The RETREAT (Risk Estimation of Tumor Recurrence After Transplant) Score is a validated tool to predict post-transplant HCC recurrence risk. Alpha-fetoprotein (AFP) bound to Lens culinaris agglutinin (AFP-L3) and des-gamma-carboxyprothrombin (DCP) measured at transplant predict worse post-LT survival and may improve the RETREAT score. Our cohort comprised 284 patients transplanted for HCC who were within or downstaged to Milan, with 23 (8.1%) experiencing HCC recurrence. The modified RETREAT (mRETREAT) score assigns AFP-L3 ≥15% 2 points and DCP ≥7.5 ng/mL 3 points. Patients with a modified RETREAT score ≥4 showed a 3-year recurrence-free survival of 73.2% versus 97.8% recurrence-free survival if <4. In comparison, the original RETREAT score had a 3-year recurrence-free survival of 80.0% if ≥2 versus 98.0% if <2. mRETREAT demonstrated a superior AUC of 0.86, compared to the original RETREAT's 0.82, and enhanced calibration and accuracy with a lower Brier score (0.04). The integration of AFP-L3 and DCP into the RETREAT score appears to enhance the prediction of post-LT HCC recurrence. Given these promising results, further study in a larger multicenter cohort is warranted for empiric derivation and validation of a modified RETREAT score, including AFP-L3 and DCP.

Worldwide trends support the increasing contribution of hepatic steatosis to the incidence of hepatocellular carcinoma (HCC). This study investigates if similar changes are seen in Hawaii, where the incidence of HCC is higher than in most of the United States.

This is a retrospective study of 1,651 patients diagnosed with HCC (1991-2023) that includes 60% to 70% of HCC cases in Hawaii. We evaluated changes in patient demographics, risk factors, and disease etiology over the past three decades.

From 1991 to 2023, there were significant increases in the proportion of HCC cases attributable to metabolic dysfunction-associated steatotic liver disease (MASLD), coinciding with an increase in the prevalence of metabolic risk factors including obesity, diabetes, hyperlipidemia, and hypertension. Cases with a history of smoking also increased through 2020. Conversely, HCC cases presenting with cirrhosis alone decreased. Hepatitis C virus (HCV)-associated cases increased through 2015 and then tapered, whereas Hepatitis B virus (HBV)-associated cases decreased through 2020. There was no significant change in the proportion of alcohol-associated cases.

Although HBV continues to be a major contributor to HCC in Hawaii, HCV-related HCC cases have tapered, whereas metabolic risk factors for HCC and cases attributable to MASLD have increased over time, paralleling overall trends observed in the United States. Efforts are needed to manage these metabolic factors to address the burden of HCC.

Although Hawaii continues to have a large burden of viral hepatitis-related HCC, metabolic factors and MASLD have affected the pathogenesis of liver cancer in Hawaii over the past three decades.

Timely and accurate diagnosis of hepatocellular carcinoma (HCC) is essential for improving patient outcomes and guiding treatment. This multicenter study aimed to optimize the diagnostic workflow for HCC through a step-wise combination of CT/MRI and contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS).

This was a multicenter, retrospective analysis of prospectively recruited high-risk HCC participants with liver observations from 4 institutions, between January 2017 and December 2021. These participants initially underwent CT/MRI followed by CEUS, with observations categorized according to CT/MRI/CEUS LI-RADS. Three step-wise diagnostic strategies were evaluated, starting with CT/MRI and followed by CEUS, and compared to CT/MRI LI-RADS alone. Performance metrics included AUC, accuracy, sensitivity, specificity, PPV, and NPV, using pathology or over one year of follow-up as standards. The impact on clinical decisions was measured by false-negative, false-positive, and biopsy rates.

Of 1264 participants, 874 (69%) were confirmed as HCC. The step-wise strategies outperformed CT/MRI LI-RADS. Strategy-3, which involved subsequent CEUS for CT/MRI LR-3/4 observations, significantly improved sensitivity (88.8% vs. 79.9%, P < 0.001) while maintaining comparable specificity (88.2% vs. 91.3%, P > 0.05). Strategy-3 reduced biopsy rate (31.5-22.4%, P = 0.028) and decreased false-negative rate (20.1-11.2%, P < 0.001). Additionally, 96% (55/57) of CT/MRI LR-3 and 97% (77/79) of CT/MRI LR-4 observations were accurately diagnosed and treated as HCC, with 61% (74/121) of CT/MRI LR-4 observations avoiding biopsy with CEUS-assisted.

A step-wise approach using CT/MRI followed by CEUS for LR-3/4 observations improved the diagnostic performance and further refined clinical decision-making in HCC.

Clinical Trial Registration Number: ChiCTR-DDD-16010089.

To compare the diagnostic performance of two algorithms for HCC diagnosis: SonoVue-CEUS based on CEUS LI-RADS version 2017 and a modified algorithm incorporating Kupffer-phase findings for Sonazoid-CEUS.

This single center prospective study enrolled high-risk patients for HCC. Each participant underwent SonoVue-CEUS and Sonazoid-CEUS. Each liver observation was assigned two LI-RADS categories according to each algorithm: SonoVue-CEUS LI-RADS and modified Sonazoid-CEUS LI-RADS. For the latter method, observations at least 10 mm with non-rim arterial phase hyperenhancement were upgraded LR-4 to LR-5 if there was no washout with a Kupffer defect and were reassigned LR-M to LR-5 if there was early washout with mild Kupffer defect. The reference standard was pathologic confirmation.

