A prospective cohort study of SARS-CoV-2 infection-induced seroconversion and disease incidence in German healthcare workers before and during the rollout of COVID-19 vaccines.

We assessed the seroepidemiology of SARS-CoV-2 infection and the incidence of coronavirus disease 2019 (COVID-19) before and during the rollout of COVID-19 vaccines, in a prospective observational cohort study on healthcare workers (HCWs) in a large tertiary hospital in Mainz, Germany. Antibody status was assessed during six visits between September 2020 and February 2022. Self-reported symptoms were collected using a smartphone application; symptomatic HCWs were tested using real-time polymerase chain reaction (RT-PCR) assays for SARS-CoV-2. Rates of virologically confirmed and severe COVID-19 were estimated using the U.S. Food and Drug Administration (FDA) and Coalition for Epidemic Preparedness Innovations (CEPI) case definitions, respectively, and were contrasted to background community transmission and circulating SARS-CoV-2 variants. A total of 3665 HCWs were enrolled (mean follow-up time: 18 months); 97 met the FDA definition of virologically confirmed COVID-19 (incidence rate (IR) 2.3/1000 person-months (PMs), one severe case). Most cases reported ≥2 symptoms, commonly, cough and anosmia or ageusia. Overall, 263 individuals seroconverted (IR 6.6/1000 PMs-2.9 times the estimated IR of COVID-19), indicating many cases were missed, either due to asymptomatic infections or to an atypical presentation of symptoms. A triphasic trend in anti-SARS-CoV-2 seroprevalence and seroconversion was observed, with an initial increase following the rollout of COVID-19 vaccines, a two-fold decline six months later, and finally a six-fold increase by the end of the study when Omicron was the dominant circulating variant. Despite the increase in infection rates at the end of the study due to the circulation of the Omicron variant, the infection and disease rates observed were lower than the published estimates in HCWs and rates in the general local population. Preferential vaccination of HCWs and the strict monitoring program for SARS-CoV-2 infection are the most likely reasons for the successful control of COVID-19 in this high-risk population.

Effects of intermittent fasting on quality of life tolerance of chemotherapy in patients with gynecological cancers: study protocol of a randomized-controlled multi-center trial.

Fatigue is a very common side effect during intravenous chemotherapy. Unfortunately, only few effective therapeutic options are available, mostly based on daily activity. In our pilot trial we were able to demonstrate that intermittent fasting can reduce fatigue in healthy people, thus we aimed to assess the effects of the fasting dietary on quality of life during chemotherapy in patients with gynecological cancer, especially on the domain of fatigue. The IFAST trial is designed as a prospective, randomized-controlled, multi-center trial. Participation will be offered to women with gynecological cancers (breast cancer, ovarian cancer including peritoneal and fallopian tube cancers, endometrial cancer and cervical cancer) who are planned to receive intravenous chemotherapy for at least three months. Eligible patients will be randomized 1:1, stratified by tumor type and study center. Primary endpoint is the difference in mean change in fatigue, assessed with the Functional Assessment of Chronic Illness Therapy-Fatigue Scale (FACIT- FS©). Exploratory secondary endpoints will include general Quality of Life impairment, tolerance of chemotherapy, immunological changes, peripheral cell damage in blood cells, as well as tumor response to chemotherapy. There is new evidence that prolonged fasting periods of 46-96 hours during chemotherapy can positively influence the quality of life during chemotherapy. However, these fasting regiments are not feasible for many patients. Intermittent fasting could be a feasible (manageable) option for many patients to actively improve their quality of life and tolerance to chemotherapy and possibly even enhance the effectiveness of chemotherapy. Trial Registration: https://drks.de, identifier DRKS00031429.

Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance.

