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Solitary fibrous tumor of the liver (SFTL) is an exceptionally rare mesenchymal tumor, with only 117 cases reported in the literature. While most SFTs are benign, some exhibit malignant behavior, including local recurrence and metastasis. This report presents two cases of SFTL with systemic metastases, both involving prior intracranial tumors. The first case, a 52-year-old woman, discovered a liver mass incidentally during a routine physical exam. Subsequent investigations revealed potential bone metastasis, and biopsy confirmed SFT. She received two TACE procedures, anlotinib targeted therapy, and radiotherapy for the iliac bone lesion, resulting in stable disease with reduction in lesion size. The second case, a 46-year-old man, presented with multiple liver, pelvic, and lung lesions following pelvic tumor resection, with pathology confirming SFT. He was treated with long-term anlotinib therapy, CyberKnife for hepatic, lung, and pelvic lesions, and radiofrequency ablation for hepatic lesions. Postoperative recovery was uneventful, with no tumor progression on follow-up. SFTL presents with atypical clinical and imaging features, and diagnosis requires pathological and genetic confirmation. Radical resection is preferred for solitary tumors, while comprehensive treatment, including surgery and long-term follow-up, is essential for cases with recurrence or metastasis. [ABSTRACT FROM AUTHOR]

Liver cancer is one of the leading causes of cancer death in the world, and early diagnosis is important. However, the similarity in shape, texture, and intensity values between the liver, tumors, and other neighboring organs such as the heart, spleen, stomach, and kidneys often complicates visual differentiation. Manual identification of tumors in the liver is time‐consuming, intricate, and susceptible to errors with potential repercussions for patient care. While machine learning–based approaches have emerged for liver organ recognition and segmenting the tumor, they continue to face challenges related to recognition accuracy and the inability to distinguish tumors of varied sizes. To solve the problems, a multiattention network made up of cascaded ResUNet and U‐Net with attention mechanisms was proposed in this study. We investigated liver tumor segmentation with various configurations of U‐Net, ResUNet, U‐Net with attention mechanisms, and ResUNet with attention mechanisms on augmented and nonaugmented data. We used the 3Dircadb dataset for training and validation purposes, and the proposed method was evaluated on dice score, intersection of union (IoU), recall, and precision. The performance metrics achieved with this method on the dataset are as follows: approximately 0.89 for the dice coefficient, 0.90 for IoU, 0.93 for recall, and 0.96 for precision in the case of liver segmentation without data augmentation and 0.92, 0.90, 0.92, and 0.94, respectively, for dice score, IoU, recall, and precision with data augmentation. For tumor segmentation, the metrics include 0.70 for dice coefficient, 0.61 for IoU, 0.91 for recall, and 0.94 for precision when the data were augmented but 0.83 for dice score, 0.78 for IoU, and 0.89 and 0.90, respectively, for recall and precision. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusion Computer‐assisted planning methods have increasingly contributed to preoperative ablation planning; however, these methods cannot automatically obtain the final optimal solution within a short time and are rarely validated in practice, greatly limiting their clinical applicability.We aimed to propose a full‐automatic multi‐stage ablation and needle trajectory planning method for CT‐guided percutaneous liver ablation to attain the final optimal plans under multiple clinical constraints rapidly.Our proposed method integrates the ablation zone planning fulfilling complete tumor coverage and critical structure avoidance while reaching a trade‐off between ablation number and healthy tissue damage, and needle trajectory planning under multiple clinical constraints. Our needle trajectory planning determines feasible skin entry regions based on hard constraints, where the multi‐objective optimization (MOO) considering soft constraints is performed using the Pareto Optimality and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods for the final optimal solution. The performance of our proposed method was evaluated on 30 tumors of various characteristics from 23 patients and clinically validated in five clinical cases.Our proposed method achieved 99.8% treatment zone coverage and 40.5% ablation efficiency without involving critical structures, and completely satisfied multiple clinical constraints in all needle trajectory planning results. The average planning time was 23.6 s for tumors of different sizes. All the plans were considered clinically acceptable by the doctors’ evaluation. Our method achieved complete tumor coverage without complications in clinical case validation.Our proposed planning method can generate a final optimal plan satisfying multiple clinical constraints within a short time, potentially facilitating preoperative planning for hepatic tumor ablation. [ABSTRACT FROM AUTHOR]

Background: Liver cancer is a significant cause of cancer-related mortality worldwide and requires tailored treatment strategies for different types. However, preoperative accurate diagnosis of the type presents a challenge. This study aims to develop an automatic diagnostic model based on multi-phase contrast-enhanced CT (CECT) images to distinguish between hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and normal individuals. Methods: We designed a Hierarchical Long Short-Term Memory (H-LSTM) model, whose core components consist of a shared image feature extractor across phases, an internal LSTM for each phase, and an external LSTM across phases. The internal LSTM aggregates features from different layers of 2D CECT images, while the external LSTM aggregates features across different phases. H-LSTM can handle incomplete phases and varying numbers of CECT image layers, making it suitable for real-world decision support scenarios. Additionally, we applied phase augmentation techniques to process multi-phase CECT images, improving the model’s robustness. Results: The H-LSTM model achieved an overall average AUROC of 0.93 (0.90, 1.00) on the test dataset, with AUROC for HCC classification reaching 0.97 (0.93, 1.00) and for ICC classification reaching 0.90 (0.78, 1.00). Comprehensive validation in scenarios with incomplete phases was performed, with the H-LSTM model consistently achieving AUROC values over 0.9. Conclusion: The proposed H-LSTM model can be employed for classification tasks involving incomplete phases of CECT images in real-world scenarios, demonstrating high performance. This highlights the potential of AI-assisted systems in achieving accurate diagnosis and treatment of liver cancer. H-LSTM offers an effective solution for processing multi-phase data and provides practical value for clinical diagnostics. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the effectiveness of deep learning-based reconstruction (DLR) in improving image quality and tumor detectability of isovoxel high-resolution breath-hold fat-suppressed T1-weighted imaging (HR-BH-FS-T1WI) in the hepatobiliary phase (HBP) of Gadoxetic acid-enhanced magnetic resonance imaging (Gd-EOB-MRI). Materials and methods: This retrospective evaluated 42 patients with 98 liver tumors who underwent Gd-EOB-MRI between March 2023 and May 2023 using three techniques based on HBP imaging: isovoxel HR-BH-FS-T1WI reconstructed (1) with DLR (BH-DLR +) and (2) without DLR (BH-DLR −) and (3) HR-FS-T1WI scanned with a free-breathing technique using a navigator-echo-triggered technique and DLR (Navi-DLR +). The three techniques were qualitatively and quantitatively compared by the Friedman test and the Bonferroni post-hoc test. Tumor detectability was compared using the McNemar test. Results: BH-DLR + (3.85, average score of two radiologists) showed significantly better qualitative scores for image noise than BH-DLR − (2.84) and Navi-DLR + (3.37) (p < 0.0167), and Navi-DLR + showed significantly better scores than BH-DLR − (p < 0.0167). BH-DLR + (3.77) and BH-DLR − (3.77) showed significantly better qualitative scores for respiratory motion artifact than Navi-DLR + (2.75) (p < 0.0167), but there was no significant difference in scores between BH-DLR + and BH-DLR − (p > 0.0167). BH-DLR + (0.32) and Navi-DLR + (0.33) showed significantly higher lesion-to-nonlesion CR than BH-DLR − (0.29) (p < 0.0167), but there was no significant difference in lesion-to-nonlesion CR between BH-DLR + and Navi-DLR + (p > 0.0167). BH-DLR + (89.8%) showed significantly better tumor detectability than BH-DLR − (76.0%) and Navi-DLR + (77.6%) (p < 0.05). Conclusion: The use of DLR for isovoxel HR-BH-FS-T1WI was effective in improving image quality and tumor detectability. [ABSTRACT FROM AUTHOR]

