Development of a population of digital brain phantoms for radionuclide imaging research in Parkinson's disease

Abstract

Purpose: Dopamine transporter (DAT) SPECT is a powerful tool for early diagnosis of Parkinson's disease (PD), while digital phantoms and Monte Carlo (MC) simulations can serve as important research tools. This study aims to develop a novel digital brain phantom population for ^99mTc-TRODAT-1 (^99mTc) and ¹²³I-ioflupane (¹²³I) brain SPECT, and to assess attenuation correction (AC) and scatter correction (SC) in DAT SPECT.

Methods: Striatum, brain background (gray and white matter), and cold regions (skull and cerebrospinal fluid) were segmented from 200 T1 MRI brain images from the PPMI dataset. Striatal binding ratio (SBR) values were retrospectively collected from 200 ¹²³I and 100 ^99mTc DAT SPECT patients with suspected PD symptoms from PPMI and a local hospital, respectively. Various activity values were assigned to the randomly paired segmented regions according to a range of SBR values based on the SPECT Visual Interpretation (VI) assessment scheme. The new phantom population was combined with MC simulation tool SIMIND to generate realistic noisy projections. Quantitative accuracy of reconstructed images with attenuation correction (AC) and scatter correction (SC) was assessed.

Results: A population of 1000 normal and abnormal PD phantoms was generated for both tracers. Visual comparisons and quantitative analyses demonstrated that simulated data exhibited high similarity to clinical data. Reconstructed images with AC + SC achieved the best quantitative results, followed by AC only, without AC and SC, and SC only.

Conclusion: The developed digital DAT SPECT phantom population can be served for a wide range of PD applications. Attenuation impacts image quality the most in DAT SPECT, while AC + SC is effective to enhance image quality and quantitative accuracy of DAT SPECT.

Keywords: Attenuation correction; DAT SPECT; Monte Carlo simulation; Parkinson’s disease; Phantom population; Scatter correction..

Fig. 1

Brain regions contribute to image contrast on DAT SPECT in different PD stages according to SPECT VI assessment scheme are indicated from sample MRI images. NC: Normal category; ANC1: Abnormal category 1; ANC2: Abnormal category 2; ANC3: Abnormal category 3

Fig. 2

Phantom population generation workflow

Fig. 3

Sample ¹²³I and ^99mTc phantoms with different VI categories in SPECT

Fig. 4

Sample simulation and clinical projections, as well as corresponding reconstructed images with AC + SC for ^99mTc and ¹²³I in different VI categories. A uniform region marked by the yellow squares is used for the COV analysis in projections. For reconstruction images, a uniform cerebellum region marked by the red squares is employed for COV/NPS evaluation and served as the reference region in the SBR calculation

Fig. 5

Noise power spectrum (NPS) of (a) ¹²³I and (b) ^99mTc reconstructed images for simulation and clinical data

Fig. 6

NMSE and SSIM1 results between reconstructed simulation and clinical data, as well as among clinical data for different VI categories for the DAT images of (a) ¹²³I and (b) ^99mTc. Mann-Whitney U test was evaluated and found no significant difference between two groups

Fig. 7

(a) Sample simulated reconstruction images with AC + SC, AC only, SC only, NOC, and GS for ¹²³I and ^99mTc distributions. (b) Profiles across the striatum location (yellow line in (a)) for different correction methods for 2 tracers

Fig. 8

Box plots of SSIM2, MAE, and SBRE results between GS and AC + SC, AC only, SC only, and NOC for the two tracers in the simulated reconstructed DAT images. ns: p > 0.05, *: p < 0.05, ****: p < 0.0001