Background Automation bias (the propensity for humans to favor suggestions from automated decision-making systems) is a known source of error in human-machine interactions, but its implications regarding artificial intelligence (AI)-aided mammography reading are unknown. Purpose To determine how automation bias can affect inexperienced, moderately experienced, and very experienced radiologists when reading mammograms with the aid of an artificial intelligence (AI) system. Materials and Methods In this prospective experiment, 27 radiologists read 50 mammograms and provided their Breast Imaging Reporting and Data System (BI-RADS) assessment assisted by a purported AI system. Mammograms were obtained between January 2017 and December 2019 and were presented in two randomized sets. The first was a training set of 10 mammograms, with the correct BI-RADS category suggested by the AI system. The second was a set of 40 mammograms in which an incorrect BI-RADS category was suggested for 12 mammograms. Reader performance, degree of bias in BI-RADS scoring, perceived accuracy of the AI system, and reader confidence in their own BI-RADS ratings were assessed using analysis of variance (ANOVA) and repeated-measures ANOVA followed by post hoc tests and Kruskal-Wallis tests followed by the Dunn post hoc test. Results The percentage of correctly rated mammograms by inexperienced (mean, 79.7% ± 11.7 [SD] vs 19.8% ± 14.0; P < .001; r = 0.93), moderately experienced (mean, 81.3% ± 10.1 vs 24.8% ± 11.6; P < .001; r = 0.96), and very experienced (mean, 82.3% ± 4.2 vs 45.5% ± 9.1; P = .003; r = 0.97) radiologists was significantly impacted by the correctness of the AI prediction of BI-RADS category. Inexperienced radiologists were significantly more likely to follow the suggestions of the purported AI when it incorrectly suggested a higher BI-RADS category than the actual ground truth compared with both moderately (mean degree of bias, 4.0 ± 1.8 vs 2.4 ± 1.5; P = .044; r = 0.46) and very (mean degree of bias, 4.0 ± 1.8 vs 1.2 ± 0.8; P = .009; r = 0.65) experienced readers. Conclusion The results show that inexperienced, moderately experienced, and very experienced radiologists reading mammograms are prone to automation bias when being supported by an AI-based system. This and other effects of human and machine interaction must be considered to ensure safe deployment and accurate diagnostic performance when combining human readers and AI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Baltzer in this issue.

Low bone mineral density is a prognostic factor for elderly patients with HCC undergoing TACE: results from a multicenter study.

OBJECTIVES: Low bone mineral density (BMD) was recently identified as a novel risk factor for patients with hepatocellular carcinoma (HCC). In this multicenter study, we aimed to validate the role of BMD as a prognostic factor for patients with HCC undergoing transarterial chemoembolization (TACE). METHODS: This retrospective multicenter trial included 908 treatment-naïve patients with HCC who were undergoing TACE as a first-line treatment, at six tertiary care centers, between 2010 and 2020. BMD was assessed by measuring the mean Hounsfield units (HUs) in the midvertebral core of the 11th thoracic vertebra, on contrast-enhanced computer tomography performed before treatment. We assessed the influence of BMD on median overall survival (OS) and performed multivariate analysis including established estimates for survival. RESULTS: The median BMD was 145 HU (IQR, 115-175 HU). Patients with a high BMD (≥ 114 HU) had a median OS of 22.2 months, while patients with a low BMD (< 114 HU) had a lower median OS of only 16.2 months (p < .001). Besides albumin, bilirubin, tumor number, and tumor diameter, BMD remained an independent prognostic factor in multivariate analysis. CONCLUSIONS: BMD is an independent predictive factor for survival in elderly patients with HCC undergoing TACE. The integration of BMD into novel scoring systems could potentially improve survival prediction and clinical decision-making. KEY POINTS: • Bone mineral density can be easily assessed in routinely acquired pre-interventional computed tomography scans. • Bone mineral density is an independent predictive factor for survival in elderly patients with HCC undergoing TACE. • Thus, bone mineral density is a novel imaging biomarker for prognosis prediction in elderly patients with HCC undergoing TACE.

Radiomics-Based Prediction of Future Portal Vein Tumor Infiltration in Patients with HCC-A Proof-of-Concept Study.

Portal vein infiltration (PVI) is a typical complication of HCC. Once diagnosed, it leads to classification as BCLC C with an enormous impact on patient management, as systemic therapies are henceforth recommended. Our aim was to investigate whether radiomics analysis using imaging at initial diagnosis can predict the occurrence of PVI in the course of disease. Between 2008 and 2018, we retrospectively identified 44 patients with HCC and an in-house, multiphase CT scan at initial diagnosis who presented without CT-detectable PVI but developed it in the course of disease. Accounting for size and number of lesions, growth type, arterial enhancement pattern, Child-Pugh stage, AFP levels, and subsequent therapy, we matched 44 patients with HCC who did not develop PVI to those developing PVI in the course of disease (follow-up ended December 2021). After segmentation of the tumor at initial diagnosis and texture analysis, we used LASSO regression to find radiomics features suitable for PVI detection in this matched set. Using an 80:20 split between training and holdout validation dataset, 17 radiomics features remained in the fitted model. Applying the model to the holdout validation dataset, sensitivity to detect occurrence of PVI was 0.78 and specificity was 0.78. Radiomics feature extraction had the ability to detect aggressive HCC morphology likely to result in future PVI. An additional radiomics evaluation at initial diagnosis might be a useful tool to identify patients with HCC at risk for PVI during follow-up benefiting from a closer surveillance.

