Automated size-specific CT dose monitoring program: assessing variability in CT dose

Radiation dose management system in computed tomography procedures: a systematic review

A systematic literature review was carried out to explore articles that reported the use of radiation dose management systems (RDMSs) in computed tomography (CT). The preferred reporting items for systematic review and meta-analysis flow chart were used to screen articles in PubMed, EBSCOhost, Web of Science, SCOPUS and Cochrane Library. A total of 1041 articles were retrieved and screened. After evaluation against criteria, 38 articles were selected and synthesised narratively. The results revealed that several RDMSs have been used in CT. The review also indicated that the use of RDMSs has promoted the implementation of diagnostic reference levels for dose optimisation. A RDMS, such as DoseWatch, is associated with compatibility challenges and failure in data transmission, while manual RDMSs are cumbersome and prone to data entry errors. Thus, a robust automated RDMS that is compatible with the different CT systems would provide efficient CT dose management.

Effectiveness of body size stratification for patient exposure optimization in Computed Tomography

PURPOSE

To establish size-dependent DRL and to estimate the effectiveness of the size-dependent DRLs over size-independent DRLs for a CT exposure optimization process.

METHODS

The study included 16,933 adult CT body examinations of the most common CT protocols. Acquisitions were included following an image quality assessment. Patients were grouped into five different classes by means of the water equivalent diameter (D_w): 21 ≤ D_w < 25, 25 ≤ D_w < 29, 29 ≤ D_w < 33,33 ≤ D_w < 37 (in cm). CTDI_vol, DLP, DLP_tot. and SSDE median values were provided both for the sample as a whole (size-independent approach) and for each D_w class (size-dependent approach). The performance of the two approaches in classifying sub-optimal examinations was evaluated through the confusion matrix and Matthews Correlation Coefficient (MCC) metric. The 75th percentile of the CTDI_vol distribution was arbitrarily chosen as a threshold level above which the acquisitions are considered sub-optimal.

RESULTS

CTDI_vol, DLP, DLP_tot and SSDE typical values (median values) are statistically different across D_w groups. The confusion matrix analysis suggests that size-independent DRL could not mark potential suboptimal protocols for small and large patients. The agreement between the size-dependent and size-independent methods is strong only for the most populous classes (MCC > 0.7). For small and large patients size-independent approach fails to identify as sub-optimal around 20 % of the acquisition (MCC≪0.2).

CONCLUSIONS

It was proven by means of the confusion matrix and MCC metric that stratifying DRLs by patient size, size-dependent DRL can be a powerful strategy in order to improve the dose optimization process shown that a size-independent DRL fails to identify sub-optimal examinations for small and large patients.

The Impact of Data Management on the Achievable Dose and Efficiency of Computed Tomography During the COVID-19 Era: A Facility-Based Ambispective Study

Purpose

This study primarily aimed to evaluate the effectiveness of computational data management and analytical software for establishing departmental diagnostic reference levels (DRLs) for computed tomography (CT) scanning in clinical settings, and monitor achievable doses (ADs) for CT imaging, particularly during the coronavirus disease 2019 (COVID-19) era. Secondarily, it aimed to correlate these standards with national and international benchmarks.

Patients and Methods

This ambidirectional cohort study enrolled 4668 patients (6419 CT-based examinations) who visited King Fahd Hospital of the University from May 25, 2021, to November 4, 2021. Participants' demographic data were acquired from their electronic medical charts, in addition to all corresponding CT-dose determinant parameters. The study was divided into two phases (pre- and post-data management) based on the implementation of digital data management software.

Results

In both phases of the study, the size-specific dose estimate (SSDE) was the most significant confounder of dose determination compared to the dose-length product (DLP) and computed tomography dose index (CTDI) (P = 0.003). The head was the most frequently imaged body region (pre-implementation, 1051 examinations [35.1%]; post-implementation, 1071 examinations [31.3%]; P = 0.001), followed by the abdominal region (pre-implementation, 616 examinations [20.6%]; post-implementation, 256 examinations [7.48%]; P = 0.001). Based on the SSDE, DLP, and volume CTDI, the average per-section radiation exposure among organ-based scanning type was highest for the lumbar spine during the pre- and post-implementation periods.

Conclusion

Data management software enabled the establishment of DRLs and reduction of ADs in CT examinations, which consequently improved key performance indicators, despite the ergonomic complexities of COVID-19. Institutions are encouraged to apply DRLs and ADs via automatic systems that monitor patient dose indices to evaluate aggregate results.

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.

Evaluation of the Correction Methods Using Age and BMI for Estimating CT Organ Dose Using a Radiophotoluminescence Glass Dosimeter and a Monte Carlo-based Dose Calculator

ABSTRACT

The size-specific dose estimates (SSDE) have been recommended to replace the volume computed tomography dose index (CTDIvol) because it takes patient size into account. On the other hand, organ dose is thought to be a more appropriate quantity in the radiation protection field due to its correlation with radiation risk. The web-based computed tomography (CT) dose calculator WAZA-ARIv2 only offers organ doses for adults with four different body shapes and for children with five different ages. Since the American Association of Physicists in Medicine (AAPM) offers the conversion factors for SSDE and the correlation of SSDE with organ dose has been demonstrated, implementation of the conversion table might improve the accuracy of WAZA-ARIv2. This study aimed to evaluate a body mass index (BMI)-based and age-based correction method for estimation of the organ dose by using a radiophotoluminescence dosimeter (RGD), an anthropomorphic phantom, and the dose calculator WAZA-ARIv2. RGDs were individually calibrated by using an ISOVOLT TITAN-320 x-ray generator. The ratio of the SSDE conversion factors (CFSSDE) was used as the comparison index. For the BMI-based correction method, the ratio of CFSSDE values for the adult phantoms was expected to be 1.065, and the average ratio of the organ doses for the adult phantoms was 1.163 ± 0.169. For the age-based correction method, the ratio of CFSSDE value for 5- and 10-y-old pediatric phantoms was expected to be 0.889, and the ratios of the organ doses were 0.866 ± 0.024 and 0.909 ± 0.047 for the WAZA-ARIv2 dosimetry system and RGD dosimetry system, respectively. In conclusion, both evaluations of the experimental results showed the consistency between WAZA-ARIv2 and the SSDE conversion factor table. Moreover, the importance of taking the measurement position into account when applying the mass attenuation coefficient was demonstrated according to this study.

