Tao, Ashley

Abstract Background The IEC exposure index (EI), deviation index (DI), and target exposure index (EI T ), represent critical standardized metrics for the evaluation of exposure and quality in radiographic imaging. Purpose This work develops and validates a systematic procedure to estimate the EI T for eight of the most common radiography imaging protocols utilizing automatic exposure control (AEC) from measurements acquired under reference conditions. Methods A model was developed to define the relationship between a systems AEC logic, and an estimation of the EI under flat‐field conditions (EIFFC). Separately, clinical data and acquisition protocol information for resultant EI during patient studies were also collected for the eight protocols studied: Chest posteroanterior (PA), Chest lateral, Abdomen anteroposterior (AP), Pelvis AP, L‐Spine AP, C‐Spine AP, T‐Spine AP, and Ribs AP. Data were collected from 41 x‐ray units spanning seven institutions. For each protocol on each unit the EIFFC was computed based on the acquisition protocol, as well as median EI from clinical exams to produce a scaling factor (SF). Kruskal–Wallis statistical tests were used to compare SF's between vendors and AEC cell configurations. Results SFs for eight radiographic imaging protocols have been produced per vendor and per AEC cell selection. A workflow has been established for end‐users to follow to apply these SFs to flat‐field measurements taken at their own locations to establish local EI T . Conclusions The study results show that in seven of the eight imaging protocols, the SFs for most units included in the study report SFs within 1 DI (± 25%) of their respective final vendor reported SF (218/228). The ribs protocol is the exception to this finding (n = 26). SFs have high utility for establishing EI T values on individual x‐ray units and normalizing EI value distributions for quality assurance purposes.

Abstract Assessment of x-ray angiography system performance is typically performed using stationary test objects with simple geometries such as a disk on a uniform background. However, these methods do not represent realistic imaging conditions in interventional cardiology as anatomy and devices are inherently non-stationary due to cardiac motion. In this work, a novel implementation of the channelized Hotelling observer (CHO) was used to assess the influence of motion blur on object detectability. A standard CHO model assumes imaging system stationarity whereby the detectability index of a test object is independent of location. However, real angiography systems are inherently non-stationary. While vendor correction gain factors and offset maps are used to compensate for visual non-uniformities, these corrections do not restore stationarity to the images. Methods to accommodate non-stationarity and allow assessment of the influence of motion blur on test object detectability will be presented. The effect of motion blur was quantified with the relative detectability index ( ), where the for an object when moving with constant linear velocity was compared to a low velocity ‘pseudo-stationary’ condition to account for system non-stationarity. The pseudo-stationary condition was used to isolate the influences of spatial non-stationarity and motion blur. Three different test object shapes (disks, spheres and capsules) with linear velocity in the range 0–30 cm · s −1 were tested. For 1 mm diameter objects and linear velocity 30 cm · s −1 , was degraded by 37%, 33% and 42% for the disk, sphere and capsule respectively, relative to the pseudo-stationary condition. Considering all test objects with diameter greater than 2 mm and linear velocity 30 cm · s −1 , was degraded by less than 10% due to motion. In summary, this work describes a new approach to assess performance of x-ray angiography systems using the CHO model and moving test objects.

PurposeWhile scatter from the patient is assumed to be the primary source of occupational radiation dose associated with fluoroscopically guided interventional procedures, the potential contribution of scatter from the x‐ray collimator assembly is unknown. The purpose of this work was to survey clinical x‐ray angiography systems to assess the potential contribution of collimator assembly scatter on occupational radiation dose.MethodsExperimental methods were designed to measure the relative contributions of scatter originating from within the collimator assembly of the x‐ray tube to total scatter, which included scatter from a patient‐simulating phantom. Measurements were acquired as a function of lateral distance from the x‐ray beam center using a posterior anterior (PA) projection and at a fixed location for variable right anterior oblique to left anterior oblique projections in the range −90º to 90º. For one system, the collimator assembly was partially disassembled to assess the scatter contribution of individual components. For two systems, 0.5 mm Pb was added to the inner surface of the collimator assembly cover and tested for efficacy to block collimator assembly scatter.ResultsConsidering all x‐ray systems and only the PA projection, collimator assembly scatter contributed 20–50% to total scatter. For x‐ray projection angles of −90º to 90º, the relative contribution of collimator assembly to total scatter was dependent on projection angle and ranged from 5% to 56%. X‐ray systems with kerma‐area product meters demonstrated higher collimator assembly scatter than those without. Considering all projection angles, the addition of 0.5 mm Pb to the inside of the collimator assembly cover reduced collimator assembly scatter from 28% to 16% of total scatter for both systems.ConclusionFindings from this work suggest that contemporary radiation safety practices and guidelines should be revised to account for scatter originating from the collimator assembly of angiographic x‐ray tubes.

BackgroundGradient nonlinearity (GNL) leads to biased apparent diffusion coefficients (ADCs) in diffusion‐weighted imaging. A gradient nonlinearity correction (GNLC) method has been developed for whole body systems, but is yet to be tested for the new compact 3T (C3T) scanner, which exhibits more complex GNL due to its asymmetrical design.PurposeTo assess the improvement of ADC quantification with GNLC for the C3T scanner.Study TypePhantom measurements and retrospective analysis of patient data.Phantom/SubjectsA diffusion quality control phantom with vials containing 0–30% polyvinylpyrrolidone in water was used. For in vivo data, 12 patient exams were analyzed (median age, 33).Field Strength/SequenceImaging was performed on the C3T and two commercial 3T scanners. A clinical DWI (repetition time [TR] = 10,000 msec, echo time [TE] = minimum, b = 1000 s/mm2) sequence was used for phantom imaging and 10 patient cases and a clinical DTI (TR = 6000–10,000 msec, TE = minimum, b = 1000 s/mm2) sequence was used for two patient cases.AssessmentThe 0% vial was measured along three orthogonal axes, and at two different temperatures. The ADC for each concentration was compared between the C3T and two whole‐body scanners. Cerebrospinal fluid and white matter ADCs were quantified for each patient and compared to values in literature.Statistical TestsPaired t‐test and two‐way analysis of variance (ANOVA).ResultsFor all PVP concentrations, the corrected ADC was within 2.5% of the reference ADC. On average, the ADC of cerebrospinal fluid and white matter post‐GNLC were within 1% and 6%, respectively, of values reported in the literature and were significantly different from the uncorrected data (P < 0.05).Data ConclusionThis study demonstrated that GNL effects were more severe for the C3T due to the asymmetric gradient design, but our implementation of a GNLC compensated for these effects, resulting in ADC values that are in good agreement with values from the literature.Level of Evidence: 4Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2018;48:1498–1507