Fast T2-Weighted Imaging With Deep Learning-Based Reconstruction: Evaluation of Image Quality and Diagnostic Performance in Patients Undergoing Radical Prostatectomy

被引：47

作者：

Park, Jae Chun ^{[1
,2
,3
]}

Park, Kye Jin ^{[1
,2
]}

Park, Mi Yeon ^{[1
,2
]}

Kim, Mi-Hyun ^{[1
,2
]}

Kim, Jeong Kon ^{[1
,2
]}

机构：

[1] Univ Ulsan, Asan Med Ctr, Coll Med, Dept Radiol, Seoul, South Korea

[2] Univ Ulsan, Asan Med Ctr, Coll Med, Res Inst Radiol, Seoul, South Korea

[3] Kosin Univ, Gospel Hosp, Dept Radiol, Coll Med, Busan, South Korea

来源：

JOURNAL OF MAGNETIC RESONANCE IMAGING | 2022年 / 55卷 / 06期

关键词：

prostate; deep learning reconstruction; fast MRI; short MRI; MRI; CANCER; MEN;

D O I：

10.1002/jmri.27992

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

Background Deep learning-based reconstruction (DLR) can potentially improve image quality by reduction of noise, thereby enabling fast acquisition of magnetic resonance imaging (MRI). However, a systematic evaluation of image quality and diagnostic performance of MRI using short acquisition time with DLR has rarely been investigated in men with prostate cancer. Purpose To assess the image quality and diagnostic performance of MRI using short acquisition time with DLR for the evaluation of extraprostatic extension (EPE). Study Type Retrospective. Population One hundred and nine men. Field Strength/Sequence 3 T; turbo spin echo T2-weighted images (T2WI), echo-planar diffusion-weighted, and spoiled gradient echo dynamic contrast-enhanced images. Assessment To compare image quality, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and subjective analysis using Likert scales on three T2WIs (MRI using conventional acquisition time, MRI using short acquisition time [fast MRI], and fast MRI with DLR) were performed. The diagnostic performance for EPE was evaluated by three independent readers. Statistical Tests SNR, CNR, and image quality scores across the three imaging protocols were compared using Friedman tests. The diagnostic performance for EPE was assessed using the area under receiver operating characteristic curves (AUCs). P < 0.05 was considered statistically significant. Results Fast MRI with DLR demonstrated significantly higher SNR (mean +/- SD, 14.7 +/- 6.8 vs. 8.8 +/- 4.9) and CNR (mean +/- SD, 6.5 +/- 6.3 vs. 3.4 +/- 3.6) values and higher image quality scores (median, 4.0 vs. 3.0 for three readers) than fast MRI. The AUCs for EPE were significantly higher with the use of DLR (0.86 vs. 0.75 for reader 2 and 0.82 vs. 0.73 for reader 3) compared with fast MRI, whereas differences were not significant for reader 1 (0.81 vs. 0.74; P = 0.09). Data Conclusion DLR may be useful in reducing the acquisition time of prostate MRI without compromising image quality or diagnostic performance. Level of Evidence 4 Technical Efficacy Stage 3

引用

页码：1735 / 1744

页数：10

共 30 条

[1] MRI-Targeted, Systematic, and Combined Biopsy for Prostate Cancer Diagnosis [J].

Ahdoot, Michael ;

Wilbur, Andrew R. ;

Reese, Sarah E. ;

Lebastchi, Amir H. ;

Mehralivand, Sherif ;

Gomella, Patrick T. ;

Bloom, Jonathan ;

Gurram, Sandeep ;

Siddiqui, Minhaj ;

Pinsky, Paul ;

Parnes, Howard ;

Linehan, W. Marston ;

Merino, Maria ;

Choyke, Peter L. ;

Shih, Joanna H. ;

Turkbey, Baris ;

Wood, Bradford J. ;

Pinto, Peter A. .

NEW ENGLAND JOURNAL OF MEDICINE, 2020, 382 (10) :917-928

[2] Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study [J].

Ahmed, Hashim U. ;

Bosaily, Ahmed El-Shater ;

Brown, Louise C. ;

Gabe, Rhian ;

Kaplan, Richard ;

Parmar, Mahesh K. ;

Collaco-Moraes, Yolanda ;

Ward, Katie ;

Hindley, Richard G. ;

Freeman, Alex ;

Kirkham, Alex P. ;

Oldroyd, Robert ;

Parker, Chris ;

Emberton, Mark .

LANCET, 2017, 389 (10071) :815-822

[3] Assessment of the Diagnostic Accuracy of Biparametric Magnetic Resonance Imaging for Prostate Cancer in Biopsy-Naive Men The Biparametric MRI for Detection of Prostate Cancer (BIDOC) Study [J].

