Primary sclerosing cholangitis (PSC) is a chronic inflammatory disease of the bile ducts that can lead to biliary cancer and end-stage liver disease. PSC is associated with inflammatory bowel disease and an altered gut microbiota. However, the molecular mechanisms underlying gut-liver interactions in PSC remain poorly characterized. Here we show that the gut microbiota-derived metabolite imidazole propionate (ImP) is a disease driver in PSC. Individuals with PSC have higher circulating ImP levels than individuals with related conditions, and high ImP levels predict reduced survival in PSC. Cholangiocytes exposed to ImP show activated mammalian target of rapamycin complex 1 (mTORC1) signalling and secrete pro-inflammatory and pro-fibrogenic factors. Chronic administration of ImP to mice induces liver inflammation and fibrosis through a p38-dependent mechanism, upstream of mTORC1. We propose that chronic exposure to ImP induces cholangiocyte injury, which alone or in concert with other factors causes clinical worsening of PSC. Therefore, targeting ImP production or signalling may represent therapeutic avenues in PSC.

Background : Liver vessel identification is crucial for clinical disease assessment and treatment planning, especially concerning local treatment of liver tumors. As artificial intelligence (AI) develops in radiology, opportunities arise to craft models adept at hepatic venous vessel segmentation, opening possibilities for creating patient-specific models of the liver anatomy quickly, despite the diverse features of CT images encountered in clinical settings. Objective: This research evaluates the performance of AI models combined with various pre-processing filters for liver vessel segmentation, emphasizing clinically relevant results. A novel evaluation method was introduced to offer more anatomically accurate assessments, moving beyond traditional metrics like the Dice score. Methods: Using open-source and proprietary datasets, we implemented residual UNet and Dense UNet in combination with smoothness and vesselness filters. We used a clinical evaluation approach focused on major and minor liver vessels, thereby underscoring the precision of AI outcomes. Results: The Dense UNet model with a specific pre-processing filter produced an average Dice score of 0.8144 in our internal dataset. For the public test dataset, the score was 0.7859. Both scores were higher than those not using pre-processing filters, 0.8052 and 0.7765. Clinical assessments showed 85% of AI predictions accurately identified all wanted vessel structures, though segmentation beyond the vessel borders did occur in half the predictions. Conclusion: This study highlights the effectiveness of AI in liver vessel segmentation, with the Dense UNet model combined with pre-processing filters showing high Dice scores and clinical accuracy.

Among those with primary sclerosing cholangitis (PSC), perihilar cholangiocarcinoma (pCCA) is often diagnosed at a late stage and is a leading source of mortality. Detection of pCCA in PSC when curative action can be taken is challenging. Our aim was to create a deep learning model that analyzed MRI to detect early-stage pCCA and compare its diagnostic performance with expert radiologists. We conducted a multicenter, international, retrospective cohort study involving adults with large duct PSC who underwent contrast-enhanced MRI. Senior abdominal radiologists reviewed the images. All patients with pCCA had early-stage cancer and were registered for liver transplantation. We trained a 3D DenseNet-121 model, a form of deep learning, using MRI images and assessed its performance in a separate test cohort. The study included 398 patients (training cohort n=150; test cohort n=248). pCCA was present in 230 individuals (training cohort n=64; test cohort n=166). In the test cohort, the respective performances of the model compared to the radiologists were: sensitivity 87.9% versus 50.0%, p <0.001; specificity 84.1% versus 100.0%, p <0.001; area under receiving operating curve 86.0% versus 75.0%, p <0.001. Even when a mass was absent, the model had a higher sensitivity for pCCA than radiologists (91.6% vs. 50.6%, p <0.001) and maintained good specificity (84.1%). The 3D DenseNet-121 MRI model effectively detects early-stage pCCA in PSC patients. Compared to expert radiologists, the model missed fewer cases of cancer.

