Author + information
- Received January 3, 2017
- Revision received May 26, 2017
- Accepted June 5, 2017
- Published online January 1, 2018.
- Sigal Trattner, PhDa,
- Sandra Halliburton, PhDb,
- Carla M. Thompson, PhDc,
- Yanping Xu, PhDd,
- Anjali Chelliah, MDe,
- Sachin R. Jambawalikar, PhDf,
- Boyu Peng, MSg,
- M. Robert Peters, MDh,
- Jill E. Jacobs, MDi,
- Munir Ghesani, MDj,
- James J. Jang, MDk,
- Hussein Al-Khalidi, PhDl and
- Andrew J. Einstein, MD, PhDm,∗ ()
- aDepartment of Medicine, Division of Cardiology, Columbia University Medical Center, and New York-Presbyterian Hospital, New York, New York
- bImaging Institute, Division of Radiology, Cleveland Clinic, Cleveland, Ohio, and Lerner Research Institute, Department of Biomedical Engineering, Cleveland Clinic, Cleveland, Ohio, and Department of Chemical and Biomedical Engineering, Cleveland State University, Cleveland, Ohio, and Philips Healthcare, Cleveland, Ohio
- cImaging Institute, Division of Radiology, Cleveland Clinic, and Lerner Research Institute, Department of Biomedical Engineering, Cleveland Clinic, and Department of Chemical and Biomedical Engineering, Cleveland State University, Cleveland, Ohio
- dRadiological Research Accelerator Facility, Center for Radiological Research, Columbia University Medical Center, Irvington, New York
- eDepartment of Pediatrics, Division of Pediatric Cardiology, New York-Presbyterian Morgan Stanley Children's Hospital, and Columbia University Medical Center, New York, New York
- fDepartment of Radiology, Columbia University Medical Center, and New York-Presbyterian Hospital, New York, New York
- gDepartment of Radiology, Columbia University Medical Center, and New York-Presbyterian Hospital, New York, New York
- hAdvanced Cardiovascular Imaging, New York, New York
- iSection of Cardiac Imaging, Department of Radiology, New York University School of Medicine, and New York University Langone Medical Center, New York, New York
- jDivision of Nuclear Medicine, Department of Radiology, New York University, and New York University Langone Medical Center, New York, New York
- kDivision of Cardiology, Kaiser Permanente San Jose Medical Center, San Jose, California
- lDuke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina
- mDepartment of Medicine, Cardiology Division, and Department of Radiology, Columbia University Medical Center, and New York Presbyterian Hospital, New York, New York
- ↵∗Address for correspondence:
Dr. Andrew J. Einstein, Columbia University Medical Center, Department of Medicine, Division of Cardiology, 622 West 168th Street, PH 10-203B, New York, New York 10032.
Objectives This study sought to determine updated conversion factors (k-factors) that would enable accurate estimation of radiation effective dose (ED) for coronary computed tomography angiography (CTA) and calcium scoring performed on 12 contemporary scanner models and current clinical cardiac protocols and to compare these methods to the standard chest k-factor of 0.014 mSv·mGy−1cm−1.
Background Accurate estimation of ED from cardiac CT scans is essential to meaningfully compare the benefits and risks of different cardiac imaging strategies and optimize test and protocol selection. Presently, ED from cardiac CT is generally estimated by multiplying a scanner-reported parameter, the dose-length product, by a k-factor which was determined for noncardiac chest CT, using single-slice scanners and a superseded definition of ED.
Methods Metal-oxide-semiconductor field-effect transistor radiation detectors were positioned in organs of anthropomorphic phantoms, which were scanned using all cardiac protocols, 120 clinical protocols in total, on 12 CT scanners representing the spectrum of scanners from 5 manufacturers (GE, Hitachi, Philips, Siemens, Toshiba). Organ doses were determined for each protocol, and ED was calculated as defined in International Commission on Radiological Protection Publication 103. Effective doses and scanner-reported dose-length products were used to determine k-factors for each scanner model and protocol.