Fully automated AI-based splenic segmentation for predicting survival and estimating the risk of hepatic decompensation in TACE patients with HCC.

OBJECTIVES: Splenic volume (SV) was proposed as a relevant prognostic factor for patients with hepatocellular carcinoma (HCC). We trained a deep-learning algorithm to fully automatically assess SV based on computed tomography (CT) scans. Then, we investigated SV as a prognostic factor for patients with HCC undergoing transarterial chemoembolization (TACE). METHODS: This retrospective study included 327 treatment-naïve patients with HCC undergoing initial TACE at our tertiary care center between 2010 and 2020. A convolutional neural network was trained and validated on the first 100 consecutive cases for spleen segmentation. Then, we used the algorithm to evaluate SV in all 327 patients. Subsequently, we evaluated correlations between SV and survival as well as the risk of hepatic decompensation during TACE. RESULTS: The algorithm showed Sørensen Dice Scores of 0.96 during both training and validation. In the remaining 227 patients assessed with the algorithm, spleen segmentation was visually approved in 223 patients (98.2%) and failed in four patients (1.8%), which required manual re-assessments. Mean SV was 551 ml. Survival was significantly lower in patients with high SV (10.9 months), compared to low SV (22.0 months, p = 0.001). In contrast, overall survival was not significantly predicted by axial and craniocaudal spleen diameter. Furthermore, patients with a hepatic decompensation after TACE had significantly higher SV (p < 0.001). CONCLUSION: Automated SV assessments showed superior survival predictions in patients with HCC undergoing TACE compared to two-dimensional spleen size estimates and identified patients at risk of hepatic decompensation. Thus, SV could serve as an automatically available, currently underappreciated imaging biomarker. KEY POINTS: • Splenic volume is a relevant prognostic factor for prediction of survival in patients with HCC undergoing TACE, and should be preferred over two-dimensional surrogates for splenic size. • Besides overall survival, progression-free survival and hepatic decompensation were significantly associated with splenic volume, making splenic volume a currently underappreciated prognostic factor prior to TACE. • Splenic volume can be fully automatically assessed using deep-learning methods; thus, it is a promising imaging biomarker easily integrable into daily radiological routine.

Reliability of extracellular contrast versus gadoxetic acid in assessing small liver lesions using liver imaging reporting and data system v.2018 and European association for the study of the liver criteria.

BACKGROUND & AIMS: The diagnostic accuracy of Liver Imaging Reporting and Data System (LI-RADS) v.2018 and European Association for the Study of the Liver (EASL) criteria for the diagnosis of HCC have been widely evaluated, but their reliability should be investigated. We aimed to assess and compare the reliability of LI-RADS v.2018 and EASL criteria for the diagnosis of HCC using MRI with extracellular contrast agents (ECAs) and gadoxetic acid (GA) and determine the effect of ancillary features on LI-RADS reliability. APPROACH & RESULTS: Ten readers reviewed MRI studies of 92 focal liver lesions measuring <3 cm acquired with ECAs and GA <1 month apart from two prospective trials, assessing EASL criteria, LI-RADS major and ancillary features, and LI-RADS categorization with and without including ancillary features. Inter-reader agreement for definite HCC diagnosis was substantial and similar for the two contrasts for both EASL and LI-RADS criteria. For ECA-MRI and GA-MRI, respectively, inter-reader agreement was k = 0.72 (95% CI, 0.63-0.81) and k = 0.72 (95% CI, 0.63-0.80); for nonrim hyperenhancement, k = 0.63 (95% CI, 0.54-0.72) and k = 0.57 (95% CI, 0.48-0.66); and for nonperipheral washout, k = 0.49 (95% CI, 0.40-0.59) and k = 0.48 (95% CI, 0.37-0.58) for enhancing capsule. The inter-reader agreement for LI-RADS after applying ancillary features remained in the same range of agreement. CONCLUSIONS: Agreement for definite HCC was substantial and similar for both scoring systems and the two contrast agents in small focal liver lesions. Agreement for LI-RADS categorization was lower for both contrast agents, and including LI-RADS ancillary features did not improve agreement.

Quantitative washout in patients with hepatocellular carcinoma undergoing TACE: an imaging biomarker for predicting prognosis?

BACKGROUND: The delayed percentage attenuation ratio (DPAR) was recently identified as a novel predictor of an early complete response in patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE). In this study, we aimed to validate the role of DPAR as a predictive biomarker for short-, mid-, and long-term outcomes after TACE. METHODS: We retrospectively reviewed laboratory and imaging data for 103 treatment-naïve patients undergoing initial TACE treatment at our tertiary care center between January 2016 and November 2020. DPAR and other washin and washout indices were quantified in the triphasic computed tomography performed before the initial TACE. The correlation of DPAR and radiologic response was investigated. Furthermore, the influence of DPAR on the 6-, 12-, 18-, and 24-month survival rates and the median overall survival (OS) was compared to other established washout indices and estimates of tumor burden and remnant liver function. RESULTS: The DPAR was significantly of the target lesions (TLs) with objective response to TACE after the initial TACE session was significantly higher compared to patients with stable disease (SD) or progressive disease (PD) (125 (IQR 118-134) vs 110 (IQR 103-116), p < 0.001). Furthermore, the DPAR was significantly higher in patients who survived the first 6 months after TACE (122 vs. 115, p = 0.04). In addition, the number of patients with a DPAR > 120 was significantly higher in this group (n = 38 vs. n = 8; p = 0.03). However, no significant differences were observed in the 12-, 18-, and 24-month survival rates after the initial TACE. Regarding the median OS, no significant difference was observed for patients with a high DPAR compared to those with a low DPAR (18.7 months vs. 12.7 months, p = 0.260). CONCLUSIONS: Our results confirm DPAR as the most relevant washout index for predicting the short-term outcome of patients with HCC undergoing TACE. However, DPAR and the other washout indices were not predictive of mid- and long-term outcomes.

Commercial AI solutions in detecting COVID-19 pneumonia in chest CT: not yet ready for clinical implementation?

OBJECTIVES: In response to the COVID-19 pandemic, many researchers have developed artificial intelligence (AI) tools to differentiate COVID-19 pneumonia from other conditions in chest CT. However, in many cases, performance has not been clinically validated. The aim of this study was to evaluate the performance of commercial AI solutions in differentiating COVID-19 pneumonia from other lung conditions. METHODS: Four commercial AI solutions were evaluated on a dual-center clinical dataset consisting of 500 CT studies; COVID-19 pneumonia was microbiologically proven in 50 of these. Sensitivity, specificity, positive and negative predictive values, and AUC were calculated. In a subgroup analysis, the performance of the AI solutions in differentiating COVID-19 pneumonia from other conditions was evaluated in CT studies with ground-glass opacities (GGOs). RESULTS: Sensitivity and specificity ranges were 62-96% and 31-80%, respectively. Negative and positive predictive values ranged between 82-99% and 19-25%, respectively. AUC was in the range 0.54-0.79. In CT studies with GGO, sensitivity remained unchanged. However, specificity was lower, and ranged between 15 and 53%. AUC for studies with GGO was in the range 0.54-0.69. CONCLUSIONS: This study highlights the variable specificity and low positive predictive value of AI solutions in diagnosing COVID-19 pneumonia in chest CT. However, one solution yielded acceptable values for sensitivity. Thus, with further improvement, commercial AI solutions currently under development have the potential to be integrated as alert tools in clinical routine workflow. Randomized trials are needed to assess the true benefits and also potential harms of the use of AI in image analysis. KEY POINTS: • Commercial AI solutions achieved a sensitivity and specificity ranging from 62 to 96% and from 31 to 80%, respectively, in identifying patients suspicious for COVID-19 in a clinical dataset. • Sensitivity remained within the same range, while specificity was even lower in subgroup analysis of CT studies with ground-glass opacities, and interrater agreement between the commercial AI solutions was minimal to nonexistent. • Thus, commercial AI solutions have the potential to be integrated as alert tools for the detection of patients with lung changes suspicious for COVID-19 pneumonia in a clinical routine workflow, if further improvement is made.

