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

Protocol parameter extraction and centralization framework for comprehensive and in-depth CT protocol review and management

CT protocol management is an arduous task that requires expertise from a variety of radiology professionals, including technologists, radiologists, radiology IT professionals, and medical physicists. Each CT vendor has unique, proprietary protocol file structures, some of which may vary by scanner model, making it difficult to develop a universal framework for distilling technical parameters to a human-readable file format. An ideal solution for CT protocol management is to minimize the work required for parameter extraction by introducing a data format into the workflow that is universal to all CT scanners. In this paper, we report a framework for CT protocol management that converts raw protocol files to an intermediary format before outputting them in a human-readable format for a variety of practical clinical applications, including routine protocol review, protocol version tracking, and cross-protocol comparisons. The framework was developed in Python 3. Technical parameters of interest were determined via collaborative effort between medical physicists and lead technologists. Protocol files were extracted and analyzed from a variety of scanners across our hospital-wide CT fleet, including various systems from Siemens and GE. Protocols were subcategorized based on relevant technical parameters into regular, dual-energy, and cardiac CT protocols. Backend code for technical parameter extraction from raw protocol files to a JavaScript Object Notation (JSON) format was performed on a per-system basis. Conversion from JSON to a readable output format (MS Excel) was performed identically for all scanners using the universal framework developed and presented in this work. Example results for Siemens and GE scanners are shown, including side-by-side comparisons for protocols with similar clinical indications. In conclusion, our CT protocol management framework may be deployed on any CT system to improve clinical efficiency in protocol review and upkeep.

Large variation in radiation dose for routine abdomen CT: reasons for excess and easy tips for reduction

OBJECTIVE

To characterize the use and impact of radiation dose reduction techniques in actual practice for routine abdomen CT.

METHODS

We retrospectively analyzed consecutive routine abdomen CT scans in adults from a large dose registry, contributed by 95 hospitals and imaging facilities. Grouping exams into deciles by, first, patient size, and second, size-adjusted dose length product (DLP), we summarized dose and technical parameters and estimated which parameters contributed most to between-protocols dose variation. Lastly, we modeled the total population dose if all protocols with mean size-adjusted DLP above 433 or 645 mGy-cm were reduced to these thresholds.

RESULTS

A total of 748,846 CTs were performed using 1033 unique protocols. When sorted by patient size, patients with larger abdominal diameters had increased dose and effective mAs (milliampere seconds), even after adjusting for patient size. When sorted by size-adjusted dose, patients in the highest versus the lowest decile in size-adjusted DLP received 6.4 times the average dose (1680 vs 265 mGy-cm) even though diameter was no different (312 vs 309 mm). Effective mAs was 2.1-fold higher, unadjusted CTDIvol 2.9-fold, and phase 2.5-fold for patients in the highest versus lowest size-adjusted DLP decile. There was virtually no change in kV (kilovolt). Automatic exposure control was widely used to modulate mAs, whereas kV modulation was rare. Phase was the strongest driver of between-protocols variation. Broad adoption of optimized protocols could result in total population dose reductions of 18.6-40%.

CONCLUSION

There are large variations in radiation doses for routine abdomen CT unrelated to patient size. Modification of kV and single-phase scanning could result in substantial dose reduction.

CLINICAL RELEVANCE

Radiation dose-optimization techniques for routine abdomen CT are routinely under-utilized leading to higher doses than needed. Greater modification of technical parameters and number of phases could result in substantial reduction in radiation exposure to patients.

KEY POINTS

• Based on an analysis of 748,846 routine abdomen CT scans in adults, radiation doses varied tremendously across patients of the same size and optimization techniques were routinely under-utilized. • The difference in observed dose was due to variation in technical parameters and phase count. Automatic exposure control was commonly used to modify effective mAs, whereas kV was rarely adjusted for patient size. Routine abdomen CT should be performed using a single phase, yet multi-phase was common. • kV modulation by patient size and restriction to a single phase for routine abdomen indications could result in substantial reduction in radiation doses using well-established dose optimization approaches.

How Do Cancer-Specific Computed Tomography Protocols Compare With the American College of Radiology Dose Index Registry? An Analysis of Computed Tomography Dose at 2 Cancer Centers

BACKGROUND

Little guidance exists on how to stratify radiation dose according to diagnostic task. Changing dose for different cancer types is currently not informed by the American College of Radiology Dose Index Registry dose survey.

METHODS

A total of 9602 patient examinations were pulled from 2 National Cancer Institute designated cancer centers. Computed tomography dose (CTDI vol ) was extracted, and patient water equivalent diameter was calculated. N-way analysis of variance was used to compare the dose levels between 2 protocols used at site 1, and three protocols used at site 2.

