Artificial intelligence for ultrasonographic detection and diagnosis of hepatocellular carcinoma and cholangiocarcinoma
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.An AI system aids in detecting and classifying liver lesions on ultrasound images, improving diagnostic accuracy. This AI tool shows promise for assisting physicians in identifying various focal liver lesions (FLLs).
Area Of Science
- Medical Imaging
- Artificial Intelligence
- Hepatology
Background
- Ultrasonography (USG) effectiveness in liver cancer screening is limited by operator expertise.
- Accurate detection and classification of focal liver lesions (FLLs) are crucial for patient management.
- AI offers potential to enhance diagnostic capabilities in medical imaging.
Purpose Of The Study
- To develop and evaluate an AI-assisted system for detecting and classifying FLLs from USG images.
- To assess the AI model's performance in identifying various types of FLLs, including malignant and benign lesions.
Main Methods
- A retrospective study utilized 26,288 USG images from 5444 patients.
- The YOLOv5 model was trained for FLLs detection and classification of seven lesion types.
- Performance was evaluated on a per-image and per-lesion basis.
Main Results
- The AI achieved an 84.8% overall FLLs detection rate, with consistent performance across lesion sizes.
- Sensitivity and specificity for distinguishing malignant from benign FLLs were both 97.0%.
- Specific detection rates included 92.2% for cholangiocarcinoma (CCA), 89.7% for focal fatty sparing (FFS), and 82.3% for hepatocellular carcinoma (HCC).
Conclusions
- The developed AI model demonstrates significant potential to assist physicians in FLLs detection and diagnosis during USG examinations.
- The system shows high accuracy in classifying malignant versus benign lesions and specific FLL types.
- Further external validation is recommended for widespread clinical application.
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
Related Concept Videos
Endoscopic Ultrasound (EUS) and FibroScan are valuable diagnostic tools in gastroenterology and hepatology, each with specific applications and techniques.
Endoscopic Ultrasound (EUS):
Technological Integration: EUS is a sophisticated integration of optical endoscopy and ultrasonography. The endoscope visualizes the mucosal surface directly, while the ultrasound component penetrates deeper to visualize organs and structures beyond the gastrointestinal wall.
Image Formation: The ultrasound...
Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called...
Introduction:
Abdominal ultrasonography, commonly known as abdominal ultrasound, is a vital, non-invasive medical imaging technique widely used in healthcare.
Procedure:
This diagnostic tool allows the clinician to visually inspect internal structures within the abdomen, including vital organs such as the liver, gallbladder, pancreas, kidneys, and spleen.
The abdominal ultrasound process begins with applying a special gel to the patient's skin over the abdomen. This gel enhances the...