Metabonomic analysis of tumor microenvironments: a mini-review.

Metabolomic analysis is a vital part of studying cancer progression. Metabonomic crosstalk, such as nutrient availability, physicochemical transformation, and intercellular interactions can affect tumor metabolism. Many original studies have demonstrated that metabolomics is important in some aspects of tumor metabolism. In this mini-review, we summarize the definition of metabolomics and how it can help change a tumor microenvironment, especially in pathways of three metabonomic tumors. Just as non-invasive biofluids have been identified as early biomarkers of tumor development, metabolomics can also predict differences in tumor drug response, drug resistance, and efficacy. Therefore, metabolomics is important for tumor metabolism and how it can affect oncology drugs in cancer therapy.

Comparison efficacy of ultrasound-guided needle release plus corticosteroid injection and mini-open surgery in patients with carpal tunnel syndrome.

This retrospective study was to compare clinical outcomes of ultrasound-guided needle release with corticosteroid injection vs. mini-open surgery in patients with carpal tunnel syndrome (CTS). From January 2021 to December 2021, 40 patients (40 wrists) with CTS were analyzed in this study. The diagnosis was based on clinical symptoms, electrophysiological imaging, and ultrasound imaging. A total of 20 wrists were treated with ultrasound-guided needle release plus corticosteroid injection (Group A), and the other 20 wrists were treated with mini-open surgery (Group B). We evaluated the Boston carpal tunnel questionnaire, electrophysiological parameters (distal motor latency, sensory conduction velocity, and sensory nerve action potential of the median nerve), and ultrasound parameters (cross-sectional area, flattening ratio, and the thicknesses of transverse carpal ligament) both before and 3 months after treatment. Total treatment cost, duration of treatment, healing time, and complications were also recorded for the two groups. The Boston carpal tunnel questionnaire and electrophysiological and ultrasound outcomes at preoperatively and 3 months postoperatively had a significant difference for each group (each with P < 0.05). There were no complications such as infection, hemorrhage, vascular, nerve, or tendon injuries in both groups. Ultrasound-guided needle release and mini-open surgery are both effective measures in treating CTS patients. Ultrasound-guided needle release plus corticosteroid injection provides smaller incision, less cost, less time of treatment, and faster recovery compared with mini-open surgery. Ultrasound-guided needle release plus corticosteroid injection is better for clinical application.

CoIn: Correlation Induced Clustering for Cognition of High Dimensional Bioinformatics Data.

Analysis of high dimensional biomedical data such as microarray gene expression data and mass spectrometry images, is crucial to provide better medical services including cancer subtyping, protein homology detection, etc. Clustering is a fundamental cognitive task which aims to group unlabeled data into multiple clusters based on their intrinsic similarities. However, for most clustering methods, including the most widely used K-means algorithm, all features of the high dimensional data are considered equally in relevance, which distorts the performance when clustering high-dimensional data where there exist many redundant variables and correlated variables. In this paper, we aim at addressing the problem of the high dimensional bioinformatics data clustering and propose a new correlation induced clustering, CoIn, to capture complex correlations among high dimensional data and guarantee the correlation consistency within each cluster. We evaluate the proposed method on a high dimensional mass spectrometry dataset of liver cancer tumor to explore the metabolic differences on tissues and discover the intra-tumor heterogeneity (ITH). By comparing the results of baselines and ours, it has been found that our method produces more explainable and understandable results for clinical analysis, which demonstrates the proposed clustering paradigm has the potential with application to knowledge discovery in high dimensional bioinformatics data.

Subclavian brachial plexus metastasis from breast cancer: A case report.

