Xiaoyu Tian

Pediatric Chest and Abdominopelvic CT: Organ Dose Estimation Based on 42 Patient Models

PURPOSE To estimate organ dose from pediatric chest and abdominopelvic computed tomography (CT) examinations and evaluate the dependency of organ dose coefficients on patient size and CT scanner models. MATERIALS AND METHODS The institutional review board approved this HIPAA-compliant study and did not require informed patient consent. A validated Monte Carlo program was used to perform simulations in 42 pediatric patient models (age range, 0-16 years; weight range, 2-80 kg; 24 boys, 18 girls). Multidetector CT scanners were modeled on those from two commercial manufacturers (LightSpeed VCT, GE Healthcare, Waukesha, Wis; SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). Organ doses were estimated for each patient model for routine chest and abdominopelvic examinations and were normalized by volume CT dose index (CTDI(vol)). The relationships between CTDI(vol)-normalized organ dose coefficients and average patient diameters were evaluated across scanner models. RESULTS For organs within the image coverage, CTDI(vol)-normalized organ dose coefficients largely showed a strong exponential relationship with the average patient diameter (R(2) > 0.9). The average percentage differences between the two scanner models were generally within 10%. For distributed organs and organs on the periphery of or outside the image coverage, the differences were generally larger (average, 3%-32%) mainly because of the effect of overranging. CONCLUSION It is feasible to estimate patient-specific organ dose for a given examination with the knowledge of patient size and the CTDI(vol). These CTDI(vol)-normalized organ dose coefficients enable one to readily estimate patient-specific organ dose for pediatric patients in clinical settings. This dose information, and, as appropriate, attendant risk estimations, can provide more substantive information for the individual patient for both clinical and research applications and can yield more expansive information on dose profiles across patient populations within a practice.

Dose coefficients in pediatric and adult abdominopelvic CT based on 100 patient models.

Recent studies have shown the feasibility of estimating patient dose from a CT exam using CTDI(vol)-normalized-organ dose (denoted as h), DLP-normalized-effective dose (denoted as k), and DLP-normalized-risk index (denoted as q). However, previous studies were limited to a small number of phantom models. The purpose of this work was to provide dose coefficients (h, k, and q) across a large number of computational models covering a broad range of patient anatomy, age, size percentile, and gender. The study consisted of 100 patient computer models (age range, 0 to 78 y.o.; weight range, 2-180 kg) including 42 pediatric models (age range, 0 to 16 y.o.; weight range, 2-80 kg) and 58 adult models (age range, 18 to 78 y.o.; weight range, 57-180 kg). Multi-detector array CT scanners from two commercial manufacturers (LightSpeed VCT, GE Healthcare; SOMATOM Definition Flash, Siemens Healthcare) were included. A previously-validated Monte Carlo program was used to simulate organ dose for each patient model and each scanner, from which h, k, and q were derived. The relationships between h, k, and q and patient characteristics (size, age, and gender) were ascertained. The differences in conversion coefficients across the scanners were further characterized. CTDI(vol)-normalized-organ dose (h) showed an exponential decrease with increasing patient size. For organs within the image coverage, the average differences of h across scanners were less than 15%. That value increased to 29% for organs on the periphery or outside the image coverage, and to 8% for distributed organs, respectively. The DLP-normalized-effective dose (k) decreased exponentially with increasing patient size. For a given gender, the DLP-normalized-risk index (q) showed an exponential decrease with both increasing patient size and patient age. The average differences in k and q across scanners were 8% and 10%, respectively. This study demonstrated that the knowledge of patient information and CTDIvol/DLP values may be used to estimate organ dose, effective dose, and risk index in abdominopelvic CT based on the coefficients derived from a large population of pediatric and adult patients.

Accurate assessment and prediction of noise in clinical CT images

PURPOSE The objectives of this study were (a) to devise a technique for measuring quantum noise in clinical body computed tomography (CT) images and (b) to develop a model for predicting that noise with high accuracy. METHODS The study included 83 clinical image sets at two dose levels (clinical and 50% reduced dose levels). The quantum noise in clinical images was measured by subtracting sequential slices and filtering out edges. Noise was then measured in the resultant uniform area. The noise measurement technique was validated using 17 clinical image cases and a turkey phantom. With a validated method to measure noise in clinical images, this noise was predicted by establishing the correlation between water-equivalent diameter (Dw) and noise in a variable-sized phantom and ascribing a noise level to the patient based on Dw estimated from CT image. The accuracy of this prediction model was validated using 66 clinical image sets. RESULTS The error in noise measurement was within 1.5 HU across two reconstruction algorithms. In terms of noise prediction, across the 83 clinical image sets, the average discrepancies between predicted and measured noise were 6.9% and 6.6% for adaptive statistical iterative reconstruction and filtered back projection reconstruction, respectively. CONCLUSIONS This study proposed a practically applicable method to assess quantum noise in clinical images. The image-based measurement technique enables automatic quality control monitoring of image noise in clinical practice. Further, a phantom-based model can accurately predict quantum noise level in patient images. The prediction model can be used to quantitatively optimize individual protocol to achieve targeted noise level in clinical images.

