A Projection-Domain Low-Count Quantitative SPECT Method for α-Particle-Emitting Radiopharmaceutical Therapy

Abstract

Single-photon emission-computed tomography (SPECT) provides a mechanism to estimate regional isotope uptake in lesions and at-risk organs after administration of α-particle-emitting radiopharmaceutical therapies (α-RPTs). However, this estimation task is challenging due to the complex emission spectra, the very low number of detected counts (~20 times lower than in conventional SPECT), the impact of stray-radiation-related noise at these low counts, and the multiple image-degrading processes in SPECT. The conventional reconstruction-based quantification methods are observed to be erroneous for α-RPT SPECT. To address these challenges, we developed a low-count quantitative SPECT (LC-QSPECT) method that directly estimates the regional activity uptake from the projection data (obviating the reconstruction step), compensates for stray-radiation-related noise, and accounts for the radioisotope and SPECT physics, including the isotope spectra, scatter, attenuation, and collimator-detector response, using a Monte Carlo-based approach. The method was validated in the context of 3-D SPECT with ²²³Ra, a commonly used radionuclide for α-RPT. Validation was performed using both realistic simulation studies, including a virtual clinical trial, and synthetic and 3-D-printed anthropomorphic physical-phantom studies. Across all studies, the LC-QSPECT method yielded reliable regional-uptake estimates and outperformed the conventional ordered subset expectation-maximization (OSEM)-based reconstruction and geometric transfer matrix (GTM)-based post-reconstruction partial-volume compensation methods. Furthermore, the method yielded reliable uptake across different lesion sizes, contrasts, and different levels of intralesion heterogeneity. Additionally, the variance of the estimated uptake approached the Cramér-Rao bound-defined theoretical limit. In conclusion, the proposed LC-QSPECT method demonstrated the ability to perform reliable quantification for α-RPT SPECT.

Keywords: Radium-223; low counts; quantitative single-photon emission-computed tomography (SPECT); regional quantification; α-particle therapies.

Fig. 1.

Digital (a) activity map and (b) attenuation map for the pelvic region generated using the anthropomorphic XCAT phantom.

Fig. 2.

Lesions with different degrees of spatial heterogeneity.

Fig. 3.

(a) CT image of the NEMA phantom. (b) Photograph of the 3-D printed vertebrae phantom.

Fig. 4.

Projections of the NEMA phantom and the profiles along the yellow-dashed lines in the projections acquired at the four angular positions using the scanner and simulated SPECT system.

Fig. 5.

Normalized error in the estimated activity uptake in the lesion region with five different diameters as a function of the iteration number of the LC-QSPECT method.

Fig. 6.

(a) Absolute ensemble NB and (b) ensemble NRMSE of the estimated uptake across different regions using the different methods in the VCT simulating a ²²³Ra imaging study. (c) A violin plot showing the distribution of the normalized error (normalized by dividing by the true value) using the proposed method across all 50 patients.

Fig. 7.

Comparing the NSD of the regional activity estimates obtained from the LC-QSPECT method with the lower bound for the NSD as defined by the CRB.

Fig. 8.

(a) Absolute NB, (b) NSD, and (c) NRMSE between the true and estimated lesion uptake as a function of the lesion diameter in the realistic simulation study.

Fig. 9.

(a) Absolute NB and (b) NSD of the estimated lesion uptake as a function of the LBUR in the realistic simulation study.

Fig. 10.

(a) Absolute NB and (b) NSD of the estimated lesion uptake as a function of different amounts of intralesion heterogeneity as quantified using the entropy parameter.

Fig. 11.

Normalized absolute error of regional-uptake estimates of the NEMA phantom using the LC-QSPECT, GTM, and OSEM-based methods.