Overall, 66 patients (mean age, 61.2 years ± 10.9; 54 male patients, 12 female patients) with 66 observations (mean size, 31 mm ± 16) were eventually enrolled. The results of Sonazoid-CEUS LI-RADS showed significant changes in sensitivity (82% vs. 65%, p < 0.001), accuracy (85% vs. 71%, p < 0.001) compared with the SonoVue-CEUS LI-RADS. There was no significant difference in specificity (93% vs. 87%, p = 0.26).

When incorporating Kupffer-phase findings, Sonazoid-CEUS LI-RADS had higher sensitivity without loss of specificity compared with SonoVue-CEUS LI-RADS.

Chronic liver disease is a cluster of disorders associated with complex haemodynamic alterations, which is characterised by structural and functional disruptions of the intrahepatic and extrahepatic vasculature. 'Vasomics' is an emerging omics discipline that comprehensively analyses and models the vascular system by integrating pathophysiology of disease, biomechanics, medical imaging, computational science and artificial intelligence. Vasomics is further typified by its multidimensional, multiscale and high-throughput nature, which depends on the rapid and robust extraction of well-defined vascular phenotypes with clear clinical and/or biological interpretability. By leveraging multimodality medical imaging techniques, vascular functional assessments, pathological image evaluation, and related computational methods, integrated vasomics provides a deeper understanding of the associations between the vascular system and disease. This in turn reveals the crucial role of the vascular system in disease occurrence, progression and treatment responses, thereby supporting precision medicine approaches. Pathological vascular features have already demonstrated their key role in different clinical scenarios. Despite this, vasomics is yet to be widely recognised. Therefore, we furnished a comprehensive definition of vasomics providing a classification of existing hepatic vascular phenotypes into the following categories: anatomical, biomechanical, biochemical, pathophysiological and composite.

Hepatocellular carcinoma (HCC) poses a heavy global disease burden; early diagnosis is critical to improve outcomes. Opportunistic screening-the use of imaging data acquired for other clinical indications for disease detection-as well as the role of noncontrast CT have been poorly investigated in the context of HCC. We aimed to develop an artificial intelligence algorithm for efficient and accurate HCC detection using solely noncontrast CTs.

A 3-D convolutional block attention module (CABM) model was developed and trained on noncontrast multiphasic CT scans. HCC was diagnosed following American Association for the Study of Liver Disease guidelines and confirmed via 12-month clinical composite reference standard. CT observations were reviewed by radiologists; observations in at-risk patients were annotated via the Liver Imaging Reporting and Data System. Internal validation, independent external testing, and sensitivity analyses were performed to evaluate model performance and generalizability.

In all, 2,223 patients were included. The CBAM model achieved an area under the receiver operating curve (AUC) of 0.807 (95% confidence interval [CI] 0.772-0.841) on the internal validation cohort, comparable to radiological interpretation at 0.851 (95% CI 0.820-0.882). Among at-risk patients, cases with definite HCC outcomes, indeterminate scans, and scans with small lesions < 2 cm in size, the model attained AUCs of 0.769 (95% CI 0.721-0.817), 0.815 (95% CI 0.778-0.853), 0.769 (95% CI 0.704-0.834), and 0.773 (95% CI 0.692-0.854). On external testing cohort with 584 patients, the CBAM model achieved an AUC of 0.789 (95% CI 0.750-0.827).

The CBAM model achieved a diagnostic accuracy comparable to radiological interpretation during internal validation. Artificial intelligence analysis of noncontrast CTs has a potential role in HCC opportunistic screening.

Many guidelines for hepatocellular carcinoma (HCC) have been published and are regularly updated worldwide. HCC management involves a broad range of treatment options and requires multidisciplinary care, resulting in significant heterogeneity in management practices across international communities. To support standardized care for HCC, we systematically appraised 13 globally recognized guidelines and expert consensus statements, including five from Asia, four from Europe, and four from the United States. These guidelines share similarities but reveal notable discrepancies in surveillance strategies, treatment allocation, and other recommendations. Geographic differences in tumor biology (e.g., prevalence of viral hepatitis, alcohol-related liver disease, or metabolic dysfunction-associated steatotic liver disease) and disparities in available medical resources (e.g., organ availability, healthcare infrastructure, and treatment accessibility) complicate the creation of universally applicable guidelines. Previously, significant gaps existed between Asian and Western guidelines, particularly regarding treatment strategies. However, these differences have diminished over the years. Presently, variations are often more attributable to publication dates than to regional differences. Nonetheless, Asia-Pacific experts continue to diverge from the Barcelona Clinic Liver Cancer system, particularly with respect to surgical resection and locoregional therapies, which are viewed as overly conservative in Western guidelines. Advancements in systemic therapies have prompted ongoing updates to these guidelines. Given that each set of guidelines reflects distinct regional characteristics, strengths, and limitations, fostering collaboration and mutual complementarity is essential for addressing discrepancies and advancing global HCC care.

Patients with HCC meeting United Network for Organ Sharing (UNOS)-downstaging (DS) criteria have excellent post-liver transplantation (LT) outcomes. Studies on HCC beyond UNOS-DS criteria ("All-Comers" [AC]) have been limited by small sample size and short follow-up time, prompting this analysis.

Three hundred twenty-six patients meeting UNOS-DS and 190 meeting AC criteria from 9 LT centers across 5 UNOS regions were enrolled from 2015 to 2023 and prospectively followed. Competing risk analysis and Kaplan-Meier method were used to evaluate DS and LT outcomes, and Fine-and-Gray and Cox models were used to identify predictors of outcomes. AC and UNOS-DS had similar median alpha-fetoprotein (15 vs. 12 ng/mL; p =0.08), MELD (9 vs. 9; p =0.52), and Child-Pugh (A vs. A; p =0.30). Two years after the first local regional therapy, 82% of UNOS-DS and 66% of AC were successfully downstaged ( p <0.001). In AC, DS rates were 72% for tumor number plus diameter of largest lesion <10, 51% for sum 10-12, and 39% for sum >12 ( p =0.01). Yttrium-90 achieved higher DS success than transarterial chemoembolization in AC (74% vs. 65%; p <0.001). 48% of UNOS-DS and 40% of AC underwent LT ( p =0.10). Five-year post-LT survival was similar between UNOS-DS and AC (74% vs. 72%; p =0.77), although 5-year post-LT recurrence was higher in AC (30% vs. 14%; p =0.02).

