Image Quality and Lesion Detection on Deep Learning Reconstruction and Iterative Reconstruction of Submillisievert Chest and Abdominal CT.

OBJECTIVE. The objective of this study was to compare image quality and clinically significant lesion detection on deep learning reconstruction (DLR) and iterative reconstruction (IR) images of submillisievert chest and abdominopelvic CT. MATERIALS AND METHODS. Our prospective multiinstitutional study included 59 adult patients (33 women, 26 men; mean age ± SD, 65 ± 12 years old; mean body mass index [weight in kilograms divided by the square of height in meters] = 27 ± 5) who underwent routine chest (n = 22; 16 women, six men) and abdominopelvic (n = 37; 17 women, 20 men) CT on a 640-MDCT scanner (Aquilion ONE, Canon Medical Systems). All patients gave written informed consent for the acquisition of low-dose (LD) CT (LDCT) after a clinically indicated standard-dose (SD) CT (SDCT). The SDCT series (120 kVp, 164-644 mA) were reconstructed with interactive reconstruction (IR) (adaptive iterative dose reduction [AIDR] 3D, Canon Medical Systems), and the LDCT (100 kVp, 120 kVp; 30-50 mA) were reconstructed with filtered back-projection (FBP), IR (AIDR 3D and forward-projected model-based iterative reconstruction solution [FIRST], Canon Medical Systems), and deep learning reconstruction (DLR) (Advanced Intelligent Clear-IQ Engine [AiCE], Canon Medical Systems). Four subspecialty-trained radiologists first read all LD image sets and then compared them side-by-side with SD AIDR 3D images in an independent, randomized, and blinded fashion. Subspecialty radiologists assessed image quality of LDCT images on a 3-point scale (1 = unacceptable, 2 = suboptimal, 3 = optimal). Descriptive statistics were obtained, and the Wilcoxon sign rank test was performed. RESULTS. Mean volume CT dose index and dose-length product for LDCT (2.1 ± 0.8 mGy, 49 ± 13mGy·cm) were lower than those for SDCT (13 ± 4.4 mGy, 567 ± 249 mGy·cm) (p < 0.0001). All 31 clinically significant abdominal lesions were seen on SD AIDR 3D and LD DLR images. Twenty-five, 18, and seven lesions were detected on LD AIDR 3D, LD FIRST, and LD FBP images, respectively. All 39 pulmonary nodules detected on SD AIDR 3D images were also noted on LD DLR images. LD DLR images were deemed acceptable for interpretation in 97% (35/37) of abdominal and 95-100% (21-22/22) of chest LDCT studies (p = 0.2-0.99). The LD FIRST, LD AIDR 3D, and LD FBP images had inferior image quality compared with SD AIDR 3D images (p < 0.0001). CONCLUSION. At submillisievert chest and abdominopelvic CT doses, DLR enables image quality and lesion detection superior to commercial IR and FBP images.

Comparison of radiation dose estimates, image noise, and scan duration in pediatric body imaging for volumetric and helical modes on 320-detector CT and helical mode on 64-detector CT.

BACKGROUND: Advanced multidetector CT systems facilitate volumetric image acquisition, which offers theoretic dose savings over helical acquisition with shorter scan times. OBJECTIVE: Compare effective dose (ED), scan duration and image noise using 320- and 64-detector CT scanners in various acquisition modes for clinical chest, abdomen and pelvis protocols. MATERIALS AND METHODS: ED and scan durations were determined for 64-detector helical, 160-detector helical and volume modes under chest, abdomen and pelvis protocols on 320-detector CT with adaptive collimation and 64-detector helical mode on 64-detector CT without adaptive collimation in a phantom representing a 5-year-old child. Noise was measured as standard deviation of Hounsfield units. RESULTS: Compared to 64-detector helical CT, all acquisition modes on 320-detector CT resulted in lower ED and scan durations. Dose savings were greater for chest (27-46%) than abdomen/pelvis (18-28%) and chest/abdomen/pelvis imaging (8-14%). Noise was similar across scanning modes, although some protocols on 320-detector CT produced slightly higher noise. CONCLUSION: Dose savings can be achieved for chest, abdomen/pelvis and chest/abdomen/pelvis examinations on 320-detector CT compared to helical acquisition on 64-detector CT, with shorter scan durations. Although noise differences between some modes reached statistical significance, this is of doubtful diagnostic significance and will be studied further in a clinical setting.

Radiation dose estimation for prospective and retrospective ECG-gated cardiac CT angiography in infants and small children using a 320-MDCT volume scanner.

