Prospective estimation of organ dose in CT under tube current modulation

CT scanner-specific organ dose coefficients generated by Monte Carlo calculation for the ICRP adult male and female reference computational phantoms

Objective.Provide analyses of new organ dose coefficients (hereafter also referred to as normalized doses) for CT that have been developed to update the widely-utilized collection of data published 30 years ago in NRPB-SR250.Approach.In order to reflect changes in technology, and also ICRP recommendations concerning use of the computational phantoms adult male (AM) and adult female (AF), 102 series of new Monte Carlo simulations have been performed covering the range of operating conditions for 12 contemporary models of CT scanner from 4 manufacturers. Normalized doses (relative to free air on axis) have been determined for 39 organs, and for every 8 mm or 4.84 mm slab of AM and AF, respectively.Main results.Analyses of results confirm the significant influence (by up to a few tens of percent), on values of normalized organ (or contributions to effective dose (E_103,phan)), for whole body exposure arising from selection of tube voltage and beam shaping filter. Use of partial (when available) rather than a Full fan beam reduced both organ and effective dose by up to 7%. Normalized doses to AF were larger than corresponding figures for AM by up to 30% for organs and by 10% forE_103,phan. Additional simulations for whole body exposure have also demonstrated that: practical simplifications in the main modelling (point source, single slice thickness, neglect of patient couch and immobility of phantom arms) have sufficiently small (<5%) effect onE_103,phan; mis-centring of the phantom away from the axis of rotation by 5 mm (in any direction) leads to changes in normalized organ dose andE_103,phanby up to 20% and 6%, respectively; and angular tube current modulation can result in reductions by up to 35% and <15% in normalized organ dose andE_103,phan, respectively, for 100% cosine variation.Significance.These analyses help advance understanding of the influence of operational scanner settings on organ dose coefficients for contemporary CT, in support of improved patient protection. The results will allow the future development of a new dose estimation tool.

Patient-level dose monitoring in computed tomography: tracking cumulative dose from multiple multi-sequence exams with tube current modulation in children

BACKGROUND

In children exposed to multiple computed tomography (CT) exams, performed with varying z-axis coverage and often with tube current modulation, it is inaccurate to add volume CT dose index (CTDI_vol) and size-specific dose estimate (SSDE) to obtain cumulative dose values.

OBJECTIVE

To introduce the patient-size-specific z-axis dose profile and its dose line integral (DLI) as new dose metrics, and to use them to compare cumulative dose calculations against conventional measures.

MATERIALS AND METHODS

In all children with 2 or more abdominal-pelvic CT scans performed from 2013 through 2019, we retrospectively recorded all series kV, z-axis tube current profile, CTDI_vol, dose-length product (DLP) and calculated SSDE. We constructed dose profiles as a function of z-axis location for each series. One author identified the z-axis location of the superior mesenteric artery origin on each series obtained to align the dose profiles for construction of each patient's cumulative profile. We performed pair-wise comparisons between the peak dose of the cumulative patient dose profile and ΣSSDE, and between ΣDLI and ΣDLP.

RESULTS

We recorded dose data in 143 series obtained in 48 children, ages 0-2 years (n=15) and 8-16 years (n=33): ΣSSDE 12.7±6.7 and peak dose 15.1±8.1 mGy, ΣDLP 278±194 and ΣDLI 550±292 mGy·cm. Peak dose exceeded ΣSSDE by 20.6% (interquartile range [IQR]: 9.9-26.4%, P<0.001), and ΣDLI exceeded ΣDLP by 114% (IQR: 86.5-147.0%, P<0.001).

CONCLUSION

Our methodology represents a novel approach for evaluating radiation exposure in recurring pediatric abdominal CT examinations, both at the individual and population levels. Under a wide range of patient variables and acquisition conditions, graphic depiction of the cumulative z-axis dose profile across and beyond scan ranges, including the peak dose of the profile, provides a better tool for cumulative dose documentation than simple summations of SSDE. ΣDLI is advantageous in characterizing overall energy absorption over ΣDLP, which significantly underestimated this in all children.

A scanner-specific framework for simulating CT images with tube current modulation

Although tube current modulation (TCM) is routinely implemented in modern computed tomography (CT) scans, no existing CT simulator is capable of generating realistic images with TCM. The goal of this study was to develop such a framework to (1) facilitate patient-specific optimization of TCM parameters and (2) enable future virtual imaging trials (VITs) with more clinically realistic image quality and x-ray flux distributions. The framework was created by developing a TCM module and integrating it with an existing CT simulator (DukeSim). The developed module utilizes scanner-calibrated TCM parameters and two localizer radiographs to compute the mAs for each simulated CT projection. This simulation pipeline was validated in two parts. First, DukeSim was validated in the context of a commercial scanner with TCM (SOMATOM Force, Siemens Healthineers) by imaging a physical CT phantom (Mercury, Sun Nuclear) and its computational analogue. Second, the TCM module was validated by imaging a computational anthropomorphic phantom (ATOM, CIRS) using DukeSim with real and module-generated TCM profiles. The validation demonstrated DukeSim's realism in terms of noise magnitude, noise texture, spatial resolution, and image contrast (with average differences of 0.38%, 6.31%, 0.43%, and -9 HU, respectively). It also demonstrated the TCM module's realism in terms of projection-level mAs and resulting noise magnitude (2.86% and -2.60%, respectively). Finally, the framework was applied to a pilot VIT simulating images of three computational anthropomorphic phantoms (XCAT, with body mass indices (BMIs) of 24.3, 28.2, and 33.0) under five different TCM settings. The optimal TCM for each phantom was characterized based on various criteria, such as minimizing mAs or maximizing image quality. 'Very Weak' TCM minimized noise for the 24.3 BMI phantom, while 'Very Strong' TCM minimized noise for the 33.0 BMI phantom. This illustrates the utility of the developed framework for future optimization studies of TCM parameters and, more broadly, large-scale VITs with scanner-specific TCM.

iPhantom: A Framework for Automated Creation of Individualized Computational Phantoms and Its Application to CT Organ Dosimetry

OBJECTIVE

This study aims to develop and validate a novel framework, iPhantom, for automated creation of patient-specific phantoms or "digital-twins (DT)" using patient medical images. The framework is applied to assess radiation dose to radiosensitive organs in CT imaging of individual patients.

METHOD

Given a volume of patient CT images, iPhantom segments selected anchor organs and structures (e.g., liver, bones, pancreas) using a learning-based model developed for multi-organ CT segmentation. Organs which are challenging to segment (e.g., intestines) are incorporated from a matched phantom template, using a diffeomorphic registration model developed for multi-organ phantom-voxels. The resulting digital-twin phantoms are used to assess organ doses during routine CT exams.

RESULT

iPhantom was validated on both with a set of XCAT digital phantoms (n = 50) and an independent clinical dataset (n = 10) with similar accuracy. iPhantom precisely predicted all organ locations yielding Dice Similarity Coefficients (DSC) 0.6 - 1 for anchor organs and DSC of 0.3-0.9 for all other organs. iPhantom showed <10% errors in estimated radiation dose for the majority of organs, which was notably superior to the state-of-the-art baseline method (20-35% dose errors).

CONCLUSION

iPhantom enables automated and accurate creation of patient-specific phantoms and, for the first time, provides sufficient and automated patient-specific dose estimates for CT dosimetry.

SIGNIFICANCE

The new framework brings the creation and application of CHPs (computational human phantoms) to the level of individual CHPs through automation, achieving wide and precise organ localization, paving the way for clinical monitoring, personalized optimization, and large-scale research.