Despite higher HCC recurrence and lower intention-to-treat survival in AC, post-LT survival was comparable between UNOS-DS and AC. Yttrium-90 attained higher DS success than transarterial chemoembolization in AC. LT after DS is feasible in AC, though defining an upper limit in tumor burden may be necessary.

Personalized precision medicine can be facilitated by clinically available preoperative microvascular invasion (MVI) prediction models that are reliable and postoperative MVI pathological grade-related recurrence prediction models that are accurate. In this study, we aimed to compare different mathematical models to derive the best preoperative prediction and postoperative recurrence prediction models for MVI.

A total of 143 patients with hepatocellular carcinoma (HCC) whose clinical, laboratory, imaging, and pathological data were available were included in the analysis. Logistic regression, Cox proportional hazards regression, LASSO regression with 10-fold cross-validation, stepwise regression, and random forest methods were used for variable screening and predictive modeling. The accuracy and validity of seven preoperative MVI prediction models and five postoperative recurrence prediction models were compared in terms of C-index, net reclassification improvement, and integrated discrimination improvement.

Multivariate logistic regression analysis revealed that a preoperative nomogram model with the variables cirrhosis diagnosis, alpha-fetoprotein > 400, and diameter, shape, and number of lesions can predict MVI in patients with HCC reliably. Postoperatively, a nomogram model with MVI grade, number of lesions, capsule involvement status, macrovascular invasion, and shape as the variables was selected after LASSO regression and 10-fold cross-validation analysis to accurately predict the prognosis for different MVI grades. The number and shape of the lesions were the most common predictors of MVI preoperatively and recurrence postoperatively.

Our study identified the best statistical approach for the prediction of preoperative MVI as well as postoperative recurrence in patients with HCC based on clinical, imaging, and laboratory tests results. This could expedite preoperative treatment decisions and facilitate postoperative management.

The purpose of this study was to compare radiation dose reduction capability for accurate liver tumor measurements of a computer-aided volumetry (CAD v ) software for filtered back projection (FBP), hybrid-type iterative reconstruction (IR), mode-based iterative reconstruction (MBIR), and deep learning reconstruction (DLR) at a phantom study.

A commercially available anthropomorphic abdominal phantom was scanned five times with a 320-detector row CT at 600 mA, 400 mA, 200 mA, and 100 mA and reconstructed by four methods. Signal-to-noise ratios (SNRs) of all lesions within the arterial and portal-venous phase inserts were calculated, and SNR of the lesion phantom was compared with that of all reconstruction methods by means of Tukey's honestly significant difference (HSD) test. Then, tumor volume ( V ) of each nodule was automatically measured using commercially available CAD v software. To compare dose reduction capability for each reconstruction method at both phases, mean differences between measured V and standard references were compared by Tukey's honestly significant difference test among the four different reconstruction methods on CT obtained at each of the four tube currents.

With each of the tube currents, SNRs for MBIR and DLR were significantly higher than those for FBP and hybrid-type IR ( p < 0.05). At the arterial phase, the mean difference in V for the CT protocol obtained at 600 or 100 mA and reconstructed with DLR was significantly smaller than that for others ( p < 0.05). At the portal-venous phase, the mean differences in V for the CT protocol obtained at 100 mA and reconstructed with hybrid-type IR, MBIR, and DLR were significantly smaller than that for FBP ( p < 0.05).

Findings of our phantom study show that reconstruction method had influence on CAD v merits for abdominal CT with not only standard but also reduced dose examinations and that DLR can potentially yield better image quality and CAD v measurements than FBP, hybrid-type IR, or MBIR in this setting.

Primary liver cancers are tumors that develop from different liver cells. Hepatocellular carcinoma (HCC), which develops from hepatocytes, accounts for approximately 75-85% of primary liver cancers.HCC is the 6th leading cause of cancer worldwide and the 3rd leading cause of cancer-related death. Its incidence is low in northern Europe, but high in sub-Saharan Africa and the Far East, where both hepatotropic viruses and exposure to mycotoxins are. It complicates cirrhosis in over 90% of cases and is predominantly male.The prevalence of HCC is increasing due to improved diagnostic techniques and criteria, but also to the persistence of hepatitis B virus (HBV) and hepatitis C virus (HCV) infections in adults. A worldwide increase in the incidence of steatopathy makes it the leading cause of liver disease worldwide, associated with alcohol abuse and/or steatohepatitis associated with metabolic dysfunction (MASH), including type 2 diabetes.Chronic hepatotropic viral infections, cirrhosis and chemical carcinogens combine to produce an annual incidence of 2-5% of hepatocellular carcinoma arising from cirrhosis. This justifies biannual surveillance of known cirrhosis, without which late diagnosis limits therapeutic options.Major advances have been made in curative treatment (liver transplantation, surgery, radiodestruction) and palliative treatment (chemo- or radioembolization, sorafenib chemotherapy or immunotherapy), depending on how early HCC is diagnosed (size, number of hepatic or extrahepatic lesions) and the severity of underlying liver disease and associated comorbidities.

The current staging system has limitations in preoperatively assessing hepatocellular carcinoma (HCC) and in precise detailed treatment allocation. This study aims to propose a new Liver Tumor Imaging Staging (LTIS) method for HCC.