Nowadays, liver cancers are well-known cancers attacking the human body. The larger segment of liver carcinomas is highly affected by alcohol-associated hepatitis as well as cirrhosis circumstances. In order to increase the survival rate of humans, premature and early diagnosis of liver cancer is very vital. Currently, discriminating the tumor and liver segments from medical imaging with the help of entirely automated computer-aided software is a highly difficult task, because the liver tumor may differ from one human being to another human being. Thus, this paper endeavors to present a new liver tumor segmentation and classification approach by incorporating an optimization-enabled deep learning model. Here, the adopted model comprises four stages, pre-processing, liver segmentation, liver tumor detection, and classification. To begin with, the collected images are given to the pre-processing stage using the African vulture's optimization-based adaptive histogram equalization (AVOAHE). The integration of the African vulture's optimization (AVO) concept in adaptive histogram equalization is named AVOAHE. After the image pre-processing phase, the liver region is segmented by utilizing kernel-based fuzzy C-means clustering. Then, the detection of liver tumor is performed using the Swin-Unet. Finally, tumor detection is done by utilizing the deep convolutional neural network (Deep CNN). Moreover, a hybrid optimization approach, called double exponential smoothing (DES)-marine predator algorithm (MPA), is developed by combining DES and MPA, which is used to train Deep CNN and serves as an enhancement. Finally, the experimental analysis has shown that the adopted technique has achieved better results in terms of accuracy, specificity, sensitivity, and precision with values of 0.957, 0.969, 0.941 and 0.915, respectively. [ABSTRACT FROM AUTHOR]

Purpose: Identifying primary hepatic angiosarcoma (PHA) preoperatively is challenging, often relying on postoperative pathology. Invasive biopsy increases bleeding risk, emphasizing the importance of early PHA diagnosis through imaging. However, comprehensive summaries of ultrasound, abdominal computed tomography (CT), magnetic resonance imaging (MRI), and whole- body positron emission tomography-CT (PET-CT) in this context are lacking. This study aimed to investigate the comprehensive imaging characteristics of PHA. Patients and methods: Imaging data were collected from 7 patients diagnosed with PHA via pathology between January 2000 and December 2019 in two provincial grade III hospitals. All patients underwent routine color ultrasound examinations before surgery, with 3 patients receiving contrast-enhanced ultrasound (CEUS).CT scans, both plain and enhanced, were performed on 5 patients, and whole-body PET-CT examinations were conducted on 2 patients. Results: Among the 7 patients with PHA, 4 presented with a single solid intrahepatic mass (2 of which were large), 1 with a single exophytic macroblock type, 1 with a mixed type featuring multiple masses and nodules, and 1 with a multiple nodule type. Conventional ultrasound of PHA showed uneven echoes within the tumor, potentially accompanied by septal zone echoes, and a blood flow grade of 0-I. CEUS displayed early-stage circular high enhancement, a central non-enhancement area, and a "vascular sign" around the tumor. CT scans revealed low-density shadows in the plain scan stage, high peripheral ring enhancement, and punctate nodular enhancement in the arterial phase, with varying intensities and the presence of a "vascular sign." During the portal vein stage, the interior of the tumor was consistently unfilled and exhibited structural disorder. PET-CT showed low-density lesions in the liver and low fluorodeoxyglucose metabolism. Conclusions: Imaging diagnosis plays a crucial role in PHA diagnosis. When liver tumor imaging matches the above characteristics, consider PHA. [ABSTRACT FROM AUTHOR]

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Purpose: Percutaneous thermal ablation is an effective treatment for primary and metastatic liver tumors and is a recommended local therapy for early-stage hepatocellular carcinoma (HCC). Reported evidence shows an increase in the ablation zone volume over the first 24-h post-liver ablation. This report compares ablation zone volumes immediately at the completion (T = 0) of 26 microwave ablations of liver tumors to 24-h post-procedure (T = 24) volumes. Materials and methods: 20 patients, 13 (65%) males, underwent a total of 26 hepatic microwave ablations (MWA) under ultrasound guidance. Contrast-enhanced CT (CECT) or MRI was performed immediately and another CECT 24 h post operatively. Evaluation of the ablation zone and comparison of the two post-operative scans were done using BioTrace software. The expansion of ablation zones on post-op CECTs was matched point by point per direction. The distance between each 2 points was measured and grouped by distance. The incidence of each specific distance was then converted into a percentage, first for each case separately, then for all cases altogether. Data were tested by a matched paired one-sided t test. Results: The median lesion diameter was 1.5 cm (range 0.5–3.3) with 16 (62%) HCC cases and 9 hepatic metastases (4 neuroendocrine carcinoma, 4 colorectal carcinomas, 1 breast carcinoma, 1 pancreatic cancer). The data show a consistent volume expansion greater than 30% (p = 7.7e−5) 24-h post-ablation, where the median expansion is 57%. Distances between T = 0 and T = 24 equal to 3–7 mm occur in over 35% of the cases. Conclusion: The ablation zone expansion at 24-h post-op was not uniform. The final ablation zone is difficult to predict at the time of the procedure. The awareness of the ablation zone expansion is important when treating near-critical structures, managing the heat sink effect, and preserving liver parenchyma. [ABSTRACT FROM AUTHOR]

Purpose: Proton therapy is highly effective for liver malignancies, and to increase its accuracy, placement of fiducial markers in the liver is preferred. We retrospectively evaluated the safety and feasibility of CT-guided fiducial marker implantation using ultra-fine 25-gauge needles before proton therapy for liver malignancies. Materials and Methods: Between May 2016 and April 2021, 334 cases were investigated. All of procedures were performed without anesthesia. Technical success was defined as the completion of implantation at the intended site. Tumor–marker distance and possibility of synchronization between tumors and markers were evaluated and compared with Mann–Whitney U test. Complications were evaluated using the Common Terminology Criteria for Adverse Events, version 4.0. Results: Technical success rate was 97.3%. Tumor–marker distance was 19.1 mm (median, range 0–96) in the group in which the implanted marker was synchronized with tumor (n = 315), while it was 34.5 mm (median, range 6–94) in the group in which the implanted marker was not synchronized (n = 13) (p value = 0.011 < 0.05). The complication rate was 2.4%, 2 were classified as grade 4 and 5 as grade 1, and 1 as grade 2. There were no grade 3 or higher complications that seemed to be related to the procedure. Conclusion: CT-guided marker implantation using a 25-gauge needle achieved a satisfactory success rate with few complications and was useful for the image-guided and respiratory-synchronized proton therapy. Level of Evidence 3: Local non-random sample. [ABSTRACT FROM AUTHOR]

Purpose: The technical difficulties of laparoscopic liver resection (LLR) are greatly associated with the location of liver tumors. Since segment 8 (S8) contains a wide area, the difficulty of LLR for S8 tumors may vary depending on the location within the segment, such as the ventral (S8v) and dorsal (S8d) area, but the difference is unclear. Methods: We retrospectively investigated 30 patients who underwent primary laparoscopic partial liver resection for liver tumors in S8 at Kobe University Hospital between January 2018 and June 2023. Results: Thirteen and 17 patients underwent LLR for S8v and S8d, respectively. The operation time was significantly longer (S8v 203[135–259] vs. S8d 261[186–415] min, P = 0.002) and the amount of blood loss was significantly higher (10[10–150] vs. 10[10–200] mL, P = 0.034) in the S8d group than in the S8v group. No significant differences were observed in postoperative complications or postoperative length of hospital stay. Additionally, intraoperative findings revealed that the rate at which the case performed partial liver mobilization in the S8d group was higher (2[15.4%] vs. 8[47.1%], P = 0.060) and the median parenchymal transection time of the S8d group was longer (102[27–148] vs. 129[37–175] min, P = 0.097) than those in the S8v group, but there were no significant differences. Conclusion: The safety of LLR for the S8d was comparable to that of LLR for S8v, although LLR for S8d resulted in longer operative time and more blood loss. The trial registration number: B230165 (approved at December 26, 2023). [ABSTRACT FROM AUTHOR]

