A projection image database to investigate factors affecting image quality in weight-based dosing: application to pediatric renal SPECT

Abstract

Balancing the tradeoff between radiation dose, acquisition duration and diagnostic image quality is essential for medical imaging modalities involving ionizing radiation. Lower administered activities to the patient can reduce absorbed dose, but can result in reduced diagnostic image quality or require longer acquisition durations. In pediatric nuclear medicine, it is desirable to use the lowest amount of administered radiopharmaceutical activity and the shortest acquisition duration that gives sufficient image quality for clinical diagnosis. However, diagnostic image quality is a complex function of patient factors including body morphometry. In this study, we present a digital population of 90 computational anatomic phantoms that model realistic variations in body morphometry and internal anatomy. These phantoms were used to generate a large database of projection images modeling pediatric SPECT imaging using a ^99mTc-DMSA tracer. We used an analytic projection code that models attenuation, spatially varying collimator-detector response, and object-dependent scatter to generate the projections. The projections for each organ were generated separately and can be subsequently scaled by parameters extracted from a pharmacokinetics model to simulate realistic tracer biodistribution, including variations in uptake, inside each relevant organ or tissue structure for a given tracer. Noise-free projection images can be obtained by summing these individual organ projections and scaling by the system sensitivity and acquisition duration. We applied this database in the context of ^99mTc-DMSA renal SPECT, the most common nuclear medicine imaging procedure in pediatric patients. Organ uptake fractions based on literature values and patient studies were used. Patient SPECT images were used to verify that the sum of counts in the simulated projection images was clinically realistic. For each phantom, 384 uptake realizations, modeling random variations in the uptakes of organs of interest, were generated, producing 34 560 noise-free projection datasets (384 uptake realizations times 90 phantoms). Noisy images modeling various count levels (corresponding to different products of acquisition duration and administered activity) were generated by appropriately scaling these images and simulating Poisson noise. Acquisition duration was fixed; six count levels were simulated corresponding to projection images acquired using 25%, 50%, 75%, 100%, 125%, and 150% of the original weight-based administrated activity as computed using the North American Guidelines (Gelfand et al 2011 J. Nucl. Med. 52 318-22). Combined, a total number of 207 360 noisy projection images were generated, creating a realistic projection database for use in renal pediatric SPECT imaging research. The phantoms and projection datasets were used to calculate three surrogate indices for factors affecting image quality: renal count density, average radius of rotation, and scatter-to-primary ratio. Differences in these indices were seen across the phantoms for dosing based on current guidelines, and especially for the phantom modeling the newborn. We also performed an image quality study using an anthropomorphic model observer that demonstrates that the weight-based dose scaling does not equalize image quality as measured by the area under the receiver-operating characteristics curve. These studies suggest that a dosing procedure beyond weight-based scaling of administered activities is required to equalize image quality in pediatric renal SPECT.

Figure 1.

Sample coronal slices of the body reminder, cortex, medulla, pelvis, liver and spleen (from left to right) of a newborn 50^th height percentile male phantom.

Figure 2.

Sample transaxial images of the attenuation distribution for the (left to right) 10^th, 50^th, and 90^th height percentile versions of the male phantom for ages (top to bottom) 0 (newborn), 1, 5, 10, and 15 years showing variations in body habitus.

Figure 3.

Noise-free projection images of the kidney cortex, medulla, spleen, liver, pelvis, and body remainder for a male, reference-height, newborn phantom.

Figure 4.

Sample noisy posterior projection images from the various count levels. From top to bottom, shows kidneys for the 0, 1, 5, 10, and 15-year-old phantoms. From left to right, the simulated count levels were 25%, 50%, 75%, 100%, 125%, and 150% of those of the 2010 North American Consensus Dosing Guidelines.

Figure 5.

From left to right, the top row shows patient images from 1.2, 5, 9, and 16 year olds reconstructed using 2 iterations of 8 subsets of the OS-EM reconstruction with detector response compensation followed by a Gaussian filter with a FWHM of 0.5mm. The bottom row shows simulated images from 1, 5, 10, and 15 year olds reconstructed using the same methods.

Figure 6.

Sample lower pole defects in noise-free reconstructed images for newborn, 1-, 5-, 10-, and 15-year-old male phantoms with reference heights in coronal and sagittal views. The defect volumes for ages 1, 5, 10 and 15 were determined by matching their contrasts to the newborn.

Figure 7.

Sample reconstructed images from noisy projection data using FBP reconstruction followed by a post-reconstruction 3D Butterworth filter with an order of eight and cutoff frequency of 0.12 cycle/pixel. Negative values were mapped to zero in the display. From left to right, the bottom and top rows shows coronal images with and without, respectively, a (lower pole) defect for the newborn, 1-, 5-, 10-, and 15-year-old male phantoms at the 50^th height percentile. The volumes of these defects were chosen to be near the limits of clinical relevance and to have the same defect contrast.

Figure 8.

Average kidney count density obtained for three different height percentiles as a function of phantom age for male and female phantoms.

Figure 9.

Sample transaxial phantom images at mid-kidney level in 10^th, 50^th, and 90^th height percentile (from left to right) from the male phantom of age 0, 1, 5, 10, and 15 (from top to bottom) showing variations in body habitus.

Figure 10.

Average scatter-to-primary ratio obtained from three different height percentiles as a function of phantom age for male and female.

Figure 11.

Average camera radius of rotation obtained from three different height percentiles as a function of phantom age for male and female.

Figure 12.

Image quality result on a defect detection task for the 1- and 5-year-old phantoms. A 20% defect contrast was modeled for these patients.