1295 patients who underwent CT or MRI and curative liver resection during January 2012 and October 2020 were retrospectively recruited from three independent institutions. All images were interpreted by two abdominal and a board-certified radiologist. LTIS was designed to discriminate low-grade (absence of microvascular invasion [MVI] and Edmondson-Steiner grade III/IV), intermediate (MVI + or Edmondson-Steiner grade III/IV but not both) and high-grade HCC (MVI + and Edmondson-Steiner grade III/IV) upon CT and MRI. Model was constructed in 578 derivation cohort (center 1) and validated in internal center 1 test cohort (n = 291), and external center 2 (n = 226) and center 3 (n = 200), respectively. Cronbach's alpha statistics were determined to assess interobserver agreement. Net clinical benefit of LTIS on recurrence-free survival (RFS) and overall survival (OS) was analyzed with a Cox proportional hazards model.

LTIS shows good inter-reader agreements in both CT and MRI datasets, with a Cronbach's alpha coefficient of 0.86 and 0.85, respectively. In independent test, LTIS achieved agreement of 73.2% (281/384), 18.9% (100/528), and 69.2% (265/383) for determining low, intermediate, and high-grade HCCs with "ground truth" results. In the Cox analysis, LTIS was comparable to "ground truth" grade for predicting RFS (hazards ratio (HR), 1.30 vs. ground truth grade, 1.36 and 1.56) and OS (HR, 1.76 vs. ground truth grade, 2.00 and 3.03) of patients after surgery. In patients conventionally classified as having low-grade tumors (serum α-fetoprotein < 400 ng/mL, stage T1), 47.4% and 35.6% were reclassified as high-grade tumors upon LTIS restaging. The resulting LTIS subgroups showed a significant difference in RFS and OS at Kaplan-Meier analysis (Log-rank test, p < 0.001).

LTIS provides a potential noninvasive way to precisely stage HCC using CT and MRI.

Prognosticating survival among patients with HCC and cirrhosis must account for both the tumor burden/stage, as well as the severity of the underlying liver disease. Although there are many staging systems used to guide therapy, they have not been widely adopted to predict patient-level survival after the diagnosis of HCC. We sought to develop a score to predict long-term survival among patients with early- to intermediate-stage HCC using purely objective criteria.

Retrospective cohort study among patients with HCC confined to the liver, without major medical comorbidities within the Veterans Health Administration from 2014 to 2023. Tumor data were manually abstracted and combined with clinical and laboratory data to predict 5-year survival from HCC diagnosis using accelerated failure time models. The data were randomly split using a 75:25 ratio for training and validation. Model discrimination and calibration were assessed and compared to other HCC staging systems.

The cohort included 1325 patients with confirmed HCC. A risk score using baseline clinical, laboratory, and HCC-related survival had excellent discrimination (integrated AUC: 0.71 in the validation set) and calibration (based on calibration plots and Brier scores). Models had superior performance to the BCLC and ALBI scores and similar performance to the combined BCLC-ALBI score.

We developed a risk score using purely objective data to accurately predict long-term survival for patients with HCC. This score, if validated, can be used to prognosticate survival for patients with HCC, and, in the setting of liver transplantation, can be incorporated to consider the net survival benefit of liver transplantation versus other curative options.

In patients evaluated for hepatocellular carcinoma (HCC), magnetic resonance imaging (MRI) is often used secondarily when multiphase contrast-enhanced computed tomography (ceCT) is inconclusive. We investigated the clinical impact of adding MRI.

This single-institution retrospective study included 48 MRI scans (44 patients) conducted from May 2016 to July 2023 due to suspicion of HCC on a multiphase ceCT scan. Data included medical history, preceding and subsequent imaging, histology when available, and decisions made at multidisciplinary team meetings.

In case of possible HCC recurrence, 63% of the MRI scans were diagnostic of HCC. For 80% of the negative MRI scans, the patients were diagnosed with HCC within a median of 165 days in the suspicious area of the liver. In case of possible de-novo HCC in patients with cirrhosis, 22% of the scans were diagnostic of HCC and 33% of the negative MRI scans were of patients diagnosed with HCC within a median of 109 days. None of the non-cirrhotic patients with possible de-novo HCC and negative MRI scans (64%) were later diagnosed with HCC, but 3/5 of the indeterminate scans were of patients diagnosed with HCC in a biopsy.

Secondary MRI to a multiphase ceCT scan suspicious of HCC is highly valuable in ruling out HCC in non-cirrhotic patients and in diagnosing HCC non-invasively in cirrhotic patients and patients with prior HCC. Patients with cirrhosis or prior HCC are still at high risk of having HCC if MRI results are inconclusive or negative.

Ultrasound (US) is recommended for HCC surveillance in high-risk patients but has limited performance in detecting early-stage HCC. We aimed to compare the diagnostic performance of biannual US and annual non-contrast abbreviated magnetic resonance imaging (NC-AMRI) as HCC surveillance modalities in high-risk patients.

This prospective, multicenter cohort study enrolled participants with an estimated annual risk of HCC greater than 5% between October 2015 and April 2017. Participants underwent six rounds of HCC surveillance at 6-month intervals, with both US and NC-AMRI at rounds 1, 3, and 5, and only US at rounds 2, 4, and 6. The sensitivity, diagnostic yield (DY), and false referral rate (FRR) for HCC detection by US and NC-AMRI were compared.

