The application value of a vendor-specific deep learning image reconstruction algorithm in "triple low" head and neck computed tomography angiography.

Background: Head and neck computed tomography angiography (CTA) technology has become the noninvasive imaging method of choice for the diagnosis and long-term follow-up of vascular lesions of the head and neck. However, issues of radiation safety and contrast nephropathy associated with CTA examinations remain concerns. In recent years, deep learning image reconstruction (DLIR) algorithms have been increasingly used in clinical studies, demonstrating their potential for dose optimization.

Reference values of normal abdominal aortic areas in Chinese population measured by contrast-enhanced computed tomography.

Objective: To generate reference values of the normal areas of the abdominal aorta at various levels among Chinese people and to explore the factors that may promote the expansion of the abdominal aorta.

Methods: The areas of normal abdominal aortas were gauged at various levels based on inner-to-inner measurements in 1,066 Chinese adult patients (>18 years) without the abdominal aortic disease. The areas of subphrenic abdominal, suprarenal abdominal, infrarenal abdominal, and distal abdominal aortas were measured.

Apparent diffusion coefficient value of diffusion-weighted imaging for differential diagnosis of ductal carcinoma in situ and infiltrating ductal carcinoma.

Purpose: The present meta-analysis investigated the clinical value of apparent diffusion coefficient (ADC) values in diffusion-weighted imaging (DWI) for differential diagnosis of ductal carcinoma in situ (DCIS) and infiltrating ductal carcinoma (IDC).

Materials And Methods: Electronic databases searches were employed to identify relevant scientific literature, and the search results were screened to selected high-quality studies for this meta-analysis. Methodological quality of the enrolled studies was evaluated by quality evaluation of diagnostic accuracy studies (QUADAS).