Intravoxel incoherent motion (IVIM) modeling is a widely used double‐exponential model for describing diffusion‐weighted imaging (DWI) signal, with a slow component related to pure molecular diffusion and a fast component associated with microcirculatory perfusion, which compensates for the limitations of traditional DWI. IVIM is a noninvasive technique for obtaining liver pathological information and characterizing liver lesions, and has potential applications in the initial diagnosis and treatment monitoring of liver diseases. Recent studies have demonstrated that IVIM‐derived parameters are useful for evaluating liver lesions, including nonalcoholic fatty liver disease (NAFLD), liver fibrosis and liver tumors. However, the results are not stable. Therefore, it is necessary to summarize the current applications of IVIM in liver disease research, identify existing shortcomings, and point out the future development direction. In this review, we searched for studies related to hepatic IVIM‐DWI applications over the past two decades in the PubMed database. We first introduce the fundamental principles and influential factors of IVIM, and then discuss its application in NAFLD, liver fibrosis, and focal hepatic lesions. It has been found that IVIM is still unstable in ensuring the robustness and reproducibility of measurements in the assessment of liver fibrosis grade and liver tumors differentiation, due to inconsistent and substantial overlap in the range of IVIM‐derived parameters for different fibrotic stages. In the end, the future direction of IVIM‐DWI in the assessment of liver diseases is discussed, emphasizing the need for further research on the stability of IVIM‐derived parameters, particularly perfusion‐related parameters, in order to promote the clinical practice of IVIM‐DWI. Level of Evidence: 5 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Surgical resection is the preferred option for hepatocellular carcinoma (HCC), but surgical navigation technology using indocyanine green still has some drawbacks such as non‐specific imaging, thus it is very important to develop new fluorescence imaging technology. All‐cis hexaphenyl‐1,3‐butadiene derivative (ZZ‐HPB‐NC) with aggregation‐induced emission (AIE) feature has been reported to be quickly turned‐on fluorescent response in the intraoperative frozen‐section slides of HCC. However, the probe did not respond to normal liver tissue around HCC. In order to enhance the diagnostic rate and elucidate the response mechanism, all‐trans configuration EE‐HPB‐NC, was furtherly synthesized. Within two minutes, non‐cancer tissues could be fluorescently labeled by EE‐HPB‐NC by spraying, showing the same effect with ZZ‐HPB‐NC to HCC. The results indicated that the configuration‐induced cross‐identification fluorescence imaging strategy was achieved through the combination of ZZ‐ and EE‐HPB‐NC. Then the mechanism of HPB‐NC localization in HCC lesions was explored, and the binding of HPB‐NC with specific proteins in cells resulted in the AIE effect to label HCC cells. On this basis, the accuracy of specific fluorescence imaging for HCC was further verified on the mouse hepatic neoplasm models, indicating that it has clinical application potential for surgical fluorescence real‐time navigation. [ABSTRACT FROM AUTHOR]

The influence of the interventional treatment approach for transarterial radioembolization (TARE) on the incidence of extrahepatic microsphere depositions and to angiographic complications was evaluated. In total, 398 TARE cycles were analyzed. Interventional treatment approaches were classified as single treatment position (TP) with interventional occlusion (IO), multiple TPs without IO, and multiple TPs with IO. Correlations with extrahepatic microsphere depositions, angiographic complications, and periprocedural clinical events were performed. Alternative treatment strategies were evaluated. Applications from multiple TPs could have ensured the safe application of microspheres in 48.2% of cases that were originally performed from a single TP after IO. Extrahepatic microsphere accumulations were detected after 5.2%, 5.3%, and 1.5% of TARE procedures from a single TP without IO, a single TP with IO, and multiple TPs without IO, respectively. Applications from multiple TPs did not increase angiographic complications. During the 30-day follow-up, nausea/vomiting and upper abdominal discomfort were observed more frequently in the group with IO than in the group without IO (7.9%/4.6% and 9.2%/5.9%, respectively). In many TARE procedures, the same target liver can be treated from multiple TPs instead of a single TP, reducing the need for the interventional occlusion of aberrant arteries and potential extrahepatic microsphere depositions. [ABSTRACT FROM AUTHOR]

Abstract Purpose Identifying primary hepatic angiosarcoma (PHA) preoperatively is challenging, often relying on postoperative pathology. Invasive biopsy increases bleeding risk, emphasizing the importance of early PHA diagnosis through imaging. However, comprehensive summaries of ultrasound, abdominal computed tomography (CT), magnetic resonance imaging (MRI), and whole- body positron emission tomography-CT (PET-CT) in this context are lacking. This study aimed to investigate the comprehensive imaging characteristics of PHA. Patients and methods Imaging data were collected from 7 patients diagnosed with PHA via pathology between January 2000 and December 2019 in two provincial grade III hospitals. All patients underwent routine color ultrasound examinations before surgery, with 3 patients receiving contrast-enhanced ultrasound (CEUS).CT scans, both plain and enhanced, were performed on 5 patients, and whole-body PET-CT examinations were conducted on 2 patients. Results Among the 7 patients with PHA, 4 presented with a single solid intrahepatic mass (2 of which were large), 1 with a single exophytic macroblock type, 1 with a mixed type featuring multiple masses and nodules, and 1 with a multiple nodule type. Conventional ultrasound of PHA showed uneven echoes within the tumor, potentially accompanied by septal zone echoes, and a blood flow grade of 0-I. CEUS displayed early-stage circular high enhancement, a central non-enhancement area, and a "vascular sign" around the tumor. CT scans revealed low-density shadows in the plain scan stage, high peripheral ring enhancement, and punctate nodular enhancement in the arterial phase, with varying intensities and the presence of a "vascular sign." During the portal vein stage, the interior of the tumor was consistently unfilled and exhibited structural disorder. PET-CT showed low-density lesions in the liver and low fluorodeoxyglucose metabolism. Conclusions Imaging diagnosis plays a crucial role in PHA diagnosis. When liver tumor imaging matches the above characteristics, consider PHA.

Abstract Nowadays, liver tumor segmentation has been widely applied for vital medical objectives such as illness diagnosis, treatment, and evaluation of liver function. In this work, we aim to improve the performance of hybrid convolution neural network (CNN) models for liver tumor segmentation. A new automatic design method is introduced to build a hybrid CNN model with an optimal architecture using a combination of the original U_Net and the Res-UNet. In the proposed design method, the Res-UNet model is divided into different blocks, and then many different candidate architectures for the hybrid CNN model can be created using gradually these blocks to replace their corresponding blocks of the original U-Net. The replacement is executed if the candidate architecture using a residual block gives better performance than the corresponding one that uses the original U-Net block. We use a genetic algorithm (GA) to get the optimal architecture among the candidate architectures that gives the best performance for the hybrid CNN model. During the optimization process, in addition to the optimal architecture, other crucial configurations such as the learning algorithm, learning rate, and batch size are also determined. We refer to the hybrid CNN model that has the best architecture as GA_Res_UNet. Comparison has been made with other CNN models that are commonly used in image segmentation of liver tumors. We use the 3D-IRCADb01 liver tumor dataset that contains 2800 magnetic resonance (MR) images of 20 patients. Each image has a liver tumor with its corresponding mask. All MR images are resized to 256 × 256 in DICOM format. The findings indicate that GA_Res_UNet outperformed the other compared models over the considered dataset. It achieves 98.5% of dice coefficient and 99.8% of accuracy. Moreover, two other liver tumor segmentation datasets (LiTS17 and CHAOS) are utilized in another comparison to show the superior performance of our proposed model. The reported results show that the proposed model outperformed the other compared state-of-the-art models.

