Michael F. McNitt-Gray

Ionizing radiation in cardiac imaging: a science advisory from the American Heart Association Committee on Cardiac Imaging of the Council on Clinical Cardiology and Committee on Cardiovascular Imaging and Intervention of the Council on Cardiovascular Radiology and Intervention.

A preliminary report on medical radiation exposures to the US population based on publicly available sources of data estimated that the collective dose received from medical uses of radiation has increased by >700% between 1980 and 2006.1 Computed tomography (CT) has had an annual growth rate of >10% per year and accounted for ≈50% of the collective dose in 2006. Approximately 65% of the collective CT dose is from studies of chest, abdomen, and pelvis. In 2006, cardiac CT accounted for 1.5% of the collective CT dose; however, utilization of cardiac CT is expected to rise, with the potential to further increase exposure to the population.1 Nuclear medicine studies in the United States have increased by 5% annually to 20 million in 2006 and accounted for ≈25% of the 2006 collective medical radiation dose. Among nuclear medicine studies, cardiac imaging represented 57% of the number of studies and ≈85% of the radiation dose.1 A number of publications on imaging with CT, fluoroscopy, or radioisotopes have emphasized the risks that may be associated with exposure to ionizing radiation.2–4 To make informed decisions concerning the use of medical radiation in imaging procedures, the following are important components: (1) A working knowledge of the principles and uncertainties of the estimation of patient dose and biological risk; (2) a comparison of the risks of radiation exposure with the risks of activities in daily life; and (3) recognition of the potential risk of failing to make important diagnoses or treatment decisions if imaging is not performed because of safety concerns. There is no federal regulation of patient radiation dose, with the exception of mammography. Most federal and state regulations are aimed at equipment performance or the handling of nuclear materials. Therefore, appropriate utilization of the equipment or nuclear material in cardiac …

Method for segmenting chest CT image data using an anatomical model: preliminary results

Presents an automated, knowledge-based method for segmenting chest computed tomography (CT) datasets. Anatomical knowledge including expected volume, shape, relative position, and X-ray attenuation of organs provides feature constraints that guide the segmentation process. Knowledge is represented at a high level using an explicit anatomical model. The model is stored in a frame-based semantic network and anatomical variability is incorporated using fuzzy sets. A blackboard architecture permits the data representation and processing algorithms in the model domain to be independent of those in the image domain. Knowledge-constrained segmentation routines extract contiguous three-dimensional (3-D) sets of voxels, and their feature-space representations are posted on the blackboard. An inference engine uses fuzzy logic to match image to model objects based on the feature constraints. Strict separation of model and image domains allows for systematic extension of the knowledge base. In preliminary experiments, the method has been applied to a small number of thoracic CT datasets. Based on subjective visual assessment by experienced thoracic radiologists, basic anatomic structures such as the lungs, central tracheobronchial tree, chest wall, and mediastinum were successfully segmented. To demonstrate the extensibility of the system, knowledge was added to represent the more complex anatomy of lung lesions in contact with vessels or the chest wall. Visual inspection of these segmented lesions was also favorable. These preliminary results suggest that use of expert knowledge provides an increased level of automation compared with low-level segmentation techniques. Moreover, the knowledge-based approach may better discriminate between structures of similar attenuation and anatomic contiguity. Further validation is required.

CT dose index and patient dose: They are not the same thing

Estimates of individual patient risk, and epidemiologic studies assessing potential late effects, must use patient size–specific dose estimates—they cannot use only scanner output (volume CT dose index or dose-length product).

Patient-specific models for lung nodule detection and surveillance in CT images

The purpose of this work is to develop patient-specific models for automatically detecting lung nodules in computed tomography (CT) images. It is motivated by significant developments in CT scanner technology and the burden that lung cancer screening and surveillance imposes on radiologists. We propose a new method that uses a patients baseline image data to assist in the segmentation of subsequent images so that changes in size and/or shape of nodules can be measured automatically. The system uses a generic, a priori model to detect candidate nodules on the baseline scan of a previously unseen patient. A user then confirms or rejects nodule candidates to establish baseline results. For analysis of follow-up scans of that particular patient, a patient-specific model is derived from these baseline results. This model describes expected features (location, volume and shape) of previously segmented nodules so that the system can relocalize them automatically on follow-up. On the baseline scans of 17 subjects, a radiologist identified a total of 36 nodules, of which 31 (86%) were detected automatically by the system with an average of 11 false positives (FPs) per case. In follow-up scans 27 of the 31 nodules were still present and, using patient-specific models, 22 (81%) were correctly relocalized by the system. The system automatically detected 16 out of a possible 20 (80%) of new nodules on follow-up scans with ten FPs per case.

