AAPM Medical Physics Practice Guideline 1.b: CT protocol management and review practice guideline.

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education and professional practice of medical physics. The AAPM has more than 8000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiology requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guidelines and technical standards by those entities not providing these services is not authorized. The following terms are used in the AAPM practice guidelines: (a) Must and Must Not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. (b) Should and Should Not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances.

Correction to: Toward clinically usable CAD for lung cancer screening with computed tomography.

The original version of this article, published on 24 July 2014, unfortunately contained a mistake. In section "Discussion," a sentence was worded incorrectly.

Toward clinically usable CAD for lung cancer screening with computed tomography.

OBJECTIVES: The purpose of this study was to define clinically appropriate, computer-aided lung nodule detection (CAD) requirements and protocols based on recent screening trials. In the following paper, we describe a CAD evaluation methodology based on a publically available, annotated computed tomography (CT) image data set, and demonstrate the evaluation of a new CAD system with the functionality and performance required for adoption in clinical practice. METHODS: A new automated lung nodule detection and measurement system was developed that incorporates intensity thresholding, a Euclidean Distance Transformation, and segmentation based on watersheds. System performance was evaluated against the Lung Imaging Database Consortium (LIDC) CT reference data set. RESULTS: The test set comprised thin-section CT scans from 108 LIDC subjects. The median (±IQR) sensitivity per subject was 100 (±37.5) for nodules ≥ 4 mm and 100 (±8.33) for nodules ≥ 8 mm. The corresponding false positive rates were 0 (±2.0) and 0 (±1.0), respectively. The concordance correlation coefficient between the CAD nodule diameter and the LIDC reference was 0.91, and for volume it was 0.90. CONCLUSIONS: The new CAD system shows high nodule sensitivity with a low false positive rate. Automated volume measurements have strong agreement with the reference standard. Thus, it provides comprehensive, clinically-usable lung nodule detection and assessment functionality. KEY POINTS: • CAD requirements can be based on lung cancer screening trial results. • CAD systems can be evaluated using publically available annotated CT image databases. • A new CAD system was developed with a low false positive rate. • The CAD system has reliable measurement tools needed for clinical use.

Success rates for computed tomography-guided musculoskeletal biopsies performed using a low-dose technique.

OBJECTIVE: To evaluate the success rate of a low-dose (50% mAs reduction) computed tomography (CT) biopsy technique. This protocol was adopted based on other successful reduced-CT radiation dose protocols in our department, which were implemented in conjunction with quality improvement projects. MATERIALS AND METHODS: The technique included a scout view and initial localizing scan with standard dose. Additional scans obtained for further guidance or needle adjustment were acquired by reducing the tube current-time product (mAs) by 50%. The radiology billing data were searched for CT-guided musculoskeletal procedures performed over a period of 8 months following the initial implementation of the protocol. These were reviewed for the type of procedure and compliance with the implemented protocol. The compliant CT-guided biopsy cases were then retrospectively reviewed for patient demographics, tumor pathology, and lesion size. Pathology results were compared to the ultimate diagnoses and were categorized as diagnostic, accurate, or successful. RESULTS: Of 92 CT-guided procedures performed during this period, two were excluded as they were not biopsies (one joint injection and one drainage), 19 were excluded due to non-compliance (operators neglected to follow the protocol), and four were excluded due to lack of available follow-up in our electronic medical records. A total of 67 compliant biopsies were performed in 63 patients (two had two biopsies, and one had three biopsies). There were 32 males and 31 females with an average age of 50 (range, 15-84 years). Of the 67 biopsies, five were non-diagnostic and inaccurate and thus unsuccessful (7%); five were diagnostic but inaccurate and thus unsuccessful (7%); 57 were diagnostic and accurate thus successful (85%). These results were comparable with results published in the radiology literature. CONCLUSIONS: The success rate of CT-guided biopsies using a low-dose protocol is comparable to published rates for conventional dose biopsies. The implemented low-dose protocol did not change the success rate of CT-guided musculoskeletal biopsies.

Assessing variability in non-contrast CT for the evaluation of stroke: The effect of CT image reconstruction conditions on AI-based CAD measurements of ASPECTS value and hypodense volume.