Microwave ablation is a minimally invasive cancer treatment with high survival and low recurrence rates. Despite the unquestionable benefits of microwave ablation, the interaction between the medical tool and the tissue may cause damage to the surrounding tissue, which can be removed by clarifying the conditions for their development. In addition to clinical methods, computer simulation has proven to be a very effective tool to optimize microwave ablation performance. This study aimed to determine the optimal input power for complete microwave tumor ablation with an adequate safety margin while avoiding injury to surrounding healthy tissue. The liver tumor model was based on a real tumor labeled 1.02 in the 3D-IRCADb-01 database. Calculations were performed for a 10-slot microwave antenna with a frequency of 2.45 GHz using COMSOL Multiphysics. The obtained simulation results revealed that with proper input power, the necrotic tissue was mainly located in the tumor with minimal damage to the surrounding healthy tissue. This study may represent a step forward in planning individual microwave ablation procedures for each patient.

Purpose: The Xsight lung tracking system (XLTS) utilizes an advanced image processing algorithm to precisely identify the position of a tumor and determine its location in orthogonal x‐ray images, instead of finding fiducials, thereby minimizing the risk of fiducial insertion‐related side effects. To assess and gauge the effectiveness of CyberKnife Synchrony in treating liver tumors located in close proximity to or within the diaphragm, we employed the Xsight diaphragm tracking system (XDTS), which was based on the XLTS. Methods: We looked back at the treatment logs of 11 patients (8/11 [XDTS], 3/11 [Fiducial‐based Target Tracking System‐FTTS]) who had liver tumors in close proximity to or within the diaphragm. And the results are compared with the patients who undergo the treatment of FTTS. The breathing data information was calculated as a rolling average to reduce the effect of irregular breathing. We tested the tracking accuracy with a dynamic phantom (18023‐A) on the basis of patient‐specific respiratory curve. Results: The average values for the XDTS and FTTS correlation errors were 1.38 ± 0.65 versus 1.50 ± 0.26 mm (superior‐inferior), 1.28 ± 0.48 versus 0.40 ± 0.09 mm (left‐right), and 0.96 ± 0.32 versus 0.47 ± 0.10 mm(anterior‐posterior), respectively. The prediction errors for two methods of 0.65 ± 0.16 versus 5.48 ± 3.33 mm in the S‐I direction, 0.34 ± 0.10 versus 1.41 ± 0.76 mm in the A‐P direction, and 0.22 ± 0.072 versus 1.22 ± 0.48 mm in the L‐R direction. The coverage rate of FTTS slightly less than that of XDTS, such as 96.53 ± 8.19% (FTTS) versus 98.03 ± 1.54 (XDTS). The prediction error, the motion amplitude, and the variation of the respiratory center phase were strongly related to each other. Especially, the higher the amplitude and the variation, the higher the prediction error. Conclusion: The diaphragm has the potential to serve as an alternative to gold fiducial markers for detecting liver tumors in close proximity or within it. We also found that we needed to reduce the motion amplitude and train the respiration of the patients during liver radiotherapy, as well as control and evaluate their breathing. [ABSTRACT FROM AUTHOR]

Objective To elucidate the mechanism of genistein on hepatocellular carcinoma by network pharmacology and bioinformatics. Methods Network pharmacology, bioinformatics and experimental validation were used. The potential targets of genistein were obtained from the Pharm Mapper database. Gene Cards database was used to obtain the pathogenic genes of hepatocellular carcinoma, and the intersection genes of potential targets of genistein and hepatocellular carcinoma-related targets were analyzed and determined. The clinical information of TCGA hepatocellular carcinoma tissue samples and normal tissue samples were used to screen out differentially expressed common target genes, and gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. The differential genes (DEGs) affecting the overall survival of patients were screened by univariate Cox analysis. The STRING platform was used to construct the target interaction network of DEGs, and the core genes were screened for verification. Molecular docking experiments were performed to detect the effect of genistein on the proliferation of hepatocellular carcinoma. Results A total of 235 potential targets of genistein and 9415 therapeutic targets of hepatocellular carcinoma were screened out, of which 40 differentially expressed common target genes affected the patient's back. Among them, ESR1, AR, HRAS, CCNA2, MMP9 and CYP3A4 were the core targets. GO functional annotation enrichment analysis obtained 333 enrichment items, and KEGG pathway enrichment analysis obtained 23 enrichment. The results of molecular docking showed that genistein had a strong binding ability with the core target protein. In vitro experiments confirmed that genistein significantly inhibited the proliferation of hepatocellular carcinoma. Conclusion Genistein inhibits the development of hepatocellular carcinoma through multiple metabolic and signaling pathways. The expression levels of ESR1, AR, HRAS, CCNA2, MMP9 and CYP3A4 can be used to predict the prognosis of patients with hepatocellular carcinoma and provide valuable targets for treatment. [ABSTRACT FROM AUTHOR]

Globally liver diseases are the most life-threatening diseases, and according to global cancer statistics, liver cancer is the most common. Early detection of liver cancer can prevent millions of patients' mortality every year. Automatic liver cancer detection will help radiologists to determine the tumour identification and its severity, and it is also helpful to reduce the occurrence of errors which results in a reduction in the number of deaths from liver cancer. It gives more accurate results in less time, saving the radiologist's effort and time. The proposed model focused on improving the segmenting of liver images and then classifying the liver tumours from the CT images. The present study suggests the hyper tangent Fuzzy C-Means (HTFCM) to segment the liver images. It used Hyper tangent distance to calculate the data point distance from the cluster centres and obtained segmentation results almost closer to the ground truth liver images. Due to the fuzziness in the liver images, all state-of-the-art models except the proposed model cannot precisely locate the tumours. This study solved the issue of linear mapping using fuzzy logic, improved the classification accuracy, and reduced the processing time of early diagnosis of liver diseases. The proposed model improves the classification accuracy to 99.58% and reduces the processing time by 2-25 s to classify the liver tumours. [ABSTRACT FROM AUTHOR]

Background: Hepatic chemosaturation by isolated percutaneous liver perfusion (CS-PHP) with melphalan controls hepatic tumor growth. However, optimal treatment frequency and the prognostic relevance of extrahepatic tumor manifestation remain unclear. We analyzed response and tolerability of repeated treatment in regular cycles of CS-PHP. Materials and methods: CS-PHP was administered to patients with primary or secondary liver tumors. Overall survival (OS) and hepatic disease control rate (hDCR) were assessed retrospectively by modified RECIST after at least one response assessment, and toxicity by Common Terminology Criteria for Adverse Events v4.03. Results: A total of 97 CS-PHP treatments were carried out in 33 patients between 2016 and 2023. Patients had unresectable intrahepatic metastases of uveal melanoma (n = 19), intrahepatic cholangiocarcinoma (n = 8), hepatocellular carcinoma (n = 2), ciliary body melanoma (n = 1), acinar cell carcinoma (n = 1), pancreatic cancer (n = 1) or tonsil cancer (n = 1). CS-PHP was carried out seven times in 1 patient, six times in 5, five times in 3, four times in 2, three times in 4, twice in 7 and once in 11 patients. The median OS was 65 weeks (standard error 13.6, 95% confidence interval 38.2-91.5 weeks). hDCR was 91% (30 of 33 patients) at last observation time point. Extrahepatic tumor manifestations were not associated with OS. CS-PHP was well tolerated. Grade III or IV pancytopenia occurred in two patients. Conclusion: CS-PHP induced hepatic disease control in the majority of patients. Extrahepatic tumor manifestation had no significant impact on OS. The relevance of CS-PHP as long-term treatment needs to be validated in future studies.

