Dose reduction in pediatric CT clinical investigations: The impact of the Adaptive Statistical Iterative Reconstruction algorithm (ASiR)

Dose reduction in pediatric CT clinical investigations: The impact of the Adaptive Statistical Iterative Reconstruction algorithm (ASiR)

e86 Abstracts/Physica Medica 32 (2016) e71–e96 of total AGD was 5.7 mGy and third-quartile of acquisition counts was 5 images for GE Senographe DS. ...

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e86

Abstracts/Physica Medica 32 (2016) e71–e96

of total AGD was 5.7 mGy and third-quartile of acquisition counts was 5 images for GE Senographe DS. We have also estimated for DS system the 75th percentile of AGD in magnification acquisitions that is equal to 3.16 mGy. In few cases we found more than 10 radiograms performed with AGD above 10 mGy. Conclusions: The dose tracking system allows to perform fast analysis of dosimetric data to define local LDR and to optimize the acquisition parameters. The 75th percentile of AGD for each radiogram was used as local LDR. Moreover, we have inserted an alert message into Radimetrics system for exams with doses higher than local LDR and that are performed with more than 10 acquisitions. http://dx.doi.org/10.1016/j.ejmp.2016.01.294 B.290 DOSE REDUCTION IN PEDIATRIC CT CLINICAL INVESTIGATIONS: THE IMPACT OF THE ADAPTIVE STATISTICAL ITERATIVE RECONSTRUCTION ALGORITHM (ASIR) A. Ostinelli *,a, M. Duchini a, P. Bonfanti a, S. Lomazzi b, M. Cacciatori a. a A.O. Sant’Anna, Como, Italy; b Università Insubria, Como, Italy Introduction: The latest iterative reconstruction techniques of CT images provide noise reduction and quality improvement at a significantly reduced radiation doses. The extent of this reduction is a critical issue in pediatric exposures, given the high radiosensitivity and the increased post-irradiation life expectancy, with a consequent increase of the tumor induction probability. In this work, pediatric CT examinations were retrospectively analyzed to evaluate the effects of the Adaptive Statistical Iterative Reconstruction algorithm (AsiR, GE). Materials and Methods: The retrospective study of children exposure was based on the examinations carried out on the LightSpeed VCT-64 (GE) CT of the Sant’Anna Hospital (Como). The scan parameters and dose indices data collection was carried out by the DoseWatch (GE) system for clinical dose monitoring, during the 2013 (pre-ASiR) and 2014 (post-ASiR) years. The overall effect of the ASiR introduction was studied as a function of the age and the anatomical region by SPSS analysis software.20 (SPSS inc. Chicago, IL, USA). Results: In 2013 the pediatric CT examinations were 282 (45% for brain) and in 2014 they were 311 (41% for brain). The analysis of these clinical investigations showed that the ASiR introduction allowed for an overall reduction of the CTDI values from 39.7 ± 4.8 mGy (median = 36.6 mGy) to 28.1 ± 1.9 mGy (median = 28.1 mGy). DLP was decreased from 592 ± 87 mGycm (median = 547 mGycm) to 438 ± 39 mGycm (median 435 mGycm). Conclusions: From the analysis of the dose indices, the introduction of ASiR image reconstruction technique represents a valuable tool for dose reduction in pediatric CT exposures, maintaining high quality standards for clinical images. http://dx.doi.org/10.1016/j.ejmp.2016.01.295 B.291 DEFINITION OF LOCAL REFERENCE DIAGNOSTIC LEVELS FOR CT WITH A DOSE-TRACKING SOFTWARE F. Palleri *,a, O. Ortenzia a, M. Sireus b, C. Ghetti a. a Department of Medical Physics, University Hospital of Parma, Parma, Italy; b University of Cagliari, Cagliari, Italy Introduction: Dose optimization in CT examinations is a mandatory issue: in this study local Diagnostic Reference Levels (lDRLs) for the most frequent CT procedures performed in our Radiology Department have been established by using a dose-tracking software. Materials and Methods: The 75thpercentiles of CTDIvol and DLP of 10 CT procedures were evaluated. Examinations were performed on adult patients from March to August 2015 in 5 Siemens CT scanners of Parma Hospital. Dosimetric data of 13,000 exams have been extracted from an automated dose-tracking software, Radimetrics (Bayer). The CT procedures were standard head (5947 exams), sinuses (289), dental (121), standard chest (1976), cardiac (103), spine (327), pulmonary angiography (416), chestabdomen (1119), chest-abdomen-pelvis (765) and abdomen (1794).

