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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.
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
3.
BMC Med Imaging ; 24(1): 151, 2024 Jun 18.
Article in English | MEDLINE | ID: mdl-38890572

ABSTRACT

BACKGROUND: Abdominal CT scans are vital for diagnosing abdominal diseases but have limitations in tissue analysis and soft tissue detection. Dual-energy CT (DECT) can improve these issues by offering low keV virtual monoenergetic images (VMI), enhancing lesion detection and tissue characterization. However, its cost limits widespread use. PURPOSE: To develop a model that converts conventional images (CI) into generative virtual monoenergetic images at 40 keV (Gen-VMI40keV) of the upper abdomen CT scan. METHODS: Totally 444 patients who underwent upper abdominal spectral contrast-enhanced CT were enrolled and assigned to the training and validation datasets (7:3). Then, 40-keV portal-vein virtual monoenergetic (VMI40keV) and CI, generated from spectral CT scans, served as target and source images. These images were employed to build and train a CI-VMI40keV model. Indexes such as Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity (SSIM) were utilized to determine the best generator mode. An additional 198 cases were divided into three test groups, including Group 1 (58 cases with visible abnormalities), Group 2 (40 cases with hepatocellular carcinoma [HCC]) and Group 3 (100 cases from a publicly available HCC dataset). Both subjective and objective evaluations were performed. Comparisons, correlation analyses and Bland-Altman plot analyses were performed. RESULTS: The 192nd iteration produced the best generator mode (lower MAE and highest PSNR and SSIM). In the Test groups (1 and 2), both VMI40keV and Gen-VMI40keV significantly improved CT values, as well as SNR and CNR, for all organs compared to CI. Significant positive correlations for objective indexes were found between Gen-VMI40keV and VMI40keV in various organs and lesions. Bland-Altman analysis showed that the differences between both imaging types mostly fell within the 95% confidence interval. Pearson's and Spearman's correlation coefficients for objective scores between Gen-VMI40keV and VMI40keV in Groups 1 and 2 ranged from 0.645 to 0.980. In Group 3, Gen-VMI40keV yielded significantly higher CT values for HCC (220.5HU vs. 109.1HU) and liver (220.0HU vs. 112.8HU) compared to CI (p < 0.01). The CNR for HCC/liver was also significantly higher in Gen-VMI40keV (2.0 vs. 1.2) than in CI (p < 0.01). Additionally, Gen-VMI40keV was subjectively evaluated to have a higher image quality compared to CI. CONCLUSION: CI-VMI40keV model can generate Gen-VMI40keV from conventional CT scan, closely resembling VMI40keV.


Subject(s)
Tomography, X-Ray Computed , Humans , Tomography, X-Ray Computed/methods , Female , Male , Middle Aged , Radiography, Abdominal/methods , Aged , Adult , Radiographic Image Interpretation, Computer-Assisted/methods , Liver Neoplasms/diagnostic imaging , Signal-To-Noise Ratio , Radiography, Dual-Energy Scanned Projection/methods , Carcinoma, Hepatocellular/diagnostic imaging , Aged, 80 and over , Contrast Media
4.
Cancer Med ; 13(11): e7374, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38864473

ABSTRACT

PURPOSE: Radical surgery, the first-line treatment for patients with hepatocellular cancer (HCC), faces the dilemma of high early recurrence rates and the inability to predict effectively. We aim to develop and validate a multimodal model combining clinical, radiomics, and pathomics features to predict the risk of early recurrence. MATERIALS AND METHODS: We recruited HCC patients who underwent radical surgery and collected their preoperative clinical information, enhanced computed tomography (CT) images, and whole slide images (WSI) of hematoxylin and eosin (H & E) stained biopsy sections. After feature screening analysis, independent clinical, radiomics, and pathomics features closely associated with early recurrence were identified. Next, we built 16 models using four combination data composed of three type features, four machine learning algorithms, and 5-fold cross-validation to assess the performance and predictive power of the comparative models. RESULTS: Between January 2016 and December 2020, we recruited 107 HCC patients, of whom 45.8% (49/107) experienced early recurrence. After analysis, we identified two clinical features, two radiomics features, and three pathomics features associated with early recurrence. Multimodal machine learning models showed better predictive performance than bimodal models. Moreover, the SVM algorithm showed the best prediction results among the multimodal models. The average area under the curve (AUC), accuracy (ACC), sensitivity, and specificity were 0.863, 0.784, 0.731, and 0.826, respectively. Finally, we constructed a comprehensive nomogram using clinical features, a radiomics score and a pathomics score to provide a reference for predicting the risk of early recurrence. CONCLUSIONS: The multimodal models can be used as a primary tool for oncologists to predict the risk of early recurrence after radical HCC surgery, which will help optimize and personalize treatment strategies.


Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Machine Learning , Neoplasm Recurrence, Local , Tomography, X-Ray Computed , Humans , Carcinoma, Hepatocellular/surgery , Carcinoma, Hepatocellular/pathology , Carcinoma, Hepatocellular/diagnostic imaging , Liver Neoplasms/surgery , Liver Neoplasms/pathology , Liver Neoplasms/diagnostic imaging , Male , Female , Middle Aged , Neoplasm Recurrence, Local/pathology , Prognosis , Aged , Hepatectomy , Adult , Radiomics
5.
Nihon Shokakibyo Gakkai Zasshi ; 121(6): 497-504, 2024.
Article in Japanese | MEDLINE | ID: mdl-38853019

ABSTRACT

An 86-year-old male patient with sustained virological response of chronic hepatitis type C was diagnosed with hepatocellular carcinoma (HCC) in hepatic segment 3. He was treated with transcatheter arterial chemoembolization (TACE) and radiation therapy because the tumor was located at the edge of the liver and umbilical portion of the portal vein. The value of alpha-fetoprotein (AFP) which is a serological tumor marker decreased, and the tumor size did not increase;however, another tumor was recognized at S3 of the liver 15 months post-TACE. The patient underwent a second TACE, and computed tomography revealed HCC recurrence at S3, S8/4, and S1 of the liver 6 months later. The patient refused to undergo another treatment, but the AFP and Des-γ-carboxy prothrombin values and the tumor size decreased 3 months postrecurrence. Two months after multiple recurrences of HCC, he received the third dose of messenger RNA-based vaccine for severe acute respiratory syndrome coronavirus 2. Tumor regression may occur after an immune-inflammatory response induced by messenger RNA-based vaccine.


Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Humans , Male , Carcinoma, Hepatocellular/therapy , Carcinoma, Hepatocellular/diagnostic imaging , Liver Neoplasms/therapy , Liver Neoplasms/diagnostic imaging , Aged, 80 and over , COVID-19 Vaccines/administration & dosage , COVID-19/immunology , COVID-19/prevention & control , Vaccination
6.
J Vis Exp ; (207)2024 May 24.
Article in English | MEDLINE | ID: mdl-38856215

ABSTRACT

This study showcases a comprehensive treatment protocol for high-risk hepatocellular carcinoma (HCC) patients, focusing on the combined use of Y-90 transarterial radioembolization (TARE) and Programmed Cell Death-1 (PD-1) inhibitors as neoadjuvant therapy. Highlighted through a case report, it offers a step-by-step reference for similar therapeutic interventions. A retrospective analysis was conducted on a patient who underwent hepatectomy following Y-90 TARE and PD-1 inhibitor treatment. Key demographic and clinical details were recorded at admission to guide therapy selection. Y-90 TARE suitability and dosage calculation were based on Technetium-99m (Tc-99m) macroaggregated albumin (MAA) perfusion mapping tests. Lesion coverage by Y-90 microspheres was confirmed through single photon emission computed tomography/computed tomography (SPECT/CT) fusion imaging, and adverse reactions and follow-up outcomes were meticulously documented. The patient, with a 7.2 cm HCC in the right hepatic lobe (T1bN0M0, BCLC A, CNLC Ib) and an initial alpha-fetoprotein (AFP) level of 66,840 ng/mL, opted for Y-90 TARE due to high recurrence risk and initial surgery refusal. The therapy's parameters, including the lung shunting fraction (LSF) and non-tumor ratio (TNR), were within therapeutic limits. A total of 1.36 GBq Y-90 was administered. At 1 month post-therapy, the tumor shrank to 6 cm with partial necrosis, and AFP levels dropped to 21,155 ng/mL, remaining stable for 3 months. After 3 months, PD-1 inhibitor treatment led to further tumor reduction to 4 cm and AFP decrease to 1.84 ng/mL. The patient then underwent hepatectomy; histopathology confirmed complete tumor necrosis. At 12 months post-surgery, no tumor recurrence or metastasis was observed in follow-up sessions. This protocol demonstrates the effective combination of Y-90 TARE and PD-1 inhibitor as a bridging strategy to surgery for HCC patients at high recurrence risk, providing a practical guide for implementing this approach.


