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 (CTDIvol), 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. DRL values of the clinical indications for cancer, urinary system stones and other pathologies were assessed based on the BMI classifications using the median and 75th percentile. An image subtraction algorithm was used to assess the image quality metrics (IQM) of the CT images. RESULTS: The 75th percentile for SSDEAP dimension for CAP cancer was 19.7, 14.9 and 12.7 mGy at Hospitals A, C and E, respectively. The median DLP for other AbP pathologies was 556.3, 1452.0 and 1960.7 mGy.cm for normal weight, overweight and obese patients, respectively, at Hospital A. The image quality varied among BMI classifications for different clinically indicated examinations. Although the dose increased with BMI, the image quality index was consistent because automatic tube current modulation (ATCM) was used. CONCLUSION: DRL values are influenced by patient size-related parameters and the clinical indication protocols, while the image quality index is independent of the BMI. IMPLICATIONS FOR PRACTICE: Size-related clinical DRL values and image quality index can be used to monitor and optimise dose and image quality. Acquisition parameters and image quality indexes should be investigated and adjusted when unusually high DRL values are noted.

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. METHOD: Polymethylmethacrylate (PMMA) slabs were stacked on each other to simulate patient thicknesses. The abdomen protocol of the unit was selected for the study. The entrance dose rates to the surface of the PMMA slabs and the scattered radiation were measured for an undercouch configuration with and without RRGs in the FOV. The exposure parameters were noted. The scattered radiation for an overcouch configuration was measured. RESULTS: The entrance dose rate increases as the FOV decreases for a fixed thickness of PMMA. The presence of RRGs in the FOV increases the exposure parameters, entrance dose rates and the scattered radiation to the eyes of the interventionalist. For the first level of RRG coverage, percentage increases in entrance dose rates and eye doses for the 23 cm FOV for all thicknesses of PMMA slabs ranged from 1.0% to 17.0% and 20.0%-30.0%, respectively; for the second level of RRG coverage, the entrance dose rates ranged from 17.0% to 45.0% and the eye doses from 50.0% to 60.0%. Percentage increases depend on the FOV, the patient's thickness, and the size and orientation of the RRGs in the FOV. Scattered radiation to the eyes of the interventionalist increases with an overcouch configuration compared to an undercouch configuration. CONCLUSION: Sterile RRGs protects the hands of the interventionalist against scattered radiation. But in the FOV, they increase the scattered radiation to the personnel and the patient entrance dose rate. IMPLICATIONS FOR PRACTICE: For best practice in C-arm fluoroscopy-guided procedures, appropriate FOV and C-arm orientation should be selected, whilst RRGs should not be in the path of the primary beam unless necessary.

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. For each mass lesion, final contours were obtained by propagation of a proposed initial level set contour and by propagation of a manually drawn contour enclosing the region of interest. Differences in shape-based descriptors were quantified using absolute percentage differences, Euclidean distances, and Bland-Altman analysis. Segmented areas were evaluated with the area overlap measure. Differences were dependent upon the characteristics of the mass margins. Boundary moments presented large percentage differences. Pearson correlation analysis showed statistically significant correlations between shape-based descriptors from both initial locations. In conclusion, boundary moments of digital mass lesions are sensitive to the placement of initial level set contours while shape-based descriptors such as Fourier descriptors, shape convexity, and shape rectangularity exhibit a certain degree of robustness to changes in the location of the initial level set contours for both segmentation algorithms.