OBJECTIVE: The purpose of this study is to determine patient dose estimates for clinical pediatric cardiac-gated CT angiography (CTA) protocols on a 320-MDCT volume scanner. MATERIALS AND METHODS: Organ doses were measured using 20 metal oxide semiconductor field effect transistor (MOSFET) dosimeters. Radiation dose was estimated for volumetrically acquired clinical pediatric prospectively and retrospectively ECG-gated cardiac CTA protocols in 5-year-old and 1-year-old anthropomorphic phantoms on a 320-MDCT scanner. Simulated heart rates of 60 beats/min (5-year-old phantom) and 120 beats/min (1- and 5-year-old phantoms) were used. Effective doses (EDs) were calculated using average measured organ doses and International Commission on Radiological Protection 103 tissue-weighting factors. Dose-length product (DLP) was recorded for each examination and was used to develop dose conversion factors for pediatric cardiac examinations acquired with volume scan mode. DLP was also used to estimate ED according to recently published dose conversion factors for pediatric helical chest examinations. Repeated measures and paired Student t test analyses were performed. RESULTS: For the 5-year-old phantom, at 60 beats/min, EDs ranged from 1.2 mSv for a prospectively gated examination to 4.5 mSv for a retrospectively gated examination. For the 5-year-old phantom, at 120 beats/min, EDs ranged from 3.0 mSv for a prospectively gated examination to 4.9 mSv for a retrospectively gated examination. For the 1-year-old phantom, at 120 beats/min, EDs ranged from 2.7 mSv for a prospectively gated examination to 4.5 mSv for a retrospectively gated examination. CONCLUSION: EDs for 320-MDCT volumetrically acquired ECG-gated pediatric cardiac CTA are lower than those published for conventional 16- and 64-MDCT scanners.

Reference dataset for benchmarking fetal doses derived from Monte Carlo simulations of CT exams.

PURPOSE: Task Group Report 195 of the American Association of Physicists in Medicine contains reference datasets for the direct comparison of results among different Monte Carlo (MC) simulation tools for various aspects of imaging research that employs ionizing radiation. While useful for comparing and validating MC codes, that effort did not provide the information needed to compare absolute dose estimates from CT exams. Therefore, the purpose of this work is to extend those efforts by providing a reference dataset for benchmarking fetal dose derived from MC simulations of clinical CT exams. ACQUISITION AND VALIDATION METHODS: The reference dataset contains the four necessary elements for validating MC engines for CT dosimetry: (a) physical characteristics of the CT scanner, (b) patient information, (c) exam specifications, and (d) fetal dose results from previously validated and published MC simulations methods in tabular form. Scanner characteristics include non-proprietary descriptions of equivalent source cumulative distribution function (CDF) spectra and bowtie filtration profiles, as well as scanner geometry information. Additionally, for the MCNPX MC engine, normalization factors are provided to convert raw simulation results to absolute dose in mGy. The patient information is based on a set of publicly available fetal dose models and includes de-identified image data; voxelized MC input files with fetus, uterus, and gestational sac identified; and patient size metrics in the form of water equivalent diameter (Dw ) z-axis distributions from a simulated topogram (Dw,topo ) and from the image data (Dw,image ). Exam characteristics include CT scan start and stop angles and table and patient locations, helical pitch, nominal collimation and measured beam width, and gantry rotation time for each simulation. For simulations involving estimating doses from exams using tube current modulation (TCM), a realistic TCM scheme is presented that is estimated based upon a validated method. (d) Absolute and CTDIvol -normalized fetal dose results for both TCM and FTC simulations are given for each patient model under each scan scenario. DATA FORMAT AND USAGE NOTES: Equivalent source CDFs and bowtie filtration profiles are available in text files. Image data are available in DICOM format. Voxelized models are represented by a header followed by a list of integers in a text file representing a three-dimensional model of the patient. Size distribution metrics are also given in text files. Results of absolute and normalized fetal dose with associated MC error estimates are presented in tabular form in an Excel spreadsheet. All data are stored on Zenodo and are publicly accessible using the following link: https://zenodo.org/record/3959512. POTENTIAL APPLICATIONS: Similar to the work of AAPM Report 195, this work provides a set of reference data for benchmarking fetal dose estimates from clinical CT exams. This provides researchers with an opportunity to compare MC simulation results to a set of published reference data as part of their efforts to validate absolute and normalized fetal dose estimates. This could also be used as a basis for comparison to other non-MC approaches, such as deterministic approaches, or to commercial packages that provide estimates of fetal doses from clinical CT exams.

The feasibility of a scanner-independent technique to estimate organ dose from MDCT scans: using CTDIvol to account for differences between scanners.