Purpose: To rule out hemorrhage, non-contrast CT (NCCT) scans are used for early evaluation of patients with suspected stroke. Recently, artificial intelligence tools have been developed to assist with determining eligibility for reperfusion therapies by automating measurement of the Alberta Stroke Program Early CT Score (ASPECTS), a 10-point scale with > 7 or ≤ 7 being a threshold for change in functional outcome prediction and higher chance of symptomatic hemorrhage, and hypodense volume. The purpose of this work was to investigate the effects of CT reconstruction kernel and slice thickness on ASPECTS and hypodense volume. Methods: The NCCT series image data of 87 patients imaged with a CT stroke protocol at our institution were reconstructed with 3 kernels (H10s-smooth, H40s-medium, H70h-sharp) and 2 slice thicknesses (1.5mm and 5mm) to create a reference condition (H40s/5mm) and 5 non-reference conditions. Each reconstruction for each patient was analyzed with the Brainomix e-Stroke software (Brainomix, Oxford, England) which yields an ASPECTS value and measure of total hypodense volume (mL). Results: An ASPECTS value was returned for 74 of 87 cases in the reference condition (13 failures). ASPECTS in non-reference conditions changed from that measured in the reference condition for 59 cases, 7 of which changed above or below the clinical threshold of 7 for 3 non-reference conditions. ANOVA tests were performed to compare the differences in protocols, Dunnett's post-hoc tests were performed after ANOVA, and a significance level of p < 0.05 was defined. There was no significant effect of kernel (p = 0.91), a significant effect of slice thickness (p < 0.01) and no significant interaction between these factors (p = 0.91). Post-hoc tests indicated no significant difference between ASPECTS estimated in the reference and any non-reference conditions. There was a significant effect of kernel (p < 0.01) and slice thickness (p < 0.01) on hypodense volume, however there was no significant interaction between these factors (p = 0.79). Post-hoc tests indicated significantly different hypodense volume measurements for H10s/1.5mm (p = 0.03), H40s/1.5mm (p < 0.01), H70h/5mm (p < 0.01). No significant difference was found in hypodense volume measured in the H10s/5mm condition (p = 0.96). Conclusion: Automated ASPECTS and hypodense volume measurements can be significantly impacted by reconstruction kernel and slice thickness.

Quantitative Computed Tomography Lung COVID Scores with Laboratory Markers: Utilization to Predict Rapid Progression and Monitor Longitudinal Changes in Patients with Coronavirus 2019 (COVID-19) Pneumonia.

Coronavirus disease 2019 (COVID-19), is an ongoing issue in certain populations, presenting rapidly worsening pneumonia and persistent symptoms. This study aimed to test the predictability of rapid progression using radiographic scores and laboratory markers and present longitudinal changes. This retrospective study included 218 COVID-19 pneumonia patients admitted at the Chungnam National University Hospital. Rapid progression was defined as respiratory failure requiring mechanical ventilation within one week of hospitalization. Quantitative COVID (QCOVID) scores were derived from high-resolution computed tomography (CT) analyses: (1) ground glass opacity (QGGO), (2) mixed diseases (QMD), and (3) consolidation (QCON), and the sum, quantitative total lung diseases (QTLD). Laboratory data, including inflammatory markers, were obtained from electronic medical records. Rapid progression was observed in 9.6% of patients. All QCOVID scores predicted rapid progression, with QMD showing the best predictability (AUC = 0.813). In multivariate analyses, the QMD score and interleukin(IL)-6 level were important predictors for rapid progression (AUC = 0.864). With >2 months follow-up CT, remained lung lesions were observed in 21 subjects, even after several weeks of negative reverse transcription polymerase chain reaction test. AI-driven quantitative CT scores in conjugation with laboratory markers can be useful in predicting the rapid progression and monitoring of COVID-19.

