Current pediatric administered activity guidelines for 99m Tc-DMSA SPECT based on patient weight do not provide the same task-based image quality

Abstract

Purpose: In the current clinical practice, administered activity (AA) for pediatric molecular imaging is often based on the North American expert consensus guidelines or the European Association of Nuclear Medicine dosage card, both of which were developed based on the best clinical practice. These guidelines were not formulated using a rigorous evaluation of diagnostic image quality (IQ) relative to AA. In the guidelines, AA is determined by a weight-based scaling of the adult AA, along with minimum and maximum AA constraints. In this study, we use task-based IQ assessment methods to rigorously evaluate the efficacy of weight-based scaling in equalizing IQ using a population of pediatric patients of different ages and body weights.

Methods: A previously developed projection image database was used. We measured task-based IQ, with respect to the detection of a renal functional defect at six different AA levels (AA relative to the AA obtained from the guidelines). IQ was assessed using an anthropomorphic model observer. Receiver-operating characteristics (ROC) analysis was applied; the area under the ROC curve (AUC) served as a figure-of-merit for task performance. In addition, we investigated patient girth (circumference) as a potential improved predictor of the IQ.

Results: The data demonstrate a monotonic and modestly saturating increase in AUC with increasing AA, indicating that defect detectability was limited by quantum noise and the effects of object variability were modest over the range of AA levels studied. The AA for a given value of the AUC increased with increasing age. The AUC vs AA plots for all the patient ages indicate that, for the current guidelines, the newborn and 10- and 15-yr phantoms had similar IQ for the same AA suggested by the North American expert consensus guidelines, but the 5- and 1-yr phantoms had lower IQ. The results also showed that girth has a stronger correlation with the needed AA to provide a constant AUC for ^99m Tc-DMSA renal SPECT.

Conclusions: The results suggest that (a) weight-based scaling is not sufficient to equalize task-based IQ for patients of different weights in pediatric ^99m Tc-DMSA renal SPECT; and (b) patient girth should be considered instead of weight in developing new administration guidelines for pediatric patients.

Keywords: DMSA; SPECT; administered activity guidelines; dose reduction/optimization; pediatric imaging; task-based image quality.

Figure 1.

Renderings of 10th, 50th, and 90th percentile height at constant 50th percentile weight newborn, 1-yr-old, 5-yr-old, 10-yr-old, and 15-yr-old hybrid phantoms.

Figure 2.

From top to bottom the images show upper, lateral, and lower pole (from left to right) defects for the 50th height percentile for the 1- and 5-year-old female and 10- and 15-year-old male phantoms. Inside each of the small block of images, top and bottom row shows coronal, sagittal, and tran-saxial slices for the defect-free and defect present images, respectively.

Figure 3.

Images of the seven anthropomorphic DOM channels used in this work. The top and bottom rows show, respectively, the frequency channels and the spatial domain templates. From left to right, the start frequencies and widths of the channels were 0.5, 1, 2, 4, 8, 16, and 32 cycles/pixel. The spatial templates are the analytic inverse Fourier Transforms of the frequency channels sampled at the image pixel size.

Figure 4.

Sub-ensemble histograms of the test statistic distributions for the no-defect (green) and with-defect (blue) cases for each of the seven channels. These data are for an upper pole defect in the 50th height percentile 1-year-old phantom (including both male and female). This illustrates the near-MVN distribution of the feature vectors.

Figure 5.

The area under the ROC curve (AUC) vs. percent AA plot for all the patient ages. The error bars are the 95% confidence intervals estimated using bootstrapping.

Figure 6.

AUC vs. AA curves and their fitted functions. The AUC was fitted to a model of AUC versus AA, as specified in equation 8, relating AUC to the mean signal difference (K1), object variability noise (K2) and quantum noise (K3), and AA.

Figure 7.

AA vs. patient girth (top) and weight (bottom) at a fixed AUC of 0.84.