U.S. Diagnostic Reference Levels and Achievable Doses for 10 Pediatric CT Examinations

Background Diagnostic reference levels (DRLs) and achievable doses (ADs) were developed for the 10 most commonly performed pediatric CT examinations in the United States using the American College of Radiology Dose Index Registry. Purpose To develop robust, current, national DRLs and ADs for the 10 most commonly performed pediatric CT examinations as a function of patient age and size. Materials and Methods Data on 10 pediatric (ie, patients aged 18 years and younger) CT examinations performed between 2016 and 2020 at 1625 facilities were analyzed. For head and neck examinations, dose indexes were analyzed based on patient age; for body examinations, dose indexes were analyzed for patient age and effective diameter. Data from 1 543 535 examinations provided medians for AD and 75th percentiles for DRLs for volume CT dose index (CTDI_vol), dose-length product (DLP), and size-specific dose estimate (SSDE). Results Of all facilities analyzed, 66% of the facilities (1068 of 1625) were community hospitals, 16% (264 of 1625) were freestanding centers, 9.5% (154 of 1625) were academic facilities, and 3.5% (57 of 1625) were dedicated children's hospitals. Fifty-two percent of the patients (798 577 of 1 543 535) were boys, and 48% (744 958 of 1 543 535) were girls. The median age of patients was 14 years (boys, 13 years; girls, 15 years). The head was the most frequent anatomy examined with CT (876 655 of 1 543 535 examinations [57%]). For head without contrast material CT examinations, the age-based CTDI_vol AD ranged from 19 to 46 mGy, and DRL ranged from 23 to 55 mGy, with both AD and DRL increasing with age. For body examinations, DRLs and ADs for size-based CTDI_vol, SSDE, and DLP increased consistently with the patient's effective diameter. Conclusion Diagnostic reference levels and achievable doses as a function of patient age and effective diameter were developed for the 10 most commonly performed CT pediatric examinations using American College of Radiology Dose Index Registry data. These benchmarks can guide CT facilities in adjusting pediatric CT protocols and resultant doses for their patients. © RSNA, 2021 An earlier incorrect version appeared online. This article was corrected on October 29, 2021.

An Improved Method of Automated Noise Measurement System in CT Images

Background:

It is necessary to have an automated noise measurement system working accurately to optimize dose in computerized tomography (CT) examinations.

Objective:

This study aims to develop an algorithm to automate noise measurement that can be implemented in CT images of all body regions.

Materials and Methods:

In this retrospective study, our automated noise measurement method consists of three steps as follows: the first is segmenting the image of the patient. The second is developing a standard deviation (SD) map by calculating the SD value for each pixel with a sliding window operation. The third step is estimating the noise as the smallest SD from the SD map. The proposed method was applied to the images of a homogenous phantom and a full body adult anthropomorphic phantom, and retrospectively applied to 27 abdominal images of patients.

Results:

For a homogeneous phantom, the noises calculated using our proposed and previous algorithms have a linear correlation with R² = 0.997. It is found that the noise magnitude closely follows the magnitude of the water equivalent diameter (D_w) in all body regions. The proposed algorithm is able to distinguish the noise magnitude due to variations in tube currents and different noise suppression techniques such as strong, standard, mild, and weak ones in a reconstructed image using the AIDR 3D algorithm.

Conclusion:

An automated noise calculation has been proposed and successfully implemented in all body regions. It is not only accurate and easy to implement but also not influenced by the subjectivity of user.

Patient-based Performance Assessment for Pediatric Abdominal CT: An Automated Monitoring System Based on Lesion Detectability and Radiation Dose

RATIONALE AND OBJECTIVE

To deploy an automated tool for evaluating pediatric body computed tomography (CT) performance utilizing metrics of radiation dose and image quality for the task of liver lesion detection.

MATERIALS AND METHODS

This IRB approved retrospective investigation used 507 IV-contrast-enhanced abdominopelvic CT scans of pediatric patients (<18 years) between June 2014 and November 2017 acquired on three scanner models from two manufacturers. The scans were evaluated in terms of radiation metrics (CTDI_vol, DLP, and SSDE) as well as task-based performance based on the clinical task of detecting a 5 mm liver lesion with a 10 HU attenuation difference from background liver. An informatics algorithm extracted a previously-validated quantitative detectability index (d') from each case reflective of the likelihood of detecting a liver lesion. The results were analyzed in terms of the relationship between d' and radiation dose metrics.

RESULTS

There was minimal SSDE variability by age. Median SSDE at 100 kV on one scanner model was 5.2 mGy (5.0-5.4 mGy interquartile range). However, when assessing image quality by applying d', the age groups separated such that the younger patients had higher d' values than older patients. Similar trends were seen in all scanners.

CONCLUSIONS

An automated method to assess clinical image quality for pediatric CT provided a metric of image quality that varied as expected across ages (i.e., higher quality for younger patients). This tool affords the establishment of a quality reference level that, in addition to dose estimations currently available, would allow for enhanced assessment (e.g., facilitated audit) of CT imaging performance.

Machine learning for the prediction of pseudorealistic pediatric abdominal phantoms for radiation dose reconstruction

Purpose: Current phantoms used for the dose reconstruction of long-term childhood cancer survivors lack individualization. We design a method to predict highly individualized abdominal three-dimensional (3-D) phantoms automatically. Approach: We train machine learning (ML) models to map (2-D) patient features to 3-D organ-at-risk (OAR) metrics upon a database of 60 pediatric abdominal computed tomographies with liver and spleen segmentations. Next, we use the models in an automatic pipeline that outputs a personalized phantom given the patient's features, by assembling 3-D imaging from the database. A step to improve phantom realism (i.e., avoid OAR overlap) is included. We compare five ML algorithms, in terms of predicting OAR left-right (LR), anterior-posterior (AP), inferior-superior (IS) positions, and surface Dice-Sørensen coefficient (sDSC). Furthermore, two existing human-designed phantom construction criteria and two additional control methods are investigated for comparison. Results: Different ML algorithms result in similar test mean absolute errors: ∼ 8    mm for liver LR, IS, and spleen AP, IS; ∼ 5    mm for liver AP and spleen LR; ∼ 80 % for abdomen sDSC; and ∼ 60 % to 65% for liver and spleen sDSC. One ML algorithm (GP-GOMEA) significantly performs the best for 6/9 metrics. The control methods and the human-designed criteria in particular perform generally worse, sometimes substantially ( + 5 - mm error for spleen IS, - 10 % sDSC for liver). The automatic step to improve realism generally results in limited metric accuracy loss, but fails in one case (out of 60). Conclusion: Our ML-based pipeline leads to phantoms that are significantly and substantially more individualized than currently used human-designed criteria.