PURPOSE: Monte Carlo radiation transport techniques have made it possible to accurately estimate the radiation dose to radiosensitive organs in patient models from scans performed with modern multidetector row computed tomography (MDCT) scanners. However, there is considerable variation in organ doses across scanners, even when similar acquisition conditions are used. The purpose of this study was to investigate the feasibility of a technique to estimate organ doses that would be scanner independent. This was accomplished by assessing the ability of CTDIvol measurements to account for differences in MDCT scanners that lead to organ dose differences. METHODS: Monte Carlo simulations of 64-slice MDCT scanners from each of the four major manufacturers were performed. An adult female patient model from the GSF family of voxelized phantoms was used in which all ICRP Publication 103 radiosensitive organs were identified. A 120 kVp, full-body helical scan with a pitch of 1 was simulated for each scanner using similar scan protocols across scanners. From each simulated scan, the radiation dose to each organ was obtained on a per mA s basis (mGy/mA s). In addition, CTDIvol values were obtained from each scanner for the selected scan parameters. Then, to demonstrate the feasibility of generating organ dose estimates from scanner-independent coefficients, the simulated organ dose values resulting from each scanner were normalized by the CTDIvol value for those acquisition conditions. RESULTS: CTDIvol values across scanners showed considerable variation as the coefficient of variation (CoV) across scanners was 34.1%. The simulated patient scans also demonstrated considerable differences in organ dose values, which varied by up to a factor of approximately 2 between some of the scanners. The CoV across scanners for the simulated organ doses ranged from 26.7% (for the adrenals) to 37.7% (for the thyroid), with a mean CoV of 31.5% across all organs. However, when organ doses are normalized by CTDIvoI values, the differences across scanners become very small. For the CTDIvol, normalized dose values the CoVs across scanners for different organs ranged from a minimum of 2.4% (for skin tissue) to a maximum of 8.5% (for the adrenals) with a mean of 5.2%. CONCLUSIONS: This work has revealed that there is considerable variation among modern MDCT scanners in both CTDIvol and organ dose values. Because these variations are similar, CTDIvol can be used as a normalization factor with excellent results. This demonstrates the feasibility of establishing scanner-independent organ dose estimates by using CTDIvol to account for the differences between scanners.

Patient-specific 3D-printed coronary models based on coronary computed tomography angiography volumes to investigate flow conditions in coronary artery disease.

BACKGROUND: 3D printed patient-specific coronary models have the ability to enable repeatable benchtop experiments under controlled blood flow conditions. This approach can be applied to CT-derived patient geometries to emulate coronary flow and related parameters such as Fractional Flow Reserve (FFR). METHODS: This study uses 3D printing to compare such benchtop FFR results with a non-invasive CT-FFR research software algorithm and catheter based invasive FFR (I-FFR) measurements. Fifty-two patients with a clinical indication for I-FFR underwent a research Coronary CT Angiography (CCTA) prior to catheterization. CT images were used to measure CT-FFR and to generate patient-specific 3D printed models of the aortic root and three main coronary arteries. Each patient-specific model was connected to a programmable pulsatile pump and benchtop FFR (B-FFR) was derived from pressures measured proximal and distal to coronary stenosis using pressure transducers. B-FFR was measured for two coronary outflow rates ('normal', 250 ml min-1; and 'hyperemic', 500 ml min-1) by adjusting the model's distal coronary resistance. RESULTS: Pearson correlations and ROC AUC were calculated using invasive I-FFR as reference. The Pearson correlation factor of CT-FFR and B-FFR-500 was 0.75 and 0.71, respectively. Areas under the ROCs for CT-FFR and B-FFR-500 were 0.80 (95%CI: 0.70-0.87) and 0.81 (95%CI: 0.64-0.91) respectively. CONCLUSION: Benchtop flow simulations with 3D printed models provide the capability to measure pressure changes at any location in the model, for ultimately emulating the FFR at several simulated physiological blood flow conditions. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/show/NCT03149042.

Initial evaluation of a convolutional neural network used for noninvasive assessment of coronary artery disease severity from coronary computed tomography angiography data.

PURPOSE: Coronary computed tomography angiography (CTA) has one of the highest diagnostic sensitivities for detection of the significance of coronary artery disease (CAD); however, sensitivity is moderate and may result in increased catheterization rates. We performed an efficacy study to determine whether a trained machine learning algorithm that uses coronary CTA data may improve CAD diagnosis accuracy. METHODS: Sixty-four-patient image datasets based on coronary CTA were retrospectively collected to generate eight views considering 45° increments around the coronary artery centerline. The dataset was randomly split into training and testing cohorts. Invasive FFR measurements were used as ground truth labels. A convolutional neural network (CNN) was trained and the model's capacity to predict severity of CAD was assessed on the testing cohort. Classification accuracy and area under the receiver operating characteristic curve (AUROC) analysis were performed. Similar CAD severity classification accuracy and AUROC analyses were performed using only percent diameter stenosis (%DS) and CT-derived FFR performed by 13 operators with various levels of expertise. RESULTS: Classification accuracy over the test cohort was 80.9% using the trained network and 72.4% using the user-operated CT-derived FFR software. AUROC over the test cohort was 0.862 using the trained network, 0.807 using %DS, and 0.758 using the human-operated CT-derived FFR software. CONCLUSIONS: A trained neural network compared noninferiorly in-terms of classification accuracy and AUROC with human operators of a CT-derived FFR software, and in-terms of AUROC with clinical decision-making using %DS.

Pediatric organ dose measurements in axial and helical multislice CT.