Multi-scale, domain knowledge-guided attention + random forest: a two-stage deep learning-based multi-scale guided attention models to diagnose idiopathic pulmonary fibrosis from computed tomography images.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, irreversible, and usually fatal lung disease of unknown reasons, generally affecting the elderly population. Early diagnosis of IPF is crucial for triaging patients' treatment planning into anti-fibrotic treatment or treatments for other causes of pulmonary fibrosis. However, current IPF diagnosis workflow is complicated and time-consuming, which involves collaborative efforts from radiologists, pathologists, and clinicians and it is largely subject to inter-observer variability. PURPOSE: The purpose of this work is to develop a deep learning-based automated system that can diagnose subjects with IPF among subjects with interstitial lung disease (ILD) using an axial chest computed tomography (CT) scan. This work can potentially enable timely diagnosis decisions and reduce inter-observer variability. METHODS: Our dataset contains CT scans from 349 IPF patients and 529 non-IPF ILD patients. We used 80% of the dataset for training and validation purposes and 20% as the holdout test set. We proposed a two-stage model: at stage one, we built a multi-scale, domain knowledge-guided attention model (MSGA) that encouraged the model to focus on specific areas of interest to enhance model explainability, including both high- and medium-resolution attentions; at stage two, we collected the output from MSGA and constructed a random forest (RF) classifier for patient-level diagnosis, to further boost model accuracy. RF classifier is utilized as a final decision stage since it is interpretable, computationally fast, and can handle correlated variables. Model utility was examined by (1) accuracy, represented by the area under the receiver operating characteristic curve (AUC) with standard deviation (SD), and (2) explainability, illustrated by the visual examination of the estimated attention maps which showed the important areas for model diagnostics. RESULTS: During the training and validation stage, we observe that when we provide no guidance from domain knowledge, the IPF diagnosis model reaches acceptable performance (AUC±SD = 0.93±0.07), but lacks explainability; when including only guided high- or medium-resolution attention, the learned attention maps are not satisfactory; when including both high- and medium-resolution attention, under certain hyperparameter settings, the model reaches the highest AUC among all experiments (AUC±SD = 0.99±0.01) and the estimated attention maps concentrate on the regions of interests for this task. Three best-performing hyperparameter selections according to MSGA were applied to the holdout test set and reached comparable model performance to that of the validation set. CONCLUSIONS: Our results suggest that, for a task with only scan-level labels available, MSGA+RF can utilize the population-level domain knowledge to guide the training of the network, which increases both model accuracy and explainability.

Radiation exposure from CT scans: how to close our knowledge gaps, monitor and safeguard exposure--proceedings and recommendations of the Radiation Dose Summit, sponsored by NIBIB, February 24-25, 2011.

This article summarizes the proceedings of a portion of the Radiation Dose Summit, which was organized by the National Institute of Biomedical Imaging and Bioengineering and held in Bethesda, Maryland, in February 2011. The current understandings of ways to optimize the benefit-risk ratio of computed tomography (CT) examinations are summarized and recommendations are made for priority areas of research to close existing gaps in our knowledge. The prospects of achieving a submillisievert effective dose CT examination routinely are assessed.

American Thoracic Society documents: an official American Thoracic Society/Society of Thoracic Radiology Clinical Practice Guideline--Evaluation of Suspected Pulmonary Embolism in Pregnancy.

BACKGROUND: Pulmonary embolism (PE) is a leading cause of maternal mortality in the developed world. Along with appropriate prophylaxis and therapy, prevention of death from PE in pregnancy requires a high index of clinical suspicion followed by a timely and accurate diagnostic approach. METHODS: To provide guidance on this important health issue, a multidisciplinary panel of major medical stakeholders was convened to develop evidence-based guidelines for evaluation of suspected pulmonary embolism in pregnancy using the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system. In formulation of the recommended diagnostic algorithm, the important outcomes were defined to be diagnostic accuracy and diagnostic yield; the panel placed a high value on minimizing cumulative radiation dose when determining the recommended sequence of tests. RESULTS: Overall, the quality of the underlying evidence for all recommendations was rated as very low or low with some of the evidence considered for recommendations extrapolated from studies of the general population. Despite the low quality evidence, strong recommendations were made for three specific scenarios: performance of chest radiography (CXR) as the first radiation-associated procedure; use of lung scintigraphy as the preferred test in the setting of a normal CXR; and performance of computed-tomographic pulmonary angiography (CTPA) rather than digital subtraction angiography (DSA) in a pregnant woman with a nondiagnostic ventilation-perfusion (V/Q) result. DISCUSSION: The recommendations presented in this guideline are based upon the currently available evidence; availability of new clinical research data and development and dissemination of new technologies will necessitate a revision and update.

Reproducibility of volume and densitometric measures of emphysema on repeat computed tomography with an interval of 1 week.