RESULTS

Sites 1 and 2 both independently stratified their doses according to cancer indications in similar ways. For example, both sites used lower doses ( P < 0.001) for follow-up of testicular cancer, leukemia, and lymphoma. Median dose at median patient size from lowest to highest dose level for site 1 were 17.9 (17.7-18.0) mGy (mean [95% confidence interval]) and 26.8 (26.2-27.4) mGy. For site 2, they were 12.1 (10.6-13.7) mGy, 25.5 (25.2-25.7) mGy, and 34.2 (33.8-34.5) mGy. Both sites had higher doses ( P < 0.001) between their routine and high-image-quality protocols, with an increase of 48% between these doses for site 1 and 25% for site 2. High-image-quality protocols were largely applied for detection of low-contrast liver lesions or subtle pelvic pathology.

CONCLUSIONS

We demonstrated that 2 cancer centers independently choose to stratify their cancer doses in similar ways. Sites 1 and 2 dose data were higher than the American College of Radiology Dose Index Registry dose survey data. We thus propose including a cancer-specific subset for the dose registry.

An Image Quality-informed Framework for CT Characterization

Background Lack of standardization in CT protocol choice contributes to radiation dose variation. Purpose To create a framework to assess radiation doses within broad CT categories defined according to body region and clinical imaging indication and to cluster indications according to the dose required for sufficient image quality. Materials and Methods This was a retrospective study using Digital Imaging and Communications in Medicine metadata. CT examinations in adults from January 1, 2016 to December 31, 2019 from the University of California San Francisco International CT Dose Registry were grouped into 19 categories according to body region and required radiation dose levels. Five body regions had a single dose range (ie, extremities, neck, thoracolumbar spine, combined chest and abdomen, and combined thoracolumbar spine). Five additional regions were subdivided according to dose. Head, chest, cardiac, and abdomen each had low, routine, and high dose categories; combined head and neck had routine and high dose categories. For each category, the median and 75th percentile (ie, diagnostic reference level [DRL]) were determined for dose-length product, and the variation in dose within categories versus across categories was calculated and compared using an analysis of variance. Relative median and DRL (95% CI) doses comparing high dose versus low dose categories were calculated. Results Among 4.5 million examinations, the median and DRL doses varied approximately 10 times between categories compared with between indications within categories. For head, chest, abdomen, and cardiac (3 266 546 examinations [72%]), the relative median doses were higher in examinations assigned to the high dose categories than in examinations assigned to the low dose categories, suggesting the assignment of indications to the broad categories is valid (head, 3.4-fold higher [95% CI: 3.4, 3.5]; chest, 9.6 [95% CI: 9.3, 10.0]; abdomen, 2.4 [95% CI: 2.4, 2.5]; and cardiac, 18.1 [95% CI: 17.7, 18.6]). Results were similar for DRL doses (all P < .001). Conclusion Broad categories based on image quality requirements are a suitable framework for simplifying radiation dose assessment, according to expected variation between and within categories. © RSNA, 2021 See also the editorial by Mahesh in this issue.

Optimisation of CT protocols in PET-CT across different scanner models using different automatic exposure control methods and iterative reconstruction algorithms

Background

A significant proportion of the radiation dose from a PET-CT examination is dependent on the CT protocol, which should be optimised for clinical purposes. Matching protocols on different scanners within an imaging centre is important for the consistency of image quality and dose. This paper describes our experience translating low-dose CT protocols between scanner models utilising different automatic exposure control (AEC) methods and reconstruction algorithms.

Methods

The scanners investigated were a newly installed Siemens Biograph mCT PET with 64-slice SOMATOM Definition AS CT using sinogram affirmed iterative reconstruction (SAFIRE) and two GE Discovery 710 PET scanners with 128-slice Optima 660 CT using adaptive statistical reconstruction (ASiR). Following exploratory phantom work, 33 adult patients of various sizes were scanned using the Siemens scanner and matched to patients scanned using our established GE protocol to give 33 patient pairs. A comparison of volumetric CT dose index (CTDI_vol) and image noise within these patient pairs informed optimisation, specifically for obese patients. Another matched patient study containing 27 patient pairs was used to confirm protocol matching. Size-specific dose estimates (SSDEs) were calculated for patients in the second cohort. With the acquisition protocol for the Siemens scanner determined, clinicians visually graded the images to identify optimal reconstruction parameters.