Clinical commissioning of intensity-modulated proton therapy systems: Report of AAPM Task Group 185

Proton therapy is an expanding radiotherapy modality in the United States and worldwide. With the number of proton therapy centers treating patients increasing, so does the need for consistent, high-quality clinical commissioning practices. Clinical commissioning encompasses the entire proton therapy system's multiple components, including the treatment delivery system, the patient positioning system, and the image-guided radiotherapy components. Also included in the commissioning process are the x-ray computed tomography scanner calibration for proton stopping power, the radiotherapy treatment planning system, and corresponding portions of the treatment management system. This commissioning report focuses exclusively on intensity-modulated scanning systems, presenting details of how to perform the commissioning of the proton therapy and ancillary systems, including the required proton beam measurements, treatment planning system dose modeling, and the equipment needed.

Precise and Automatic Patient Positioning in Computed Tomography: Avatar Modeling of the Patient Surface Using a 3-Dimensional Camera

OBJECTIVES

The aim of this study was to evaluate the accuracy of a 3-dimensional (3D) camera algorithm for automatic and individualized patient positioning based on body surface detection and to compare the results of the 3D camera with manual positioning performed by technologists in routinely obtained chest and abdomen computed tomography (CT) examinations.

MATERIALS AND METHODS

This study included data of 120 patients undergoing clinically indicated chest (n = 68) and abdomen (n = 52) CT. Fifty-two of the patients were scanned with CT using a table height manually selected by technologists; 68 patients were automatically positioned with the 3D camera, which is based on patient-specific body surface and contour detection. The ground truth table height (TGT) was defined as the table height that aligns the axial center of the patient's body region in the CT scanner isocenter. Off-centering was defined as the difference between the ground truth table height (TGT) and the actual table position used in all CT examinations. The t test was performed to determine significant differences in the vertical offset between automatic and manual positioning. The χ test was used to check whether there was a relationship between patient size and the magnitude of off-centering.

RESULTS

We found a significant improvement in patient centering (offset 5 ± 3 mm) when using the automatic positioning algorithm with the 3D camera compared with manual positioning (offset 19 ± 10 mm) performed by technologists (P < 0.005). Automatic patient positioning based on the 3D camera reduced the average offset in vertical table position from 19 mm to 7 mm for chest and from 18 mm to 4 mm for abdomen CT. The absolute maximal offset was 39 mm and 43 mm for chest and abdomen CT, respectively, when patients were positioned manually, whereas with automatic positioning using the 3D camera the offset never exceeded 15 mm. In chest CT performed with manual patient positioning, we found a significant correlation between vertical offset greater than 20 mm and patient size (body mass index, >26 kg/m, P < 0.001). In contrast, no such relationship was found for abdomen CT (P = 0.38).

CONCLUSIONS

Automatic individualized patient positioning using a 3D camera allows for accurate patient centering as compared with manual positioning, which improves radiation dose utilization.

Expanding the Concept of Diagnostic Reference Levels to Noise and Dose Reference Levels in CT

OBJECTIVE. Diagnostic reference levels were developed as guidance for radiation dose in medical imaging and, by inference, diagnostic quality. The objective of this work was to expand the concept of diagnostic reference levels to explicitly include noise of CT examinations to simultaneously target both dose and quality through corresponding reference values. MATERIALS AND METHODS. The study consisted of 2851 adult CT examinations performed with scanners from two manufacturers and two clinical protocols: abdominopelvic CT with IV contrast administration and chest CT without IV contrast administration. An institutional informatics system was used to automatically extract protocol type, patient diameter, volume CT dose index, and noise magnitude from images. The data were divided into five reference patient size ranges. Noise reference level, noise reference range, dose reference level, and dose reference range were defined for each size range. RESULTS. The data exhibited strong dependence between dose and patient size, weak dependence between noise and patient size, and different trends for different manufacturers with differing strategies for tube current modulation. The results suggest size-based reference intervals and levels for noise and dose (e.g., noise reference level and noise reference range of 11.5-12.9 HU and 11.0-14.0 HU for chest CT and 10.1-12.1 HU and 9.4-13.7 HU for abdominopelvic CT examinations) that can be targeted to improve clinical performance consistency. CONCLUSION. New reference levels and ranges, which simultaneously consider image noise and radiation dose information across wide patient populations, were defined and determined for two clinical protocols. The methods of new quantitative constraints may provide unique and useful information about the goal of managing the variability of image quality and dose in clinical CT examinations.

Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond

The four-dimensional (4-D) eXtended CArdiac-Torso (XCAT) series of phantoms was developed to provide accurate computerized models of the human anatomy and physiology. The XCAT series encompasses a vast population of phantoms of varying ages from newborn to adult, each including parameterized models for the cardiac and respiratory motions. With great flexibility in the XCAT's design, any number of body sizes, different anatomies, cardiac or respiratory motions or patterns, patient positions and orientations, and spatial resolutions can be simulated. As such, the XCAT phantoms are gaining a wide use in biomedical imaging research. There they can provide a virtual patient base from which to quantitatively evaluate and improve imaging instrumentation, data acquisition, techniques, and image reconstruction and processing methods which can lead to improved image quality and more accurate clinical diagnoses. The phantoms have also found great use in radiation dosimetry, radiation therapy, medical device design, and even the security and defense industry. This review paper highlights some specific areas in which the XCAT phantoms have found use within biomedical imaging and other fields. From these examples, we illustrate the increasingly important role that computerized phantoms and computer simulation are playing in the research community.

Synthetic breast phantoms from patient based eigenbreasts

PURPOSE

The limited number of 3D patient-based breast phantoms available could be augmented by synthetic breast phantoms in order to facilitate virtual clinical trials (VCTs) using model observers for breast imaging optimization and evaluation.

METHODS

These synthetic breast phantoms were developed using Principal Component Analysis (PCA) to reduce the number of dimensions needed to describe a training set of images. PCA decomposed a training set of M breast CT volumes (with millions of voxels each) into an M-1-dimensional space of eigenvectors, which we call eigenbreasts. Each of the training breast phantoms was compactly represented by the mean image plus a weighted sum of eigenbreasts. The distribution of weights observed from training was then sampled to create new synthesized breast phantoms.

RESULTS

The resulting synthesized breast phantoms demonstrated a high degree of realism, as supported by an observer study. Two out of three experienced physicist observers were unable to distinguish between the synthesized breast phantoms and the patient-based phantoms. The fibroglandular density and noise power law exponent of the synthesized breast phantoms agreed well with the training data.

CONCLUSIONS

Our method extends our series of digital breast phantoms based on breast CT data, providing the capability to generate new, statistically varying ensembles consisting of tens of thousands of virtual subjects. This work represents an important step toward conducting future virtual trials for task-based assessment of breast imaging, where it is vital to have a large ensemble of realistic phantoms for statistical power as well as clinical relevance.

Physical validation of a Monte Carlo-based, phantom-derived approach to computed tomography organ dosimetry under tube current modulation

PURPOSE

To physically validate the accuracy of a Monte Carlo-based, phantom-derived methodology for computed tomography (CT) dosimetry that utilizes organ doses from precomputed axial scans and that accounts for tube current modulation (TCM).

METHODS

The output of a Toshiba Aquilion ONE CT scanner was modeled, based on physical measurement, in the Monte Carlo radiation transport code MCNPX (v2.70). CT examinations were taken of two anthropomorphic phantoms representing pediatric and adult patients (15-yr-old female and adult male) at various energies, in which physical organ dose measurements were made using optically stimulated luminescence dosimeters (OSLDs). These exams (chest-abdomen-pelvis) were modeled using organ dose data obtained from the computationally equivalent phantom of each anthropomorphic phantom. TCM was accounted for by weighting all organ dose contributions by both the relative attenuation of the phantom and the image-derived mA value (from the DICOM header) at the same z-extent (cranial-caudal direction) of the axial dose data.

RESULTS

The root mean squares of percent difference in organ dose when comparing the physical organ dose measurements to the computational estimates were 21.2, 12.1, and 15.1% for the uniform (no attenuation weighting), weighted (computationally derived), and image-based methodologies, respectively.