Results k-Factors averaged 0.026 mSv·mGy−1cm−1 (95% confidence interval: 0.0258 to 0.0266) and ranged between 0.020 and 0.035 mSv·mGy−1cm−1. The standard chest k-factor underestimates ED by an average of 46%, ranging from 30% to 60%, depending on scanner, mode, and tube potential. Factors were higher for prospective axial versus retrospective helical scan modes, calcium scoring versus coronary CTA, and higher (100 to 120 kV) versus lower (80 kV) tube potential and varied among scanner models (range of average k-factors: 0.0229 to 0.0277 mSv·mGy−1cm−1).
Conclusions Cardiac k-factors for all scanners and protocols are considerably higher than the k-factor currently used to estimate ED of cardiac CT studies, suggesting that radiation doses from cardiac CT have been significantly and systematically underestimated. Using cardiac-specific factors can more accurately inform the benefit-risk calculus of cardiac-imaging strategies.
Cardiac computed tomography (CT) has experienced tremendous advances in the past decade. Growing evidence supports the role of coronary artery calcium scoring for risk stratification, and some guidelines now recommend it as a reasonable test for asymptomatic adults at intermediate risk (1). Coronary computed tomography angiography (CTA) has demonstrated high accuracy for diagnosing obstructive coronary artery disease (2), the ability to improve prognostication (3), and in some settings, capability to more rapidly and cost-effectively diagnose chest pain in patients (4). In many clinical contexts, coronary CTA now stands as an option that can be selected to guide optimal patient management and incorporated into clinical pathways (5,6).
Each cardiac imaging modality has strengths and weaknesses, and optimizing management requires a weighting of these features for each option in the context of the patient and clinical question. One particular concern for coronary CTA is its associated radiation burden. Although initial studies found high radiation dose and risk (7), numerous technical advances such as prospectively triggered axial scan modes, lower tube potentials, and iterative image reconstruction now enable, in the best-case scenario, performing coronary CTA with extremely low radiation burden, comparable to that of several chest radiographs (8). However, such low coronary CTA doses require a confluence of several factors: availability of these technical advances which are not all implemented on entry level scanners, operator expertise, favorable patient heart rate and rhythm and habitus, and willingness to tolerate some image noise and limitation in the number of phases of the cardiac cycle available for interpretation. Thus, although some patients will receive extremely low doses, many will still receive considerably higher doses. Indeed, contemporary coronary CTA practice is characterized by a wide range of radiation doses among laboratories and among patients (9), and thus the benefit-risk calculus of coronary CTA and its comparison with other modalities may vary depending on the particular radiation dose. In particular, when taking care of patients with chest pain, the physician’s choice between coronary CTA and nuclear myocardial perfusion imaging may depend in part on radiation burden. Such comparison is predicated on accurate radiation dosimetry for both examinations.
The single parameter most commonly used to compare ionizing radiation burdens among different imaging modalities, scanners, and protocols is the effective dose (ED), in units of millisieverts (mSv). Effective dose characterizes whole-body exposure from a nonuniform radiation exposure as a weighted average of organ absorbed doses. It is presently defined in accordance with a formulation specified by the International Commission on Radiological Protection (ICRP) in its Publication 103 (10) as the sum over all specified organs of doubly weighted organ-absorbed doses, where weights reflect both the relative sensitivity of each organ to radiation and the radiation source. Effective dose is not without limitations (11,12); for example, the organ weights are averages for all ages and both sexes, thus precluding a sex-specific ED; and ED is not patient-size dependent. Accordingly, ED is not designed for patient-specific radiation risk assessment. Nevertheless it remains the only metric that can be easily used to compare whole-body radiation exposure across modalities and protocols. This has led to its great popularity in clinical publications and practice. ICRP Publication 103 (10) updated the radiation weighting factors for each organ based on a comprehensive, updated review of radioepidemiological and radiobiological evidence and refined methodology in comparison with the previous specification of ED in ICRP Publication 60 (13).
