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1.
Sensors (Basel) ; 24(11)2024 May 30.
Article in English | MEDLINE | ID: mdl-38894328

ABSTRACT

OBJECTIVE: Aiming at the shortcomings of artificial surgical path planning for the thermal ablation of liver tumors, such as the time-consuming and labor-consuming process, and relying heavily on doctors' puncture experience, an automatic path-planning system for thermal ablation of liver tumors based on CT images is designed and implemented. METHODS: The system mainly includes three modules: image segmentation and three-dimensional reconstruction, automatic surgical path planning, and image information management. Through organ segmentation and three- dimensional reconstruction based on CT images, the personalized abdominal spatial anatomical structure of patients is obtained, which is convenient for surgical path planning. The weighted summation method based on clinical constraints and the concept of Pareto optimality are used to solve the multi-objective optimization problem, screen the optimal needle entry path, and realize the automatic planning of the thermal ablation path. The image information database was established to store the information related to the surgical path. RESULTS: In the discussion with clinicians, more than 78% of the paths generated by the planning system were considered to be effective, and the efficiency of system path planning is higher than doctors' planning efficiency. CONCLUSION: After improvement, the system can be used for the planning of the thermal ablation path of a liver tumor and has certain clinical application value.


Subject(s)
Liver Neoplasms , Tomography, X-Ray Computed , Humans , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/surgery , Liver Neoplasms/pathology , Tomography, X-Ray Computed/methods , Imaging, Three-Dimensional/methods , Ablation Techniques/methods , Algorithms , Image Processing, Computer-Assisted/methods , Surgery, Computer-Assisted/methods , Liver/surgery , Liver/diagnostic imaging
2.
Sensors (Basel) ; 24(11)2024 Jun 05.
Article in English | MEDLINE | ID: mdl-38894444

ABSTRACT

This work describes a sapphire cryo-applicator with the ability to sense tissue freezing depth during cryosurgery by illumination of tissue and analyzing diffuse optical signals in a steady-state regime. The applicator was manufactured by the crystal growth technique and has several spatially resolved internal channels for accommodating optical fibers. The method of reconstructing freezing depth proposed in this work requires one illumination and two detection channels. The analysis of the detected intensities yields the estimation of the time evolution of the effective attenuation coefficient, which is compared with the theoretically calculated values obtained for a number of combinations of tissue parameters. The experimental test of the proposed applicator and approach for freezing depth reconstruction was performed using gelatin-based tissue phantom and rat liver tissue in vivo. It revealed the ability to estimate depth up to 8 mm. The in vivo study confirmed the feasibility of the applicator to sense the freezing depth of living tissues despite the possible diversity of their optical parameters. The results justify the potential of the described design of a sapphire instrument for cryosurgery.


Subject(s)
Aluminum Oxide , Cryosurgery , Freezing , Liver , Phantoms, Imaging , Animals , Cryosurgery/methods , Rats , Liver/surgery , Liver/diagnostic imaging , Aluminum Oxide/chemistry
3.
Cancer Imaging ; 24(1): 77, 2024 Jun 17.
Article in English | MEDLINE | ID: mdl-38886836

ABSTRACT

BACKGROUND: The Response Evaluation Criteria in Solid Tumors (RECIST) are often inadequate for the early assessment of the response to cancer therapy, particularly bevacizumab-based chemotherapy. In a first cohort of patients with colorectal cancer liver metastases (CRLM), we showed that variations of the tumor-to-liver density (TTLD) ratio and modified size-based criteria determined using computed tomography (CT) data at the first restaging were better prognostic criteria than the RECIST. The aims of this study were to confirm the relevance of these radiological biomarkers as early predictors of the long-term clinical outcome and to assess their correlation with contrast-enhanced ultrasound (CEUS) parameters in a new patient cohort. METHODS: In this post-hoc study of the multicenter STIC-AVASTIN trial, we retrospectively reviewed CT data of patients with CRLM treated with bevacizumab-based regimens. We determined the size, density and TTLD ratio of target liver lesions at baseline and at the first restaging and also performed a morphologic evaluation according to the MD Anderson criteria. We assessed the correlation of these parameters with progression-free survival (PFS) and overall survival (OS) using the log-rank test and a Cox proportional hazard model. We also examined the association between TTLD ratio and quantitative CEUS parameters. RESULTS: This analysis concerned 79 of the 137 patients included in the STIC-AVASTIN trial. PFS and OS were significantly longer in patients with tumor size reduction > 15% at first restaging, but were not correlated with TTLD ratio variations. However, PFS was longer in patients with TTLD ratio > 0.6 at baseline and first restaging than in those who did not reach this threshold. In the multivariate analysis, only baseline TTLD ratio > 0.6 was a significant survival predictor. TTLD ratio > 0.6 was associated with improved perfusion parameters. CONCLUSIONS: Although TTLD ratio variations did not correlate with the long-term clinical outcomes, TTLD absolute values remained a good predictor of survival at baseline and first restaging, and may reflect tumor microvascular features that might influence bevacizumab-based treatment efficiency. TRIAL REGISTRATION: NCT00489697, registration number of the STIC-AVASTIN trial.