CONCLUSIONS

Overall, these data suggest that the Monte Carlo-based dosimetry presented in this work is viable for CT dosimetry. Additionally, for CT exams with TCM, local attenuation weighting of organ dose contributions from precomputed axial dosimetry libraries increases organ dose accuracy.

Characterization of radiation dose from tube current modulated CT examinations with considerations of both patient size and variable tube current

PURPOSE

The volume CT dose index (CTDI_vol ) and the size-specific dose estimate (SSDE) are widely used for monitoring patient dose from CT examinations. Both metrics may represent the average dose over the central scan plane of the CTDI phantom or the patient under constant tube current (mA), but they are not intended for the tube current modulation (TCM)-enabled CT examinations, in which the peak dose across the scanned range may not be at the scan range center. To overcome the limitation, this paper illustrates an alternative approach, its implementation, and the relationship between longitudinal dose distribution D_L (z) in water cylinder and mA line shape, scan length, as well as phantom diameter.

METHODS

A dose calculation algorithm and the published data by Li et al. [Med. Phys. 40, 031903 (10pp.) (2013); 41, 111910 (5pp.) (2014)] were used to calculate D_L (z) for the central and peripheral axes of 10- to 50-cm diameter water phantoms undergoing CT scans of one constant and three variable mA distributions, each of which in three scan lengths of 10, 28.6, and 50 cm. All scans had an identical average tube current over the scan ranges. The results in the scanned ranges were used to assess the D_L (z) to mA(z) ratios, and their coefficients of variation (CV = stdev/mean) were used to compare the line shapes of D_L (z) and mA(z) for congruence: identical line shapes would result in CV = 0, but largely different line shapes would result in high CV.

RESULTS

In 30-cm diameter water phantom, the line shape of D_L (z) was largely different from that of mA(z). CV was higher in a variable mA scan than in a constant mA scan. As the scan length of variable mA scan increased, CV mostly decreased, and the line shape of D_L (z) more closely resembled that of mA(z). When two phantom axes were compared, CV was smaller and the line shape of D_L (z) more closely resembled that of mA(z) on the peripheral axis than on the central axis. In 41 water phantoms included in this study, CV mostly increased with phantom diameter, and approached the limiting levels on the peripheral axes of large phantoms. In constant mA scans, CV ranged from 5.5% to 14.0% on the phantom central axes and from 4.6% to 6.4% on the phantom peripheral axes. However, in variable tube current scans, CV ranged from 7.4% to 70.0% on the phantom central axes and from 5.1% to 35.9% on the phantom peripheral axes.

CONCLUSION

D_L (z) (water) may be advantageous over current CT dose metrics in characterizing the dose dependences on both patient size and mA line shape from tube current modulated examinations. Evaluating D_L (z) (water) with the water equivalent diameter and tube current curve from clinical examinations has a potential to improve CT dose monitoring program.

Estimating patient dose from CT exams that use automatic exposure control: Development and validation of methods to accurately estimate tube current values

PURPOSE

The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturer's AEC system to enable accurate estimates of patient dose.

METHODS

Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x-ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual-topo) as well as the simulated topogram based on image data (sim-topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating patient organ doses, Monte Carlo simulations were performed by creating voxelized models of each patient, identifying key organs and incorporating tube current values into the simulations to estimate dose to the lungs and breasts (females only) for chest scans and the liver, kidney, and spleen for abdomen/pelvis scans. Organ doses from simulations using the actual tube current values were compared to those using each of the estimated tube current values (actual-topo and sim-topo).

RESULTS

When compared to the actual tube current values, the average error for tube current values estimated from the actual topogram (actual-topo) and simulated topogram (sim-topo) was 3.9% and 5.8% respectively. For Monte Carlo simulations of chest CT exams using the actual tube current values and estimated tube current values (based on the actual-topo and sim-topo methods), the average differences for lung and breast doses ranged from 3.4% to 6.6%. For abdomen/pelvis exams, the average differences for liver, kidney, and spleen doses ranged from 4.2% to 5.3%.

