FACTORS INFLUENCING SIZE-SPECIFIC DOSE ESTIMATES OF SELECTED COMPUTED TOMOGRAPHY PROTOCOLS AT TWO CLINICAL PRACTICES IN SOUTH AFRICA.

The study aimed to determine the factors that impact the size-specific dose estimate (SSDE) for computed tomography (CT) examinations of the chest-abdomen-pelvis and abdomen-pelvis protocols in two clinical radiology practices and evaluate the image quality of these protocols. Imaging parameters, protocols, dose metrics from the CT units and size-related parameters to calculate the SSDE were documented. The image quality of the CT images was assessed using an image subtraction algorithm. The SSDE increased as the volumetric CT dose index (CTDIvol), and the patient's body mass index increased, respectively. Significant differences (p < 0.001) occurred between the two hospitals regarding image quality. However, these differences were not indicative of differences in the diagnostic performances for task-based imaging protocols. Different clinical protocols should be reviewed to optimise dose. The inclusion of the pre-monitoring sequence, age of the machine and the scan requisition parameters impacted the SSDEs. Image quality should be assessed to evaluate the consistency of image quality between protocols applied by different CT units when assessing SSDEs.

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. Quadratic surface plots reveal that the exposure parameters of the default AEC mode are optimised for the 4-cm thickness of the PMMA. However, the exposure parameters of the 5-cm thickness of PMMA need fine-tuning to obtain a maximum value for the FOM.

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 18.4% less than the average breast compression force of mammograms without mass lesions. The average mean glandular dose (MGD), tube potential (kVp) and compressed breast thickness (CBT) values were 2.14 mGy, 30.5 kVp and 63.9 mm, respectively, for mammograms with mass lesions, and 1.45 mGy, 29.6 kVp and 56.9 mm, respectively, for mammograms without mass lesions. Overall, the average MGD and mean CBT of mammograms with mass lesion were significantly higher compared to those without mass lesions (p < 0.05), although there was no significant difference in their tube potentials (p > 0.05).

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. We compared our results with the Chan-Vese segmentation and a published global segmentation model on masses detected on direct digital mammograms. METHODS AND MATERIALS: The regional term of the convex active contour model maximizes the posterior partitioning probability for binary segmentation. Suppose the probability matrix is binary thresholded using the particle swarm optimization to obtain a value T1, we define the optimal threshold value for the global minimizer of the convex active contour as the mean intensity of all pixels whose probabilities are greater than T1. RESULTS: The mean Jaccard similarity indices were 0.89±0.07 for the proposed/Chan-Vese method and 0.88±0.06 for the proposed/published segmentation model. The mean Euclidean distance between Fourier descriptors of the segmented areas was 0.05±0.03 for the proposed/Chan-Vese method and 0.06±0.04 for the proposed/published segmentation model. CONCLUSIONS: This efficient method avoids problems of initial level set contour placement and contour re-initialization. Moreover, optimum segmentation results are realized for all masses improving on the fixed threshold value of 0.5 proposed elsewhere.