Subject(s)
Bevacizumab , Colorectal Neoplasms , Liver Neoplasms , Humans , Bevacizumab/therapeutic use , Colorectal Neoplasms/drug therapy , Colorectal Neoplasms/pathology , Colorectal Neoplasms/mortality , Liver Neoplasms/secondary , Liver Neoplasms/drug therapy , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/mortality , Male , Female , Middle Aged , Aged , Retrospective Studies , Prognosis , Tomography, X-Ray Computed/methods , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Adult , Ultrasonography/methods , Liver/diagnostic imaging , Liver/pathology
4.
Ultrasound Q ; 40(3)2024 Sep 01.
Article in English | MEDLINE | ID: mdl-38889400

ABSTRACT

METHODS: Twenty-three peer-reviewed articles on HRI measurements published between 2018 through 2023 were reviewed, and 11 were selected based on common subjects. The search terms included "hepatorenal index," "HRI," "HRI ultrasound," "hepatorenal ultrasound index," and "HRI ultrasound measurement."Three common subject areas were identified in the literature and synthesized down to 11 articles. The common subjects identified were HRI technique, HRI limitations, and HRI diagnostic accuracy. The matrix provided a quick overview of the general information in each piece, aiding in the paper's overall organization. Thirteen articles were rejected as not relevant or out of date. The research question leading this review was, "What does the literature say about the value of HRI in determining moderate to severe hepatic steatosis?" RESULTS: The literature revealed that HRI could be valuable in determining moderate to severe hepatic steatosis. HRI could not accurately determine normal or mild steatosis and has several limitations. CONCLUSIONS: HRI is a more objective method for determining the degree of hepatic steatosis compared with traditional B-mode ultrasound scoring and does not require additional or specialized equipment. Many studies excluded patients with various liver diseases, which may not make HRI a practical tool for clinical usefulness. Further studies should be conducted with larger patient cohorts, a greater degree of hepatic steatosis, and determine specific standardized cutoff values.


Subject(s)
Fatty Liver , Liver , Ultrasonography , Humans , Ultrasonography/methods , Fatty Liver/diagnostic imaging , Liver/diagnostic imaging , Kidney/diagnostic imaging , Severity of Illness Index , Reproducibility of Results
5.
Medicine (Baltimore) ; 103(23): e38444, 2024 Jun 07.
Article in English | MEDLINE | ID: mdl-38847728

ABSTRACT

To investigate changes in skeletal muscle mass and fat fraction in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) and type 2 diabetes mellitus (T2DM) undergoing treatment with Semaglutide for 6months. This single-arm pilot study included 21 patients with MASLD who received semaglutide for T2DM. Body weight, metabolic parameters, liver enzymes, fibrosis markers, skeletal muscle index (cm2/m2), and fat fraction (%) at the L3 level using the two-point Dixon method on magnetic resonance imaging (MRI), as well as liver steatosis and liver stiffness assessed using MRI-based proton density fat fraction (MRI-PDFF) and MR elastography, respectively, were prospectively examined before and 6 months after semaglutide administration. The mean age of the patients was 53 years and 47.6% were females. The median liver steatosis-fraction (%) and skeletal muscle steatosis-fraction values (%) significantly decreased (22.0 vs 12.0; P = .0014) and (12.8 vs 9.9; P = .0416) at baseline and 6 months, respectively, while maintaining muscle mass during treatment. Semaglutide also dramatically reduced hemoglobin A1c (%) (6.8 vs 5.8, P = .0003), AST (IU/L) (54 vs 26, P < .0001), ALT (IU/L) (80 vs 34, P = .0004), and γ-GTP (IU/L) levels (64 vs 34, P = .0007). Although not statistically significant, Body weight (kg) (79.9 vs 77.4), body mass index (BMI) (kg/m2) (28.9 vs 27.6), and liver stiffness (kPa) (28.9 vs 27.6) showed a decreasing trend. Fibrosis markers such as M2BPGi, type IV collagen, and skeletal muscle area did not differ. Semaglutide demonstrated favorable effects on liver and skeletal muscle steatosis, promoting improved liver function and diabetic status.


Subject(s)
Diabetes Mellitus, Type 2 , Glucagon-Like Peptides , Liver , Muscle, Skeletal , Humans , Female , Middle Aged , Male , Diabetes Mellitus, Type 2/drug therapy , Prospective Studies , Muscle, Skeletal/drug effects , Glucagon-Like Peptides/therapeutic use , Glucagon-Like Peptides/administration & dosage , Pilot Projects , Liver/drug effects , Liver/diagnostic imaging , Liver/pathology , Hypoglycemic Agents/therapeutic use , Fatty Liver/drug therapy , Adult , Glucagon-Like Peptide-1 Receptor/agonists , Magnetic Resonance Imaging , Elasticity Imaging Techniques , Glycated Hemoglobin/drug effects , Glycated Hemoglobin/analysis , Aged
6.
Math Biosci Eng ; 21(4): 5735-5761, 2024 Apr 24.
Article in English | MEDLINE | ID: mdl-38872556

