Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study

• Published in: Journal of Nuclear Medicine Vol. 62; no. 11; pp. 1645 - 1652
• Main Authors: Yang, Jaewon, Shi, Luyao, Wang, Rui, Miller, Edward J., Sinusas, Albert J., Liu, Chi, Gullberg, Grant T., Seo, Youngho
• Format: Journal Article
• Language: English
• Published: United States Society of Nuclear Medicine 01.11.2021
• Subjects: Aged; Artificial neural networks; Attenuation; Cadmium; Cameras; Computed tomography; Deep Learning; Feasibility Studies; Female; Field of view; Heart; Heart - diagnostic imaging; Humans; Image processing; Image Processing, Computer-Assisted - methods; Image quality; Image reconstruction; Male; Middle Aged; Myocardial Perfusion Imaging - methods; Neural networks; Perfusion; Physics and Instrumentation: SPECT and SPECT/CT; Radiation dosage; Retrospective Studies; Scanners; Single photon emission computed tomography; Single Photon Emission Computed Tomography Computed Tomography - methods; Tellurides; Tomography, Emission-Computed, Single-Photon - methods; deep learning; attenuation correction; cardiac SPECT; MPI
• ISSN: 0161-5505; 1535-5667; 2159-662X; 1535-5667
• DOI: 10.2967/jnumed.120.256396

Dedicated cardiac SPECT scanners with cadmium-zinc-telluride cameras have shown capabilities for shortened scan times or reduced radiation doses, as well as improved image quality. Since most dedicated scanners do not have integrated CT, image quantification with attenuation correction (AC) is challenging and artifacts are routinely encountered in daily clinical practice. In this work, we demonstrated a direct AC technique using deep learning (DL) for myocardial perfusion imaging (MPI). In an institutional review board-approved retrospective study, 100 cardiac SPECT/CT datasets with Tc-tetrofosmin, obtained using a scanner specifically with a small field of view, were collected at the Yale New Haven Hospital. A convolutional neural network was used for generating DL-based attenuation-corrected SPECT (SPECT ) directly from noncorrected SPECT (SPECT ) without undergoing an additional image reconstruction step. The accuracy of SPECT was evaluated by voxelwise and segmentwise analyses against the reference, CT-based AC (SPECT ), using the 17-segment myocardial model of the American Heart Association. Polar maps of representative (best, median, and worst) cases were visually compared to illustrate potential benefits and pitfalls of the DL approach. The voxelwise correlations with SPECT were 92.2% ± 3.7% (slope, 0.87; = 0.81) and 97.7% ± 1.8% (slope, 0.94; = 0.91) for SPECT and SPECT , respectively. The segmental errors of SPECT scattered from -35% to 21% ( < 0.001), whereas the errors of SPECT stayed mostly within ±10% ( < 0.001). The average segmental errors (mean ± SD) were -6.11% ± 8.06% and 0.49% ± 4.35% for SPECT and SPECT , respectively. The average absolute segmental errors were 7.96% ± 6.23% and 3.31% ± 2.87% for SPECT and SPECT , respectively. Review of polar maps revealed successful reduction of attenuation artifacts; however, the performance of SPECT was not consistent for all subjects, likely because of different amounts of attenuation and different uptake patterns. We demonstrated the feasibility of direct AC using DL for SPECT MPI. Overall, our DL approach reduced attenuation artifacts substantially compared with SPECT , justifying further studies to establish safety and consistency for clinical applications in stand-alone SPECT systems suffering from attenuation artifacts.