In total, 208 participants underwent 980 US and 516 NC-AMRI examinations during 30 months of follow-up. Among them, 34 HCCs were diagnosed in 31 participants, with 20 (64.5%) classified as very early-stage and 11 (35.5%) as early-stage HCC. The sensitivity of annual NC-AMRI (71.0%, 22/31) was marginally higher than that of biannual US (45.2%, 14/31; p = 0.077). NC-AMRI showed a significantly higher DY than US (4.26% vs. 1.43%, p <0.001), with a similar FRR (2.91% vs. 3.06%, p = 0.885). A simulation of alternating US and NC-AMRI at 6-month intervals yielded a sensitivity of 83.9% (26/31), significantly exceeding that of biannual US (p = 0.006).

Annual NC-AMRI showed a marginally higher sensitivity than biannual US for HCC detection in high-risk patients. The DY of annual NC-AMRI was significantly higher than that of biannual US, without increasing the FRR. Thus, alternating US and NC-AMRI at 6-month intervals could be an optimal surveillance strategy for high-risk patients.

Current guidelines permit the use of magnetic resonance imaging (MRI) as a surveillance tool for hepatocellular carcinoma in patients in whom ultrasonography (US) is inadequate. However, the specific indications, imaging sequences, and intervals for MRI surveillance remain unclear. In our study, we found that annual non-contrast abbreviated MRI exhibited marginally higher sensitivity and significantly better diagnostic yield than biannual US in patients at high risk of hepatocellular carcinoma. Alternating US and non-contrast abbreviated MRI at 6-month intervals led to significantly improved sensitivity compared to biannual US, making it a potentially optimal surveillance strategy for high-risk patients.

NCT02551250.

Microvascular invasion (MVI) is a recognized biomarker associated with poorer prognosis in patients with hepatocellular carcinoma. Dual-energy computed tomography (DECT) is a highly sensitive technique that can determine the iodine concentration (IC) in tumour and provide an indirect evaluation of internal microcirculatory perfusion. This study aimed to assess whether the combination of DECT with laboratory data can improve preoperative MVI prediction.

This retrospective study enrolled 119 patients who underwent DECT liver angiography at 2 medical centres preoperatively. To compare DECT parameters and laboratory findings between MVI-negative and MVI-positive groups, Mann-Whitney U test was used. Additionally, principal component analysis (PCA) was conducted to determine fundamental components. Mann-Whitney U test was applied to determine whether the principal component (PC) scores varied across MVI groups. Finally, a general linear classifier was used to assess the classification ability of each PC score.

Significant differences were noted (P < .05) in alpha-fetoprotein (AFP) level, normalized arterial phase IC, and normalized portal phase IC between the MVI groups in the primary and validation datasets. The PC1-PC4 accounted for 67.9% of the variance in the primary dataset, with loadings of 24.1%, 16%, 15.4%, and 12.4%, respectively. In both primary and validation datasets, PC3 and PC4 were significantly different across MVI groups, with area under the curve values of 0.8410 and 0.8373, respectively.

The recombination of DECT IC and laboratory features based on varying factor loadings can well predict MVI preoperatively.

Utilizing PCA, the amalgamation of DECT IC and laboratory features, considering diverse factor loadings, showed substantial promise in accurately classifying MVI. There have been limited endeavours to establish such a combination, offering a novel paradigm for comprehending data in related research endeavours.

Large language models show promise for improving radiology workflows, but their performance on structured radiological tasks such as Reporting and Data Systems (RADS) categorization remains unexplored.

This study aims to evaluate 3 large language model chatbots-Claude-2, GPT-3.5, and GPT-4-on assigning RADS categories to radiology reports and assess the impact of different prompting strategies.

This cross-sectional study compared 3 chatbots using 30 radiology reports (10 per RADS criteria), using a 3-level prompting strategy: zero-shot, few-shot, and guideline PDF-informed prompts. The cases were grounded in Liver Imaging Reporting & Data System (LI-RADS) version 2018, Lung CT (computed tomography) Screening Reporting & Data System (Lung-RADS) version 2022, and Ovarian-Adnexal Reporting & Data System (O-RADS) magnetic resonance imaging, meticulously prepared by board-certified radiologists. Each report underwent 6 assessments. Two blinded reviewers assessed the chatbots' response at patient-level RADS categorization and overall ratings. The agreement across repetitions was assessed using Fleiss κ.

Claude-2 achieved the highest accuracy in overall ratings with few-shot prompts and guideline PDFs (prompt-2), attaining 57% (17/30) average accuracy over 6 runs and 50% (15/30) accuracy with k-pass voting. Without prompt engineering, all chatbots performed poorly. The introduction of a structured exemplar prompt (prompt-1) increased the accuracy of overall ratings for all chatbots. Providing prompt-2 further improved Claude-2's performance, an enhancement not replicated by GPT-4. The interrun agreement was substantial for Claude-2 (k=0.66 for overall rating and k=0.69 for RADS categorization), fair for GPT-4 (k=0.39 for both), and fair for GPT-3.5 (k=0.21 for overall rating and k=0.39 for RADS categorization). All chatbots showed significantly higher accuracy with LI-RADS version 2018 than with Lung-RADS version 2022 and O-RADS (P<.05); with prompt-2, Claude-2 achieved the highest overall rating accuracy of 75% (45/60) in LI-RADS version 2018.

When equipped with structured prompts and guideline PDFs, Claude-2 demonstrated potential in assigning RADS categories to radiology cases according to established criteria such as LI-RADS version 2018. However, the current generation of chatbots lags in accurately categorizing cases based on more recent RADS criteria.

Chronic hepatitis B virus (HBV) infection is the predominant cause of hepatocellular carcinoma in west Africa, yet data on the incidence of HBV-related hepatocellular carcinoma remain scarce. We aimed to describe the uptake and early outcomes of systematic ultrasound-based hepatocellular carcinoma screening in SEN-B, which is a prospective HBV cohort in Senegal.