ABSTRACT

Precise segmentation of liver tumors from computed tomography (CT) scans is a prerequisite step in various clinical applications. Multi-phase CT imaging enhances tumor characterization, thereby assisting radiologists in accurate identification. However, existing automatic liver tumor segmentation models did not fully exploit multi-phase information and lacked the capability to capture global information. In this study, we developed a pioneering multi-phase feature interaction Transformer network (MI-TransSeg) for accurate liver tumor segmentation and a subsequent microvascular invasion (MVI) assessment in contrast-enhanced CT images. In the proposed network, an efficient multi-phase features interaction module was introduced to enable bi-directional feature interaction among multiple phases, thus maximally exploiting the available multi-phase information. To enhance the model's capability to extract global information, a hierarchical transformer-based encoder and decoder architecture was designed. Importantly, we devised a multi-resolution scales feature aggregation strategy (MSFA) to optimize the parameters and performance of the proposed model. Subsequent to segmentation, the liver tumor masks generated by MI-TransSeg were applied to extract radiomic features for the clinical applications of the MVI assessment. With Institutional Review Board (IRB) approval, a clinical multi-phase contrast-enhanced CT abdominal dataset was collected that included 164 patients with liver tumors. The experimental results demonstrated that the proposed MI-TransSeg was superior to various state-of-the-art methods. Additionally, we found that the tumor mask predicted by our method showed promising potential in the assessment of microvascular invasion. In conclusion, MI-TransSeg presents an innovative paradigm for the segmentation of complex liver tumors, thus underscoring the significance of multi-phase CT data exploitation. The proposed MI-TransSeg network has the potential to assist radiologists in diagnosing liver tumors and assessing microvascular invasion.


Subject(s)
Algorithms , Contrast Media , Liver Neoplasms , Microvessels , Tomography, X-Ray Computed , Humans , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/pathology , Liver Neoplasms/blood supply , Microvessels/diagnostic imaging , Microvessels/pathology , Neoplasm Invasiveness , Image Processing, Computer-Assisted/methods , Liver/diagnostic imaging , Liver/pathology , Liver/blood supply , Radiographic Image Interpretation, Computer-Assisted/methods , Male , Female
7.
Curr Med Imaging ; 20(1): e15734056267873, 2024.
Article in English | MEDLINE | ID: mdl-38874040

ABSTRACT

OBJECTIVE: To compare the diagnostic value of multi-slice computed tomography (CT) and magnetic resonance imaging (MRI) in liver tumors. METHODS: Retrospective selection of CT and MRI imaging data from 109 cases of liver tumors treated in our hospital from January 2020 to March 2023. The selection was determined through pathological examination. RESULTS: According to the pathological examination results, 61 cases were benign tumors, and 48 cases were malignant tumors. The hepatic portal flow (HPF), hepatic artery perfusion index (HPI) and hepatic artery perfusion (HAF) of malignant tumors were significantly lower than in benign tumors (P<0.05). The signal enhancement ratio of malignant tumors was significantly higher than in benign tumors, and the peak time was significantly lower than in benign tumors (P<0.05). The sensitivity (97.92%) and accuracy (97.25%) of the combined examination were significantly higher than those of MRI (83.33%, 90.83%) or CT alone (81.25%, 88.99%) (P<0.05). CONCLUSION: CT and MRI have high application value in the diagnosis and evaluation of liver tumors, and the combination of these two methods can further improve diagnostic sensitivity and accuracy, providing an objective reference for early diagnosis and treatment of liver cancer.

.


Subject(s)
Liver Neoplasms , Magnetic Resonance Imaging , Tomography, X-Ray Computed , Humans , Liver Neoplasms/diagnostic imaging , Magnetic Resonance Imaging/methods , Retrospective Studies , Male , Female , Middle Aged , Tomography, X-Ray Computed/methods , Adult , Aged , Case-Control Studies , Sensitivity and Specificity , Hepatic Artery/diagnostic imaging , Liver/diagnostic imaging
8.
J Med Primatol ; 53(3): e12712, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38825748

ABSTRACT

BACKGROUND: Platynosomiasis in non-human primates kept under human care causes chronic disease of the bile ducts and liver, which initially presents with nonspecific signs and can culminate in the death of the animal. Diagnosing this disease is a challenge, and an ultrasound examination can be an excellent tool when it is suspected. METHODS: This study describes the ultrasound findings from 57 marmosets with suspected infection by Platynosomum sp., the correlated hepatobiliary changes, and the anatomopathological findings that confirmed the occurrence of platynosomiasis. RESULTS: In six marmosets (one C. aurita, two C. jacchus, and three Callithrix sp.), Platynosomum infection was confirmed macroscopically (presence of adult trematodes in the gallbladder) and microscopically (adults, larvae, and eggs in histological examinations and eggs in bile and feces). These findings were compatible with the hepatobiliary changes and with images suggestive of parasitic structures in ante-mortem assessments. CONCLUSION: Ultrasound examination demonstrated its usefulness within the clinical routine for investigating this parasitosis.


