Clinical impact of ampulla of Vater cancer subtype classification based on immunohistochemical staining.

BACKGROUND: The histological subtype is an important prognostic factor for ampulla of Vater (AoV) cancer. This study proposes a classification system for the histological subtyping of AoV cancer based on immunohistochemical (IHC) staining and its prognostic significance. METHODS: Seventy-five AoV cancers were analyzed for cytokeratin 7 (CK7), CK20, and causal-type homeobox transcription factor 2 (CDX2) expression by IHC staining. We differentiated the subtypes (INT, intestinal; PB, pancreatobiliary; MIX, mixed; NOS, not otherwise specified) into classification I: CK7/CK20, classification II: CK7/CK20 or CDX2, classification III: CK7/CDX2 and examined their associations with clinicopathological factors. RESULTS: Classifications I, II, and III subtypes were INT (7, 10, and 10 cases), PB (43, 37, and 38 cases), MIX (13, 19, and 18 cases), and NOS (12, 9, and 9 cases). Significant differences in disease-free survival among the subtypes were observed in classifications II and III using CDX2; the PB and NOS subtype exhibited shorter survival time compared with INT subtype. In classification III, an association was revealed between advanced T/N stage, poor differentiation, lymphovascular invasion (LVI), the PB and NOS subtypes, and recurrence risk. In classification III, the subtypes differed significantly in T/N stage and LVI. Patients with the PB subtype had advanced T and N stages and a higher incidence of LVI. CONCLUSIONS: Classification using CDX2 revealed subtypes with distinct prognostic significance. Combining CK7 and CDX2 or adding CDX2 to CK7/CK20 is useful for distinguishing subtypes, predicting disease outcomes, and impacting the clinical management of patients with AoV cancer.

Laparoscopic gastric wedge resection and spleen-preserving distal pancreatectomy performed on a 6-cm gastric desmoid tumour with pancreatic invasion.

Desmoid tumours are rare tumours originating from fibroblasts, and are characterised by local infiltration and no metastasis. When complete resection is possible, surgical resection is considered a first-line treatment. In the case of large desmoid tumours, it is mainly performed by laparotomy, not laparoscopy. We report a case of a 43-year-old female patient presenting with a hypodense mass of approximately 5 cm in the posterior wall of the gastric antrum on computed tomography. There was no history of familial adenomatous polyposis, trauma or abdominal surgery. The patient underwent laparoscopic gastric wedge resection and spleen-preserving distal pancreatectomy without peri-operative complications. Pathological analysis revealed a desmoid tumour, which originated from the stomach and invaded the pancreas. Despite the large size and the locally infiltrative characteristics of these tumours, laparoscopic surgery can be an optimal treatment option due to its advantages.

Sarcopenia is associated with cardiovascular risk in men with COPD, independent of adiposity.

BACKGROUND: Sarcopenia is a well-established risk factor for atherosclerotic cardiovascular disease (ASCVD), but its relationship with chronic obstructive pulmonary disease (COPD) has not been fully determined. This study is aimed to investigate the association between sarcopenia and risk for ASCVD in patients with COPD, independent of central obesity and fat mass. METHODS: Data regarding 704 men with COPD (mean age: 63.4 years) were extracted from the 2008 to 2011 Korean National Health and Nutrition Examination Surveys. Sarcopenia index and fat mass were assessed using dual-energy X-ray absorptiometry. Sarcopenia was defined according to the presence of sarcopenia index values < 1 standard deviation from the cutoff (0.774) among the study participants. ASCVD risk was evaluated using American College of Cardiology/American Heart Association guidelines. High probability of ASCVD was defined as ASCVD risk > 20%. RESULTS: The quartile-stratified sarcopenia index was negatively associated with ASCVD risk (P < 0.001). ASCVD risk and prevalence of high ASCVD risk were significantly greater in sarcopenic participants than in non-sarcopenic participants, regardless of central obesity and fat mass (all P < 0.001). Multivariate regression analyses demonstrated an independent association between sarcopenia and ASCVD risk (estimated ± standard error = 3.63 ± 0.77%, P < 0.001) and high ASCVD risk (odds ratio [OR] = 2.32, 95% confidence interval [CI] 1.05-5.15, P = 0.039). Furthermore, sarcopenia was an independent factor for high ASCVD risk in participants with moderate to very severe airflow limitation (OR = 2.97, 95% CI 1.06-8.36, P < 0.001). CONCLUSIONS: Sarcopenia was significantly associated with an increased risk for ASCVD in men with COPD, independent of central obesity and fat mass. High ASCVD risk was significantly associated with sarcopenia, particularly in participants with moderate to very severe airflow limitation.

