Clinical diagnostic reference levels and image quality metrics for CT in oncology patients.

Background: In CT, the volumetric CT dose index (CTDI), dose-length product (DLP) and patient's size-specific dose estimates (SSDE) are used as diagnostic reference level (DRL) metrics.

Objectives: To develop clinical local DRL values for CT chest-abdomen-pelvis (CAP) examinations using the CTDI, DLP and SSDE, and to determine the image quality achieved.

Method: In total, 201 cancer patients were included in the study.

Size based dependence of patient dose metrics, and image quality metrics for clinical indicator-based imaging protocols in abdominal CT procedures.

Introduction: Diagnostic reference level (DRL) values for computed tomography (CT) based on clinical indication are warranted since imaging protocols are indication-dependent. This study proposes clinical DRL values using the CT dose metrics and five patient size-related parameters while considering image quality.

Methods: The volumetric CT dose index (CTDI), dose-length product (DLP) and five size-related parameters of size-specific dose estimates (SSDE), namely the anterior-posterior (AP) dimension, lateral (LAT) dimension, sum dimension, effective diameter, and the body mass index (BMI), were used to calculate DRL values for CT chest-abdomen-pelvis (CAP) and abdomen-pelvis (AbP) protocols.

Influence of radiation dose reduction gloves on exposure parameters, entrance dose rates and eye doses of interventionalists during mobile C-arm fluoroscopic procedures: A phantom study.

Introduction: During fluoroscopic examinations, radiation dose reduction gloves (RRGs) protect the hands of the interventionalist against ionising scattered radiation from the patient. Some fluoroscopic procedures may require the hands of the interventionalist in the path of the primary X-ray beam. This study investigates the influence of RRGs in the field of view (FOV) on exposure parameters, entrance dose rates and eye doses of interventionalists during mobile C-arm fluoroscopic procedures.

VERIFICATION AND OPTIMISATION OF PRESELECTED EXPOSURE PARAMETERS IN SCREENING MAMMOGRAPHY: A CENTRAL COMPOSITE DESIGN METHODOLOGY.

In screening mammography, the automatic exposure control (AEC) device selects the optimum exposure parameters for each patient exposure. In practice, this device is calibrated to deliver an optimum figure of merit (FOM) for each set of exposure parameters. This study utilises the central composite design methodology to verify the operating level of the AEC performance for polymethyl methacrylate (PMMA) thicknesses of 4 and 5 cm.

EXPOSURE PARAMETERS OF MAMMOGRAMS WITH AND WITHOUT MASS LESIONS FROM A SOUTH AFRICAN BREAST CARE CENTRE.

In South African breast care centres, full-field digital mammography units provide breast imaging services to symptomatic and asymptomatic women simultaneously. This study evaluated the technical exposure parameters of 800 mammograms of which 100 mammograms had obvious mass lesions in the fibroglandular tissue. The average breast compression force of mammograms with mass lesions in the fibroglandular tissue was 18.

Interactive breast mass segmentation using a convex active contour model with optimal threshold values.

Introduction: A convex active contour model requires a predefined threshold value to determine the global solution for the best contour to use when doing mass segmentation. Fixed thresholds or manual tuning of threshold values for optimum mass boundary delineation are impracticable. A proposed method is presented to determine an optimized mass-specific threshold value for the convex active contour derived from the probability matrix of the mass with the particle swarm optimization method.

Dependence of Shape-Based Descriptors and Mass Segmentation Areas on Initial Contour Placement Using the Chan-Vese Method on Digital Mammograms.

Variation in signal intensity within mass lesions and missing boundary information are intensity inhomogeneities inherent in digital mammograms. These inhomogeneities render the performance of a deformable contour susceptible to the location of its initial position and may lead to poor segmentation results for these images. We investigate the dependence of shape-based descriptors and mass segmentation areas on initial contour placement with the Chan-Vese segmentation method and compare these results to the active contours with selective local or global segmentation model.