Subject(s)
Monkey Diseases , Trematode Infections , Ultrasonography , Animals , Ultrasonography/veterinary , Ultrasonography/methods , Monkey Diseases/diagnostic imaging , Monkey Diseases/parasitology , Monkey Diseases/pathology , Monkey Diseases/diagnosis , Trematode Infections/veterinary , Trematode Infections/diagnostic imaging , Trematode Infections/diagnosis , Trematode Infections/parasitology , Trematode Infections/pathology , Male , Female , Callithrix , Liver/pathology , Liver/diagnostic imaging , Liver/parasitology
9.
Int J Mol Sci ; 25(11)2024 May 29.
Article in English | MEDLINE | ID: mdl-38892130

ABSTRACT

Acetaminophen overdose is a leading cause of acute liver failure (ALF), and effective treatment depends on early prediction of disease progression. ALF diagnosis currently requires blood collection 24-72 h after APAP ingestion, necessitating repeated tests and hospitalization. Here, we assessed earlier ALF diagnosis using positron emission tomography (PET) imaging of translocator proteins (TSPOs), which are involved in molecular transport, oxidative stress, apoptosis, and energy metabolism, with the radiotracer [18F]GE180. We intraperitoneally administered propacetamol hydrochloride to male C57BL/6 mice to induce ALF. We performed in vivo PET/CT imaging 3 h later using the TSPO-specific radiotracer [18F]GE180 and quantitatively analyzed the PET images by determining the averaged standardized uptake value (SUVav) in the liver parenchyma. We assessed liver TSPO expression levels via real-time polymerase chain reaction, Western blotting, and immunohistochemistry. [18F]GE180 PET imaging 3 h after propacetamol administration (1500 mg/kg) significantly increased liver SUVav compared to controls (p = 0.001). Analyses showed a 10-fold and 4-fold increase in TSPO gene and protein expression, respectively, in the liver, 3 h after propacetamol induction compared to controls. [18F]GE180 PET visualized and quantified propacetamol-induced ALF through TSPO overexpression. These findings highlight TSPO PET's potential as a non-invasive imaging biomarker for early-stage ALF.


Subject(s)
Acetaminophen , Liver Failure, Acute , Mice, Inbred C57BL , Receptors, GABA , Animals , Liver Failure, Acute/chemically induced , Liver Failure, Acute/diagnostic imaging , Liver Failure, Acute/metabolism , Acetaminophen/adverse effects , Male , Mice , Receptors, GABA/metabolism , Receptors, GABA/genetics , Positron-Emission Tomography/methods , Liver/metabolism , Liver/diagnostic imaging , Positron Emission Tomography Computed Tomography/methods , Fluorine Radioisotopes , Radiopharmaceuticals/metabolism , Disease Models, Animal , Carbazoles
10.
Sci Rep ; 14(1): 13352, 2024 06 10.
Article in English | MEDLINE | ID: mdl-38858467

ABSTRACT

Liver cancer ranks as the fifth leading cause of cancer-related death globally. Direct intratumoral injections of anti-cancer therapeutics may improve therapeutic efficacy and mitigate adverse effects compared to intravenous injections. Some challenges of intratumoral injections are that the liquid drug formulation may not remain localized and have unpredictable volumetric distribution. Thus, drug delivery varies widely, highly-dependent upon technique. An X-ray imageable poloxamer 407 (POL)-based drug delivery gel was developed and characterized, enabling real-time feedback. Utilizing three needle devices, POL or a control iodinated contrast solution were injected into an ex vivo bovine liver. The 3D distribution was assessed with cone beam computed tomography (CBCT). The 3D distribution of POL gels demonstrated localized spherical morphologies regardless of the injection rate. In addition, the gel 3D conformal distribution could be intentionally altered, depending on the injection technique. When doxorubicin (DOX) was loaded into the POL and injected, DOX distribution on optical imaging matched iodine distribution on CBCT suggesting spatial alignment of DOX and iodine localization in tissue. The controllability and localized deposition of this formulation may ultimately reduce the dependence on operator technique, reduce systemic side effects, and facilitate reproducibility across treatments, through more predictable standardized delivery.


Subject(s)
Cone-Beam Computed Tomography , Doxorubicin , Drug Delivery Systems , Hydrogels , Needles , Poloxamer , Hydrogels/chemistry , Animals , Doxorubicin/administration & dosage , Doxorubicin/chemistry , Doxorubicin/pharmacology , Drug Delivery Systems/methods , Poloxamer/chemistry , Cattle , Cone-Beam Computed Tomography/methods , Liver/diagnostic imaging , Liver/metabolism
11.
Comput Biol Med ; 177: 108625, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38823365