High-Resolution CT Scan Findings in Patients With Symptomatic Scleroderma-Related Interstitial Lung Disease

BACKGROUND Lung disease has become the leading cause of mortality and morbidity in scleroderma (SSc) patients. The frequency, nature, and progression of interstitial lung disease seen on high-resolution CT (HRCT) scans in patients with diffuse SSc (dcSSc) compared with those with limited SSc (lcSSc) has not been well characterized. METHODS Baseline HRCT scan images of 162 participants randomized into a National Institutes of Health-funded clinical trial were compared to clinical features, pulmonary function test measures, and BAL fluid cellularity. The extent and distribution of interstitial lung disease HRCT findings, including pure ground-glass opacity (pGGO), pulmonary fibrosis (PF), and honeycomb cysts (HCs), were recorded in the upper, middle, and lower lung zones on baseline and follow-up CT scan studies. RESULTS HRCT scan findings included 92.9% PF, 49.4% pGGO, and 37.2% HCs. There was a significantly higher incidence of HCs in the three zones in lcSSc patients compared to dcSSc patients (p = 0.034, p = 0.048, and p = 0.0007, respectively). The extent of PF seen on HRCT scans was significantly negatively correlated with FVC (r = - 0.22), diffusing capacity of the lung for carbon monoxide (r = - 0.44), and total lung capacity (r = - 0.36). A positive correlation was found between pGGO and the increased number of acute inflammatory cells found in BAL fluid (r = 0.28). In the placebo group, disease progression was assessed as 30% in the upper and middle lung zones, and 45% in the lower lung zones. No difference in the progression rate was seen between lcSSc and dcSSc patients. CONCLUSIONS PF and GGO were the most common HRCT scan findings in symptomatic SSc patients. HCs were seen in more than one third of cases, being more common in lcSSc vs dcSSc. There was no relationship between progression and baseline PF extent or lcSSc vs dcSSc. TRIAL REGISTRATION Clinicaltrials.gov Identifier: NCT00004563.

A Monte Carlo based method to estimate radiation dose from multidetector CT (MDCT): cylindrical and anthropomorphic phantoms

The purpose of this work was to extend the verification of Monte Carlo based methods for estimating radiation dose in computed tomography (CT) exams beyond a single CT scanner to a multidetector CT (MDCT) scanner, and from cylindrical CTDI phantom measurements to both cylindrical and physical anthropomorphic phantoms. Both cylindrical and physical anthropomorphic phantoms were scanned on an MDCT under the specified conditions. A pencil ionization chamber was used to record exposure for the cylindrical phantom, while MOSFET (metal oxide semiconductor field effect transistor) detectors were used to record exposure at the surface of the anthropomorphic phantom. Reference measurements were made in air at isocentre using the pencil ionization chamber under the specified conditions. Detailed Monte Carlo models were developed for the MDCT scanner to describe the x-ray source (spectra, bowtie filter, etc) and geometry factors (distance from focal spot to isocentre, source movement due to axial or helical scanning, etc). Models for the cylindrical (CTDI) phantoms were available from the previous work. For the anthropomorphic phantom, CT image data were used to create a detailed voxelized model of the phantoms geometry. Anthropomorphic phantom material compositions were provided by the manufacturer. A simulation of the physical scan was performed using the mathematical models of the scanner, phantom and specified scan parameters. Tallies were recorded at specific voxel locations corresponding to the MOSFET physical measurements. Simulations of air scans were performed to obtain normalization factors to convert results to absolute dose values. For the CTDI body (32 cm) phantom, measurements and simulation results agreed to within 3.5% across all conditions. For the anthropomorphic phantom, measured surface dose values from a contiguous axial scan showed significant variation and ranged from 8 mGy/100 mAs to 16 mGy/100 mAs. Results from helical scans of overlapping pitch (0.9375) and extended pitch (1.375) were also obtained. Comparisons between the MOSFET measurements and the absolute dose value derived from the Monte Carlo simulations demonstrate agreement in terms of absolute dose values as well as the spatially varying characteristics. This work demonstrates the ability to extend models from a single detector scanner using cylindrical phantoms to an MDCT scanner using both cylindrical and anthropomorphic phantoms. Future work will be extended to voxelized patient models of different sizes and to other MDCT scanners.

Application of the noise power spectrum in modern diagnostic MDCT: part I. Measurement of noise power spectra and noise equivalent quanta.

Dose reduction efforts in diagnostic CT have brought the tradeoff of dose versus image quality to the forefront. The need for meaningful characterization of image noise beyond that offered by pixel standard deviation is becoming increasingly important. This work aims to study the implementation of the noise power spectrum (NPS) and noise equivalent quanta (NEQ) on modern, multislice diagnostic CT scanners. The details of NPS and NEQ measurement are outlined and special attention is paid to issues unique to multislice CT. Aliasing, filter design and effects of acquisition geometry are investigated. While it was found that both metrics can be implemented in modern CT, it was discovered that NEQ cannot be aptly applied with certain non-traditional reconstruction filters or in helical mode. NPS and NEQ under a variety of conditions are examined. Extensions of NPS and NEQ to uses in protocol standardization are also discussed.

Coronary artery calcium: Alternate methods for accurate and reproducible quantitation

RATIONALE AND OBJECTIVES The aim of this study was to determine a more precise and accurate method of quantitating coronary artery calcium (CAC) detected with electron-beam computed tomography (CT) in patients with low CAC scores. MATERIALS AND METHODS Two 40-section, 3-mm-collimation, electrocardiographically gated electron-beam CT examinations of the heart were performed in each patient. Fifty patients with average scores between 2 and 100, as determined with the conventional scoring algorithm, were selected. The modified conventional scoring algorithm was compared with two techniques: calculated calcium volume and approximated calcium mass. RESULTS The percentage difference between scans ranged from 37.2% for the conventional scoring method to 28.2% and 28.4% for volume- and mass-based methods, respectively. Increasing lesion size thresholds does not improve quantitative precision and reduces accuracy in patients with small amounts of CAC. CONCLUSION Quantification methods based on calcification volume or mass decrease score variation compared with the conventional scoring method, and increased size threshold does not improve accuracy.

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 size1

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.

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.