Machine learning-based survival rate prediction of Korean hepatocellular carcinoma patients using multi-center data.

AIM: To predict survival time of Korean hepatocellular carcinoma (HCC) patients using multi-center data as a foundation for the development of a predictive artificial intelligence model according to treatment methods based on machine learning. METHODS: Data of patients who underwent treatment for HCC from 2008 to 2015 was provided by Korean Liver Cancer Study Group and Korea Central Cancer Registry. A total of 10,742 patients with HCC were divided into two groups, with Group I (2920 patients) confirmed on biopsy and Group II (5562 patients) diagnosed as HCC according to HCC diagnostic criteria as outlined in Korean Liver Cancer Association guidelines. The data were modeled according to features of patient clinical characteristics. Features effective in predicting survival rate were analyzed retrospectively. Various machine learning methods were used. RESULTS: Target was overall survival time, which divided into approximately 60 months (= /< 60 m, > 60 m). Target distribution in Group I (total 514 samples) was 28.8%: (148 samples) less than 60 months, 71.2% (366 samples) greater than 60 months, and in Group II (total 757 samples) was 66.6% (504 samples) less than 60 months, 33.4% (253 samples) greater than 60 months. Using NG Boost method, its accuracy was 83%, precision 84%, sensitivity 95%, and F1 score 89% for more than 60 months survival time in Group I with surgical resection. Moreover, its accuracy was 79%, precision 82%, sensitivity 87%, and F1 score 84% for less than 60 months survival time in Group II with TACE. The feature importance with gain criterion indicated that pathology, portal vein invasion, surgery, metastasis, and needle biopsy features could be explained as important factors for prediction in case of biopsy (Group I). CONCLUSION: By developing a predictive model using machine learning algorithms to predict prognosis of HCC patients, it is possible to project optimized treatment by case according to liver function and tumor status.

Next Generation Proteomic Pipeline for Chromosome-Based Proteomic Research Using NeXtProt and GENCODE Databases.

Human Proteome Project aims to map all human proteins including missing proteins as well as proteoforms with post translational modifications, alternative splicing variants (ASVs), and single amino acid variants (SAAVs). neXtProt and Ensemble databases are usually used to provide curated information on human coding genes. However, to find these proteoforms, we (Chr #11 team) first introduce a streamlined pipeline using customized and concatenated neXtProt and GENCODE originated from Ensemble, with controlled false discovery rate (FDR). Because of large sized databases used in this pipeline, we found more stringent FDR filtering (0.1% at the peptide level and 1% at the protein level) to claim novel findings, such as GENCODE ASVs and missing proteins, from human hippocampus data set (MSV000081385) and ProteomeXchange (PXD007166). Using our next generation proteomic pipeline (nextPP) with neXtProt and GENCODE databases, two missing proteins such as activity-regulated cytoskeleton-associated protein (ARC, Chr 8) and glutamate receptor ionotropic, kainite 5 (GRIK5, Chr 19) were additionally identified with two or more unique peptides from human brain tissues. Additionally, by applying the pipeline to human brain related data sets such as cortex (PXD000067 and PXD000561), spinal cord, and fetal brain (PXD000561), seven GENCODE ASVs such as ACTN4-012 (Chr.19), DPYSL2-005 (Chr.8), MPRIP-003 (Chr.17), NCAM1-013 (Chr.11), EPB41L1-017 (Chr.20), AGAP1-004 (Chr.2), and CPNE5-005 (Chr.6) were identified from two or more data sets. The identified peptides of GENCODE ASVs were mapped onto novel exon insertions, alternative translations at 5'-untranslated region, or novel protein coding sequence. Applying the pipeline to male reproductive organ related data sets, 52 GENCODE ASVs were identified from two testis (PXD000561 and PXD002179) and a spermatozoa (PXD003947) data sets. Four out of 52 GENCODE ASVs such as RAB11FIP5-008 (Chr. 2), RP13-347D8.7-001 (Chr. X), PRDX4-002 (Chr. X), and RP11-666A8.13-001 (Chr. 17) were identified in all of the three samples.

