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In the setting of mass casualty incidents (MCIs), hospitals need to divert from normal routine to delivering the best possible care to the largest number of victims. This should be accomplished by activating an established hospital disaster management plan (DMP) known to all staff through prior training drills. Over the recent decades, imaging has increasingly been used to evaluate critically ill patients. It can also be used to increase the accuracy of triaging MCI victims, since overtriage (falsely higher triage category) and undertriage (falsely lower triage category) can severely impact resource availability and mortality rates, respectively. This article emphasizes the importance of including the radiology department in hospital preparations for a MCI and highlights factors expected to influence performance during hospital DMP activation including issues pertinent to effective simulation, such as establishing proper learning objectives. After-action reviews including performance evaluation and debriefing on issues are invaluable following simulation drills and DMP activation, in order to improve subsequent preparedness. Historically, most hospital DMPs have not adequately included radiology department operations, and they have not or to a little extent been integrated in the DMP activation simulation. This article aims to increase awareness of the need for radiology department engagement in order to increase radiology department preparedness for DMP activation after a MCI occurs.

Objective: The purpose of this study was to evaluate the impact of the use of 64-MDCT and volume image reading on the radiologic workflow during a mass casualty incident simulation., Materials and Methods: For this simulation, casualties were taken to our level I trauma center, and triage was done with whole-body 64-MDCT. The complete raw dataset of thin-section images was sent to a dedicated 3D workstation for further interpretation and simultaneous reformations. This new reading method is called volume image reading. Several time frames were documented to evaluate the workflow: examination time, time needed for image processing, and mean image transfer rates. The results were compared with those of a previous study using a 4-MDCT with axial images only and transfer of data to a PACS., Results: The time for complete image processing (acquisition, reconstruction, and transfer) for 64-MDCT was 4.1 minutes (range, 3.9-4.3 minutes) compared with 9.0 minutes (range, 6.4-10.2 minutes) for 4-MDCT (p ≤ 0.001). The image processing capacity was 14.8 examinations/h for 64-MDCT compared with 6.7 examinations/h for 4-MDCT. The mean number of images was 953 for 64-MDCT compared with 202 for 4-MDCT (p ≤ 0.001). There were no significant differences between 64- and 4-MDCT for the time needed to prepare patients., Conclusion: The use of 64-MDCT with volume image reading led to evident advantages in the radiologic trauma workflow compared with 4-MDCT. Reading of the full image set including reformations can be initiated earlier with volume image reading.

The purpose of this study was to evaluate the response to an automated alarm system of a radiology department during a mass casualty incident simulation. An automated alarm system provided by an external telecommunications provider handling up to 480 ISDN lines was used at a level I trauma center. During the exercise, accessibility, availability, and estimated time of arrival (ETA) of the called in staff were recorded. Descriptive methods were used for the statistical analysis. Of the 49 employees, 29 (59%) were accessible, of which 23 (79%) persons declared to be available to come to the department. The ETA was at an average 29 min (SD ±23). Radiologists and residents reported an ETA to their workplace almost two times shorter compared with technicians (19 ± 16 and 22 ± 16 vs. 40 ± 27 min, p > 0.05). Additional staff reserve is crucial for handling mass casualty incidents. An automated alarm procedure might be helpful. However, the real availability of the employees could not be exactly determined because of unpredictable parameters. But our results allow estimation of the manpower reserve and calculation of maximum radiology service capacities.

The purpose of this study was to evaluate the feasibility, stability, and reproducibility of a dedicated CT protocol for the triage of patients in two separate large-scale exercises that simulated a mass casualty incident (MCI). In both exercises, a bomb explosion at the local soccer stadium that had caused about 100 casualties was simulated. Seven casualties who were rated "critical" by on-site field triage were admitted to the emergency department and underwent whole-body CT. The CT workflow was simulated with phantoms. The history of the casualties was matched to existing CT examinations that were used for evaluation of image reading under MCI conditions. The times needed for transfer and preparation of patients, examination, image reconstruction, total time in the CT examination room, image transfer to PACS, and image reading were recorded, and mean capacities were calculated and compared using the Mann-Whitney U test. We found no significant time differences in transfer and preparation of patients, duration of CT data acquisition, image reconstruction, total time in the CT room, and reading of the images. The calculated capacities per hour were 9.4 vs. 9.8 for examinations completed, and 8.2 vs. 7.2 for reports completed. In conclusion, CT triage is feasible and produced constant results with this dedicated and fast protocol.