# Development and task-based evaluation of a scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT

## TL;DR

This paper introduces a deep learning-based attenuation correction method for myocardial perfusion SPECT that eliminates the need for additional transmission scans, reducing radiation and cost while maintaining diagnostic accuracy.

## Contribution

The study presents a novel scatter-window projection and deep learning approach for transmission-less attenuation correction in SPECT MPI, validated against traditional CT-based methods.

## Key findings

- SLAC method achieves similar ROC and AUC to CTAC in detecting perfusion defects.
- The proposed method reduces reliance on additional transmission scans.
- Results support clinical potential of transmission-less attenuation correction.

## Abstract

Attenuation compensation (AC) is beneficial for visual interpretation tasks in single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). However, traditional AC methods require the availability of a transmission scan, most often a CT scan. This approach has the disadvantages of increased radiation dose, increased scanner cost, and the possibility of inaccurate diagnosis in cases of misregistration between the SPECT and CT images. Further, many SPECT systems do not include a CT component. To address these issues, we developed a Scatter-window projection and deep Learning-based AC (SLAC) method to perform AC without a separate transmission scan. To investigate the clinical efficacy of this method, we then objectively evaluated the performance of this method on the clinical task of detecting perfusion defects on MPI in a retrospective study with anonymized clinical SPECT/CT stress MPI images. The proposed method was compared with CT-based AC (CTAC) and no-AC (NAC) methods. Our results showed that the SLAC method yielded an almost overlapping receiver operating characteristic (ROC) plot and a similar area under the ROC (AUC) to the CTAC method on this task. These results demonstrate the capability of the SLAC method for transmission-less AC in SPECT and motivate further clinical evaluation.