Subject(s)
Carcinoma, Hepatocellular , Embolization, Therapeutic , Liver Neoplasms , Neoadjuvant Therapy , Yttrium Radioisotopes , Humans , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/therapy , Liver Neoplasms/drug therapy , Liver Neoplasms/pathology , Carcinoma, Hepatocellular/diagnostic imaging , Carcinoma, Hepatocellular/therapy , Carcinoma, Hepatocellular/drug therapy , Carcinoma, Hepatocellular/pathology , Neoadjuvant Therapy/methods , Embolization, Therapeutic/methods , Yttrium Radioisotopes/therapeutic use , Male , Retrospective Studies , Immune Checkpoint Inhibitors/therapeutic use , Middle Aged , Aged , Radiopharmaceuticals/therapeutic use
7.
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
8.
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
9.
Technol Cancer Res Treat ; 23: 15330338241260331, 2024.
Article in English | MEDLINE | ID: mdl-38860337

ABSTRACT

OBJECTIVE: To compare the ability of gadolinium ethoxybenzyl dimeglumine (Gd-EOB-DTPA) and gadobenate dimeglumine (Gd-BOPTA) to display the 3 major features recommended by the Liver Imaging Reporting and Data System (LI-RADS 2018v) for diagnosing hepatocellular carcinoma (HCC). MATERIALS AND METHODS: In this retrospective study, we included 98 HCC lesions that were scanned with either Gd-EOB-DTPA-MR or Gd-BOPTA-M.For each lesion, we collected multiple variables, including size and enhancement pattern in the arterial phase (AP), portal venous phase (PVP), transitional phase (TP), delayed phase (DP), and hepatobiliary phase (HBP). The lesion-to-liver contrast (LLC) was measured and calculated for each phase and then compared between the 2 contrast agents. A P value < .05 was considered statistically significant. The display efficiency of the LLC between Gd-BOPTA and Gd-EOB-DTPA for HCC features was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: Between Gd-BOPTA and Gd-EOB-DTPA, significant differences were observed regarding the display efficiency for capsule enhancement and the LLC in the AP/PVP/DP (P < .05), but there was no significant difference regarding the LLC in the TP/HBP. Both Gd-BOPTA and Gd-EOB-DTPA had good display efficiency in each phase (AUCmin > 0.750). When conducting a total evaluation of the combined data across the 5 phases, the display efficiency was excellent (AUC > 0.950). CONCLUSION: Gd-BOPTA and Gd-EOB-DTPA are liver-specific contrast agents widely used in clinical practice. They have their own characteristics in displaying the 3 main signs of HCC. For accurate noninvasive diagnosis, the choice of agent should be made according to the specific situation.


Subject(s)
Carcinoma, Hepatocellular , Contrast Media , Gadolinium DTPA , Liver Neoplasms , Magnetic Resonance Imaging , Meglumine , Organometallic Compounds , ROC Curve , Humans , Carcinoma, Hepatocellular/diagnosis , Carcinoma, Hepatocellular/diagnostic imaging , Liver Neoplasms/diagnosis , Liver Neoplasms/diagnostic imaging , Magnetic Resonance Imaging/methods , Male , Female , Meglumine/analogs & derivatives , Middle Aged , Aged , Retrospective Studies , Adult , Image Enhancement/methods , Aged, 80 and over
10.
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
11.
Phys Med ; 122: 103384, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38824827

ABSTRACT

The dosimetry evaluation for the selective internal radiation therapy is currently performed assuming a uniform activity distribution, which is in contrast with literature findings. A 2D microscopic model of the perfused liver was developed to evaluate the effect of two different 90Y microspheres distributions: i) homogeneous partitioning with the microspheres equally distributed in the perfused liver, and ii) tumor-clustered partitioning where the microspheres distribution is inferred from the patient specific images. METHODS: Two subjects diagnosed with liver cancer were included in this study. For each subject, abdominal CT scans acquired prior to the SIRT and post-treatment 90Y positron emission tomography were considered. Two microspheres partitionings were simulated namely homogeneous and tumor-clustered partitioning. The homogeneous and tumor-clustered partitionings were derived starting from CT images. The microspheres radiation is simulated by means of Russell's law. RESULTS: In homogenous simulations, the dose delivery is uniform in the whole liver while in the tumor-clustered simulations a heterogeneous distribution of the delivered dose is visible with higher values in the tumor regions. In addition, in the tumor-clustered simulation, the delivered dose is higher in the viable tumor than in the necrotic tumor, for all patients. In the tumor-clustered case, the dose delivered in the non-tumoral tissue (NTT) was considerably lower than in the perfused liver. CONCLUSIONS: The model proposed here represents a proof-of-concept for personalized dosimetry assessment based on preoperative CT images.


Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Microspheres , Radiotherapy Dosage , Yttrium Radioisotopes , Liver Neoplasms/radiotherapy , Liver Neoplasms/diagnostic imaging , Carcinoma, Hepatocellular/radiotherapy , Carcinoma, Hepatocellular/diagnostic imaging , Humans , Yttrium Radioisotopes/therapeutic use , Models, Biological , Tomography, X-Ray Computed , Radiation Dosage , Microscopy
12.
BMC Cancer ; 24(1): 700, 2024 Jun 07.
Article in English | MEDLINE | ID: mdl-38849749

ABSTRACT

BACKGROUND: Although radical surgical resection is the most effective treatment for hepatocellular carcinoma (HCC), the high rate of postoperative recurrence remains a major challenge, especially in patients with alpha-fetoprotein (AFP)-negative HCC who lack effective biomarkers for postoperative recurrence surveillance. Emerging radiomics can reveal subtle structural changes in tumors by analyzing preoperative contrast-enhanced computer tomography (CECT) imaging data and may provide new ways to predict early recurrence (recurrence within 2 years) in AFP-negative HCC. In this study, we propose to develop a radiomics model based on preoperative CECT to predict the risk of early recurrence after surgery in AFP-negative HCC. PATIENTS AND METHODS: Patients with AFP-negative HCC who underwent radical resection were included in this study. A computerized tool was used to extract radiomic features from the tumor region of interest (ROI), select the best radiographic features associated with patient's postoperative recurrence, and use them to construct the radiomics score (RadScore), which was then combined with clinical and follow-up information to comprehensively evaluate the reliability of the model. RESULTS: A total of 148 patients with AFP-negative HCC were enrolled in this study, and 1,977 radiographic features were extracted from CECT, 2 of which were the features most associated with recurrence in AFP-negative HCC. They had good predictive ability in both the training and validation cohorts, with an area under the ROC curve (AUC) of 0.709 and 0.764, respectively. Tumor number, microvascular invasion (MVI), AGPR and radiomic features were independent risk factors for early postoperative recurrence in patients with AFP-negative HCC. The AUCs of the integrated model in the training and validation cohorts were 0.793 and 0.791, respectively. The integrated model possessed the clinical value of predicting early postoperative recurrence in patients with AFP-negative HCC according to decision curve analysis, which allowed the classification of patients into subgroups of high-risk and low-risk for early recurrence. CONCLUSION: The nomogram constructed by combining clinical and imaging features has favorable performance in predicting the probability of early postoperative recurrence in AFP-negative HCC patients, which can help optimize the therapeutic decision-making and prognostic assessment of AFP-negative HCC patients.


Subject(s)
Carcinoma, Hepatocellular , Contrast Media , Liver Neoplasms , Neoplasm Recurrence, Local , Tomography, X-Ray Computed , alpha-Fetoproteins , Humans , Carcinoma, Hepatocellular/surgery , Carcinoma, Hepatocellular/diagnostic imaging , Carcinoma, Hepatocellular/pathology , Liver Neoplasms/surgery , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/pathology , Male , Female , alpha-Fetoproteins/metabolism , alpha-Fetoproteins/analysis , Neoplasm Recurrence, Local/diagnostic imaging , Middle Aged , Tomography, X-Ray Computed/methods , Aged , Retrospective Studies , Adult , Hepatectomy , Prognosis , Radiomics
13.
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
14.
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
15.
ACS Nano ; 18(23): 15249-15260, 2024 Jun 11.
Article in English | MEDLINE | ID: mdl-38818704