Abstract Surgical resection is the preferred option for hepatocellular carcinoma (HCC), but surgical navigation technology using indocyanine green still has some drawbacks such as non‐specific imaging, thus it is very important to develop new fluorescence imaging technology. All‐cis hexaphenyl‐1,3‐butadiene derivative (ZZ‐HPB‐NC) with aggregation‐induced emission (AIE) feature has been reported to be quickly turned‐on fluorescent response in the intraoperative frozen‐section slides of HCC. However, the probe did not respond to normal liver tissue around HCC. In order to enhance the diagnostic rate and elucidate the response mechanism, all‐trans configuration EE‐HPB‐NC, was furtherly synthesized. Within two minutes, non‐cancer tissues could be fluorescently labeled by EE‐HPB‐NC by spraying, showing the same effect with ZZ‐HPB‐NC to HCC. The results indicated that the configuration‐induced cross‐identification fluorescence imaging strategy was achieved through the combination of ZZ‐ and EE‐HPB‐NC. Then the mechanism of HPB‐NC localization in HCC lesions was explored, and the binding of HPB‐NC with specific proteins in cells resulted in the AIE effect to label HCC cells. On this basis, the accuracy of specific fluorescence imaging for HCC was further verified on the mouse hepatic neoplasm models, indicating that it has clinical application potential for surgical fluorescence real‐time navigation.

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://medicaldecathlon.com/. In addition, both data and online evaluation are accessible via https://competitions.codalab.org/competitions/17094.

Yuqing Bu,1,&ast; Junye Wen,2,&ast; Fayan Wang,1,3 Shibo Dong,4 Liya He,1 Yang Li,1,5 Jinlong Liang,1,3 Hongzhen Zhang1,3,5 1Department of Oncology, Hebei General Hospital, Shijiazhuang, Hebei Province, 050051, People’s Republic of China; 2Department of Hepatobiliary Surgery, Hebei General Hospital, Shijiazhuang, Hebei Province, 050051, People’s Republic of China; 3Department of Medicine, Hebei North University, Zhangjiakou, Hebei Province, 075000, People’s Republic of China; 4Department of Imaging, Hebei General Hospital, Shijiazhuang, Hebei Province, 050051, People’s Republic of China; 5Department of Medicine, North China University of Science and Technology, Tangshan, Hebei Province, 063210, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Hongzhen Zhang, Email hongzhenzhang456@sohu.comAbstract: This study presents a case of dual primary liver cancer involving small cell neuroendocrine carcinoma and hepatocellular carcinoma. The 58-year-old Chinese male patient, who has a medical history of viral hepatitis B, presented with right upper abdominal pain persisting for one month. Imaging studies indicated the presence of multiple liver masses in segments V and VII–VIII, as well as a mass in the left lung. Subsequent hepatic biopsy performed on both segments confirmed the presence of hepatocellular carcinoma in segment V and small cell neuroendocrine carcinoma in segment VII–VIII. After undergoing one cycle of chemotherapy, the lung mass exhibited a reduction in size, while the liver masses showed an inadequate response. Subsequently, the patient underwent Transcatheter Arterial Chemoembolization (TACE) and Hepatic Artery Infusion Chemotherapy (HIAC), resulting in partial remission (PR). However, the patient was diagnosed with brain metastasis and subsequently treated with Sorafenib and Tirelizumab, a Programmed Death 1 (PD-1) immune checkpoint inhibitor. The efficacy evaluation indicated stability, and no severe adverse effects were observed at the time of writing. The patient’s survival time was 16 months.Keywords: synchronous tumor, liver tumor, primary tumor, small cell neuroendocrine carcinoma, hepatocellular carcinoma

Hepatocellular adenoma is a rare benign liver tumor that occurs predominantly in young women who use exogenous estrogens. We describe a case of a 40-year-old woman on birth control pill who presented with acute right hypochondrial pain and signs of hemodynamical instability triggered by a large bleeding tumor in the right liver lobe. Arterial embolization was performed with cessation of bleeding. To determine etiology, magnetic resonance imaging was conducted with findings suggestive of a hepatocellular adenoma. The tumor was surgically resected, and histologic examination made the definite diagnosis of an inflammatory hepatocellular adenoma. This is a noteworthy case of a rare but potentially fatal complication of liver tumors, whose diagnosis requires a high index of suspicion. Clinicians should consider this diagnosis in young women on oral contraceptive pills who present with severe unexplained abdominal pain and hemodynamical instability. This case aimed to raise awareness of this condition, while reviewing important aspects concerning the management of hepatocellular adenomas.

The treatment of unresectable colorectal liver metastasis (CRLM) has previously been limited to palliative chemotherapy. Traditionally, the role of liver transplant has not been associated with sufficient survival to justify a patient undergoing a major operation with the associated requirement for postoperative immunosuppression. With improvements in chemotherapy options, a certain subset of patients can experience stable disease for years, which has prompted investigation into the role of liver transplant in these patients. Several recent studies have shown promising results in well-selected patients, with posttransplant survival approaching that of liver transplant recipients for other diseases. Here, we present a review of the data and current protocols for liver transplant for unresectable CRLM.

Purpose To explore the feasibility and safety of a microwave ablation (MWA) strategy involving intraductal chilled saline perfusion (ICSP) via percutaneous transhepatic cholangial drainage (PTCD) combined with ultrasound-magnetic resonance (US-MR) fusion imaging for liver tumors proximal to the hilar bile ducts (HBDs).Methods Patients with liver tumors proximal to the HBDs (≤5 mm) who underwent MWA at our hospital between June 2020 and April 2023 were retrospectively analyzed. The strategy of US-MR fusion imaging combined with PTCD-ICSP was used to assist the MWA procedures. The technical success, technique efficacy, local tumor progression, intrahepatic distant recurrence and complications were recorded and analyzed.Results In total, 12 patients with 12 liver tumors were retrospectively enrolled in this study. US-MR fusion imaging was utilized in all patients, and PTCD-ICSP assistance was successfully used for 4 nodules abutting HBDs (0 mm). The rates of technical success, technique efficacy, local tumor progression and intrahepatic distant recurrence were 91.7%, 83.3%, 0% and 8.3%, respectively. The major complication of biliary infection occurred in only one patient who had previously undergone left hemihepatectomy and bile-intestinal anastomosis.Conclusions MWA for liver tumors proximal to HBDs assisted by US-MR fusion imaging combined with PTCD-ICSP was feasible and safe. This strategy made MWA of liver tumors abutting HBDs possible.

