Dataset Information

Quantitative MRI Musculoskeletal Techniques: An Update.

ABSTRACT: OBJECTIVE. For many years, MRI of the musculoskeletal system has relied mostly on conventional sequences with qualitative analysis. More recently, using quantitative MRI applications to complement qualitative imaging has gained increasing interest in the MRI community, providing more detailed physiologic or anatomic information. CONCLUSION. In this article, we review the current state of quantitative MRI, technical and software advances, and the most relevant clinical and research musculoskeletal applications of quantitative MRI.

SUBMITTER: de Mello R

PROVIDER: S-EPMC6706325 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantitative MRI Musculoskeletal Techniques: An Update.

de Mello Ricardo R Ma Yajun Y Ji Yang Y Du Jiang J Chang Eric Y EY

AJR. American journal of roentgenology 20190417 3

<b>OBJECTIVE.</b> For many years, MRI of the musculoskeletal system has relied mostly on conventional sequences with qualitative analysis. More recently, using quantitative MRI applications to complement qualitative imaging has gained increasing interest in the MRI community, providing more detailed physiologic or anatomic information. <b>CONCLUSION.</b> In this article, we review the current state of quantitative MRI, technical and software advances, and the most relevant clinical and research ...[more]

PMID: 30995086

Similar Datasets

Project description:PURPOSE:To develop a super-resolution technique using convolutional neural networks for generating thin-slice knee MR images from thicker input slices, and compare this method with alternative through-plane interpolation methods. METHODS:We implemented a 3D convolutional neural network entitled DeepResolve to learn residual-based transformations between high-resolution thin-slice images and lower-resolution thick-slice images at the same center locations. DeepResolve was trained using 124 double echo in steady-state (DESS) data sets with 0.7-mm slice thickness and tested on 17 patients. Ground-truth images were compared with DeepResolve, clinically used tricubic interpolation, and Fourier interpolation methods, along with state-of-the-art single-image sparse-coding super-resolution. Comparisons were performed using structural similarity, peak SNR, and RMS error image quality metrics for a multitude of thin-slice downsampling factors. Two musculoskeletal radiologists ranked the 3 data sets and reviewed the diagnostic quality of the DeepResolve, tricubic interpolation, and ground-truth images for sharpness, contrast, artifacts, SNR, and overall diagnostic quality. Mann-Whitney U tests evaluated differences among the quantitative image metrics, reader scores, and rankings. Cohen's Kappa (?) evaluated interreader reliability. RESULTS:DeepResolve had significantly better structural similarity, peak SNR, and RMS error than tricubic interpolation, Fourier interpolation, and sparse-coding super-resolution for all downsampling factors (p?<?.05, except 4?×?and 8?×?sparse-coding super-resolution downsampling factors). In the reader study, DeepResolve significantly outperformed (p?<?.01) tricubic interpolation in all image quality categories and overall image ranking. Both readers had substantial scoring agreement (??=?0.73). CONCLUSION:DeepResolve was capable of resolving high-resolution thin-slice knee MRI from lower-resolution thicker slices, achieving superior quantitative and qualitative diagnostic performance to both conventionally used and state-of-the-art methods.

Dataset Information

Quantitative MRI Musculoskeletal Techniques: An Update.

Publications

Quantitative MRI Musculoskeletal Techniques: An Update.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure