Significant Dose Errors Research Articles

Significant Insulin Dose Errors May Occur if Blood Glucose Results are Obtained from Miscoded Meters

The objective of this study was to determine inaccuracies of miscoded blood glucose (BG) meters and potential errors in insulin dose based on values from these meters. Fasting diabetic subjects at three clinical centers participated in a 2-hour meal tolerance test. At various times subjects' blood was tested on five BG meters and on a Yellow Springs Instruments laboratory glucose analyzer. Some meters were purposely miscoded. Using the BG values from these meters, along with three insulin dose algorithms, Monte Carlo simulations were conducted to generate ideal and simulated-meter glucose values and subsequent probability of insulin dose errors based on normal and empirical distribution assumptions. Maximal median percentage biases of miscoded meters were +29% and -37%, while maximal median percentage biases of correctly coded meters were only +0.64% and -10.45% (p = 0.000, chi(2) test, df = 1). Using the low-dose algorithm and the normal distribution assumption, the combined data showed that the probability of insulin error of +/-1U, +/-2, +/-3, +/-4, and +/-5U for miscoded meters could be as high as 49.6, 50.0, 22.3, 1.4, and 0.04%, respectively. This is compared to manually, correctly coded meters where the probability of error of +/-1, +/-2, and +/-3U could be as high as 44.6, 7.1, and 0.49%, respectively. There was no instance of a +/-4 or +/-5U insulin dose error with a manually, correctly coded meter. For autocoded meters, the probability of +/-1 and +/-2U could be as high as 35.4 and 1.4%, respectively. For autocoded meters there were no calculated insulin dose errors above +/-2U. The probability of insulin misdosing with either manually, correctly coded or autocoded meters was significantly lower than that with miscoded meters. Results using empirical distributions showed similar trends of insulin dose errors. Blood glucose meter coding errors may result in significant insulin dosing errors. To avoid error, patients should be instructed to code their meters correctly or be advised to use an autocoded meter that showed superior performance over manually, correctly coded meters in this study.

Dosimetric and radiobiological impact of dose fractionation on respiratory motion induced IMRT delivery errors: A volumetric dose measurement study

Respiratory motion can introduce substantial dose errors during IMRT delivery. These errors are difficult to predict because of the nonsynchronous interplay between radiation beams and tissues. The present study investigates the impact of dose fractionation on respiratory motion induced dosimetric errors during IMRT delivery and their radiobiological implications by using measured 3D dose. We focused on IMRT delivery with dynamic multileaf collimation (DMLC-IMRT). IMRT plans using several beam arrangements were optimized for and delivered to a polystyrene phantom containing a simulated target and critical organs. The phantom was set in linear sinusoidal motion at a frequency of 15 cycles/min (0.25 Hz). The amplitude of the motion was +/- 0.75 cm in the longitudinal direction and +/- 0.25 cm in the lateral direction. Absolute doses were measured with a 0.125 cc ionization chamber while dose distributions were measured with transverse films spaced 6 mm apart. Measurements were performed for varying number of fractions with motion, with respiratory-gated motion, and without motion. A tumor control probability (TCP) model for an inhomogeneously irradiated tumor was used to calculate and compare TCPs for the measurements and the treatment plans. Equivalent uniform doses (EUD) were also computed. For individual fields, point measurements using an ionization chamber showed substantial dose deviations (-11.7% to 47.8%) for the moving phantom as compared to the stationary phantom. However, much smaller deviations (-1.7% to 3.5%) were observed for the composite dose of all fields. The dose distributions and DVHs of stationary and gated deliveries were in good agreement with those of treatment plans, while those of the nongated moving phantom showed substantial differences. Compared to the stationary phantom, the largest differences observed for the minimum and maximum target doses were -18.8% and +19.7%, respectively. Due to their random nature, these dose errors tended to average out over fractionated treatments. The results of five-fraction measurements showed significantly improved agreement between the moving and stationary phantom. The changes in TCP were less than 4.3% for a single fraction, and less than 2.3% for two or more fractions. Variation of average EUD per fraction was small (< 3.1 cGy for a fraction size of 200 cGy), even when the DVHs were noticeably different from that of the stationary tumor. In conclusion, IMRT treatment of sites affected by respiratory motion can introduce significant dose errors in individual field doses; however, these errors tend to cancel out between fields and average out over dose fractionation. 3D dose distributions, DVHs, TCPs, and EUDs for stationary and moving cases showed good agreement after two or more fractions, suggesting that tumors affected by respiration motion may be treated using IMRT without significant dosimetric and biological consequences.

Sensitivity study for CT image use in Monte Carlo treatment planning

An important step in Monte Carlo treatment planning (MCTP), which is commonly performed uncritically, is segmentation of the patient CT data into a voxel phantom for dose calculation. In addition to assigning mass densities to voxels, as is done in conventional TP, this entails assigning media. Mis-assignment of media can potentially lead to significant dose errors in MCTP. In this work, a test phantom with exact-known composition was used to study CT segmentation errors and to quantify subsequent MCTP inaccuracies. For our test cases, we observed dose errors in some regions of up to 10% for 6 and 15 MV photons, more than 30% for an 18 MeV electron beam and more than 40% for 250 kVp photons. It is concluded that a careful CT calibration with a suitable phantom is essential. Generic calibrations and the use of commercial CT phantoms have to be critically assessed.