Technical Note: Validation of TG 233 phantom methodology to characterize noise and dose in patient CT data

PURPOSE

Phantoms are useful tools in diagnostic CT, but practical limitations reduce phantoms to being only a limited patient surrogate. Furthermore, a phantom with a single cross sectional area cannot be used to evaluate scanner performance in modern CT scanners that use dose reduction techniques such as automated tube current modulation (ATCM) and iterative reconstruction (IR) algorithms to adapt x-ray flux to patient size, reduce radiation dose, and achieve uniform image noise. A new multisized phantom (Mercury Phantom, MP) has been introduced, representing multiple diameters. This work aimed to ascertain if measurements from MP can predict radiation dose and image noise in clinical CT images to prospectively inform protocol design.

METHODS

The adult MP design included four different physical diameters (18.5, 23.0, 30.0, and 37.0 cm) representing a range of patient sizes. The study included 1457 examinations performed on two scanner models from two vendors, and two clinical protocols (abdominopelvic with and chest without contrast). Attenuating diameter, radiation dose, and noise magnitude (average pixel standard deviation in uniform image) was automatically estimated in patients and in the MP using a previously validated algorithm. An exponential fit of CTDI_vol and noise as a function of size was applied to patients and MP data. Lastly, the fit equations from the phantom data were used to fit the patient data. In each patient distribution fit, the normalized root mean square error (nRMSE) values were calculated in the residuals' plots as a metric to indicate how well the phantom data can predict dose and noise in clinical operations as a function of size.

RESULTS

For dose across patient size distributions, the difference between nRMSE from patient fit and MP model data prediction ranged between 0.6% and 2.0% (mean 1.2%). For noise across patient size distributions, the nRMSE difference ranged between 0.1% and 4.7% (mean 1.4%).

CONCLUSIONS

The Mercury Phantom provided a close prediction of radiation dose and image noise in clinical patient images. By assessing dose and image quality in a phantom with multiple sizes, protocol parameters can be designed and optimized per patient size in a highly constrained setup to predict clinical scanner and ATCM system performance.

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.

Assessment of patient dose and noise level of clinical CT images: automated measurements

We investigated comparisons between patient dose and noise in pelvic, abdominal, thoracic and head CT images using an automatic method. 113 patient images (37 pelvis, 34 abdominal, 25 thoracic, and 17 head examinations) were retrospectively and automatically examined in this study. Water-equivalent diameter (Dw), size-specific dose estimates (SSDE) and noise were automatically calculated from the center slice for every patient image. The Dw was calculated based on auto-contouring of the patients' edges, and the SSDE was calculated as the product of the volume CT dose index (CTDIvol) extracted from the Digital Imaging and Communications in Medicine (DICOM) header and the size conversion factor based on the Dw obtained from AAPM 204. The noise was automatically measured as a minimum standard deviation in the map of standard deviations. A square region of interest of about 1 cm² was used in the automated noise measurement. The SSDE values for the pelvis, abdomen, thorax, and head were 21.8 ± 7.3 mGy, 22.0 ± 4.5 mGy, 21.5 ± 4.7 mGy, and 65.1 ± 1.7 mGy, respectively. The SSDEs for the pelvis, abdomen, and thorax increased linearly with increasing Dw, and for the head with constant tube current, the SSDE decreased with increasing Dw. The noise in the pelvis, abdomen, thorax, and head were 5.9 ± 1.5 HU, 5.2 ± 1.4 HU, 4.9 ± 0.8 HU and 3.9 ± 0.2 HU, respectively. The noise levels for the pelvis, abdomen, and thorax of the patients were relatively constant with Dw because of tube current modulation. The noise in the head image was also relatively constant because Dw variations in the head are very small. The automated approach provides a convenient and objective tool for dose optimizations.

Can Patient's Body Weight Represent Body Diameter for Pediatric Size-Specific Dose Estimate in Thoracic and Abdominal Computed Tomography?

Objective

The objective of the study was to determine whether body weight (BW) can be substituted for body diameters to calculate size-specific dose estimate (SSDE) in the children.

Materials and Methods

A total of 196 torso computed tomography (CT) studies were retrospectively reviewed. Anteroposterior diameter (D_AP) and lateral diameter (D_lat) were measured, and D_AP+D_lat, effective diameter, SSDE diameter and SSDE_BW were calculated. Correlation coefficients among body diameters, all SSDE types and percentage changes between CT dose index volumes and SSDEs were analyzed by BW and age subgroups.

Results

Overall BW was more strongly correlated with body diameter (r = 0.919-0.960, P < 0.001) than was overall age (r = 0.852-0.898, P < 0.001). The relationship between CT dose index volume and each of the SSDE types (r = 0.934-0.953, P < 0.001), between SSDE_BW and all SSDE diameters (r = 0.934-0.953, P < 0.001), and among SSDE diameters (r = 0.950-0.989, P < 0.001) overall had strong correlations with statistical significance. The lowest magnitude difference was SSDE_BW-SSDE_eff.

Conclusion

BW can be used instead of body diameter to calculate all SSDE types, with our suggested best accuracy for SSDE_eff and the least variation in age < four years and BW < 20 kg.

Key Messages

Size-specific dose estimate (SSDE) is a new and accurate dose-estimating parameter for the individual patient which is based on the actual size or body diameter of the patient. BW can be an important alternative for all body diameters to estimate size-specific dose or calculate SSDE in children.

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.

Coronary CT angiography radiation dose trends: A 10-year analysis to develop institutional diagnostic reference levels

PURPOSE

To develop institutional diagnostic reference levels (IDRL) for coronary CT angiography (CCTA) according to patient size by analyzing radiation dose changes over the past 10 years.

MATERIALS AND METHODS

This IRB approved retrospective investigation analyzed radiation dose data from CCTA between 2007 and 2016 at our institution. Annual trends in radiation dose were described for each scanner type and scanning mode. Radiation levels were analyzed for normorhythmic patients, patients with prior coronary artery bypass grafting (CABG), arrhythmia, and according to patient size and tube voltage. Median, and quartile values for volume CT dose index (CTDIvol), dose-length product (DLP), and size-specific dose estimate (SSDE) were calculated. Wilcoxon rank-sum test and Kruskal Wallis test were performed to assess the significance of quantitative data.

