Evolution of liver function during immune checkpoint inhibitor treatment for hepatocellular carcinoma.

BACKGROUND AND AIMS: Deterioration of liver function is a leading cause of death in patients with advanced hepatocellular carcinoma (HCC). We evaluated the impact of immune checkpoint inhibitor (ICI)-treatment on liver function and outcomes. METHOD: HCC patients receiving ICIs or sorafenib between 04/2003 and 05/2024 were included. Liver function (assessed by Child-Pugh score [CPS]) was evaluated at the start of ICI-treatment (baseline, BL) and 3 and 6 months thereafter. A ≥1 point change in CPS was defined as deterioration (-) or improvement (+), while equal CPS points were defined as stable (=). RESULTS: Overall, 182 ICI-treated patients (66.8 ± 11.8 years; cirrhosis: n = 134, 74%) were included. At BL, median CPS was 5 (IQR: 5-6; CPS-A: 147, 81%). After 3 months, liver function improved/stabilized in 102 (56%) and deteriorated in 61 (34%) patients, while 19 (10%) patients deceased/had missing follow-up (d/noFU). Comparable results were observed at 6 months (+/=: n = 82, 45%; -: n = 55, 30%; d/noFU: n = 45, 25%). In contrast, 54 (34%) and 33 (21%) out of 160 sorafenib patients achieved improvement/stabilization at 3 and 6 months, respectively. Radiological response was linked to CPS improvement/stabilization at 6 months (responders vs. non-responders, 73% vs. 50%; p = 0.007). CPS improvement/stabilization at 6 months was associated with better overall survival following landmark analysis (6 months: +/=: 28.4 [95% CI: 18.7-38.1] versus -: 14.2 [95% CI: 10.3-18.2] months; p < 0.001). Of 35 ICI-patients with CPS-B at BL, improvement/stabilization occurred in 16 (46%) patients, while 19 (54%) patients deteriorated/d/noFU at 3 months. Comparable results were observed at 6 months (CPS +/=: 14, 40%, -: 8, 23%). Importantly, 6/35 (17%) and 9/35 (26%) patients improved from CPS-B to CPS-A at 3 and 6 months. CONCLUSION: Radiological response to ICI-treatment was associated with stabilization or improvement in liver function, which correlated with improved survival, even in patients with Child-Pugh class B at baseline.

Benign and malignant focal liver lesions displaying rim arterial phase hyperenhancement on CT and MRI.

Rim arterial phase hyperenhancement is an imaging feature commonly encountered on contrast-enhanced CT and MRI in focal liver lesions. Rim arterial phase hyperenhancement is a subtype of arterial phase hyperenhancement mainly present at the periphery of lesions on the arterial phase. It is caused by a relative arterialization of the periphery compared with the center of the lesion and needs to be differentiated from other patterns of peripheral enhancement, including the peripheral discontinuous nodular enhancement and the corona enhancement. Rim arterial phase hyperenhancement may be a typical or an atypical imaging presentation of many benign and malignant focal liver lesions, challenging the radiologists during imaging interpretation. Benign focal liver lesions that may show rim arterial phase hyperenhancement may have a vascular, infectious, or inflammatory origin. Malignant focal liver lesions displaying rim arterial phase hyperenhancement may have a vascular, hepatocellular, biliary, lymphoid, or secondary origin. The differences in imaging characteristics on contrast-enhanced CT may be subtle, and a multiparametric approach on MRI may be helpful to narrow the list of differentials. This article aims to review the broad spectrum of focal liver lesions that may show rim arterial phase hyperenhancement, using an approach based on the benign and malignant nature of lesions and their histologic origin. CRITICAL RELEVANCE STATEMENT: Rim arterial phase hyperenhancement may be an imaging feature encountered in benign and malignant focal liver lesions and the diagnostic algorithm approach provided in this educational review may guide toward the final diagnosis. KEY POINTS: Several focal liver lesions may demonstrate rim arterial phase hyperenhancement. Rim arterial phase hyperenhancement may occur in vascular, inflammatory, and neoplastic lesions. Rim arterial phase hyperenhancement may challenge radiologists during image interpretation.

Imaging and prognostic characterization of fat-containing hepatocellular carcinoma subtypes.

PURPOSE: Steatohepatitic hepatocellular carcinoma (SH-HCC) is characterized by intratumoral fat with > 50% inflammatory changes. However, intratumoral fat (with or without inflammation) can also be found in not-otherwise specified HCC (NOS-HCC). We compared the imaging features and outcome of resected HCC containing fat on pathology including SH-HCC (> 50% steatohepatitic component), NOS-HCC with < 50% steatohepatitic component (SH-NOS-HCC), and fatty NOS-HCC (no steatohepatitic component). MATERIAL AND METHODS: From September 2012 to June 2021, 94 patients underwent hepatic resection for fat-containing HCC on pathology. Imaging features and categories were assessed using LIRADS v2018. Fat quantification was performed on chemical-shift MRI. Recurrence-free and overall survival were estimated. RESULTS: Twenty-one patients (26%) had nonalcoholic steatohepatitis (NASH). The median intra-tumoral fat fraction was 8%, with differences between SH-HCC and SH-NOS-HCC (9.5% vs. 5% p = 0.03). There was no difference in major LI-RADS features between all groups; most tumors were classified as LR-4/5. A mosaic architecture on MRI was rare (7%) in SH-HCC, a fat in mass on CT was more frequently depicted (48%) in SH-HCC. A combination of NASH with no mosaic architecture on MRI or NASH with fat in mass on CT yielded excellent specificity for diagnosing SH-HCC (97.6% and 97.7%, respectively). The median recurrence-free and overall survival were 58 and 87 months, with no difference between groups (p = 0.18 and p = 0.69). CONCLUSION: In patients with NASH, an SH-HCC may be suspected in L4/LR-5 observations with no mosaic architecture at MRI or with fat in mass on CT. Oncological outcomes appear similar between fat-containing HCC subtypes.

