An Automated, Dynamic Radiation Oncology Prescription Checking System

PURPOSE

Despite serving as a critical communication tool, radiation oncology prescriptions are entered manually and prone to error. An automated prescription checking system was developed and implemented to help address this problem.

METHODS AND MATERIALS

Rules defining clinically appropriate prescriptions were generated, examining specific types of errors: (1) unapproved dose per fraction for a given disease site; (2) dose per fraction too large for nonstereotactic treatment technique; and (3) dose per fraction too low. With a goal of catching errors as upstream as possible to minimize their propagation, a report was created and ran every 30 minutes to check all newly written or approved prescriptions against the 3 rules. When a prescription violated these rules, an automated email was immediately sent to the prescriber alerting them of the potential error. System performance was continuously monitored and the criteria triggering an alert adjusted to balance error detection against false positives. Alerts leading to prescription amendment were considered true errors.

RESULTS

From June 2021 to November 2022, the system checked 24,047 prescriptions. A total of 241 email alerts were triggered, for an average alert rate of 1%. Of the 241 alerts, 198 (82.2%) were unapproved doses per fraction for the disease site, 14 (5.8%) were doses per fraction that were too low, and 29 (12%) were doses too large for nonstereotactic treatment technique. Thirty-one percent of alerts led to a change of prescription, suggesting they were true errors. The baseline rate of erroneous prescription entry was 0.3%. A regression model showed that trainee prescription entry and dose per fraction <150 cGy were significantly associated with true errors.

CONCLUSIONS

Given the significant consequences of erroneous prescription entry, which ranged from wasted resources and treatment delays to potentially serious misadministration, there is significant value in implementing automated prescription checking systems in radiation oncology clinics.

TU-E-BRB-02: A Decision Support Tool for SBRT Planning Using a Searchable DVH Database

PURPOSE

Develop a decision support tool that aids dosimetrists, physicians, and physicists in assessing and improving plan quality through comparison to plans previously used in similar clinical situations.

METHODS

Software was developed to capture and store DVHs and other clinically relevant treatment plan characteristics in a database. In addition to the plan DVH, the database contains a total of 24 plan characteristics including fractionation, prescribed dose, treatment volume, prior surgery, tumor position, and smoking history. DVH and other plan data was captured from the treatment planning system via exported dicom RT files. Structures in the plan were automatically matched by name to a list of standard structures using a system of regular expressions. Additional fields were entered manually using a simple java interface. As a support tool, a plan under development can be quickly compared to similar plans in the database based on selected plan characteristics. A plot displaying the current and historical DVHs provides an easy visual comparison. Our interface also provides statistics for comparison for each dose/volume level such as average, minimum, maximum and standard deviation.

RESULTS

DVHs from 111 lung SBRT plans treated from 2009-2011 were imported in accordance with an approved IRB protocol. As an example of data comparisons that can be easily performed to guide plan evaluation, we examined plans prescribing 5400cGy in 3 fractions and found that tumors >7.5cc (n=34) had an average PTV coverage of 94.2% (range: 73.5-95.0%), and tumors =7.5cc (n=35) had an average PTV coverage of 94.9% (range: 81.6-99.6%).

CONCLUSION

A searchable DVH database was constructed to provide planners, physicists, and physicians with a straightforward means of comparing plans against historic distributions of DVHs. In the future, outcome data will be included in the database to strengthen its functionality as a decision support and research tool.

Systemic RNAi in Caenorhabditis elegans

RNA interference (RNAi) in Caenorhabditis elegans induced by ingestion or injection of double-stranded RNA (dsRNA) spreads throughout the organism and is even transmitted to the progeny. We have identified two proteins required for spreading of RNAi, SID-1 and SID-2, whose structure, subcellular localization, and expression pattern have been informative for how dsRNA can be transported into and between cells. SID-1 is a transmembrane protein that functions as a pore or channel that transports dsRNA into and out of cells. Proteins homologous to SID-1 are present in a wide range of invertebrate and vertebrate animals but are absent from plants. SID-2 is a small transmembrane protein that is expressed in the gut and localizes strongly to the luminal membrane where it appears to act as a receptor for uptake of dsRNA from the environment. Characterization of SID-2 activity in a variety of Caenorhabditis nematodes indicates that C. elegans SID-2 may have a novel activity.