# Simultaneous reduction of radiation dose and scatter-to-primary ratio using a truncated detector and advanced algorithms for dedicated cone-beam breast CT

## TL;DR

This study shows that using a narrower detector and a new algorithm in breast CT can reduce radiation and scatter while keeping image quality.

## Contribution

The study introduces a self-supervised algorithm (AFN) that enables narrower detectors in breast CT without image artifacts.

## Key findings

- AFN algorithm reconstructed images without artifacts at detector width of 536 pixels.
- AFN with 536-pixel detector reduced radiation dose and scatter by 37.85% and 33.46%, respectively.
- AFN maintained image quality comparable to full-width detector reconstructions.

## Abstract

Objective. To determine the minimum detector width along the fan-angle direction in offset-detector cone-beam breast CT for multiple advanced reconstruction algorithms and to investigate the effect on radiation dose, scatter, and image quality. Approach. Complete sinograms (m × n = 1024 × 768 pixels) of 30 clinical breast CT datasets previously acquired on a clinical-prototype cone-beam breast CT system were reconstructed using Feldkamp-Davis-Kress (FDK) algorithm and served as the reference. Complete sinograms were retrospectively truncated to varying widths to understand the limits of four image reconstruction algorithms—FDK with redundancy weighting (FDK-W), compressed-sensing based FRIST, fully-supervised MS-RDN, and self-supervised AFN. Upon determining the truncation limits, numerical phantoms generated by segmenting the reference reconstructions into skin, adipose, and fibroglandular tissues were used to determine the radiation dose and scatter-to-primary ratio (SPR) using Monte Carlo simulations. Main results. FDK-W, FRIST, and MS-RDN showed artifacts when m < 596, whereas AFN reconstructed images without artifacts for m > = 536. Reducing the detector width reduced signal-difference to noise ratio (SDNR) for FDK-W, whereas FRIST, MS-RDN and AFN maintained or improved SDNR. Reference reconstruction and AFN with m = 536 had similar quantitative measures of image quality. Significance. For the 30 cases, AFN with m = 536 reduced the radiation dose and SPR by 37.85% and 33.46%, respectively, compared to the reference. Qualitative and quantitative image quality indicate the feasibility of AFN for offset-detector cone-beam breast CT. Radiation dose and SPR were simultaneously reduced with a 536 × 768 detector and when used in conjunction with AFN algorithm had similar image quality as the reference reconstruction.