CT Breast Dose Reduction with the Use of Breast Positioning and Organ-Based Tube Current Modulation

Purpose: This study aimed to investigate the breast dose reduction potential of a breast‐positioning (BP) technique for thoracic CT examinations with organ‐based tube current modulation (OTCM). Methods: This study included 13 female anthropomorphic computational phantoms (XCAT, age range: 27–65 y.o., weight range: 52–105.8 kg). Each phantom was modified to simulate three breast sizes in standard supine geometry. The modeled breasts were then morphed to emulate BP that constrained the majority of the breast tissue inside the 120° anterior tube current (mA) reduction zone. The OTCM mA value was modeled using a ray‐tracing program, which reduced the mA to 20% in the anterior region with a corresponding increase to the posterior region. The organ doses were estimated by a validated Monte Carlo program for a typical clinical CT system (SOMATOM Definition Flash, Siemens Healthcare). The simulated organ doses and organ doses normalized by CTDIvol were used to compare three CT protocols: attenuation‐based tube current modulation (ATCM), OTCM, and OTCM with BP (OTCMBP). Results: On average, compared to ATCM, OTCM reduced breast dose by 19.3 ± 4.5%, whereas OTCMBP reduced breast dose by 38.6 ± 8.1% (an additional 23.8 ± 9.4%). The dose saving of OTCMBP was more significant for larger breasts (on average 33, 38, and 44% reduction for 0.5, 1, and 2 kg breasts, respectively). Compared to ATCM, OTCMBP also reduced thymus and heart dose by 15.1 ± 7.4% and 15.9 ± 6.2% respectively. Conclusions: In thoracic CT examinations, OTCM with a breast‐positioning technique can markedly reduce unnecessary exposure to radiosensitive organs in anterior chest wall, specifically breast tissue. The breast dose reduction is more notable for women with larger breasts.

Projection-based dose metric: accuracy testing and applications for CT design

The purpose of this study was to develop and validate a projection-based dose metric that enables computationally efficient dose estimation. The two physical quantities determining dose, absorbed energy and mass, were estimated in projection space. The absorbed energy was estimated using the difference between the imparted energy and detected energy. The mass was estimated using the area under the attenuation profile. A series of phantom simulations were conducted to test the metric’s applicability for multi-material phantoms, different kVp settings, and bowtie filters. Projection-based dose estimates were benchmarked against results from the Monte Carlo (MC) simulation. The projection-based dose metric shows a strong linear correlation with MC dose estimates (R2 > 0.96). The prediction errors for projection-based dose metric are below 14%. This study demonstrates a computationally efficient and relatively accurate dose estimation method based on the projection data. It further suggests the possibility to achieve real-time and patient-specific dose optimization when applied prior to a CT scan.

Prospective optimization of CT under tube current modulation: I. organ dose

In an environment in which computed tomography (CT) has become an indispensable diagnostic tool employed with great frequency, dose concerns at the population level have become a subject of public attention. In that regard, optimizing radiation dose has become a core problem to the CT community. As a fundamental step to optimize radiation dose, it is crucial to effectively quantify radiation dose for a given CT exam. Such dose estimates need to be patient-specific to reflect individual radiation burden. It further needs to be prospective so that the scanning parameters can be dynamically adjusted before the scan is performed. The purpose of this study was to prospectively estimate organ dose in abdominopelvic CT exams under tube current modulation (TCM). CTDIvol-normalized-organ dose coefficients ( hfixed ) for fixed tube current were first estimated using a validated Monte Carlo simulation program and 58 computational phantoms. To account for the effect of TCM scheme, a weighted CTDIvol was computed for each organ based on the tube current modulation profile. The organ dose was predicted by multiplying the weighted CTDIvol with the organ dose coefficients ( hfixed ). To quantify prediction accuracy, each predicted organ dose was compared with organ dose simulated from Monte Carlo program with TCM profile explicitly modeled. The predicted organ dose showed good agreement with simulated organ dose across all organs and modulation strengths. For an average CTDIvol of a CT exam of 10 mGy, the absolute median error across all organs were 0.64 mGy (-0.21 and 0.97 for 25th and 75th percentiles, respectively). The percentage differences (normalized by CTDIvol of the exam) were within 15%. This study developed a quantitative model to predict organ dose under clinical abdominopelvic scans. Such information may aid in the optimization of CT protocols.