ABSTRACT

Bimetallic iron-noble metal alloy nanoparticles have emerged as promising contrast agents for magnetic resonance imaging (MRI) due to their biocompatibility and facile control over the element distribution. However, the inherent surface energy discrepancy between iron and noble metal often leads to Fe atom segregation within the nanoparticle, resulting in limited iron-water molecule interactions and, consequently, diminished relaxometric performance. In this study, we present the development of a class of ligand-induced atomically segregation-tunable alloy nanoprobes (STAN) composed of bimetallic iron-gold nanoparticles. By manipulating the oxidation state of Fe on the particle surface through varying molar ratios of oleic acid and oleylamine ligands, we successfully achieve surface Fe enrichment. Under the application of a 9 T MRI system, the optimized STAN formulation, characterized by a surface Fe content of 60.1 at %, exhibits an impressive r1 value of 2.28 mM-1·s-1, along with a low r2/r1 ratio of 6.2. This exceptional performance allows for the clear visualization of hepatic tumors as small as 0.7 mm in diameter in vivo, highlighting the immense potential of STAN as a next-generation contrast agent for highly sensitive MR imaging.


Subject(s)
Alloys , Contrast Media , Gold , Magnetic Resonance Imaging , Metal Nanoparticles , Alloys/chemistry , Ligands , Gold/chemistry , Animals , Contrast Media/chemistry , Metal Nanoparticles/chemistry , Humans , Mice , Iron/chemistry , Surface Properties , Particle Size , Liver Neoplasms/diagnostic imaging , Oleic Acid/chemistry
16.
J Pak Med Assoc ; 74(4 (Supple-4)): S29-S36, 2024 Apr.
Article in English | MEDLINE | ID: mdl-38712406

ABSTRACT

Introduction: Hepatocellular carcinoma constitutes for approximately 75% of primary cancers of liver. Around 80- 90% of patients with HCC have cirrhosis at the time of diagnosis. Use of AI has recently gained significance in the field of hepatology, especially for the detection of HCC, owing to its increasing incidence and specific radiological features which have been established for its diagnostic criteria. Objectives: A systematic review was performed to evaluate the current literature for early diagnosis of hepatocellular carcinoma in cirrhotic patients. METHODS: Systematic review was conducted using PRISMA guidelines and the relevant studies were narrated in detail with assessment of quality for each paper. RESULTS: This systematic review displays the significance of AI in early detection and prognosis of HCC with the pressing need for further exploration in this field. CONCLUSIONS: AI can have a significant role in early diagnosis of HCC in cirrhotic patients.


Subject(s)
Carcinoma, Hepatocellular , Early Detection of Cancer , Liver Cirrhosis , Liver Neoplasms , Humans , Liver Neoplasms/diagnosis , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/complications , Liver Cirrhosis/complications , Liver Cirrhosis/diagnosis , Carcinoma, Hepatocellular/diagnosis , Carcinoma, Hepatocellular/diagnostic imaging , Early Detection of Cancer/methods , Artificial Intelligence
17.
PET Clin ; 19(3): 431-446, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38816137

ABSTRACT

This article provides a thorough overview of the practice and multistep approach of hepatic radioembolization. The current literature on hepatic radioembolization in primary or metastatic liver tumors as well as future perspectives are discussed.


Subject(s)
Embolization, Therapeutic , Liver Neoplasms , Radiopharmaceuticals , Humans , Liver Neoplasms/radiotherapy , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/secondary , Embolization, Therapeutic/methods , Radiopharmaceuticals/therapeutic use , Yttrium Radioisotopes/therapeutic use , Liver/diagnostic imaging
18.
Clin Imaging ; 111: 110185, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38781614

ABSTRACT

Despite considerable advances in surgical technique, many patients with hepatic malignancies are not operative candidates due to projected inadequate hepatic function following resection. Consequently, the size of the future liver remnant (FLR) is an essential consideration when predicting a patient's likelihood of liver insufficiency following hepatectomy. Since its initial description 30 years ago, portal vein embolization has become the standard of care for augmenting the size and function of the FLR preoperatively. However, new minimally invasive techniques have been developed to improve surgical candidacy, chief among them liver venous deprivation and radiation lobectomy. The purpose of this review is to discuss the status of preoperative liver augmentation prior to resection of hepatocellular carcinoma with a focus on these three techniques, highlighting the distinctions between them and suggesting directions for future investigation.