BACKGROUND: The common area of breast cancer metastases are bone, lung and liver. Brachial plexus metastasis from breast cancer is extremely rare. We report a case of subclavian brachial plexus metastasis from breast cancer 6 years postoperative, which were detected by ultrasound, magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography and computed tomography (FDG-PET/CT). CASE SUMMARY: Our study reports a 64-year-old woman who had right breast cancer and underwent radical mastectomy 6 years before. Ultrasound first revealed a soft lesion measuring 38 mm × 37 mm which located on the right side of the clavicle to the armpit subcutaneously. The right subclavian brachial plexus (beam level) was significantly thickened, wrapped around by a hypoechoic lesion, the surrounded axillary artery and vein were pressed. MRI brachial plexus scan showed that the right side of brachial plexus was enlarged compared with the left side and brachial plexus bundle in the distance showed a flake shadow. FDG-PET/CT revealed that the right side of brachial plexus nodular appearance with increased FDG metabolism. These results supported brachial plexus metastasis from breast cancer. Ultrasound exam also found many lesions between pectoralis major, deltoid muscle and inner upper arm. The lesion puncture was performed under ultrasound guidance and the tissue was sent for pathology. Pathology showed large areas of tumor cells in fibroblast tissue. Immunohistochemistry showed the following results: A2-1: GATA3 (+), ER (+, strong, 90%), PR (+, moderate, 10%), HER-2 (3+), Ki67 (+15%), P120 (membrane+), P63 (-), E-cadherin (+), CK5/6 (-). These results were consistent with the primary right breast cancer characteristics, thus supporting lesion metastasis from breast cancer. CONCLUSION: The brachial plexus metastasis from breast cancer is uncommon. Ultrasound has great value in detecting brachial plexus metastasis of breast cancer. It is an easy, non-invasive and affordable method. Close attention should be paid to new grown out lesions in those patients who had a history of breast cancer when doing ultrasound review.

CycleDNN - A Novel Deep Neural Network Model for CETSA Feature Prediction cross Cell Lines.

Cellular Thermal Shift Assay (CETSA) has been widely used in drug discovery, cancer cell biology, immunology, etc. One of the barriers for CETSA applications is that CETSA experiments have to be conducted on various cell lines, which is extremely time-consuming and costly. In this study, we make an effort to explore the translation of CETSA features cross cell lines, i.e., known CETSA feature of a given protein in one cell line, can we automatically predict the CETSA feature of this protein in another cell line, and vice versa? Inspired by pix2pix and CycleGAN, which perform well on image-to-image translation cross various domains in computer vision, we propose a novel deep neural network model called CycleDNN for CETSA feature translation cross cell lines. Given cell lines A and B, the proposed CycleDNN consists of two auto-encoders, the first one encodes the CETSA feature from cell line A into Z in the latent space [Formula: see text], then decodes Z into the CETSA feature in cell line B., Similarly, the second one translates the CETSA feature from cell line B to cell line A through the latent space [Formula: see text]. In such a way, the two auto-encoders form a cyclic feature translation between cell lines. The reconstructed loss, cycle-consistency loss, and latent vector regularization loss are used to guide the training of the model. The experimental results on a public CETSA dataset demonstrate the effectiveness of the proposed approach.

ADAN: An Adversarial Domain Adaptation Neural Network for Early Gastric Cancer Prediction.

Gastric cancer is a highly prevalent cancer world-wide. Accurate diagnosis of Early Gastric Cancer (EGC) is of great significance to improve the treatment and survival rate of patients. However, EGC and gastric ulcers have similar en-doscopic image characteristics, resulting in a high misdiagnosis rate. Most existing deep learning and machine learning models for EGC recognition have the disadvantages of cumbersome pre-processing steps and high leakage ratios. To address the above challenges, we propose an end-to-end Adversarial Do-main Adaptation Neural network (ADAN) for EGC prediction on endoscopic images. ADAN network consists of a source domain feature extractor, a source domain classifier, two target domain feature extractors, a target domain classifier, and a domain discriminator. A source domain feature extractor is designed to train the model on public gastrointestinal datasets, which effectively solves the problem of insufficient training data. In addition, an adaptive source-target domain mapping classifier is added to each target domain feature extractor for automatically adjusting the number of classification categories in the target domain. Experimental results show that the proposed ADAN network is superior to the most advanced methods and can accurately predict EGC in clinical practice. Clinical relevance-In this study, the EGC diagnosis model based on the adversarial domain adaptive construction will be more applicable to the real clinical scenario, with higher accuracy and sensitivity and assist the endoscopist to make more accurate diagnosis for EGC and reduce the workload.

Residual Channel Attention Network for Brain Glioma Segmentation.