AbstractThe liver is an important and multifunctional human organ. Early and accurate diagnosis of a liver tumor can save lives. Computed Tomography (CT) images provide comprehensive information for liver tumor diagnosis using feature extraction techniques. These extracted features help classify liver tumors using Machine Learning (ML) and Deep Learning (DL) methods. For this research, twelve 1hundred CT images were acquired from the Radiology Department of Nishter Medical University & Hospital. The noise was removed using Gabor Filter after converting CT images into grayscale. Image quality was enhanced by adopting Histogram Equalization (HE), and finally, the Image’s edges and boundaries were improved using a smoothening and sharpening algorithm. Preprocessed images were forwarded to extract six features: Histogram, Run-length, Co-occurrence, Autogressive, Gradient, and Wavelet Transform. A major focus of this research is to evaluate that ML methods produced good accuracy using already extracted features while DL Algorithms could not produce better results. Firstly, ML methods such as Decision Tree (DT), Random Forest (RF), Boost, and Support Vector Machine (SVM) are deployed using an already extracted feature list containing all six features. It was observed that DT, RF, Boost, and SVM produced 96.5%, 99.6%, 99.7%, and 98.0% classification accuracy. After that, DL Algorithms such as Neural Networks (NN), Long-Short Term Memory (LSTM), Bi-Directional Long Short Term Memory (Bi-LSTM), and Convolutional Neural Networks (CNN) were deployed. The results showed that NN, LSTM, Bi-LSTM, and CNN produced 50.0%, 53.0%, 54.0%, and 54.0% accuracy respectively. To validate the major focus of this research, finally, Pre-trained DL Algorithms such as Residual Network 50 (Resnet50), Visual Geometry Group 16 (VGG16) and LSTM + CNN were deployed. Results showed that Resnet50, VGG16, and LSTM + CNN attained 78.0%, 88.0%, and 97.0% accuracy respectively. Hence, ML methods performed better using already extracted features, while DL Algorithms could not produce promising results on these extracted features.

Introduction and Objectives: Blood glucose fluctuates severely in the diabetes (DM) and tumor microenvironment. Our previous works have found Hepatitis B virus X protein (HBx) differentially regulated metastasis and apoptosis of hepatoma cells depending on glucose concentration. We here aimed to explore whether HBx played dual roles in the angiogenesis of hepatocellular carcinoma varying on different glucose levels. Materials and Methods: We collected conditioned medium from HBx-overexpressing cells cultured with two solubilities of glucose, and then applied to EA.hy926 cells. Alternatively, a co-culture cell system was established with hepatoma cells and EA.hy926 cells. We analyzed the angiogenesis of EA.hy926 cells with CCK8, wound-healing, transwell-migartion and tube formation experiment. ELISA was conducted to detect the secretion levels of angiogenesis-related factors. siRNAs were used to detect the P53-VEGF axis. Results: HBx expressed in hepatoma cells suppressed VEGF secretion, and subsequently inhibited the proliferation, migration and tube formation of EA.hy926 cells in a high glucose condition, while attenuating these in the lower glucose condition. Furthermore, the p53-VEGF axis was required for the dual role of HBx in angiogenesis. Additionally, HBx mainly regulated the nuclear p53. Conclusions: These data suggest that the dual roles of HBx confer hepatoma cells to remain in a glucose-rich environment and escape from the glucose-low milieu through tumor vessels, promoting liver tumor progression overall. We exclusively revealed the dual role of HBx on the angiogenesis of liver tumors, which may shed new light on the mechanism and management strategy of HBV- and DM-related hepatocellular carcinoma.

Objectives: Gypenoside (Gyp) is easily degraded in the gastrointestinal tract, resulting in its low bioavailability. We aimed to develop a tumor-targeted Gyp nanodrug delivery system and to investigate its antitumor effect in vitro. Materials and Methods: We used Gyp as the therapeutic drug molecule, mesoporous silica (MSN) and liposome (Lipo) as the drug carrier and protective layers, and aptamer SYL3C as the targeting element to establish a tumor-targeted nanodrug delivery system (i.e., SYL3C-Lipo@Gyp-MSN). The characteristics of SYL3C-Lipo@Gyp-MSN were investigated, and its drug release performance, cell uptake, and antitumor activity in vitro were evaluated. Results: A tumor-targeted Gyp nanodrug delivery system was successfully prepared. The SYL3C-Lipo@Gyp-MSN was spherical or ellipsoidal; had good dispersion, which enabled it to specifically target and kill the liver tumor cell HepG2; and effectively protected the early leakage of Gyp. Conclusions: We have established a tumor-targeted nanodrug delivery system that can target and kill liver cancer cells and may provide a strategy for preparing new nanodrug-loaded preparations of traditional Chinese medicine. [ABSTRACT FROM AUTHOR]

Segmenting liver tumors in CT scans plays a vital role in medical analysis planning. The clinicians require a detailed 3D understanding of the tumor's location and liver anatomy, to decide about the proper surgical resection approach. Manual segmentation requires a lot of efforts and time also it depends on the expertise of clinicians. An automatic U-net based method for liver tumors delineation in CT images is proposed. It relies on employing attention-based processes to enhance the performance of U-net. Hard attention and soft attention are used to orient the U-net in learning the intended features from the target CT scans. Soft attention mechanisms, spatial and channel attentions, are employed to help in extracting the long-range relationships and allow the network to successfully distinguish tumors from the surrounding parenchyma. The paper addressed the use of region based active contour implemented using Chan and Vese approach as postprocessing step to improve the predicted segmented tumors. The proposed approach is validated using a challenging big LiTS datasets. The achieved Dice score for the segmenting of liver tumors is 0.81 which shows a superior performance compared to other proposed method in the state of art. The suggested method was successful in discriminating liver tumors from surrounding tissue in heterogeneous CT scans, taking the advantage from the important preprocessing enhancement step. The method demonstrates its generalizability and reliability to be used for automatic analysis of the liver tumors in daily clinical practice. Also, the method proved its ability to achieve high accuracy in detecting stroke that proves its ability to be utilized as clinical tool for a preoperative clinical planning. [ABSTRACT FROM AUTHOR]

Familial adenomatous polyposis (FAP) is an autosomal dominant syndrome caused by a germline mutation in the adenomatous polyposis coli (APC) gene, characterized by numerous colorectal adenomas. In addition, FAP patients may develop extraintestinal manifestations. Several cases of hepatocellular adenomas (HCA) detected accidentally in FAP patients have raised the so-far unsolved question of whether they represent a specific manifestation of FAP or a mere coincidence. To investigate the incidence of liver tumors in FAP patients, we analyzed our diagnostic database from 1991 to 2021. Among the 58 hepatic mass lesions identified, five HCAs occurring in three patients with FAP were identified, and comprehensive morphological, immunohistological, and molecular analysis employing targeted next-generation sequencing was conducted for characterization. The HCAs in this study showed no cytological or histological atypia. They displayed a diffuse, strong positivity for glutamine synthetase but no nuclear beta-catenin immunostaining. In two patients, the adenomas showed moderate immunoreactivity against serum amyloid A. Consistent with the diagnosis of FAP, molecular profiling revealed a pathogenic germline mutation of the APC gene in all analyzed adenomas as well as deleterious somatic second hits. All somatic mutations were localized between codons 1345 and 1577. No mutations were found in the catenin beta 1 gene. HCA in FAP patients can be a specific, although rare, neoplastic manifestation of this inborn disease and represents a distinct subgroup of HCAs. These benign tumors represent an important differential diagnosis for hepatic metastases in FAP patients and require adequate clinical and molecular (diagnostic) assessments for optimal patient guidance. [ABSTRACT FROM AUTHOR]