Subject(s)
Carcinoma, Hepatocellular , Embolization, Therapeutic , Hepatectomy , Liver Neoplasms , Portal Vein , Humans , Liver Neoplasms/surgery , Liver Neoplasms/radiotherapy , Liver Neoplasms/diagnostic imaging , Carcinoma, Hepatocellular/surgery , Carcinoma, Hepatocellular/diagnostic imaging , Carcinoma, Hepatocellular/therapy , Carcinoma, Hepatocellular/radiotherapy , Embolization, Therapeutic/methods , Hepatectomy/methods , Surgery, Computer-Assisted/methods
19.
Surg Endosc ; 38(6): 3441-3447, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38691133

ABSTRACT

BACKGROUND: Intraoperative indocyanine green (ICG) fluorescence imaging has been shown to be a new and innovative way to illustrate the optimal resection margin in hepatectomy for hepatocellular carcinoma. This study investigated its accuracy in resection margin determination by looking into the correlation of ICG intensity gradients with pathological examination results of resected specimens. METHODS: This was a prospective, single-center, non-randomized controlled study. Patients who had liver tumors indicating liver resection were recruited. The hypothesis was that the use of intraoperative near-infrared/ICG fluorescence imaging would be a promising guiding tool for removing hepatocellular carcinoma with a better resection margin. Patients were given ICG (0.25 mg/kg) 1 day before operation. Resected specimens were inspected under a fluorescent imaging system. Biopsies were taken from tumors and normal tissue. Color signals obtained from ICG fluorescence imaging were compared with biopsies for analysis. RESULTS: Twenty-two patients were recruited for study. The median size of their tumors was 2.25 cm. One patient had resection margin involvement. Under ICG fluorescence, the tumors typically lighted up as yellow color, wrapped by a zone of green color. Tumors of 17 patients (77.3%) displayed yellow color and were confirmed malignancy, while tumors of 12 patients (54.5%) displayed green color and were confirmed malignancy. Receiver operating characteristic curve was used to measure the sensitivity and specificity of the green color to look for a clear resection margin. The area under the curve was 85.3% (p = 0.019, 95% confidence interval 0.696-1.000), with a sensitivity of 0.706 and specificity of 1.000. CONCLUSION: The use of ICG fluorescence can be helpful in determining resection margins. Resection of tumor should include complete resection of the green zone shown in the fluorescence image.


Subject(s)
Carcinoma, Hepatocellular , Coloring Agents , Hepatectomy , Indocyanine Green , Liver Neoplasms , Margins of Excision , Humans , Prospective Studies , Male , Female , Liver Neoplasms/surgery , Liver Neoplasms/pathology , Liver Neoplasms/diagnostic imaging , Middle Aged , Aged , Hepatectomy/methods , Carcinoma, Hepatocellular/surgery , Carcinoma, Hepatocellular/pathology , Carcinoma, Hepatocellular/diagnostic imaging , Optical Imaging/methods , Adult
20.
Khirurgiia (Mosk) ; (5): 65-74, 2024.
Article in Russian | MEDLINE | ID: mdl-38785241

ABSTRACT

Parenchyma- sparing liver resections are aimed at maximizing the possible preservation of parenchyma not affected by the tumor - a current trend in hepatopancreatobiliary surgery. On the other hand, a prerequisite for operations is to ensure their radicality. To effectively solve this problem, all diagnostic imaging methods available in the arsenal are used, which make it possible to comprehensively solve the issues of perioperative planning of the volume and technical features of the planned operation. Diagnostic imaging methods that allow intraoperative navigation through intraoperative, instrumentally based determination of the tumor border and resection plane have additional value. One of the methods of such mapping is ICG video fluorescence intraoperative navigation. An analysis of the clinical use of the domestic video fluorescent navigation system "MARS" for parenchymal-sparing resections of focal liver lesions is presented. An assessment was made of the dynamics of the distribution of the contrast agent during ICG videofluorescent mapping during parenchymal-sparing resection interventions on the liver, with the analysis of materials from histological examination of tissues taking into account three-zonal videofluorescent marking of the resection edge, performed using the domestic videofluorescence imaging system «MARS¼.


Subject(s)
Hepatectomy , Indocyanine Green , Liver Neoplasms , Liver , Optical Imaging , Humans , Hepatectomy/methods , Liver Neoplasms/surgery , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/pathology , Liver/surgery , Liver/diagnostic imaging , Optical Imaging/methods , Male , Indocyanine Green/administration & dosage , Surgery, Computer-Assisted/methods , Female , Middle Aged
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