BACKGROUND:The incidence of colorectal cancer is increasing, and the liver remains the predominant site for metastases. Whereas liver resection is the standard treatment for colorectal liver metastases (CRLMs), liver transplantation (LT) has re-emerged as a viable option for selected patients. The aim of this study was to investigate whether tumour volume and changes in tumour volume during chemotherapy before transplantation predict overall survival. METHODS:Patients who underwent LT for CRLMs between November 2006 and August 2020 were included. Tumour volumes were measured via manual segmentation on computerized tomography scans at baseline, at maximum tumour volume, and immediately before LT. Response to chemotherapy was assessed using Response Evaluation Criteria in Solid Tumours (RECIST) criteria, and the heterogeneous response was noted to investigate whether this subgroup performs differently. Receiver operating characteristic analysis was conducted to determine a tumour volume cut-off value for predicting overall survival. Overall survival between groups was compared using Kaplan-Meier curves and log rank test. RESULTS:Fifty-nine patients who underwent LT for CRLMs were analysed retrospectively. Receiver operating characteristic analysis revealed that final tumour volume at time of LT was a strong predictor of 5-year overall survival (area under the curve= 0.789), with a 35 mL cut-off providing optimal clinical discrimination. Patients achieving a final tumour volume below 35 mL, either consistently or via downstaging, demonstrated significantly improved survival compared with those with persistently high tumour volumes (4.54 years versus 2.17 years; P < 0.001). Heterogeneous responses to chemotherapy were associated with poorer prognosis with no patients surviving beyond 2.16 years (P < 0.001). CONCLUSION:Dynamic tumour assessment, particularly measuring tumour volume to below 35 mL, is an important prognostic marker in LT for CRLMs.

Background and aims: We previously demonstrated that people with primary sclerosing cholangitis (PSC) had reduced gut microbial capacity to produce active vitamin B6 (pyridoxal 5'-phosphate [PLP]), which corresponded to lower circulating PLP levels and poor outcomes. Here, we define the extent and biochemical and clinical impact of vitamin B6 deficiency in people with PSC from several centers before and after liver transplantation (LT). Methods: We used targeted liquid chromatography-tandem mass spectrometry to measure B6 vitamers and B6-related metabolic changes in blood from geographically distinct cross-sectional cohorts totaling 373 people with PSC and 100 healthy controls to expand on our earlier findings. Furthermore, we included a longitudinal PSC cohort (n =158) sampled prior to and serially after LT, and cohorts of people with inflammatory bowel disease (IBD) without PSC (n = 51) or with primary biliary cholangitis (PBC) (n = 100), as disease controls. We used Cox regression to measure the added value of PLP to predict outcomes before and after LT. Results: In different cohorts, 17-38% of people with PSC had PLP levels below the biochemical definition of a vitamin B6 deficiency. The deficiency was more pronounced in PSC than in IBD without PSC and PBC. Reduced PLP was associated with dysregulation of PLP-dependent pathways. The low B6 status largely persisted after LT. Low PLP independently predicted reduced LT-free survival in both non-transplanted people with PSC and in transplant recipients with recurrent disease. Conclusions: Low vitamin B6 status with associated metabolic dysregulation is a persistent feature of PSC. PLP was a strong prognostic biomarker for LT-free survival both in PSC and recurrent disease. Our findings suggest that vitamin B6 deficiency modifies the disease and provides a rationale for assessing B6 status and testing supplementation.(c) 2023 The Author(s). Published by Elsevier B.V. on behalf of European Association for the Study of the Liver. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Background Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease that can lead to cirrhosis and hepatic decompensation. However, predicting future outcomes in patients with PSC is challenging. Our aim was to extract magnetic resonance imaging (MRI) features that predict the development of hepatic decompensation by applying algebraic topology-based machine learning (ML). Methods We conducted a retrospective multicenter study among adults with large duct PSC who underwent MRI. A topological data analysis-inspired nonlinear framework was used to predict the risk of hepatic decompensation, which was motivated by algebraic topology theory-based ML. The topological representations (persistence images) were employed as input for classification to predict who developed early hepatic decompensation within one year after their baseline MRI. Results We reviewed 590 patients; 298 were excluded due to poor image quality or inadequate liver coverage, leaving 292 potentially eligible subjects, of which 169 subjects were included in the study. We trained our model using contrast-enhanced delayed phase T1-weighted images on a single center derivation cohort consisting of 54 patients (hepatic decompensation, n = 21; no hepatic decompensation, n = 33) and a multicenter independent validation cohort of 115 individuals (hepatic decompensation, n = 31; no hepatic decompensation, n = 84). When our model was applied in the independent validation cohort, it remained predictive of early hepatic decompensation (area under the receiver operating characteristic curve = 0.84). Conclusions Algebraic topology-based ML is a methodological approach that can predict outcomes in patients with PSC and has the potential for application in other chronic liver diseases.