Simple Summary: Image-guided tumor ablation has become an indispensable part of oncological care, with an increasing demand and need for novel implements to optimize treatment outcomes. The purpose of this pictorial essay was to illustrate the added value of intra-arterial contrast administration during CT-guided liver tumor ablation procedures. Eight clinical cases from three tertiary referral institutions demonstrate the ability to improve the conspicuity of the target liver tumor(s) and identify surrounding critical vascular structures, promptly detect 'vanished' and/or additional tumors, differentiate local tumor progression from non-enhancing scar tissue, and instantly detect and respond to iatrogenic hemorrhagic events. In conclusion, although at the cost of adding a minor but safe intervention, the use of an intra-arterial-administered contrast agent during a CT-guided thermal ablation procedure is a potential quality-improving real-time image-guiding method and should therefore be embedded in (inter)national standards of practice. With the rapidly evolving field of image-guided tumor ablation, there is an increasing demand and need for tools to optimize treatment success. Known factors affecting the success of (non-)thermal liver ablation procedures are the ability to optimize tumor and surrounding critical structure visualization, ablation applicator targeting, and ablation zone confirmation. A recent study showed superior local tumor progression-free survival and local control outcomes when using transcatheter computed tomography hepatic angiography (CTHA) guidance in percutaneous liver ablation procedures. This pictorial review provides eight clinical cases from three institutions, MD Anderson (Houston, TX, USA), Gustave Roussy (Paris, France), and Amsterdam UMC (Amsterdam, The Netherlands), with the intent to demonstrate the added value of real-time CTHA guided tumor ablation for primary liver tumors and liver-only metastatic disease. The clinical illustrations highlight the ability to improve the detectability of the initial target liver tumor(s) and identify surrounding critical vascular structures, detect 'vanished' and/or additional tumors intraprocedurally, differentiate local tumor progression from non-enhancing scar tissue, and promptly detect and respond to iatrogenic hemorrhagic events. Although at the cost of adding a minor but safe intervention, CTHA-guided liver tumor ablation minimizes complications of the actual ablation procedure, reduces the number of repeat ablations, and improves the oncological outcome of patients with liver malignancies. Therefore, we recommend adopting CTHA as a potential quality-improving guiding method within the (inter)national standards of practice. [ABSTRACT FROM AUTHOR]

Deep learning (DL) algorithms used for DOTATATE PET lesion detection typically require large, well-annotated training datasets. These are difficult to obtain due to low incidence of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and the high cost of manual annotation. Furthermore, networks trained and tested with data acquired from site specific PET/CT instrumentation, acquisition and processing protocols have reduced performance when tested with offsite data. This lack of generalizability requires even larger, more diverse training datasets. The objective of this study is to investigate the feasibility of improving DL algorithm performance by better matching the background noise in training datasets to higher noise, out-of-domain testing datasets. 68Ga-DOTATATE PET/CT datasets were obtained from two scanners: Scanner1, a state-of-the-art digital PET/CT (GE DMI PET/CT; n = 83 subjects), and Scanner2, an older-generation analog PET/CT (GE STE; n = 123 subjects). Set1, the data set from Scanner1, was reconstructed with standard clinical parameters (5 min; Q.Clear) and list-mode reconstructions (VPFXS 2, 3, 4, and 5-min). Set2, data from Scanner2 representing out-of-domain clinical scans, used standard iterative reconstruction (5 min; OSEM). A deep neural network was trained with each dataset: Network1 for Scanner1 and Network2 for Scanner2. DL performance (Network1) was tested with out-of-domain test data (Set2). To evaluate the effect of training sample size, we tested DL model performance using a fraction (25%, 50% and 75%) of Set1 for training. Scanner1, list-mode 2-min reconstructed data demonstrated the most similar noise level compared that of Set2, resulting in the best performance (F1 = 0.713). This was not significantly different compared to the highest performance, upper-bound limit using in-domain training for Network2 (F1 = 0.755; p-value = 0.103). Regarding sample size, the F1 score significantly increased from 25% training data (F1 = 0.478) to 100% training data (F1 = 0.713; p < 0.001). List-mode data from modern PET scanners can be reconstructed to better match the noise properties of older scanners. Using existing data and their associated annotations dramatically reduces the cost and effort in generating these datasets and significantly improves the performance of existing DL algorithms. List-mode reconstructions can provide an efficient, low-cost method to improve DL algorithm generalizability. [ABSTRACT FROM AUTHOR]

Simple Summary: Further information is necessary regarding the influence of besifovir (BSV), a new nucleotide analogue, on the occurrence of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). When we compared the HCC incidence in non-cirrhotic CHB patients receiving BSV with the predicted number derived from the REACH-B (risk estimation for HCC in CHB) model, the standardized incidence ratio (SIR) was significantly reduced to 0.128 at 7 years. The incidence of HCC in patients with cirrhosis was compared using the GAG-HCC (guide with age, gender, HBV DNA, core promotor mutation, and cirrhosis) model, and the SIR was significantly decreased to 0.371 at 7.5 years. HCC prediction was available for BSV-treated patients using existing models. We concluded that BSV decreases the risk of HCC in patients with CHB, and HCC risk prediction models are applicable. No information is available regarding the influence of besifovir (BSV), a new nucleotide analogue, on the occurrence of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). This study evaluated the reduced risk of HCC in patients undergoing BSV treatment. A total of 188 patients with CHB were treated with BSV for up to 8 years. We prospectively assessed the incidence of HCC compared with the risk from prediction models. During the follow-up, 5 patients developed HCC: 1 of 139 patients with non-cirrhotic CHB, and 4 of 49 patients with liver cirrhosis. We compared the HCC incidence in non-cirrhotic and cirrhotic patients with the predicted number derived from the REACH-B (risk estimation for HCC in CHB) model and GAG-HCC (guide with age, gender, HBV DNA, core promotor mutation, and cirrhosis) model, respectively. The standardized incidence ratio (SIR) was 0.128 (p = 0.039) at 7 years in non-cirrhotic CHB patients, and the SIR was 0.371 (p = 0.047) at 7.5 years in cirrhotic patients, suggesting a significantly decreased HCC incidence in both groups. HCC prediction was available for BSV-treated patients using existing models. In conclusion, BSV decreased the risk of HCC in patients with CHB, and prediction models were applicable. Clinical trial registry website and trial number: ClinicalTrials.gov no: NCT01937806. [ABSTRACT FROM AUTHOR]

This study aims to explore the feasibility of utilizing a combination of original and delta cone-beam CT (CBCT) radiomics for predicting treatment response in liver tumors undergoing stereotactic body radiation therapy (SBRT). A total of 49 patients are included in this study, with 36 receiving 5-fraction SBRT, 3 receiving 4-fraction SBRT, and 10 receiving 3-fraction SBRT. The CBCT and planning CT images from liver cancer patients who underwent SBRT are collected to extract overall 547 radiomics features. The CBCT features which are reproducible and interchangeable with pCT are selected for modeling analysis. The delta features between fractions are calculated to depict tumor change. The patients with 4-fraction SBRT are only used for screening robust features. In patients receiving 5-fraction SBRT, the predictive ability of both original and delta CBCT features for two-level treatment response (local efficacy vs. local non-efficacy; complete response (CR) vs. partial response (PR)) is assessed by utilizing multivariable logistic regression with leave-one-out cross-validation. Additionally, univariate analysis is conducted to validate the capability of CBCT features in identifying local efficacy in patients receiving 3-fraction SBRT. In patients receiving 5-fraction SBRT, the combined models incorporating original and delta CBCT radiomics features demonstrate higher area under the curve (AUC) values compared to models using either original or delta features alone for both classification tasks. The AUC values for predicting local efficacy vs. local non-efficacy are 0.58 for original features, 0.82 for delta features, and 0.90 for combined features. For distinguishing PR from CR, the respective AUC values for original, delta and combined features are 0.79, 0.80, and 0.89. In patients receiving 3-fraction SBRT, eight valuable CBCT radiomics features are identified for predicting local efficacy. The combination of original and delta radiomics derived from fractionated CBCT images in liver cancer patients undergoing SBRT shows promise in providing comprehensive information for predicting treatment response. [ABSTRACT FROM AUTHOR]