By far, the simplest and most commonly used method to estimate ED for CT scans is by multiplying another radiation parameter, the dose-length product (DLP), by a conversion factor, often referred to as the k-factor. Dose-length product, which is limited to CT, is reported on the scanner console after each CT scan and reflects both the intensity of the radiation exposure (in milligray) and the craniocaudal length irradiated (in centimeters). The k-factor that is conventionally used for cardiac scans, 0.014 mSv·mGy−1·cm−1, was introduced in European Commission guidelines for chest CT scans (14) and later adopted by the American Association of Physicists in Medicine (15). Using this chest k-factor to estimate ED from cardiac CT has limitations that potentially compromise the accuracy of ED estimates. First, the chest k-factor was never designed for cardiac studies but rather for thoracic CT; second, it is based on the older, now superseded, ICRP 60 definition of ED; and third, it was determined using three single-slice scanners, which technologically, are markedly different from the CT scanners currently in use for cardiac CT. Moreover, the European Commission guidelines document (14) had in fact provided 2 different chest k-factors: 0.019 mSv·mGy−1·cm−1 (in its Appendix A) and 0.014 mSv·mGy−1·cm−1 (in its Appendix C).
Thus, updated dosimetric methodology is essential to ensure accurate estimation of ED from cardiac CT. Heretofore, there has been no systematic attempt to determine k-factors for the diversity of scanner models and protocols used in cardiac CT practice, and the k-factors in published studies covering a limited combination of scanners and modes (Table 1) have not been widely adopted. In the present study, we systematically determined k-factors for all contemporary cardiac coronary CTA scanner designs and protocols to provide a single source of data that could be used to more accurately estimate ED of cardiac CT. Our approach was to estimate EDs from measurements performed using solid-state metal-oxide–semiconductor field-effect transistor (MOSFET) dosimeters placed in an anthropomorphic phantom and to determine k-factors relating these EDs to scanner-reported DLPs.
A whole-body adult anthropomorphic dosimetry verification phantom (Figure 1) was used for all experiments (ATOM 701, CIRS, Norfolk, Virginia). The phantom weighs 73 kg and has thoracic dimensions of 23 × 32 cm without breasts. It is constructed from tissue-equivalent resins and polymers that represent the body’s anatomy and radiation attenuation characteristics at diagnostic photon energies, and thus, it both physically and radiographically simulates an adult patient. The phantom is composed of a stack of 25-mm-thick contiguous transverse sections, each of which contains several 5-mm-diameter holes through which detectors can be placed for organ dose measurements. In these holes, tissue-equivalent MOSFET holders were used to place the MOSFET detectors. Holes in which MOSFETs were not placed were filled with tissue-equivalent plugs. For female scans, medium-sized tissue-equivalent breast phantoms were constructed from actual CT data of a female lying in the supine position and affixed to the body phantom. Further methodologic details for all sections are provided in the Online Appendix.
MOSFET dosimeters and organ dose determination
Organ dosimetry was performed using a mobile MOSFET dose verification system (TN-RD-70W, Best Medical, Ottawa, Ontario, Canada), associated with high-sensitivity MOSFETs (TN-1002RD-H, Best Medical). Voltage (in millivolt [mV]) readings were translated to dose (mGy) by calibration of the MOSFETs, using an ion chamber (10X6-3CT, Radcal, Monrovia, California) with a control unit (Accu-Dose 2186, Radcal), and a standard 32-cm-diameter cylinder poly (methyl methacrylate) phantom (West Physics Consulting, Atlanta, Georgia), according to the calibration scheme of Trattner et al. (16). Separate calibration factors were determined for each x-ray tube potential used for cardiac scan modes due to MOSFET sensitivity to energy spectra.
MOSFETs were positioned within the phantom in all 27 internal organs contributing to ED determination (10). The MOSFET voltage reading in a given tissue was translated to dose in that tissue bywhere the calibration factor, CF, is in units of mGy/mV, and is a scaling factor which converts dose-in-air to dose-in-tissue at the effective energy of x-rays used and is defined as:that is, the ratio of the mass energy-absorption coefficient of the specific tissue to that of air (15). Mass energy absorption coefficients were obtained from data tabulated by the National Institute of Standards and Technology at the appropriate effective energy (17), which was determined based on information obtained from the CT manufacturers (17) or, if not available, simulations using the Monte Carlo radiation transport program MCNP/MCNPX (Los Alamos National Laboratory, Los Alamos, New Mexico) to obtain effective energies. These simulations were validated with known values of effective energy.
To characterize doses to the 27 organs, we used 44 and 41 MOSFETs for female and male phantoms, respectively. Doses in larger or highly radiosensitive organs such as lungs and female breasts were determined based on measurements in multiple MOSFETs (Table 2⇑⇓), and an average was used to estimate the organ-absorbed dose. For lung, a weighted average was taken in which the weight for each MOSFET reading was determined by the percentage of the lung’s volume surrounding the relevant MOSFET. Bone surface and bone marrow doses were measured in 8 different MOSFET locations, and a weighted average was determined according to their mass as specified by Eckerman et al. (18).
Twelve contemporary CT scanner models representing all 5 major CT manufacturers were studied. These scanner models were chosen based on their use in the PROMISE (PROspective Multicenter Imaging Study for Evaluation of Chest Pain) trial, a 193-site, pragmatic comparative effectiveness trial which randomized outpatients with chest pain to initial testing with either coronary CTA or functional testing (5), performed in local laboratories. Therefore, the CT scanner models used reflect those used in current clinical practice. All models have either single or dual x-ray sources, and between 32 and 320 detector rows available for cardiac imaging. We performed medical physics experiments in physical anthropomorphic phantoms using one scanner of each model. Experiments were performed on multiple scanners at New York-Presbyterian Hospital/Columbia University Medical Center and at the Cleveland Clinic, Cleveland, Ohio, and on single scanners at several additional facilities (Table 3).
A variety of protocols are used for cardiac imaging in contemporary scanners, with the particular protocol options differing among scanners. Components of a protocol include the scan mode, tube potential, and other scan parameters. Almost all scanners have a retrospectively gated low-pitch helical mode, generally with an option for echocardiogram (ECG)-controlled tube current modulation which lowers the x-ray tube current to ≤20% of its maximum, except during a designated portion of the cardiac cycle. Most newer and all higher-end scanners have in addition at least one prospectively triggered scan mode which turns the x-ray beam off except during a designated portion of the cardiac cycle, most commonly diastasis. Additional “padding” of x-ray exposure time may be performed enabling reconstruction of additional phases of the cardiac cycle. Prospectively ECG-triggered scanning is most commonly axial but may be helical, sometimes with a high pitch, or a volume scan with no movement of the patient couch.
Typical protocols for each cardiac mode were determined for each scanner studied based on discussion with physicists and applications specialists from the vendor, as well as experienced radiologists, cardiologists, and technologists at each collaborating site. Since k-factors may vary based on photon energy (19), scans were generally performed for each scanner and scan mode at tube potentials of 80, 100, and 120 kVp, unless a tube potential was not available on the scanner or the scan mode was not typically used at a particular tube potential. In addition, for a few scanners, scans for determining k-factors were performed using less commonly used tube potentials of 70, 135, and 140 kVp. In some cases, to optimize MOSFET statistics, scans were performed at a tube current higher than that which would be used in clinical practice. The choice of tube current does not affect k-factors because both DLP and MOSFET voltages scale linearly with tube current. In all other respects, scans were performed with parameters mimicking those typically used clinically for that protocol. In addition to coronary CTA protocols, coronary artery calcium scoring scans were performed for most scanners. A simulator was used to generate the ECG signal (“chicken heart”) for all studies. Most scans were performed using a signal simulating normal sinus rhythm at 60 beats/min; in a few cases, where a protocol is intended for patients with higher heart rates, the simulated heart rate was increased to 80 beats/min.
Dosimetry measurements were performed separately for the female and male phantoms. For each protocol, MOSFET readings were recorded for multiple scans, equally divided between male and female phantoms, with the phantom in the identical position for each repetition. The number of scans performed was determined according to the approach described by Trattner et al. (20) to ensure that the ED estimate was within ±10% of its true value with >90% confidence. The number of scans ranged from 4 to 10; for most protocols (84 of 120; 70%), 10 scans were performed. Scan numbers as well as additional details for each protocol are found in Online Table 1.