Tumor heterogeneity is a primary cause of treatment failure. However, changes in drug sensitivity over time are not well mapped in cancer. Patient-derived organoids (PDOs) may predict clinical drug responses ex vivo and offer an opportunity to evaluate novel treatment strategies in a personalized fashion. Here we have evaluated spatio-temporal functional and molecular dynamics of five PDO models established after hepatic re-resections and neoadjuvant combination chemotherapies in a patient with microsatellite stable and KRAS mutated metastatic rectal cancer. Histopathological differentiation phenotypes of the PDOs corresponded with the liver metastases, and ex vivo drug sensitivities generally reflected clinical responses and selection pressure, assessed in comparison to a reference data set of PDOs from metastatic colorectal cancers. PDOs from the initial versus the two recurrent metastatic settings showed heterogeneous cell morphologies, protein marker expression, and drug sensitivities. Exploratory analyses of a drug screen library of 33 investigational anticancer agents showed the strongest ex vivo sensitivity to the SMAC mimetic LCL161 in PDOs of recurrent disease compared to those of the initial metastasis. Functional analyses confirmed target inhibition and apoptosis induction in the LCL161 sensitive PDOs from the recurrent metastases. Gene expression analyses indicated an association between LCL161 sensitivity and tumor necrosis factor alpha signaling and RIPK1 gene expression. In conclusion, LCL161 was identified as a possible experimental therapy of a metastatic rectal cancer that relapsed after hepatic resection and standard systemic treatment.

In a blind, dual-center, multi-observer setting, we here identify the pre-treatment radiologic features by Magnetic Resonance Imaging (MRI) associated with subsequent treatment options in patients with glioma. Study included 220 previously untreated adult patients from two institutions (94 + 126 patients) with a histopathologically confirmed diagnosis of glioma after surgery. Using a blind, cross-institutional and randomized setup, four expert neuroradiologists recorded radiologic features, suggested glioma grade and corresponding confidence. The radiologic features were scored using the Visually AcceSAble Rembrandt Images (VASARI) standard. Results were retrospectively compared to patient treatment outcomes. Our findings show that patients receiving a biopsy or a subtotal resection were more likely to have a tumor with pathological MRI-signal (by T2-weighted Fluid-Attenuated Inversion Recovery) crossing the midline (Hazard Ratio; HR = 1.30 [1.21–1.87], P < 0.001), and those receiving a biopsy sampling more often had multifocal lesions (HR = 1.30 [1.16–1.64], P < 0.001). For low-grade gliomas (N = 50), low observer confidence in the radiographic readings was associated with less chance of a total resection ( P = 0.002) and correlated with the use of a more comprehensive adjuvant treatment protocol (Spearman = 0.48, P < 0.001). This study may serve as a guide to the treating physician by identifying the key radiologic determinants most likely to influence the treatment decision-making process.