An anthropomorphic pediatric phantom (5-yr-old equivalent) was used to determine organ doses at specific surface and internal locations resulting from computed tomography (CT) scans. This phantom contains four different tissue-equivalent materials: Soft tissue, bone, brain, and lung. It was imaged on a 64-channel CT scanner with three head protocols (one contiguous axial scan and two helical scans [pitch = 0.516 and 0.984]) and four chest protocols (one contiguous axial scan and three helical scans [pitch = 0.516, 0.984, and 1.375]). Effective mA s [= (tube current x rotation time)/pitch] was kept nearly constant at 200 effective mA s for head and 290 effective mA s for chest protocols. Dose measurements were acquired using thermoluminescent dosimeter powder in capsules placed at locations internal to the phantom and on the phantom surface. The organs of interest were the brain, both eyes, thyroid, sternum, both breasts, and both lungs. The organ dose measurements from helical scans were lower than for contiguous axial scans by 0% to 25% even after adjusting for equivalent effective mA s. There was no significant difference (p > 0.05) in organ dose values between the 0.516 and 0.984 pitch values for both head and chest scans. The chest organ dose measurements obtained at a pitch of 1.375 were significantly higher than the dose values obtained at the other helical pitches used for chest scans (p < 0.05). This difference was attributed to the automatic selection of the large focal spot due to a higher tube current value. These findings suggest that there may be a previously unsuspected radiation dose benefit associated with the use of helical scan mode during computed tomography scanning.

Reducing radiation dose to selected organs by selecting the tube start angle in MDCT helical scans: a Monte Carlo based study.

PURPOSE: Previous work has demonstrated that there are significant dose variations with a sinusoidal pattern on the peripheral of a CTDI 32 cm phantom or on the surface of an anthropomorphic phantom when helical CT scanning is performed, resulting in the creation of "hot" spots or "cold" spots. The purpose of this work was to perform preliminary investigations into the feasibility of exploiting these variations to reduce dose to selected radiosensitive organs solely by varying the tube start angle in CT scans. METHODS: Radiation dose to several radiosensitive organs (including breasts, thyroid, uterus, gonads, and eye lenses) resulting from MDCT scans were estimated using Monte Carlo simulation methods on voxelized patient models, including GSF's Baby, Child, and Irene. Dose to fetus was also estimated using four pregnant female models based on CT images of the pregnant patients. Whole-body scans were simulated using 120 kVp, 300 mAs, both 28.8 and 40 mm nominal collimations, and pitch values of 1.5, 1.0, and 0.75 under a wide range of start angles (0 degree-340 degrees in 20 degrees increments). The relationship between tube start angle and organ dose was examined for each organ, and the potential dose reduction was calculated. RESULTS: Some organs exhibit a strong dose variation, depending on the tube start angle. For small peripheral organs (e.g., the eye lenses of the Baby phantom at pitch 1.5 with 40 mm collimation), the minimum dose can be 41% lower than the maximum dose, depending on the tube start angle. In general, larger dose reductions occur for smaller peripheral organs in smaller patients when wider collimation is used. Pitch 1.5 and pitch 0.75 have different mechanisms of dose reduction. For pitch 1.5 scans, the dose is usually lowest when the tube start angle is such that the x-ray tube is posterior to the patient when it passes the longitudinal location of the organ. For pitch 0.75 scans, the dose is lowest when the tube start angle is such that the x-ray tube is anterior to the patient when it passes the longitudinal location of the organ. CONCLUSIONS: Helical MDCT scanning at pitch 1.5 and pitch 0.75 results in "cold spots" and "hot spots" that are created both at surface and in-depth locations within patients. For organs that have a relatively small longitudinal extent, dose can vary considerably with different start angles. While current MDCT systems do not provide the user with the ability to control the tube start angle, these results indicate that in these specific situations (pitch 1.5 or pitch 0.75, small organs and especially small patients), there could be significant dose savings to organs if that functionality would be provided.

Variability of surface and center position radiation dose in MDCT: Monte Carlo simulations using CTDI and anthropomorphic phantoms.

The larger coverage afforded by wider z-axis beams in multidetector CT (MDCT) creates larger cone angles and greater beam divergence, which results in substantial surface dose variation for helical and contiguous axial scans. This study evaluates the variation of absorbed radiation dose in both cylindrical and anthropomorphic phantoms when performing helical or contiguous axial scans. The approach used here was to perform Monte Carlo simulations of a 64 slice MDCT. Simulations were performed with different radiation profiles (simulated beam widths) for a given collimation setting (nominal beam width) and for different pitch values and tube start angles. The magnitude of variation at the surface was evaluated under four different conditions: (a) a homogeneous CTDI phantom with different combinations of pitch and simulated beam widths, (b) a heterogeneous anthropomorphic phantom with one measured beam collimation and various pitch values, (c) a homogeneous CTDI phantom with fixed beam collimation and pitch, but with different tube start angles, and (d) pitch values that should minimize variations of surface dose-evaluated for both homogeneous and heterogeneous phantoms. For the CTDI phantom simulations, peripheral dose patterns showed variation with percent ripple as high as 65% when pitch is 1.5 and simulated beam width is equal to the nominal collimation. For the anterior surface dose on an anthropomorphic phantom, the percent ripple was as high as 40% when the pitch is 1.5 and simulated beam width is equal to the measured beam width. Low pitch values were shown to cause beam overlaps which created new peaks. Different x-ray tube start angles create shifts of the peripheral dose profiles. The start angle simulations showed that for a given table position, the surface dose could vary dramatically with minimum values that were 40% of the peak when all conditions are held constant except for the start angle. The last group of simulations showed that an "ideal" pitch value can be determined which reduces surface dose variations, but this pitch value must take into account the measured beam width. These results reveal the complexity of estimating surface dose and demonstrate a range of dose variability at surface positions for both homogeneous cylindrical and heterogeneous anthropomorphic phantoms. These findings have potential implications for small-sized dosimeter measurements in phantoms, such as with TLDs or small Farmer chambers.