ABSTRACT

Liver segmentation is a fundamental prerequisite for the diagnosis and surgical planning of hepatocellular carcinoma. Traditionally, the liver contour is drawn manually by radiologists using a slice-by-slice method. However, this process is time-consuming and error-prone, depending on the radiologist's experience. In this paper, we propose a new end-to-end automatic liver segmentation framework, named ResTransUNet, which exploits the transformer's ability to capture global context for remote interactions and spatial relationships, as well as the excellent performance of the original U-Net architecture. The main contribution of this paper lies in proposing a novel fusion network that combines Unet and Transformer architectures. In the encoding structure, a dual-path approach is utilized, where features are extracted separately using both convolutional neural networks (CNNs) and Transformer networks. Additionally, an effective feature enhancement unit is designed to transfer the global features extracted by the Transformer network to the CNN for feature enhancement. This model aims to address the drawbacks of traditional Unet-based methods, such as feature loss during encoding and poor capture of global features. Moreover, it avoids the disadvantages of pure Transformer models, which suffer from large parameter sizes and high computational complexity. The experimental results on the LiTS2017 dataset demonstrate remarkable performance for our proposed model, with Dice coefficients, volumetric overlap error (VOE), and relative volume difference (RVD) values for liver segmentation reaching 0.9535, 0.0804, and -0.0007, respectively. Furthermore, to further validate the model's generalization capability, we conducted tests on the 3Dircadb, Chaos, and Sliver07 datasets. The experimental results demonstrate that the proposed method outperforms other closely related models with higher liver segmentation accuracy. In addition, significant improvements can be achieved by applying our method when handling liver segmentation with small and discontinuous liver regions, as well as blurred liver boundaries. The code is available at the website: https://github.com/Jouiry/ResTransUNet.


Subject(s)
Liver , Neural Networks, Computer , Tomography, X-Ray Computed , Humans , Liver/diagnostic imaging , Tomography, X-Ray Computed/methods , Liver Neoplasms/diagnostic imaging , Carcinoma, Hepatocellular/diagnostic imaging , Algorithms
12.
Med Image Anal ; 96: 103221, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38824864

ABSTRACT

Image-guided surgery collocates patient-specific data with the physical environment to facilitate surgical decision making. Unfortunately, these guidance systems commonly become compromised by intraoperative soft-tissue deformations. Nonrigid image-to-physical registration methods have been proposed to compensate for deformations, but clinical utility requires compatibility of these techniques with data sparsity and temporal constraints in the operating room. While finite element models can be effective in sparse data scenarios, computation time remains a limitation to widespread deployment. This paper proposes a registration algorithm that uses regularized Kelvinlets, which are analytical solutions to linear elasticity in an infinite domain, to overcome these barriers. This algorithm is demonstrated and compared to finite element-based registration on two datasets: a phantom liver deformation dataset and an in vivo breast deformation dataset. The regularized Kelvinlets algorithm resulted in a significant reduction in computation time compared to the finite element method. Accuracy as evaluated by target registration error was comparable between methods. Average target registration errors were 4.6 ± 1.0 and 3.2 ± 0.8 mm on the liver dataset and 5.4 ± 1.4 and 6.4 ± 1.5 mm on the breast dataset for the regularized Kelvinlets and finite element method, respectively. Limitations of regularized Kelvinlets include the lack of organ-specific geometry and the assumptions of linear elasticity and infinitesimal strain. Despite limitations, this work demonstrates the generalizability of regularized Kelvinlets registration on two soft-tissue elastic organs. This method may improve and accelerate registration for image-guided surgery, and it shows the potential of using regularized Kelvinlets on medical imaging data.


Subject(s)
Algorithms , Finite Element Analysis , Liver , Phantoms, Imaging , Humans , Liver/diagnostic imaging , Female , Surgery, Computer-Assisted/methods , Breast/diagnostic imaging , Reproducibility of Results , Image Interpretation, Computer-Assisted/methods , Sensitivity and Specificity
13.
Med Image Anal ; 96: 103212, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38830326

ABSTRACT

Deformable image registration is an essential component of medical image analysis and plays an irreplaceable role in clinical practice. In recent years, deep learning-based registration methods have demonstrated significant improvements in convenience, robustness and execution time compared to traditional algorithms. However, registering images with large displacements, such as those of the liver organ, remains underexplored and challenging. In this study, we present a novel convolutional neural network (CNN)-based unsupervised learning registration method, Cascaded Multi-scale Spatial-Channel Attention-guided Network (CMAN), which addresses the challenge of large deformation fields using a double coarse-to-fine registration approach. The main contributions of CMAN include: (i) local coarse-to-fine registration in the base network, which generates the displacement field for each resolution and progressively propagates these local deformations as auxiliary information for the final deformation field; (ii) global coarse-to-fine registration, which stacks multiple base networks for sequential warping, thereby incorporating richer multi-layer contextual details into the final deformation field; (iii) integration of the spatial-channel attention module in the decoder stage, which better highlights important features and improves the quality of feature maps. The proposed network was trained using two public datasets and evaluated on another public dataset as well as a private dataset across several experimental scenarios. We compared CMAN with four state-of-the-art CNN-based registration methods and two well-known traditional algorithms. The results show that the proposed double coarse-to-fine registration strategy outperforms other methods in most registration evaluation metrics. In conclusion, CMAN can effectively handle the large-deformation registration problem and show potential for application in clinical practice. The source code is made publicly available at https://github.com/LocPham263/CMAN.git.