ED and conversion coefficient calculation
We determined ED for each combination of scanner, scan mode, and voltage according to ICRP Publication 103 definition (10) as:where are the average absorbed doses determined for each organ or tissue, T, for male and female phantoms, respectively. These averages were obtained over the repeated scans for each protocol. We also determined ED according to the superseded ICRP Publication 60 definition (13), which included fewer organs and some differences in tissue weightings.
Actual DLP values, as reported on the scanner console, were recorded after each scan performed. For each combination of scanner and protocol, all DLPs of repeated scans for both female and male were averaged. Each k-factor was determined as the ratio of the ED to the averaged DLP.
Cardiac k-factors of 12 scanners and 120 cardiac protocols (each protocol incorporating a scan mode, tube potential, and other parameter selections), calculated using the up-to-date (10) definition of ED, are presented in Table 4. A detailed description of each protocol is available in Online Table 1, as are additional protocols and k-factors at 70, 135, and 140 kVp tube potential. k-Factor mean and median were 0.026 mSv·mGy−1cm−1, ranging between 0.020 and 0.035 mSv·mGy−1cm−1 (95% confidence interval: 0.0258 to 0.0266 mSv·mGy−1cm−1; coefficient of variation: 8.9%). Thus, using the European chest k-factor guideline of 0.014 mSv·mGy−1cm−1 underestimates ED by 46%, in comparison with using an average cardiac k-factor, and by 30 to 60%, in comparison to using a scanner- and protocol-specific cardiac k-factor.
The average k-factor for prospectively ECG-triggered axial coronary CTA protocols was 0.0272 mSv·mGy−1cm−1, slightly higher than the average k-factor of retrospectively ECG-gated helical coronary CTA protocols of 0.0252 mSv·mGy−1cm−1. Calcium scoring scans had an average k-factor of 0.0289 mSv·mGy−1cm−1, higher than that for coronary CTAs which averaged 0.0260 mSv·mGy−1cm−1. Coronary CTA 80 kVp protocols averaged 0.0250 mSv·mGy−1cm−1, lower than 100 to 120 kVp protocols, which averaged 0.0264 mSv·mGy−1cm−1. Average k-factors for scanner models varied between 0.0229 and 0.0277 mSv·mGy−1cm−1, a range of 20%. As seen in Online Table 1, 72% of the k-factors determined had 5% precision at a 95% confidence level, whereas 98% had 10% precision at this level. At a 90% confidence level, 80% of k-factors had 5% precision, and all had 10% precision.
k-Factors based on the older ICRP 60 definition of ED (13) are shown in Online Table 2, with an average k-factor of 0.021 mSv·mGy−1cm−1. Thus, even when the same superseded definition of ED is used, calculation of ED with the chest k-factor of 0.014 mSv·mGy−1cm−1 underestimates ED by 33% in comparison to using the average cardiac k-factor.
The proposed cardiac k-factors determined for 12 contemporary scanners and more than 120 contemporary cardiac CT protocols using the current definition of ED are all greater than the chest k-factor that is widely used to estimate ED from cardiac scans and is incorporated into professional society guidelines (14,15). Use of this chest k-factor to estimate ED results in an underestimation of ED by 46% compared with the average cardiac k-factor we determined and by 30 to 60%, depending on the specific scanner and protocol.
Our findings are consistent with recent findings from several other studies, each investigating a limited number of protocols (Table 1). All studies, including one (21) led by a member of the European Commission group which introduced the chest k-factor of 0.014 mSv·mGy−1·cm−1, found considerably higher k-factors, also varying among scanners and protocols and ranging from 0.020 to 0.043 mSv·mGy−1·cm−1. Given our findings, together with this supportive data, we believe that the use of the European Commission chest k-factor to estimate ED in cardiac CT, a practice never endorsed by the European Commission or American Association of Physicists in Medicine, should be reconsidered. For a better estimation of ED, we propose that, ideally, a scanner- and protocol-specific factor be used, and if one is not easily available, then we recommend use of our mean (as well as median) k-factor of 0.026 mSv·mGy−1·cm−1.
