Patient dose monitoring software in radiology

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Abstract

An increase in the number of diagnostic procedures using ionizing radiation (computed tomography, interventional procedures, and the use of nuclear medicine) results in an increase in radiation exposure and, consequently, an increase in collective and individual doses of radiation to patients.

Diagnostic studies from the international professional community are extensively focusing on issues such as management and dose optimization. Worldwide practice can resolve these issues using software for monitoring patient doses to automatically collect, analyze, and account for patient doses in various types of diagnostic studies. The software allows to obtain data on the doses of patients from X-ray procedures and detailed information about studies, track the total accumulated dose of the patient, and maintain statistics on the device, X-ray laboratory, and the medical organization. It also helps analyze the collected dosimetric data, deduce the causal relationship between dose indications and diagnostic procedure conditions, and monitor the effectiveness of the equipment.

The basic capabilities of patient dose monitoring software (DMS) available on the global market were investigated. The major technical requirements for the software functional needed in practical work were defined.

Modern DMS have a wide range of possibilities for automated collection, storage, and management of patient radiation exposure data in radiology departments. DMS increase the quality of healthcare services, provide patient safety, and optimize the workflow of medical organizations.

About the authors

Maria P. Shatenok

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies

Email: maria.prusova@gmail.com
ORCID iD: 0000-0001-9217-7011
SPIN-code: 5165-7113
Russian Federation, Moscow

Sergey A. Ryzhov

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies; Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology

Email: s.ryzhov@npcmr.ru
ORCID iD: 0000-0002-0640-7368
SPIN-code: 6595-4011
Russian Federation, Moscow; Moscow

Zoya A. Lantukh

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies

Email: z.lantukh@npcmr.ru
ORCID iD: 0000-0001-6623-9610
SPIN-code: 5486-6496
Russian Federation, Moscow

Yuliya V. Druzhinina

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies; Russian Medical Academy of Continuous Professional Education

Email: yu.druzhinina@npcmr.ru
ORCID iD: 0000-0002-3230-3722
SPIN-code: 1973-2848
Russian Federation, Moscow; Moscow

Kirill V. Tolkachev

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies

Author for correspondence.
Email: k.tolkachev@npcmr.ru
ORCID iD: 0000-0001-8871-8700
SPIN-code: 3196-7497
Russian Federation, Moscow

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Supplementary files

Supplementary Files
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1. JATS XML
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2. Fig. 1. An example of Dose Report and RDSR.

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3. Fig. 3. Tabular view of data presentation, DoseTrack, Sectra.

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4. Fig. 4. Diagnosis reference level diagram for patient dose monitoring software, Radimetrics, Bayer.

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5. Fig. 6. Histogram for parameter "Interval between patients in minutes", Teamplay, Siemens Healthineers.

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6. Fig. 7. Formation of alarm alerts by levels of DLP values, DoseWise Portal, Philips.

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7. Fig. 8. Color indication of CT parameters, Radimetrics, Bayer.

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8. Fig. 9. Patient dose history, DoseWise Portal, Philips.

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9. Fig. 10. Setting local reference diagnostic levels, DoseTrack, Sectra.

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10. Fig. 11. Number of exams distributed by DLP ranges and by model of computed tomography scanners, total number of exams per scanner, DoseWatch, GE.

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11. Fig. 12. Example of a table with ten maximum dose studies, DoseWatch, GE.

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12. Fig. 13. Computed Tomography Patient Centering Assessment, DoseWatch, GE.

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13. Fig. 14. Monitoring and optimization of peak skin dose in interventional procedures, Radimetrics, Bayer.

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14. Fig. 15. Patient effective organ dose analysis, DoseWatch, GE.

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15. Fig. 2. An example of a typical connection of software for monitoring patient doses.

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16. Fig. 5. Statistical analysis of dose distributions by DLP parameter, Teamplay, Siemens Healthineers.

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17. Fig. 6. Histogram for the parameter “interval between patients in minutes,” Teamplay, Siemens Healthineers.

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