Clinical Impacts of Donor Types of Living vs. Deceased Donors: Predictors of One-Year Mortality in Patients with Liver Transplantation.

Transplantation studies about the clinical differences according to the type of donors are mostly conducted in western countries with rare reports from Asians. The aims of this study were to evaluate the clinical impacts of the type of donor, and the predictors of 1-year mortality in patients who underwent liver transplantation (LT). This study was performed for liver transplant recipients between May 2010 and December 2014 at the Pusan National University Yangsan Hospital. A total of 185 recipients who underwent LT were analyzed. Of the 185 recipients, 109 (58.9%) belonged to the living donor liver transplantation (LDLT) group. The median age was 52.4 years. LDLT recipients had lower model for end-stage liver disease (MELD) score compared with better liver function than deceased donor liver transplantation (DDLT) recipients (mean ± standard deviation [SD], 12.5 ± 8.3 vs. 24.9 ± 11.7, respectively; P < 0.001), and had more advanced hepatocellular carcinoma (HCC) (62.4% vs. 21.1%, respectively; P = 0.001). In complications and clinical outcomes, LDLT recipients showed shorter stay in intensive care unit (ICU) (mean ± SD, 10.8 ± 8.8 vs. 23.0 ± 13.8 days, respectively, P < 0.001), ventilator care days, and post-operative admission days, and lower 1-year mortality (11% vs. 27.6%, respectively, P = 0.004). Bleeding and infectious complications were less in LDLT recipients. Recipients with DDLT (P = 0.004) showed higher mortality in univariate analysis, and multi-logistic regression analysis found higher MELD score and higher pre-operative serum brain natriuretic peptide (BNP) were associated with 1-year mortality. This study may guide improved management before and after LT from donor selection to post-operation follow up.

Key players in neurodegenerative disorders in focus-New insights into the proteomic profile of Alzheimer's disease, schizophrenia, ALS, and multiple sclerosis-24th HUPO BPP Workshop: September 29, 2015, Vancouver, Canada.

The HUPO Brain Proteome Project (HUPO BPP) held its 24th workshop in Vancouver, Canada, September 29, 2015. The focus of the autumn workshop was on new insights into the proteomic profile of Alzheimer's disease, schizophrenia, ALS and multiple sclerosis.

Integrated Proteomic Pipeline Using Multiple Search Engines for a Proteogenomic Study with a Controlled Protein False Discovery Rate.