RESULTS

35,375 examinations from 33,317 patients (median age, 58 [50-66] years; male patients, 21,087 [58.7%]) were analyzed. CTDIvol, DLP, and SSDE significantly decreased by 9.0%, 30.8%, and 40.1% (all P < 0.05) for all examinations, respectively. All radiation dose metrics progressively decreased across scanning modes (especially retrospectively ECG-gated spiral and prospectively ECG-triggered high-pitch spiral acquisition mode), but did not significantly change across scanners in the last 6 years. CTDIvol and DLP increased with patient size when water-equivalent diameters were >19 cm for normorhythmic and CABG patients. In arrhythmic patients, CTDIvol increased progressively with water-equivalent diameters across all groups.

CONCLUSION

CCTA radiation dose has progressively decreased in the past decade except in patients with prior CABG and arrhythmia. Size-specific IDRLs may optimize radiation utilization in these patients going forward.

Radiation Dose for Pediatric CT: Comparison of Pediatric versus Adult Imaging Facilities

Background The American College of Radiology Dose Index Registry for CT enables evaluation of radiation dose as a function of patient characteristics and examination type. The hypothesis of this study was that academic pediatric CT facilities have optimized CT protocols that may result in a lower and less variable radiation dose in children. Materials and Methods A retrospective study of doses (mean patient age, 12 years; age range, 0-21 years) was performed by using data from the National Radiology Data Registry (year range, 2016-2017) (n = 239 622). Three examination types were evaluated: brain without contrast enhancement, chest without contrast enhancement, and abdomen-pelvis with intravenous contrast enhancement. Three dose indexes-volume CT dose index (CTDI_vol), size-specific dose estimate (SSDE), and dose-length product (DLP)-were analyzed by using six different size groups. The unequal variance t test and the F test were used to compare mean dose and variances, respectively, at academic pediatric facilities with those at other facility types for each size category. The Bonferroni-Holm correction factor was applied to account for the multiple comparisons. Results Pediatric radiation dose in academic pediatric facilities was significantly lower, with smaller variance for all brain, 42 of 54 (78%) chest, and 48 of 54 (89%) abdomen-pelvis examinations across all six size groups, three dose descriptors, and when compared with that at the other three facilities. For example, abdomen-pelvis SSDE for the 14.5-18-cm size group was 3.6, 5.4, 5.5, and 8.3 mGy, respectively, for academic pediatric, nonacademic pediatric, academic adult, and nonacademic adult facilities (SSDE mean and variance P < .001). Mean SSDE for the smallest patients in nonacademic adult facilities was 51% (6.1 vs 11.9 mGy) of the facility's adult dose. Conclusion Academic pediatric facilities use lower CT radiation dose with less variation than do nonacademic pediatric or adult facilities for all brain examinations and for the majority of chest and abdomen-pelvis examinations. © RSNA, 2019 See also the editorial by Strouse in this issue.

Medical Physics 3.0: Ensuring Quality and Safety in Medical Imaging

Medical imaging often involves radiation and thus radiation protection. Radiation protection in medicine is only one component of the broader calling of health care professionals: fostering human health. As such, radiation risk needs to be put into the context of the larger mandate of improved outcomes in health care. Medical physicists, according to the new vision of Medical Physics 3.0, make a significant contribution to this mandate as they engage proactively and meaningfully in patient care. Facing the new realities of value-based, personalized, and evidence-based practice, Medical Physics 3.0 is an initiative to make physics inform every patient's care by fostering new skills and expanding horizons for the medical physics profession. It provides a framework by which medical physicists can maintain and improve their integral roles in, and contributions to, health care, its innovation, and its precision. One way that Medical Physics 3.0 will manifest itself in medical imaging practice is by engaging physicists to ensure the precise and optimized use of radiation. Optimization takes place through knowing the defining attributes of the technology in use, the specifics of the patient's situation, and the goals of the imaging and/or intervention. The safety as well as the quality of the procedure is ascertained quantitatively and optimized prospectively, ensuring a proper balance between quality and safety to offer maximum potential benefit to the patient. The results of procedures across the health care operation are then retrospectively analyzed to ensure that each procedure has, in actuality, delivered the targeted quality and safety objectives. Characterizing quality and safety in quantitative terms, objectively optimizing them in the practice of personalized care, and analyzing the results from clinical operations all require the unique combination of precision and innovation that physicists bring to the development and practice of medicine.

The Need for Practical and Accurate Measures of Value for Radiology

Radiologists play a critical role in helping the health care system achieve greater value. Unfortunately, today radiology is often judged by simple "checkbox" metrics, which neither directly reflect the value radiologists provide nor the outcomes they help drive. To change this system, first, we must attempt to better define the elusive term value and, then, quantify the value of imaging through more relevant and meaningful metrics that can be more directly correlated with outcomes. This framework can further improve radiology's value by enhancing radiologists' integration into the care team and their engagement with patients. With these improvements, we can maximize the value of imaging in the overall care of patients.

Tailoring CT Dose to Patient Size: Implementation of the Updated 2017 ACR Size-specific Diagnostic Reference Levels

RATIONALE AND OBJECTIVES

To use an automatic computed tomography (CT) dose monitoring system to analyze the institutional chest and abdominopelvic CT dose data as regards the updated 2017 American College of Radiology (ACR) diagnostic reference levels (DRLs) based on water-equivalent diameter (Dw) and size-specific dose estimates (SSDE) to detect patient-size subgroups in which CT dose can be optimized.

MATERIALS AND METHODS

All chest CT examinations performed between July 2016 and April 2017 with and without contrast material, CT of the pulmonary arteries, and abdominopelvic CT with and without contrast material were included in this retrospective study. Dw and SSDE were automatically calculated for all scans using a previously validated in-house developed Matlab software and stored into our CT dose monitoring system. CT dose data were analyzed as regards the updated ACR DRLs (size groups: 21-25 cm, 25-29 cm, 29-33 cm, 33-37 cm, 37-41 cm). SSDE and volumetric computed tomography dose index (CTDIvol) were used as CT dose parameter.

