Browsing by Author "Kapadia, Anuj"

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    Accuracy and Patient Dose in Neutron Stimulated Emission Computed Tomography for Diagnosis of Liver Iron Overload: Simulations in GEANT4
    (2007-08-13) Kapadia, Anuj
    Neutron stimulated emission computed tomography (NSECT) is being proposed as an experimental technique to diagnose iron overload in patients. Proof-of-concept experiments have suggested that NSECT may have potential to make a non-invasive diagnosis of iron overload in a clinical system. The technique's sensitivity to high concentrations of iron combined with tomographic acquisition ability gives it a unique advantage over other competing modalities. While early experiments have demonstrated the efficacy of detecting samples with high concentrations of iron, a tomography application for patient diagnosis has never been tested. As with any other tomography system, the performance of NSECT will depend greatly on the acquisition parameters that are used to scan the patient. In order to determine the best acquisition geometry for a clinical system, it is important to evaluate and understand the effects of varying each individual acquisition parameter on the accuracy of the reconstructed image. This research work proposes to use Monte-Carlo simulations to optimize a clinical NSECT system for iron overload diagnosis.Simulations of two NSECT systems have been designed in GEANT4, a spectroscopy system to detect uniform concentrations of iron in the liver, and a tomography system to detect non-uniform iron overload. Each system has been used to scan simulated samples of both disease models in humans to determine the best scanning strategy for each. The optimal scanning strategy is defined as the combination of parameters that provides maximum accuracy with minimum radiation dose. Evaluation of accuracy is performed through ROC analysis of the reconstructed spectrums and images. For the spectroscopy system, the optimal acquisition geometry is defined in terms of the number of neutrons required to detect a clinically relevant concentration of iron. For the tomography system, the optimal scanning strategy is defined in terms of the number of neutrons and the number of spatial and angular translation steps used during acquisition. Patient dose for each simulated system is calculated by measuring the energy deposited by the neutron beam in the liver and surrounding body tissue. Simulation results indicate that both scanning systems can detect wet iron concentrations of 5 mg/g or higher. Spectroscopic scanning with sufficient accuracy is possible with 1 million neutrons per scan, corresponding to a patient dose of 0.02 mSv. Tomographic scanning requires 8 angles that sample the image matrix at 1 cm projection intervals with 4 million neutrons per projection, which corresponds to a total body dose of 0.56 mSv. The research performed for this dissertation has two important outcomes. First, it demonstrates that NSECT has the clinical potential for iron overload diagnosis in patients. Second, it provides a validated simulation of the NSECT system which can be used to guide future development and experimental implementation of the technique.
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    Clinical Decision Making in CT: Risk Assessment Comparison Across 12 Risk Metrics in Patient Populations
    (Journal of Medical Physics, 2020-06-30) Ria, Francesco; Fu, wanyi; Hoye, Jocelyn; Segars, William; Kapadia, Anuj; Samei, Ehsan
    Purpose The Medical Physics 3.0 initiative aims to enhance direct physicist involvement in clinical decision making to improve patient care. In this involvement, it is crucial to achieve effective and patient-specific radiation risk assessment. CT risk characterization presents a variety of metrics, many of which used as radiation risk surrogates; some are related to the device output (CTDI), whereas others include patient organ risk-, age-, and gender-factors (Effective Dose, Risk Index). It is unclear how different metrics can accurately reflect the radiological risk. This study compared how twelve metrics characterize risk across CT patient populations to inform effective clinical decision making in radiology. Methods This IRB-approved study included 1394 adult CT examinations (abdominopelvic and chest). Organ doses were calculated using Monte Carlo methods. The following risk surrogate metrics were calculated: CTDIvol, DLP, SSDE, DLP-based Effective Dose (EDk), organ-dose-based ED (EDOD), dose to defining organ (stomach- and lungs-ODD), organ-dose-based Risk Index (RI), and 20 y.o. patient Risk Index (RIr). Furthermore, ODD,0, ED0, and RI0 were calculated for a reference patient (ICRP 110). Lastly, an adjusted ED (ED') was computed as the product of RI/RIr and EDOD. A linear regression was applied to assess each metric’s dependency to RI, assumed to be the closest patient risk surrogate. The normalized-slope (nS) and a Minimum Risk Detectability Index (MRDI=RMSE/slope) were calculated for each fit. Results The analysis reported significant differences between the metrics. ED’ showed the best concordance with RI in terms of nS and MRDI. Across all metrics and protocols, nS ranged between 0.37(SSDE) to 1.29(RI0); MRDI ranged between 39.11(EDk) to 1.10(ED’) cancers per 105 patients per 0.1Gy. Conclusion Radiation risk characterization in CT populations is strongly affected by the index used to describe it. When involved in clinical decisions, medical physicists should exercise care in ascribing an implicit risk to factors that do not closely reflect risk.
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    Clinical Decision Making in CT: Risk Assessment Comparison Across 12 Risk Metrics in Patient Populations
    (Journal of Medical Physics, 2020-06-30) Ria, Francesco; Fu, Wanyi; Hoye, Jocelyn; Segars, William; Kapadia, Anuj; Samei, Ehsan
    Purpose The Medical Physics 3.0 initiative aims to enhance direct physicist involvement in clinical decision making to improve patient care. In this involvement, it is crucial to achieve effective and patient-specific radiation risk assessment. CT risk characterization presents a variety of metrics, many of which used as radiation risk surrogates; some are related to the device output (CTDI), whereas others include patient organ risk-, age-, and gender-factors (Effective Dose, Risk Index). It is unclear how different metrics can accurately reflect the radiological risk. This study compared how twelve metrics characterize risk across CT patient populations to inform effective clinical decision making in radiology. Methods This IRB-approved study included 1394 adult CT examinations (abdominopelvic and chest). Organ doses were calculated using Monte Carlo methods. The following risk surrogate metrics were calculated: CTDIvol, DLP, SSDE, DLP-based Effective Dose (EDk), organ-dose-based ED (EDOD), dose to defining organ (stomach- and lungs-ODD), organ-dose-based Risk Index (RI), and 20 y.o. patient Risk Index (RIr). Furthermore, ODD,0, ED0, and RI0 were calculated for a reference patient (ICRP 110). Lastly, an adjusted ED (ED') was computed as the product of RI/RIr and EDOD. A linear regression was applied to assess each metric’s dependency to RI, assumed to be the closest patient risk surrogate. The normalized-slope (nS) and a Minimum Risk Detectability Index (MRDI=RMSE/slope) were calculated for each fit. Results The analysis reported significant differences between the metrics. ED’ showed the best concordance with RI in terms of nS and MRDI. Across all metrics and protocols, nS ranged between 0.37(SSDE) to 1.29(RI0); MRDI ranged between 39.11(EDk) to 1.10(ED’) cancers per 105 patients per 0.1Gy. Conclusion Radiation risk characterization in CT populations is strongly affected by the index used to describe it. When involved in clinical decisions, medical physicists 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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    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.