Boesen, Lars ;

Norgaard, Nis ;

Logager, Vibeke ;

Balslev, Ingegerd ;

Bisbjerg, Rasmus ;

Thestrup, Karen-Cecilie ;

Winther, Mads D. ;

Jakobsen, Henrik ;

Thomsen, Henrik S. .

JAMA NETWORK OPEN, 2018, 1 (02)

[4] ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition, interpretation and radiologists' training [J].

de Rooij, Maarten ;

Israel, Bas ;

Tummers, Marcia ;

Ahmed, Hashim U. ;

Barrett, Tristan ;

Giganti, Francesco ;

Hamm, Bernd ;

Logager, Vibeke ;

Padhani, Anwar ;

Panebianco, Valeria ;

Puech, Philippe ;

Richenberg, Jonathan ;

Rouviere, Olivier ;

Salomon, Georg ;

Schoots, Ivo ;

Veltman, Jeroen ;

Villeirs, Geert ;

Walz, Jochen ;

Barentsz, Jelle O. .

EUROPEAN RADIOLOGY, 2020, 30 (10) :5404-5416

[5] Population-Based Prostate Cancer Screening With Magnetic Resonance Imaging or Ultrasonography The IP1-PROSTAGRAM Study [J].

Eldred-Evans, David ;

Burak, Paula ;

Connor, Martin J. ;

Day, Emily ;

Evans, Martin ;

Fiorentino, Francesca ;

Gammon, Martin ;

Hosking-Jervis, Feargus ;

Klimowska-Nassar, Natalia ;

McGuire, William ;

Padhani, Anwar R. ;

Prevost, A. Toby ;

Price, Derek ;

Sokhi, Heminder ;

Tam, Henry ;

Winkler, Mathias ;

Ahmed, Hashim U. .

JAMA ONCOLOGY, 2021, 7 (03) :395-402

[6] Deep learning-accelerated T2-weighted imaging of the prostate: Reduction of acquisition time and improvement of image quality [J].

Gassenmaier, Sebastian ;

Afat, Saif ;

Nickel, Dominik ;

Mostapha, Mahmoud ;

Herrmann, Judith ;

Othman, Ahmed E. .

EUROPEAN JOURNAL OF RADIOLOGY, 2021, 137

[7] Learning a variational network for reconstruction of accelerated MRI data [J].

Hammernik, Kerstin ;

Klatzer, Teresa ;

Kobler, Erich ;

Recht, Michael P. ;

Sodickson, Daniel K. ;

Pock, Thomas ;

Knoll, Florian .

MAGNETIC RESONANCE IN MEDICINE, 2018, 79 (06) :3055-3071

[8] Reducing acquisition time in clinical MRI by data undersampling and compressed sensing reconstruction [J].

Hollingsworth, Kieren Grant .

PHYSICS IN MEDICINE AND BIOLOGY, 2015, 60 (21) :R297-R322

[9] MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis [J].

Kasivisvanathan, V ;

Rannikko, A. S. ;

Borghi, M. ;

Panebianco, V ;

Mynderse, L. A. ;

Vaarala, M. H. ;

Briganti, A. ;

Budaus, L. ;

Hellawell, G. ;

Hindley, R. G. ;

Roobol, M. J. ;

Eggener, S. ;

Ghei, M. ;

Villers, A. ;

Bladou, F. ;

Villeirs, G. M. ;

Virdi, J. ;

Boxler, S. ;

Robert, G. ;

Singh, P. B. ;

Venderink, W. ;

Hadaschik, B. A. ;

Ruffion, A. ;

Hu, J. C. ;

Margolis, D. ;

Crouzet, S. ;

Klotz, L. ;

Taneja, S. S. ;

Pinto, P. ;

Gill, I ;

Allen, C. ;

Giganti, F. ;

Freeman, A. ;

Morris, S. ;

Punwani, S. ;

Williams, N. R. ;

Brew-Graves, C. ;

Deeks, J. ;

Takwoingi, Y. ;

Emberton, M. ;

Moore, C. M. .

NEW ENGLAND JOURNAL OF MEDICINE, 2018, 378 (19) :1767-1777

[10] Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting [J].

Kim, Minjae ;

Kim, Ho Sung ;

Kim, Hyun Jin ;

Park, Ji Eun ;

Park, Seo Young ;

Kim, Young-Hoon ;

Kim, Sang Joon ;

Lee, Joonsung ;

Lebel, Marc R. .

RADIOLOGY, 2021, 298 (01) :114-122

← 1 2 3 →