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

Abstract. 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.

Estimation of breast dose saving potential using a breast positioning technique for organ-based tube current modulated CT

In thoracic CT, organ-based tube current modulation (OTCM) reduces breast dose by lowering the tube current in the 120° anterior dose reduction zone of patients. However, in practice the breasts usually expand to an angle larger than the dose reduction zone. This work aims to simulate a breast positioning technique (BPT) to constrain the breast tissue to within the dose reduction zone for OTCM and to evaluate the corresponding potential reduction in breast dose. Thirteen female anthropomorphic computational phantoms were studied (age range: 27-65 y.o., weight range: 52-105.8 kg). Each phantom was modeled in the supine position with and without application of the BPT. Attenuation-based tube current (ATCM, reference mA) was generated by a ray-tracing program, taking into account the patient attenuation change in the longitudinal and angular plane (CAREDose4D, Siemens Healthcare). OTCM was generated by reducing the mA to 20% between ± 60° anterior of the patient and increasing the mA in the remaining projections correspondingly (X-CARE, Siemens Healthcare) to maintain the mean tube current. Breast tissue dose was estimated using a validated Monte Carlo program for a commercial scanner (SOMATOM Definition Flash, Siemens Healthcare). Compared to standard tube current modulation, breast dose was significantly reduced using OTCM by 19.8±4.7%. With the BPT, breast dose was reduced by an additional 20.4±6.5% to 37.1±6.9%, using the same CTDIvol. BPT was more effective for phantoms simulating women with larger breasts with the average breast dose reduction of 30.2%, 39.2%, and 49.2% from OTCMBP to ATCM, using the same CTDIvol for phantoms with 0.5, 1.5, and 2.5 kg breasts, respectively. This study shows that a specially designed BPT improves the effectiveness of OTCM.

Organ dose conversion coefficients for tube current modulated CT protocols for an adult population

In computed tomography (CT), patient-specific organ dose can be estimated using pre-calculated organ dose conversion coefficients (organ dose normalized by CTDIvol, h factor) database, taking into account patient size and scan coverage. The conversion coefficients have been previously estimated for routine body protocol classes, grouped by scan coverage, across an adult population for fixed tube current modulated CT. The coefficients, however, do not include the widely utilized tube current (mA) modulation scheme, which significantly impacts organ dose. This study aims to extend the h factors and the corresponding dose length product (DLP) to create effective dose conversion coefficients (k factor) database incorporating various tube current modulation strengths. Fifty-eight extended cardiac-torso (XCAT) phantoms were included in this study representing population anatomy variation in clinical practice. Four mA profiles, representing weak to strong mA dependency on body attenuation, were generated for each phantom and protocol class. A validated Monte Carlo program was used to simulate the organ dose. The organ dose and effective dose was further normalized by CTDIvol and DLP to derive the h factors and k factors, respectively. The h factors and k factors were summarized in an exponential regression model as a function of body size. Such a population-based mathematical model can provide a comprehensive organ dose estimation given body size and CTDIvol. The model was integrated into an iPhone app XCATdose version 2, enhancing the 1st version based upon fixed tube current modulation. With the organ dose calculator, physicists, physicians, and patients can conveniently estimate organ dose.

An automated technique for estimating patient-specific regional imparted energy and dose in TCM CT exams

Currently computed tomography (CT) dosimetry relies on CT dose index (CTDI) and size specific dose estimates (SSDE). Organ dose is a better metric of radiation burden. However, organ dose estimation requires precise knowledge of organ locations. Regional imparted energy and dose can also be used to quantify radiation burden. Estimating the imparted energy from CT exams is beneficial in that it does not require precise estimates of the organ size or location. This work investigated an automated technique for retrospectively estimating the imparted energy from chest and abdominopelvic tube current modulated (TCM) CT exams. Monte Carlo simulations of chest and abdominopelvic TCM CT examinations across various tube potentials and TCM strengths were performed on 58 adult computational extended cardiac-torso (XCAT) phantoms to develop relationships between scanned mass and imparted energy normalized by dose length product (DLP). An automated algorithm for calculating the scanned patient volume was further developed using an open source mesh generation toolbox. The scanned patient volume was then used to estimate the scanned mass accounting for diverse density within the scan region. The scanned mass and DLP from the exam were used to estimate the imparted energy to the patient using the knowledgebase developed from the Monte Carlo simulations. Patientspecific imparted energy estimates were made from 20 chest and 20 abdominopelvic clinical CT exams. The average imparted energy was 274 ± 141 mJ and 681 ± 376 mJ for the chest and abdominopelvic exams, respectively. This method can be used to estimate the regional imparted energy and/or regional dose in chest and abdominopelvic TCM CT exams across clinical operations.