A glioma is a malignant brain tumor that seriously affects cognitive functions and lowers patients' life quality. Segmentation of brain glioma is challenging because of inter-class ambiguities in tumor regions. Recently, deep learning approaches have achieved outstanding performance in the automatic segmentation of brain glioma. However, existing al-gorithms fail to exploit channel-wise feature interdependence to select semantic attributes for glioma segmentation. In this study, we implement a novel deep neural network that integrates residual channel attention modules to calibrate intermediate features for glioma segmentation. The proposed channel at-tention mechanism adaptively weights feature channel-wise to optimize the latent representation of gliomas. We evaluate our method on the established dataset BraTS2017. Experimental results indicate the superiority of our method. Clinical relevance - While existing glioma segmentation approaches do not leverage channel-wise feature dependence for feature selection our method can generate segmentation masks with higher accuracies and provide more insights on graphic patterns in brain MRI images for further clinical reference.

Malignancy Suspicious Region Guided Deep Neural Networks for Gastric Ulcer Classification.

Malignant transformation of gastric ulcer can result in gastric cancer, hence an accurate gastric ulcer classification method is of vital importance. Despite marvelous progress has been achieved in recent years, there are still many challenges in diagnosis of gastric ulcer. In this paper, we propose a mechanism to mimic gastroenterologist's behaviours based on deep learning techniques, by integrating the segmented malignancy suspicious masks with gastroscopic images for gastric ulcer classification, which instructs the model to focus on the area where symptoms occur for gastric ulcer diagnosis. Specifically, a U-Net-type deep neural network is built to segment the suspicious pathological regions from gastroscopic images, then the segmented regions are treated as an attention channel of gastroscopic images for the gastric ulcer classification by a ResNet-type deep neural network. Experiments on a real gastroscopic dataset with 900+ patient cases demonstrate that our proposed approach achieves much better performance for gastric ulcer diagnosis, compared with standard method with only gastroscopic images.

Efficacy and Safety of Ultrasound-Guided Radiofrequency Ablation for Primary Hyperparathyroidism: A Prospective Study.

OBJECTIVE: To assess the efficacy and safety of ultrasound (US)-guided radiofrequency ablation (RFA) in patients with primary hyperparathyroidism (PHPT). MATERIALS AND METHODS: This prospective study enrolled 39 participants (14 male, 25 female; mean age, 59.5 ± 15.3 [range, 18-87] years) between September 1, 2018, and January 31, 2021. All participants had parathyroid lesions causing PHPT, proven biochemically and through imaging. The imaging features of the PHPT nodules, including the shape, margin, size, composition, and location, were evaluated before treatment. Serum intact parathyroid hormone, calcium, and phosphorus levels; parathyroid nodule volume; and PHPT-related symptoms were recorded before and after treatment. We calculated the technical success, biochemical cure, and clinical cure rates for these patients. Complications were evaluated during and after the ablation. RESULTS: Complete ablation was achieved in 38 of the 39 nodules in the 39 enrolled participants. All the patients were treated in one session. The technical success rate was 97.4% (38/39). The mean follow-up duration was 13.2 ± 4.6 (range, 6.0-24.9) months. At 6 and 12 months post-RFA, the biochemical cure rates were 82.1% (32/39) and 84.4% (27/32), respectively, and the clinical cure rates were 100% (39/39) and 96.9% (31/32), respectively. Only 2.6% (1/39) of the patients had recurrent PHPT. At 1, 3, 6, and 12 months after technically successful RFA, 44.7% (17/38), 34.3% (12/35), 15.8% (6/38), and 12.5% (4/32) of participants, respectively, had elevated eucalcemic parathyroid hormone levels. Recurrent laryngeal nerve paralysis occurred in 5.1% (2/39) of the patients, who recovered spontaneously within 1-3 months. CONCLUSION: US-guided RFA was effective and safe for PHPT patients. RFA may be an alternative treatment tool for patients who cannot tolerate or refuse to undergo surgery.

Immunoprognostic model of lung adenocarcinoma and screening of sensitive drugs.

Screening of mRNAs and lncRNAs associated with prognosis and immunity of lung adenocarcinoma (LUAD) and used to construct a prognostic risk scoring model (PRS-model) for LUAD. To analyze the differences in tumor immune microenvironment between distinct risk groups of LUAD based on the model classification. The CMap database was also used to screen potential therapeutic compounds for LUAD based on the differential genes between distinct risk groups. he data from the Cancer Genome Atlas (TCGA) database. We divided the transcriptome data into a mRNA subset and a lncRNA subset, and use multiple methods to extract mRNAs and lncRNAs associated with immunity and prognosis. We further integrated the mRNA and lncRNA subsets and the corresponding clinical information, randomly divided them into training and test set according to the ratio of 5:5. Then, we performed the Cox risk proportional analysis and cross-validation on the training set to construct a LUAD risk scoring model. Based on the risk scoring model, patients were divided into distinct risk group. Moreover, we evaluate the prognostic performance of the model from the aspects of Area Under Curve (AUC) analysis, survival difference analysis, and independent prognostic analysis. We analyzed the differences in the expression of immune cells between the distinct risk groups, and also discuss the connection between immune cells and patient survival. Finally, we screened the potential therapeutic compounds of LUAD in the Connectivity Map (CMap) database based on differential gene expression profiles, and verified the compound activity by cytostatic assays. We extracted 26 mRNAs and 74 lncRNAs related to prognosis and immunity by using different screening methods. Two mRNAs (i.e., KLRC3 and RAET1E) and two lncRNAs (i.e., AL590226.1 and LINC00941) and their risk coefficients were finally used to construct the PRS-model. The risk score positions of the training and test set were 1.01056590 and 1.00925190, respectively. The expression of mRNAs involved in model construction differed significantly between the distinct risk population. The one-year ROC areas on the training and test sets were 0.735 and 0.681. There was a significant difference in the survival rate of the two groups of patients. The PRS-model had independent predictive capabilities in both training and test sets. Among them, in the group with low expression of M1 macrophages and resting NK cells, LUAD patients survived longer. In contrast, the monocyte expression up-regulated group survived longer. In the CMap drug screening, three LUAD therapeutic compounds, such as resveratrol, methotrexate, and phenoxybenzamine, scored the highest. In addition, these compounds had significant inhibitory effects on the LUAD A549 cell lines. The LUAD risk score model constructed using the expression of KLRC3, RAET1E, AL590226.1, LINC00941 and their risk coefficients had a good independent prognostic power. The optimal LUAD therapeutic compounds screened in the CMap database: resveratrol, methotrexate and phenoxybenzamine, all showed significant inhibitory effects on LUAD A549 cell lines.

Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in hepatocellular carcinoma: the PLANET study.

Intra-tumor heterogeneity (ITH) is a key challenge in cancer treatment, but previous studies have focused mainly on the genomic alterations without exploring phenotypic (transcriptomic and immune) heterogeneity. Using one of the largest prospective surgical cohorts for hepatocellular carcinoma (HCC) with multi-region sampling, we sequenced whole genomes and paired transcriptomes from 67 HCC patients (331 samples). We found that while genomic ITH was rather constant across stages, phenotypic ITH had a very different trajectory and quickly diversified in stage II patients. Most strikingly, 30% of patients were found to contain more than one transcriptomic subtype within a single tumor. Such phenotypic ITH was found to be much more informative in predicting patient survival than genomic ITH and explains the poor efficacy of single-target systemic therapies in HCC. Taken together, we not only revealed an unprecedentedly dynamic landscape of phenotypic heterogeneity in HCC, but also highlighted the importance of studying phenotypic evolution across cancer types.

Bioresponsive Nanomaterials: Recent Advances in Cancer Multimodal Imaging and Imaging-Guided Therapy.

Cancer is a serious health problem which increasingly causes morbidity and mortality worldwide. It causes abnormal and uncontrolled cell division. Traditional cancer treatments include surgery, chemotherapy, radiotherapy and so on. These traditional therapies suffer from high toxicity and arouse safety concern in normal area and have difficulty in accurately targeting tumour. Recently, a variety of nanomaterials could be used for cancer diagnosis and therapy. Nanomaterials have several advantages, e.g., high concentration in tumour via targeting design, reduced toxicity in normal area and controlled drug release after various rational designs. They can combine with many types of biomaterials in order to improve biocompatibility. In this review, we outlined the latest research on the use of bioresponsive nanomaterials for various cancer imaging modalities (magnetic resonance imaging, positron emission tomography and phototacoustic imaging) and imaging-guided therapy means (chemotherapy, radiotherapy, photothermal therapy and photodynamic therapy), followed by discussing the challenges and future perspectives of this bioresponsive nanomaterials in biomedicine.

Radiofrequency ablation for primary hyperparathyroidism and risk factors for postablative eucalcemic parathyroid hormone elevation.