A method to generate equivalent energy spectra and filtration models based on measurement for multidetector CT Monte Carlo dosimetry simulations.

The purpose of this study was to present a method for generating x-ray source models for performing Monte Carlo (MC) radiation dosimetry simulations of multidetector row CT (MDCT) scanners. These so-called "equivalent" source models consist of an energy spectrum and filtration description that are generated based wholly on the measured values and can be used in place of proprietary manufacturer's data for scanner-specific MDCT MC simulations. Required measurements include the half value layers (HVL1 and HVL2) and the bowtie profile (exposure values across the fan beam) for the MDCT scanner of interest. Using these measured values, a method was described (a) to numerically construct a spectrum with the calculated HVLs approximately equal to those measured (equivalent spectrum) and then (b) to determine a filtration scheme (equivalent filter) that attenuates the equivalent spectrum in a similar fashion as the actual filtration attenuates the actual x-ray beam, as measured by the bowtie profile measurements. Using this method, two types of equivalent source models were generated: One using a spectrum based on both HVL1 and HVL2 measurements and its corresponding filtration scheme and the second consisting of a spectrum based only on the measured HVL1 and its corresponding filtration scheme. Finally, a third type of source model was built based on the spectrum and filtration data provided by the scanner's manufacturer. MC simulations using each of these three source model types were evaluated by comparing the accuracy of multiple CT dose index (CTDI) simulations to measured CTDI values for 64-slice scanners from the four major MDCT manufacturers. Comprehensive evaluations were carried out for each scanner using each kVp and bowtie filter combination available. CTDI experiments were performed for both head (16 cm in diameter) and body (32 cm in diameter) CTDI phantoms using both central and peripheral measurement positions. Both equivalent source model types result in simulations with an average root mean square (RMS) error between the measured and simulated values of approximately 5% across all scanner and bowtie filter combinations, all kVps, both phantom sizes, and both measurement positions, while data provided from the manufacturers gave an average RMS error of approximately 12% pooled across all conditions. While there was no statistically significant difference between the two types of equivalent source models, both of these model types were shown to be statistically significantly different from the source model based on manufacturer's data. These results demonstrate that an equivalent source model based only on measured values can be used in place of manufacturer's data for Monte Carlo simulations for MDCT dosimetry.

Dose to radiosensitive organs during routine chest CT: effects of tube current modulation.

OBJECTIVE: The aims of this study were to estimate the dose to radiosensitive organs (glandular breast and lung) in patients of various sizes undergoing routine chest CT examinations with and without tube current modulation; to quantify the effect of tube current modulation on organ dose; and to investigate the relation between patient size and organ dose to breast and lung resulting from chest CT examinations. MATERIALS AND METHODS: Thirty voxelized models generated from images of patients were extended to include lung contours and were used to represent a cohort of women of various sizes. Monte Carlo simulation-based virtual MDCT scanners had been used in a previous study to estimate breast dose from simulations of a fixed-tube-current and a tube current-modulated chest CT examinations of each patient model. In this study, lung doses were estimated for each simulated examination, and the percentage organ dose reduction attributed to tube current modulation was correlated with patient size for both glandular breast and lung tissues. RESULTS: The average radiation dose to lung tissue from a chest CT scan obtained with fixed tube current was 23 mGy. The use of tube current modulation reduced the lung dose an average of 16%. Reductions in organ dose (up to 56% for lung) due to tube current modulation were more substantial among smaller patients than larger. For some larger patients, use of tube current modulation for chest CT resulted in an increase in organ dose to the lung as high as 33%. For chest CT, lung dose and breast dose estimates had similar correlations with patient size. On average the two organs receive approximately the same dose effects from tube current modulation. CONCLUSION: The dose to radiosensitive organs during fixed-tube-current and tube current-modulated chest CT can be estimated on the basis of patient size. Organ dose generally decreases with the use of tube current-modulated acquisition, but patient size can directly affect the dose reduction achieved.

Monte Carlo simulations to assess the effects of tube current modulation on breast dose for multidetector CT.