CONCLUSIONS

Strong agreement between organ doses estimated using actual and estimated tube current values provides validation of both methods for estimating tube current values based on data provided in the topogram or simulated from image data.

Estimating organ doses from tube current modulated CT examinations using a generalized linear model

PURPOSE

Currently, available Computed Tomography dose metrics are mostly based on fixed tube current Monte Carlo (MC) simulations and/or physical measurements such as the size specific dose estimate (SSDE). In addition to not being able to account for Tube Current Modulation (TCM), these dose metrics do not represent actual patient dose. The purpose of this study was to generate and evaluate a dose estimation model based on the Generalized Linear Model (GLM), which extends the ability to estimate organ dose from tube current modulated examinations by incorporating regional descriptors of patient size, scanner output, and other scan-specific variables as needed.

METHODS

The collection of a total of 332 patient CT scans at four different institutions was approved by each institution's IRB and used to generate and test organ dose estimation models. The patient population consisted of pediatric and adult patients and included thoracic and abdomen/pelvis scans. The scans were performed on three different CT scanner systems. Manual segmentation of organs, depending on the examined anatomy, was performed on each patient's image series. In addition to the collected images, detailed TCM data were collected for all patients scanned on Siemens CT scanners, while for all GE and Toshiba patients, data representing z-axis-only TCM, extracted from the DICOM header of the images, were used for TCM simulations. A validated MC dosimetry package was used to perform detailed simulation of CT examinations on all 332 patient models to estimate dose to each segmented organ (lungs, breasts, liver, spleen, and kidneys), denoted as reference organ dose values. Approximately 60% of the data were used to train a dose estimation model, while the remaining 40% was used to evaluate performance. Two different methodologies were explored using GLM to generate a dose estimation model: (a) using the conventional exponential relationship between normalized organ dose and size with regional water equivalent diameter (WED) and regional CTDIvol as variables and (b) using the same exponential relationship with the addition of categorical variables such as scanner model and organ to provide a more complete estimate of factors that may affect organ dose. Finally, estimates from generated models were compared to those obtained from SSDE and ImPACT.

RESULTS

The Generalized Linear Model yielded organ dose estimates that were significantly closer to the MC reference organ dose values than were organ doses estimated via SSDE or ImPACT. Moreover, the GLM estimates were better than those of SSDE or ImPACT irrespective of whether or not categorical variables were used in the model. While the improvement associated with a categorical variable was substantial in estimating breast dose, the improvement was minor for other organs.

CONCLUSIONS

The GLM approach extends the current CT dose estimation methods by allowing the use of additional variables to more accurately estimate organ dose from TCM scans. Thus, this approach may be able to overcome the limitations of current CT dose metrics to provide more accurate estimates of patient dose, in particular, dose to organs with considerable variability across the population.

Automated, patient-specific estimation of regional imparted energy and dose from tube current modulated computed tomography exams across 13 protocols

Currently, computed tomography (CT) dosimetry relies on surrogates for dose, such as CT dose index and size-specific dose estimates, rather than dose per se. Organ dose is considered as the gold standard for radiation dosimetry. However, organ dose estimation requires precise knowledge of organ locations. Regional imparted energy and dose can also be used to quantify radiation burden and are beneficial because they do not require knowledge of organ size or location. This work investigated an automated technique to retrospectively estimate the imparted energy from tube current-modulated (TCM) CT exams across 13 protocols. Monte Carlo simulations of various head and body TCM CT examinations across various tube potentials and TCM strengths were performed on 58 adult computational extended cardiac-torso phantoms to develop relationships between scanned mass and imparted energy normalized by dose length product. Results from the Monte Carlo simulations indicate that normalized imparted energy increases with increasing both scanned mass and tube potential, but it is relatively unaffected by the strength of the TCM. The automated algorithm was tested on 40 clinical datasets with a 98% success rate.