Liver segmental volumes and their relationship with 5-year prognostication.

PURPOSE: This study aimed to analyze the predictive value of caudate to right lobe ratio (CRL-R) and liver segmental volume ratio (LSVR) for chronic liver disease (CLD) on routine abdominal CT scans and their association with 5-year decompensation- and transplant-free survival. METHOD: This retrospective study included 108 patients without CLD and 98 patients with biopsy-proven CLD. All patients underwent abdominal CT scans between 03/2015 and 08/2017. Patients with CLD were divided into three groups: early CLD (F0-F2; eCLD; n = 40), advanced CLD (F3-F4; aCLD; n = 20), and aCLD with clinically significant portal hypertension (aCLDPH; n = 38). CRL-R and LSVR were compared between groups using Kruskal-Wallis test and ROC analysis to determine cutoff-values. 5-year decompensation- and transplant-free survival were assessed by Kaplan-Meier curve analysis. RESULTS: CRL-R and LSVR were significantly different between all groups (p < 0.001). A CRL-R cutoff-value of > 0.99 predicted aCLD with a sensitivity of 69% and a specificity of 80% (AUC = 0.75, p < 0.001), while LSVR > 0.37 had a sensitivity of 67% and a specificity of 84% (AUC = 0.80, p < 0.001). CLD-patients with both CRL-R > 0.99 and LSVR > 0.37 had a significantly lower probability of 5-year decompensation-free survival (31%) as well as lower probability of 5-year transplant-free survival (41%) than those with a CRL-R < 0.99 and/or LSVR < 0.37 (70%, 62%, p = 0.006, p = 0.038). CONCLUSION: CRL-R and LSVR showed a high predictive value for CLD on routine abdominal CT scans. In patients with CLD, both CRL-R and LSVR may be combined and are associated with 5-year decompensation-free and transplant-free survival.

Impact of Simulated Reduced-Dose Chest CT on Diagnosing Pulmonary T1 Tumors and Patient Management.

To determine the diagnostic performance of simulated reduced-dose chest CT scans regarding pulmonary T1 tumors and assess the potential impact on patient management, a repository of 218 patients with histologically proven pulmonary T1 tumors was used. Virtual reduced-dose images were simulated at 25%- and 5%-dose levels. Tumor size, attenuation, and localization were scored by two experienced chest radiologists. The impact on patient management was assessed by comparing hypothetical LungRADS scores. The study included 210 patients (41% females, mean age 64.5 ± 9.2 years) with 250 eligible T1 tumors. There were differences between the original and the 5%-but not the 25%-dose simulations, and LungRADS scores varied between the dose levels with no clear trend. Sensitivity of Reader 1 was significantly lower using the 5%-dose vs. 25%-dose vs. original dose for size categorization (0.80 vs. 0.85 vs. 0.84; p = 0.007) and segmental localization (0.81 vs. 0.86 vs. 0.83; p = 0.018). Sensitivities of Reader 2 were unaffected by a dose reduction. A CT dose reduction may affect the correct categorization and localization of pulmonary T1 tumors and potentially affect patient management.

MRI Extracellular Volume Fraction in Liver Fibrosis-A Comparison of Different Time Points and Blood Pool Measurements.