RESULTS

Overall, 30,002 CT examinations were performed in the study period, 3860 of which were included in the analysis (mean age 62.1 ± 16.4 years, Dw 29.0 ± 3.3 cm; n = 577 chest CT without contrast material, n = 628 chest CT with contrast material, n = 346 CT of chest pulmonary, n = 563 abdominopelvic CT without contrast material, n = 1746 abdominopelvic CT with contrast material). Mean SSDE and CTDIvol relative to the updated DRLs were 43.3 ± 26.4 and 45.1 ± 27.9% for noncontrast chest CT, 52.3 ± 23.1 and 52.0 ± 23.1% for contrast-enhanced chest CT, 68.8 ± 29.5 and 70.0 ± 31.0% for CT of pulmonary arteries, 41.9 ± 29.2 and 43.3 ± 31.3% for noncontrast abdominopelvic CT, and 56.8 ± 22.2 and 58.8 ± 24.4% for contrast-enhanced abdominopelvic CT. Lowest dose compared to the DRLs was found for the Dw group of 21-25 cm in noncontrast abdominopelvic CT (SSDE 30.4 ± 21.8%, CTDIvol 30.8 ± 21.4%). Solely the group of patients with a Dw of 37-41 cm undergoing noncontrast abdominopelvic CT exceeded the ACR DRL (SSDE 100.3 ± 59.0%, CTDIvol 107.1 ± 63.5%).

CONCLUSIONS

On average, mean SSDE and CTDIvol of our institutional chest and abdominopelvic CT protocols were lower than the updated 2017 ACR DRLs. Size-specific subgroup analysis revealed a wide variability of SSDE and CTDIvol across CT protocols and patient size groups with a transgression of DRLs in noncontrast abdominopelvic CT of large patients (Dw 37-41 cm).

Medical imaging dose optimisation from ground up: expert opinion of an international summit

As in any medical intervention, there is either a known or an anticipated benefit to the patient from undergoing a medical imaging procedure. This benefit is generally significant, as demonstrated by the manner in which medical imaging has transformed clinical medicine. At the same time, when it comes to imaging that deploys ionising radiation, there is a potential associated risk from radiation. Radiation risk has been recognised as a key liability in the practice of medical imaging, creating a motivation for radiation dose optimisation. The level of radiation dose and risk in imaging varies but is generally low. Thus, from the epidemiological perspective, this makes the estimation of the precise level of associated risk highly uncertain. However, in spite of the low magnitude and high uncertainty of this risk, its possibility cannot easily be refuted. Therefore, given the moral obligation of healthcare providers, 'first, do no harm,' there is an ethical obligation to mitigate this risk. Precisely how to achieve this goal scientifically and practically within a coherent system has been an open question. To address this need, in 2016, the International Atomic Energy Agency (IAEA) organised a summit to clarify the role of Diagnostic Reference Levels to optimise imaging dose, summarised into an initial report (Järvinen et al 2017 Journal of Medical Imaging 4 031214). Through a consensus building exercise, the summit further concluded that the imaging optimisation goal goes beyond dose alone, and should include image quality as a means to include both the benefit and the safety of the exam. The present, second report details the deliberation of the summit on imaging optimisation.

Institutional computed tomography diagnostic reference levels based on water-equivalent diameter and size-specific dose estimates

Size-specific institutional diagnostic reference levels (DRLs) were generated for chest and abdominopelvic computed tomography (CT) based on size-specific dose estimates (SSDEs) and depending on patients' water-equivalent diameter (Dw). 1690 CT examinations were included in the IRB-approved retrospective study. SSDEs based on the mean water-equivalent diameter of the entire scan volume were calculated automatically. SSDEs were analyzed for different patient sizes and institutional DRLs (iDRLS; 75% percentiles) based on Dw and SSDEs were generated. iDRLs were compared to the national DRLs. Mean volumetric computed tomography dose index (CTDIvol), Dw and SSDEs for all 1690 CT examinations were 7.2 ± 4.0 mGy (0.84-47.9 mGy), 29.0 ± 3.4 cm and 8.5 ± 3.8 mGy (1.2-37.7 mGy), respectively. Overall, the mean SSDEs of all CT examinations were higher than the CTDIvol in chest CT, abdominopelvic CT and upper abdominal CT, respectively (p < 0.001 for all). There was a strong linear correlation between Dw and SSDEs in chest (R² = 0.66), abdominopelvic (R² = 0.98) and upper abdominal CT (R² = 0.96) allowing for the implementation of size-specific institutional DRLs based on SSDEs and patients' Dw. We generated size-specific, Dw-dependent institutional DRLs based on SSDEs, which allow for easier and more comprehensive analyses of CT radiation exposure. Our results indicate that implementation of SSDEs into national DRLs may be beneficial.

A SIMPLE METHOD FOR CALIBRATING PIXEL VALUES OF THE CT LOCALIZER RADIOGRAPH FOR CALCULATING WATER-EQUIVALENT DIAMETER AND SIZE-SPECIFIC DOSE ESTIMATE

The purpose of this study is to establish the relationship between the pixel value (I) of the CT localizer radiograph and water-equivalent thickness (tw) in a straightforward procedure. We used a body CTDI phantom, which was scanned in the AP and LAT projections. After transformation from the pixel values of the images to tw, water-equivalent diameter (Dw) and size-specific dose estimate were calculated on an anthropomorphic phantom and 30 patients retrospectively. We found a linear correlation between I and tw, with R2 ≥ 0.980. The Dw values based on the CT localizer radiograph were comparable to those calculated using axial images. The Dw difference for the anthropomorphic phantom between AP projection and axial images was 5.4 ± 4.2%, and between LAT projection and axial images was 6.7 ± 5.3%. The Dw differences for the patients between CT localizer radiograph and axial images was 2.3 ± 3.2%.

Method for automatic detection of defective ultrasound linear array transducers based on uniformity assessment of clinical images - A case study

The purpose of the present study was to test an idea of and describe a concept of a novel method of detecting defects related to horizontal nonuniformities in ultrasound equipment. The method is based on the analysis of ultrasound images collected directly from the clinical workflow. In total over 31000 images from three ultrasound scanners from two vendors were collected retrospectively from a database. An algorithm was developed and applied to the images, 150 at a time, for detection of systematic dark regions in the superficial part of the images. The result was compared with electrical measurements (FirstCall) of the transducers, performed at times when the transducers were known to be defective. The algorithm made similar detection of horizontal nonuniformities for images acquired at different time points over long periods of time. The results showed good subjective visual agreement with the available electrical measurements of the defective transducers, indicating a potential use of clinical images for early and automatic detection of defective transducers, as a complement to quality control.