Prevalence and clinical significance of clinically evident portal hypertension in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

BACKGROUND: Clinically evident portal hypertension (CEPH) was previously identified as a prognostic factor for patients with hepatocellular carcinoma (HCC). However, little is known about the prognostic influence of CEPH on the long-term outcome of patients with HCC undergoing transarterial chemoembolization (TACE), particularly in Western populations. OBJECTIVES: This study investigated the prevalence and prognostic influence of CEPH in a Western population of patients with HCC undergoing TACE. METHODS: This retrospective study included 349 treatment-naïve patients that received initial TACE treatment at our tertiary care center between January 2010 and November 2020. CEPH was defined as a combination of ascites, esophageal/gastric varices, splenomegaly and a low platelet count. We assessed the influence of CEPH and its defining factors on median overall survival (OS) in HCC patients. We compared the effects of CEPH to those of well-known prognostic factors. RESULTS: Of the 349 patients included, 304 (87.1%) patients had liver cirrhosis. CEPH was present in 241 (69.1%) patients. The median OS times were 10.6 months for patients with CEPH and 17.1 months for patients without CEPH (log rank p = 0.036). Median OS without a present surrogate was 17.1 months, while patients with one respectively more than two present CEPH surrogates had a median OS of 10.8 and 9.4 months (log rank p = 0.053). In multivariate analysis, CEPH was no significant risk factor for OS (p = 0.190). Of the CEPH-defining factors, only ascites reached significance in a univariate analysis. CONCLUSION: CEPH was present in more than two thirds of the patients with HCC undergoing TACE in our cohort of Western patients. Patients with CEPH had a significantly impaired survival in univariate analysis. However, no significance was reached in multivariate analysis. Thus, when TACE treatment is deemed oncologically reasonable, patients should not be excluded from TACE treatment due to the presence of surrogates of portal hypertension alone.

Longitudinal Study of the Signal Strength in two Serologic Assays for Detection of SARS-CoV-2 Specific Antibodies.

BACKGROUND: In the course of the current SARS-CoV-2 pandemic, antibody assays provide an important means for guidance of public health efforts. Thus, characterization of the course of antibody signals on different widely used assays is needed. METHODS: We selected 25 PCR-confirmed SARS-CoV-2 cases among 3,273 healthcare workers and measured the course of the antibody signal using the Abbott Architect SARS-CoV-2 IgG assay and the Roche Elecsys® Anti-SARS-CoV-2 immunoassay. The signal strength was then modelled using linear mixed models adjusted for age. RESULTS: Since first sampling, the assay signal decreased per day in the Abbott assay (standardized slope (ß) = -0.46, 95% CI = -0.54 to -0.39). In contrast, an increase in the signal was ascertained by the Roche immunoassay per day (ß = 0.25, 95% CI = 0.09 to 0.41). CONCLUSIONS: Roche Elecsys® Anti-SARS-CoV-2 immunoassay may exhibit greater sensitivity in detecting SARS-CoV-2-specific antibodies in individuals in late stages of postinfection.

Immunonutritive Scoring for Patients with Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization: Evaluation of the CALLY Index.

The novel CRP-albumin-lymphocyte (CALLY) index is an improved immunonutritive scoring system, based on serum C-reactive protein (CRP), serum albumin, and the lymphocyte count. It has shown promise as a prognostic index for patients with hepatocellular carcinoma (HCC) undergoing resections. This study evaluated the prognostic ability of the CALLY index for patients with HCC undergoing transarterial chemoembolization (TACE). We retrospectively identified 280 treatment-naïve patients with HCC that underwent an initial TACE at our institution, between 2010 and 2020. We compared the CALLY index to established risk factors in univariate and multivariate regression analyses for associations with median overall survival (OS). A low CALLY score was associated with low median OS (low vs. high CALLY: 9.0 vs. 24.0 months, p < 0.001). In the multivariate analysis, the CALLY index remained an independent prognostic predictor (p = 0.008). Furthermore, all factors of the CALLY index reached significance in univariate and in-depth multivariate analyses. However, the concordance index (C-index) of the CALLY index (0.60) was similar to the C-indices of established immunonutritive and inflammation scoring systems (range: 0.54 to 0.63). In conclusion, the CALLY index showed promise as a stratification tool for patients with HCC undergoing TACE. Notably, the CALLY index was not superior to other immunonutritive and inflammation scoring systems in predicting the median OS. Thus, future studies should re-evaluate the mathematical calculation of the index, particularly the contributions of individual parameters.