Subject(s)
Imaging, Three-Dimensional , Liver , Neural Networks, Computer , Tomography, X-Ray Computed , Humans , Tomography, X-Ray Computed/methods , Liver/diagnostic imaging , Imaging, Three-Dimensional/methods , Algorithms , Deep Learning , Radiographic Image Interpretation, Computer-Assisted/methods
14.
Clin Imaging ; 112: 110209, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38833916

ABSTRACT

PURPOSE: This meta-analysis aimed to compare the diagnostic effectiveness of [18F]FDG PET/CT with that of [18F]FDG PET/MRI in terms of identifying liver metastasis in patients with primary cancer. METHODS: PubMed, Embase, Web of Science, and the Cochrane Library were searched, and studies evaluating the diagnostic efficacy of [18F]FDG PET/CT and [18F]FDG PET/MRI in patients with liver metastasis of primary cancer were included. We used a random effects model to analyze their sensitivity and specificity. Subgroup analyses and corresponding meta-regressions focusing on race, image analysis, study design, and analysis methodologies were conducted. Cochrane Q and I2 statistics were used to assess intra-group and inter-group heterogeneity. RESULTS: Seven articles with 343 patients were included in this meta-analysis. The sensitivity of [18F]FDG PET/CT was 0.82 (95 % CI: 0.63-0.96), and that of [18F]FDG PET/MRI was 0.91 (95 % CI: 0.82-0.98); there was no significant difference between the two methods (P = 0.32). Similarly, both methods showed equal specificity: 1.00 (95 % CI: 0.95-1.00) for [18F]FDG PET/CT and 1.00 (95 % CI: 0.96-1.00) for [18F]FDG PET/MRI, and thus, there was no significant difference between the methods (P = 0.41). Furthermore, the subgroup analyses revealed no differences. Meta-regression analysis revealed that race was a potential source of heterogeneity for [18F]FDG PET/CT (P = 0.01), while image analysis and contrast agent were found to be potential sources of heterogeneity for [18F]FDG PET/MRI (P = 0.02). CONCLUSIONS: [18F]FDG PET/MRI has similar sensitivity and specificity to [18F]FDG PET/CT for detecting liver metastasis of primary cancer in both the general population and in subgroups. [18F]FDG PET/CT may be a more cost-effective option. However, the conclusions of this meta-analysis are tentative due to the limited number of studies included, and further research is necessary for validation.


Subject(s)
Fluorodeoxyglucose F18 , Liver Neoplasms , Magnetic Resonance Imaging , Positron Emission Tomography Computed Tomography , Radiopharmaceuticals , Sensitivity and Specificity , Humans , Liver Neoplasms/secondary , Liver Neoplasms/diagnostic imaging , Positron Emission Tomography Computed Tomography/methods , Magnetic Resonance Imaging/methods , Positron-Emission Tomography/methods , Multimodal Imaging/methods , Liver/diagnostic imaging , Liver/pathology
15.
Sci Rep ; 14(1): 12922, 2024 06 05.
Article in English | MEDLINE | ID: mdl-38839921

ABSTRACT

The incidence of non-alcoholic fatty liver disease (NAFLD) tends to be younger. And the role of theobromine in fatty liver disease remains unclear. The purpose of this study was to investigate the relationship between dietary theobromine intake and degree of hepatic steatosis in individuals aged 45 and below, using data from the 2017-2020 National Health and Nutrition Examination Survey (NHANES) and liver ultrasonography transient elastography. A total of 1796 participants aged below 45 years were included from NHANES 2017-2020 data after applying exclusion criteria. Multivariate regression and subgroup analyses were conducted to examine the associations between theobromine intake and controlled attenuation parameter (CAP), adjusting for potential confounders. Generalized additive models and two-piecewise linear regression were used to analyze nonlinear relationships. In the unadjusted Model 1 and preliminarily adjusted Model 2, there was no significant correlation between theobromine intake and CAP values. However, in Models 3 and 4, which accounted for confounding factors, a higher intake of theobromine was significantly associated with lower CAP values. Subgroup analyses in the fully adjusted Model 4 revealed a significant negative correlation among individuals aged 18-45, women, and white populations. Nonlinear analysis revealed a U-shaped relationship in black Americans, with the lowest CAP values at 44.5 mg/day theobromine. This study provides evidence that higher theobromine intake is correlated with lower degree of hepatic steatosis in young people, especially those aged 18-45 years, women, and whites. For black Americans, maintaining theobromine intake around 44.5 mg/day may help minimize liver steatosis. These findings may help personalize clinical nutritional guidance, prevent the degree of hepatic steatosis, and provide pharmacological approaches to reverse fatty liver disease in young people.


