Native myocardial T mapping using inversion recovery T-weighted turbo field echo sequence.

Kida, Katsuhiro;Kurosaki, Takamasa;Fukui, Ryohei;Matsuura, Ryutaro;Goto, Sachiko;
Radiological physics and technology 2024
68
kida2024nativeradiological

Abstract

This study proposes the use of the inversion recovery T-weighted turbo field echo (IR-TTFE) sequence for myocardial T mapping and compares the results obtained with those of the modified Look-Locker inversion recovery (MOLLI) method for accuracy, precision, and reproducibility. A phantom containing seven vials with different T values was imaged, thereby comparing the T measurements between the inversion recovery spin-echo (IR-SE) technique, MOLLI, and the IR-TTFE. The accuracy, precision, and reproducibility of the T-mapping sequences were analyzed in a phantom study. Fifteen healthy subjects were recruited for the in vivo comparison of native myocardial T mapping using MOLLI and IR-TTFE sequences. After myocardium segmentation, the T value of the entire myocardium was calculated. In the phantom study, excellent accuracy was achieved using IR-TTFE for all T ranges. MOLLI displayed lower accuracy than IR-TTFE (p =0.016), substantially underestimating T at large T values (> 1000 ms). In the in vivo study, the first mean myocardial T values ± SD using MOLLI and IR-TTFE were 1306 ± 70 ms and 1484 ± 28 ms, respectively, and the second were 1297 ± 68 ms and 1474 ± 43 ms, respectively. The native myocardial T obtained with MOLLI was lower than that of IR-TTFE (p < 0.001). The reproducibility of native myocardial T mapping within the same sequence was not statistically significant (p = 0.11). This study demonstrates the utility and validity of myocardial T mapping using IR-TTFE, which is a common sequence. This method was found to have high accuracy and reproducibility.

Citation

ID: 278724
Ref Key: kida2024nativeradiological
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
278724
Unique Identifier:
10.1007/s12194-024-00795-w
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet