Liver Observation Segmentation on Contrast-Enhanced MRI: SAM and MedSAM Performance in Patients With Probable or Definite Hepatocellular Carcinoma.

Purpose: To evaluate factors impacting the Segment Anything Model (SAM) and variant MedSAM performance for segmenting liver observations on contrast-enhanced (CE) magnetic resonance imaging (MRI) in high-risk patients with probable hepatocellular carcinoma (HCC) (LR-4) and definite HCC (LR-5). Methods: A retrospective cohort of liver observations (LR-4/LR-5) on CE-MRI from 97 patients at high-risk for HCC was derived (2013-2018). Using bounding-boxes as prompts under 5-fold cross-validation, segmentation performance was evaluated at the model and liver observation-levels for: (1) model types: SAM versus MedSAM, (2) image sizes: 256 × 256 versus 512 × 512, (3) image channel composition: CE sequences at 3 phases of enhancement independently and combined, (4) liver observation size: >10 mm versus >20 mm, (5) certainty of diagnosis: LR-4 versus LR-5, and (6) contrast-agent type: hepatobiliary versus extracellular. Segmentation performance, quantified using Dice coefficient, were compared using univariate (Wilcoxon signed-rank and t-test) and multivariable analyses (multiple correspondence analysis and subsequent linear modelling). Results: MedSAM trained on 512 × 512 combined CE sequences performed best with mean Dice coefficient 0.68 (95% confidence interval 0.66, 0.69). Overall, all factors except contrast-agent type affected performance, with larger image size resulting in the highest performance improvement (512 × 512: 0.57, 256 × 256: 0.26, P < .001) at the model-level. Contrast-agents affected performance for patients with LR-4 observations using MedSAM-based models (P < .03). Larger observation size, image size, and higher certainty of diagnosis were associated with better segmentation on multivariable analysis. Conclusion: A variety of factors were found to impact SAM/MedSAM performance for segmenting liver observations in patients with probable and definite HCC on CE-MRI. Future models may be optimized by accounting for these factors.

MRI features associated with HCC histologic subtypes: a western American and European bicenter study.

OBJECTIVES: To evaluate if preoperative MRI can predict the most frequent HCC subtypes in North American and European patients treated with surgical resection. METHODS: A total of 119 HCCs in 97 patients were included in the North American group and 191 HCCs in 176 patients were included in the European group. Lesion subtyping was based on morphologic features and immuno-histopathological analysis. Two radiologists reviewed preoperative MRI and evaluated the presence of imaging features including LI-RADS major and ancillary features to identify clinical, biologic, and imaging features associated with the main HCC subtypes. RESULTS: Sixty-four percent of HCCs were conventional. The most frequent subtypes were macrotrabecular-massive (MTM-15%) and steatohepatitic (13%). Necrosis (OR = 3.32; 95% CI: 1.39, 7.89; p = .0064) and observation size (OR = 1.011; 95% CI: 1.0022, 1.019; p = .014) were independent predictors of MTM-HCC. Fat in mass (OR = 15.07; 95% CI: 6.57, 34.57; p < .0001), tumor size (OR = 0.97; 95% CI: 0.96, 0.99; p = .0037), and absence of chronic HCV infection (OR = 0.24; 95% CI: 0.084, 0.67; p = .0068) were independent predictors of steatohepatitic HCC. Independent predictors of conventional HCCs were viral C hepatitis (OR = 3.20; 95% CI: 1.62, 6.34; p = .0008), absence of fat (OR = 0.25; 95% CI: 0.12, 0.52; p = .0002), absence of tumor in vein (OR = 0.34; 95% CI: 0.13, 0.84; p = .020), and higher tumor-to-liver ADC ratio (OR = 1.96; 95% CI: 1.14, 3.35; p = .014) CONCLUSION: MRI is useful in predicting the most frequent HCC subtypes even in cohorts with different distributions of liver disease etiologies and tumor subtypes which might have future treatment and management implications. KEY POINTS: • Representation of both liver disease etiologies and HCC subtypes differed between the North American and European cohorts of patients. • Retrospective two-center study showed that liver MRI is useful in predicting the most frequent HCC subtypes.

Deep learning-guided weighted averaging for signal dropout compensation in DWI of the liver.

PURPOSE: To develop an algorithm for the retrospective correction of signal dropout artifacts in abdominal DWI resulting from cardiac motion. METHODS: Given a set of image repetitions for a slice, a locally adaptive weighted averaging is proposed that aims to suppress the contribution of image regions affected by signal dropouts. Corresponding weight maps were estimated by a sliding-window algorithm, which analyzed signal deviations from a patch-wise reference. In order to ensure the computation of a robust reference, repetitions were filtered by a classifier that was trained to detect images corrupted by signal dropouts. The proposed method, named Deep Learning-guided Adaptive Weighted Averaging (DLAWA), was evaluated in terms of dropout suppression capability, bias reduction in the ADC, and noise characteristics. RESULTS: In the case of uniform averaging, motion-related dropouts caused signal attenuation and ADC overestimation in parts of the liver, with the left lobe being affected particularly. Both effects could be substantially mitigated by DLAWA while preventing global penalties with respect to SNR due to local signal suppression. Performing evaluations on patient data, the capability to recover lesions concealed by signal dropouts was demonstrated as well. Further, DLAWA allowed for transparent control of the trade-off between SNR and signal dropout suppression by means of a few hyperparameters. CONCLUSION: This work presents an effective and flexible method for the local compensation of signal dropouts resulting from motion and pulsation. Because DLAWA follows a retrospective approach, no changes to the acquisition are required.

Simultaneous comprehensive liver T1 , T2 , T2∗ , T1ρ , and fat fraction characterization with MR fingerprinting.

PURPOSE: To develop a novel simultaneous co-registered T1 , T2 , T2∗ , T1ρ , and fat fraction abdominal MR fingerprinting (MRF) approach for fully comprehensive liver-tissue characterization in a single breath-hold scan. METHODS: A gradient-echo liver MRF sequence with low fixed flip angle, multi-echo radial readout, and varying magnetization preparation pulses for multiparametric encoding is performed at 1.5 T. The T2∗ and fat fraction are estimated from a graph/cut water/fat separation method using a six-peak fat model. Water/fat singular images obtained are then matched to an MRF dictionary, estimating water-specific T1 , T2 , and T1ρ . The proposed approach was tested in phantoms and 10 healthy subjects and compared against conventional sequences. RESULTS: For the phantom studies, linear fits show excellent coefficients of determination (r2 > 0.9) for every parametric map. For in vivo studies, the average values measured within regions of interest drawn on liver, spleen, muscle, and fat are statistically different from the reference scans (p < 0.05) for T1 , T2 , and T1⍴ but not for T2∗ and fat fraction, whereas correlation between MRF and reference scans is excellent for each parameter (r2 > 0.92 for every parameter). CONCLUSION: The proposed multi-echo inversion-recovery, T2 , and T1⍴ prepared liver MRF sequence presented in this work allows for quantitative T1 , T2 , T2∗ , T1⍴ , and fat fraction liver-tissue characterization in a single breath-hold scan of 18 seconds. The approach showed good agreement and correlation with respect to reference clinical maps.

Free-breathing contrast-enhanced multiphase MRI of the liver in patients with a high risk of breath-holding failure: comparison of compressed sensing-accelerated radial and Cartesian acquisition techniques.

BACKGROUND: Knowing the advantages and disadvantages of each magnetic resonance (MR) technique, would allow us to choose a sequence better suited in patients with a high risk of breath-holding failure. PURPOSE: To compare the image quality of free-breathing contrast-enhanced multiphase MR imaging (MRI) using incoherent Cartesian k-space sampling combined with a motion-resolved compressed sensing reconstruction (XD-VIBE) and Golden-Angle Radial Sparse Parallel MRI (GRASP). MATERIAL AND METHODS: A total of 67 patients were included. Overall image quality, motion artifacts, and liver edge sharpness on arterial and portal-venous phase were evaluated by two radiologists. We evaluated the signal intensity ratio between liver in the late arterial phase to aorta at peak enhancement and the detection rate of hypervascular lesions. RESULTS: Overall image quality, artifact, and liver edge sharpness scores of XD-VIBE and GRASP were not significantly different (P = 0.070-0.397). Four (reviewer 1, 12.1%) and seven patients (reviewer 2, 21.2%) received non-diagnostic quality in the XD-VIBE group whereas one patient (reviewer 2, 2.9%) received non-diagnostic quality in the GRASP group. The ratio between the aorta and liver signal for GRASP was significantly higher than that of XD-VIBE (0.32 ± 0.10 vs. 0.47 ± 0.13; P < 0.001). The hypervascular lesion detection rate of XD-VIBE (86.7%) was higher than that of GRASP (57.1%) in the arterial phase without a statistically significant difference (P = 0.081). CONCLUSION: Overall image quality of XD-VIBE and GRASP were not significantly different. More XD-VIBE examinations were rated non-diagnostic. On the other hand, the relative liver parenchymal enhancement to the aorta in the late arterial phase of GRASP was higher than that of XD-VIBE, which potentially leads to lower detectability of hypervascular lesions on arterial phase images.

Clinical added value of MRI to CT in patients scheduled for local therapy of colorectal liver metastases (CAMINO): study protocol for an international multicentre prospective diagnostic accuracy study.

BACKGROUND: Abdominal computed tomography (CT) is the standard imaging method for patients with suspected colorectal liver metastases (CRLM) in the diagnostic workup for surgery or thermal ablation. Diffusion-weighted and gadoxetic-acid-enhanced magnetic resonance imaging (MRI) of the liver is increasingly used to improve the detection rate and characterization of liver lesions. MRI is superior in detection and characterization of CRLM as compared to CT. However, it is unknown how MRI actually impacts patient management. The primary aim of the CAMINO study is to evaluate whether MRI has sufficient clinical added value to be routinely added to CT in the staging of CRLM. The secondary objective is to identify subgroups who benefit the most from additional MRI. METHODS: In this international multicentre prospective incremental diagnostic accuracy study, 298 patients with primary or recurrent CRLM scheduled for curative liver resection or thermal ablation based on CT staging will be enrolled from 17 centres across the Netherlands, Belgium, Norway, and Italy. All study participants will undergo CT and diffusion-weighted and gadoxetic-acid enhanced MRI prior to local therapy. The local multidisciplinary team will provide two local therapy plans: first, based on CT-staging and second, based on both CT and MRI. The primary outcome measure is the proportion of clinically significant CRLM (CS-CRLM) detected by MRI not visible on CT. CS-CRLM are defined as liver lesions leading to a change in local therapeutical management. If MRI detects new CRLM in segments which would have been resected in the original operative plan, these are not considered CS-CRLM. It is hypothesized that MRI will lead to the detection of CS-CRLM in ≥10% of patients which is considered the minimal clinically important difference. Furthermore, a prediction model will be developed using multivariable logistic regression modelling to evaluate the predictive value of patient, tumor and procedural variables on finding CS-CRLM on MRI. DISCUSSION: The CAMINO study will clarify the clinical added value of MRI to CT in patients with CRLM scheduled for local therapy. This study will provide the evidence required for the implementation of additional MRI in the routine work-up of patients with primary and recurrent CRLM for local therapy. TRIAL REGISTRATION: The CAMINO study was registered in the Netherlands National Trial Register under number NL8039 on September 20th 2019.

Benign Neoplasms, Mass-Like Infections, and Pseudotumors That Mimic Hepatic Malignancy at MRI.

A variety of conditions may mimic hepatic malignancy at MRI. These include benign hepatic tumors and tumor-like entities such as focal nodular hyperplasia-like lesions, hepatocellular adenoma, hepatic infections, inflammatory pseudotumor, vascular entities, and in the cirrhotic liver, confluent fibrosis, and hypertrophic pseudomass. These conditions demonstrate MRI features that overlap with hepatic malignancy, and can be challenging for radiologists to diagnose accurately. In this review we discuss the MRI manifestations of various conditions that mimic hepatic malignancy, and highlight features that may allow distinction from malignancy. Level of Evidence 5 Technical Efficacy Stage 3.

Evaluation of Primary Liver Cancers Using Hepatocyte-Specific Contrast-Enhanced MRI: Pitfalls and Potential Tips.

When radiologists interpret hepatic focal lesions seen on dynamic magnetic resonance imaging (MRI) scans, it is important not only to distinguish malignant lesions from benign ones but also to distinguish nonhepatocellular carcinoma (HCC) malignancies from HCCs. In addition, most major guidelines, including those of the American Association for the Study of Liver Disease, European Association for the Study of the Liver, and Korean Liver Cancer Association and National Cancer Center, allow for the noninvasive imaging diagnosis of HCC in at-risk patients. However, ~40% of HCC cases show atypical imaging features mimicking non-HCC malignancies. Furthermore, several benign and malignant lesions, such as flash-filling hemangioma and intrahepatic mass-forming cholangiocarcinoma, frequently look like HCC. In contrast, although multiparametric MRI options, including hepatobiliary phase and diffusion-weighted imaging, provide useful information that could help address these challenges, there remain several unresolved issues with regard to the noninvasive diagnostic criteria characterizing HCC. In this article, we discuss the typical imaging features and challenging situations related to primary liver cancers in MRI, while considering how to make a correct diagnosis. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.

Clinical Performance of Abbreviated Liver MRI for the Follow-Up of Patients With Colorectal Liver Metastases.