Association of LI-RADS and Histopathologic Features with Survival in Patients with Solitary Resected Hepatocellular Carcinoma.

Background Both Liver Imaging Reporting and Data System (LI-RADS) and histopathologic features provide prognostic information in patients with hepatocellular carcinoma (HCC), but whether LI-RADS is independently associated with survival is uncertain. Purpose To assess the association of LI-RADS categories and features with survival outcomes in patients with solitary resected HCC. Materials and Methods This retrospective study included patients with solitary resected HCC from three institutions examined with preoperative contrast-enhanced CT and/or MRI between January 2008 and December 2019. Three independent readers evaluated the LI-RADS version 2018 categories and features. Histopathologic features including World Health Organization tumor grade, microvascular and macrovascular invasion, satellite nodules, and tumor capsule were recorded. Overall survival and disease-free survival were assessed with Cox regression models. Marginal effects of nontargetoid features on survival were estimated using propensity score matching. Results A total of 360 patients (median age, 64 years [IQR, 56-70 years]; 280 male patients) were included. At CT and MRI, the LI-RADS LR-M category was associated with increased risk of recurrence (CT: hazard ratio [HR] = 1.83 [95% CI: 1.26, 2.66], P = .001; MRI: HR = 2.22 [95% CI: 1.56, 3.16], P < .001) and death (CT: HR = 2.47 [95% CI: 1.72, 3.55], P < .001; MRI: HR = 1.80 [95% CI: 1.32, 2.46], P < .001) independently of histopathologic features. The presence of at least one nontargetoid feature was associated with an increased risk of recurrence (CT: HR = 1.80 [95% CI: 1.36, 2.38], P < .001; MRI: HR = 1.93 [95% CI: 1.81, 2.06], P < .001) and death (CT: HR = 1.51 [95% CI: 1.10, 2.07], P < .010) independently of histopathologic features. In matched samples, recurrence was associated with the presence of at least one nontargetoid feature at CT (HR = 2.06 [95% CI: 1.15, 3.66]; P = .02) or MRI (HR = 1.79 [95% CI: 1.01, 3.20]; P = .048). Conclusion In patients with solitary resected HCC, LR-M category and nontargetoid features were negatively associated with survival independently of histopathologic characteristics. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kartalis and Grigoriadis in this issue.

Automated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics.

OBJECTIVES: To develop and evaluate a deep convolutional neural network (DCNN) for automated liver segmentation, volumetry, and radiomic feature extraction on contrast-enhanced portal venous phase magnetic resonance imaging (MRI). MATERIALS AND METHODS: This retrospective study included hepatocellular carcinoma patients from an institutional database with portal venous MRI. After manual segmentation, the data was randomly split into independent training, validation, and internal testing sets. From a collaborating institution, de-identified scans were used for external testing. The public LiverHccSeg dataset was used for further external validation. A 3D DCNN was trained to automatically segment the liver. Segmentation accuracy was quantified by the Dice similarity coefficient (DSC) with respect to manual segmentation. A Mann-Whitney U test was used to compare the internal and external test sets. Agreement of volumetry and radiomic features was assessed using the intraclass correlation coefficient (ICC). RESULTS: In total, 470 patients met the inclusion criteria (63.9±8.2 years; 376 males) and 20 patients were used for external validation (41±12 years; 13 males). DSC segmentation accuracy of the DCNN was similarly high between the internal (0.97±0.01) and external (0.96±0.03) test sets (p=0.28) and demonstrated robust segmentation performance on public testing (0.93±0.03). Agreement of liver volumetry was satisfactory in the internal (ICC, 0.99), external (ICC, 0.97), and public (ICC, 0.85) test sets. Radiomic features demonstrated excellent agreement in the internal (mean ICC, 0.98±0.04), external (mean ICC, 0.94±0.10), and public (mean ICC, 0.91±0.09) datasets. CONCLUSION: Automated liver segmentation yields robust and generalizable segmentation performance on MRI data and can be used for volumetry and radiomic feature extraction. CLINICAL RELEVANCE STATEMENT: Liver volumetry, anatomic localization, and extraction of quantitative imaging biomarkers require accurate segmentation, but manual segmentation is time-consuming. A deep convolutional neural network demonstrates fast and accurate segmentation performance on T1-weighted portal venous MRI. KEY POINTS: • This deep convolutional neural network yields robust and generalizable liver segmentation performance on internal, external, and public testing data. • Automated liver volumetry demonstrated excellent agreement with manual volumetry. • Automated liver segmentations can be used for robust and reproducible radiomic feature extraction.