A comparison study of size-specific dose estimate calculation methods

BACKGROUND

The size-specific dose estimate (SSDE) has emerged as an improved metric for use by medical physicists and radiologists for estimating individual patient dose. Several methods of calculating SSDE have been described, ranging from patient thickness or attenuation-based (automated and manual) measurements to weight-based techniques.

OBJECTIVE

To compare the accuracy of thickness vs. weight measurement of body size to allow for the calculation of the size-specific dose estimate (SSDE) in pediatric body CT.

MATERIALS AND METHODS

We retrospectively identified 109 pediatric body CT examinations for SSDE calculation. We examined two automated methods measuring a series of level-specific diameters of the patient's body: method A used the effective diameter and method B used the water-equivalent diameter. Two manual methods measured patient diameter at two predetermined levels: the superior endplate of L2, where body width is typically most thin, and the superior femoral head or iliac crest (for scans that did not include the pelvis), where body width is typically most thick; method C averaged lateral measurements at these two levels from the CT projection scan, and method D averaged lateral and anteroposterior measurements at the same two levels from the axial CT images. Finally, we used body weight to characterize patient size, method E, and compared this with the various other measurement methods. Methods were compared across the entire population as well as by subgroup based on body width.

RESULTS

Concordance correlation (ρ_c) between each of the SSDE calculation methods (methods A-E) was greater than 0.92 across the entire population, although the range was wider when analyzed by subgroup (0.42-0.99). When we compared each SSDE measurement method with CTDI_vol, there was poor correlation, ρ_c<0.77, with percentage differences between 20.8% and 51.0%.

CONCLUSION

Automated computer algorithms are accurate and efficient in the calculation of SSDE. Manual methods based on patient thickness provide acceptable dose estimates for pediatric patients <30 cm in body width. Body weight provides a quick and practical method to identify conversion factors that can be used to estimate SSDE with reasonable accuracy in pediatric patients with body width ≥20 cm.

THE SIZE-SPECIFIC DOSE ESTIMATE (SSDE) FOR TRUNCATED COMPUTED TOMOGRAPHY IMAGES

The purpose of this study is to investigate truncated axial computed tomography (CT) images in the clinical environment and to produce correction factors for abdomen, thoracic and head regions based on clinical data, in order to accurately predict the water-equivalent diameter (DW) and size-specific dose estimate (SSDE). We investigated axial images of 75 patients who underwent CT examinations. Truncated axial images were characterized by the truncation percentage (TP). Correction factors were calculated by using the value of DW for a certain TP (truncated image) divided by the value of DW for TP = 0% (the non-truncated image). Most of the thorax images acquired for this study were truncated images (86.2%), in the abdomen region about half of the images were truncated (48.1%), and in the head region only a small portion were truncated (9.1%). In the thorax region the value of TP for the truncated images varied up to 50%, in the abdomen region it varied up to 35%, and in the head region it was smaller than 10%. We have shown how to accurately estimate DW and SSDE by applying a correction factor to the truncated images. The correction factors increase exponentially with increasing TP. The corrected DW and SSDE for the truncated images were significant in the thoracic region, but were not significant in the abdomen and head regions.

Pediatric Chest CT Diagnostic Reference Ranges: Development and Application

Purpose To determine diagnostic reference ranges on the basis of the size of a pediatric patient's chest and to develop a method to estimate computed tomographic (CT) scanner-specific mean size-specific dose estimates (SSDEs) as a function of patient size and the radiation output of each CT scanner at a site. Materials and Methods The institutional review boards of each center approved this retrospective, HIPAA-compliant, multicenter study; informed consent was waived. CT dose indexes (SSDE, volume CT dose index, and dose length product) of 518 pediatric patients (mean age, 9.6 years; male patients, 277 [53%]) who underwent CT between July 1, 2012, and June 30, 2013, according to the guidelines of the Quality Improvement Registry in CT Scans in Children were retrieved from a national dose data registry. Diagnostic reference ranges were developed after analysis of image quality of a subset of 111 CT examinations to validate image quality at the lower bound. Pediatric dose reduction factors were calculated on the basis of SSDEs for pediatric patients divided by SSDEs for adult patients. Results Diagnostic reference ranges (SSDEs) were 1.8-3.9, 2.2-4.5, 2.7-5.1, 3.6-6.6, and 5.5-8.4 mGy for effective diameter ranges of less than 15 cm, 15-19 cm, 20-24 cm, 25-29 cm, and greater than or equal to 30 cm, respectively. The fractions of adult doses (pediatric dose reduction factors) used within the consortium for patients with lateral dimensions of 8, 11, 14, 17, 20, 23, 26, 29, 32, 35, and 38 cm were 0.29, 0.33, 0.38, 0.44, 0.50, 0.58, 0.66, 0.76, 0.87, 1.0, and 1.15, respectively. Conclusion Diagnostic reference ranges developed in this study provided target ranges of pediatric dose indexes on the basis of patient size, while the pediatric dose reduction factors of this study allow calculation of unique reference dose indexes on the basis of patient size for each of a site's CT scanners. ^© RSNA, 2017 Online supplemental material is available for this article.

How accurate is size-specific dose estimate in pediatric body CT examinations?

BACKGROUND

Size-specific dose estimate is gaining increased acceptance as the preferred index of CT dose in children. However it was developed based on non-clinical data.

OBJECTIVE

To compare the accuracy of size-specific dose estimate (SSDE) based on geometric and body weight measures in pediatric chest and abdomen CT scans, versus the more accurate [Formula: see text] (mean SSDE based on water-equivalent diameter).

MATERIALS AND METHODS

We retrospectively identified 50 consecutive children (age <18 years) who underwent chest CT examination and 50 children who underwent abdomen CT. We measured anteroposterior diameter (DAP) and lateral diameter (DLAT) at the central slice (of scan length) of each patient and calculated DAP+LAT (anteroposterior diameter plus lateral diameter) and DED (effective diameter) for each patient. We calculated the following in each child: (1) SSDEs based on DAP, DLAT, DAP+LAT, DED, and body weight, and (2) SSDE based on software calculation of mean water-equivalent diameter ([Formula: see text] adopted standard within our study). We used intraclass correlation coefficient (ICC) and Bland-Altman analysis to compare agreement between the SSDEs and [Formula: see text].