Objectives: To evaluate magnetic resonance imaging (MRI) findings in vascular malformations by assessing (1) the prevalence of phleboliths and flow voids and (2) dynamic contrast enhancement characteristics in early and delayed contrast phases. Methods: Ninety-eight patients (median age 27 years) were included. MRI analyses were performed by 2 radiologists that were blinded to clinical information. Phleboliths and flow-voids were assessed with T1 and short tau inversion recovery. Artery-lesion enhancement time (ALET) was assessed with time-resolved MRI angiography. Contrast accumulation until 15 minutes postinjection was assessed using subtraction techniques based on volumetric interpolated breath-hold examination. Standard statistical methods were applied. Results: Eighty-nine patients had low-flow malformations and 9 patients had high-flow malformations. Phleboliths were present in 13.5% of low-flow malformations, and 0% of high-flow malformations (P = .60). Flow voids were observed in 16.9% of low-flow malformations and 55.6% of high-flow malformations (P < .05). Median ALET of low-flow malformations was 9.2 seconds and of high-flow malformations (n = 8) was 0.8 seconds (P < .05). Twenty-one low-flow malformations had ALET that overlapped with ALET of high-flow malformations (≤6.3 seconds). Contrast accumulation between preinjection and 2 minutes postinjection was observed in 97.5% of low-flow malformations and 100% of high-flow malformations, whereas contrast accumulation between 2 and 15 minutes postinjection was observed in 92.6% of low-flow malformations and 62.5% of high-flow malformations (P < .05). Conclusion: Our data suggest that phleboliths are infrequent in vascular malformations and that flow voids may be unreliable markers of high-flow malformations. Both high- and low-flow malformations may present with considerable overlap regarding flow dynamics, implying vascular heterogeneity within both malformation types.

Abstract Patients with metastatic colorectal cancer (CRC) have few targeted treatment options compared with other major malignancies, and both over- and undertreatment with cytostatic drugs remain a challenge. Recent studies show that patient-derived organoids (PDOs) can predict clinical responses to systemic therapies in a personalized manner, but tumor heterogeneity may limit the clinical benefit of anticancer therapies, as well as the accuracy of preclinical predictions. PDO lineage establishment from multiple distinct lesions per patient presents a novel opportunity for preclinical investigation of intrapatient pharmacotranscriptomic heterogeneity. From September 2017 until November 2019, we have established a living biobank of 107 PDOs from 53 patients who underwent resection of CRC liver metastases at Oslo University Hospital, Norway, 31 of whom had multiple (2-5) metastases. All PDOs were screened for sensitivity to 40 anticancer agents, including clinically relevant targeted drugs and conventional chemotherapies. Molecular profiling by gene expression and mutation analyses is ongoing and currently completed for 27 PDOs. Recapitulation of known pharmacogenomic/transcriptomic associations was confirmed in PDOs for EGFR inhibition and RAS/BRAFV600E mutation status, as well as TP53-MDM2 inhibition and TP53 mutation status and TP53 transcriptional activity. Antimetabolites such as gemcitabine and methotrexate, or small-molecule inhibitors in late-stage clinical development targeting Aurora A, PLK1, and HSP90, showed strong differential activities, enabling identification of sensitive subgroups. Strong sensitivity to HSP90 inhibition was associated with low protein expression of Heat Shock Transcription Factor 1, which had a homogenous intrapatient intermetastatic expression pattern. Principal component analyses revealed a clear patient-wise separation of PDOs based on both their pharmacologic and transcriptomic profiles separately, indicating only modest intrapatient heterogeneity among distinct metastatic lesions. Accurate prediction of clinical responses to 5-FU and oxaliplatin was shown in PDOs from one patient treated for recurrent liver metastases. Additionally, PDOs from recurrent liver metastases showed an increased sensitivity to off-label drugs compared to PDOs from the first liver resection, supporting therapy repurposing in later lines of treatment. In summary, patient-derived models of CRC liver metastases reveal modest intrapatient pharmacotranscriptomic heterogeneity—an encouraging result for further efforts to develop personalized drug repurposing strategies for this poor-prognosis patient group. Citation Format: Kushtrim Kryeziu, Jarle Bruun, Peter W. Eide, Seyed H. Moosavi, Ina A. Eilertsen, Jonas Langerud, Bård Røsok, Tuva H. Brunsell, Marianne G. Guren, Andreas Abildgaard, Arild Nesbakken, Bjørn Atle Bjørnbeth, Anita Sveen, Ragnhild A. Lothe. Modeling intrapatient pharmacotranscriptomic heterogeneity with organoids derived from colorectal cancer liver metastases [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr A19.

