Update on the Role of Imaging in the Diagnosis, Staging, and Prognostication of Gallbladder Cancer DOI Creative Commons

Pratyaksha Rana,

Daneshwari Kalage, Raghuraman Soundararajan

et al.

Indian journal of radiology and imaging - new series/Indian journal of radiology and imaging/Indian Journal of Radiology & Imaging, Journal Year: 2024, Volume and Issue: 35(02), P. 218 - 233

Published: Aug. 26, 2024

Abstract Gallbladder cancer (GBC) is a highly aggressive malignancy with dismal prognosis. GBC characterized by marked geographic predilection. has distinct morphological types that pose unique challenges in diagnosis and differentiation from benign lesions. There are no specific clinical or serological markers of GBC. Imaging plays key role not only staging but also prognostication. Ultrasound (US) the initial test choice allows risk stratification wall thickening polypoidal type gallbladder US findings guide further investigations management. Computed tomography (CT) for as it comprehensive evaluation lesion, liver involvement, lymph nodes, peritoneum, other distant sites potential metastases. Magnetic resonance imaging (MRI) magnetic cholangiopancreatography allow better delineation biliary system involvement. Contrast-enhanced advanced MRI techniques including diffusion-weighted dynamic contrast-enhanced used problem-solving tools cases where distinction lesion challenging at CT. Positron emission selected accurate disease. In this review, we provide an up-to-date insight into diagnosis, staging, prognostication

Language: Английский

Radiomics in Early Detection of Bilio-Pancreatic Lesions: A Narrative Review DOI
Calogero Casà, Daniel Portik, Ahmed Nadeem Abbasi

et al.

Best Practice & Research Clinical Gastroenterology, Journal Year: 2025, Volume and Issue: unknown, P. 101997 - 101997

Published: Feb. 1, 2025

Language: Английский

Citations

0
GBCHV an advanced deep learning anatomy aware model for accurate classification of gallbladder cancer utilizing ultrasound images DOI Creative Commons
Md. Zahid Hasan, Md. Awlad Hossen Rony,

Sadia Sultana Chowa

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 28, 2025

This study introduces a novel deep learning approach aimed at accurately classifying Gallbladder Cancer (GBC) into benign, malignant, and normal categories using ultrasound images from the challenging GBC USG (GBCU) dataset. The proposed methodology enhances image quality specifies gallbladder wall boundaries by employing sophisticated processing techniques like median filtering contrast-limited adaptive histogram equalization. Unlike traditional convolutional neural networks, which struggle with complex spatial patterns, transformer-based model, Horizontal-Vertical Transformer (GBCHV), incorporates GBCHV-Trans block self-attention mechanisms. In order to make model anatomy-aware, square-shaped input patches of transformer are transformed horizontal vertical strips obtain distinctive relationships within tissues. novelty this lies in its anatomy-aware mechanism, employs horizontal-vertical strip transformations depict anatomical features more accurately. achieved an overall diagnostic accuracy 96.21% performing ablation study. A performance comparison between seven transfer models is further conducted, where consistently outperformed models, showcasing superior robustness. Moreover, decision-making process explained visually through utilization Gradient-weighted Class Activation Mapping (Grad-CAM). With integration advanced techniques, offers promising solution for precise early-stage classification GBC, surpassing conventional methods efficacy.

Language: Английский

Citations

0
Applications of artificial intelligence in biliary tract cancers DOI
Pankaj Gupta, Soumen Basu, Chetan Arora

et al.

Indian Journal of Gastroenterology, Journal Year: 2024, Volume and Issue: 43(4), P. 717 - 728

Published: March 1, 2024

Language: Английский

Citations

3
Exploring the Incremental Value of Aorta Enhancement Normalization Method in Evaluating Renal Cell Carcinoma Histological Subtypes: A Multi-center Large Cohort Study DOI
Zexin Huang, Lei Wang,

Hangru Mei

et al.

Academic Radiology, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

0
Deep learning-based segmentation of gallbladder cancer on abdominal computed tomography scans: a multicenter study DOI
Pankaj Gupta,

Niharika Dutta,

Ajay Tomar

et al.

Abdominal Radiology, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

Citations

0
Advances and current research status of early diagnosis for gallbladder cancer DOI
Jiajia He,

Wei-Lv Xiong,

Wei-Qi Sun

et al.

Hepatobiliary & pancreatic diseases international, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 1, 2024

Language: Английский

Citations

2
A Systematic Review on Role of Deep Learning in CT scan for Detection of Gall Bladder Cancer DOI
Abhishek Sehrawat, Varun P. Gopi, Anita Gupta

et al.

Archives of Computational Methods in Engineering, Journal Year: 2024, Volume and Issue: 31(6), P. 3303 - 3311

Published: Feb. 5, 2024

Language: Английский

Citations

1
Update on the Role of Imaging in the Diagnosis, Staging, and Prognostication of Gallbladder Cancer DOI Creative Commons

Pratyaksha Rana,

Daneshwari Kalage, Raghuraman Soundararajan

et al.

Indian journal of radiology and imaging - new series/Indian journal of radiology and imaging/Indian Journal of Radiology & Imaging, Journal Year: 2024, Volume and Issue: 35(02), P. 218 - 233

Published: Aug. 26, 2024

Abstract Gallbladder cancer (GBC) is a highly aggressive malignancy with dismal prognosis. GBC characterized by marked geographic predilection. has distinct morphological types that pose unique challenges in diagnosis and differentiation from benign lesions. There are no specific clinical or serological markers of GBC. Imaging plays key role not only staging but also prognostication. Ultrasound (US) the initial test choice allows risk stratification wall thickening polypoidal type gallbladder US findings guide further investigations management. Computed tomography (CT) for as it comprehensive evaluation lesion, liver involvement, lymph nodes, peritoneum, other distant sites potential metastases. Magnetic resonance imaging (MRI) magnetic cholangiopancreatography allow better delineation biliary system involvement. Contrast-enhanced advanced MRI techniques including diffusion-weighted dynamic contrast-enhanced used problem-solving tools cases where distinction lesion challenging at CT. Positron emission selected accurate disease. In this review, we provide an up-to-date insight into diagnosis, staging, prognostication

Language: Английский

Citations

0