In the Chromosome-Centric Human Proteome Project (C-HPP), false-positive identification by peptide spectrum matches (PSMs) after database searches is a major issue for proteogenomic studies using liquid-chromatography and mass-spectrometry-based large proteomic profiling. Here we developed a simple strategy for protein identification, with a controlled false discovery rate (FDR) at the protein level, using an integrated proteomic pipeline (IPP) that consists of four engrailed steps as follows. First, using three different search engines, SEQUEST, MASCOT, and MS-GF+, individual proteomic searches were performed against the neXtProt database. Second, the search results from the PSMs were combined using statistical evaluation tools including DTASelect and Percolator. Third, the peptide search scores were converted into E-scores normalized using an in-house program. Last, ProteinInferencer was used to filter the proteins containing two or more peptides with a controlled FDR of 1.0% at the protein level. Finally, we compared the performance of the IPP to a conventional proteomic pipeline (CPP) for protein identification using a controlled FDR of <1% at the protein level. Using the IPP, a total of 5756 proteins (vs 4453 using the CPP) including 477 alternative splicing variants (vs 182 using the CPP) were identified from human hippocampal tissue. In addition, a total of 10 missing proteins (vs 7 using the CPP) were identified with two or more unique peptides, and their tryptic peptides were validated using MS/MS spectral pattern from a repository database or their corresponding synthetic peptides. This study shows that the IPP effectively improved the identification of proteins, including alternative splicing variants and missing proteins, in human hippocampal tissues for the C-HPP. All RAW files used in this study were deposited in ProteomeXchange (PXD000395).

Proteogenomics of the human hippocampus: The road ahead.

The hippocampus is one of the most essential components of the human brain and plays an important role in learning and memory. The hippocampus has drawn great attention from scientists and clinicians due to its clinical importance in diseases such as Alzheimer's disease (AD), non-AD dementia, and epilepsy. Understanding the function of the hippocampus and related disease mechanisms requires comprehensive knowledge of the orchestration of the genome, epigenome, transcriptome, proteome, and post-translational modifications (PTMs) of proteins. The past decade has seen remarkable advances in the high-throughput sequencing techniques that are collectively called next generation sequencing (NGS). NGS enables the precise analysis of gene expression profiles in cells and tissues, allowing powerful and more feasible integration of expression data from the gene level to the protein level, even allowing "-omic" level assessment of PTMs. In addition, improved bioinformatics algorithms coupled with NGS technology are finally opening a new era for scientists to discover previously unidentified and elusive proteins. In the present review, we will focus mainly on the proteomics of the human hippocampus with an emphasis on the integrated analysis of genomics, epigenomics, transcriptomics, and proteomics. Finally, we will discuss our perspectives on the potential and future of proteomics in the field of hippocampal biology. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

A Long Journey from Childhood to Senility: The 23rd HUPO BPP Workshop: 16-17 April 2015, São Paulo, Brazil.

The HUPO Brain Proteome Project (HUPO BPP) held its 23rd workshop in São Paulo, Brazil, April 16-17, 2015. The focus of the spring workshop was on strategies and predictive therapies concerning neurodegenerative diseases.

Amyloid-beta-activated human microglial cells through ER-resident proteins.

Microglial activation in the central nervous system is a key event in the neuroinflammation that accompanies neurodegenerative diseases such as Alzheimer's disease (AD). Among cytokines involved in microglial activation, amyloid ß (Aß) peptide is known to be a key molecule in the induction of diverse inflammatory products, which may lead to chronic inflammation in AD. However, proteomic studies of microglia in AD are limited due to lack of proper cell or animal model systems. In this study, we performed a proteomic analysis of Aß-stimulated human microglial cells using SILAC (stable isotope labeling with amino acids in cell culture) combined with LC-MS/MS. Results showed that 60 proteins increased or decreased their abundance by 1.5 fold or greater. Among these, ER-resident proteins such as SERPINH1, PDIA6, PDIA3, and PPIB were revealed to be key molecular biomarkers of human microglial activation by validation of the proteomic results by immunostaining, PCR, ELISA, and Western blot. Taken together, our data suggest that ER proteins play an essential role in human microglial activation by Aß and may be important molecular therapeutic targets for treatment of AD.

Chromosome-Based Proteomic Study for Identifying Novel Protein Variants from Human Hippocampal Tissue Using Customized neXtProt and GENCODE Databases.