OBJECTIVES: The reproducibilities of CT lung volume and densitometric measures of emphysema were assessed over 1 week. The influence of breathhold on reproducibility was assessed. METHODS: HRCT was performed on 44 subjects at inspiration on two visits with a 7-day interval. CT lung volume, relative area below -950HU (RA950-raw), and 15th percentile density (PD15-raw) were computed. Volume correction was used to obtain RA950-adj and PD15-adj. Reproducibilities between visits were assessed using concordance correlation coefficient (CCC) and repeatability coefficient (RC). Reproducibilities were compared between raw and adjusted measures. Differences between visits were computed for volume and density measures. Correlations were computed for density differences versus volume difference. Subgroup analysis was performed using a 0.25 L volume difference threshold. RESULTS: High CCC were observed for all measures in full group (CCC > 0.97). Reproducibilities of volume (RC = 0.67 L), RA950-raw (RC = 2.3%), and PD15-raw (RC = 10.6HU) were observed. Volume correction significantly improved PD15 (RC = 3.6HU) but not RA950 (RC = 1.7%). RA950-raw and PD15-raw had significantly better RC in <0.25 L subgroup than ≥0.25 L. Significant correlations with volume were observed for RA950-raw and PD15-raw (R (2) > 0.71), but not RA950-adj or PD15-adj (R (2) < 0.11). CONCLUSIONS: Good breathhold and RA950 reproducibilities were achieved. PD15 was less reproducible but improved with volume correction or superior breathhold reproduction. KEY POINTS: • Good breath-hold reproducibility is achievable between multiple CT examinations. • Reproducibility of densitometric measures may be improved by statistical volume correction. • Volume correction may result in decreased signal. • Densitometric reproducibility may also be improved by achieving good breath-hold reproduction. • Careful consideration of signal and noise is necessary in reproducibility assessment.

Emphysema lung lobe volume reduction: effects on the ipsilateral and contralateral lobes.

OBJECTIVES: To investigate volumetric and density changes in the ipsilateral and contralateral lobes following volume reduction of an emphysematous target lobe. METHODS: The study included 289 subjects with heterogeneous emphysema, who underwent bronchoscopic volume reduction of the most diseased lobe with endobronchial valves and 132 untreated controls. Lobar volume and low-attenuation relative area (RA) changes post-procedure were measured from computed tomography images. Regression analysis (Spearman's rho) was performed to test the association between change in the target lobe volume and changes in volume and density variables in the other lobes. RESULTS: The target lobe volume at full inspiration in the treatment group had a mean reduction of -0.45 L (SE = 0.034, P < 0.0001), and was associated with volume increases in the ipsilateral lobe (rho = -0.68, P < 0.0001) and contralateral lung (rho = -0.16, P = 0.006), and overall reductions in expiratory RA (rho = 0.31, P < 0.0001) and residual volume (RV)/total lung capacity (TLC) (rho = 0.13, P = 0.03). CONCLUSIONS: When the volume of an emphysematous target lobe is reduced, the volume is redistributed primarily to the ipsilateral lobe, with an overall reduction. Image-based changes in lobar volumes and densities indicate that target lobe volume reduction is associated with statistically significant overall reductions in air trapping, consistent with expansion of the healthier lung. KEY POINTS: Computed tomography allows assessment of the treatment of emphysema with endobronchial valves. • Endobronchial valves can reduce the volume of an emphysematous lung lobe. • Compensatory expansion is greater in ipsilateral lobes than in the contralateral lung. • Reduced air trapping is measurable by RV/TLC and smaller low attenuation area.

A comparison of methods to estimate organ doses in CT when utilizing approximations to the tube current modulation function.

PURPOSE: Most methods to estimate patient dose from computed tomography (CT) exams have been developed based on fixed tube current scans. However, in current clinical practice, many CT exams are performed using tube current modulation (TCM). Detailed information about the TCM function is difficult to obtain and therefore not easily integrated into patient dose estimate methods. The purpose of this study was to investigate the accuracy of organ dose estimates obtained using methods that approximate the TCM function using more readily available data compared to estimates obtained using the detailed description of the TCM function. METHODS: Twenty adult female models generated from actual patient thoracic CT exams and 20 pediatric female models generated from whole body PET∕CT exams were obtained with IRB (Institutional Review Board) approval. Detailed TCM function for each patient was obtained from projection data. Monte Carlo based models of each scanner and patient model were developed that incorporated the detailed TCM function for each patient model. Lungs and glandular breast tissue were identified in each patient model so that organ doses could be estimated from simulations. Three sets of simulations were performed: one using the original detailed TCM function (x, y, and z modulations), one using an approximation to the TCM function (only the z-axis or longitudinal modulation extracted from the image data), and the third was a fixed tube current simulation using a single tube current value which was equal to the average tube current over the entire exam. Differences from the reference (detailed TCM) method were calculated based on organ dose estimates. Pearson's correlation coefficients were calculated between methods after testing for normality. Equivalence test was performed to compare the equivalence limit between each method (longitudinal approximated TCM and fixed tube current method) and the detailed TCM method. Minimum equivalence limit was reported for each organ. RESULTS: Doses estimated using the longitudinal approximated TCM resulted in small differences from doses obtained using the detailed TCM function. The calculated root-mean-square errors (RMSE) for adult female chest simulations were 9% and 3% for breasts and lungs, respectively; for pediatric female chest and whole body simulations RMSE were 9% and 7% for breasts and 3% and 1% for lungs, respectively. Pearson's correlation coefficients were consistently high for the longitudinal approximated TCM method, ranging from 0.947 to 0.999, compared to the fixed tube current value ranging from 0.8099 to 0.9916. In addition, an equivalence test illustrated that across all models the longitudinal approximated TCM is equivalent to the detailed TCM function within up to 3% for lungs and breasts. CONCLUSIONS: While the best estimate of organ dose requires the detailed description of the TCM function for each patient, extracting these values can be difficult. The presented results show that an approximation using available data extracted from the DICOM header provides organ dose estimates with RMSE of less than 10%. On the other hand, the use of the overall average tube current as a single tube current value was shown to result in poor and inconsistent estimates of organ doses.