Tube current modulation was designed to reduce radiation dose in CT imaging while maintaining overall image quality. This study aims to develop a method for evaluating the effects of tube current modulation (TCM) on organ dose in CT exams of actual patient anatomy. This method was validated by simulating a TCM and a fixed tube current chest CT exam on 30 voxelized patient models and estimating the radiation dose to each patient's glandular breast tissue. This new method for estimating organ dose was compared with other conventional estimates of dose reduction. Thirty detailed voxelized models of patient anatomy were created based on image data from female patients who had previously undergone clinically indicated CT scans including the chest area. As an indicator of patient size, the perimeter of the patient was measured on the image containing at least one nipple using a semi-automated technique. The breasts were contoured on each image set by a radiologist and glandular tissue was semi-automatically segmented from this region. Previously validated Monte Carlo models of two multidetector CT scanners were used, taking into account details about the source spectra, filtration, collimation and geometry of the scanner. TCM data were obtained from each patient's clinical scan and factored into the model to simulate the effects of TCM. For each patient model, two exams were simulated: a fixed tube current chest CT and a tube current modulated chest CT. X-ray photons were transported through the anatomy of the voxelized patient models, and radiation dose was tallied in the glandular breast tissue. The resulting doses from the tube current modulated simulations were compared to the results obtained from simulations performed using a fixed mA value. The average radiation dose to the glandular breast tissue from a fixed tube current scan across all patient models was 19 mGy. The average reduction in breast dose using the tube current modulated scan was 17%. Results were size dependent with smaller patients getting better dose reduction (up to 64% reduction) and larger patients getting a smaller reduction, and in some cases the dose actually increased when using tube current modulation (up to 41% increase). The results indicate that radiation dose to glandular breast tissue generally decreases with the use of tube current modulated CT acquisition, but that patient size (and in some cases patient positioning) may affect dose reduction.

Estimating fetal dose from tube current-modulated (TCM) and fixed tube current (FTC) abdominal/pelvis CT examinations.

PURPOSE: The purpose of this work was to estimate scanner-independent CTDIvol -to-fetal-dose coefficients for tube current-modulated (TCM) and fixed tube current (FTC) computed tomography (CT) examinations of pregnant patients of various gestational ages undergoing abdominal/pelvic CT examinations. METHODS: For 24 pregnant patients of gestational age from <5 to 36 weeks who underwent clinically indicated CT examinations, voxelized models of maternal and fetal (or embryo) anatomy were created from abdominal/pelvic image data. Absolute fetal dose (Dfetus ) was estimated using Monte Carlo (MC) simulations of helical scans covering the abdomen and pelvis for TCM and FTC scans. Estimated TCM schemes were generated for each patient model using a validated method that accounts for patient attenuation and scanner output limits for one scanner model and were incorporated into MC simulations. FTC scans were also simulated for each patient model with multidetector row CT scanners from four manufacturers. Normalized fetal dose estimates, nDfetus , was obtained by dividing Dfetus from the MC simulations by CTDIvol . Patient size was described using water equivalent diameter (Dw ) measured at the three-dimensional geometric centroid of the fetus. Fetal depth (DEf ) was measured from the anterior skin surface to the anterior part of the fetus. nDfetus and Dw were correlated using an exponential model to develop equations for fetal dose conversion coefficients for TCM and FTC abdominal/pelvic CT examinations. Additionally, bivariate linear regression was performed to analyze the correlation of nDfetus with Dw and fetal depth (DEf ). For one scanner model, nDfetus from TCM was compared to FTC and the size-specific dose estimate (SSDE) conversion coefficients (f-factors) from American Association of Physicists in Medicine (AAPM) Report 204. nDfetus from FTC simulations was averaged across all scanners for each patient ( n D fetus ¯ ) . n D fetus ¯ was then compared with SSDE f-factors and correlated with Dw using an exponential model and with Dw and DEf using a bivariate linear model. RESULTS: For TCM, the coefficient of determination (R2 ) of nDfetus and Dw was observed to be 0.73 using an exponential model. Using the bivariate linear model with Dw and DEf , an R2 of 0.78 was observed. For the TCM technology modeled, TCM yielded nDfetus values that were on average 6% and 17% higher relative to FTC and SSDE f-factors, respectively. For FTC, the R2 of n D fetus ¯ with respect to Dw was observed to be 0.64 using an exponential model. Using the bivariate linear model, an R2 of 0.75 was observed for n D fetus ¯ with respect to Dw and DEf . A mean difference of 0.4% was observed between n D fetus ¯ and SSDE f-factors. CONCLUSION: Good correlations were observed for nDfetus from TCM and FTC scans using either an exponential model with Dw or a bivariate linear model with both Dw and DEf . These results indicate that fetal dose from abdomen/pelvis CT examinations of pregnant patients of various gestational ages may be reasonably estimated with models that include (a) scanner-reported CTDIvol and (b) Dw as a patient size metric, in addition to (c) DEf if available. These results also suggest that SSDE f-factors may provide a reasonable (within ±25%) estimate of nDfetus for TCM and FTC abdomen/pelvis CT exams.

Can fully iterative reconstruction technique enable routine abdominal CT at less than 1 mSv?