OBJECTIVE. The objective of our study was to compare an abbreviated liver MRI protocol with a standard liver MRI protocol for the posttreatment follow-up of colorectal metastases in assessing disease presence, segmental involvement, and response to chemotherapy and for surgical planning. MATERIALS AND METHODS. This retrospective single-center study reviewed consecutive chemotherapy-naïve patients with colorectal liver metastases (April 1, 2011-August 31, 2017) who underwent gadoxetate disodium-enhanced MRI on a 1.5-T unit before and 8-12 weeks after chemotherapy. Two radiologists blinded to outcomes independently reviewed images obtained using standard MRI sequences at baseline and after treatment. The standard MRI sequences were the following: axial T1-weighted, axial T2-weighted, axial DWI (b values = 0-750 s/mm2), axial multiphase contrast-enhanced T1-weighted, and axial and coronal hepatobiliary phase (HBP) T1-weighted sequences. The standard sequences obtained at baseline and the abbreviated protocol sequences (i.e., HBP gadoxetate disodium-enhanced T1-weighted and DWI sequences) obtained after treatment were reviewed. For each image set, reviewers assessed disease presence and segmental involvement; in addition, for images obtained after therapy, treatment response according to RECIST 1.1 was recorded. RESULTS. One hundred thirteen patients (73 men and 40 women; mean age, 61.6 years) were evaluated. The total number of metastases showed high agreement between the standard protocol and abbreviated protocol (intraclass correlation coefficient = 0.97). There was good agreement between the protocols for segmental involvement (weighted κ = 0.73-0.85), and the weighted kappa was 0.82 for all segments. Discrepancies in segmental involvement did not alter potential surgical planning. Categorization of RECIST 1.1 treatment response using the abbreviated protocol versus the standard protocol showed excellent agreement (weighted κ = 0.92). CONCLUSION. An abbreviated liver MRI protocol (i.e., HBP gadoxetate disodium-enhanced T1-weighted and DWI sequences) allows assessment after chemotherapy similar to a standard liver MRI protocol. Use of the abbreviated protocol can reduce imaging time without sacrificing diagnostic performance for the follow-up of colorectal liver metastases.

Multi-parametric liver tissue characterization using MR fingerprinting: Simultaneous T1 , T2 , T2 *, and fat fraction mapping.

PURPOSE: Quantitative T1 , T2 , T2 *, and fat fraction (FF) maps are promising imaging biomarkers for the assessment of liver disease, however these are usually acquired in sequential scans. Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1 , T2 , T2 *, and FF mapping from a single ~14 s breath-hold scan. METHODS: A gradient echo (GRE) liver MRF sequence with nine readouts per TR, low flip angles (5-15°), varying magnetisation preparation and golden angle radial trajectory is acquired at 1.5T to encode T1 , T2 , T2 *, and FF simultaneously. The nine-echo time-series are reconstructed using a low-rank tensor constrained reconstruction and used to fit T2 *, B0 and to separate the water and fat signals. Water- and fat-specific T1 , T2, and M0 are obtained through dictionary matching, whereas FF estimation is extracted from the M0 maps. The framework was evaluated in a standardized T1 /T2 phantom, a water-fat phantom, and 12 subjects in comparison to reference methods. Preliminary clinical feasibility is shown in four patients. RESULTS: The proposed water T1 , water T2 , T2 *, and FF maps in phantoms showed high coefficients of determination (r2 > 0.97) relative to reference methods. Measured liver MRF values in vivo (mean ± SD) for T1 , T2 , T2 *, and FF were 671 ± 60 ms, 43.2 ± 6.8 ms, 29 ± 6.6 ms, and 3.2 ± 2.6% with biases of 92 ms, -7.1 ms, -1.4 ms, and 0.63% when compared to conventional methods. CONCLUSION: A nine-echo liver MRF sequence allows for quantitative multi-parametric liver tissue characterization in a single breath-hold scan of ~14 s. Future work will aim to validate the proposed approach in patients with liver disease.

Has the non-resection rate decreased during the last two decades among patients undergoing surgical exploration for pancreatic adenocarcinoma?

PURPOSE: To determine if improvement in imaging reduces the non-resection rate (NRR) among patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: From 2000 to 2019, 751 consecutive patients with PDAC were considered eligible for a intention-to-treat pancreatectomy and entered the operating room. In April 2011, our institution acquired a dual energy spectral computed tomography (CT) scanner and liver diffusion weighted magnetic resonance imaging (DW-MRI) was included in the imaging workup. We consequently considered 2 periods of inclusion: period #1 (February 2000-March 2011) and period #2 (April 2011-August 2019). RESULTS: All patients underwent a preoperative CT scan with a median delay to surgery of 18 days. Liver DW-MRI was performed among 407 patients (54%). Median delay between CT and surgery decreased (21 days to 16 days, P < .01), and liver DW-MRI was significantly most prescribed during period #2 (14% vs 75%, P < .01). According to the intraoperative findings, the overall NRR was 24.5%, and remained stable over the two periods (25% vs 24%, respectively). While vascular invasion, liver metastasis, and carcinomatosis rates remained stable, para-aortic lymph nodes invasion rate (0.4% vs 4.6%; P < 0.001) significantly increased over the 2 periods. The mean size of the bigger extra pancreatic tumor significantly decrease (7.9 mm vs 6.4 mm (P < .01), respectively) when the resection was not done. In multivariate analysis, CA 19-9 < 500 U/mL (P < .01), and liver DW-MRI prescription (P < .01) favoured the resection. CONCLUSIONS: Due to changes in our therapeutic strategies, the NRR did not decrease during two decades despite imaging improvement.