OBJECTIVE: To investigate the efficacy of radiofrequency ablation (RFA) as a treatment option for primary hyperparathyroidism (pHPT) and risk factors for postablative eucalcemic parathyroid hormone elevation (ePTH). METHODS: This retrospective study included 51 patients with pHPT who underwent RFA. The patients were divided into the ePTH and normal PTH groups, based on the serum intact parathyroid hormone (iPTH) level one month after ablation. Serum iPTH, calcium, and phosphorus levels, and the volume reduction rates (VRR) of the parathyroid glands were compared between the groups at each follow-up point. Risk factors for ePTH at one month after ablation were examined. RESULTS: After RFA, one (2%) patient had persistent pHPT, and 50 (98%) patients were cured. The incidence rates of ePTH at 1, 3, 6, and 12 months were 48%, 30%, 20%, and 16%, respectively. Serum iPTH levels in the ePTH group were higher than those in the normal PTH group at each follow-up point (all p < 0.05), except 1 day after ablation (p > 0.05). Serum calcium and phosphorus levels, and the VRR of the glands were comparable in both groups at each follow-up point (all p > 0.05), except for calcium levels 3 days after RFA (p < 0.05). Baseline iPTH (odds ratio, 1.067; p = 0.045) and calcium (odds ratio, 3.923; p = 0.038) levels were independent risk factors for ePTH 1 month after RFA. CONCLUSIONS: RFA is safe and effective for the treatment of pHPT. Moreover, ePTH occurrence after RFA was associated with baseline iPTH and calcium levels and did not increase the risk of recurrent pHPT.

Ultrasound-guided needle release plus corticosteroid injection of superficial radial nerve: A case report.

BACKGROUND: The radial nerve (RN) splits into two main branches at the elbow: The superficial branch of RN (SBRN) and the deep branch of RN. The SBRN can be easily damaged in acute trauma due to its superficial feature. CASE SUMMARY: A 55-year-old male patient injured his right wrist 10 mo ago. Debridement, suturing and bandaging were performed in the emergency room. Six months after the scar had healed, he felt numbness and tingling in the dorsal surface of the thumb of the right hand. So the surgery of resection and SBRN anastomosis were performed. The pathological findings showed it as traumatic neuroma. Four months after surgery, the patient felt numbness and tingling in the right dorsal surface of the thumb again. The tenderness was marked in the operated area. Ultrasound indicated that the SBRN was adhered to the surrounding tissue. The patient refused further surgical treatment and underwent ultrasound-guided needle release plus corticosteroid injection of the SBRN. Four weeks later, the tenderness in the surgical area was reduced by 70%, the numbness in the dorsal surface of the thumb of the right hand was reduced by 40% and the nerve swelling evaluated by ultrasound was reduced. Four months passed, he did not feel any numbness or tingling sensation of his right wrist. This is the first report of ultrasound-guided needle release plus corticosteroid injection of the SBRN. CONCLUSION: Ultrasound can evaluate the condition of the RN, and the relationship with surrounding tissues. Ultrasound-guided needle release plus corticosteroid injection is an effective and safe treatment for SBRN adhesion.

Phase-Changeable Nanoparticle-Mediated Energy Conversion Promotes Highly Efficient High-Intensity Focused Ultrasound Ablation.

This review describes how phase-changeable nanoparticles enable highly-efficient high-intensity focused ultrasound ablation (HIFU). HIFU is effective in the clinical treatment of solid malignant tumors; however, it has intrinsic disadvantages for treating some deep lesions, such as damage to surrounding normal tissues. When phase-changeable nanoparticles are used in HIFU treatment, they could serve as good synergistic agents because they are transported in the blood and permeated and accumulated effectively in tissues. HIFU's thermal effects can trigger nanoparticles to undergo a special phase transition, thus enhancing HIFU ablation efficiency. Nanoparticles can also carry anticancer agents and release them in the targeted area to achieve chemo-synergistic therapy response. Although the formation of nanoparticles is complicated and HIFU applications are still in an early stage, the potential for their use in synergy with HIFU treatment shows promising results.

Use of Ultrasound to Observe Mycosis Fungoides: A Case Report and Review of Literature.

