Informatics in Radiology: RADIANCE: An Automated, Enterprise-wide Solution for Archiving and Reporting CT Radiation Dose Estimates

Cook, Tessa S.; Zimmerman, Stefan L.; Steingall, Scott R; Maidment, Andrew D. A.; Kim, Woojin; Boonn, William W.

doi:10.1148/rg.317115048

Cited by 50 publications

(24 citation statements)

References 20 publications

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“…The California legislature responded by mandating the recording of "patient dose" in the radiology report, which became effective on July 1, 2012 (5). Informatics toolkits have been developed to collect radiation exposure data from individual examinations (6)(7)(8) and to provide the automation necessary to aggregate individual information for large-scale study (9). Recording CT scanner metrics, such as the volume CT dose index (CTDI vol ) and the dose-length product, can aid in successfully monitoring x-ray tube output, but these metrics fall short of measuring radiation dose to the patient (10)(11)(12).…”

Section: Setting and Cohortmentioning

confidence: 99%

Estimating Patient Dose from X-ray Tube Output Metrics: Automated Measurement of Patient Size from CT Images Enables Large-scale Size-specific Dose Estimates

Ikuta¹,

Warden²,

Andriole³

et al. 2013

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Purpose:To test the hypothesis that patient size can be accurately calculated from axial computed tomographic (CT) images, including correction for the effects of anatomy truncation that occur in routine clinical CT image reconstruction. Materials and Methods:Institutional review board approval was obtained for this HIPAA-compliant study, with waiver of informed consent. Water-equivalent diameter (D W ) was computed from the attenuation-area product of each image within 50 adult CT scans of the thorax and of the abdomen and pelvis and was also measured for maximal field of view (FOV Results:In the thorax, D W versus D eff had an R 2 of 0.51 (n = 200, 50 patients at four anatomic locations); in the abdomen and pelvis, R 2 was 0.90 (n = 150, 50 patients at three anatomic locations). By correcting for image truncation, the proportion of clinically reconstructed images with an extracted D W within 65% of the maximal FOV D W increased from 54% to 90% in the thorax (3602 images) and from 95% to 100% in the abdomen and pelvis (6181 images). Conclusion:The D W extracted from axial CT images is a reliable measure of patient size, and varying degrees of clinical image truncation can be readily corrected. Automated measurement of patient size combined with CT radiation exposure metrics may enable patient-specific dose estimation on a large scale.q RSNA, 2013

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Section: Setting and Cohortmentioning

confidence: 99%

Estimating Patient Dose from X-ray Tube Output Metrics: Automated Measurement of Patient Size from CT Images Enables Large-scale Size-specific Dose Estimates

Ikuta¹,

Warden²,

Andriole³

et al. 2013

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“…This is an attractive option as evidenced by the widespread adoption of Radiance [21], a completely opensource dose monitoring software. Besides being free-ofcharge, open-source software like Radiance can be modified to the particularities of an institution.…”

Section: Amend An Open-source Dose Monitoring Package To Theirmentioning

confidence: 99%

Open-Source Radiation Exposure Extraction Engine (RE3) with Patient-Specific Outlier Detection

et al. 2015

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We present an open-source, picture archiving and communication system (PACS)-integrated radiation exposure extraction engine (RE3) that provides study-, series-, and slice-specific data for automated monitoring of computed tomography (CT) radiation exposure. RE3 was built using opensource components and seamlessly integrates with the PACS. RE3 calculations of dose length product (DLP) from the Digital imaging and communications in medicine (DICOM) headers showed high agreement (R 2 =0.99) with the vendor dose pages. For study-specific outlier detection, RE3 constructs robust, automatically updating multivariable regression models to predict DLP in the context of patient gender and age, scan length, waterequivalent diameter (D w ), and scanned body volume (SBV). As proof of concept, the model was trained on 811 CT chest, abdomen + pelvis (CAP) exams and 29 outliers were detected. The continuous variables used in the outlier detection model were scan length (R 2 =0.45), D w (R 2 =0.70), SBV (R 2 =0.80), and age (R 2 =0.01). The categorical variables were gender (male average 1182.7 ±26.3 and female 1047.1±26.9 mGy cm) and pediatric status (pediatric average 710.7±73.6 mGy cm and adult 1134.5±19.3 mGy cm).

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“…Furthermore, there is increasing use of decision support systems to curb overutilization, and national dose registries are under way that will allow facilities to compare their CT doses against national benchmarks (3,5,7,8). The latter will be increasingly facilitated by automated technologies designed to capture doserelated parameters, which are soon to be more widely available (9,10). In the near future, most institutions will be able to query a database that will provide aggregate dose information from all CT examinations performed at their institution (9,10).…”

Section: Evolution Of Patient Dose Registriesmentioning

confidence: 99%

“…The latter will be increasingly facilitated by automated technologies designed to capture doserelated parameters, which are soon to be more widely available (9,10). In the near future, most institutions will be able to query a database that will provide aggregate dose information from all CT examinations performed at their institution (9,10).…”

Section: Evolution Of Patient Dose Registriesmentioning

confidence: 99%

Falling Prey to the Sunk Cost Bias: A Potential Harm of Patient Radiation Dose Histories

Eisenberg¹,

Harvey²,

Moore³

et al. 2012

Radiology

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Informatics in Radiology: RADIANCE: An Automated, Enterprise-wide Solution for Archiving and Reporting CT Radiation Dose Estimates

Cited by 50 publications

References 20 publications

Estimating Patient Dose from X-ray Tube Output Metrics: Automated Measurement of Patient Size from CT Images Enables Large-scale Size-specific Dose Estimates

Estimating Patient Dose from X-ray Tube Output Metrics: Automated Measurement of Patient Size from CT Images Enables Large-scale Size-specific Dose Estimates

Open-Source Radiation Exposure Extraction Engine (RE3) with Patient-Specific Outlier Detection

Falling Prey to the Sunk Cost Bias: A Potential Harm of Patient Radiation Dose Histories

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