions on hepatobiliary phase magnetic resonance images.

Focal fatty sparing in liver can be detected as hyperintense pseudolesions on hepatobiliary phase magnetic resonance imaging (MRI). Distinguishing these pseudolesions from liver lesions may make diagnosis challenging. The aim of this study was to evaluate the imaging features of fatty sparing areas on liver MRI in pediatric patients who have been administered gadoxetate disodium. A total of 63 patients between January 2018 and June 2023 underwent gadoxetate disodium-enhanced liver MRI, and 9 (14%) patients with a focal fatty sparing were included in the study. The fat spared areas were evaluated qualitatively and quantitatively including signal intensity measurements and fat fraction calculations. The liver MRI examinations of 9 patients (5 boys, 4 girls; aged 8-18 years, median age: 14.4) using gadoxetate disodium were evaluated. Based on in-phase and opposed-phase sequences, 13 areas of focal fatty sparing were identified. The mean fat fraction of the liver and fat spared areas were 26.2% (range, 15-47) and 9% (range, 2-17), respectively. All fat spared areas were hyperintense in the hepatobiliary phase images. The mean relative enhancement ratios of the liver and fat spared areas were 0.78 (range, 0.35-1.6) and 1.11 (range, 0.45-1.9), respectively. Focal fatty sparing in liver in children was observed as hyperintense on hepatobiliary phase MRI, and it should not be identified as a focal liver lesion.

Congenital diaphragmatic hernia: automatic lung and liver MRI segmentation with nnU-Net, reproducibility of pyradiomics features, and a machine learning application for the classification of liver herniation

Prenatal assessment of lung size and liver position is essential to stratify congenital diaphragmatic hernia (CDH) fetuses in risk categories, guiding counseling, and patient management. Manual segmentation on fetal MRI provides a quantitative estimation of total lung volume and liver herniation. However, it is time-consuming and operator-dependent. In this study, we utilized a publicly available deep learning (DL) segmentation system (nnU-Net) to automatically contour CDH-affected fetal lungs and liver on MRI sections. Concordance between automatic and manual segmentation was assessed by calculating the Jaccard coefficient. Pyradiomics standard features were then extracted from both manually and automatically segmented regions. The reproducibility of features between the two groups was evaluated through the Wilcoxon rank-sum test and intraclass correlation coefficients (ICCs). We finally tested the reliability of the automatic-segmentation approach by building a ML classifier system for the prediction of liver herniation based on support vector machines (SVM) and trained on shape features computed both in the manual and nnU-Net-segmented organs. We compared the area under the classifier receiver operating characteristic curve (AUC) in the two cases. Pyradiomics features calculated in the manual ROIs were partly reproducible by the same features calculated in nnU-Net segmented ROIs and, when used in the ML procedure, to predict liver herniation (both AUC around 0.85). Conclusion: Our results suggest that automatic MRI segmentation is feasible, with good reproducibility of pyradiomics features, and that a ML system for liver herniation prediction offers good reliability. Trial registration: https://clinicaltrials.gov/ct2/show/NCT04609163?term=NCT04609163&draw=2&rank=1; Clinical Trial Identification no. NCT04609163.What is Known:• Magnetic resonance imaging (MRI) is crucial for prenatal congenital diaphragmatic hernia (CDH) assessment. It enables the quantification of the total lung volume and the extent of liver herniation, which are essential for stratifying the severity of CDH, guiding counseling, and patient management.• The manual segmentation of MRI scans is a time-consuming process that is heavily reliant upon the skill set of the operator.What is New:• MRI lung and liver automatic segmentation using the deep learning nnU-Net system is feasible, with good Jaccard coefficient values and satisfactory reproducibility of pyradiomics features compared to manual results.• A feasible ML system for predicting liver herniation could improve prenatal assessments and CDH patient management.

Pancreatic iron in pediatric transfusion-dependent beta-thalassemia patients: A longitudinal MRI study.

