Browsing by Author "Segars, W Paul"

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    A systematic assessment and optimization of photon-counting CT for lung density quantifications.
    (Medical physics, 2024-02) Sotoudeh-Paima, Saman; Segars, W Paul; Ghosh, Dhrubajyoti; Luo, Sheng; Samei, Ehsan; Abadi, Ehsan

    Background

    Photon-counting computed tomography (PCCT) has recently emerged into clinical use; however, its optimum imaging protocols and added benefits remains unknown in terms of providing more accurate lung density quantification compared to energy-integrating computed tomography (EICT) scanners.

    Purpose

    To systematically assess the performance of a clinical PCCT scanner for lung density quantifications and compare it against EICT.

    Methods

    This cross-sectional study involved a retrospective analysis of subjects scanned (August-December 2021) using a clinical PCCT system. The influence of altering reconstruction parameters was studied (reconstruction kernel, pixel size, slice thickness). A virtual CT dataset of anthropomorphic virtual subjects was acquired to demonstrate the correspondence of findings to clinical dataset, and to perform systematic imaging experiments, not possible using human subjects. The virtual subjects were imaged using a validated, scanner-specific CT simulator of a PCCT and two EICT (defined as EICT A and B) scanners. The images were evaluated using mean absolute error (MAE) of lung and emphysema density against their corresponding ground truth.

    Results

    Clinical and virtual PCCT datasets showed similar trends, with sharper kernels and smaller voxel sizes increasing percentage of low-attenuation areas below -950 HU (LAA-950) by up to 15.7 ± 6.9% and 11.8 ± 5.5%, respectively. Under the conditions studied, higher doses, thinner slices, smaller pixel sizes, iterative reconstructions, and quantitative kernels with medium sharpness resulted in lower lung MAE values. While using these settings for PCCT, changes in the dose level (13 to 1.3 mGy), slice thickness (0.4 to 1.5 mm), pixel size (0.49 to 0.98 mm), reconstruction technique (70 keV-VMI to wFBP), and kernel (Qr48 to Qr60) increased lung MAE by 15.3 ± 2.0, 1.4 ± 0.6, 2.2 ± 0.3, 4.2 ± 0.8, and 9.1 ± 1.6 HU, respectively. At the optimum settings identified per scanner, PCCT images exhibited lower lung and emphysema MAE than those of EICT scanners (by 2.6 ± 1.0 and 9.6 ± 3.4 HU, compared to EICT A, and by 4.8 ± 0.8 and 7.4 ± 2.3 HU, compared to EICT B). The accuracy of lung density measurements was correlated with subjects' mean lung density (p < 0.05), measured by PCCT at optimum setting under the conditions studied.

    Conclusion

    Photon-counting CT demonstrated superior performance in density quantifications, with its influences of imaging parameters in line with energy-integrating CT scanners. The technology offers improvement in lung quantifications, thus demonstrating potential toward more objective assessment of respiratory conditions.
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    ItemOpen Access
    Comparison of 12 surrogates to characterize CT radiation risk across a clinical population.
    (European radiology, 2021-02-23) Ria, Francesco; Fu, Wanyi; Hoye, Jocelyn; Segars, W Paul; Kapadia, Anuj J; Samei, Ehsan

    Objectives

    Quantifying radiation burden is essential for justification, optimization, and personalization of CT procedures and can be characterized by a variety of risk surrogates inducing different radiological risk reflections. This study compared how twelve such metrics can characterize risk across patient populations.

    Methods

    This study included 1394 CT examinations (abdominopelvic and chest). Organ doses were calculated using Monte Carlo methods. The following risk surrogates were considered: volume computed tomography dose index (CTDIvol), dose-length product (DLP), size-specific dose estimate (SSDE), DLP-based effective dose (EDk ), dose to a defining organ (ODD), effective dose and risk index based on organ doses (EDOD, RI), and risk index for a 20-year-old patient (RIrp). The last three metrics were also calculated for a reference ICRP-110 model (ODD,0, ED0, and RI0). Lastly, motivated by the ICRP, an adjusted-effective dose was calculated as [Formula: see text]. A linear regression was applied to assess each metric's dependency on RI. The results were characterized in terms of risk sensitivity index (RSI) and risk differentiability index (RDI).