Peak skin and eye lens radiation dose from brain perfusion CT based on Monte Carlo simulation.

OBJECTIVE: The purpose of our study was to accurately estimate the radiation dose to skin and the eye lens from clinical CT brain perfusion studies, investigate how well scanner output (expressed as volume CT dose index [CTDI(vol)]) matches these estimated doses, and investigate the efficacy of eye lens dose reduction techniques. MATERIALS AND METHODS: Peak skin dose and eye lens dose were estimated using Monte Carlo simulation methods on a voxelized patient model and 64-MDCT scanners from four major manufacturers. A range of clinical protocols was evaluated. CTDI(vol) for each scanner was obtained from the scanner console. Dose reduction to the eye lens was evaluated for various gantry tilt angles as well as scan locations. RESULTS: Peak skin dose and eye lens dose ranged from 81 mGy to 348 mGy, depending on the scanner and protocol used. Peak skin dose and eye lens dose were observed to be 66-79% and 59-63%, respectively, of the CTDI(vol) values reported by the scanners. The eye lens dose was significantly reduced when the eye lenses were not directly irradiated. CONCLUSION: CTDI(vol) should not be interpreted as patient dose; this study has shown it to overestimate dose to the skin or eye lens. These results may be used to provide more accurate estimates of actual dose to ensure that protocols are operated safely below thresholds. Tilting the gantry or moving the scanning region further away from the eyes are effective for reducing lens dose in clinical practice. These actions should be considered when they are consistent with the clinical task and patient anatomy.

An official American Thoracic Society/Society of Thoracic Radiology clinical practice guideline: evaluation of suspected pulmonary embolism in pregnancy.

BACKGROUND: Pulmonary embolism (PE) is a leading cause of maternal mortality in the developed world. Along with appropriate prophylaxis and therapy, prevention of death from PE in pregnancy requires a high index of clinical suspicion followed by a timely and accurate diagnostic approach. METHODS: To provide guidance on this important health issue, a multidisciplinary panel of major medical stakeholders was convened to develop evidence-based guidelines for evaluation of suspected pulmonary embolism in pregnancy using the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system. In formulation of the recommended diagnostic algorithm, the important outcomes were defined to be diagnostic accuracy and diagnostic yield; the panel placed a high value on minimizing cumulative radiation dose when determining the recommended sequence of tests. RESULTS: Overall, the quality of the underlying evidence for all recommendations was rated as very low or low, with some of the evidence considered for recommendations extrapolated from studies of the general population. Despite the low-quality evidence, strong recommendations were made for three specific scenarios: performance of chest radiography (CXR) as the first radiation-associated procedure; use of lung scintigraphy as the preferred test in the setting of a normal CXR; and performance of computed-tomographic pulmonary angiography (CTPA) rather than digital subtraction angiography (DSA) in a pregnant woman with a nondiagnostic ventilation-perfusion (V/Q) result. DISCUSSION: The recommendations presented in this guideline are based upon the currently available evidence; availability of new clinical research data and development and dissemination of new technologies will necessitate a revision and update.

The feasibility of patient size-corrected, scanner-independent organ dose estimates for abdominal CT exams.