Results

In the first matched patient study, the mean percentage difference in CTDI_vol for Siemens compared to GE was − 10.7% (range − 41.7 to 50.1%), and the mean percentage difference in noise measured in the patients’ liver was 7.6% (range − 31.0 to 76.8%). In the second matched patient study, the mean percentage difference in CTDI_vol for Siemens compared to GE was − 20.5% (range − 43.1 to 1.9%), and the mean percentage difference in noise was 19.8% (range − 27.0 to 146.8%). For these patients, the mean SSDEs for patients scanned on the Siemens and GE scanners were 3.27 (range 2.83 to 4.22) mGy and 4.09 (range 2.81 to 4.82) mGy, respectively. The analysis of the visual grading study indicated no preference for any of the SAFIRE strengths.

Conclusions

Given the different implementations of acquisition parameters and reconstruction algorithms between vendors, careful consideration is required to ensure optimisation and standardisation of protocols.

Applying a New CT Quality Metric in Radiology: How CT Pulmonary Angiography Repeat Rates Compare Across Institutions

OBJECTIVES

To quantify overall CT repeat and reject rates at five institutions and investigate repeat and reject rates for CT pulmonary angiography (CTPA).

METHODS

In this retrospective study, we apply an automated repeat rate analysis algorithm to 103,752 patient examinations performed at five institutions from July 2017 to August 2019. The algorithm identifies repeated scans for specific scanner and protocol combinations. For each institution, we compared repeat rates for CTPA to all other CT protocols. We used logistic regression and analysis of deviance to compare CTPA repeat rates across institutions and size-based protocols.

RESULTS

Of 103,752 examinations, 1,447 contained repeated helical scans (1.4%). Overall repeat rates differed across institutions (P < .001) ranging from 0.8% to 1.8%. Large-patient CTPA repeat rates ranged from 3.0% to 11.2% with the odds (95% confidence intervals) of a repeat being 4.8 (3.5-6.6) times higher for large- relative to medium-patient CTPA protocols. CTPA repeat rates were elevated relative to all other CT protocols at four of five institutions, with strong evidence of an effect at two institutions (P < .001 for each; odds ratios: 2.0 [1.6-2.6] and 6.2 [4.4-8.9]) and somewhat weaker evidence at the others (P = .005 and P = 0.011; odds ratios: 2.2 [1.3-3.8] and 3.7 [1.5-9.1], respectively). Accounting for size-based protocols, CTPA repeat rates differed across institutions (P < .001).

DISCUSSION

The results indicate low overall repeat rates (<2%) with CTPA rates elevated relative to other protocols. Large-patient CTPA rates were highest (eg, 11.2% at one institution). Differences in repeat rates across institutions suggest the potential for quality improvement.

Effect of contrast agent administration on water equivalent diameter in CT

PURPOSE

Water equivalent diameter (WED) is the preferred surrogate for patient size in computed tomography (CT). It is better than geometric size surrogates and patient weight/height/BMI/age because it correlates the best with x-ray attenuation. The administration of oral/IV contrast agents increases a patient's attenuation and should therefore increase WED. Here we study the clinically relevant effect of oral and IV contrast agent on WED.

METHODS

We pulled 1703 routine adult abdominal/pelvis cases acquired at 100, 120, and 140 kV from our PACS under retrospective IRB approval. One hundred and forty cases cases had no oral or IV contrast (NONCON), 285 had just IV contrast (IV), 107 had just oral contrast (ORAL), and 1171 had both oral and IV contrast (BOTH). For each case, we measured the water equivalent and effective diameter (ED) from axial CT images. We plotted the WED versus the ED for each class of contrast. We used a linear regression model and omnibus F-test to determine if significant differences between WED distributions existed between the contrast groups for each kV. We then performed a post hoc analysis to determine if any significant differences existed in pairwise comparisons of the different contrast groups. Bonferroni correction was used to account for multiple comparisons.

RESULTS

We found statistically significant changes at 100 and 120 kV with a maximum change of 2.1 mm. We measured a ~25 mm spread (i.e., prediction interval) of WEDs within all four contrast groups.

CONCLUSIONS

While our sample size was large enough to detect statistically significant differences between some of the contrast groups, the differences were clinically irrelevant when one considers that the change in size-specific dose estimate (SSDE) caused by our observations is roughly 1%.