BACKGROUND: Mycosis fungoides (MF) is the most common form of cutaneous T-cell lymphoma with many clinicopathological variants, thus difficult to diagnose in its early stages. CASE PRESENTATION: This case report is about a 76 years old Chinese woman presented with 2 years history of erythematous plaque on the lateral right thigh; after combining clinical manifestations with results of pathological examinations, it is consistent with the diagnosis of MF. DISCUSSION: Mycosis fungoides (MF) is the most common form of cutaneous T-cell lymphoma. The patient in this case had a long course of disease and repeated attacks. Ultrasound shows a small patch of liquid dark area of the lesion. Color Doppler image shows rich blood flow, which just looks like lacustrine. Thick and nourishing blood vessels could be seen in the depth. CONCLUSION: Our case report using ultrasound to observe MF and demonstrate that ultrasound is helpful in diagnosing and evaluating effectiveness in treating MF.

Study of ultrasound-guided percutaneous microwave ablation combined with portal vein embolization for rapid future liver remnant increase of planned hepatectomy.

Purpose: To evaluate the efficacy of ultrasound-guided percutaneous microwave ablation (PMA) combined with portal vein embolization (PVE) for planned hepatectomy. Methods: We retrospectively reviewed data of 18 patients with multiple right liver tumors or hilar tumor of liver invades the surrounding tissue and insufficient future liver remnant (FLR) for hepatectomy from July 2015 to March 2017. Ultrasound-guided PMA was performed by using PMCT cold circulation microwave treatment apparatus. PVE was performed after PMA. The increase of FLR was evaluated by computed tomography (CT) 6-22 days after PVE. The proportion of FLR, increase in the amplitude of FLR, procedure-related complications, perioperative morbidity and mortality, and overall survival (OS) rates, the median survival time were analyzed. Results: The median volume of FLR before PMA and PVE was 369.7 ml (range: 239.4-493.1 ml). After a median waiting period of 11.5 days (range: 6-22 days), the median volume of FLR was increased to 523.4 ml (range: 355.4-833.3 ml). The changes in FLR before and after PMA and PVE were statistically significant (p<0.001). No serious perioperative complications or mortality were found. After a median follow-up time of 51.0 months (range: 2-54 months), the 6-month, 1-year, 2-year, 3-year and 4-year survival rates were 88.9%, 72.2%, 44.4%, 33.3%, 22.2%, respectively, and the median survival time was 15.0 ± 7.1 months. Conclusion: PMA combined with PVE increases FLR rapidly, avoids touching malignant tumors, and produces fewer procedure-related complications. It appears safe and efficacious for planned hepatectomy.

Mitochondria-Targeted Nanocarriers Promote Highly Efficient Cancer Therapy: A Review.

Mitochondria are the primary organelles which can produce adenosine triphosphate (ATP). They play vital roles in maintaining normal functions. They also regulated apoptotic pathways of cancer cells. Given that, designing therapeutic agents that precisely target mitochondria is of great importance for cancer treatment. Nanocarriers can combine the mitochondria with other therapeutic modalities in cancer treatment, thus showing great potential to cancer therapy in the past few years. Herein, we summarized lipophilic cation- and peptide-based nanosystems for mitochondria targeting. This review described how mitochondria-targeted nanocarriers promoted highly efficient cancer treatment in photodynamic therapy (PDT), chemotherapy, combined immunotherapy, and sonodynamic therapy (SDT). We further discussed mitochondria-targeted nanocarriers' major challenges and future prospects in clinical cancer treatment.

Multi-Slice Dense-Sparse Learning for Efficient Liver and Tumor Segmentation.

Accurate automatic liver and tumor segmentation plays a vital role in treatment planning and disease monitoring. Recently, deep convolutional neural network (DCNNs) has obtained tremendous success in 2D and 3D medical image segmentation. However, 2D DCNNs cannot fully leverage the inter-slice information, while 3D DCNNs are computationally expensive and memory intensive. To address these issues, we first propose a novel dense-sparse training flow from a data perspective, in which, densely adjacent slices and sparsely adjacent slices are extracted as inputs for regularizing DCNNs, thereby improving the model performance. Moreover, we design a 2.5D light-weight nnU-Net from a network perspective, in which, depthwise separable convolutions are adopted to improve the efficiency. Extensive experiments on the LiTS dataset have demonstrated the superiority of the proposed method.Clinical relevance- The proposed method can effectively segment livers and tumors from CT scans with low complexity, which can be easily implemented into clinical practice.