In this prospective cohort study, we included treatment-naive, HBsAg-positive individuals who were referred to the two infectious diseases clinics (the Department of Tropical and Infectious Diseases and Ambulatory Treatment Center) at Fann University Hospital of Dakar, Senegal, between Oct 1, 2019, and Oct 31, 2022. All participants resided within the Dakar region. Participants underwent abdominal ultrasound, transient elastography, and clinical and virological assessments at inclusion and every 6 months. Liver lesions at least 1 cm in diameter on ultrasound were assessed using four-phase CT, MRI, or liver biopsy. Adherence to hepatocellular carcinoma surveillance was measured using the proportion of time covered, calculated by dividing the cumulative months covered by abdominal ultrasound examinations by the overall follow-up time, defined as the number of months from the date of cohort entry until the last recorded visit, hepatocellular carcinoma diagnosis, or death. Optimal adherence was defined as a proportion of time covered of 100%.

Overall, 755 (99·6%) of 758 participants had at least one abdominal ultrasound performed. The median age of the enrolled participants was 31 years (IQR 25-39), 355 (47·0%) of 755 participants were women, and 82 (10·9%) had a family history of hepatocellular carcinoma. 15 (2·0%) of 755 individuals were HBeAg positive, 206 (27·3%) of 755 individuals had HBV DNA of more than 2000 IU/mL, and 27 (3·6%) of 755 had elastography-defined liver cirrhosis. Of ten (1·3%) participants with a focal lesion at least 1 cm at initial assessment, CT or MRI ruled out hepatocellular carcinoma in nine, whereas imaging and subsequent liver biopsy confirmed one patient with hepatocellular carcinoma. Two further patients with hepatocellular carcinoma were diagnosed at study presentation due to the presence of portal thrombosis on ultrasound. Excluding the three participants with hepatocellular carcinoma identified at baseline, 752 participants were eligible for screening every 6 months. Median follow-up time was 12 months (IQR 6-18) and the median number of ultrasounds per patient was 3 (2-4). During 809·5 person-years of follow-up, one incident hepatocellular carcinoma was reported, resulting in an incidence rate of 1·24 cases per 1000 person-years (95% CI 0·18-8·80). Overall, 702 (93·0%) of 755 participants showed optimal hepatocellular carcinoma surveillance, but this proportion decreased to 77·8% (42 of 54 participants) after 24 months.

Hepatocellular carcinoma screening is feasible in HBV research cohorts in west Africa, but its longer-term acceptability needs to be evaluated. Long-term hepatocellular carcinoma incidence data are crucial for shaping tailored screening recommendations.

Swiss National Science Foundation, the Swiss Cancer Research Foundation, the National Cancer Institute, and Roche Diagnostics.

For the French translation of the abstract see Supplementary Materials section.

Available data on hepatocellular carcinoma (HCC) recurrence after direct-acting antivirals (DAAs) treatment for hepatitis C virus (HCV) are conflicting. No randomized trials were done. This study aims to compare the 1-year HCC recurrence rates in patients who received DAAs after tumor ablation versus those who postponed HCV treatment for 1 year.

Included patients were randomized after complete HCC ablation into two groups: a postponed DAAs group for whom DAAs initiation was postponed for 12 months and a DAAs group who were given sofosbuvir/velpatasvir. Patients were followed for 1 year.

Eighty-four HCV patients with a mean age of 56.35 ± 8.12 years were included; 78.57% of them were males. The number of lesions per patient ranged from 1 to 3 lesions, and the size of the largest lesion ranged from 1.5 to 5 cm. There were no statistically significant differences between both groups regarding baseline characteristics. In the DAAs group (43 patients), 11 patients had HCC recurrence, while 25 patients in the postponed DAAs group (41 patients) had HCC recurrence. Using Kaplan-Meier analysis, the 1-year recurrence-free survival (RFS) was significantly higher in the DAAs group (72.2% vs. 38%, P = 0.001). On multivariate analysis, both higher albumin levels (HR 0.147, 95% CI 0.066-0.329) and receiving DAAs (HR 0.358, 95% CI 0.176-0.730) 1 year after ablation were associated with significantly lower recurrence.

Direct-acting antiviral usage after complete hepatocellular carcinoma ablation significantly decreases the 1-year HCC recurrence rates, but the risk of recurrence is still not eliminated. The study registration number on clinicaltrials.gov : NCT04653818 (initial release on 28/11/2020).

We conducted a comprehensive review of the current literature of published data and clinical trials (MEDLINE), as well as published congress contributions and active recruiting clinical trials on targeted therapies in hepatocellular carcinoma. Combinations of different agents and medical therapy along with radiological interventions were analyzed for the setting of advanced HCC. Those settings were also analyzed in combination with adjuvant situations after resection or radiological treatments. We summarized the current knowledge for each therapeutic setting and combination that currently is or has been under clinical evaluation. We further discuss the results in the background of current treatment guidelines. In addition, we review the pathophysiological mechanisms and pathways for each of these investigated targets and drugs to further elucidate the molecular background and underlying mechanisms of action. Established and recommended targeted treatment options that already exist for patients are considered for systemic treatment: atezolizumab/bevacizumab, durvalumab/tremelimumab, sorafenib, lenvatinib, cabozantinib, regorafenib, and ramucirumab. Combination treatment for systemic treatment and local ablative treatment or transarterial chemoembolization and adjuvant and neoadjuvant treatment strategies are under clinical investigation.