    Results

    The analysis reported significant differences between the metrics with EDr showing the best concordance with RI in terms of RSI and RDI. Across all metrics and protocols, RSI ranged between 0.37 (SSDE) and 1.29 (RI0); RDI ranged between 0.39 (EDk) and 0.01 (EDr) cancers × 103patients × 100 mGy.

    Conclusion

    Different risk surrogates lead to different population risk characterizations. EDr exhibited a close characterization of population risk, also showing the best differentiability. Care should be exercised in drawing risk predictions from unrepresentative risk metrics applied to a population.

    Key points

    • Radiation risk characterization in CT populations is strongly affected by the surrogate used to describe it. • Different risk surrogates can lead to different characterization of population risk. • Healthcare professionals should exercise care in ascribing an implicit risk to factors that do not closely reflect risk.
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    Dose coefficients for organ dosimetry in tomosynthesis imaging of adults and pediatrics across diverse protocols.
    (Medical physics, 2022-06-11) Sharma, Shobhit; Kapadia, Anuj; Ria, Francesco; Segars, W Paul; Samei, Ehsan

    Purpose

    The gold-standard method for estimation of patient-specific organ doses in digital tomosynthesis (DT) requires protocol-specific Monte Carlo (MC) simulations of radiation transport in anatomically accurate computational phantoms. Although accurate, MC simulations are computationally expensive, leading to a turnaround time in the order of core hours for simulating a single exam. This limits their clinical utility. The purpose of this study is to overcome this limitation by utilizing patient- and protocol-specific MC simulations to develop a comprehensive database of air-kerma-normalized organ dose coefficients for a virtual population of adult and pediatric patient models over an expanded set of exam protocols in DT for retrospective and prospective estimation of radiation dose in clinical tomosynthesis.

    Materials and methods

    A clinically representative virtual population of 14 patient models was used, with pediatric models (M and F) at ages 1, 5, 10, and 15 and adult patient models (M and F) with BMIs at 10th , 50th , and 90th percentiles of the US population. A GPU-based MC simulation framework was used to simulate organ doses in the patient models, incorporating the scanner-specific configuration of a clinical DT system (VolumeRad, GE Healthcare, Waukesha, WI) and an expanded set of exam protocols including 21 distinct acquisition techniques for imaging a variety of anatomical regions (head and neck, thorax, spine, abdomen, and knee). Organ dose coefficients (hn ) were estimated by normalizing organ dose estimates to air kerma at 70 cm (X70cm ) from the source in the scout view. The corresponding coefficients for projection radiography were approximated using organ doses estimated for the scout view. The organ dose coefficients were further used to compute air-kerma-normalized patient-specific effective dose coefficients (Kn ) for all combinations of patients and protocols, and a comparative analysis examining the variation of radiation burden across sex, age, and exam protocols in DT, and with projection radiography was performed.

    Results

    The database of organ dose coefficients (hn ) containing 294 distinct combinations of patients and exam protocols was developed and made publicly available. The values of Kn were observed to produce estimates of effective dose in agreement with prior studies and consistent with magnitudes expected for pediatric and adult patients across the different exam protocols, with head and neck regions exhibiting relatively lower and thorax and C-spine (apsc, apcs) regions relatively higher magnitudes. The ratios (r = Kn /Kn,rad ) quantifying the differences air-kerma-normalized patient-specific effective doses between DT and projection radiography were centered around 1.0 for all exam protocols, with the exception of protocols covering the knee region (pawk, patk).

