PURPOSE: To investigate the value of a computed tomography (CT)-based deep learning (DL) model to predict the presence of micropapillary or solid (M/S) growth pattern in invasive lung adenocarcinoma (ILADC).
Journal of magnetic resonance imaging : JMRI
Mar 12, 2024
BACKGROUND: Early and accurate identification of lymphatic node metastasis (LNM) and lymphatic vascular space invasion (LVSI) for endometrial cancer (EC) patients is important for treatment design, but difficult on multi-parametric MRI (mpMRI) images...
Liver international : official journal of the International Association for the Study of the Liver
Mar 4, 2024
BACKGROUND AND AIMS: Accurate preoperative prediction of microvascular invasion (MVI) and recurrence-free survival (RFS) is vital for personalised hepatocellular carcinoma (HCC) management. We developed a multitask deep learning model to predict MVI ...
PURPOSE: To investigate the value of a multimodal deep learning (MDL) model based on computed tomography (CT) and magnetic resonance imaging (MRI) for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC).
BACKGROUND: The incidence of breast cancer ranks highest among cancers and is exceedingly heterogeneous. Immunohistochemical staining is commonly used clinically to identify the molecular subtype for subsequent treatment and prognosis.
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Feb 3, 2024
Approximately 10% of submucosal invasive (T1) colorectal cancers demonstrate extraintestinal lymph node metastasis, necessitating surgical intervention with lymph node dissection. The ability to identify T1b (submucosal invasion depth ≥ 1000 µm) as a...
PURPOSE: To develop a deep learning (DL) model based on preoperative contrast-enhanced computed tomography (CECT) images to predict microvascular invasion (MVI) and pathological differentiation of hepatocellular carcinoma (HCC).
PURPOSE: To develop a convolutional neural network (CNN) model to diagnose skull-base invasion by nasopharyngeal malignancies in CT images and evaluate the model's diagnostic performance.
RATIONALE AND OBJECTIVES: This study aimed to determine the feasibility of using the deep learning (DL) method to determine the degree (whether myometrial invasion [MI] >50%) of MI in patients with endometrial cancer (EC) based on ultrasound (US) ima...
RATIONALE AND OBJECTIVES: Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma (LUAD), and preoperative knowledge of STAS status is helpful in choosing an appropriate surgical approach.