Online teaching in radiology as a pilot model for modernizing medical education: results of an international study in cooperation with the ESR.

BACKGROUND: Due to the outbreak of the coronavirus disease 2019 (COVID-19), it proved necessary to rapidly change medical education from on-site to online teaching. Thus, medical educators were forced to rethink the purpose of teaching and the best form of transmission of knowledge. In cooperation with the European Society of Radiology (ESR), we investigated the attitudes of radiologists in Europe and North America toward innovative online teaching concepts. METHODS: In total, 224 radiologists from 31 different countries participated in our cross-sectional, web-based survey study. On a 7-point Likert scale, participants had to answer 27 questions about the online teaching situation before/during the pandemic, technical and social aspects of online teaching and the future role of online teaching in radiology. RESULTS: An overwhelming majority stated that radiology is particularly well-suited for online teaching (91%), that online teaching should play a more prominent role after the pandemic (73%) and that lecturers should be familiar with online teaching techniques (89%). Difficulties include a higher workload in preparing online courses (59%), issues with motivating students to follow online courses (56%) and the risk of social isolation (71%). Before the pandemic, only 12% of teaching was provided online; for the future, our participants deemed a proportion of approximately 50% online teaching appropriate. CONCLUSION: Our participants are open-minded about online teaching in radiology. As the best way of transferring knowledge in medical education is still unclear, online teaching offers potential for innovation in radiology education. To support online teaching development, a structured, framework-based "online curriculum" should be established.

How COVID-19 kick-started online learning in medical education-The DigiMed study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic led to far-reaching restrictions of social and professional life, affecting societies all over the world. To contain the virus, medical schools had to restructure their curriculum by switching to online learning. However, only few medical schools had implemented such novel learning concepts. We aimed to evaluate students' attitudes to online learning to provide a broad scientific basis to guide future development of medical education. METHODS: Overall, 3286 medical students from 12 different countries participated in this cross-sectional, web-based study investigating various aspects of online learning in medical education. On a 7-point Likert scale, participants rated the online learning situation during the pandemic at their medical schools, technical and social aspects, and the current and future role of online learning in medical education. RESULTS: The majority of medical schools managed the rapid switch to online learning (78%) and most students were satisfied with the quantity (67%) and quality (62%) of the courses. Online learning provided greater flexibility (84%) and led to unchanged or even higher attendance of courses (70%). Possible downsides included motivational problems (42%), insufficient possibilities for interaction with fellow students (67%) and thus the risk of social isolation (64%). The vast majority felt comfortable using the software solutions (80%). Most were convinced that medical education lags behind current capabilities regarding online learning (78%) and estimated the proportion of online learning before the pandemic at only 14%. In order to improve the current curriculum, they wish for a more balanced ratio with at least 40% of online teaching compared to on-site teaching. CONCLUSION: This study demonstrates the positive attitude of medical students towards online learning. Furthermore, it reveals a considerable discrepancy between what students demand and what the curriculum offers. Thus, the COVID-19 pandemic might be the long-awaited catalyst for a new "online era" in medical education.

Refining Prognosis in Chemoembolization for Hepatocellular Carcinoma: Immunonutrition and Liver Function.

A combination of albumin-bilirubin (ALBI) grading and the Prognostic Nutritional Index (PNI) was identified recently as a highly predictive tool for patients with hepatocellular carcinoma (HCC) undergoing tumor ablation. The present study evaluated this combination in patients undergoing transarterial chemoembolization (TACE). Between 2010 and 2020, 280 treatment-naïve patients were retrospectively identified. The influence of ALBI grade, PNI and the novel ALBI-PNI on the median overall survival (OS) was assessed. In the next step, the prognostic ability of the combined approach was compared to established scoring systems. Both ALBI grade 2-3 and a low PNI were highly predictive for median OS (ALBI grade 1-3: 39.0 vs. 16.3 vs. 5.4 months, p < 0.001; high vs. low PNI: 21.4 vs. 7.5, p < 0.001). The combination of both resulted in a median OS of 39.0, 20.1, 10.3, and 5.4 months (p < 0.001). With a Concordance Index (C-Index) of 0.69, ALBI-PNI outperformed each individual score (ALBI 0.65, PNI 0.64) and was also better than BCLC, HAP, mHAP-II, and the Six-and-Twelve score (C-Indices 0.66, 0.60, 0.59, and 0.55). Thus, the easy-to-calculate ALBI-PNI may be a promising stratification tool for patients with HCC undergoing TACE, reflecting both immunonutritive status and liver function.