Characterizing a short T2 * signal component in the liver using ultrashort TE chemical shift-encoded MRI at 1.5T and 3.0T.

PURPOSE: Recent studies have suggested the presence of short-T2 * signals in the liver, which may confound chemical shift-encoded (CSE) fat quantification when using short echo times (TEs). The purpose of this study was to characterize the liver signal at short echo times and to determine its impact on liver fat quantification. METHODS: An ultrashort echo time (UTE) chemical shift-encoded MRI (CSE-MRI) technique and a multicomponent reconstruction were developed to characterize short-T2 * liver signals. Subsequently, liver fat fraction was quantified using a short-TE (first TE = 0.7 ms) and UTE CSE-MRI acquisitions and compared with a standard CSE-MRI (first TE = 1.2 ms). RESULTS: Short-T2 * signals were consistently observed in the liver of all healthy volunteers imaged at both 1.5T and 3.0T. At 3.0T, short-T2 * signal fractions of 9.6 ± 1.5%, 7.0 ± 1.7%, and 7.4 ± 1.7% with T2 * of 0.23 ± 0.05 ms, 0.20 ± 0.05 ms, and 0.10 ± 0.02 ms were measured in healthy volunteers, patients with liver cirrhotic disease, and patients with hepatic steatosis (but no cirrhosis), respectively. For proton density fat fraction (PDFF) estimation, 1.7% (P < .01) and 3.4% (P < .01) biases were observed in subjects imaged using short-TE CSE-MRI and using UTE CSE-MRI at 1.5T, respectively. The biases were reduced to 0.4% and -0.7%, respectively, by excluding short echoes less than 1 ms. A 3.2% bias (P < .01) was observed in subjects imaged using UTE CSE-MRI at 3.0T, which was reduced to 0.1% by excluding short echoes <1 ms. CONCLUSIONS: A liver short-T2 * signal component was consistently observed and was shown to confound liver fat quantification when short echo times were used with CSE-MRI.

View-Sharing Artifact Reduction With Retrospective Compressed Sensing Reconstruction in the Context of Contrast-Enhanced Liver MRI for Hepatocellular Carcinoma (HCC) Screening.

BACKGROUND: View-sharing (VS) increases spatiotemporal resolution in dynamic contrast-enhanced (DCE) MRI by sharing high-frequency k-space data across temporal phases. This temporal sharing results in respiratory motion within any phase to propagate artifacts across all shared phases. Compressed sensing (CS) eliminates the need for VS by recovering missing k-space data from pseudorandom undersampling, reducing temporal blurring while maintaining spatial resolution. PURPOSE: To evaluate a CS reconstruction algorithm on undersampled DCE-MRI data for image quality and hepatocellular carcinoma (HCC) detection. STUDY TYPE: Retrospective. SUBJECTS: Fifty consecutive patients undergoing MRI for HCC screening (29 males, 21 females, 52-72 years). FIELD STRENGTH/SEQUENCE: 3.0T MRI. Multiphase 3D-SPGR T1 -weighted sequence undersampled in arterial phases with a complementary Poisson disc sampling pattern reconstructed with VS and CS algorithms. ASSESSMENT: VS and CS reconstructions evaluated by blinded assessments of image quality and anatomic delineation on Likert scales (1-4 and 1-5, respectively), and HCC detection by OPTN/UNOS criteria including a diagnostic confidence score (1-5). Blinded side-by-side reconstruction comparisons for lesion depiction and overall series preference (-3-3). STATISTICAL ANALYSIS: Two-tailed Wilcoxon signed rank tests for paired nonparametric analyses with Bonferroni-Holm multiple-comparison corrections. McNemar's test for differences in lesion detection frequency and transplantation eligibility. RESULTS: CS compared with VS demonstrated significantly improved contrast (mean 3.6 vs. 2.9, P < 0.0001) and less motion artifact (mean 3.6 vs. 3.2, P = 0.006). CS compared with VS demonstrated significantly improved delineations of liver margin (mean 4.5 vs. 3.8, P = 0.0002), portal veins (mean 4.5 vs. 3.7, P < 0.0001), and hepatic veins (mean 4.6 vs. 3.5, P < 0.0001), but significantly decreased delineation of hepatic arteries (mean 3.2 vs. 3.7, P = 0.004). No significant differences were seen in the other assessments. DATA CONCLUSION: Applying a CS reconstruction to data acquired for a VS reconstruction significantly reduces motion artifacts in a clinical DCE protocol for HCC screening. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:984-993.