BACKGROUND: Extracellular volume (ECV) correlates with the degree of liver fibrosis. PURPOSE: To analyze the performance of liver MRI-based ECV evaluations with different blood pool measurements at different time points. STUDY TYPE: Prospective. SAMPLE: 73 consecutive patients (n = 31 females, mean age 56 years) with histopathology-proven liver fibrosis. FIELD STRENGTH/SEQUENCE: 3T acquisition within 90 days of biopsy, including shortened modified look-locker inversion recovery T1 mapping. ASSESSMENT: Polygonal regions of interest were manually drawn in the liver, aorta, vena cava, and in the main, left and right portal vein on four slices before and after Gd-DOTA administration at 5/10/15 minutes. ECV was calculated 1) on one single slice on portal bifurcation level, and 2) averaged over all four slices. STATISTICAL TESTS: Parameters were compared between patients with fibrosis grades F0-2 and F3-F4 with the Mann-Whitney U and fishers exact test. ROC analysis was used to assess the performance of the parameters to predict F3-4 fibrosis. A P-value <0.05 was considered statistically significant. RESULTS: ECV was significantly higher in F3-4 fibrosis (35.4% [33.1%-37.6%], 36.1% [34.2%-37.5%], and 37.0% [34.8%-39.2%] at 5/10/15 minutes) than in patients with F0-2 fibrosis (33.3% [30.8%-34.8%], 33.7% [31.6%-34.7%] and 34.9% [32.2%-36.0%]; AUC = 0.72-0.75). Blood pool T1 relaxation times in the aorta and vena cava were longer on the upper vs. lower slices at 5 minutes, but not at 10/15 minutes. AUC values were similar when measured on a single slice (AUC = 0.69-0.72) or based on blood pool measurements in the cava or portal vein (AUC = 0.63-0.67 and AUC = 0.65-0.70). DATA CONCLUSION: Liver ECV is significantly higher in F3-4 fibrosis compared to F0-2 fibrosis with blood pool measurements performed in the aorta, inferior vena cava, and portal vein at 5, 10, and 15 minutes. However, a smaller variability was observed for blood pool measurements between slices at 15 minutes. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

MSCs mediate long-term efficacy in a Crohn's disease model by sustained anti-inflammatory macrophage programming via efferocytosis.

Mesenchymal stem cells (MSCs) are novel therapeutics for the treatment of Crohn's disease. However, their mechanism of action is unclear, especially in disease-relevant chronic models of inflammation. Thus, we used SAMP-1/YitFc (SAMP), a chronic and spontaneous murine model of small intestinal inflammation, to study the therapeutic effects and mechanism of action of human bone marrow-derived MSCs (hMSC). hMSC dose-dependently inhibited naïve T lymphocyte proliferation via prostaglandin E2 (PGE2) secretion and reprogrammed macrophages to an anti-inflammatory phenotype. We found that the hMSCs promoted mucosal healing and immunologic response early after administration in SAMP when live hMSCs are present (until day 9) and resulted in a complete response characterized by mucosal, histological, immunologic, and radiological healing by day 28 when no live hMSCs are present. hMSCs mediate their effect via modulation of T cells and macrophages in the mesentery and mesenteric lymph nodes (mLN). Sc-RNAseq confirmed the anti-inflammatory phenotype of macrophages and identified macrophage efferocytosis of apoptotic hMSCs as a mechanism that explains their long-term efficacy. Taken together, our findings show that hMSCs result in healing and tissue regeneration in a chronic model of small intestinal inflammation and despite being short-lived, exert long-term effects via sustained anti-inflammatory programming of macrophages via efferocytosis.

Automated liver segmental volume ratio quantification on non-contrast T1-Vibe Dixon liver MRI using deep learning.

PURPOSE: To evaluate the effectiveness of automated liver segmental volume quantification and calculation of the liver segmental volume ratio (LSVR) on a non-contrast T1-vibe Dixon liver MRI sequence using a deep learning segmentation pipeline. METHOD: A dataset of 200 liver MRI with a non-contrast 3 mm T1-vibe Dixon sequence was manually labeledslice-by-sliceby an expert for Couinaud liver segments, while portal and hepatic veins were labeled separately. A convolutional neural networkwas trainedusing 170 liver MRI for training and 30 for evaluation. Liver segmental volumes without liver vessels were retrieved and LSVR was calculated as the liver segmental volumes I-III divided by the liver segmental volumes IV-VIII. LSVR was compared with the expert manual LSVR calculation and the LSVR calculated on CT scans in 30 patients with CT and MRI within 6 months. RESULTS: Theconvolutional neural networkclassified the Couinaud segments I-VIII with an average Dice score of 0.770 ± 0.03, ranging between 0.726 ± 0.13 (segment IVb) and 0.810 ± 0.09 (segment V). The calculated mean LSVR with liver MRI unseen by the model was 0.32 ± 0.14, as compared with manually quantified LSVR of 0.33 ± 0.15, resulting in a mean absolute error (MAE) of 0.02. A comparable LSVR of 0.35 ± 0.14 with a MAE of 0.04 resulted with the LSRV retrieved from the CT scans. The automated LSVR showed significant correlation with the manual MRI LSVR (Spearman r = 0.97, p < 0.001) and CT LSVR (Spearman r = 0.95, p < 0.001). CONCLUSIONS: A convolutional neural network allowed for accurate automated liver segmental volume quantification and calculation of LSVR based on a non-contrast T1-vibe Dixon sequence.

Mesenchymal stem cells ameliorate inflammation in an experimental model of Crohn's disease via the mesentery.

Objective: Mesenchymal stem cells (MSCs) are novel therapeutics for treatment of Crohn's disease. However, their mechanism of action is unclear, especially in disease-relevant chronic models of inflammation. Thus, we used SAMP-1/YitFc, a chronic and spontaneous murine model of small intestinal inflammation, to study the therapeutic effect and mechanism of human bone marrow-derived MSCs (hMSC). Design: hMSC immunosuppressive potential was evaluated through in vitro mixed lymphocyte reaction, ELISA, macrophage co-culture, and RT-qPCR. Therapeutic efficacy and mechanism in SAMP were studied by stereomicroscopy, histopathology, MRI radiomics, flow cytometry, RT-qPCR, small animal imaging, and single-cell RNA sequencing (Sc-RNAseq). Results: hMSC dose-dependently inhibited naïve T lymphocyte proliferation in MLR via PGE 2 secretion and reprogrammed macrophages to an anti-inflammatory phenotype. hMSC promoted mucosal healing and immunologic response early after administration in SAMP model of chronic small intestinal inflammation when live hMSCs are present (until day 9) and resulted in complete response characterized by mucosal, histological, immunologic, and radiological healing by day 28 when no live hMSCs are present. hMSC mediate their effect via modulation of T cells and macrophages in the mesentery and mesenteric lymph nodes (mLN). Sc-RNAseq confirmed the anti-inflammatory phenotype of macrophages and identified macrophage efferocytosis of apoptotic hMSCs as a mechanism of action that explains their long-term efficacy. Conclusion: hMSCs result in healing and tissue regeneration in a chronic model of small intestinal inflammation. Despite being short-lived, exert long-term effects via macrophage reprogramming to an anti-inflammatory phenotype. Data Transparency Statement: Single-cell RNA transcriptome datasets are deposited in an online open access repository 'Figshare' (DOI: https://doi.org/10.6084/m9.figshare.21453936.v1 ).

Literature review: Imaging in prostate cancer.

Imaging plays an increasingly important role in the detection and characterization of prostate cancer (PC). This review summarizes the key conventional and advanced imaging modalities including multiparametric magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging and tries to instruct clinicians in finding the best image modality depending on the patient`s PC-stage. We aim to give an overview of the different image modalities and their benefits and weaknesses in imaging PC. Emphasis is put on primary prostate cancer detection and staging as well as on recurrent and castration resistant prostate cancer. Results from studies using various imaging techniques are discussed and compared. For the different stages of PC, advantages and disadvantages of the different imaging modalities are discussed. Moreover, this review aims to give an outlook about upcoming, new imaging modalities and how they might be implemented in the future into clinical routine. Imaging patients suffering from PC should aim for exact diagnosis, accurate detection of PC lesions and should mirror the true tumor burden. Imaging should lead to the best patient treatment available in the current PC-stage and should avoid unnecessary therapeutic interventions. New image modalities such as long axial field of view PET/CT with photon-counting CT and radiopharmaceuticals like androgen receptor targeting radiopharmaceuticals open up new possibilities. In conclusion, PC imaging is growing and each image modality is aiming for improvement.