Immunonutritive Scoring in Patients With Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization: Prognostic Nutritional Index or Controlling Nutritional Status Score?

OBJECTIVES: The Prognostic Nutritional Index (PNI) and Controlling Nutritional Status (CONUT) score are immunonutritive scoring systems with proven predictive ability in various cancer entities, including hepatocellular carcinoma (HCC). We performed the first evaluation of the CONUT score for patients undergoing transarterial chemoembolization (TACE) and compared CONUT and PNI in the ability to predict median overall survival (OS). METHODS: Between 2010 and 2020, we retrospectively identified 237 treatment-naïve patients with HCC who underwent initial TACE at our institution. Both scores include the albumin level and total lymphocyte count. The CONUT additionally includes the cholesterol level. Both scores were compared in univariate and multivariate regression analyses taking into account established risk factors. In a second step, a subgroup analysis was performed on BCLC stage B patients, for whom TACE is the recommended first-line treatment. RESULTS: A high CONUT score and low PNI were associated with impaired median OS (8.7 vs. 22.3 months, p<0.001 and 6.8 vs. 20.1 months, p<0.001, respectively). In multivariate analysis, only the PNI remained an independent prognostic predictor (p=0.003), whereas the CONUT score lost its predictive ability (p=0.201). In the subgroup of recommended TACE candidates, both CONUT and PNI were able to stratify patients according to their median OS (6.6 vs. 17.9 months, p<0.001 and 10.3 vs. 22.0 months, p<0.001, respectively). Again, in the multivariate analysis, only the PNI remained an independent prognostic factor (p=0.012). CONCLUSION: Both scores were able to stratify patients according to their median OS, but only the PNI remained an independent prognostic factor. Therefore, PNI should be preferred when evaluating the nutritional status of patients undergoing TACE.

Survival Prediction in Intrahepatic Cholangiocarcinoma: A Proof of Concept Study Using Artificial Intelligence for Risk Assessment.

Several scoring systems have been devised to objectively predict survival for patients with intrahepatic cholangiocellular carcinoma (ICC) and support treatment stratification, but they have failed external validation. The aim of the present study was to improve prognostication using an artificial intelligence-based approach. We retrospectively identified 417 patients with ICC who were referred to our tertiary care center between 1997 and 2018. Of these, 293 met the inclusion criteria. Established risk factors served as input nodes for an artificial neural network (ANN). We compared the performance of the trained model to the most widely used conventional scoring system, the Fudan score. Predicting 1-year survival, the ANN reached an area under the ROC curve (AUC) of 0.89 for the training set and 0.80 for the validation set. The AUC of the Fudan score was significantly lower in the validation set (0.77, p < 0.001). In the training set, the Fudan score yielded a lower AUC (0.74) without reaching significance (p = 0.24). Thus, ANNs incorporating a multitude of known risk factors can outperform conventional risk scores, which typically consist of a limited number of parameters. In the future, such artificial intelligence-based approaches have the potential to improve treatment stratification when models trained on large multicenter data are openly available.

Hepatic vein tumor thrombosis in patients with hepatocellular carcinoma: Prevalence and clinical significance.