Subject(s)
Non-alcoholic Fatty Liver Disease , Nutrition Surveys , Theobromine , Humans , Theobromine/administration & dosage , Female , Male , Adult , Non-alcoholic Fatty Liver Disease/epidemiology , Adolescent , Young Adult , Middle Aged , Liver/diagnostic imaging , Liver/pathology , Elasticity Imaging Techniques , Fatty Liver/epidemiology , Fatty Liver/diagnostic imaging
16.
Phys Med Biol ; 69(12)2024 Jun 17.
Article in English | MEDLINE | ID: mdl-38838679

ABSTRACT

Purpose.4D MRI with high spatiotemporal resolution is desired for image-guided liver radiotherapy. Acquiring densely sampling k-space data is time-consuming. Accelerated acquisition with sparse samples is desirable but often causes degraded image quality or long reconstruction time. We propose the Reconstruct Paired Conditional Generative Adversarial Network (Re-Con-GAN) to shorten the 4D MRI reconstruction time while maintaining the reconstruction quality.Methods.Patients who underwent free-breathing liver 4D MRI were included in the study. Fully- and retrospectively under-sampled data at 3, 6 and 10 times (3×, 6× and 10×) were first reconstructed using the nuFFT algorithm. Re-Con-GAN then trained input and output in pairs. Three types of networks, ResNet9, UNet and reconstruction swin transformer (RST), were explored as generators. PatchGAN was selected as the discriminator. Re-Con-GAN processed the data (3D +t) as temporal slices (2D +t). A total of 48 patients with 12 332 temporal slices were split into training (37 patients with 10 721 slices) and test (11 patients with 1611 slices). Compressed sensing (CS) reconstruction with spatiotemporal sparsity constraint was used as a benchmark. Reconstructed image quality was further evaluated with a liver gross tumor volume (GTV) localization task using Mask-RCNN trained from a separate 3D static liver MRI dataset (70 patients; 103 GTV contours).Results.Re-Con-GAN consistently achieved comparable/better PSNR, SSIM, and RMSE scores compared to CS/UNet models. The inference time of Re-Con-GAN, UNet and CS are 0.15, 0.16, and 120 s. The GTV detection task showed that Re-Con-GAN and CS, compared to UNet, better improved the dice score (3× Re-Con-GAN 80.98%; 3× CS 80.74%; 3× UNet 79.88%) of unprocessed under-sampled images (3× 69.61%).Conclusion.A generative network with adversarial training is proposed with promising and efficient reconstruction results demonstrated on an in-house dataset. The rapid and qualitative reconstruction of 4D liver MR has the potential to facilitate online adaptive MR-guided radiotherapy for liver cancer.


Subject(s)
Liver , Magnetic Resonance Imaging , Humans , Liver/diagnostic imaging , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/radiotherapy , Image Processing, Computer-Assisted/methods , Neural Networks, Computer , Imaging, Three-Dimensional/methods
17.
Sci Rep ; 14(1): 12613, 2024 06 01.
Article in English | MEDLINE | ID: mdl-38824206

ABSTRACT

The aim of the study was to assess healthy tissue metabolism (HTM) using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) during chemotherapy in Hodgkin lymphoma (HL) and the association of HTM with baseline metabolic tumour volume (MTV), haematological parameters, adverse events (AEs), early response and progression-free survival (PFS). We retrospectively identified 200 patients with advanced HL from the RATHL trial with [18F]FDG-PET/CT before (PET0) and following 2 cycles of chemotherapy (PET2). [18F]FDG-uptake was measured in bone marrow (BM), spleen, liver and mediastinal blood pool (MBP). Deauville score (DS) 1-3 was used to classify responders and DS 4-5, non-responders. [18F]FDG-uptake decreased significantly in BM and spleen and increased in liver and MBP at PET2 (all p < 0.0001), but was not associated with MTV. Higher BM uptake at PET0 was associated with lower baseline haemoglobin and higher absolute neutrophil counts, platelets, and white blood cells. High BM, spleen, and liver uptake at PET0 was associated with neutropenia after cycles 1-2. BM uptake at PET0 was associated with treatment failure at PET2 and non-responders with higher BM uptake at PET2 had significantly inferior PFS (p = 0.023; hazard ratio = 2.31). Based on these results, we concluded that the change in HTM during chemotherapy was most likely a direct impact of chemotherapy rather than a change in MTV. BM uptake has prognostic value in HL.


Subject(s)
Fluorodeoxyglucose F18 , Hodgkin Disease , Positron Emission Tomography Computed Tomography , Humans , Hodgkin Disease/drug therapy , Hodgkin Disease/diagnostic imaging , Hodgkin Disease/metabolism , Hodgkin Disease/pathology , Positron Emission Tomography Computed Tomography/methods , Male , Female , Adult , Middle Aged , Prognosis , Retrospective Studies , Young Adult , Bone Marrow/diagnostic imaging , Bone Marrow/metabolism , Bone Marrow/pathology , Bone Marrow/drug effects , Aged , Liver/diagnostic imaging , Liver/metabolism , Liver/pathology , Adolescent , Radiopharmaceuticals , Spleen/diagnostic imaging , Spleen/metabolism , Spleen/pathology
18.
Opt Express ; 32(11): 20194-20206, 2024 May 20.
Article in English | MEDLINE | ID: mdl-38859135

ABSTRACT

In this work, a common-path optical coherence tomography (OCT) system is demonstrated for characterizing the tissue in terms of some optical properties. A negative axicon structure chemically etched inside the fiber tip is employed as optical probe in the OCT. This probe generates a quality Bessel beam owning a large depth-of-field, ∼700 µm and small central spot size, ∼3 µm. The OCT system is probing the sample without using any microscopic lens. For experimental validation, the OCT imaging of chicken tissue has been obtained along with estimation of its refractive index and optical attenuation coefficient. Afterwards, the cancerous tissue is differentiated from the normal tissue based on the OCT imaging, refractive index, and optical attenuation coefficient. The respective tissue samples are collected from the human liver and pancreas. This probe could be a useful tool for endoscopic or minimal-invasive inspection of malignancy inside the tissue either at early-stage or during surgery.