Convolutional neural network for automated segmentation of the liver and its vessels on non-contrast T1 vibe Dixon acquisitions.

We evaluated the effectiveness of automated segmentation of the liver and its vessels with a convolutional neural network on non-contrast T1 vibe Dixon acquisitions. A dataset of non-contrast T1 vibe Dixon liver magnetic resonance images was labelled slice-by-slice for the outer liver border, portal, and hepatic veins by an expert. A 3D U-Net convolutional neural network was trained with different combinations of Dixon in-phase, opposed-phase, water, and fat reconstructions. The neural network trained with the single-modal in-phase reconstructions achieved a high performance for liver parenchyma (Dice 0.936 ± 0.02), portal veins (0.634 ± 0.09), and hepatic veins (0.532 ± 0.12) segmentation. No benefit of using multi-modal input was observed (p = 1.0 for all experiments), combining in-phase, opposed-phase, fat, and water reconstruction. Accuracy for differentiation between portal and hepatic veins was 99% for portal veins and 97% for hepatic veins in the central region and slightly lower in the peripheral region (91% for portal veins, 80% for hepatic veins). In conclusion, deep learning-based automated segmentation of the liver and its vessels on non-contrast T1 vibe Dixon was highly effective. The single-modal in-phase input achieved the best performance in segmentation and differentiation between portal and hepatic veins.

Computer-aided diagnosis through medical image retrieval in radiology.

Currently, radiologists face an excessive workload, which leads to high levels of fatigue, and consequently, to undesired diagnosis mistakes. Decision support systems can be used to prioritize and help radiologists making quicker decisions. In this sense, medical content-based image retrieval systems can be of extreme utility by providing well-curated similar examples. Nonetheless, most medical content-based image retrieval systems work by finding the most similar image, which is not equivalent to finding the most similar image in terms of disease and its severity. Here, we propose an interpretability-driven and an attention-driven medical image retrieval system. We conducted experiments in a large and publicly available dataset of chest radiographs with structured labels derived from free-text radiology reports (MIMIC-CXR-JPG). We evaluated the methods on two common conditions: pleural effusion and (potential) pneumonia. As ground-truth to perform the evaluation, query/test and catalogue images were classified and ordered by an experienced board-certified radiologist. For a profound and complete evaluation, additional radiologists also provided their rankings, which allowed us to infer inter-rater variability, and yield qualitative performance levels. Based on our ground-truth ranking, we also quantitatively evaluated the proposed approaches by computing the normalized Discounted Cumulative Gain (nDCG). We found that the Interpretability-guided approach outperforms the other state-of-the-art approaches and shows the best agreement with the most experienced radiologist. Furthermore, its performance lies within the observed inter-rater variability.

Multicenter Repeatability and Reproducibility of MR Fingerprinting in Phantoms and in Prostatic Tissue.

PURPOSE: To evaluate multicenter repeatability and reproducibility of T1 and T2 maps generated using MR fingerprinting (MRF) in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom and in prostatic tissues. METHODS: MRF experiments were performed on 5 different 3 Tesla MRI scanners at 3 different institutions: University Hospitals Cleveland Medical Center (Cleveland, OH), Brigham and Women's Hospital (Boston, MA) in the United States, and Diagnosticos da America (Rio de Janeiro, RJ) in Brazil. Raw MRF data were reconstructed using a Gadgetron-based MRF online reconstruction pipeline to yield quantitative T1 and T2 maps. The repeatability of T1 and T2 values over 6 measurements in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom was assessed to demonstrate intrascanner variation. The reproducibility between the 4 clinical scanners was assessed to demonstrate interscanner variation. The same-day test-retest normal prostate mean T1 and T2 values from peripheral zone and transitional zone were also compared using the intraclass correlation coefficient and Bland-Altman analysis. RESULTS: The intrascanner variation of values measured using MRF was less than 2% for T1 and 4.7% for T2 for relaxation values, within the range of 307.7 to 2360 ms for T1 and 19.1 to 248.5 ms for T2 . Interscanner measurements showed that the T1 variation was less than 4.9%, and T2 variation was less than 8.1% between multicenter scanners. Both T1 and T2 values in in vivo prostatic tissue demonstrated high test-retest reliability (intraclass correlation coefficient > 0.92) and strong linear correlation (R2  > 0.840). CONCLUSION: Prostate MRF measurements of T1 and T2 are repeatable and reproducible between MRI scanners at different centers on different continents for the above measurement ranges.