We compared our lDRLs with Dlgs 187/00, with an Italian paper (Parolini ER 2014) and with recent published international surveys (McGregor Radiology 2015, Foley BJR 2012, Mafalanka RPD 2014). Results: The 75thpercentiles of CTDIvol head (mGy) and DLPtot head (mGycm) were 64 and 1005 for head, 38 and 465 for sinuses; 12 and 139 for dental. The 75thpercentiles of CTDIvol body (mGy) and DLPtot body (mGycm) were 10 and 408 for chest, 16 and 719 for cardiac, 25 and 520 for spine, 6 and 425 for CT pulmonary angiography, 14 and 1749 for chest-abdomen, 14 and 2138 for CAP, 9 and 1390 for abdomen. Our values result generally lower than values reported in scientific literature except for CTDIvol of Sinuses CT and DLP of CAP examinations. Conclusions: The analysis of a large amount of data was possible with the use of a dose-tracking software; we have established lLDRs for the most frequent CT examinations performed in our hospital and we have focused which are the CT scan protocols that need an optimization. The setting of some dosimetric alerts in Radimetrics allows to control in real time the CT scans and to perform the necessary corrective actions. http://dx.doi.org/10.1016/j.ejmp.2016.01.296

B.292 DESIGN AND IMPLEMENTATION OF AN IT MANAGEMENT SYSTEM FOR A MEDICAL PHYSICS DEPARTMENT (MPD) ACTIVITY WORKFLOWS M. Paolucci *,a,b, L. Servoli b, B. Checcucci b, R. Di Lorenzo a,b, M. Paladino a. a USL Umbria 2, Servizio Di Fisica Medica, Foligno, Italy; b Istituto Nazionale Di Fisica Nucleare, Perugia, Italy Purpose: The activities of a MPD, either in a single Hospital or in a network of Medical Institutions, are very complex and the data flow management coming from different tasks is difficult and time consuming and there are currently no commercial products that tackle in a satisfactory manner the problem. The aim of this work is to describe the design, implementation and operation of an Enterprise Resource Planning and a Database Management System focused on managing the most important workflows of a MPD. Materials and Methods: The system requirements are based on the application of Italian national radiation protection and quality assurance (QA) regulations, national and international guidelines and operating procedures of the USL Umbria 2 MPD. The systems have been using a 3-tier architecture, implemented via incremental releases: presentation, middleware and data level with a presentation layer using a user friendly Graphical User Interface. Results: The system prototype is capable of recording information related to all the medical instruments, MPD equipment, their relevant characteristics, status and history, all the data coming from the quality controls and maintenance activities, digest them and produce the relevant legal and administrative reports. Furthermore it has dedicated sections for Occupational Exposure to Ionizing Radiation (radiological surveillance of working environment and workers) and QA program in diagnostic radiology. The prototype system has been deployed and used from 2013. Conclusions: The most relevant results are the increased levels of data security, the optimization of scheduled tasks, implying a more efficient use of manpower, the homogeneity of the approach to the management of many different activities. Therefore there’s a high degree of innovation, which could bring significant benefits to the work of medical physics staff and a model for future developments. http://dx.doi.org/10.1016/j.ejmp.2016.01.297

B.293 A PROPOSAL OF MAMMOGRAPHY QC-RELATED INDICATOR FOR HTA EVALUATION M. Piergentili *,a, F. Bisi b, F. Cavagnetto c, N. Canevarollo b, D. Rembado d, A. Rivolta e , R. Rosasco b , E.M.L. Vaccara c , E. Zucchi f , R. Rebagliati b , F. Foppiano a. a ASL5, La Spezia, Italy; b ASL3, Genova, Italy; c I.R.C.C.S. Azienda Ospedaliera Universitaria San Martino, IST, Genova, Italy; d ASL2, Savona, Italy; e ASL4, Chiavari, Italy; f ASL1, Imperia, Italy