Fast T2-weighted liver MRI: Image quality and solid focal lesions conspicuity using a deep learning accelerated single breath-hold HASTE fat-suppressed sequence - 30/09/22
, Rym Kharrat a, Pierre Zerbib a, Aurélien Massire d, Marcel Dominik Nickel e, Khalid Ambarki d, Edouard Reizine a, b, c, Laurence Baranes a, Benhalima Zegai a, Frederic Pigneur a, Hicham Kobeiter a, b, Alain Luciani a, b, c
Benvenuto su EM|consulte, il riferimento dei professionisti della salute.
Articolo gratuito.
Si connetta per beneficiarne
Highlights |
• | HASTEDL sequence reduces liver T2-weighted acquisition time at 1.5 T. |
• | HASTEDL improves image quality and focal liver lesion contrast-to-noise ratio, notably in patients with chronic liver disease. |
• | HASTEDL could be favorably embedded in abbreviated liver MRI protocols. |
Abstract |
Purpose |
Acceleration of MRI acquisitions and especially of T2-weighted sequences is essential to reduce the duration of MRI examinations but also kinetic artifacts in liver imaging. The purpose of this study was to compare the acquisition time and the image quality of a single-shot fat-suppressed turbo spin-echo (TSE) T2-weighted sequence with deep learning reconstruction (HASTEDL) with that of a fat-suppressed T2-weighted BLADE TSE sequence in patients with focal liver lesions.
Materials and methods |
Ninety-five patients (52 men, 43 women; mean age: 61 ± 14 [SD]; age range: 28–87 years) with 42 focal liver lesions (17 hepatocellular carcinomas, 10 sarcoidosis lesions, 9 myeloma lesions, 3 liver metastases and 3 focal nodular hyperplasias) who underwent liver MRI at 1.5 T including HASTEDL and BLADE sequences were retrospectively included. Overall image quality, noise level in the liver, lesion conspicuity and sharpness of liver lesion contours were assessed by two independent readers. Liver signal-to-noise ratio (SNR) and lesion contrast-to-noise ratio (CNR) were measured and compared between the two sequences, as well as the mean duration of the sequences (Student t-test or Wilcoxon test for paired data).
Results |
Median overall quality on HASTEDL images (3; IQR: 3, 3) was significantly greater than that on BLADE images (2; IQR: 1, 3) (P < 0.001). Median noise level in the liver on HASTEDL images (0; IQR: 0, 0.5) was significantly lower than that on BLADE images (1; IQR: 1, 2) (P < 0.001). On HASTEDL images, mean liver SNR (107.3 ± 39.7 [SD]) and mean focal liver lesion CNR (87.0 ± 76.6 [SD]) were significantly greater than those on BLADE images (67.1 ± 23.8 [SD], P < 0.001 and 48.6 ± 43.9 [SD], P = 0.027, respectively). Acquisition time was significantly shorter with the HASTEDL sequence (18 ± [0] s; range: 18–18 s) compared to BLADE sequence (152 ± 47 [SD] s; range: 87–263 s) (P < 0.001).
Conclusion |
By comparison with the BLADE sequence, HASTEDL sequence significantly reduces acquisition time while improving image quality, liver SNR and focal liver lesions CNR.
Il testo completo di questo articolo è disponibile in PDF.Keywords : Deep learning, Liver neoplasms, Magnetic resonance imaging
Abbreviations : CI, CNR, HASTEDL, HCC, IQR, MRI, ROI, SD, SI, SNR, TSE
Mappa
Vol 103 - N° 10
P. 479-485 - ottobre 2022 Ritorno al numero
Articolo precedente
- Detection of parametrial invasion in women with uterine cervical cancer using diffusion tensor imaging at 1.5T MRI
- Valerio Di Paola, Federica Perillo, Benedetta Gui, Luca Russo, Francesco Pierconti, Vincenzo Fiorentino, Rosa Autorino, Gabriella Ferrandina, Vincenzo Valentini, Giovanni Scambia, Riccardo Manfredi
- Association between contralateral background parenchymal enhancement on MRI and outcome in patients with unilateral invasive breast cancer receiving neoadjuvant chemotherapy
- Rossella Rella, Enida Bufi, Paolo Belli, Anna Rita Scrofani, Federica Petta, Alberto Borghetti, Fabio Marazzi, Vincenzo Valentini, Riccardo Manfredi
Benvenuto su EM|consulte, il riferimento dei professionisti della salute.