Ablation Techniques

Study on microwave ablation temperature prediction model based on grayscale ultrasound texture and machine learning.

PloS one 39321182

BACKGROUND: Temperature prediction is crucial in the clinical ablation treatment of liver cancer, as it can be used to estimate the coagulation zone of microwave ablation.

Ablation Techniques Algorithms Animals Liver Liver Neoplasms Machine Learning Microwaves Swine Temperature Ultrasonography

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Survival Analysis for Multimode Ablation Using Self-Adapted Deep Learning Network Based on Multisource Features.

IEEE journal of biomedical and health informatics 37015120

Novel multimode thermal therapy by freezing before radio-frequency heating has achieved a desirable therapeutic effect in liver cancer. Compared with surgical resection, ablation treatment has a relatively high risk of tumor recurrence. To monitor tu...

Ablation Techniques Deep Learning Female Humans Liver Neoplasms Magnetic Resonance Imaging Male Middle Aged Survival Analysis

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Pre-operative lung ablation prediction using deep learning.

European radiology 38775950

OBJECTIVE: Microwave lung ablation (MWA) is a minimally invasive and inexpensive alternative cancer treatment for patients who are not candidates for surgery/radiotherapy. However, a major challenge for MWA is its relatively high tumor recurrence rat...

Ablation Techniques Aged Deep Learning Female Humans Lung Lung Neoplasms Male Microwaves Middle Aged Retrospective Studies Tomography, X-Ray Computed

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Machine Learning Based on Clinical Information and Integrated CT Radiomics to Predict Local Recurrence of Stage Ia Lung Adenocarcinoma after Microwave Ablation.

Journal of vascular and interventional radiology : JVIR 39208929

PURPOSE: To develop and compare 3 different machine learning-based models of clinical information and integrated radiomics features predicting the local recurrence of Stage Ia lung adenocarcinoma after microwave ablation (MWA) for assisting clinical ...

Ablation Techniques Adenocarcinoma of Lung Aged Clinical Decision-Making Decision Support Techniques Female Humans Lung Neoplasms Machine Learning Male Margins of Excision Microwaves Middle Aged Neoplasm Recurrence, Local Neoplasm Staging Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Radiomics Retrospective Studies Risk Assessment Risk Factors Time Factors Tomography, X-Ray Computed Treatment Outcome

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Feasibility of Artificial Intelligence Powered Adverse Event Analysis: Using a Large Language Model to Analyze Microwave Ablation Malfunction Data.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes 39169480

Determine if a large language model (LLM, GPT-4) can label and consolidate and analyze interventional radiology (IR) microwave ablation device safety event data into meaningful summaries similar to humans. Microwave ablation safety data from Januar...

Ablation Techniques Artificial Intelligence Equipment Failure Feasibility Studies Humans Microwaves

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Precise ablation zone segmentation on CT images after liver cancer ablation using semi-automatic CNN-based segmentation.

Medical physics 39250658

BACKGROUND: Ablation zone segmentation in contrast-enhanced computed tomography (CECT) images enables the quantitative assessment of treatment success in the ablation of liver lesions. However, fully automatic liver ablation zone segmentation in CT i...

Ablation Techniques Automation Humans Image Processing, Computer-Assisted Liver Neoplasms Neural Networks, Computer Tomography, X-Ray Computed

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Predicting Survival and Recurrence of Lung Ablation Patients Using Deep Learning-Based Automatic Segmentation and Radiomics Analysis.

Cardiovascular and interventional radiology 39604700

PURPOSE: To predict survival and tumor recurrence following image-guided thermal ablation (IGTA) of lung tumors segmented using a deep learning approach.

Ablation Techniques Aged Deep Learning Female Humans Lung Lung Neoplasms Male Middle Aged Neoplasm Recurrence, Local Radiomics Retrospective Studies Surgery, Computer-Assisted Tomography, X-Ray Computed

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Predicting lack of clinical improvement following varicose vein ablation using machine learning.

Journal of vascular surgery. Venous and lymphatic disorders 39732288

OBJECTIVE: Varicose vein ablation is generally indicated in patients with active/healed venous ulcers. However, patient selection for intervention in individuals without venous ulcers is less clear. Tools that predict lack of clinical improvement (LC...

Ablation Techniques Aged Clinical Decision-Making Databases, Factual Decision Support Techniques Female Humans Machine Learning Male Middle Aged Postoperative Complications Predictive Value of Tests Retrospective Studies Risk Assessment Risk Factors Time Factors Treatment Outcome Varicose Veins

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Utility of a Large Language Model for Extraction of Clinical Findings from Healthcare Data following Lung Ablation: A Feasibility Study.

Journal of vascular and interventional radiology : JVIR 39662619

To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevant information from healthcare data in patients who have undergone microwave ablation for lung tumors. In this single-center retrospective study, radio...

Ablation Techniques Aged Data Mining Electronic Health Records Feasibility Studies Female Hemoptysis Hemothorax Humans Large Language Models Lung Neoplasms Male Microwaves Middle Aged Natural Language Processing Neoplasm Recurrence, Local Pneumothorax Predictive Value of Tests Recurrence Reproducibility of Results Retrospective Studies Time Factors Treatment Outcome

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Deep learning-based reconstruction and superresolution for MR-guided thermal ablation of malignant liver lesions.

Cancer imaging : the official publication of the International Cancer Imaging Society 40176185

OBJECTIVE: This study evaluates the impact of deep learning-enhanced T1-weighted VIBE sequences (DL-VIBE) on image quality and procedural parameters during MR-guided thermoablation of liver malignancies, compared to standard VIBE (SD-VIBE).

Ablation Techniques Aged Deep Learning Female Humans Liver Liver Neoplasms Magnetic Resonance Imaging Magnetic Resonance Imaging, Interventional Male Microwaves Middle Aged Retrospective Studies

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Study on microwave ablation temperature prediction model based on grayscale ultrasound texture and machine learning.

Survival Analysis for Multimode Ablation Using Self-Adapted Deep Learning Network Based on Multisource Features.

Pre-operative lung ablation prediction using deep learning.

Machine Learning Based on Clinical Information and Integrated CT Radiomics to Predict Local Recurrence of Stage Ia Lung Adenocarcinoma after Microwave Ablation.

Feasibility of Artificial Intelligence Powered Adverse Event Analysis: Using a Large Language Model to Analyze Microwave Ablation Malfunction Data.

Precise ablation zone segmentation on CT images after liver cancer ablation using semi-automatic CNN-based segmentation.

Predicting Survival and Recurrence of Lung Ablation Patients Using Deep Learning-Based Automatic Segmentation and Radiomics Analysis.

Predicting lack of clinical improvement following varicose vein ablation using machine learning.

Utility of a Large Language Model for Extraction of Clinical Findings from Healthcare Data following Lung Ablation: A Feasibility Study.

Deep learning-based reconstruction and superresolution for MR-guided thermal ablation of malignant liver lesions.

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