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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Computed Tomography-Derived Liver Surface Nodularity and Sarcopenia as Prognostic Factors in Patients with Resectable Metabolic Syndrome-Related Hepatocellular Carcinoma.

OBJECTIVE: The aim of this study was to assess the prognostic value of liver surface nodularity (LSN) and sarcopenia from preoperative computed tomography (CT) in patients with resectable metabolic syndrome (MS)-related hepatocellular carcinoma (HCC). METHODS: Patients with MS undergoing hepatectomy for HCC between 2006 and 2018 at a single center were retrospectively analyzed. LSN and sarcopenia were assessed on preoperative CT scans, and their association with severe (Clavien-Dindo grade 3-5) postoperative complications was analyzed on multivariate analysis. The influence of LSN and sarcopenia on overall survival (OS) and recurrence-free survival (RFS) was assessed. RESULTS: Overall, 110 patients (92 men [84%], mean 67.7 ± 7.7 years of age) were analyzed. Severe postoperative complications occurred in 34/110 (31%) patients. Patients with severe complications had a significantly higher LSN score (area under the receiver operating characteristic curve 0.68 ± 0.05, optimal cut-off > 2.50) and were more frequently sarcopenic (47% vs. 13% without major complications, p < 0.001). Multivariate analysis identified sarcopenia (odds ratio [OR] 6.51, 95% confidence interval [CI] 2.08-20.39; p < 0.001), LSN > 2.50 (OR 7.05, 95% CI 2.13-23.35; p < 0.001), and preoperative portal vein embolization (PVE; OR 6.06, 95% CI 1.71-21.48; p = 0.005) as independent predictors of severe complications. LSN and sarcopenia had no influence on OS. Stratification according to a combination of LSN > 2.50 and sarcopenia predicted the risk of severe postoperative complications from 7% (no sarcopenia and LSN ≤2.50) to 71% (sarcopenia and LSN > 2.50; p < 0.001), as well as RFS from 61 months (95% CI 40-82) to 17 months (95% CI 9-25; p = 0.033). Results remained significant in 52 patients without advanced fibrosis. CONCLUSIONS: The combination of LSN and sarcopenia derived from routine preoperative CT seems to help predict severe postoperative complications and stratification of RFS in patients with MS and resectable HCC.

HCC advances in diagnosis and prognosis: Digital and Imaging.

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide. Understanding of the pathogenesis of HCC has significantly improved in the past few years due to advances in genetics, molecular biology and pathology. Several subtypes have been identified with different backgrounds and outcomes, leading to possible changes in disease management and challenging the role of imaging. Indeed, despite its pivotal role in the diagnostic workup, prognosis, and the decision-making process in patients with HCC, these recent developments are progressively redefining the role of imaging. First and most important, liver imaging is shifting from a purely qualitative to a quantitative paradigm, integrating quantitative imaging and radiomics in a digital era. Second, to improve patient management, imaging has gradually moved beyond tumor-centered assessment to include a broader evaluation of the liver and its function. This review describes and discusses these advances in the imaging for the diagnosis and prognosis of HCC.

Liver surface nodularity: a novel predictor of post-hepatectomy liver failure in patients with colorectal liver metastases following chemotherapy.

OBJECTIVES: The goal of this study was to assess the relationship between liver surface nodularity (LSN), chemotherapy-associated liver injury (CALI), and clinically relevant post-hepatectomy liver failure (CR-PHLF) (i.e., ≥ grade B) in patients undergoing hepatectomy for colorectal liver metastases (CLM). METHODS: Preoperative CT scans of patients who underwent chemotherapy followed by hepatectomy for CLM between 2010 and 2017 were retrospectively analyzed. LSN was measured using semi-automated CT software CT images in patients who had available preoperative CT scans within 6 weeks before hepatectomy, and was computed based on the means of one to 10 measurements by two abdominal radiologists consensually. The association of LSN, CALI, and CR-PHLF was analyzed. RESULTS: Two hundred fifty-six patients were analyzed (149 men and 107 women; overall median age, 61 [range, 29-88 years]). A total of 26 patients (10.2%) developed CR-PHLF. The optimal LSN cut-off value for detecting CR-PHLF was 2.5, as determined by receiver operative characteristic analysis (p < 0.001). LSN ≥ 2.5 was associated with prolonged chemotherapy (> 6 cycles, p = 0.018), but not with CALIs. After propensity score matching, LSN remained significantly associated with CR-PHLF (p = 0.031). Furthermore, multivariate analysis identified LSN ≥ 2.50 and future liver remnant (FLR) < 30% as significant preoperative predictors of CR-PHLF in 102 patients undergoing major hepatectomy. LSN ≥ 2.50 was more frequent in patients undergoing major hepatectomy despite FLR ≥ 30% (p = 0.008). CONCLUSION: LSN quantified on CT is an independent surrogate of CR-PHLF in patients who undergo chemotherapy followed by hepatectomy for CLM and may provide a valuable additional tool in the preoperative assessment of these patients. KEY POINTS: • LSN was not associated with chemotherapy- associated liver injury but high LSN (defined ≥ 2.5) was associated with prolonged chemotherapy (> 6 cycles). • High LSN was an independent predictor of clinically relevant postoperative liver failure in patients undergoing hepatectomy for CRLM. • LSN ≥ 2.50 was more frequent in patients with PHLF after major hepatectomy despite a future liver remnant ≥ 30%.

Influence of pretreatment tumor growth rate on objective response of hepatocellular carcinoma treated with transarterial chemoembolization.

BACKGROUND AND AIM: The study aims to assess the influence of pretreatment tumor growth rate (TGR) on modified response evaluation criteria in solid tumors (mRECIST) objective response (OR) after a first session of selective transarterial chemoembolization (TACE) for the treatment of hepatocellular carcinoma (HCC). METHODS: One hundred fifteen patients (101 men [88%], mean 65.1 ± 10.5 years [range 26-87]) with 169 tumors (mean 34.2 ± 29.3 mm [10-160]), undergoing a first session of selective TACE for the treatment of HCC between 2011 and 2016, were included. TGR was calculated as the percentage change in tumor volume per month (%/month) on imaging before treatment. TGR cut-off for prediction of OR was identified by receiver operating characteristic curve analysis. RESULTS: Overall 88/189 (52%) and 46/189 (27%) tumors showed complete response (CR) and partial response (PR) (OR rate 79%), while 32/189 (19%) showed stable disease (SD), and 3/189 (2%) were progressive disease (PD) on computed tomography at 1-month post-TACE. The mean pretreatment TGR was 12.0 ± 15.4 (-3.2-90.4) %/month. TGR of tumors showing CR, PR, SD, and PD was a mean 13.2 ± 16.4%, 12.1 ± 15.1%, 5.3 ± 4.5%, and 44.8 ± 20.4%, respectively (P < 0.001). The three tumors showing PD had TGR values > 20%/month. TGR was significantly higher in tumors with OR (12.8 ± 15.9% vs 5.3 ± 4.5% in SD, P = 0.009). A cut-off value of 6.5%/month had the highest predictive value of OR (AUROC 0.65 ± 0.05, P = 0.009). CONCLUSION: Pretreatment TGR is highly variable in HCC before TACE with a U-shaped distribution for the prediction of tumor response. It provides insight into tumor biology that may be used during pretreatment workup to help stratify patients.

Quantification of Liver Surface Nodularity at CT: Utility for Detection of Portal Hypertension.

Purpose To determine whether quantification of liver surface nodularity (LSN) provides an estimate of the presence of clinically significant portal hypertension (CSPH) in patients with cirrhosis. Materials and Methods This retrospective study included a training cohort (n = 189) and separate external validation cohort (n = 78), both composed of patients with cirrhosis who underwent abdominal CT and hepatic venous pressure gradient (HVPG) measurement between 2010 and 2016. The LSN score, liver and spleen volumes, liver-to-spleen volume ratio, platelet count to spleen diameter ratio, Iranmanesh score, aspartate amino transferase-to-platelet ratio index, and Fibrosis-4 index were derived from CT images and serum laboratories. The accuracy of the various tests for predicting CSPH was evaluated with area under the receiver operating characteristic curve (AUROC) and compared by using the DeLong test. Student t test and Pearson correlation coefficient were used. Results One hundred eighty-nine patients were analyzed (119 men [mean age ± standard deviation, 57 years ± 11; range, 29-81 years] and 70 women [mean age, 61 years ± 10; range, 34-83 years]; overall mean age, 58 years ± 10; range, 29-83 years). A total of 102 patients (54%) had CSPH. LSN score correlated with HVPG (r = 0.75; P < .001). Patients with CSPH had a higher LSN score than did those without CSPH (3.2 ± 0.6 vs 2.4 ± 0.3; P < .001). A cutoff value of 2.8 had a positive predictive value of 88% for CSPH; the AUROC of LSN was 0.88 ± 0.03. This was higher than that of other available noninvasive tests (DeLong, all P < .001). In the validation cohort, LSN score of 2.8 had a positive predictive value of 86% for CSPH; the AUROC was 0.87 ± 0.04. Conclusion The CT-based liver surface nodularity score demonstrated high diagnostic performance for detecting clinically significant portal hypertension and outperformed multiple other noninvasive tests. © RSNA, 2018 Online supplemental material is available for this article.

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.

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.