In pediatric transfusion-dependent thalassemia (TDT) patients, we evaluated the prevalence, pattern, and clinical associations of pancreatic siderosis and the changes in pancreatic iron levels and their association with baseline and changes in total body iron balance. We considered 86 pediatric TDT patients consecutively enrolled in the Extension-Myocardial Iron Overload in Thalassemia Network. Iron overload (IO) was quantified by R2* magnetic resonance imaging (MRI). Sixty-three (73%) patients had pancreatic IO (R2*>38Hz). Global pancreas R2* values were significantly correlated with mean serum ferritin levels, MRI liver iron concentration (LIC) values, and global heart R2* values. Global pancreas R2* values were significantly higher in patients with altered versus normal glucose metabolism. Thirty-one patients also performed the follow-up MRI at 18±3months. Higher pancreatic R2* values were detected at the follow-up, but the difference versus the baseline MRI was not significant. The 20% of patients with baseline pancreatic IO showed no pancreatic IO at the follow-up. The 46% of patients without baseline pancreatic IO developed pancreatic siderosis. The changes in global pancreas R2* between the two MRIs were not correlated with baseline serum ferritin levels, baseline, final, and changes in MRI LIC values, or baseline pancreatic iron levels. In children with TDT, pancreatic siderosis is a frequent finding associated with hepatic siderosis and represents a risk factor for myocardial siderosis and alterations of glucose metabolism. Iron removal from the pancreas is exceptionally challenging and independent from hepatic iron status.

Multi-average high-acceleration modified volumetric interpolated breath-hold examination (VIBE) for free-breathing multiphase contrast-enhanced liver MRI: a comparative study with breath-hold VIBE.

Breath-hold volumetric interpolated breath-hold examination (BH-VIBE) of multiphase contrast-enhanced liver magnetic resonance imaging (MPCE-LMRI) requires good cooperative individuals to comply with multiple breath-holds. To develop a free-breathing modified VIBE (FB-mVIBE) as a substitute of BH-VIBE in MPCE-LMRI. We modified VIBE with a high acceleration factor (2 × 2) and four averages to produce the mVIBE scan. A total of 90 individuals (40 men; mean age = 54.6 ± 10.0 years) who had received MPCE-LMRI as part of a voluntary health check-up for oncology survey were enrolled. Each participant was scanned in four phases (pre-contrast, arterial phase, venous phase, and delay phase), and each phase had two sequential scans. To encounter the timing effect of contrast enhancement, three scan orders were designed: BH-VIBE and FB-mVIBE (group A, n = 30); BH-VIBE and FB-VIBE (group B, n = 30); and FB-mVIBE and BH-VIBE (group C, n = 30). The comparisons included the objective measurements and 25 visual-score by two abdominal radiologists independently. Consistency between raters was observed for all three sequences (intraclass correlation coefficient [ICC] = 0.741-0.829). For rater 1, the mean scores of FB-mVIBE (23.67 ± 1.32) were equal to those of BH-VIBE (23.83 ± 1.98) in groups C and B (P = 0.852). The mean scores of FB-mVIBE (22.07 ± 3.02), but significantly higher than those of FB-VIBE (14.7 ± 3.41) in groups A and B (P <0.001). Similar scores were found for rater 2. The objective measurement of FB-mVIBE were equal to or higher than BH-VIBE and markedly superior to FB-VIBE. FB-mVIBE is a practical alternative to BH-VIBE for individuals who cannot cooperate with multiple breath-holds for MPCE-LMRI.

Signal Intensity Trajectories Clustering for Liver Vasculature Segmentation and Labeling (LiVaS) on Contrast-Enhanced MR Images: A Feasibility Pilot Study.