Several factors contribute to this difference between cardiac and chest k-factors. One factor is a fundamental distinction between cardiac scans, which typically involve approximately 12 to 14 cm of craniocaudal coverage, and thoracic scans covering the entire chest, which spans approximately 27 cm craniocaudally. Although all or most of the breast tissue is typically irradiated in both cardiac and chest CT scans, chest scans extend both cranially and caudally to include areas without breast tissue, and thus, there is more breast irradiation per length scanned in cardiac CT. Because the breasts are highly radiosensitive organs, one should expect a higher k-factor for a cardiac scan (22,23). Additionally, most vendors of CT scanners used in this study report using different “bow tie” filters for cardiac and chest scans, which is another factor which contributes to the difference between cardiac and chest k-factors.
Another contributor to the difference between our cardiac k-factors and the European chest scan k-factor is the definition of ED used. The older definition resulted, for cardiac scans, in a k-factor that is 21% lower than that in the current ED definition. The primary driver of this difference is the updated tissue weighting factors determining each organ’s contribution to the whole-body ED, which are incorporated in ICRP 103 ED definition to better reflect the current state of radiation epidemiological data. In particular, the tissue weighting factor for the breast increased from 0.05 to 0.12. Because the breast is directly irradiated by the x-ray beam in cardiac scans, it has a high organ radiation dose and, together with lung dose, is the main organ contributing to the ED from cardiac CT. Additionally, in the ICRP 103 formulation of ED, the heart is included among the “remainder organs,” whereas previously the heart had not been assigned a tissue weighting factor and thus did not contribute to ED. The update in the tissue weighting factors, which is not reflected in the European Commission chest k-factor, is another source for ED underestimation using this factor.
An additional limitation of the European guidelines chest conversion factor of 0.014 mSv·mGy−1·cm−1 is that it was determined based on modeling 3 now-antiquated single-slice scanners, none of which were capable of performing coronary CTA (Siemens DRH [Siemens, Munich, Germany], GE 9800 [GE, Hannover, Maryland], and Philips LX [Philips, Amsterdam, the Netherlands]). The use of these old scanners for contemporary cardiac CT dosimetry should no longer be considered applicable. Moreover, as noted above, the very same European guidelines document, in another appendix which considered some more recent scanners (up to 16-slice), already suggested a higher (noncardiac) chest conversion factor of 0.019 mSv·mGy−1·cm−1.
There are several experimental and computational components to the determination of a k-factor, each with associated uncertainty. These components include the scanner-reported DLP, effective energy calculation, energy dependent absorption coefficients, and MOSFET measurement and calibration (16). However, we performed repeated measurements to ensure that ED determination had high precision with high confidence, using the scheme of Trattner et al. (20). Additionally, we performed most scans with a simulated heart rate of 60 beats/min without heart rate variability. Fluctuations in heart rate or higher rates that cannot be controlled have the potential to alter data acquisition and impact the k-factor. However, in a recent MOSFET study in pediatric cardiac CT, Trattner et al. (23) found no impact of heart rate on k-factor. The use of up to 44 MOSFETs simultaneously raises a question of a potential impact of the wires on the measured dose levels and hence on the k-factors. However, we have tested such impact using a pediatric phantom with 50 MOSFETs which were more densely placed than in the adult phantom here and found that individual k-factors typically varied by only ±0.001 mSv·mGy−1·cm−1 depending on whether or not all 50 MOSFETs were placed simultaneously (23). The effective energy values used to determine the f-factors above refer to the energy just upon entrance to the phantom’s body and not at the exact location of the MOSFET. However, experiments we performed using various protocols in one scanner demonstrated the difference in simulated effective energy in the exact MOSFET location versus simulated effective energy upon entrance to the phantom body was approximately 1%, a sufficiently low error to justify the use of body-entrance effective energy values. Finally, ED is more formally defined computationally, and our approach was largely experimental. Our motivation was to avoid the need to make assumptions regarding proprietary aspects of scanner design and protocols, which would have been required for Monte Carlo simulation. Even so, for a single scanner, we have compared MOSFET to Monte Carlo estimation of effective dose and found outstanding agreement (24).