Avoiding the Intercostal Arteries in Percutaneous Thoracic Interventions.

The purpose of this study was to define relevant intercostal artery (ICA) anatomy potentially impacting the safety of thoracic percutaneous interventional procedures. An ICA abutting the upper rib and running in the subcostal groove was defined as the lowest risk zone for interventions requiring a supracostal needle puncture. A theoretical high-risk zone was defined by the ICA coursing in the lower half of the intercostal space (ICS), and a theoretical moderate-risk zone was defined by the ICA coursing below the subcostal groove but in the upper half of the ICS. Arterial phase computed tomography data from 250 patients were analyzed, revealing demographic variability, with high-risk zones extending more laterally with advancing age and with more cranial ribs. Overall, within the 97.5th percentile, an ICS puncture >7-cm lateral to the spinous process incurs moderate risk and >10-cm lateral incurs the lowest risk.

T1 reduction rate with Gd-EOB-DTPA determines liver function on both 1.5 T and 3 T MRI.

Magnetic resonance T1 mapping before and after Gd-EOB-DTPA administration allows quantification of the T1 reduction rate as a non-invasive surrogate marker of liver function. A major limitation of T1 relaxation time measurement is its dependency on MRI field strengths. Since T1 reduction rate is calculated as the relative shortening of T1 relaxation time before and after contrast administration, we hypothesized that the T1 reduction rate is comparable between 1.5 and 3 T. We thus compared liver T1 relaxation times between 1.5 and 3 T in a total of 243 consecutive patients (124, 1.5 T and 119, 3 T) between 09/2018 and 07/2019. T1 reduction rates were compared between patients with no cirrhosis and patients with cirrhosis Child-Pugh A-C. There was no significant difference of T1 reduction rate between 1.5 and 3 T in any patient group (p-value 0.126-0.861). On both 1.5 T and 3 T, T1 reduction rate allowed to differentiate between patients with no cirrhosis and patients with liver cirrhosis Child A-C (p < 0.001). T1 reduction rate showed a good performance to predict liver cirrhosis Child A (AUC = 0.83, p < 0.001), Child B (AUC = 0.83, p < 0.001) and Child C (AUC = 0.92, p < 0.001). In conclusion, T1 reduction rate allows to determine liver function on Gd-EOB-DTPA MRI with comparable values on 1.5 T and 3 T.

Diagnostic validation of a deep learning nodule detection algorithm in low-dose chest CT: determination of optimized dose thresholds in a virtual screening scenario.

OBJECTIVES: This study was conducted to evaluate the effect of dose reduction on the performance of a deep learning (DL)-based computer-aided diagnosis (CAD) system regarding pulmonary nodule detection in a virtual screening scenario. METHODS: Sixty-eight anthropomorphic chest phantoms were equipped with 329 nodules (150 ground glass, 179 solid) with four sizes (5 mm, 8 mm, 10 mm, 12 mm) and scanned with nine tube voltage/current combinations. The examinations were analyzed by a commercially available DL-based CAD system. The results were compared by a comparison of proportions. Logistic regression was performed to evaluate the impact of tube voltage, tube current, nodule size, nodule density, and nodule location. RESULTS: The combination with the lowest effective dose (E) and unimpaired detection rate was 80 kV/50 mAs (sensitivity: 97.9%, mean false-positive rate (FPR): 1.9, mean CTDIvol: 1.2 ± 0.4 mGy, mean E: 0.66 mSv). Logistic regression revealed that tube voltage and current had the greatest impact on the detection rate, while nodule size and density had no significant influence. CONCLUSIONS: The optimal tube voltage/current combination proposed in this study (80 kV/50 mAs) is comparable to the proposed combinations in similar studies, which mostly dealt with conventional CAD software. Modification of tube voltage and tube current has a significant impact on the performance of DL-based CAD software in pulmonary nodule detection regardless of their size and composition. KEY POINTS: • Modification of tube voltage and tube current has a significant impact on the performance of deep learning-based CAD software. • Nodule size and composition have no significant impact on the software's performance. • The optimal tube voltage/current combination for the examined software is 80 kV/50 mAs.