Prospective Comparison of Attenuation Imaging and Controlled Attenuation Parameter for Liver Steatosis Diagnosis in Patients With Nonalcoholic Fatty Liver Disease and Type 2 Diabetes.

BACKGROUND & AIMS: Similarly to the controlled attenuation parameter (CAP), the ultrasound-based attenuation imaging (ATI) can quantify hepatic steatosis. We prospectively compared the performance of ATI and CAP for the diagnosis of hepatic steatosis in patients with type 2 diabetes and nonalcoholic fatty liver disease using histology and magnetic resonance imaging-proton density fat fraction (MRI-PDFF) as references. METHODS: Patients underwent ATI and CAP measurement, MRI, and biopsy on the same day. Steatosis was classified as S0, S1, S2, and S3 on histology (<5%, 5%-33%, 33%-66%, and >66%, respectively) while the thresholds of 6.4%, 17.4%, and 22.1%, respectively, were used for MRI-PDFF. The area under the curve (AUC) of ATI and CAP was compared using a DeLong test. RESULTS: Steatosis could be evaluated in 191 and 187 patients with MRI-PDFF and liver biopsy, respectively. For MRI-PDFF steatosis, the AUC of ATI and CAP were 0.86 (95% confidence interval [CI], 0.81-0.91) vs 0.69 (95% CI, 0.62-0.75) for S0 vs S1-S3 (P = .02) and 0.71 (95% CI, 0.64-0.77) vs 0.69 (95% CI, 0.61-0.75) for S0-S1 vs S2-S3 (P = .60), respectively. For histological steatosis, the AUC of ATI and CAP were 0.92 (95% CI, 0.87-0.95) vs 0.95 (95% CI, 0.91-0.98) for S0 vs S1-S3 (P = .64) and 0.79 (95% CI, 0.72-0.84) vs 0.76 (95% CI, 0.69-0.82) for S0-S1 vs S2-S3 (P = .61), respectively. CONCLUSION: ATI may be used as an alternative to CAP for the diagnosis and quantification of steatosis, in patients with type 2 diabetes and nonalcoholic fatty liver disease.

Transversal psoas muscle thickness measurement is associated with response and survival in patients with HCC undergoing immunotherapy.

BACKGROUND: Sarcopenia is a common problem in patients with HCC. We aimed to evaluate the prognostic and predictive value of baseline transversal psoas muscle thickness (TPMT) measurement in patients with HCC undergoing immunotherapy. METHODS: HCC patients treated with programmed death ligand 1-based therapies between June 2016 and October 2022 at the Vienna General Hospital (n = 80) and the Hôpital Beaujon Clichy (n = 96) were included and followed until April 2023. TPMT at the level of the third lumbar vertebra was measured independently by 2 radiologists to evaluate interreader reliability. TPMT <12 mm/m in men and <8 mm/m in women indicated sarcopenia. RESULTS: Overall, 176 patients (age: 66.3±11.7 y; male: n=143, 81%, Barcelona-Clinic Liver Cancer C: n=121, 69%) were included, of which 131 (74%) exhibited cirrhosis. Interreader agreement for the diagnosis of sarcopenia based on TPMT was 92.6%, and Cohen κ showed a "strong agreement" [κ = 0.84 (95% CI: 0.75-0.92)]. Sarcopenia, present in 58 patients (33%), was associated with shorter median overall survival [7.2 (95% CI: 5.0-9.5) vs. 22.6 (95% CI: 16.4-28.8 months); p < 0.001] and median progression-free survival [3.4 (95% CI: 0.2-6.8) vs. 7.9 (95% CI: 5.8-9.9 months), p = 0.001], and an independent predictor of overall [adjusted HR: 1.63 (95% CI: 1.07-2.48)] and progression-free mortality [adjusted HR: 1.54 (95% CI: 1.06-2.23)] in multivariable analyses. The objective response rate [evaluable in 162 subjects (92.0%)] per modified Response Evaluation Criteria In Solid Tumors (mRECIST) in patients with and without sarcopenia was 22% and 39%, respectively (p = 0.029). Survival and radiological responses were worse in patients with sarcopenia and systemic inflammation [median overall survival: 6.1 (95% CI: 3.6-8.6) mo; median progression-free survival: 2.8 (95% CI: 2.1-3.4) mo; objective response rate=16%; disease control rate=39%]. CONCLUSIONS: Evaluation of sarcopenia using TPMT measurement is reliable and identifies HCC patients with a dismal prognosis and response to immunotherapy.

Automated CT LI-RADS v2018 scoring of liver observations using machine learning: A multivendor, multicentre retrospective study.