The goal of the Chromosome-Centric Human Proteome Project (C-HPP) is to fully provide proteomic information from each human chromosome, including novel proteoforms, such as novel protein-coding variants expressed from noncoding genomic regions, alternative splicing variants (ASVs), and single amino acid variants (SAAVs). In the 144 LC/MS/MS raw files from human hippocampal tissues of control, epilepsy, and Alzheimer's disease, we identified the novel proteoforms with a workflow including integrated proteomic pipeline using three different search engines, MASCOT, SEQUEST, and MS-GF+. With a <1% false discovery rate (FDR) at the protein level, the 11 detected peptides mapped to four translated long noncoding RNA variants against the customized databases of GENCODE lncRNA, which also mapped to coding-proteins at different chromosomal sites. We also identified four novel ASVs against the customized databases of GENCODE transcript. The target peptides from the variants were validated by tandem MS fragmentation pattern from their corresponding synthetic peptides. Additionally, a total of 128 SAAVs paired with their wild-type peptides were identified with FDR <1% at the peptide level using a customized database from neXtProt including nonsynonymous single nucleotide polymorphism (nsSNP) information. Among these results, several novel variants related in neuro-degenerative disease were identified using the workflow that could be applicable to C-HPP studies. All raw files used in this study were deposited in ProteomeXchange (PXD000395).

Cyanobacterial phytochrome2 regulates the heterotrophic metabolism and has a function in the heat and high-light stress response.

Cyanobacteria combine the photosynthetic and respiratory electron transport in one membrane system, the thylakoid membrane. This feature requires an elaborate regulation mechanism to maintain a certain redox status of the electron transport chain, hence allowing proper photosynthetic and respiratory energy metabolism. In this context, metabolic adaptations, as seen in the light-to-dark and dark-to-light transitions, are particularly challenging. However, the molecular basis of the underlying regulatory mechanisms is not well-understood. Here, we describe a function of cyanobacterial phytochrome2 (Cph2), a phytochrome of the cyanobacterial model system Synechocystis sp. PCC 6803, in regulation of the primary energy metabolism. When cells are shifted from photoautotrophic planktonic growth to light-activated heterotrophic growth and biofilm initiation, knockout of Cph2 results in impaired growth, a decrease in the activity of Glc-6-P dehydrogenase, a decrease of the transcript abundance/activity of cytochrome-c-oxidase, and slower phycocyanin degradation. Measurements of the plastoquinone reduction confirm an impaired heterotrophic metabolism in the cph2 knockout. When cells that were adapted to heterotrophic metabolism are shifted back to light conditions, the knockout of Cph2 results in an altered photosystem II chlorophyll fluorescence induction curve, which is indicative of an impaired redox balance of the electron transport chain. Moreover, Cph2 plays a role in the heat and high-light stress response, particularly under photomixotrophic conditions. Our results show a function of Cph2 in the adaptation of the primary energy metabolism to changing trophic conditions. The physiological role of Cph2 in biofilm formation is discussed.

Enrichment of single neurons and defined brain regions from human brain tissue samples for subsequent proteome analysis.

Brain function in normal aging and neurological diseases has long been a subject of interest. With current technology, it is possible to go beyond descriptive analyses to characterize brain cell populations at the molecular level. However, the brain comprises over 100 billion highly specialized cells, and it is a challenge to discriminate different cell groups for analyses. Isolating intact neurons is not feasible with traditional methods, such as tissue homogenization techniques. The advent of laser microdissection techniques promises to overcome previous limitations in the isolation of specific cells. Here, we provide a detailed protocol for isolating and analyzing neurons from postmortem human brain tissue samples. We describe a workflow for successfully freezing, sectioning and staining tissue for laser microdissection. This protocol was validated by mass spectrometric analysis. Isolated neurons can also be employed for western blotting or PCR. This protocol will enable further examinations of brain cell-specific molecular pathways and aid in elucidating distinct brain functions.

Frontiers in neurodegeneration--new insights and prospects--20th HUPO BPP Workshop: 15 September 2013, Yokohama, Japan.

