LowDoseCT

Low-dose computed tomography (LowDoseCT) refers to CT imaging protocols that aim to minimize ionizing radiation exposure while maintaining diagnostic image quality sufficient for a defined clinical task.

Dose reduction is achieved through multiple strategies, including lowering tube current (mA) and tube voltage (kV), applying automatic exposure control and dose modulation, and using sparse sampling. Image quality is further preserved with advanced reconstruction techniques such as iterative reconstruction, model-based iterative reconstruction, and deep learning-based denoising that compensate for increased noise.

Common indications include lung cancer screening in high-risk individuals, pediatric chest imaging to reduce lifetime radiation, and short-interval follow-up of known nodules or other thoracic conditions where repeated scans are required.

Safety aspects and dose metrics: radiation exposure is reported as CTDIvol and dose-length product (DLP), which are used to estimate the effective dose. The goal is to follow ALARA (as low as reasonably achievable) and tailor protocols to patient size and clinical need, balancing image quality against dose.

Limitations: Increased noise and potential artifacts can reduce sensitivity for small or low-contrast findings, particularly at very low doses. The performance depends on reconstruction algorithms and scanner capabilities, and LDCT may not be adequate for all diagnostic tasks without adjustments.

History and research: The approach matured in the late 20th century with the introduction of iterative reconstruction, with modern LDCT contributing to lung cancer screening programs. Ongoing work includes AI-based reconstructions and task-specific dose optimization to further improve accuracy at low exposures.