Subject(s)
Chickens , Tomography, Optical Coherence , Tomography, Optical Coherence/methods , Tomography, Optical Coherence/instrumentation , Humans , Animals , Equipment Design , Liver/diagnostic imaging , Liver/pathology , Pancreas/diagnostic imaging , Refractometry
19.
Radiology ; 311(3): e232462, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38860893

ABSTRACT

Background Despite a proven role in the characterization of liver lesions, use of the gadolinium-based contrast agent (GBCA) gadoxetate disodium at MRI is limited in children due to a lack of comparative safety data. Purpose To evaluate the safety of the GBCA gadoxetate disodium (a linear ionic hepatobiliary contrast agent [HBA]) in children and adolescents, compared with extracellular contrast agents (ECA). Materials and Methods A retrospective analysis was conducted in children and adolescents aged 18 years or younger who underwent HBA-enhanced MRI at one of three tertiary hospitals from January 2010 to December 2022. The incidence of GBCA-associated acute adverse events was compared between MRI examinations with a HBA and those with ECA. Severity was categorized according to American College of Radiology guidelines (mild, moderate, or severe). (a) Propensity score matching using multivariable logistic regression models and (b) inverse probability of treatment weighting analysis based on nine covariates (age, sex, asthma, allergic rhinitis, chronic urticaria or atopy, food allergy, drug allergy, premedication, and history of GBCA-associated adverse events) were used for confounder adjustment. Results A total of 1629 MRI examinations (ECA, n = 1256; HBA, n = 373) in 1079 patients were included (mean age, 8.6 years ± 6.5; 566 girls). The per-examination incidence of GBCA-associated acute adverse events showed no evidence of a difference, with rates of 0.9% (11 of 1256 examinations) for ECA and 1.3% (five of 373 examinations) for HBA (odds ratio [OR], 1.55 [95% CI: 0.54, 4.46]; P = .42). Acute adverse events were all mild with ECA, whereas with HBA, they were mild for four patients and moderate for one patient. There was no evidence of a difference in the incidence of acute adverse events, even in propensity score matching (OR, 1.33 [95% CI: 0.30, 5.96]; P = .71) and inverse probability of treatment weighting analysis (OR, 0.84 [95% CI: 0.25, 2.86]; P = .78). Conclusion Gadoxetate disodium showed no difference in acute adverse events compared with ECA in children and adolescents, with further large-scale pediatric studies required to confirm its safety. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Otero in this issue.


Subject(s)
Contrast Media , Gadolinium DTPA , Magnetic Resonance Imaging , Humans , Male , Female , Child , Adolescent , Retrospective Studies , Magnetic Resonance Imaging/methods , Contrast Media/adverse effects , Child, Preschool , Liver/diagnostic imaging , Infant , Liver Diseases/diagnostic imaging
20.
BMC Med Imaging ; 24(1): 129, 2024 May 31.
Article in English | MEDLINE | ID: mdl-38822274

ABSTRACT

BACKGROUND: Segmenting liver vessels from contrast-enhanced computed tomography images is essential for diagnosing liver diseases, planning surgeries and delivering radiotherapy. Nevertheless, identifying vessels is a challenging task due to the tiny cross-sectional areas occupied by vessels, which has posed great challenges for vessel segmentation, such as limited features to be learned and difficult to construct high-quality as well as large-volume data. METHODS: We present an approach that only requires a few labeled vessels but delivers significantly improved results. Our model starts with vessel enhancement by fading out liver intensity and generates candidate vessels by a classifier fed with a large number of image filters. Afterwards, the initial segmentation is refined using Markov random fields. RESULTS: In experiments on the well-known dataset 3D-IRCADb, the averaged Dice coefficient is lifted to 0.63, and the mean sensitivity is increased to 0.71. These results are significantly better than those obtained from existing machine-learning approaches and comparable to those generated from deep-learning models. CONCLUSION: Sophisticated integration of a large number of filters is able to pinpoint effective features from liver images that are sufficient to distinguish vessels from other liver tissues under a scarcity of large-volume labeled data. The study can shed light on medical image segmentation, especially for those without sufficient data.


Subject(s)
Liver , Tomography, X-Ray Computed , Humans , Tomography, X-Ray Computed/methods , Liver/diagnostic imaging , Liver/blood supply , Contrast Media , Machine Learning , Algorithms , Deep Learning
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