BACKGROUND: There is strong evidence that portal vein tumor thrombosis (PVTT) is associated with poor survival in patients with hepatocellular carcinoma (HCC). However, data regarding the clinical significance of hepatic vein tumor thrombosis (HVTT) is rare, particularly in Western patients. OBJECTIVE: To determine the HVTT prevalence in a Western patient population and its impact on survival. METHODS: We included 1310 patients with HCC treated in our tertiary referral center between January 2005 and December 2016. HVTT and PVTT were diagnosed with contrast-enhanced cross-sectional imaging. Overall survival (OS) was calculated starting from the initial HCC diagnosis, and in a second step, starting from the first appearance of vascular invasion. RESULTS: We observed macrovascular invasion (MVI) in 519 patients who suffered from either isolated HVTT (n = 40), isolated PVTT (n = 352), or both combined (HVTT + PVTT) (n = 127). Calculated from the initial HCC diagnosis, the median OS for patients with isolated HVTT was significantly shorter than that of patients without MVI (13.3 vs. 32.5 months, p < 0.001). Calculated from the first appearance of MVI, the median OS was similar among patients with isolated HVTT (6.5 months), isolated PVTT (5 months), and HVTT + PVTT (5 months). Multivariate analysis confirmed HVTT as an independent risk factor for poor survival. CONCLUSIONS: HVTT may be more common than typically reported. In most patients, it was accompanied by PVTT. Isolated HVTT occurred less frequently and later than isolated PVTT; however, once developed, it had the same deleterious impact on survival. Therefore, patients with HVTT should be classified as advanced stage of HCC.

The impact of portal vein tumor thrombosis on survival in patients with hepatocellular carcinoma treated with different therapies: A cohort study.

BACKGROUND: Portal vein tumor thrombosis (PVTT) is a frequent complication of hepatocellular carcinoma (HCC), which leads to classification as advanced stage disease (regardless of the degree of PVTT) according to the Barcelona Clinic Liver Cancer Classification. For such patients, systemic therapy is the standard of care. However, in clinical reality, many patients with PVTT undergo different treatments, such as resection, transarterial chemoembolization (TACE), selective internal radiation therapy (SIRT), or best supportive care (BSC). Here we examined whether patients benefited from such alternative therapies, according to the extent of PVTT. METHODS: This analysis included therapy-naïve patients with HCC and PVTT treated between January 2005 and December 2016. PVTT was classified according to the Liver Cancer study group of Japan as follows: Vp1 = segmental PV invasion; Vp2 = right anterior or posterior PV; Vp3 = right or left PV; Vp4 = main trunk. Overall survival (OS) was analyzed for each treatment subgroup considering the extent of PVTT. We performed Cox regression analysis with adjustment for possible confounders. To further attenuate selection bias, we applied propensity score weighting using the inverse probability of treatment weights. RESULTS: A total of 278 treatment-naïve patients with HCC and PVTT were included for analysis. The median observed OS in months for each treatment modality (resection, TACE/SIRT, sorafenib, BSC, respectively) was 32.4, 8.1, N/A, and 1.7 for Vp1; 10.7, 6.9, 5.5, and 1.2 for Vp2; 6.6, 7.5, 2.9, and 0.6 for Vp3; and 8.0, 3.6, 5.3, and 0.7 for Vp4. Thus, the median OS in the resection group in case of segmental PVTT (Vp1) was significantly longer compared to any other treatment group (all p values <0.01). CONCLUSIONS: Treatment strategy for HCC with PVTT should not be limited to systemic therapy in general. The extent of PVTT should be considered when deciding on treatment alternatives. In patients with segmental PVTT (Vp1), resection should be evaluated.

Current Strategies to Identify Patients That Will Benefit from TACE Treatment and Future Directions a Practical Step-by-Step Guide.

Treatment of hepatocellular carcinoma (HCC) depends on the stage of disease. In the Western Hemisphere, the Barcelona Clinic Liver Cancer classification (BCLC) is the preferred staging system. Approximately one-third of patients initially present with intermediate-stage disease. For these patients, transarterial chemoembolization (TACE) is the treatment of choice. However, the intermediate-stage comprises a heterogeneous subgroup of patients with considerable differences in tumor burden and liver function. In addition, differences in individual factors that are not captured by the BCLC framework, such as the tumor growth pattern, degree of hypervascularity, and vascular supply, complicate further evaluation of these patients. Due to these differences, not all patients benefit equally from TACE. Several tools and scoring systems have been devised to provide decision-making support. All of these have shown promising initial results but failed external evaluation and have not been translated to the clinic. Nevertheless, criteria for objectifying treatment decisions in daily clinical practice are needed in all stages of disease. Therefore, this review provides a concise practical step-by-step guide on current strategies for patient selection and decision-making, with a focus on TACE, to critically evaluate the existing decision-support tools and provide a summary of the latest updates in the field.