Detection of liver metastases on gadobenate dimeglumine-enhanced MRI: systematic review, meta-analysis, and similarities with gadoxetate-enhanced MRI.

OBJECTIVES: To determine the sensitivity and positive predictive value (PPV) of gadobenate-enhanced MR imaging for the detection of liver metastases. METHODS: This systematic review and meta-analysis was conducted according to PRISMA guidelines. A comprehensive search (EMBASE, PubMed) was performed to identify relevant articles up to December 2017. Studies eligible for inclusion were performed using appropriate methodology with complete verification by means of histopathology, intraoperative observation and/or follow-up, and sufficient information to permit determination of true-positive (TP), false-negative (FN), and false-positive (FP) values. Sources of bias were assessed using the QUADAS-2 tool. An inverse variance-weighted random-effects model was used to obtain sensitivity and PPV estimates. Information was analyzed and presented using Cochran's Q statistic, funnel plots, and modified Deeks' analysis. RESULTS: Ten articles (256 patients, 562 metastases) were included. Sensitivity estimates for pre-contrast (unenhanced) imaging, gadobenate-enhanced dynamic imaging, and combined unenhanced, dynamic, and delayed hepatobiliary phase imaging for detecting liver metastases on a per-lesion basis were 77.8% (95% CI 71.4-84.3%, 7 assessments), 88.1% (95% CI, 84.0-92.2%, 13 assessments), and 95.1% (95% CI 93.1-97.1%, 15 assessments), respectively. The addition of hepatobiliary phase images significantly improved the detection of liver metastases. The overall PPV was 90.9% (95% CI 86.6-95.1%, 11 assessments). Deeks' funnel analysis revealed no association between sample size and sensitivity (ß = 0.02, p = 0.814) indicating no significant publication bias. CONCLUSIONS: Gadobenate-enhanced MR imaging has high sensitivity and PPV for the detection of liver metastases on a per-lesion basis. The sensitivity and PPV for detection is comparable to reported values for the pure liver-specific agent gadoxetate. KEY POINTS: • Gadobenate dimeglumine is a hepatobiliary MR contrast agent that permits acquisition of contrast-enhanced liver images during the immediate post-injection dynamic phase, like any extracellular agent, and in the delayed hepatobiliary phase, after specific uptake by the hepatocytes. • The hepatobiliary phase improves detection of liver metastases when compared either to pre-contrast unenhanced images alone or to pre-contrast + gadobenate-enhanced dynamic phase images. • The meta-analysis showed an overall sensitivity of 95.1% and PPV of 90.9% of gadobenate-enhanced MRI for the detection of metastases, when based on the evaluation of all available acquisitions.

Self-gated 4D-MRI of the liver: Initial clinical results of continuous multiphase imaging of hepatic enhancement.

PURPOSE: To evaluate the feasibility of a self-gated free-breathing volume-interpolated breath-hold examination (VIBE) sequence using compressed sensing (CS) for contrast-enhanced multiphase liver MRI. MATERIALS AND METHODS: We identified 23 patients who underwent multiphase gadobutrol-enhanced liver magnetic resonance imaging (MRI) using 1) a prototype free-breathing VIBE sequence with respiratory self-gating and CS (VIBECS ), and 2) a standard breath-hold VIBE (VIBESTD ) on the same 1.5T scanner at two timepoints. VIBECS was continuously acquired for 128 seconds and a time-series of 16 timepoints was jointly reconstructed from the dataset. The unenhanced, arterial, portal-venous, and venous timepoints with the best image quality were selected and compared to the corresponding VIBESTD series serving as reference. Image quality was assessed qualitatively (image quality, sharpness, lesion conspicuity, vessel contrast, noise, motion/other artifacts; two readers independently; 5-point Likert scale; 5 = excellent) and quantitatively (vessel contrast [VC], coefficient-of-variation [CV]) Statistics were performed using Wilcoxon-sign-rank (ordinal) and paired t-test (continuous variables). RESULTS: Image quality and lesion conspicuity revealed no significant differences between the sequences (P ≥ 0.3). VIBESTD showed a tendency to higher motion artifacts (P ≥ 0.07). Image sharpness significantly increased in VIBECS as compared to VIBESTD (P ≤ 0.03). Arterial phase vessel contrast appeared significantly lower in VIBECS than in VIBESTD (P = 0.04). VIBECS showed reconstruction artifacts not present in VIBESTD (P = 0.001). Image noise was significantly lower in VIBECS than in VIBESTD (P ≤ 0.004). Arterial phase VC was significantly lower in VIBECS than in VIBESTD (P = 0.01). CV revealed no differences between sequences (P = 0.7). CONCLUSION: VIBECS is feasible for continuous free-breathing contrast-enhanced multiphase liver MRI, providing similar image quality and lesion conspicuity as VIBESTD . LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:459-467.