Background & Aims: Assessment of computed tomography (CT)/magnetic resonance imaging Liver Imaging Reporting and Data System (LI-RADS) v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. We assessed the performance and added-value of a machine learning (ML)-based algorithm in assessing CT LI-RADS major features and categorisation of liver observations compared with qualitative assessment performed by a panel of radiologists. Methods: High-risk patients as per LI-RADS v2018 with pathologically proven liver lesions who underwent multiphase contrast-enhanced CT at diagnosis between January 2015 and March 2019 in seven centres in five countries were retrospectively included and randomly divided into a training set (n = 84 lesions) and a test set (n = 345 lesions). An ML algorithm was trained to classify non-rim arterial phase hyperenhancement, washout, and enhancing capsule as present, absent, or of uncertain presence. LI-RADS major features and categories were compared with qualitative assessment of two independent readers. The performance of a sequential use of the ML algorithm and independent readers were also evaluated in a triage and an add-on scenario in LR-3/4 lesions. The combined evaluation of three other senior readers was used as reference standard. Results: A total of 318 patients bearing 429 lesions were included. Sensitivity and specificity for LR-5 in the test set were 0.67 (95% CI, 0.62-0.72) and 0.91 (95% CI, 0.87-0.96) respectively, with 242 (70.1%) lesions accurately categorised. Using the ML algorithm in a triage scenario improved the overall performance for LR-5. (0.86 and 0.93 sensitivity, 0.82 and 0.76 specificity, 78% and 82.3% accuracy for the two independent readers). Conclusions: Quantitative assessment of CT LI-RADS v2018 major features is feasible and diagnoses LR-5 observations with high performance especially in combination with the radiologist's visual analysis in patients at high-risk for HCC. Impact and implications: Assessment of CT/MRI LI-RADS v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. Rather than replacing radiologists, our results highlight the potential benefit from the radiologist-artificial intelligence interaction in improving focal liver lesions characterisation by using the developed algorithm as a triage tool to the radiologist's visual analysis. Such an AI-enriched diagnostic pathway may help standardise and improve the quality of analysis of liver lesions in patients at high risk for HCC, especially in non-expert centres in liver imaging. It may also impact the clinical decision-making and guide the clinician in identifying the lesions to be biopsied, for instance in patients with multiple liver focal lesions.

Performances and variability of CT radiomics for the prediction of microvascular invasion and survival in patients with HCC: a matter of chance or standardisation?

OBJECTIVES: To measure the performance and variability of a radiomics-based model for the prediction of microvascular invasion (MVI) and survival in patients with resected hepatocellular carcinoma (HCC), simulating its sequential development and application. METHODS: This study included 230 patients with 242 surgically resected HCCs who underwent preoperative CT, of which 73/230 (31.7%) were scanned in external centres. The study cohort was split into training set (158 patients, 165 HCCs) and held-out test set (72 patients, 77 HCCs), stratified by random partitioning, which was repeated 100 times, and by a temporal partitioning to simulate the sequential development and clinical use of the radiomics model. A machine learning model for the prediction of MVI was developed with least absolute shrinkage and selection operator (LASSO). The concordance index (C-index) was used to assess the value to predict the recurrence-free (RFS) and overall survivals (OS). RESULTS: In the 100-repetition random partitioning cohorts, the radiomics model demonstrated a mean AUC of 0.54 (range 0.44-0.68) for the prediction of MVI, mean C-index of 0.59 (range 0.44-0.73) for RFS, and 0.65 (range 0.46-0.86) for OS in the held-out test set. In the temporal partitioning cohort, the radiomics model yielded an AUC of 0.50 for the prediction of MVI, a C-index of 0.61 for RFS, and 0.61 for OS, in the held-out test set. CONCLUSIONS: The radiomics models had a poor performance for the prediction of MVI with a large variability in the model performance depending on the random partitioning. Radiomics models demonstrated good performance in the prediction of patient outcomes. CLINICAL RELEVANCE STATEMENT: Patient selection within the training set strongly influenced the performance of the radiomics models for predicting microvascular invasion; therefore, a random approach to partitioning a retrospective cohort into a training set and a held-out set seems inappropriate. KEY POINTS: • The performance of the radiomics models for the prediction of microvascular invasion and survival widely ranged (AUC range 0.44-0.68) in the randomly partitioned cohorts. • The radiomics model for the prediction of microvascular invasion was unsatisfying when trying to simulate its sequential development and clinical use in a temporal partitioned cohort imaged with a variety of CT scanners. • The performance of the radiomics models for the prediction of survival was good with similar performances in the 100-repetition random partitioning and temporal partitioning cohorts.

Quantitative imaging predicts pancreatic fatty infiltration on routine CT examination.

