Technical Note: Model-based magnification/minification correction of patient size surrogates extracted from CT localizers

An in-house step-wedge phantom for the calibration of pixel values in CT localizer radiographs for water-equivalent diameter measurement

Introduction: To develop an in-house acrylic-based step-wedge phantom with several thickness configurations for calibrating computed tomography (CT) localizer radiographs in order to measure the water-equivalent diameter (Dw) and the size-specific dose estimate (SSDE).

Method: We developed an in-house step-wedge phantom using 3 mm thick acrylic, filled with water. The phantom had five steps with thicknesses of 6, 12, 18, 24, and 30 cm. The phantom was scanned using a 64-slice Siemens Definition AS CT scanner with tube currents of 50, 100, 150, 200, and 250 mA. The relationship between pixel value (PV) and water-equivalent thickness (tw) was obtained for the different step thicknesses. This was used to calibrate the CT localizer radiographs in order to measure Dw and SSDE. The results of Dw and SSDE from the radiographs were compared with those calculated from axial CT images.

Results: The relationship between PV and tw from CT localizer radiographs of the phantom step-wedge produced a linear relationship with R2 > 0.990. The linear relationships of the Dw and SSDE values obtained from CT localizer radiographs and axial CT images had R2 values > 0.94 with a statistical test of p-value > 0.05. The Dw difference between those from CT localizer radiographs and axial CT images was 3.7% and the SSDE difference between both was 4.3%.

Conclusion: We have successfully developed a step-wedge phantom to calibrate the relationship between PV and tw. Our phantom can be easily used to calibrate CT localizer radiographs in order to measure Dw and SSDE.

Impacts of Phantom Off-Center Positioning on CT Numbers and Dose Index CTDIv: An Evaluation of Two CT Scanners from GE

The purpose of this work is to evaluate the impacts of body off-center positioning on CT numbers and dose index CTDIv of two scanners from GE. HD750 and APEX scanners were used to acquire a PBU60 phantom of Kagaku and a 062M phantom of CIRS respectively. CT images were acquired at various off-center positions under automatic tube current modulation using various peak voltages. CTDIv were recorded for each of the acquisitions. An abdomen section of the PBU60 phantom was used for CT number analysis and tissue inserts of the 062M phantom were filled with water balloons to mimic the human abdomen. CT numbers of central regions of interests were averaged using the Fiji software. As phantoms were lifted above the iso-center, both CTDIv and CT numbers were increased for the HD750 scanner whilst they were approximately constant for the APEX scanner. The measured sizes of anterior-posterior projection images were also increased for both scanners whilst the sizes of lateral projection images were increased for the HD750 scanner but decreased for the APEX scanner. Off-center correction algorithms were implemented in the APEX scanner. Matching the X-ray projection center with the system's iso-center could improve the accuracy of CT imaging.

A comparison of automatic and manual compensation methods for the calculation of tube currents during off-centered patient positioning with a noise-based automatic exposure control system in computed tomography

Automatic exposure control (AEC) is used to optimize the X-ray tube output during computed tomography (CT) scans. However, calculation of the tube current by AEC can be affected when a patient is not aligned with the rotational center of the X-ray tube. An automatic couch height-positioning compensation mechanism provides a corrective function when the patient is off-center. In this study, we aimed to (a) evaluate the performance characteristics of the positioning compensation mechanism and (b) confirm whether our proposed compensation method can be properly applied to a noise-based AEC system even if the CT device is not equipped with a positioning compensation mechanism. An elliptical phantom was scanned at various table heights on systems without/with the positioning compensation mechanism. Expressions describing the offset from the gantry's isocenter and adjusted standard deviation settings were derived and used in our proposed compensation method. A phantom was scanned at various table heights with our proposed compensation method, and volume CT dose index (CTDI_vol) and image noise levels were obtained. An anthropomorphic chest phantom was also scanned using the proposed compensation method to verify its accuracy. When the positioning compensation mechanism was used, it yielded a constant CTDI_vol and image noise levels at various table heights tested. A comparison between our proposed method and the positioning compensation mechanism for both the elliptical and chest phantoms yielded similar CTDI_vol. Therefore, both automatic and manual positioning compensation methods are useful for avoiding AEC miscalculations in off-centered patient positioning cases.

Inadequate object positioning and improvement of automatic exposure control system calculations based on an empirical algorithm

When using automatic exposure control (AEC) systems in computed tomography (CT), miscalculation of tube current occurs when a patient is not aligned with the rotational center of the X-ray tube. A positioning compensation mechanism provides a corrective function when the patient is off-center; however, not all CT systems are equipped with this mechanism. AEC systems can broadly be divided into noise- and empirical-based. The authors studied empirical-based AEC systems to derive a compensation process to achieve an equivalent effect to that offered by the mechanism and to verify the accuracy of this process. A relational equation was derived to keep the tube current constant with variations in table height and quality reference milliampere-seconds (QRmAs), and this was adopted as the proposed compensation method. The radiation dose and image quality were evaluated for phantom imaging with and without the proposed compensation method using AEC and varying table heights. The output radiation dose and image quality were also evaluated for anthropomorphic chest phantom imaging to verify the compensatory effect of the proposed method. With the proposed compensation method, changes in the table height resulted in only small changes in the output radiation dose and noise level. Conversely, when the proposed compensation method was not used, changes in the table height resulted in widely varying output radiation dose and noise level. Imaging the anthropomorphic chest phantom with the proposed compensation method also yielded a stable output radiation dose.