RESULTS

Gender and age distribution were similar between chest and abdomen CT groups; mean body weight was 37 kg for both groups, with ranges of 6-130 kg (chest) and 8-107 kg (abdomen). SSDEs had very strong agreement (ICC>0.9) with [Formula: see text]. SSDEs based on DLAT had 95% limits of agreement of up to 43% with [Formula: see text]. SSDEs based on other parameters (body weight, DAP, DAP+LAT, DED) had 95% limits of agreement of up to 25%.

CONCLUSION

Differences between SSDEs calculated using various indications of patient size (geometric indices and patient weight) and the more accurate [Formula: see text] calculated using proprietary software were generally small, with the possible exception for lateral diameter, and provide acceptable dose estimates for body CT in children.

Automated Calculation of Water-equivalent Diameter (DW) Based on AAPM Task Group 220

The purpose of this study is to accurately and effectively automate the calculation of the water‐equivalent diameter (DW) from 3D CT images for estimating the size‐specific dose. DW is the metric that characterizes the patient size and attenuation. In this study, DW was calculated for standard CTDI phantoms and patient images. Two types of phantom were used, one representing the head with a diameter of 16 cm and the other representing the body with a diameter of 32 cm. Images of 63 patients were also taken, 32 who had undergone a CT head examination and 31 who had undergone a CT thorax examination. There are three main parts to our algorithm for automated DW calculation. The first part is to read 3D images and convert the CT data into Hounsfield units (HU). The second part is to find the contour of the phantoms or patients automatically. And the third part is to automate the calculation of DW based on the automated contouring for every slice (DW,all). The results of this study show that the automated calculation of DW and the manual calculation are in good agreement for phantoms and patients. The differences between the automated calculation of DW and the manual calculation are less than 0.5%. The results of this study also show that the estimating of DW,all using DW,n=1 (central slice along longitudinal axis) produces percentage differences of −0.92%±3.37% and 6.75%±1.92%, and estimating DW,all using DW,n=9 produces percentage differences of 0.23%±0.16% and 0.87%±0.36%, for thorax and head examinations, respectively. From this study, the percentage differences between normalized size‐specific dose estimate for every slice (nSSDEall) and nSSDEn=1 are 0.74%±2.82% and −4.35%±1.18% for thorax and head examinations, respectively; between nSSDEall and nSSDEn=9 are 0.00%±0.46% and −0.60%±0.24% for thorax and head examinations, respectively.

PACS number(s): 87.57.Q‐, 87.57.uq‐

Imaging wisely: patient safety in CT

The past decade has seen a significant growth in diagnostic CT imaging as a direct result of the clinical value provided by CT imaging. At the same time, many new techniques and resources are now available to make CT imaging safe. This article presents the basics of CT dosimetry and their usage in clinical practices, methods to implement CT dose reduction, followed by a summary of legislation, and guidelines related to patient safety in diagnostic CT imaging. Also, CT radiation dose diagnostic reference levels from published regional and national surveys are reviewed and applied in a CT dose tracking and monitoring program.

Variation in Pediatric Cervical Spine Computed Tomography Radiation Dose Index

OBJECTIVES

The objective was to evaluate variation in the current estimated radiation dose index for pediatric cervical spine (c-spine) computed tomography (CT) examinations.

METHODS

This was a retrospective analysis of pediatric (age younger than 19 years) c-spine CT examinations from the American College of Radiology Dose Index Registry, July 2011 through December 2014. We used the volume CT dose index (CTDIvol) as the radiation dose estimate and used summary statistics to describe patient and hospital characteristics.

RESULTS

There were 12,218 pediatric CT c-spine examinations performed across 296 participating hospitals. Fifty-six percent were in male patients, and 79% were in children older than 10 years. Most hospitals (55%) were community hospitals without trauma designations, and the largest proportion of examinations (41%) were performed at these hospitals. The median CTDIvol was 15 mGy (interquartile range = 9 to 23 mGy) representing a more than 2.5-fold difference between the 25th and 75th percentiles. Pediatric hospitals (both trauma and nontrauma centers) delivered the lowest CTDIvol across all age groups and showed the least amount of variability in dose.

CONCLUSIONS

There is significant variation in the radiation dose index for pediatric c-spine CT examinations. Pediatric hospitals practice at lower CT dose estimates than other hospitals. Individual hospitals should examine their practices in an effort to ensure standardization and optimization of CT parameters to minimize radiation exposures to pediatric patients.

CT protocol management: simplifying the process by using a master protocol concept

This article explains a method for creating CT protocols for a wide range of patient body sizes and clinical indications, using detailed tube current information from a small set of commonly used protocols. Analytical expressions were created relating CT technical acquisition parameters which can be used to create new CT protocols on a given scanner or customize protocols from one scanner to another. Plots of mA as a function of patient size for specific anatomical regions were generated and used to identify the tube output needs for patients as a function of size for a single master protocol. Tube output data were obtained from the DICOM header of clinical images from our PACS and patient size was measured from CT localizer radiographs under IRB approval. This master protocol was then used to create 11 additional master protocols. The 12 master protocols were further combined to create 39 single and multiphase clinical protocols. Radiologist acceptance rate of exams scanned using the clinical protocols was monitored for 12,857 patients to analyze the effectiveness of the presented protocol management methods using a two‐tailed Fisher's exact test. A single routine adult abdominal protocol was used as the master protocol to create 11 additional master abdominal protocols of varying dose and beam energy. Situations in which the maximum tube current would have been exceeded are presented, and the trade‐offs between increasing the effective tube output via 1) decreasing pitch, 2) increasing the scan time, or 3) increasing the kV are discussed. Out of 12 master protocols customized across three different scanners, only one had a statistically significant acceptance rate that differed from the scanner it was customized from. The difference, however, was only 1% and was judged to be negligible. All other master protocols differed in acceptance rate insignificantly between scanners. The methodology described in this paper allows a small set of master protocols to be adapted among different clinical indications on a single scanner and among different CT scanners.