BACKGROUND:The prevalence and clinical implications of genetic heterogeneity in patients with multiple colorectal liver metastases remain largely unknown. In a prospective series of patients undergoing resection of colorectal liver metastases, the aim was to investigate the inter-metastatic and primary-to-metastatic heterogeneity of mutations in KRAS, NRAS, BRAF, and PIK3CA and their prognostic impact. PATIENTS AND METHODS:We analyzed the mutation status among 372 liver metastases and 78 primary tumors from 106 patients by methods used in clinical routine testing, by Sanger sequencing, by next-generation sequencing (NGS), and/or by droplet digital polymerase chain reaction. The 3-year cancer-specific survival (CSS) was analyzed using the Kaplan-Meier method. RESULTS:Although Sanger sequencing indicated inter-metastatic mutation heterogeneity in 14 of 97 patients (14%), almost all cases were refuted by high-sensitive NGS. Also, heterogeneity among metastatic deposits was concluded only for PIK3CA in 2 patients. Similarly, primary-to-metastatic heterogeneity was indicated in 8 of 78 patients (10%) using Sanger sequencing but for only 2 patients after NGS, showing the emergence of 1 KRAS and 1 PIK3CA mutation in the metastatic lesions. KRAS mutations were present in 53 of 106 patients (50%) and were associated with poorer 3-year CSS after liver resection (37% vs. 61% for KRAS wild-type; P = .004). Poor prognostic associations were found also for the combination of KRAS/NRAS/BRAF mutations compared with triple wild-type (P = .002). CONCLUSION:Intra-patient mutation heterogeneity was virtually undetected, both between the primary tumor and the liver metastases and among the metastatic deposits. KRAS mutations separately, and KRAS/NRAS/BRAF mutations combined, were associated with poor patient survival after partial liver resection.

Introduction: Surgery combined with perioperative chemotherapy has become standard of care in patients with resectable colorectal liver metastases. However, poor outcome is expected for a significant subgroup. The clinical implications of inter-metastatic heterogeneity remain largely unknown. In a prospective, population-based series of patients undergoing resection of multiple colorectal liver metastases, the aim was to investigate the prevalence and prognostic impact of heterogeneous response to neoadjuvant chemotherapy. Materials and Methods: Radiological response to treatment was evaluated in a lesion-specific manner in 2-5 metastases per patient. Change of lesion diameter was evaluated and response/progression was classified according to three different size thresholds; 3, 4 and 5 mm. A heterogeneous response was defined as progression and response of different metastases in the same patient. Results: In total, 142 patients with 585 liver metastases were examined with the same radiological method (MRI or CT) before and after neoadjuvant treatment. Heterogeneous response to treatment was seen in 16 patients (11%) using the 3 mm size change threshold, and this group had a 5-year cancer-specific survival of 19% compared to 49% for patients with response in all lesions (p = 0.003). Cut-off values of 4-5 mm were less sensitive for detecting a heterogeneous response, but the survival difference was similar and significant. Conclusion: A subgroup of patients with multiple colorectal liver metastases had heterogeneous radiological response to neoadjuvant chemotherapy and poor prognosis. The evaluation of response pattern is easy to perform, feasible in clinical practice and, if validated, a promising biomarker for treatment decisions. (C) 2019 The Authors. Published by Elsevier Ltd.

President Trump has closed the borders of the United States for all citizens from a selected group of Islamic countries.1Trump DJ Executive order: protecting the nation from foreign terrorist entry into the United States. The White House Office of the Press Secretary.https://www.whitehouse.gov/the-press-office/2017/01/27/executive-order-protecting-nation-foreign-terrorist-entry-united-statesDate: Jan 27, 2017Google Scholar This ban will affect a large number of our colleague surgeons and physicians in their work as clinicians and academics. We view this as unjustified and unacceptable discrimination on the basis of religion, citizenship and culture. Until this ban is lifted, we encourage our colleague hepato-pancreato-biliary and transplant surgeons to consider the ethical implications of participating at meetings and congresses held in the United States. The board of the Norwegian Association of Gastrointestinal and Hepato-pancreato-biliary (HPB) surgeons (NFGK) endorses the content of this letter. We declare no competing interests.