PURPOSE: The purpose of this study was to assess the performance of quantitative computed tomography (CT) imaging for detecting pancreatic fatty infiltration, using the results of histopathological analysis as reference. MATERIALS AND METHODS: Sixty patients who underwent pancreatic surgery for a pancreatic tumor between 2016 and 2019 were retrospectively included. There were 33 women and 27 men with a mean age of 56 ± 12 (SD) years (age range: 18-79 years). Patients with dilatation of the main pancreatic duct, chronic pancreatitis, or preoperative treatment were excluded to prevent any bias in the radiological-pathological correlation. Pancreatic fatty infiltration was recorded at pathology. Pancreatic surface lobularity, pancreatic attenuation, visceral fat area, and subcutaneous fat area were derived from preoperative CT images. The performance for the prediction of fatty infiltration was assessed using area under receiver operating characteristic curve (AUC) and backward binary logistic regression analysis. Results were validated in a separate cohort of 34 patients (17 women; mean age, 50 ± 14 [SD] years; age range: 18-73). RESULTS: A total of 28/60 (47%) and 17/34 (50%) patients had pancreatic fatty infiltration in the derivation and validation cohorts, respectively. In the derivation cohort, patients with pancreatic fatty infiltration had a significantly higher PSL (P < 0.001) and a lower pancreatic attenuation on both precontrast and portal venous phase images (P = 0.011 and 0.003, respectively), and higher subcutaneous fat area and visceral fat area (P = 0.010 and 0.007, respectively). Multivariable analysis identified pancreatic surface lobularity > 7.6 and pancreatic attenuation on portal venous phase images < 83.5 Hounsfield units as independently associated with fatty infiltration. The combination of these variables resulted in an AUC of 0.85 (95% CI: 0.74-0.95) and 0.83 (95% CI: 0.67-0.99) in the derivation and validation cohorts, respectively. CONCLUSION: CT-based quantitative imaging accurately predicts pancreatic fatty infiltration.

Adherence to LI-RADS and EASL high-risk population criteria: A systematic review.

BACKGROUND AND AIMS: The Liver Imaging Reporting and Data System (LI-RADS) and European Association for the Study of the Liver (EASL) diagnostic criteria for noninvasive diagnosis of HCC can only be applied to patients at a high risk of HCC. This systematic review assesses adherence to the LI-RADS and EASL high-risk population criteria in published studies. APPROACH AND RESULTS: PubMed was searched for original research, published between January 2012 and December 2021, reporting LI-RADS and EASL diagnostic criteria on contrast-enhanced ultrasound, CT, or MRI. The algorithm version, publication year, risk status, and etiologies of chronic liver disease were recorded for each study. Adherence to high-risk population criteria was evaluated as optimal (unequivocal adherence), suboptimal (equivocal), or inadequate (clear violation). A total of 219 original studies were included, with 215 that used the LI-RADS criteria, 4 EASL only, and 15 that evaluated both LI-RADS and EASL criteria. Optimal, suboptimal, or inadequate adherence to high-risk population criteria was observed in 111/215 (51.6%), 86/215 (40.0%), and 18/215 (8.4%) LI-RADS and 6/19 (31.6%), 5/19 (26.3%), and 8/19 (42.1%) EASL studies ( p < 0.001) regardless of the imaging modality. Adherence to high-risk population criteria significantly improved according to the CT/MRI LI-RADS versions (optimal in v2018 in 64.5% of studies; v2017, 45.8%; v2014, 24.4%; v2013.1, 33.3%; p < 0.001) and the publication year (2020-2021, 62.5%; 2018-2019, 33.9%; 2014-2017, 39.3% of all LI-RADS studies; p = 0.002). No significant differences in adherence to high-risk population criteria were observed in the versions of contrast-enhanced ultrasound LI-RADS ( p = 0.388) or EASL ( p = 0.293). CONCLUSION: Adherence to high-risk population criteria was optimal or suboptimal in about 90% and 60% of LI-RADS and EASL studies, respectively.

Differentiation of hepatocellular adenoma by subtype and hepatocellular carcinoma in non-cirrhotic liver by fractal analysis of perfusion MRI.

BACKGROUND: To investigate whether fractal analysis of perfusion differentiates hepatocellular adenoma (HCA) subtypes and hepatocellular carcinoma (HCC) in non-cirrhotic liver by quantifying perfusion chaos using four-dimensional dynamic contrast-enhanced magnetic resonance imaging (4D-DCE-MRI). RESULTS: A retrospective population of 63 patients (47 female) with histopathologically characterized HCA and HCC in non-cirrhotic livers was investigated. Our population consisted of 13 hepatocyte nuclear factor (HNF)-1α-inactivated (H-HCAs), 7 ß-catenin-exon-3-mutated (bex3-HCAs), 27 inflammatory HCAs (I-HCAs), and 16 HCCs. Four-dimensional fractal analysis was applied to arterial, portal venous, and delayed phases of 4D-DCE-MRI and was performed in lesions as well as remote liver tissue. Diagnostic accuracy of fractal analysis was compared to qualitative MRI features alone and their combination using multi-class diagnostic accuracy testing including kappa-statistics and area under the receiver operating characteristic curve (AUC). Fractal analysis allowed quantification of perfusion chaos, which was significantly different between lesion subtypes (multi-class AUC = 0.90, p < 0.001), except between I-HCA and HCC. Qualitative MRI features alone did not allow reliable differentiation between HCA subtypes and HCC (κ = 0.35). However, combining qualitative MRI features and fractal analysis reliably predicted the histopathological diagnosis (κ = 0.89) and improved differentiation of high-risk lesions (i.e., HCCs, bex3-HCAs) and low-risk lesions (H-HCAs, I-HCAs) from sensitivity and specificity of 43% (95% confidence interval [CI] 23-66%) and 47% (CI 32-64%) for qualitative MRI features to 96% (CI 78-100%) and 68% (CI 51-81%), respectively, when adding fractal analysis. CONCLUSIONS: Combining qualitative MRI features with fractal analysis allows identification of HCA subtypes and HCCs in patients with non-cirrhotic livers and improves differentiation of lesions with high and low risk for malignant transformation.