OBJECTIVE: We assessed the effect of the forward projected model-based reconstruction technique (FIRST) on lesion detection of routine abdomen CT at <1 mSv. MATERIALS AND METHODS: Thirty-seven adult patients gave written informed consent for acquisition of low-dose CT (LDCT) immediately after their clinically-indicated, standard of care dose (SDCT), routine abdomen CT on a 640-slice MDCT (Aquillion One, Canon Medical System). The LDCT series were reconstructed with FIRST (at STD (Standard) and STR (Strong) levels), and SDCT series with filtered back projection (FBP). Two radiologists assessed lesions in LD-FBP and FIRST images followed by SDCT images. Then, SDCT and LDCT were compared for presence of artifacts in a randomized and blinded fashion. Patient demographics, size and radiation dose descriptors (CTDIvol, DLP) were recorded. Descriptive statistics and inter-observer variability were calculated for data analysis. RESULTS: Mean CTDIvol for SDCT and LDCT were 13 ± 4.7 mGy and 2.2 ± 0.8 mGy, respectively. There were 46 true positive lesions detected on SDCT. Radiologists detected 38/46 lesions on LD-FIRST-STD compared to 26/46 lesions on LD-FIRST-STR. The eight lesions (liver and kidney cysts, pancreatic lesions, sub-cm peritoneal lymph node) missed on LD-FIRST-STD were seen in patients with BMI > 25.8 kg/m2. Diagnostic confidence for lesion assessment was optimal in LD-FIRST-STD setting in most patients regardless of their size. The inter-observer agreement (kappa-value) for overall image quality were 0.98 and 0.84 for LD-FIRST-STD and STR levels, respectively. CONCLUSION: FIRST enabled optimal lesion detection in routine abdomen CT at less than 1 mSv radiation dose in patients with body mass less than ≤25.8 kg/m2.

Initial evaluation of three-dimensionally printed patient-specific coronary phantoms for CT-FFR software validation.

We developed three-dimensionally (3D) printed patient-specific coronary phantoms that are capable of sustaining physiological flow and pressure conditions. We assessed the accuracy of these phantoms from coronary CT acquisition, benchtop experimentation, and CT-FFR software. Five patients with coronary artery disease underwent 320-detector row coronary CT angiography (CCTA) (Aquilion ONE, Canon Medical Systems) and a catheter lab procedure to measure fractional flow reserve (FFR). The aortic root and three main coronary arteries were segmented (Vitrea, Vital Images) and 3D printed (Eden 260V, Stratasys). Phantoms were connected into a pulsatile flow loop, which replicated physiological flow and pressure gradients. Contrast was introduced and the phantoms were scanned using the same CT scanner model and CCTA protocol as used for the patients. Image data from the phantoms were input to a CT-FFR research software (Canon Medical Systems) and compared to those derived from the clinical data, along with comparisons between image measurements and benchtop FFR results. Phantom diameter measurements were within 1 mm on average compared to patient measurements. Patient and phantom CT-FFR results had an absolute mean difference of 4.34% and Pearson correlation of 0.95. We have demonstrated the capabilities of 3D printed patient-specific phantoms in a diagnostic software.

Inter- and Intraoperator Variability in Measurement of On-Site CT-derived Fractional Flow Reserve Based on Structural and Fluid Analysis: A Comprehensive Analysis.

PURPOSE: To measure the inter- and intraobserver variability among operators of varying expertise in conducting CT-derived fractional flow reserve (CT FFR) measurements on-site by using structural and fluid analysis and to evaluate differences in reproducibility between two different training methods for end users. MATERIALS AND METHODS: This retrospective analysis of the prospectively enrolled cohort included 22 symptomatic patients who underwent both 320-detector row coronary CT angiography and catheter-derived fractional flow reserve (FFR) within 90 days. Thirteen operators of varying expertise were assigned to one of two training arms: arm 1, on-site training by a specialist in CT FFR technology; arm 2, self-training through use of written materials. After the training, all 13 operators reviewed the CT data and measured CT FFR in 24 vessels in 22 patients. Inter- and intraoperator variability and agreements between CT FFR and catheter-derived FFR measurements were evaluated. RESULTS: The overall intraclass correlation coefficient (ICC) among operators was 0.71 (95% confidence interval: 0.58, 0.83) with a mean absolute difference (± standard deviation) of 0.027 ± 0.022. The operators in arm 2 showed greater interoperator differences than those in arm 1 (0.031 ± 0.024 vs 0.023 ± 0.018; P = .024). Among operators who recalculated CT FFR, the mean CT FFR value did not significantly differ between the first and second calculations (ICC, 0.66; 95% confidence interval: 0.46, 0.87), with the medical specialists producing the lowest intraoperator variability (0.053 ± 0.060). The overall correlation coefficient between CT FFR and catheter FFR was r = 0.61, with a mean absolute difference of 0.096 ± 0.089. CONCLUSION: Good reproducibility of CT FFR values calculated on-site on the basis of structural and fluid analysis was observed among operators of varying expertise. Face-to-face training sessions may cause less variability.© RSNA, 2019Supplemental material is available for this article.

Radiation dose to the fetus for pregnant patients undergoing multidetector CT imaging: Monte Carlo simulations estimating fetal dose for a range of gestational age and patient size.

