Implementation of absolute quantification in small-animal SPECT imaging: Phantom and animal studies.

Shabnam Khorasani Gerdekoohi,Kaveh Tanha,Naser Vosoughi,Pardis Ghafarian,Mohammad Reza Ay,Majid Assadi,Arman Rahmim

doi:10.1002/acm2.12094

Abstract

PurposePresence of photon attenuation severely challenges quantitative accuracy in single‐photon emission computed tomography (SPECT) imaging. Subsequently, various attenuation correction methods have been developed to compensate for this degradation. The present study aims to implement an attenuation correction method and then to evaluate quantification accuracy of attenuation correction in small‐animal SPECT imaging.MethodsImages were reconstructed using an iterative reconstruction method based on the maximum‐likelihood expectation maximization (MLEM) algorithm including resolution recovery. This was implemented in our designed dedicated small‐animal SPECT (HiReSPECT) system. For accurate quantification, the voxel values were converted to activity concentration via a calculated calibration factor. An attenuation correction algorithm was developed based on the first‐order Chang's method. Both phantom study and experimental measurements with four rats were used in order to validate the proposed method.ResultsThe phantom experiments showed that the error of −15.5% in the estimation of activity concentration in a uniform region was reduced to +5.1% when attenuation correction was applied. For in vivo studies, the average quantitative error of −22.8 ± 6.3% (ranging from −31.2% to −14.8%) in the uncorrected images was reduced to +3.5 ± 6.7% (ranging from −6.7 to +9.8%) after applying attenuation correction.ConclusionThe results indicate that the proposed attenuation correction algorithm based on the first‐order Chang's method, as implemented in our dedicated small‐animal SPECT system, significantly improves accuracy of the quantitative analysis as well as the absolute quantification.

Highlights

Preclinical single-photon emission computed tomography (SPECT) imaging is significantly utilized in present day imaging and research.[1,2,3] Quantification can expand capabilities of SPECT and play a significant role in drug development,[4,5] organ dosimetry,[6] and therapy response assessment.[7]
Calibration factors (CF) were obtained for five radius of rotation (ROR) and a function was fitted on these data; as a result, we obtained calibration factor (CF) for any other RORs that will be used in data acquisition
We significantly improve the quantitative accuracy of our system with a postprocessing attenuation correction method, instead of iterative methods

Summary

Introduction

Preclinical single-photon emission computed tomography (SPECT) imaging is significantly utilized in present day imaging and research.[1,2,3] Quantification can expand capabilities of SPECT and play a significant role in drug development,[4,5] organ dosimetry,[6] and therapy response assessment.[7]. The finding of Vanhove et al.[16] showed that quantitative errors in mice experiments could be reduced to À7.9 Æ 10.4% when attenuation and scatter corrections were applied. Wou et al.[17] developed a method for attenuation correction to improve the absolute quantification for the U-SPECT-II, a stationary multipinhole SPECT system for small-animal imaging. In their phantom experiments, a quantification error of À18.7% was reduced to À1.7% when including both scatter and attenuation corrections; by contrast, in animal experiments, the errors were between À6.3% and +4.3%. Due to the small size of mice, a uniform attenuation map may be sufficient for quantification

Objectives

Methods

Results

Conclusion