Laparoscopic Pancreatoduodenectomy with Resection of the Inferior Vena Cava and Reconstruction with a Peritoneal Patch.

BACKGROUND: Laparoscopic resection of the inferior vena cava (IVC) during laparoscopic pancreatoduodenectomy (LPD) has never been described. A 32-year-old male with large solid pseudopapillary neoplasm underwent LPD with resection of the IVC and reconstruction by a peritoneal patch (PP). METHODS: In this indication, the dissection is achieved by resection of the IVC. Kocher maneuver is difficult owing to the caval invasion, and section of the retroportal lamina tissue, before Kocher maneuver, is needed to control the left side of the IVC. Extended lymphadenectomy is not needed because the risk of lymph node invasion is low, and venous resection may be required for severe tumor adhesions without necessary histological invasion, to avoid tumor rupture at high risk of recurrence.1,2 The IVC was clamped by a laparoscopic vascular clamp and reconstructed (5-6 cm) with a PP. RESULTS: The operative duration was 430 min, including IVC clamping for 27 min. The outcome was marked by biliary fistula and 24 days of hospital stay. Histology showed 6 cm tumor without histological invasion of the IVC wall. After 15 months of follow-up, there was no recurrence and no stenosis of the IVC. In our experience, reconstruction of the IVC with a PP is a safe procedure, with no PP-related complications and high patency rate (> 90%).3 CONCLUSION: Laparoscopic resection of the IVC is feasible in highly selected centers. The harvesting of the PP is easier than that of other autologous venous grafts, especially when done by the laparoscopic approach.

Performance of non-invasive biomarkers compared with invasive methods for risk prediction of posthepatectomy liver failure in hepatocellular carcinoma.

BACKGROUND: Posthepatectomy liver failure (PHLF) is a rare but dreaded complication. The aim was to test whether a combination of non-invasive biomarkers (NIBs) and CT data could predict the risk of PHLF in patients who underwent resection of hepatocellular carcinoma (HCC). METHODS: Patients with HCC who had liver resection between 2012 and 2020 were included. A relevant combination of NIBs (NIB model) to model PHLF risk was identified using a doubly robust estimator (inverse probability weighting combined with logistic regression). The adjustment variables were body surface area, ASA fitness grade, male sex, future liver remnant (FLR) ratio, difficulty of liver resection, and blood loss. The reference invasive biomarker (IB) model comprised a combination of pathological analysis of the underlying liver and hepatic venous pressure gradient (HVPG) measurement. Various NIB and IB models for prediction of PHLF were fitted and compared. NIB model performances were validated externally. Areas under the curve (AUCs) were corrected using bootstrapping. RESULTS: Overall 323 patients were included. The doubly robust estimator showed that hepatitis C infection (odds ratio (OR) 4.33, 95 per cent c.i. 1.29 to 9.20; P = 0.001), MELD score (OR 1.26, 1.04 to 1.66; P = 0.001), fibrosis-4 score (OR 1.36, 1.06 to 1.85; P = 0.001), liver surface nodularity score (OR 1.55, 1.28 to 4.29; P = 0.031), and FLR volume ratio (OR 0.99, 0.97 to 1.00; P = 0.014) were associated with PHLF. Their combination (NIB model) was fitted externally (2-centre cohort, 165 patients) to model PHLF risk (AUC 0.867). Among 129 of 323 patients who underwent preoperative HVPG measurement, NIB and IB models had similar performances (AUC 0.753 versus 0.732; P = 0.940). A well calibrated nomogram was drawn based on the NIB model (AUC 0.740). The risk of grade B/C PHLF could be ruled out in patients with a cumulative score of less than 160 points. CONCLUSION: The NIB model provides reliable preoperative evaluation with performance at least similar to that of invasive methods for PHLF risk prediction.

Contrast-enhanced CT and liver surface nodularity for the diagnosis of porto-sinusoidal vascular disorder: A case-control study.

BACKGROUND AND AIMS: Porto-sinusoidal vascular disorder (PSVD) is a rare and commonly overlooked cause of portal hypertension. The interest of CT analysis, including quantification of liver surface nodularity (LSN) for PSVD diagnosis has not been established. This study aimed at assessing the performance of LSN and CT features for a PSVD diagnosis in patients with signs of portal hypertension. APPROACH AND RESULTS: This retrospective case-control study included a learning cohort consisting of 50 patients with histologically proven PSVD, according to VALDIG criteria, and 100 control patients with histologically proven cirrhosis, matched on ascites. All patients and controls had at least one sign of portal hypertension and CT available within 1 year of liver biopsy. Principal component analysis of CT features separated patients with PSVD from patients with cirrhosis. Patients with PSVD had lower median LSN than those with cirrhosis (2.4 vs. 3.1, p < 0.001). Multivariate analysis identified LSN < 2.5 and normal-sized or enlarged segment IV as independently associated with PSVD. Combination of these two features had a specificity of 90% for PSVD and a diagnostic accuracy of 84%. Even better results were obtained in an independent multicenter validation cohort including 53 patients with PSVD and 106 control patients with cirrhosis (specificity 94%, diagnostic accuracy 87%). CONCLUSIONS: This study that included a total of 103 patients with PSVD and 206 patients with cirrhosis demonstrates that LSN < 2.5 combined with normal-sized or enlarged segment IV strongly suggests PSVD in patients with signs of portal hypertension.