PURPOSE: A recent work has demonstrated the feasibility of estimating the dose to individual organs from multidetector CT exams using patient-specific, scanner-independent CTDIvol-to-organ-dose conversion coefficients. However, the previous study only investigated organ dose to a single patient model from a full-body helical CT scan. The purpose of this work was to extend the validity of this dose estimation technique to patients of any size undergoing a common clinical exam. This was done by determining the influence of patient size on organ dose conversion coefficients generated for typical abdominal CT exams. METHODS: Monte Carlo simulations of abdominal exams were performed using models of 64-slice MDCT scanners from each of the four major manufacturers to obtain dose to radiosensitive organs for eight patient models of varying size, age, and gender. The scanner-specific organ doses were normalized by corresponding CTDIvol values and averaged across scanners to obtain scanner-independent CTDIvol-to-organ-dose conversion coefficients for each patient model. In order to obtain a metric for patient size, the outer perimeter of each patient was measured at the central slice of the abdominal scan region. Then, the relationship between CTDIvol-to-organ-dose conversion coefficients and patient perimeter was investigated for organs that were directly irradiated by the abdominal scan. These included organs that were either completely ("fully irradiated") or partly ("partially irradiated") contained within the abdominal exam region. Finally, dose to organs that were not at all contained within the scan region ("nonirradiated") were compared to the doses delivered to fully irradiated organs. RESULTS: CTDIvol-to-organ-dose conversion coefficients for fully irradiated abdominal organs had a strong exponential correlation with patient perimeter. Conversely, partially irradiated organs did not have a strong dependence on patient perimeter. In almost all cases, the doses delivered to nonirradiated organs were less than 5%, on average across patient models, of the mean dose of the fully irradiated organs. CONCLUSIONS: This work demonstrates the feasibility of calculating patient-specific, scanner-independent CTDIvol-to-organ-dose conversion coefficients for fully irradiated organs in patients undergoing typical abdominal CT exams. A method to calculate patient-specific, scanner-specific, and exam-specific organ dose estimates that requires only knowledge of the CTDIvol for the scan protocol and the patient's perimeter is thus possible. This method will have to be extended in future studies to include organs that are partially irradiated. Finally, it was shown that, in most cases, the doses to nonirradiated organs were small compared to the dose to fully irradiated organs.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans.

PURPOSE: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. METHODS: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ("nodule > or =3 mm," "nodule <3 mm," and "non-nodule > or =3 mm"). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. RESULTS: The Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked "nodule > or =3 mm" by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. CONCLUSIONS: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.

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.

Precision of dosimetry-related measurements obtained on current multidetector computed tomography scanners.

PURPOSE: Computed tomography (CT) intrascanner and interscanner variability has not been well characterized. Thus, the purpose of this study was to examine the within-run, between-run, and between-scanner precision of physical dosimetry-related measurements collected over the course of 1 yr on three different makes and models of multidetector row CT (MDCT) scanners. METHODS: Physical measurements were collected using nine CT scanners (three scanners each of GE VCT, GE LightSpeed 16, and Siemens Sensation 64 CT). Measurements were made using various combinations of technical factors, including kVp, type of bowtie filter, and x-ray beam collimation, for several dosimetry-related quantities, including (a) free-in-air CT dose index (CTDI100,air); (b) calculated half-value layers and quarter-value layers; and (c) weighted CT dose index (CTDIW) calculated from exposure measurements collected in both a 16 and 32 cm diameter CTDI phantom. Data collection was repeated at several different time intervals, ranging from seconds (for CTDI100,air values) to weekly for 3 weeks and then quarterly or triannually for 1 yr. Precision of the data was quantified by the percent coefficient of variation (%CV). RESULTS: The maximum relative precision error (maximum %CV value) across all dosimetry metrics, time periods, and scanners included in this study was 4.33%. The median observed %CV values for CTDI100,air ranged from 0.05% to 0.19% over several seconds, 0.12%-0.52% over 1 week, and 0.58%-2.31% over 3-4 months. For CTDIW for a 16 and 32 cm CTDI phantom, respectively, the range of median %CVs was 0.38%-1.14% and 0.62%-1.23% in data gathered weekly for 3 weeks and 1.32%-2.79% and 0.84%-2.47% in data gathered quarterly or triannually for 1 yr. CONCLUSIONS: From a dosimetry perspective, the MDCT scanners tested in this study demonstrated a high degree of within-run, between-run, and between-scanner precision (with relative precision errors typically well under 5%).

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.

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.