We determined cardiac-specific conversion factors for contemporary scanners and routinely used clinical protocols to enable a more accurate estimation of ED, given a scanner-reported DLP, as compared to estimation utilizing the commonly used factor of 0.014 mSv·mGy−1·cm−1. Although mentioned in current guidelines, this latter factor was determined for chest rather than cardiac CT, based on now-obsolete single-slice scanners and using a now-outdated definition of ED. The cardiac-specific factors we determined are, for all 12 scanners and 120 scan protocols used, considerably higher than the chest conversion factor, suggesting that radiation doses from cardiac CT have been significantly and systematically underestimated. We suggest that, ideally, a scanner- and protocol-specific conversion factor should be used for estimating ED from cardiac CT, or if scanning information is unavailable, then one should use our mean and median conversion factor of 0.026 mSv·mGy−1·cm−1. The use of cardiac-specific factors is critical to ensure more accurate dosimetry to inform the benefit-risk calculus of cardiac imaging strategies, and optimize radiation safety of patients.
COMPETENCY IN MEDICAL KNOWLEDGE: New methodology introduced here provides more accurate tools to estimate radiation effective dose from cardiac CT scans.
COMPETENCY IN PATIENT CARE AND PROCEDURAL SKILLS: Updated methodology for determining radiation dose from cardiac CT should be used to enhance the benefit-risk calculus of cardiac imaging strategies and optimize test and protocol selection.
TRANSLATIONAL OUTLOOK: The use of a more accurate methodology for estimating radiation dose from CT may affect the balance of benefits and risks of cardiac imaging strategies. Additional studies are needed, incorporating this methodology as well as updated dosimetry methodology for other modalities, to reassess the comparative effectiveness of strategies for managing patients with chest pain and other clinical scenarios requiring cardiovascular evaluation.
The authors thank Richard Maldonado, Sheldon Herbert, Ted Pozniakoff, Ketan Bhatia, Amsale Robi, Tony Zapata, Carlos DeOleo, and Jose Casado (New York-Presbyterian Hospital); Michael Manning (Cleveland Clinic), Donna McKenzie (SUNY Downstate Medical Center); Carol Murphy (NYU Langone Medical Center); and Steven Wolff (Carnegie Hill Radiology) for administrative and technical assistance in scanning. We also thank Grant Stevens (GE), Donald Boshela (Hitachi), Peter Prinsen and Tom Morton (Philips), Tom O’Donnell (Siemens), and Di Zhang and Erin Angel (Toshiba) for technical information regarding scanners, Abdelbasset Hallil (Best Medical) for information regarding and technical support for MOSFETs, and Pamela Douglas (Duke), Udo Hoffmann (MGH), and Brian Ghoshhajra (MGH) for helpful comments on the manuscript.
This study was supported by National Institutes of Health/National Heart, Lung, and Blood Institute grant R01 HL109711. Dr. Einstein is supported by Herbert Irving Associate Professorship and Victoria and Esther Aboodi Cardiology Researcher. Dr. Halliburton has received institutional research grants to Cleveland Clinic from Philips Healthcare and Siemens Healthcare; and is currently an employee of Philips Healthcare (her role in data collection and analysis was all performed as an employee of Cleveland Clinic, prior to her employment by Philips Healthcare). Dr. Peters has received institutional research grants from and served on the speakers’ bureau of Toshiba America Medical Systems. Dr. Einstein has received institutional research grants from GE Healthcare, Philips Healthcare, and Toshiba America Medical Systems. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. Dr. Thompson’s current affiliation is Vanderbilt University, Nashville, Tennessee. Dr. Xu’s current affiliation is Department of Physics, East Carolina University, Greenville, North Carolina.
- Abbreviations and Acronyms
- computed tomography
- computed tomography angiography
- dose-length product
- effective dose
- kilovolt peak
- metal-oxide semiconductor field-effect transistor
- Received January 3, 2017.
- Revision received May 26, 2017.
- Accepted June 5, 2017.
- 2018 The Authors
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