Automated image quality evaluation of T2 -weighted liver MRI utilizing deep learning architecture.

PURPOSE: To develop and test a deep learning approach named Convolutional Neural Network (CNN) for automated screening of T2 -weighted (T2 WI) liver acquisitions for nondiagnostic images, and compare this automated approach to evaluation by two radiologists. MATERIALS AND METHODS: We evaluated 522 liver magnetic resonance imaging (MRI) exams performed at 1.5T and 3T at our institution between November 2014 and May 2016 for CNN training and validation. The CNN consisted of an input layer, convolutional layer, fully connected layer, and output layer. 351 T2 WI were anonymized for training. Each case was annotated with a label of being diagnostic or nondiagnostic for detecting lesions and assessing liver morphology. Another independently collected 171 cases were sequestered for a blind test. These 171 T2 WI were assessed independently by two radiologists and annotated as being diagnostic or nondiagnostic. These 171 T2 WI were presented to the CNN algorithm and image quality (IQ) output of the algorithm was compared to that of two radiologists. RESULTS: There was concordance in IQ label between Reader 1 and CNN in 79% of cases and between Reader 2 and CNN in 73%. The sensitivity and the specificity of the CNN algorithm in identifying nondiagnostic IQ was 67% and 81% with respect to Reader 1 and 47% and 80% with respect to Reader 2. The negative predictive value of the algorithm for identifying nondiagnostic IQ was 94% and 86% (relative to Readers 1 and 2). CONCLUSION: We demonstrate a CNN algorithm that yields a high negative predictive value when screening for nondiagnostic T2 WI of the liver. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:723-728.

Evolution of indeterminate hepatocellular nodules at Gd-EOB-DPTA-enhanced MRI in cirrhotic patients.

PURPOSE: To retrospectively analyze the evolution of indeterminate hepatocellular nodules in cirrhotic patients on serial Gd-EOB-DPTA-enhanced MRI, and to identify predictors of HCC development. MATERIALS AND METHODS: This IRB approved study included 33 cirrhotic patients with 69 indeterminate hepatocellular nodules (mean diameter 1.1 cm) at baseline Gd-EOB-DPTA-enhanced MRI and a Gd-EOB-DPTA-enhanced-MRI follow-up of at least 2 years. Two radiologists evaluated size and signal intensity of each nodule at baseline and follow-up. Age, cirrhosis etiology, and HCC history were recorded. Data were compared between nodules that became HCCs at follow-up (HCC) and those that did not (no-HCC). RESULTS: On follow-up, 5/69 nodules became HCCs and 64/69 showed indeterminate characteristics. HCC history was more frequently found in HCCs than in no-HCCs. Age, sex, and cirrhosis etiology were not significantly different between HCCs and no-HCCs. HCCs had a significantly greater baseline diameter and increase in size than no-HCCs. Hepatobiliary phase hypointensity was significantly more common in HCCs than in no-HCCs. Multivariate regression analysis showed that increase in size (OR 10.48; sensitivity, 100%; specificity, 81.2%; p < 0.001) and hepatobiliary phase hypointensity (OR 1.02; sensitivity, 100%; specificity, 78.1%; p < 0.001) was associated with HCC development. CONCLUSION: Indeterminate hepatocellular nodules at Gd-EOB-DPTA-enhanced MRI in cirrhotic patients rarely became HCCs. Hepatobiliary phase hypointensity had a weak association with HCC development.

Quantitative ultrashort echo time imaging for assessment of massive iron overload at 1.5 and 3 Tesla.

PURPOSE: Hepatic iron content (HIC) quantification via transverse relaxation rate (R2*)-MRI using multi-gradient echo (mGRE) imaging is compromised toward high HIC or at higher fields due to the rapid signal decay. Our study aims at presenting an optimized 2D ultrashort echo time (UTE) sequence for R2* quantification to overcome these limitations. METHODS: Two-dimensional UTE imaging was realized via half-pulse excitation and radial center-out sampling. The sequence includes chemically selective saturation pulses to reduce streaking artifacts from subcutaneous fat, and spatial saturation (sSAT) bands to suppress out-of-slice signals. The sequence employs interleaved multi-echo readout trains to achieve dense temporal sampling of rapid signal decays. Evaluation was done at 1.5 Tesla (T) and 3T in phantoms, and clinical applicability was demonstrated in five patients with biopsy-confirmed massively high HIC levels (>25 mg Fe/g dry weight liver tissue). RESULTS: In phantoms, the sSAT pulses were found to remove out-of-slice contamination, and R2* results were in excellent agreement to reference mGRE R2* results (slope of linear regression: 1.02/1.00 for 1.5/3T). UTE-based R2* quantification in patients with massive iron overload proved successful at both field strengths and was consistent with biopsy HIC values. CONCLUSION: The UTE sequence provides a means to measure R2* in patients with massive iron overload, both at 1.5T and 3T. Magn Reson Med 78:1839-1851, 2017. © 2017 Wiley Periodicals, Inc.

