著者

Hitomi Numamoto Koji Fujimoto Kanae Kawai Miyake Yasutaka Fushimi Sachi Okuchi Rimika Imai Hiroki Kondo Tsuneo Saga Yuji Nakamoto

出版者

Japanese Society for Magnetic Resonance in Medicine

雑誌

Magnetic Resonance in Medical Sciences (ISSN:13473182)

巻号頁・発行日

pp.mp.2023-0102, (Released:2023-11-10)

参考文献数

20

被引用文献数

1

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Purpose: To compare image distortion and reproducibility of quantitative values between reverse encoding distortion correction (RDC) diffusion-weighted imaging (DWI) and conventional DWI techniques in a phantom study and in healthy volunteers.Methods: This prospective study was conducted with the approval of our institutional review board. Written informed consent was obtained from each participant. RDC-DWIs were created from images obtained at 3T in three orthogonal directions in a phantom and in 10 participants (mean age, 70.9 years; age range, 63–83 years). Images without distortion correction (noDC-DWI) and those corrected with B0 (B0c-DWI) were also created. To evaluate distortion, coefficients of variation were calculated for each voxel and ROIs were placed at four levels of the brain. To evaluate the reproducibility of apparent diffusion coefficient (ADC) measurements, intra- and inter-scan variability (%CVADC) were calculated from repeated scans of the phantom. Analysis was performed using Wilcoxon signed-rank test with Bonferroni correction, and P < 0.05 was considered statistically significant.Results: In the phantom, distortion was less in RDC-DWI than in B0c-DWI (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). Intra-scan %CVADC was within 1.30%, and inter-scan %CVADC was within 2.99%. In the volunteers, distortion was less in RDC-DWI than in B0c-DWI in three of four locations (P < 0.006), and was less in B0c-DWI than in noDC-DWI (P < 0.006). At the middle cerebellar peduncle, distortion was less in RDC-DWI than in noDC-DWI (P < 0.006), and was less in noDC-DWI than in B0c-DWI (P < 0.0177).Conclusion: In both the phantom and in volunteers, distortion was the least in RDC-DWI than in B0c-DWI and noDC-DWI.

著者

Noriyuki Fujima Koji Kamagata Daiju Ueda Shohei Fujita Yasutaka Fushimi Masahiro Yanagawa Rintaro Ito Takahiro Tsuboyama Mariko Kawamura Takeshi Nakaura Akira Yamada Taiki Nozaki Tomoyuki Fujioka Yusuke Matsui Kenji Hirata Fuminari Tatsugami Shinji Naganawa

出版者

Japanese Society for Magnetic Resonance in Medicine

雑誌

Magnetic Resonance in Medical Sciences (ISSN:13473182)

巻号頁・発行日

pp.rev.2023-0047, (Released:2023-08-01)

参考文献数

123

被引用文献数

4

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Due primarily to the excellent soft tissue contrast depictions provided by MRI, the widespread application of head and neck MRI in clinical practice serves to assess various diseases. Artificial intelligence (AI)-based methodologies, particularly deep learning analyses using convolutional neural networks, have recently gained global recognition and have been extensively investigated in clinical research for their applicability across a range of categories within medical imaging, including head and neck MRI. Analytical approaches using AI have shown potential for addressing the clinical limitations associated with head and neck MRI. In this review, we focus primarily on the technical advancements in deep-learning-based methodologies and their clinical utility within the field of head and neck MRI, encompassing aspects such as image acquisition and reconstruction, lesion segmentation, disease classification and diagnosis, and prognostic prediction for patients presenting with head and neck diseases. We then discuss the limitations of current deep-learning-based approaches and offer insights regarding future challenges in this field.

著者

Azusa Sakurama Yasutaka Fushimi Satoshi Nakajima Akihiko Sakata Takuya Hinoda Sonoko Oshima Sayo Otani Krishna Pandu Wicaksono Wei Liu Takakuni Maki Tomohisa Okada Ryosuke Takahashi Yuji Nakamoto

出版者

Japanese Society for Magnetic Resonance in Medicine

雑誌

Magnetic Resonance in Medical Sciences (ISSN:13473182)

巻号頁・発行日

pp.mp.2021-0065, (Released:2021-10-01)

参考文献数

40

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Purpose: To compare reliability and elucidate clinical application of magnetization-prepared rapid gradient-echo (MPRAGE) with 9-fold acceleration by using wave-controlled aliasing in parallel imaging (Wave-CAIPI 3 × 3) in comparison to conventional MPRAGE accelerated by using generalized autocalibrating partially parallel acquisition (GRAPPA) 2 × 1.Methods: A total of 26 healthy volunteers and 33 patients were included in this study. Subjects were scanned with two MPRAGEs, GRAPPA 2 × 1 and Wave-CAIPI 3 × 3 acquired in 5 min 21 s and 1 min 42 s, respectively, on a 3T MR scanner. Healthy volunteers underwent additional two MPRAGEs (CAIPI 3 × 3 and GRAPPA 3 × 3). The image quality of the four MPRAGEs was visually evaluated with a 5-point scale in healthy volunteers, and the SNR of four MPRAGEs was also calculated by measuring the phantom 10 times with each MPRAGE. Based on the results of the visual evaluation, voxel-based morphometry (VBM) analyses, including subfield analysis, were performed only for GRAPPA 2 × 1 and Wave-CAIPI 3 × 3. Correlation of segmentation results between GRAPPA 2 × 1 and Wave-CAIPI 3 × 3 was assessed.Results: In visual evaluations, scores for MPRAGE GRAPPA 2 × 1 (mean rank: 4.00) were significantly better than those for Wave-CAIPI 3 × 3 (mean rank: 3.00), CAIPI 3 × 3 (mean rank: 1.83), and GRAPPA 3 × 3 (mean rank: 1.17), and scores for Wave-CAIPI 3×3 were significantly better than those for CAIPI 3 × 3 and GRAPPA 3 × 3. Image noise was evident at the center for additional MPRAGE CAIPI 3 × 3 and GRAPPA 3 × 3. The correlation of segmentation results between GRAPPA 2 × 1 and Wave-CAIPI 3 × 3 was higher than 0.85 in all VOIs except globus pallidus. Subfield analysis of hippocampus also showed a high correlation between GRAPPA 2 × 1 and Wave-CAIPI 3 × 3.Conclusion: MPRAGE Wave-CAIPI 3 × 3 shows relatively better contrast, despite of its short scan time of 1 min 42 s. The volumes derived from automated segmentation of MPRAGE Wave-CAIPI are considered to be reliable measures.