The HUPO Brain Proteome Project (HUPO BPP) held its 20th workshop in Yokohama, Japan, September 15, 2013. The focus of the autumn workshop was on new insights and prospects of neurodegenerative diseases.

Human temporal lobe epilepsy analyses by tissue proteomics.

Although there are many types of epilepsy, temporal lobe epilepsy (TLE) is probably in humans the most common and most often studied. TLE represents 40% of the total epilepsy form of the disease and is difficult to treat. Despite a wealth of descriptive data obtained from the disease history of patients, the EEG recording, imaging techniques, and histological studies, the epileptogenic process remains poorly understood. However, it is unlikely that a single factor or a single mechanism can cause many changes associated with this neuropathological phenomenon. MALDI mass spectrometry imaging (MSI) coupled to protein identification, because of its ability to study a wide range of molecules, appears to be suitable for the preparation of molecular profiles in TLE. Seven neuropeptides have been have been identified in Dental gyrus regions of the hippocampus in relation with TLE pathology. Shot-gun studies taking into account gender influence have been performed. Tissue microextraction from control (10) toward 10 TLE patients have been analyzed after trypsin digestion followed by separation on nanoLC coupled to LTQ orbitrap. From the shot-gun analyses, results confirmed the presence of specific neuropeptides precursors and receptors in TLE patients as well as proteins involved in axons regeneration including neurotrophins, ECM proteins, cell surface proteins, membrane proteins, G-proteins, cytoskeleton proteins and tumor suppressors. Among the tumor suppressors identified, the Leucine-rich glioma inactivated 1 (LGI1) protein was found. LGI1 gene recently been demonstrated being implicated in heritability of TLE. We have also demonstrate the presence a complete profile of tumor suppressors in TLE patients, 7 have been identified. Refining this analysis taken into account the gender influence in both control and in TLE reflected the presence of specific proteins between male and female and thus mechanisms in pathology development could be completely different.

Large-scale analysis of posttranslational modifications in the hippocampus of patients with Alzheimer's disease using pI shift and label-free quantification without enrichment.

Posttranslational modifications modulate protein function in cells. Global analysis of multiple posttranslational modifications can provide insight into physiology and disease, but presents formidable challenges. In the present study, we used a technique that does not require target enrichment to analyze alterations in the phosphorylation and ubiquitination of proteins from patients with Alzheimer's disease (AD). Guided by our previous findings, we applied three strategies to further our understanding of the dysregulation of posttranslationally modified proteins. We first identified phosphorylation sites by determining peptide pI shifts using OFFGEL. Second, using tandem mass spectrometry, we determined the ubiquitination status of the proteins using an assay for a trypsin digestion remnant of ubiquitination (Gly-Gly). Third, for large-scale discovery, we quantified the global differences in protein expression. Of the proteins expressed in AD tissue at levels of 2.0 or greater compared with controls, 60 were phosphorylated and 56 were ubiquitinated. Of the proteins expressed at levels of 0.5 or lower compared with controls, 81 were phosphorylated and 56 were ubiquitinated. Approximately 98 % of the phosphopeptides exhibited a pI shift. We identified 112 new phosphorylation sites (51.38 %), and 92 new ubiquitination sites (96.84 %). Taken together, our findings suggest that analysis of the alterations in posttranslationally modified proteins may contribute to understanding the pathogenesis of AD and other diseases.

Clinical course of pancreas cancer diagnosed after spleen-preserving distal pancreatectomy with borderline lesion: two case reports.

Distal pancreatectomy with splenectomy is considered the standard operation for pancreas tail and body cancer. However, splenectomy may be option for benign or low-grade malignant tumors including mucinous cystadenoma and intraductal papillary mucinous neoplasm. If spleen-preserving distal pancreatectomy (SPDP) with borderline lesion is performed and pancreas cancer is diagnosed on postoperative pathologic finding, if it is R0 resection, the necessity of additional splenectomy remains questionable. The authors would like report two clinical cases diagnosed as pancreatic cancer on postoperative pathology after SPDP and under observation without additional splenectomy.