[Calculation of water equivalent diameter based on anteroposterior localizer CT images]

ObjectiveTo explore a method for calculating water equivalent diameter (D_w) based on localizer CT images for calculation of the size specific dose estimates (SSDE).MethodGE Revolution CT and LightSpeed VCT were used to scan CT dose index phantoms 16 cm and 32 cm in diameter at the tube voltages of 80, 100 and 120 kV to obtain the axial image and anteroposterior localizer radiograph. According to the definition of CT Hounsfield unit, the axial images were used to calculate the conversion factors that convert the phantom thickness to water equivalent thickness. The gray value of the localizer radiograph and the water equivalent thickness were calibrated with a linear equation, and the parameters of the calibration were used to calculate the water equivalent thickness. The method was verified using 2 CT dose index phantoms and in 22 patients undergoing chest and abdominal CT examination.ResultComparison of the water equivalent diameter (D_w) based on the localizer radiograph and axial image of the 2 phantoms showed that the percentage difference between D_w from the axial images and from the localizer radiograph was below 3%. The trend of D_w variations with location in the two methods was sonsistent. The difference in D_w in intermediate region of interest between the axial image and the localizer radiograph from the 22 patients was below 6.6%. With the mean D_w in the ROI, the maximum percentage difference was 7.5%.ConclusionCalibration of the gray value of the localizer radiograph and the water equivalent thickness using the axial image and localizer radiograph of CT dose index phantoms allows quick calculation of the SSDE based on the parameters of calibration.

Estimating patient water equivalent diameter from CT localizer images - A longitudinal and multi-institutional study of the stability of calibration parameters

PURPOSE

Water equivalent diameter (WED) is a robust patient-size descriptor. Localizer-based WED estimation is less sensitive to truncation errors resulting from limited field of view, and produces WED estimates at different locations within one localizer radiograph, prior to the initiation of axial scans. This method is considered difficult to implement by the clinical community due to the necessary calibration between localizer pixel values (LPV) and attenuation, and the unknown stability of calibration results across scanners and over time. We investigated the stability of calibration results across 25 computed tomography (CT) scanners from three medical centers, and their stability over 3 ∼ 29 months for 14 of those scanners.

METHODS

Localizer and axial images of ACR and body computed tomography dose index phantoms were acquired, using routine clinical techniques (120 kV and lateral localizers) on each of the 25 CT scanners: 8 GE scanners (CT750HD, VCT, and Revolution), 8 Siemens scanners (Definition AS, Force, Flash, and Edge), 5 Canon scanners (Aquilion-One, Aquilion-Prime80, and Aquilion-64), and 4 Philips scanners (iCT 256, iQon, and Ingenuity). By associating axial images with the corresponding localizer lines, the relationship between the scaled water equivalent area (WEA) and averaged LPV were established through regression analysis.

RESULTS

Linear relationships between the scaled WEA and the averaged LPV were observed in all 25 CT scanners ( R 2 > 0.999 ). Calibration parameters were similar for CT scanners from the same vendor: the coefficients of variation (COV) were ≤ 1% in all four vendor groups for the calibration slope, and < 7% for the intercept. By analyzing the deviation of WED resulted from errors in the calibration slope or intercept alone, we derived the tolerance ranges for the slope or intercept for a given WED error level. The variation of slope and intercept from different CT scanners of the same vendor introduced <±2.5% error in the estimated WED for subjects of 20 and 30-cm WED. The calibration parameters remained stable over time, with the maximum deviations all within the boundary values that introduce ±2.5% error in the estimated WED for subjects of 20 and 30-cm WED.

CONCLUSIONS

The stability in calibration results among CT scanners of the same vendor and over time demonstrated the feasibility of implementing WED estimation for routine clinical use.

Method of determining geometric patient size surrogates using localizer images in CT

Purpose

Size‐specific dose estimates (SSDE) requires accurate estimates of patient size surrogates. AAPM Report 204 shows that the SSDE is the product of CTDIvol and a scaling factor, the normalized dose coefficient (NDC) which depends on patient size surrogates for CT axial images. However, SSDE can be determined from CT localizer prior to CT scanning. AAPM Report 220 charges that a magnification correction is needed for geometric patient size‐surrogates. In this study, we demonstrate a novel “model‐based” magnification correction on patient data.

Methods

573 patient scans obtained from a clinical CT system including 229 adult abdomen, 284 adult chest, 48 pediatric abdomen, and 12 pediatric chest exams. LAT and AP dimensions were extracted from CT localizers using a threshold extraction method (the ACR DIR). The model‐based magnification correction was applied to the AP and LAT dimensions extracted using the ACR DIR. NDC was calculated using the effective diameter for the ACR DIR only, the model‐based localizer‐based and axial‐based approaches. The LAT and AP dimensions were extracted from the “gold” standard CT axial scans. Outliers are defined as points outside the 95% confidence intervals and were analyzed.

Results

NDC estimates for the localizer‐based model‐based approach had an excellent correlation (R² = 0.92) with the gold standard approach. The effective diameter for ACR DIR and model‐based approaches are 8.0% and 1.0% greater than the gold standard respectively. Outliers were determined to be primarily patient truncation, with arms down or with devices. ACR DIR size extraction method fails for bariatric patients where the threshold is too high and some of their anatomy was included in the CT couch, and small patients due to the CT couch being included in the size measurement.

Conclusion

The model‐based magnification method gives an accurate estimate of patient size surrogates extracted from CT localizers that are needed for calculating NDC to achieve accurate SSDE.