The treatment of unresectable colorectal liver metastasis (CRLM) has previously been limited to palliative chemotherapy. Traditionally, the role of liver transplant has not been associated with sufficient survival to justify a patient undergoing a major operation with the associated requirement for postoperative immunosuppression. With improvements in chemotherapy options, a certain subset of patients can experience stable disease for years, which has prompted investigation into the role of liver transplant in these patients. Several recent studies have shown promising results in well-selected patients, with posttransplant survival approaching that of liver transplant recipients for other diseases. Here, we present a review of the data and current protocols for liver transplant for unresectable CRLM. [ABSTRACT FROM AUTHOR]

Background and aim: A novel study found interferon enhanced antitumor activity of anti-PD-1-based immunotherapy and played a crucial role in improving efficacy on HCC, but the opposite results about the efficacy of interferon on HBV-related HCC were obtained from previous clinical studies and meta-analyses. Thus, this meta-analysis aimed to re-evaluate whether interferon could improve survival and reduce recurrence of patients with HBV-related HCC after curative surgery. Methods: MEDLINE/PubMed, Cochrane Library, EMBASE, Web of Science and CNKI were searched for eligible studies from inception to November 2022 and a meta-analysis was done. Results: 10 trials with a total of 2062 subjects were screened. Interferon significantly improved 1-, 2-, 3- and 5-year OS and 1-, 2- and 3-year DFS, and reduced 2-, 3- and 5-year recurrence rates of patients with HBV-related HCC after curative surgery. However, interferon did not improve 8-year OS and 5-year DFS, did not reduce 1-year recurrence rate. Conclusions: Interferon may significantly reduce recurrence and improve DFS of patients with HBV-related HCC after curative surgery, and finally improve the OS. However, the efficacy advantage may gradually weaken as time goes on. The clinical application of interferon combined with NAs recommended in this meta-analysis is needed to be further studied. [ABSTRACT FROM AUTHOR]

It has been reported that dodecanoic acid (DDA) exerts anticancer effects on cancers of the reproductive system and digestive system. However, its role in liver cancer and its potential mechanism have rarely been defined. Therefore, in this study, Hepa 1-6 liver cancer cells were incubated with different DDA concentrations (0.1, 0.3, 0.5, 1, 2, 4 mM) for 24, 48 and 72h, and the optimal DDA concentration was determined via a cell viability test. Apoptosis and cell cycle distribution were determined by flow cytometry. SOD activity, mitochondrial membrane potential (MMP), ATP, GSH and ROS levels were measured by commercial assay kits; Bcl-2, Bax and Caspase-3 protein levels were analyzed by western blot. The results showed that 0.5 mM DDA decreased cell viability in a time-dependent manner, so this concentration was used to investigate how DDA leads to Hepa 1-6 cell apoptosis. After treatment with DDA, a significant, time-dependent increase in the cell apoptotic rate was detected despite the accumulation of S-phase cells. The increased ROS levels and decreased GSH levels and SOD activity in DDA-treated cells indicated the occurrence of oxidative stress. Mitochondrial dysfunction was evidenced by a decreased MMP and reduced ATP levels. Cell apoptotic death via the mitochondrial pathway was indicated by a reduced Bcl-2/Bax ratio and increased caspase-3 protein levels. It can be concluded that DDA can effectively trigger liver cancer cell death by inducing oxidative stress and disrupting mitochondrial function. These findings provide new insight into the potential mechanism of action of DDA in liver cancer.

One of the most common forms of cancer is liver cancer, and successful treatment depends greatly on an early diagnosis. The two primary steps in liver tumor segmentation are liver identification and then tumor segmentation. A sophisticated meta-heuristic technique called Improved Probabilistic Neural Networks and Bayesian Optimization (IPNN-BO) is also introduced to carry out the best classification. In the study, liver computed tomography (CT) scan pictures were gathered for training purposes and added to the LiTs17 dataset. Utilizing performance matrices like accuracy, precision, recall, specificity, sensitivity, and F Measure, the suggested technique is implemented in MATLAB 2021(a). Modern technologies such as KNN, CNN, and DCNN, among others, are used to organize and validate possible policies. The comparison results reveal that the proposed technique outperforms and outperforms the most recent methodologies. IPNN-BO may obtain validation accuracy of up to 99.25 % after applying Bayesian optimization, while KNN, CNN, and DCNN only manage validation accuracy of 88 %, 92.85 %, and 93.75 %, respectively.

Liver surgery is the cornerstone of the curative treatment of malignant liver tumors. However, the liver anatomy is very complex, and liver surgery is still associated with relevant morbidity despite many technical advances. The Brisbane nomenclature is used worldwide to classify liver resection. However, this nomenclature has several limitations as multiple terms are used for the same type of resection. Non-anatomical resections, multiple resections, and combined bilio-vascular resections were not mentioned. Therefore, new terminologies have been proposed for the precise and simple classification of liver resection. Furthermore, in recent years, many technical innovations have been introduced in liver surgery, such as 3D imaging systems and indocyanine green fluorescence, for better preoperative and intraoperative identification of tumor localization and critical vascular structures. Minimally invasive techniques are used more frequently in liver surgery. Potential benefits include less intraoperative blood loss, less pain, and a shorter hospital stay. The implementation of robotic systems also has an impact on liver surgery, and the number of cases reported in the literature is constantly increasing. The potential benefits of robotic liver resection over laparoscopic liver resection will be the subject of future studies.

Liver biopsy is a crucial diagnostic procedure for liver-related conditions. However, it is challenging to use in cases with substantial ascites or coagulopathy. Transjugular liver biopsy has been introduced as an alternative method to overcome these limitations. Although transjugular liver biopsy is commonly used for diffuse liver diseases, its application to localized tumors has been limited. We report the case of a 66-year-old male initially diagnosed with unresectable pancreatic carcinoma, who later developed liver metastasis, peritoneal dissemination, and ascites. Treatment planning required tumor re-evaluation, but percutaneous liver biopsy was not viable because of the rapid accumulation of ascites and its presence on the liver surface. However, transjugular liver biopsy was a suitable alternative, given the proximity of the tumor to the right hepatic vein. The procedure, performed under fluoroscopic and ultrasound guidance, successfully obtained 4 specimens that were promptly diagnosed as liver metastases originating from pancreatic cancer. This case underscored the effectiveness of transjugular liver biopsy in situations where percutaneous biopsy is challenging because of conditions such as ascites. The combination of ultrasound guidance and rapid specimen assessment by pathology technicians can enhance diagnostic success rates. Transjugular liver biopsy is a valuable diagnostic tool in scenarios where percutaneous access poses significant difficulties.

The influence of the interventional treatment approach for transarterial radioembolization (TARE) on the incidence of extrahepatic microsphere depositions and to angiographic complications was evaluated. In total, 398 TARE cycles were analyzed. Interventional treatment approaches were classified as single treatment position (TP) with interventional occlusion (IO), multiple TPs without IO, and multiple TPs with IO. Correlations with extrahepatic microsphere depositions, angiographic complications, and periprocedural clinical events were performed. Alternative treatment strategies were evaluated. Applications from multiple TPs could have ensured the safe application of microspheres in 48.2% of cases that were originally performed from a single TP after IO. Extrahepatic microsphere accumulations were detected after 5.2%, 5.3%, and 1.5% of TARE procedures from a single TP without IO, a single TP with IO, and multiple TPs without IO, respectively. Applications from multiple TPs did not increase angiographic complications. During the 30-day follow-up, nausea/vomiting and upper abdominal discomfort were observed more frequently in the group with IO than in the group without IO (7.9%/4.6% and 9.2%/5.9%, respectively). In many TARE procedures, the same target liver can be treated from multiple TPs instead of a single TP, reducing the need for the interventional occlusion of aberrant arteries and potential extrahepatic microsphere depositions.