Knee Diameter and Cross-Sectional Area as Biomarkers for Cartilage Knee Degeneration on Magnetic Resonance Images.

Background and Objectives: Osteoarthritis (OA) of the knee is a degenerative disorder characterized by damage to the joint cartilage, pain, swelling, and walking disability. The purpose of this study was to assess whether demographic and radiologic parameters (knee diameters and knee cross-sectional area from magnetic resonance (MR) images) could be used as surrogate biomarkers for the prediction of OA. Materials and Methods: The knee diameters and cross-sectional areas of 481 patients were measured on knee MR images, and the corresponding demographic parameters were extracted from the patients' clinical records. The images were graded based on the modified Outerbridge arthroscopic classification that was used as ground truth. Receiver-operating characteristic (ROC) analysis was performed on the collected data. Results: ROC analysis established that age was the most accurate predictor of severe knee cartilage degeneration (corresponding to Outerbridge grades 3 and 4) with an area under the curve (AUC) of the specificity-sensitivity plot of 0.865 ± 0.02. An age over 41 years was associated with a sensitivity and specificity for severe degeneration of 82.8% (CI: 77.5-87.3%), and 76.4% (CI: 70.4-81.6%), respectively. The second-best degeneration predictor was the normalized knee cross-sectional area, with an AUC of 0.767 ± 0.04), followed by BMI (AUC = 0.739 ± 0.02), and normalized knee maximal diameter (AUC = 0.724 ± 0.05), meaning that knee degeneration increases with increasing knee diameter. Conclusions: Age is the best predictor of knee damage progression in OA and can be used as surrogate marker for knee degeneration. Knee diameters and cross-sectional area also correlate with the extent of cartilage lesions. Though less-accurate predictors of damage progression than age, they have predictive value and are therefore easily available surrogate markers of OA that can be used also by general practitioners and orthopedic surgeons.

Dual-energy CT of acute bowel ischemia.

Acute bowel ischemia is a condition with high mortality and requires rapid intervention to avoid catastrophic outcomes. Swift and accurate imaging diagnosis is essential because clinical findings are commonly nonspecific. Conventional contrast enhanced CT of the abdomen has been the imaging modality of choice to evaluate suspected acute bowel ischemia. However, subtlety of image findings and lack of non-contrast or arterial phase images can make correct diagnosis challenging. Dual-energy CT provides valuable information toward assessing bowel ischemia. Dual-energy CT exploits the differential X-ray attenuation at two different photon energy levels to characterize the composition of tissues and reveal the presence or absence of faint intravenous iodinated contrast to improve reader confidence in detecting subtle bowel wall enhancement. With the same underlying technique, virtual non-contrast images can help to show non-enhancing hyperdense hemorrhage of the bowel wall in intravenous contrast-enhanced scans without the need to acquire actual non-contrast scans. Dual-energy CT derived low photon energy (keV) virtual monoenergetic images emphasize iodine contrast and provide CT angiography-like images from portal venous phase scans to better evaluate abdominal arterial patency. In Summary, dual-energy CT aids diagnosing acute bowel ischemia in multiple ways, including improving visualization of the bowel wall and mesenteric vasculature, revealing intramural hemorrhage in contrast enhanced scans, or possibly reducing intravenous contrast dose.

Noninvasive assessment of clinically significant portal hypertension using ΔT1 of the liver and spleen and ECV of the spleen on routine Gd-EOB-DTPA liver MRI.