Liver surface nodularity on non-contrast MRI identifies advanced fibrosis in patients with NAFLD.

OBJECTIVES: To evaluate the diagnostic performance of liver surface nodularity (LSN) for the assessment of advanced fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). METHODS: We retrospectively analysed patients with pathologically proven NAFLD who underwent liver MRI. Demographic, clinical, and laboratory data (including FIB-4 scores) were gathered. The SAF score was used to assess NAFLD. MRI-proton density fat fraction (PDFF) and LSN were determined on pre-contrast MR sequences. ROC curve analysis was performed to evaluate the diagnostic performance of MRI-LSN for the diagnosis of advanced (F3-F4) liver fibrosis. RESULTS: The final population included 142 patients. Sixty-seven (47%) patients had non-alcoholic steatohepatitis (NASH), and 52 (37%) had advanced fibrosis. The median MRI-PDFF increased with the grades of steatosis: 8.1%, 18.1%, and 31% in S1, S2, and S3 patients, respectively (p < 0.001). The area under the ROC curve (AUC) of MRI-LSN ≥ 2.50 was 0.838 (95%CI 0.767-0.894, sensitivity 67.3%, specificity 88.9%, positive and negative predictive values 77.8% and 82.5%, respectively) for the diagnosis of advanced fibrosis. Combining FIB-4 and MRI-LSN correctly classified 103/142 (73%) patients. This was validated in an external cohort of 75 patients. CONCLUSIONS: MRI-LSN has good diagnostic performance in diagnosis of advanced fibrosis in NAFLD patients. A combination of FIB-4 and MRI-LSN derived from pre-contrast MRI could be helpful to detect advanced fibrosis. KEY POINTS: • MRI-LSN ≥ 2.5 was accurate for the diagnosis of advanced hepatic fibrosis in NAFLD patients. • The combination of FIB-4 and MRI-LSN improved the detection of advanced fibrosis. • MRI-LSN can be easily derived by unenhanced MRI sequences that are routinely acquired.

MR imaging features and long-term evolution of benign focal liver lesions in Budd-Chiari syndrome and Fontan-associated liver disease.

PURPOSE: To compare the magnetic resonance imaging (MRI) features of benign liver lesions developed on Budd-Chiari syndrome (BCS) with those on Fontan-associated liver disease (FALD) and to describe their long-term progression. MATERIALS AND METHODS: Patients with BCS or FALD who underwent MRI between 2010 and 2020 were retrospectively included. MRI features of nodules (≥ 5 mm) at baseline and at final follow-up were reviewed. The final diagnosis of benign lesion was based on a combination of clinical and biological data and findings at follow-up MRI examination. RESULTS: Two-hundred and thirty benign liver lesions in 39 patients with BCS (10 men, 29 women; mean age, 36 ±â€¯11 [SD] years; age range: 15-66 years) and 84 benign lesions in 14 patients with FALD (2 men, 12 women; mean age, 31 ±â€¯10 [SD] years; age range: 20-48 years) were evaluated. On baseline MRI, BCS nodules were more frequently hyperintense on T1-weighted (183/230, 80%) and hypointense on T2-weighted (142/230; 62%) images, while FALD nodules were usually isointense on both T1- (70/84; 83%) and T2-weighted (64/84; 76%) images (all P< 0.01). Most lesions showed arterial phase hyperenhancement (222/230 [97%] vs. 80/84 [95%] in BCS and FALD, respectively; P = 0.28) but wash-out was more common in BCS (64/230 [28%] vs. 9/84 [11%]; P < 0.01). At follow-up, changes were more frequent in BCS nodules with more frequent disappearance (P < 0.01), changes in size, signal intensity on T2-weighted, portal, and delayed phase, and in the depiction of washout and capsule (all P ≤ 0.03). CONCLUSION: MRI features of benign lesions are different at diagnosis and during the course of the disease between BCS and FALD. Changes in size and MRI features are more frequent in benign lesions developed in BCS.

Multicenter study on recent portal venous system thrombosis associated with cytomegalovirus disease.