A Multiinstitutional Study on Wasted CT Scans for Over 60,000 Patients

OBJECTIVE. Repeated imaging is an unnecessary source of patient radiation exposure, a detriment to patient satisfaction, and a waste of time and money. Although analysis of rates of repeated and rejected images is mandated in mammography and recommended in radiography, the available data on these rates for CT are limited. MATERIALS AND METHODS. In this retrospective study, an automated repeat-reject rate analysis algorithm was used to quantify repeat rates from 61,102 patient examinations obtained between 2015 and 2018. The algorithm used DICOM metadata to identify repeat acquisitions. We quantified rates for one academic site and one rural site. The method allows scanner-, technologist-, protocol-, and indication-specific rates to be determined. Positive predictive values and sensitivity were estimated for correctly identifying and classifying repeat acquisitions. Repeat rates were compared between sites to identify areas for targeted technologist training. RESULTS. Of 61,102 examinations, 4676 instances of repeat scanning contributed excess radiation dose to patients. Estimated helical overlap repeat rates were 1.4% (95% CI, 1.2-1.6%) for the rural site and 1.1% (95% CI, 1.0-1.2%) for the academic site. Significant differences in rates of repeat imaging required because of bolus tracking (11.6% vs 4.3%; p < 0.001) and helical extension (3.3% vs 1.8%; p < 0.001) were observed between sites. Positive predictive values ranged from 91% to 99% depending on the reason for repeat imaging and site location. Sensitivity of the algorithm was 92% (95% CI, 87-96%). Rates tended to be highest for emergent imaging procedures and exceeded 9% for certain protocols. CONCLUSION. Our multiinstitutional automated quantification of repeat rates for CT provided a useful metric for unnecessary radiation exposure and identification of technologists in need of training.

Technical Note: Increased photon starvation artifacts at low helical pitch in ultra-low-dose CT

PURPOSE

The aim of this study was to demonstrate that a low helical pitch causes increased photon starvation artifacts at ultra-low-dose CT.

METHODS

A cylindrical water phantom with a diameter of 30 cm was scanned on two different generation CT scanners: a 64-slice scanner (Sensation 64, Siemens Healthcare) and a 192-slice scanner (Somatom Force, Siemens Healthcare) at multiple effective mAs levels (mAs/pitch = 200, 100, 50, 25, and 12). The corresponding CTDI_vol values were 4.1, 2.0, 1.0, 0.5 mGy, on the 64-slice scanner and 3.8, 1.9, 1.0, 0.5 mGy on the 192-slice scanner, for the selected effective mAs values. For each dose setting, the scan was repeated at four helical pitches: 1.2, 0.9, 0.6, and the lowest achievable pitch on each scanner. The tube current was automatically adjusted by the scanner so that the effective mAs, and thus CTDI_vol , were kept the same for different pitches. All CT data sets were reconstructed with a slice thickness of 3mm and a medium smooth kernel. Images acquired at the same dose level but different helical pitches were visually inspected to assess photon starvation artifacts and noise levels.

RESULTS

At the same radiation dose, image noise increased with the decreasing helical pitch. The increase was more severe on the old-generation 64-slice scanner. Photon starvation artifacts were evident at 200 effective mAs on the 64-slice scanner at 80 kV. On the 192-slice scanner there was no visible photon starvation artifacts at both 200 and 50 effective mAs (CTDI_vol  = 4.1 mGy and 1.0 mGy, respectively); nor was there a visible impact from the lower helical pitch. Only when the dose was lowered to be extremely low (~0.26 mGy, achievable at 70 kV), did photon starvation artifacts become evident.

CONCLUSIONS

A low helical pitch may increase image noise and photon starvation artifacts compared to a higher pitch for the same dose level, particularly at ultra-low dose CT.

CT and MR Protocol Standardization Across a Large Health System: Providing a Consistent Radiologist, Patient, and Referring Provider Experience

Building and maintaining a comprehensive yet simple set of standardized protocols for a cross-sectional image can be a daunting task. A single department may have difficulty preventing "protocol creep," which almost inevitably occurs when an organized "playbook" of protocols does not exist and individual radiologists and technologists alter protocols at will and on a case-by-case basis. When multiple departments or groups function in a large health system, the lack of uniformity of protocols can increase exponentially. In 2012, the University of Colorado Hospital formed a large health system (UCHealth) and became a 5-hospital provider network. CT and MR imaging studies are conducted at multiple locations by different radiology groups. To facilitate consistency in ordering, acquisition, and appearance of a given study, regardless of location, we minimized the number of protocols across all scanners and sites of practice with a clinical indication-driven protocol selection and standardization process. Here we review the steps utilized to perform this process improvement task and insure its stability over time. Actions included creation of a standardized protocol template, which allowed for changes in electronic storage and management of protocols, designing a change request form, and formation of a governance structure. We utilized rapid improvement events (1 day for CT, 2 days for MR) and reduced 248 CT protocols into 97 standardized protocols and 168 MR protocols to 66. Additional steps are underway to further standardize output and reporting of imaging interpretation. This will result in an improved, consistent radiologist, patient, and provider experience across the system.