Prognostic Impact of Mucin Expression in Curatively Resected Ampulla of Vater Cancer.

Introduction: Mucins play a pivotal role in epithelial carcinogenesis; however, their role remains elusive in ampulla of Vater (AoV) cancer, regardless of histological subtype. Therefore, we investigated the clinical significance of MUC1, MUC2, MUC5AC, and MUC6 expression in AoV cancer. Methods: Using samples from 68 patients with AoV cancer, we performed immunohistochemical staining for MUC1, MUC2, MUC5AC, and MUC6 using a tissue microarray. Subsequently, we analyzed their expression patterns in relation to clinicopathological parameters and patient outcomes. Results: Of the patients, 98.5% exhibited positive expression for MUC1, while MUC2, MUC5AC, and MUC6 were expressed in 44.1%, 47.1%, and 41.2% of the patients, respectively. Correlation analyses between mucin expression and clinicopathological factors revealed no significant associations, except between MUC5AC expression and N stage. Univariate analysis demonstrated significant associations between MUC5AC expression and overall survival (OS). Multivariate analysis further confirmed that MUC5AC expression was a significant predictor of OS, along with the N stage. However, MUC5AC expression was not meaningfully associated with recurrence-free survival (RFS). The patients positive for MUC5AC expression had a considerably shorter OS than those with negative expression. Conclusions: Our study provides insights into the clinical impact of mucins on AoV cancer, regardless of the histological subtype. Although MUC1 expression is universal, MUC5AC expression is a significant prognostic indicator that correlates with lymph node metastasis and poor OS. These results emphasize the possible utility of MUC5AC as a biomarker for extensive lymph node dissection and the prognostic evaluation of patients with AoV cancer.

Deep learning-based image reconstruction for the multi-arterial phase images: improvement of the image quality to assess the small hypervascular hepatic tumor on gadoxetic acid-enhanced liver MRI.

PURPOSE: To evaluated the impact of a deep learning (DL)-based image reconstruction on multi-arterial-phase magnetic resonance imaging (MA-MRI) for small hypervascular hepatic masses in patients who underwent gadoxetic acid-enhanced liver MRI. METHODS: We retrospectively enrolled 55 adult patients (aged ≥ 18 years) with small hepatic hypervascular mass (≤ 3 cm) between December 2022 and February 2023. All patients underwent MA-MRI, subsequently reconstructed with a DL-based application. Qualitative assessment with Linkert scale including motion artifact (MA), liver edge (LE), hepatic vessel clarity (HVC) and image quality (IQ) was performed. Quantitative image analysis including signal to noise ratio (SNR), contrast to noise ratio (CNR) and noise was performed. RESULTS: On both arterial phases (APs), all qualitative parameters were significantly improved after DL-based image reconstruction. (LE on 1st AP, 1.22 vs 1.61; LE on 2nd AP, 1.21 vs 1.65; HVC on 1st AP, 1.24 vs 1.39; HVC on 2nd AP, 1.24 vs 1.44; IQ on 1st AP, 1.17 vs 1.45; IQ on 2nd AP, 1.17 vs 1.47, all p values < 0.05). The SNR, CNR and noise were significantly improved after DL-based image reconstruction. (SNR on AP1, 279.08 vs 176.14; SNR on AP2, 334.34 vs 199.24; CNR on AP1, 106.09 vs 64.14; CNR on AP2, 129.66 vs 73.73; noise on AP1, 1.51 vs 2.33; noise on AP2, 1.45 vs 2.28, all p values < 0.05). CONCLUSIONS: Gadoxetic acid-enhanced MA-MRI with DL-based image reconstruction improved the qualitative and quantitative parameters. Despite the short acquisition time, high-quality MA-MRI is now achievable.