BACKGROUND & AIMS: Recent non-malignant non-cirrhotic portal venous system thrombosis (PVT) is a rare condition. Among risk factors for PVT, cytomegalovirus (CMV) disease is usually listed based on a small number of reported cases. The aim of this study was to determine the characteristics and outcomes of PVT associated with CMV disease. METHODS: We conducted a French multicenter retrospective study comparing patients with recent PVT and CMV disease ("CMV positive"; n = 23) to patients with recent PVT for whom CMV testing was negative ("CMV negative"; n = 53) or unavailable ("CMV unknown"; n = 297). RESULTS: Compared to patients from the "CMV negative" and "CMV unknown" groups, patients from the "CMV positive" group were younger, more frequently had fever, and had higher heart rate, lymphocyte count and serum ALT levels (p ≤0.01 for all). The prevalence of immunosuppression did not differ between the 3 groups (4%, 4% and 6%, respectively). Extension of PVT was similar between the 3 groups. Thirteen out of 23 "CMV positive" patients had another risk factor for thrombosis. Besides CMV disease, the number of risk factors for thrombosis was similar between the 3 groups. Heterozygosity for the prothrombin G20210A gene variant was more frequent in "CMV positive" patients (22%) than in the "CMV negative" (4%, p = 0.01) and "CMV unknown" (8%, p = 0.03) groups. Recanalization rate was not influenced by CMV status. CONCLUSIONS: In patients with recent PVT, features of mononucleosis syndrome should raise suspicion of CMV disease. CMV disease does not influence thrombosis extension nor recanalization. More than half of "CMV positive" patients have another risk factor for thrombosis, with a particular link to the prothrombin G20210A gene variant. LAY SUMMARY: Patients with cytomegalovirus (CMV)-associated portal venous system thrombosis have similar thrombosis extension and evolution as patients without CMV disease. However, patients with CMV-associated portal venous system thrombosis more frequently have the prothrombin G20210A gene variant, suggesting that these entities act synergistically to promote thrombosis.

Imaging features of histological subtypes of hepatocellular carcinoma: Implication for LI-RADS.

BACKGROUND & AIMS: The histopathological subtypes of hepatocellular carcinoma (HCC) are associated with distinct clinical features and prognoses. This study aims to report Liver Imaging Reporting and Data System (LI-RADS)-defined imaging features of different HCC subtypes in a cohort of resected tumours and to assess the influence of HCC subtypes on computed tomography (CT)/magnetic resonance imaging (MRI) LI-RADS categorisation in the subgroup of high-risk patients. METHODS: This retrospective institutional review board-approved study included patients with resected HCCs and available histopathological classification. Three radiologists independently reviewed preoperative CT and MRI exams. The readers evaluated the presence of imaging features according to LI-RADS v2018 definitions and provided a LI-RADS category in patients at high risk of HCC. Differences in LI-RADS features and categorisations were assessed for not otherwise specified (NOS-HCC), steatohepatitic (SH-HCC), and macrotrabecular-massive (MTM-HCC) types of HCCs. RESULTS: Two hundred and seventy-seven patients (median age 64.0 years, 215 [77.6%] men) were analysed, which involved 295 HCCs. There were 197 (66.7%) NOS-HCCs, 62 (21.0%) SH-HCCs, 23 (7.8%) MTM-HCCs, and 13 (4.5%) other rare subtypes. The following features were more frequent in MTM-HCC: elevated α-foetoprotein serum levels (p <0.001), tumour-in-vein (p <0.001 on CT, p ≤0.052 on MRI), presence of at least 1 LR-M feature (p ≤0.010 on CT), infiltrative appearance (p ≤0.032 on CT), necrosis or severe ischaemia (p ≤0.038 on CT), and larger size (p ≤0.006 on CT, p ≤0.011 on MRI). SH-HCC was associated with fat in mass (p <0.001 on CT, p ≤0.002 on MRI). The distribution of the LI-RADS major features and categories in high-risk patients did not significantly differ among the 3 main HCC subtypes. CONCLUSIONS: The distribution of LI-RADS major features and categories is not different among the HCC subtypes. Nevertheless, careful analysis of tumour-in-vein, LR-M, and ancillary features as well as clinico-biological data can provide information for the non-invasive diagnosis of HCC subtypes. LAY SUMMARY: In high-risk patients, the overall distribution of LI-RADS major features and categories is not different among the histological subtypes of hepatocellular carcinoma, but tumour-in-vein, presence of LR-M features, and ancillary features can provide information for the non-invasive diagnosis of hepatocellular carcinoma subtypes.

2D-shear wave elastography: number of acquisitions can be reduced according to clinical setting.

BACKGROUND: The factors affecting intra-operator variability of two-dimensional shear wave elastography (2D-SWE) have not been clearly established. We evaluated 2D-SWE variability according to the number of measurements, clinical and laboratory features, and liver stiffness measurements (LSM). METHODS: At least three LSM were performed in 452 patients who underwent LSM by 2D-SWE (supersonic shear imaging) out of an initial database of 1650 patients. The mean value of the three LSM was our best measurement method. Bland-Altman plots were used to evaluate intra-operator variability when considering only one, or the first two measurements. Variability was assessed by taking the absolute value of the difference between the first LSM and the mean of the three LSM. Logistic regression was used to assess the factors associated with the highest tertile of variability. RESULTS: The limit of agreement was narrower with the mean of the first and second measurements than with each measurement taken separately (- 2.83 to 2.99 kPa vs. - 5.86 to 6.21 kPa and - 5.77 to 5.73 kPa for the first and second measurement, respectively). A BMI ≥ 25 kg/m2 and a first LSM by 2D-SWE ≥ 7.1 kPa increased the odds of higher variability by 3.4 and 3.9, respectively. Adding a second LSM didn't change the variability in patients with BMI < 25 and a first LSM by 2D-SWE < 7.1 kPa. CONCLUSIONS: Intra-operator variability of LSM by 2D-SWE increases with both a high BMI and high LSM value. In patients with BMI < 25 kg/m2 and a first LSM < 7.1 kPa we recommend performing only one LSM.