PURPOSE: To analyze the predictive value of ΔT1 of the liver and spleen as well as the extracellular volume fraction (ECV) of the spleen as noninvasive biomarkers for the determination of clinically significant portal hypertension (CSPH) on routine Gd-EOB-DTPA liver MRI. METHOD: 195 consecutive patients with known or suspected chronic liver disease from 9/2018 to 7/2019 with Gd-EOB-DTPA liver MRI and abdominal T1 mapping were retrospectively included. Based on the presence of splenomegaly with thrombocytopenia, ascites and portosystemic collaterals, the patients were divided into noCSPH (n = 113), compensated CSPH (cCSPH, ≥1 finding without ascites; n = 55) and decompensated CSPH (dCSPH, ascites ± other findings; n = 27). T1 times were measured in the liver, spleen and abdominal aorta in the unenhanced and contrast-enhanced T1 maps. Native T1 times and ΔT1 of the liver and spleen as well as ECV of the spleen were compared between groups using the Kruskal-Wallis test with Dunn's post hoc test. Furthermore, cutoff values for group differentiation were calculated using ROC analysis with Youden's index. RESULTS: ΔT1 of the liver was significantly lower in patients with cCSPH and dCSPH (p < 0.001) compared to patients with noCSPH. In the ROC analyses for differentiation between noCSPH and CSPH (cCSPH + dCSPH), a cutoff of < 0.67 for ΔT1 of the liver (AUC = 0.79) performed better than ΔT1 (AUC = 0.69) and ECV (AUC = 0.63) of the spleen with cutoffs of > 0.29 and > 41.9, respectively. CONCLUSION: ΔT1 of the liver and spleen in addition to ECV of the spleen allow for determination of CSPH on routine Gd-EOB-DTPA liver MRI.

Radial self-navigated native magnetic resonance angiography in comparison to navigator-gated contrast-enhanced MRA of the entire thoracic aorta in an aortic patient collective.

BACKGROUND: The native balanced steady state with free precession (bSSFP) magnetic resonance angiography (MRA) technique has been shown to provide high diagnostic image quality for thoracic aortic disease. This study compares a 3D radial respiratory self-navigated native MRA (native-SN-MRA) based on a bSSFP sequence with conventional Cartesian, 3D, contrast-enhanced MRA (CE-MRA) with navigator-gated respiration control for image quality of the entire thoracic aorta. METHODS: Thirty-one aortic native-SN-MRA were compared retrospectively (63.9 ± 10.3 years) to 61 CE-MRA (63.1 ± 11.7 years) serving as a reference standard. Image quality was evaluated at the aortic root/ascending aorta, aortic arch and descending aorta. Scan time was recorded. In 10 patients with both MRA sequences, aortic pathologies were evaluated and normal and pathologic aortic diameters were measured. The influence of artifacts on image quality was analyzed. RESULTS: Compared to the overall image quality of CE-MRA, the overall image quality of native-SN-MRA was superior for all segments analyzed (aortic root/ascending, p < 0.001; arch, p < 0.001, and descending, p = 0.005). Regarding artifacts, the image quality of native-SN-MRA remained superior at the aortic root/ascending aorta and aortic arch before and after correction for confounders of surgical material (i.e., susceptibility-related artifacts) (p = 0.008 both) suggesting a benefit in terms of motion artifacts. Native-SN-MRA showed a trend towards superior intraindividual image quality, but without statistical significance. Intraindividually, the sensitivity and specificity for the detection of aortic disease were 100% for native-SN-MRA. Aortic diameters did not show a significant difference (p = 0.899). The scan time of the native-SN-MRA was significantly reduced, with a mean of 05:56 ± 01:32 min vs. 08:51 ± 02:57 min in the CE-MRA (p < 0.001). CONCLUSIONS: Superior image quality of the entire thoracic aorta, also regarding artifacts, can be achieved with native-SN-MRA, especially in motion prone segments, in addition to a shorter acquisition time.