A model for hepatic fibrosis: the competing effects of cell loss and iron on shortened modified Look-Locker inversion recovery T1 (shMOLLI-T1 ) in the liver.

PURPOSE: To propose a simple multicompartment model of the liver and use Bloch-McConnell simulations to demonstrate the effects of iron and fibrosis on shortened-MOLLI (shMOLLI) T1 measurements. Liver T1 values have shown sensitivity to inflammation and fibrosis, but are also affected by hepatic iron content. Modified Look-Locker inversion recovery (MOLLI) T1 measurements are biased by the lower T2 associated with high iron. MATERIALS AND METHODS: A tissue model was generated consisting of liver cells and extracellular fluid (ECF), with iron-dependent relaxation rates. Fibrosis was imitated by increasing the ECF proportion. Simulations of the shMOLLI sequence produced a look-up table (LUT) of shMOLLI-T1 for a given ECF fraction and iron content. The LUT was used to calculate ECF(shMOLLI-T1 ), assuming normal hepatic iron content (HIC), and ECF(shMOLLI- T1,T2*), accounting for HIC determined by T2*, for 77 patients and compared to fibrosis assessed by liver biopsy. RESULTS: Simulations showed that increasing HIC decreases shMOLLI-T1 , with an increase in HIC from 1.0 to 2.5 mg/g at normal ECF fraction decreasing shMOLLI-T1 by 160 msec, while increasing ECF increased ShMOLLI-T1 , with an increase of 20% ECF at normal iron increasing shMOLLI-T1 by 200 msec. Calculated patient ECF(shMOLLI-T1 ) showed a strong dependence on Ishak score (3.3 ± 0.8 %ECF/Ishak stage) and 1/T2* (-0.23 ± 0.04 %ECF/Hz). However, when iron was accounted for to produce ECF(shMOLLI- T1,T2*), it was independent of HIC but retained sensitivity to Ishak score. CONCLUSION: Use of this multicompartment model of the liver with Bloch-McConnell simulation should enable compensation of iron effects when using shMOLLI-T1 to assess fibrosis. LEVEL OF EVIDENCE: 1 J. Magn. Reson. Imaging 2017;45:450-462.

Radial Ultrashort TE Imaging Removes the Need for Breath-Holding in Hepatic Iron Overload Quantification by R2* MRI.

OBJECTIVE: The objective of this study is to evaluate radial free-breathing (FB) multiecho ultrashort TE (UTE) imaging as an alternative to Cartesian FB multiecho gradient-recalled echo (GRE) imaging for quantitative assessment of hepatic iron content (HIC) in sedated patients and subjects unable to perform breath-hold (BH) maneuvers. MATERIALS AND METHODS: FB multiecho GRE imaging and FB multiecho UTE imaging were conducted for 46 test group patients with iron overload who could not complete BH maneuvers (38 patients were sedated, and eight were not sedated) and 16 control patients who could complete BH maneuvers. Control patients also underwent standard BH multiecho GRE imaging. Quantitative R2* maps were calculated, and mean liver R2* values and coefficients of variation (CVs) for different acquisitions and patient groups were compared using statistical analysis. RESULTS: FB multiecho GRE images displayed motion artifacts and significantly lower R2* values, compared with standard BH multiecho GRE images and FB multiecho UTE images in the control cohort and FB multiecho UTE images in the test cohort. In contrast, FB multiecho UTE images produced artifact-free R2* maps, and mean R2* values were not significantly different from those measured by BH multiecho GRE imaging. Motion artifacts on FB multiecho GRE images resulted in an R2* CV that was approximately twofold higher than the R2* CV from BH multiecho GRE imaging and FB multiecho UTE imaging. The R2* CV was relatively constant over the range of R2* values for FB multiecho UTE, but it increased with increases in R2* for FB multiecho GRE imaging, reflecting that motion artifacts had a stronger impact on R2* estimation with increasing iron burden. CONCLUSION: FB multiecho UTE imaging was less motion sensitive because of radial sampling, produced excellent image quality, and yielded accurate R2* estimates within the same acquisition time used for multiaveraged FB multiecho GRE imaging. Thus, FB multiecho UTE imaging is a viable alternative for accurate HIC assessment in sedated children and patients who cannot complete BH maneuvers.