PURPOSE: To use Monte Carlo simulations of a current-technology multidetector computed tomographic (CT) scanner to investigate fetal radiation dose resulting from an abdominal and pelvic examination for a range of actual patient anatomies that include variation in gestational age and maternal size. MATERIALS AND METHODS: Institutional review board approval was obtained for this HIPAA-compliant retrospective study. Twenty-four models of maternal and fetal anatomy were created from image data from pregnant patients who had previously undergone clinically indicated CT examination. Gestational age ranged from less than 5 weeks to 36 weeks. Simulated helical scans of the abdominal and pelvic region were performed, and a normalized dose (in milligrays per 100 mAs) was calculated for each fetus. Stepwise multiple linear regression was performed to analyze the correlation of dose with gestational age and anatomic measurements of maternal size and fetal location. Results were compared with several existing fetal dose estimation methods. RESULTS: Normalized fetal dose estimates from the Monte Carlo simulations ranged from 7.3 to 14.3 mGy/100 mAs, with an average of 10.8 mGy/100 mAs. Previous methods yielded values of 10-14 mGy/100 mAs. The correlation between gestational age and fetal dose was not significant (P = .543). Normalized fetal dose decreased linearly with increasing patient perimeter (R(2) = 0.681, P < .001), and a two-factor model with patient perimeter and fetal depth demonstrated a strong correlation with fetal dose (R(2) = 0.799, P < .002). CONCLUSION: A method for the estimation of fetal dose from models of actual patient anatomy that represented a range of gestational age and patient size was developed. Fetal dose correlated with maternal perimeter and varied more than previously recognized. This correlation improves when maternal size and fetal depth are combined.

3D Printed Cardiovascular Patient Specific Phantoms Used for Clinical Validation of a CT-derived FFR Diagnostic Software.

PURPOSE: 3D printed patient specific vascular models provide the ability to perform precise and repeatable benchtop experiments with simulated physiological blood flow conditions. This approach can be applied to CT-derived patient geometries to determine coronary flow related parameters such as Fractional Flow Reserve (FFR). To demonstrate the utility of this approach we compared bench-top results with non-invasive CT-derived FFR software based on a computational fluid dynamics algorithm and catheter based FFR measurements. MATERIALS AND METHODS: Twelve patients for whom catheter angiography was clinically indicated signed written informed consent to CT Angiography (CTA) before their standard care that included coronary angiography (ICA) and conventional FFR (Angio-FFR). The research CTA was used first to determine CT-derived FFR (Vital Images) and second to generate patient specific 3D printed models of the aortic root and three main coronary arteries that were connected to a programmable pulsatile pump. Benchtop FFR was derived from pressures measured proximal and distal to coronary stenosis using pressure transducers. RESULTS: All 12 patients completed the clinical study without any complication, and the three FFR techniques (Angio-FFR, CT-FFR, and Benchtop FFR) are reported for one or two main coronary arteries. The Pearson correlation among Benchtop FFR/Angio-FFR, CT-FFR/ Benchtop FFR, and CT-FFR/ Angio-FFR are 0.871, 0.877, and 0.927 respectively. CONCLUSIONS: 3D printed patient specific cardiovascular models successfully simulated hyperemic blood flow conditions, matching invasive Angio-FFR measurements. This benchtop flow system could be used to validate CT-derived FFR diagnostic software, alleviating both cost and risk during invasive procedures.

Initial Simulated FFR Investigation Using Flow Measurements in Patient-specific 3D Printed Coronary Phantoms.

PURPOSE: Accurate patient-specific phantoms for device testing or endovascular treatment planning can be 3D printed. We expand the applicability of this approach for cardiovascular disease, in particular, for CT-geometry derived benchtop measurements of Fractional Flow Reserve, the reference standard for determination of significant individual coronary artery atherosclerotic lesions. MATERIALS AND METHODS: Coronary CT Angiography (CTA) images during a single heartbeat were acquired with a 320×0.5mm detector row scanner (Toshiba Aquilion ONE). These coronary CTA images were used to create 4 patient-specific cardiovascular models with various grades of stenosis: severe, <75% (n=1); moderate, 50-70% (n=1); and mild, <50% (n=2). DICOM volumetric images were segmented using a 3D workstation (Vitrea, Vital Images); the output was used to generate STL files (using AutoDesk Meshmixer), and further processed to create 3D printable geometries for flow experiments. Multi-material printed models (Stratasys Connex3) were connected to a programmable pulsatile pump, and the pressure was measured proximal and distal to the stenosis using pressure transducers. Compliance chambers were used before and after the model to modulate the pressure wave. A flow sensor was used to ensure flow rates within physiological reported values. RESULTS: 3D model based FFR measurements correlated well with stenosis severity. FFR measurements for each stenosis grade were: 0.8 severe, 0.7 moderate and 0.88 mild. CONCLUSIONS: 3D printed models of patient-specific coronary arteries allows for accurate benchtop diagnosis of FFR. This approach can be used as a future diagnostic tool or for testing CT image-based FFR methods.