The aim of this study was to evaluate outcomes of transarterial radioembolization (TARE) for hepatocellular carcinoma (HCC) in patients previously treated with transarterial embolization (TAE). In this retrospective study, all HCC patients who received TARE from 1/2012 to 12/2022 for treatment of residual or recurrent disease after TAE were identified. Overall survival (OS) was estimated using the Kaplan-Meier method. Univariate Cox regression was performed to determine significant predictors of OS after TARE. Twenty-one patients (median age 73.4 years, 18 male, 3 female) were included. Median dose to the perfused liver volume was 121 Gy (112-444, range), and 18/21 (85.7%) patients received 112-140 Gy. Median OS from time of HCC diagnosis was 32.9 months (19.4-61.4, 95% CI). Median OS after first TAE was 29.3 months (15.3-58.9, 95% CI). Median OS after first TARE was 10.6 months (6.8-27.0, 95% CI). ECOG performance status of 0 (p = 0.038), index tumor diameter < 4 cm (p = 0.022), and hepatic tumor burden < 25% (p = 0.018) were significant predictors of longer OS after TARE. TARE may provide a survival benefit for appropriately selected patients with HCC who have been previously treated with TAE.

Diagnostic performance of imaging for regional lymph node assessment in gastric cancer is still limited, and there is a lack of consensus on radiological evaluation. At the same time, there is an increasing demand for structured reporting using Reporting and Data Systems (RADS) to standardize oncological imaging. We aimed at investigating the diagnostic performance of Node-RADS compared to the use of various individual criteria for assessing regional lymph nodes in gastric cancer using histopathology as reference.

In this retrospective single-center study, consecutive 91 patients (median age, 66 years, range 33-91 years, 54 men) with CT scans and histologically proven gastric adenocarcinoma were assessed using Node-RADS assigning scores from 1 to 5 for the likelihood of regional lymph node metastases. Additionally, different Node-RADS criteria as well as subcategories of altered border contour (lobulated, spiculated, indistinct) were assessed individually. Sensitivity, specificity, and Youden's index were calculated for Node-RADS scores, and all criteria investigated. Interreader agreement was calculated using Cohen's kappa.

Among all criteria, best performance was found for Node-RADS scores ≥ 3 and ≥ 4 with a sensitivity/specificity/Youden's index of 56.8%/90.7%/0.48 and 48.6%/98.1%/0.47, respectively, both with substantial interreader agreement (κ = 0.73 and 0.67, p < 0.01). Among individual criteria, the best performance was found for short-axis diameter of 10 mm with sensitivity/specificity/Youden's index of 56.8%/87.0%/0.44 (κ = 0.65, p < 0.01).

This study shows that structured reporting of combined size and configuration criteria of regional lymph nodes in gastric cancer slightly improves overall diagnostic performance compared to individual criteria including short-axis diameter alone. The results show an increase in specificity and unchanged sensitivity.

The results of this study suggest that Node-RADS may be a suitable tool for structured reporting of regional lymph nodes in gastric cancer.

• Assessment of lymph nodes in gastric cancer is still limited, and there is a lack of consensus on radiological evaluation. • Node-RADS in gastric cancer improves overall diagnostic performance compared to individual criteria including short-axis diameter. • Node-RADS may be a suitable tool for structured reporting of regional lymph nodes in gastric cancer.

Cholangiocarcinoma (CCA), a highly aggressive primary liver cancer arising from the bile duct epithelium, represents a substantial proportion of hepatobiliary malignancies, posing formidable challenges in diagnosis and treatment. Notably, the global incidence of intrahepatic CCA has seen a rise, necessitating a critical examination of diagnostic and management strategies, especially due to presence of close imaging mimics such as hepatocellular carcinoma (HCC) and combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA). Hence, it is imperative to understand the role of various imaging modalities such as ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), elucidating their strengths, and limitations in diagnostic precision and staging accuracy. Beyond conventional approaches, there is emerging significance of functional imaging tools including positron emission tomography (PET)-CT and diffusion-weighted (DW)-MRI, providing pivotal insights into diagnosis, therapeutic assessment, and prognostic evaluation. This comprehensive review explores the risk factors, classification, clinical features, and role of imaging in the holistic spectrum of diagnosis, staging, management, and restaging for CCA, hence serving as a valuable resource for radiologists evaluating CCA.

The aim of this study is to describe a comprehensive contrast-enhanced ultrasound (CEUS) imaging protocol and analysis method to implement CEUS LI-RADS (Liver Imaging Reporting and Data System) in a quantifiable manner. The methods that are validated with a prospective single-center study aim to simplify CEUS LI-RADS evaluation, remove observer bias, and potentially improve the sensitivity of CEUS LI-RADS.

This prospective single-center study enrolled patients with hepatocellular carcinoma (April 2021-June 2022; N = 31; mean age ± SD, 67 ± 6 years; 24 men/7 women). For each patient, at least 2 CEUS loops spanning over 5 minutes were collected for different lesion scan planes using an articulated arm to hold the transducer. Automatic respiratory gating and motion compensation algorithms removed errors due to breathing motion. The long axis of the lesion was measured in the contrast and fundamental images to capture nodule size. Parametric processing of time-intensity curve analysis on linearized data provided quantifiable information of the wash-in and washout dynamics via rise time ( RT ) and degree of washout ( DW ) parameters extracted from the time-intensity curve, respectively. A Welch t test was performed between lesion and parenchyma RT for each lesion to confirm statistically significant differences. P values for bootstrapped 95% confidence intervals of the relative degree of washout ( rDW ), ratio of DW between the lesion and surrounding parenchyma, were computed to quantify lesion washout. Coefficient of variation (COV) of RT , DW , and rDW was calculated for each patient between injections for both the lesion and surrounding parenchyma to gauge reproducibility of these metrics. Spearman rank correlation tests were performed among size, RT , DW , and rDW values to evaluate statistical dependence between the variables.