PACS number: 87.57.Q

Compliance with AAPM Practice Guideline 1.a: CT Protocol Management and Review - from the perspective of a university hospital

The purpose of this paper is to describe our experience with the AAPM Medical Physics Practice Guideline 1.a: “CT Protocol Management and Review Practice Guideline”. Specifically, we will share how our institution's quality management system addresses the suggestions within the AAPM practice report. We feel this paper is needed as it was beyond the scope of the AAPM practice guideline to provide specific details on fulfilling individual guidelines. Our hope is that other institutions will be able to emulate some of our practices and that this article would encourage other types of centers (e.g., community hospitals) to share their methodology for approaching CT protocol optimization and quality control. Our institution had a functioning CT protocol optimization process, albeit informal, since we began using CT. Recently, we made our protocol development and validation process compliant with a number of the ISO 9001:2008 clauses and this required us to formalize the roles of the members of our CT protocol optimization team. We rely heavily on PACS‐based IT solutions for acquiring radiologist feedback on the performance of our CT protocols and the performance of our CT scanners in terms of dose (scanner output) and the function of the automatic tube current modulation. Specific details on our quality management system covering both quality control and ongoing optimization have been provided. The roles of each CT protocol team member have been defined, and the critical role that IT solutions provides for the management of files and the monitoring of CT protocols has been reviewed. In addition, the invaluable role management provides by being a champion for the project has been explained; lack of a project champion will mitigate the efforts of a CT protocol optimization team. Meeting the guidelines set forth in the AAPM practice guideline was not inherently difficult, but did, in our case, require the cooperation of radiologists, technologists, physicists, IT, administrative staff, and hospital management. Some of the IT solutions presented in this paper are novel and currently unique to our institution.

PACS number: 87.57.Q

Comparison of patient specific dose metrics between chest radiography, tomosynthesis, and CT for adult patients of wide ranging body habitus

PURPOSE

Given the radiation concerns inherent to the x-ray modalities, accurately estimating the radiation doses that patients receive during different imaging modalities is crucial. This study estimated organ doses, effective doses, and risk indices for the three clinical chest x-ray imaging techniques (chest radiography, tomosynthesis, and CT) using 59 anatomically variable voxelized phantoms and Monte Carlo simulation methods.

METHODS

A total of 59 computational anthropomorphic male and female extended cardiac-torso (XCAT) adult phantoms were used in this study. Organ doses and effective doses were estimated for a clinical radiography system with the capability of conducting chest radiography and tomosynthesis (Definium 8000, VolumeRAD, GE Healthcare) and a clinical CT system (LightSpeed VCT, GE Healthcare). A Monte Carlo dose simulation program (PENELOPE, version 2006, Universitat de Barcelona, Spain) was used to mimic these two clinical systems. The Duke University (Durham, NC) technique charts were used to determine the clinical techniques for the radiographic modalities. An exponential relationship between CTDIvol and patient diameter was used to determine the absolute dose values for CT. The simulations of the two clinical systems compute organ and tissue doses, which were then used to calculate effective dose and risk index. The calculation of the two dose metrics used the tissue weighting factors from ICRP Publication 103 and BEIR VII report.

RESULTS

The average effective dose of the chest posteroanterior examination was found to be 0.04 mSv, which was 1.3% that of the chest CT examination. The average effective dose of the chest tomosynthesis examination was found to be about ten times that of the chest posteroanterior examination and about 12% that of the chest CT examination. With increasing patient average chest diameter, both the effective dose and risk index for CT increased considerably in an exponential fashion, while these two dose metrics only increased slightly for radiographic modalities and for chest tomosynthesis. Effective and organ doses normalized to mAs all illustrated an exponential decrease with increasing patient size. As a surface organ, breast doses had less correlation with body size than that of lungs or liver.

CONCLUSIONS

Patient body size has a much greater impact on radiation dose of chest CT examinations than chest radiography and tomosynthesis. The size of a patient should be considered when choosing the best thoracic imaging modality.

The impact on CT dose of the variability in tube current modulation technology: a theoretical investigation

Body CT scans are routinely performed using tube-current-modulation (TCM) technology. There is notable variability across CT manufacturers in terms of how TCM technology is implemented. Some manufacturers aim to provide uniform image noise across body regions and patient sizes, whereas others aim to provide lower noise for smaller patients. The purpose of this study was to conduct a theoretical investigation to understand how manufacturer-dependent TCM scheme affects organ dose, and to develop a generic approach for assessing organ dose across TCM schemes. The adult reference female extended cardiac-torso (XCAT) phantom was used for this study. A ray-tracing method was developed to calculate the attenuation of the phantom for a given projection angle based on phantom anatomy, CT system geometry, x-ray energy spectrum, and bowtie filter filtration. The tube current (mA) for a given projection angle was then calculated as a log-linear function of the attenuation along that projection. The slope of this function, termed modulation control strength, α, was varied from 0 to 1 to emulate the variability in TCM technology. Using a validated Monte Carlo program, organ dose was simulated for five α values (α = 0, 0.25, 0.5, 0.75, and 1) in the absence and presence of a realistic system mA limit. Organ dose was further normalized by volume-weighted CT dose index (CTDIvol) to obtain conversion factors (h factors) that are relatively independent of system specifics and scan parameters. For both chest and abdomen-pelvis scans and for 24 radiosensitive organs, organ dose conversion factors varied with α, following second-order polynomial equations. This result suggested the need for α-specific organ dose conversion factors (i.e., conversion factors specific to the modulation scheme used). On the other hand, across the full range of α values, organ dose in a TCM scan could be derived from the conversion factors established for a fixed-mA scan (hFIXED). This was possible by multiplying hFIXED by a revised definition of CTDIvol that accounts for two factors: (a) the tube currents at the location of an organ and (b) the variation in organ volume along the longitudinal direction. This α-generic approach represents an approximation. The error associated with this approximation was evaluated using the α-specific organ dose (i.e., the organ dose obtained by using α-specific mA profiles as inputs into the Monte Carlo simulation) as the reference standard. When the mA profiles were constrained by a realistic system limit, this α-generic approach had errors of less than ~20% for the full range of α values. This was the case for 24 radiosensitive organs in both chest and abdomen-pelvis CT scans with the exception of thyroid in the chest scan and bladder in the abdomen-pelvis scan. For these two organs, the errors were less than ~40%. The results of this theoretical study suggested that knowing the mA modulation profile and the fixed-mA conversion factors, organ dose may be estimated for a TCM scan independent of the specific modulation scheme applied.