3D Isotropic Super-resolution Prostate MRI Using Generative Adversarial Networks and Unpaired Multiplane Slices

We developed a deep learning–based super-resolution model for prostate MRI. 2D T2-weighted turbo spin echo (T2w-TSE) images are the core anatomical sequences in a multiparametric MRI (mpMRI) protocol. These images have coarse through-plane resolution, are non-isotropic, and have long acquisition times (approximately 10–15 min). The model we developed aims to preserve high-frequency details that are normally lost after 3D reconstruction. We propose a novel framework for generating isotropic volumes using generative adversarial networks (GAN) from anisotropic 2D T2w-TSE and single-shot fast spin echo (ssFSE) images. The CycleGAN model used in this study allows the unpaired dataset mapping to reconstruct super-resolution (SR) volumes. Fivefold cross-validation was performed. The improvements from patch-to-volume reconstruction (PVR) to SR are 80.17%, 63.77%, and 186% for perceptual index (PI), RMSE, and SSIM, respectively; the improvements from slice-to-volume reconstruction (SVR) to SR are 72.41%, 17.44%, and 7.5% for PI, RMSE, and SSIM, respectively. Five ssFSE cases were used to test for generalizability; the perceptual quality of SR images surpasses the in-plane ssFSE images by 37.5%, with 3.26% improvement in SSIM and a higher RMSE by 7.92%. SR images were quantitatively assessed with radiologist Likert scores. Our isotropic SR volumes are able to reproduce high-frequency detail, maintaining comparable image quality to in-plane TSE images in all planes without sacrificing perceptual accuracy. The SR reconstruction networks were also successfully applied to the ssFSE images, demonstrating that high-quality isotropic volume achieved from ultra-fast acquisition is feasible.

     

Dynamic infrared imaging for the detection of malignancy

The potential for malignancy detection using dynamic infrared imaging (DIRI) has been investigated in an animal model of human malignancy. Malignancy was apparent in images formed at the vasomotor and cardiogenic frequencies of tumour bearing mice. The observation of malignancy was removed by the administration of an agent that blocks vasodilation caused by nitric oxide (NO). Image patterns similar to those that characterize malignancy could be mimicked in normal mice using an NO producing agent. Apparently DIRI allows for cancer detection in this model through vasodilation caused by malignancy generated NO. Dynamic infrared detection of vasomotor and cardiogenic surface perfusion was validated in human subjects by a comparison with laser Doppler flowmetry (LDF). Dynamic infrared imaging technology was then applied to breast cancer detection. It is shown that dynamic infrared images formed at the vasomotor and cardiogenic frequencies of the normal and malignant breast have image pattern differences, which may allow for breast cancer detection.     

High-resolution simulation of B0 field conditions in the human heart from segmented computed tomography images

B₀ inhomogeneity leads to imaging artifacts in cardiac magnetic resonance imaging (MRI), in particular dark band artifacts with steady-state free precession pulse sequences. The limited spatial resolution of MR-derived in vivo B₀ maps and the lack of population data prevent systematic analysis of the problem at hand and the development of optimized B₀ shim strategies. We used readily available clinical computed tomography (CT) images to simulate the B₀ conditions in the human heart at high spatial resolution. Calculated B₀ fields showed consistency with MRI-based B₀ measurements. The B₀ maps for both the simulations and in vivo measurements showed local field inhomogeneities in the vicinity of lung tips with dominant Z3 spherical harmonic terms in the field distribution. The presented simulation approach allows for the derivation of B₀ field conditions at high spatial resolution from CT images and enables the development of subject- and population-specific B₀ shim strategies for the human heart.     

Cardiac-Specific Conversion Factors to Estimate Radiation Effective Dose From Dose-Length Product in Computed Tomography

Objectives

This study sought to determine updated conversion factors (k-factors) that would enable accurate estimation of radiation effective dose (ED) for coronary computed tomography angiography (CTA) and calcium scoring performed on 12 contemporary scanner models and current clinical cardiac protocols and to compare these methods to the standard chest k-factor of 0.014 mSv·mGy^?1cm^?1.