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Accelerated Diffusion-Weighted MRI of Rectal Cancer Using a Residual Convolutional Network
Mohaddese Mohammadi1, Elena A Kaye1, Or Alus1
1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Bioengineering (Basel, Switzerland)
|March 29, 2023
Summary
This study introduces a deep learning denoising method to speed up rectal cancer MRI scans. The technique allows for faster imaging with comparable or even improved diagnostic image quality.
Area of Science:
- Radiology
- Medical Imaging
- Artificial Intelligence
Background:
- Diffusion-weighted MRI (DW-MRI) is crucial for rectal cancer diagnosis.
- Acquiring high b-value DW-MRI is time-consuming, limiting clinical application.
- Accelerated acquisition techniques often compromise image quality.
Purpose of the Study:
- To develop and evaluate a deep learning-based denoising technique for accelerating high b-value DW-MRI in rectal cancer.
- To assess the feasibility of using fewer repetitions (NEX) for faster image acquisition.
- To compare the image quality of denoised accelerated scans against the clinical standard.
Main Methods:
- A denoising convolutional neural network (DCNN) with a combined L1-L2 loss function was developed.
- DCNN was trained on 85 rectal cancer patient datasets and tested on 20 datasets.
- Scans were acquired with varying NEX (1, 2, 4), corresponding to acceleration factors of 16, 8, and 4.
- Image quality was qualitatively assessed by expert radiologists.
Main Results:
- Denoised images with 8-fold acceleration (NEX=2) achieved image quality comparable to the clinical standard.
- Denoised images with 4-fold acceleration (NEX=4) surpassed the quality of the clinical standard.
- Expert readers reported similar or improved image quality for accelerated, denoised scans compared to reference scans.
- The technique effectively reduced noise in faster-acquired images.
Conclusions:
- Deep learning-based denoising can significantly accelerate high b-value DW-MRI acquisition for rectal cancer.
- Eightfold acceleration yields similar image quality, while fourfold acceleration provides superior quality compared to standard methods.
- This technique holds promise for improving diagnostic efficiency and accuracy in rectal cancer imaging.