This study aims to develop a semiautomated pipeline and user interface (LiVaS) for rapid segmentation and labeling of MRI liver vasculature and evaluate its time efficiency and accuracy against manual reference standard. Retrospective feasibility pilot study. Liver MR images from different scanners from 36 patients were included, and 4/36 patients were randomly selected for manual segmentation as referenced standard. The liver was segmented in each contrast phase and masks registered to the pre-contrast segmentation. Voxel-wise signal trajectories were clustered using the k-means algorithm. Voxel clusters that best segment the liver vessels were selected and labeled by three independent radiologists and a research scientist using LiVaS. Segmentation times were compared using a paired-sample t-test on log-transformed data. The agreement was analyzed qualitatively and quantitatively using DSC for hepatic and portal vein segmentations. The mean segmentation time among four readers was significantly shorter than manual (3.6 ± 1.4 vs. 70.0 ± 29.2min; p < 0.001), even when using a higher number of clusters to enhance accuracy. The DSC for portal and hepatic veins reached up to 0.69 and 0.70, respectively. LiVaS segmentations were overall of good quality, with variations in performance related to the presence/severity of liver disease, acquisition timing, and image quality. Our semi-automated pipeline was robust to different MRI vendors in producing segmentation and labeling of liver vasculature in agreement with expert manual annotations, with significantly higher time efficiency. LiVaS could facilitate the creation of large, annotated datasets for training and validation of neural networks for automated MRI liver vascularity segmentation. HIGHLIGHTS: Key Finding: In this pilot feasibility study, our semiautomated pipeline for segmentation of liver vascularity (LiVaS) on MR images produced segmentations with simultaneous labeling of portal and hepatic veins in good agreement with the manual reference standard but at significantly shorter times (mean LiVaS 3.6 ± 1.4 vs. mean manual 70.0 ± 29.2min; p < 0.001). Importance: LiVaS was robust in producing liver MRI vascular segmentations across images from different scanners in agreement with expert manual annotations, with significant ly higher time efficiency, and therefore potential scalability.

Perfusion MR Imaging of Liver: Principles and Clinical Applications.

Perfusion imaging techniques provide quantitative characterization of tissue microvasculature. Perfusion MR of liver is particularly challenging because of dual afferent flow, need for large organ high-resolution coverage, and significant movement with respiration. The most common MR technique used for quantifying liver perfusion is dynamic contrast-enhanced MR imaging. Here, the authors describe the various perfusion MR models of the liver, the basic concepts behind implementing a perfusion acquisition, and clinical results that have been obtained using these models.

From strength to precision: A systematic review exploring the clinical utility of 7-Tesla magnetic resonance imaging in abdominal imaging.

After approval for clinical use in 2017 early investigations of ultra-high-field abdominal magnetic resonance imaging (MRI) have demonstrated the feasibility as well as diagnostic capabilities of liver, kidney, and prostate MRI at 7-Tesla. However, the elevation of the field strength to 7-Tesla not only brought advantages to abdominal MRI but also presented considerable challenges and drawbacks, primarily stemming from heightened artifacts and limitations in Specific Absorption Rate, etc. Furthermore, evidence in the literature is relatively scarce concerning human studies in comparison to phantom/animal studies which necessitates an investigation into the evidence so far in humans and summarizing all relevant evidence. To offer a comprehensive overview of current literature on clinical abdominal 7T MRI that emphasizes current trends, details relevant challenges, and provides a concise set of potential solutions. This systematic review adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A PubMed search, utilizing Medical Subject Headings terms such as "7-Tesla" and organ-specific terms, was conducted for articles published between January 1, 1985, and July 25, 2023. Eligibility criteria included studies exploring 7T MRI for imaging human abdominal organs, encompassing various study types (in-vivo/ex-vivo, method development, reviews/meta-analyses). Exclusion criteria involved animal studies and those lacking extractable data. Study selection involved initial identification via title/abstract, followed by a full-text review by two researchers, with discrepancies resolved through discussion. Data extraction covered publication details, study design, population, sample size, 7T MRI protocol, image characteristics, endpoints, and conclusions. The systematic review included a total of 21 studies. The distribution of clinical 7T abdominal imaging studies revealed a predominant focus on the prostate (n = 8), followed by the kidney (n = 6) and the hepatobiliary system (n = 5). Studies on these organs, and in the pancreas, demonstrated clear advantages at 7T. However, small bowel studies showed no significant improvements compared to traditional MRI at 1.5T. The majority of studies evaluated originated from Germany (n = 10), followed by the Netherlands (n = 5), the United States (n = 5), Austria (n = 2), the United Kingdom (n = 1), and Italy (n = 1). Further increase of abdominal clinical MRI field strength to 7T demonstrated high imaging potential, yet also limitations mainly due to the inhomogeneous radiofrequency (RF) excitation field relative to lower field strengths. Hence, further optimization of dedicated RF coil elements and pulse sequences are expected to better optimize clinical imaging at high magnetic field strength.