Evaluation of AAPM Reports 204 and 220: Estimation of effective diameter, water-equivalent diameter, and ellipticity ratios for chest, abdomen, pelvis, and head CT scans

Purpose

To confirm AAPM Reports 204/220 and provide data for the future expansion of these reports by: (a) presenting the first large‐scale confirmation of the reports using clinical data, (b) providing the community with size surrogate data for the head region which was not provided in the original reports, and additionally providing the measurements of patient ellipticity ratio for different body regions.

Method

A total of 884 routine scans were included in our analysis including data from the head, thorax, abdomen, and pelvis for adults and pediatrics. We calculated the ellipticity ratio and all of the size surrogates presented in AAPM Reports 204/220. We correlated the purely geometric‐based metrics with the “gold standard” water‐equivalent diameter (D_W).

Results

Our results and AAPM Reports 204/220 agree within our data's 95% confidence intervals. Outliers to the AAPM reports’ methods were caused by excess gas in the GI tract, exceptionally low BMI, and cranial metaphyseal dysplasia. For the head, we show lower correlation (R² = 0.812) between effective diameter and D_W relative to other body regions. The ellipticity ratio of the shoulder region was the highest at 2.28 ± 0.22 and the head the smallest at 0.85 ± 0.08. The abdomen pelvis, chest, thorax, and abdomen regions all had ellipticity values near 1.5.

Conclusion

We confirmed AAPM reports 204/220 using clinical data and identified patient conditions causing discrepancies. We presented new size surrogate data for the head region and for the first time presented ellipticity data for all regions. Future automatic exposure control characterization should include ellipticity information.

Variation in CT Number and Image Noise Uniformity According to Patient Positioning in MDCT

OBJECTIVE

Many algorithms for clinical decision making rely on assessment of the CT number (expressed as Hounsfield units); however, to our knowledge, few, if any, studies have addressed how CT numbers change as a function of patient positioning within the scanner.

MATERIALS AND METHODS

An anthropomorphic phantom underwent imaging with varying amounts of vertical orientation misalignment with respect to isocenter. CT number and noise were measured using ROIs in the upper thorax, mid thorax, and abdomen. The degree of noise nonuniformity and changes in the CT number were assessed by comparing values obtained in the anterior versus posterior ROIs. To add clinical relevance, data on vertical mispositioning were collected from 20,316 clinical abdominal CT scans. Box-and-whisker plot analysis was used to identify the range of patient positioning.

RESULTS

Absolute CT number changes of more than 20 HU were observed for some ROIs at phantom positions of 10 cm from isocenter, with important differences noted between the thoracic and abdominal regions. Noise uniformity varied by more than twofold for all regions at 10 cm below isocenter. On clinical CT examinations, off-centering of more than 1, 2, 4, and 6 cm occurred for 41%, 19%, 1.9%, and 0.3% of patients, respectively.

CONCLUSION

Radiologists should treat CT number measurements with caution when patients are grossly mispositioned in the scanner. The substantial changes in attenuation values shown in the present study are large enough to warrant further investigation.

Tracking Patterns of Nonadherence to Prescribed CT Protocol Parameters

PURPOSE

Quantification of the frequency, understanding the motivation, and documentation of the changes made by CT technologists at scan time are important components of monitoring a quality CT workflow.

METHODS

CT scan acquisition data were collected from one CT scanner for a period of 1 year. The data included all relevant acquisition parameters needed to define the technical side of a CT protocol. An algorithm was created to sort these data in groups of irradiation events with the same combinations of scan acquisition parameters. For scans modified at scan time, it was hypothesized that these examinations would show up only once in the organized data. A classification scheme was developed to place each "one-off" examination into a category related to what motivated the scan-time change.

RESULTS

A total of 132,707 irradiation events were organized into 434 groups of unique scan acquisition parameters. One hundred forty-four irradiation events had acquisition parameters that showed up only once in the data. These "one-offs" were classified as follows: 25% represented rarely used protocols, 17% were due to service scans, 16% were changed for unknown and therefore undesired reasons, 15% were changed by technologists trying to adapt protocol to patient size, 12% were allowable scan-time changes, 8% of scans had tube current maxed out, and 6% of scans were changed to a higher dose mode as requested by radiologists.

CONCLUSIONS

The outcome of this study suggests many areas of needed technologist training and chances for optimizing this institution's CT protocols.