    Conclusions

    This study developed a database of organ dose coefficients for a virtual population of 14 adult and pediatric XCAT patient models over a set of 21 exam protocols in DT. Using empirical measurements of air kerma in the clinic, these organ dose coefficients enable practical retrospective and prospective patient-specific radiation dosimetry. The computation of air-kerma-normalized patient-specific effective doses further enable the comparison of radiation burden to the patient populations between protocols and between imaging modalities (e.g., DT and projection radiography), as presented in this study. This article is protected by copyright. All rights reserved.
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    Enhanced CT simulation using realistic vascular flow dynamics
    (Medical Imaging 2024: Physics of Medical Imaging, 2024-04-01) Tanade, Cyrus; Felice, Nicholas; Samei, Ehsan; Randles, Amanda; Segars, W Paul
    As medical technologies advance with increasing speed, virtual imaging trials (VITs) are emerging as a crucial tool in the evaluation and optimization of new imaging techniques. Widely used in many VITs is the four-dimensional extended cardiac-torso (XCAT) phantom, a comprehensive computational model that accurately represents human anatomy and physiology. While the XCAT phantom offers a powerful tool for imaging research, it offers only a limited model of blood flow to compartmentalized organs, potentially limiting the realism and clinical applicability of contrast-enhanced scan simulations. This study bridges that gap by combining realistic CT simulation with an accurate model of blood flow dynamics to enable more realistic simulations of contrast-enhanced imaging. To achieve this, a validated one-dimensional blood flow simulator, HARVEY1D, was used to model flow throughout the vessels of the XCAT phantom. DukeSim, a validated CT simulation platform, was then modified to incorporate the resulting flow into its simulations, thus enabling the genera􀆟on of simulated CT scans reflective of real-world blood-based contrast-enhanced imaging scenarios. To demonstrate the utility of this pipeline in an initial application to cardiac imaging, three heart models were studied: a non-diseased model, a 50% stenosis model, and an 80% stenosis model. Three seconds of contrast propagation were tracked in each heart model, and CT scans corresponding to two timepoints were simulated. Results demonstrated that the presence of stenosis significantly impacted blood flow, with greater resistance to blood flow leading to altered flow patterns visible in the simulated CT images. This work showcases a pipeline that leverages both computational fluid dynamics and medical imaging simulations to enhance the realism of virtual imaging trials and facilitate the evaluation, optimization, and development of diagnostic tools for contrast-enhanced imaging.
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    Organ doses from CT localizer radiographs: Development, validation, and application of a Monte Carlo estimation technique
    (MEDICAL PHYSICS, 2019-11-01) Hoye, Jocelyn; Sharma, Shobhit; Zhang, Yakun; Fu, Wanyi; Ria, Francesco; Kapadia, Anuj; Segars, W Paul; Wilson, Joshua; Samei, Ehsan
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    Organ Doses from CT Localizer Radiographs: Development, Validation, and Application of a Monte Carlo Estimation Technique.
    (Medical physics, 2019-08-23) Hoye, Jocelyn; Sharma, Shobhit; Zhang, Yakun; Fu, Wanyi; Ria, Francesco; Kapadia, Anuj; Segars, W Paul; Wilson, Joshua; Samei, Ehsan
    PURPOSE:The purpose of this study was to simulate and validate organ doses from different CT localizer radiograph geometries using Monte Carlo methods for a population of patients. METHODS:A Monte Carlo method was developed to estimate organ doses from CT localizer radiographs using PENELOPE. The method was validated by comparing dosimetry estimates with measurements using an anthropomorphic phantom imbedded with thermoluminescent dosimeters (TLDs) scanned on a commercial CT system (Siemens SOMATOM Flash). The Monte Carlo simulation platform was then applied to conduct a population study with fifty-seven adult computational phantoms (XCAT). In the population study, clinically relevant chest localizer protocols were simulated with the x-ray tube in anterior-posterior (AP), right lateral, and PA positions. Mean organ doses and associated standard deviations (in mGy) were then estimated for all simulations. The obtained organ doses were studied as a function of patient chest diameter. Organ doses for breast and lung were compared across different views and represented as a percentage of organ doses from rotational CT scans. RESULTS:The validation study showed an agreement between the Monte Carlo and physical TLD measurements with a maximum percent difference of 15.5% and a mean difference of 3.5% across all organs. The XCAT population study showed that breast dose from AP localizers was the highest with a mean value of 0.24 mGy across patients, while the lung dose was relatively consistent across different localizer geometries. The organ dose estimates were found to vary across the patient population, partially explained by the changes in the patient chest diameter. The average effective dose was 0.18 mGy for AP, 0.09 mGy for lateral, and 0.08 mGy for PA localizer. CONCLUSION:A platform to estimate organ doses in CT localizer scans using Monte Carlo methods was implemented and validated based on comparison with physical dose measurements. The simulation platform was applied to a virtual patient population, where the localizer organ doses were found to range within 0.4-8.6% of corresponding organ doses for a typical CT scan, 0.2-3.3% of organ doses for a CT pulmonary angiography scan, and 1.1-20.8% of organ doses for a low dose lung cancer screening scan.