The predictive value of coronary artery calcium (CAC) in heart transplant (HTX) patients is not established. We explored if the absence of CAC on computed tomography (CT) could exclude moderate and severe cardiac allograft vasculopathy [CAV2-3 ; the International Society for Heart and Lung Transplantation (ISHLT) recommended nomenclature] and significant coronary artery stenosis (diameter reduction ≥50%) and predict long-term clinical outcomes. HTX recipients (n = 133) were prospectively included and underwent CT for CAC scoring and invasive coronary angiography (ICA) 7.8 ± 5.0 years after HTX. CAC was detected in 73 (55%) patients. The absence of CAC on CT had a negative predictive value of 97% for ISHLT CAV2-3 and 88% for significant stenosis on ICA. During 7.5 ± 2.6 years of follow-up after CAC CT (n = 127), there were 57 (45%) nonfatal major adverse cardiac events and 23 (18%) deaths or graft losses registered as first events. Patients with CAC had significantly more events (P = 0.011). In an adjusted Cox regression analysis, the presence of CAC was significantly associated with a negative outcome (HR 1.8, 95% CI 1.1-3.0; P = 0.023). The absence of CAC predicted low prevalences of ISHLT CAV2-3 and significant coronary artery stenosis in HTX patients. The presence of CACS was significantly associated with a worse long-term outcome.

Background Cardiac allograft vasculopathy (CAV) is an accelerated form of atherosclerosis unique to heart transplant (HTX) patients. Purpose To investigate the detection of significant coronary artery stenosis and CAV, determinants of image quality, and the radiation dose in coronary computed tomography angiography (CCTA) of HTX patients with 64-slice multidetector CT (64-MDCT). Material and Methods Fifty-two HTX recipients scheduled for invasive coronary angiography (ICA) were prospectively enrolled and underwent CCTA before ICA with intravascular ultrasound (IVUS). Results Interpretable CCTA images were acquired in 570 (95%) coronary artery segments ≥2 mm in diameter. Sensitivity, specificity, and positive and negative predictive values of CCTA for the detection of segments with significant stenosis (lumen reduction ≥50%) on ICA were 100%, 98%, 7.7%, and 100%, respectively. Twelve significant stenoses were located in segments with uninterpretable image quality or vessel diameter <2 mm; only one was eligible for intervention. IVUS detected CAV (maximal intimal thickness ≥0.5 mm) in 33/41 (81%) patients; CCTA and ICA identified CAV (any wall or luminal irregularity) in 18 (44%) and 14 (34%) of these 33 patients, respectively. The mean estimated radiation dose was 19.0 ± 3.4 mSv for CCTA and 5.7 ± 3.3 mSv for ICA ( P < 0.001). Conclusion CCTA with interpretable image quality had a high negative predictive value for ruling out significant stenoses suitable for intervention. The modest detection of CAV by CCTA implied a limited value in identifying subtle CAV. The high estimated radiation dose for 64-MDCT is of concern considering the need for repetitive examinations in the HTX population.

The liver is the most frequent metastatic site in colorectal cancer (CRC), and relevant orthotopic in vivo models are needed to study the efficacy of anticancer drugs in the metastatic setting. A challenge when utilizing such models is monitoring tumor growth during the experiments. In this study, experimental liver metastases were established in nude mice by splenic injection of the CRC cell lines HT29 and HCT116, and the mice were treated with the antiangiogenic drug aflibercept. Tumor growth was monitored using magnetic resonance imaging (MRI) and bioluminescence imaging (BLI). Aflibercept treatment was well tolerated and resulted in increased animal survival in HCT116, but not in HT29, while inhibited tumor growth was observed in both models. Treatment efficacy was monitored with high precision using MRI, while BLI detected small-volume disease with high sensitivity, but was less accurate in end-stage disease. Apparent diffusion coefficient (ADC) values obtained by diffusion weighted MRI (DW-MRI) were highly predictive of treatment response, with increased ADC corresponding well with areas of necrosis observed by histological evaluation of aflibercept-treated xenografts. The results showed that the efficacy of the antiangiogenic drug aflibercept varied between the two models, possibly reflecting unique growth patterns in the liver that may be representative of human disease. Non-invasive imaging, especially MRI and DW-MRI, can be used to effectively monitor tumor growth and treatment response in orthotopic liver metastasis models.