The mean ± SD lesion diameter was 23 ± 8 mm. The RT for all lesions, capturing arterial phase hyperenhancement, was shorter than that of surrounding liver parenchyma ( P < 0.05). All lesions also demonstrated significant ( P < 0.05) but variable levels of washout at both 2-minute and 5-minute time points, quantified in rDW . The COV of RT for the lesion and surrounding parenchyma were both 11%, and the COV of DW and rDW at 2 and 5 minutes ranged from 22% to 31%. Statistically significant relationships between lesion and parenchyma RT and between lesion RT and lesion DW at the 2- and 5-minute time points were found ( P < 0.05).

The imaging protocol and analysis method presented provide robust, quantitative metrics that describe the dynamic vascular patterns of LI-RADS 5 lesions classified as hepatocellular carcinomas. The RT of the bolus transit quantifies the arterial phase hyperenhancement, and the DW and rDW parameters quantify the washout from linearized CEUS intensity data. This unique methodology is able to implement the CEUS-LIRADS scheme in a quantifiable manner for the first time and remove its existing issues of currently being qualitative and suffering from subjective evaluations.

To investigate the value of differential diagnosis of hepatocellular carcinoma (HCC) and non-hepatocellular carcinoma (non-HCC) based on CT and MR multiphase radiomics combined with different machine learning models and compare the diagnostic efficacy between different radiomics models.

Primary liver cancer is one of the most common clinical malignancies, hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, accounting for approximately 90% of cases. A clear diagnosis of HCC is important for the individualized treatment of patients with HCC. However, more sophisticated diagnostic modalities need to be explored.

This retrospective study included 211 patients with liver lesions: 97 HCC and 124 non-hepatocellular carcinoma (non-HCC) who underwent CT and MRI. Imaging data were used to obtain imaging features of lesions and radiomics regions of interest (ROI). The extracted imaging features were combined to construct different radiomics models. The clinical data and imaging features were then combined with radiomics features to construct the combined models. Support Vector Machine (SVM), K-nearest Neighbor (KNN), RandomForest (RF), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Multilayer Perceptron (MLP) six machine learning models were used for training. Five-fold cross-validation was used to train the models, and ROC curves were used to analyze the diagnostic efficacy of each model and calculate the accuracy rate. Model training and efficacy test were performed as before.

Statistical analysis showed that some clinical data (gender and concomitant cirrhosis) and imaging features (presence of envelope, marked enhancement in the arterial phase, rapid contouring in the portal phase, uniform density/signal and concomitant steatosis) were statistical differences (P < 0.001). The results of machine learning models showed that KNN had the best diagnostic efficacy. The results of the combined model showed that SVM had the best diagnostic efficacy, indicating that the combined model (accuracy 0.824) had better diagnostic efficacy than the radiomics-only model.

Our results demonstrate that the radiomic features of CT and MRI combined with machine learning models enable differential diagnosis of HCC and non-HCC (malignant, benign). The diagnostic model with dual radiomic had better diagnostic efficacy. The combined model was superior to the radiomic model alone.

Liver malignancies, particularly hepatocellular carcinoma and metastasis, stand as prominent contributors to cancer mortality. Much of the data from abdominal computed tomography images remain underused by radiologists. This study explores the application of machine learning in differentiating tumor tissue from healthy liver tissue using radiomics features. Preoperative contrast-enhanced images of 94 patients were used. A total of 1686 features classified as first-order, second-order, higher-order, and shape statistics were extracted from the regions of interest of each patient's imaging data. Then, the variance threshold, the selection of statistically significant variables using the Student's t-test, and lasso regression were used for feature selection. Six classifiers were used to identify tumor and non-tumor liver tissue, including random forest, support vector machines, naive Bayes, adaptive boosting, extreme gradient boosting, and logistic regression. Grid search was used as a hyperparameter tuning technique, and a 10-fold cross-validation procedure was applied. The area under the receiver operating curve (AUROC) assessed the performance. The AUROC scores varied from 0.5929 to 0.9268, with naive Bayes achieving the best score. The radiomics features extracted were classified with a good score, and the radiomics signature enabled a prognostic biomarker for hepatic tumor screening.

To identify factors of incomplete treatment after segmental transarterial radioembolization (TARE) for treatment-naive and solitary hepatocellular carcinoma (HCC).

A total of 75 consecutive patients (age, 68.5 years [SD ± 8.0]; 25/75 [33.3%] women) with treatment-naive, solitary HCC underwent segmental or subsegmental TARE with glass microspheres (tumor size, 3.8 cm [SD ± 2.2]; administered dose, 222.6 Gy [SD ± 123.9]) at a single institution from November 2015 to June 2022. Radiologic response and progression-free survival (PFS) were assessed as per modified Response Evaluation Criteria in Solid Tumors.

Complete treatment was achieved in 48 of 75 (64.0%) patients (mean follow-up, 33.2 months [SD ± 27.4]). Patients with incomplete treatment (27/75, 36%) presented with larger tumor size (5.0 [SD ± 2.5] vs 3.1 [SD ± 1.6] cm; P = .0001), with more tumors located in the watershed zone (81.5% vs 41.7%; P = .001). These patients were less likely to be bridged to transplant or resection (22.2% vs 52.1%; P = .015). Watershed tumors demonstrated worse target tumor PFS (median PFS, 19 months vs not reached; P = .0104) and overall PFS (9.1 months vs not reached; P = .0077). Watershed location was associated with worse PFS among tumors >3 cm in size (8.4 months vs not reached; P = .035) but not in tumors ≤3 cm in size (52.2 months vs not reached; P = .915).

Tumor size and watershed location were associated with incomplete treatment after segmental TARE for HCC. Watershed tumors were associated with worse PFS, particularly tumors larger than 3 cm. These tumors may require careful treatment planning and repeated treatments to ensure a durable response.